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10.1101/005082
diCal-IBD: demography-aware inference of identity-by-descent tracts in unrelated individuals
Paula Tataru;Jasmine A. Nirody;Yun S. Song;
Paula Tataru
Bioinformatics Research Centre, Aarhus University, Denmark
2014-09-03
3
New Results
cc_by_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/09/03/005082.source.xml
Summary: We present a tool, diCal-IBD, for detecting identity-by-descent (IBD) tracts between pairs of genomic sequences. Our method builds on a recent demographic inference method based on the coalescent with recombination, and is able to incorporate demographic information as a prior. Simulation study shows that diCal-IBD has significantly higher recall and precision than that of existing IBD detection methods, while retaining reasonable accuracy for IBD tracts as small as 0.1 cM.\n\nAvailability: http://sourceforge.net/p/dical-ibd\n\nContact: [email protected]
10.1093/bioinformatics/btu563
biorxiv
10.1101/005033
bíogo: a simple high-performance bioinformatics toolkit for the Go language
R Daniel Kortschak;David L Adelson;
R Daniel Kortschak
University of Adelaide
2014-05-12
1
New Results
cc_by_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/12/005033.source.xml
biogo is a framework designed to ease development and maintenance of computationally intensive bioinformatics applications. The library is written in the Go programming language, a garbage-collected, strictly typed compiled language with built in support for concurrent processing, and performance comparable to C and Java. It provides a variety of data types and utility functions to facilitate manipulation and analysis of large scale genomic and other biological data. biogo uses a concise and expressive syntax, lowering the barriers to entry for researchers needing to process large data sets with custom analyses while retaining computational safety and ease of code review. We believe biogo provides an excellent environment for training and research in computational biology because of its combination of strict typing, simple and expressive syntax, and high performance.
null
biorxiv
10.1101/005033
bíogo: a simple high-performance bioinformatics toolkit for the Go language
R Daniel Kortschak;David L Adelson;
R Daniel Kortschak
University of Adelaide
2015-03-27
2
New Results
cc_by_nd
Bioinformatics
https://www.biorxiv.org/content/early/2015/03/27/005033.source.xml
biogo is a framework designed to ease development and maintenance of computationally intensive bioinformatics applications. The library is written in the Go programming language, a garbage-collected, strictly typed compiled language with built in support for concurrent processing, and performance comparable to C and Java. It provides a variety of data types and utility functions to facilitate manipulation and analysis of large scale genomic and other biological data. biogo uses a concise and expressive syntax, lowering the barriers to entry for researchers needing to process large data sets with custom analyses while retaining computational safety and ease of code review. We believe biogo provides an excellent environment for training and research in computational biology because of its combination of strict typing, simple and expressive syntax, and high performance.
null
biorxiv
10.1101/005074
CasFinder: Flexible algorithm for identifying specific Cas9 targets in genomes
John Aach;Prashant Mali;George M Church;
John Aach
Harvard Medical School
2014-05-12
1
New Results
cc_by
Genomics
https://www.biorxiv.org/content/early/2014/05/12/005074.source.xml
CRISPR/Cas9 systems enable many molecular activities to be efficiently directed in vivo to user-specifiable DNA sequences of interest, including generation of dsDNA cuts and nicks, transcriptional activation and repression, and fluorescence. CRISPR targeting relies on base pairing of short RNA transcripts with their target DNA sequences that must also be adjacent to fixed DNA motifs. However, rules for Cas9 targeting specificity are incompletely known. With increasing numbers of Cas9 systems being developed and deployed in more and more organisms, there is now strong need for a flexible and rational method for finding Cas9 sites with low off-targeting potential. We address this through the CasFinder system, which we demonstrate by generating human and mouse exome-wide catalogs of specific sites for three varieties of Cas9 - S. pyogenes, S. thermophilus (ST1), and N. meningitidis - that each target 56-74% of all exons. We also generate reduced sets of up to 3 targets per gene for use in high-throughput Cas9-based gene knockout screens that target 75-80% of all genes.
null
biorxiv
10.1101/005058
Diversity and evolution of centromere repeats in the maize genome
Paul Bilinski;Kevin Distor;Jose Gutierrez-Lopez;Gabriela Mendoza Mendoza;Jinghua Shi;R. Kelly Dawe;Jeffrey Ross-Ibarra;
Jeffrey Ross-Ibarra
University of California Davis
2014-05-12
1
New Results
cc_by
Genomics
https://www.biorxiv.org/content/early/2014/05/12/005058.source.xml
Centromere repeats are found in most eukaryotes and play a critical role in kinetochore formation. Though CentC repeats exhibit considerable diversity both within and among species, little is understood about the mechanisms that drive cen- tromere repeat evolution. Here, we use maize as a model to investigate how a complex history involving polyploidy, fractionation, and recent domestication has impacted the diversity of the maize CentC repeat. We first validate the existence of long tan- dem arrays of repeats in maize and other taxa in the genus Zea. Although we find considerable sequence diversity among CentC copies genome-wide, genetic similar- ity among repeats is highest within these arrays, suggesting that tandem duplica- tions are the primary mechanism for the generation of new copies. Genetic clustering analyses identify similar sequences among distant repeats, and simulations suggest that this pattern may be due to homoplasious mutation. Although the two ancestral subgenomes of maize have contributed nearly equal numbers of centromeres, our analysis shows that the vast majority of all CentC repeats derive from one of the parental genomes. Finally, by comparing maize with its wild progenitor teosinte, we find that the abundance of CentC has decreased through domestication while the peri- centromeric repeat Cent4 has drastically increased.
10.1007/s00412-014-0483-8
biorxiv
10.1101/005041
The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin
Bargavi Thyagarajan;Jesse D Bloom;
Jesse D Bloom
Fred Hutchinson Cancer Research Center
2014-05-12
1
New Results
cc_by
Microbiology
https://www.biorxiv.org/content/early/2014/05/12/005041.source.xml
Influenza is notable for its evolutionary capacity to escape immunity targeting the viral hemagglutinin. We used deep mutational scanning to examine the extent to which a high inherent mutational tolerance contributes to this antigenic evolvability. We created mutant viruses that incorporate most of the {approx} 104 amino-acid mutations to hemagglutinin from A/WSN/1933 (H1N1) influenza. After passaging these viruses in tissue culture to select for functional variants, we used deep sequencing to quantify mutation frequencies before and after selection. These data enable us to infer the preference for each amino acid at each site in hemagglutinin. These inferences are consistent with existing knowledge about the proteins structure and function, and can be used to create a model that describes hemagglutinins evolution far better than existing phylogenetic models. We show that hemagglutinin has a high inherent tolerance for mutations at antigenic sites, suggesting that this is one factor contributing to influenzas antigenic evolution.
10.7554/eLife.03300
biorxiv
10.1101/005041
The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin
Bargavi Thyagarajan;Jesse D Bloom;
Jesse D Bloom
Fred Hutchinson Cancer Research Center
2014-06-22
2
New Results
cc_by
Microbiology
https://www.biorxiv.org/content/early/2014/06/22/005041.source.xml
Influenza is notable for its evolutionary capacity to escape immunity targeting the viral hemagglutinin. We used deep mutational scanning to examine the extent to which a high inherent mutational tolerance contributes to this antigenic evolvability. We created mutant viruses that incorporate most of the {approx} 104 amino-acid mutations to hemagglutinin from A/WSN/1933 (H1N1) influenza. After passaging these viruses in tissue culture to select for functional variants, we used deep sequencing to quantify mutation frequencies before and after selection. These data enable us to infer the preference for each amino acid at each site in hemagglutinin. These inferences are consistent with existing knowledge about the proteins structure and function, and can be used to create a model that describes hemagglutinins evolution far better than existing phylogenetic models. We show that hemagglutinin has a high inherent tolerance for mutations at antigenic sites, suggesting that this is one factor contributing to influenzas antigenic evolution.
10.7554/eLife.03300
biorxiv
10.1101/005041
The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin
Bargavi Thyagarajan;Jesse D Bloom;
Jesse D Bloom
Fred Hutchinson Cancer Research Center
2014-06-23
3
New Results
cc_by
Microbiology
https://www.biorxiv.org/content/early/2014/06/23/005041.source.xml
Influenza is notable for its evolutionary capacity to escape immunity targeting the viral hemagglutinin. We used deep mutational scanning to examine the extent to which a high inherent mutational tolerance contributes to this antigenic evolvability. We created mutant viruses that incorporate most of the {approx} 104 amino-acid mutations to hemagglutinin from A/WSN/1933 (H1N1) influenza. After passaging these viruses in tissue culture to select for functional variants, we used deep sequencing to quantify mutation frequencies before and after selection. These data enable us to infer the preference for each amino acid at each site in hemagglutinin. These inferences are consistent with existing knowledge about the proteins structure and function, and can be used to create a model that describes hemagglutinins evolution far better than existing phylogenetic models. We show that hemagglutinin has a high inherent tolerance for mutations at antigenic sites, suggesting that this is one factor contributing to influenzas antigenic evolution.
10.7554/eLife.03300
biorxiv
10.1101/005041
The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin
Bargavi Thyagarajan;Jesse D Bloom;
Jesse D Bloom
Fred Hutchinson Cancer Research Center
2014-06-23
4
New Results
cc_by
Microbiology
https://www.biorxiv.org/content/early/2014/06/23/005041.source.xml
Influenza is notable for its evolutionary capacity to escape immunity targeting the viral hemagglutinin. We used deep mutational scanning to examine the extent to which a high inherent mutational tolerance contributes to this antigenic evolvability. We created mutant viruses that incorporate most of the {approx} 104 amino-acid mutations to hemagglutinin from A/WSN/1933 (H1N1) influenza. After passaging these viruses in tissue culture to select for functional variants, we used deep sequencing to quantify mutation frequencies before and after selection. These data enable us to infer the preference for each amino acid at each site in hemagglutinin. These inferences are consistent with existing knowledge about the proteins structure and function, and can be used to create a model that describes hemagglutinins evolution far better than existing phylogenetic models. We show that hemagglutinin has a high inherent tolerance for mutations at antigenic sites, suggesting that this is one factor contributing to influenzas antigenic evolution.
10.7554/eLife.03300
biorxiv
10.1101/005066
Independent Theta Phase Coding Accounts for CA1 Population Sequences and Enables Flexible Remapping
Angus Chadwick;Mark C. W. van Rossum;Matthew F. Nolan;
Matthew F. Nolan
University of Edinburgh
2014-05-12
1
New Results
cc_no
Neuroscience
https://www.biorxiv.org/content/early/2014/05/12/005066.source.xml
Populations of hippocampal place cells encode an animals past, current and future location through sequences of action potentials generated within each cycle of the network theta rhythm. These sequential representations have been suggested to result from temporally coordinated synaptic interactions within and between cell assemblies. In contrast, we show that a model based on rate and phase coding in independent neurons is sufficient to explain the organization of CA1 population activity during theta states. We show that CA1 population activity can be described as an evolving traveling wave that exhibits phase coding, rate coding, spike sequences and that generates an emergent population theta rhythm. We identify measures of global remapping and intracellular theta dynamics as critical for distinguishing mechanisms for pacemaking and coordination of sequential population activity. Our analysis suggests that independent coding enables flexible generation of sequential population activity within the duration of a single theta cycle.
10.7554/eLife.03542
biorxiv
10.1101/004978
Evidences of a cytotoxic activity of S-adenosylmethionine on OCI-AML3 cells
Kathrin Aprile von Hohenstaufen;Irina Puoti;Marisa Meloni;Barbara De Servi;
Kathrin Aprile von Hohenstaufen
Liber Augustalis Biomedical Research Association
2014-05-08
1
New Results
cc_no
Pharmacology and Toxicology
https://www.biorxiv.org/content/early/2014/05/08/004978.source.xml
BackgroundThe acute myeloid leukemia (AML) cell line OCI-AML3, carrying both NPM1 mutation A and the heterozygous DNMT3A R882C mutation, represents the model for in vitro studies on AML with mutated NPM11. AML with mutated NPM1 harbours a hypo-methylated profile distinct from those of the other AML subtypes2. This characteristic is probably related to the inhibitory effect of the mutant DNMT3A on the wild type protein3. S-adenosylmethionine (SAM) is a universal methyl donor acting as a coenzyme of DNMT3A. There are growing evidences of the antineoplastic effect of SAM in vitro and in murine models of gastric cancer, colon cancer and hepatocellular carcinoma, where SAM induces the downregulation of several oncogenes4-10. Moreover SAM upregulates the expression of DNMT enzymes in lung cancer cells11. In our knowledge there are no published data exploring the effect of SAM on the growth of OCI-AML3 cells and its ability to modulate DNMT3A activity in this cell line. Study design and methodsThe present data have been generated between August 2013 and April 2014 at the VITROSCREEN facilities in Milan-ITALY. We used a 3-(4,5-dimethylthiazol-2-yl)-2,5-dephenyl tetrazolium bromide (MTT) assay to assess the cytotoxic effect of SAM iodide (Sigma-Aldrich) on OCI-AML3 cells (DSMZ Leibniz Institut). We analyzed then the ability of SAM to induce apoptosis by Tali Image-Based Cytometer (green Annexin V - Alexa Fluor 488 for apoptotic cells, red propidium and green Annexin V-Alexa Fluor 488 for necrotic cells). ResultsThe MTT assays were performed after having treated the OCI-AML3 cells with various concentrations of the indicated drug for 24 hours. We observed no significant effects on cells viability using 0.5M, 10 M and 100 M of SAM (data not shown). In contrast, a dose dependent cytotoxic effect of SAM on OCI-AML3 cells was evident for concentrations equal or superior to 500 M, with an IC50 of 500 M (Figure 1). Since a Cmax of 211(SD 94)M after single intravenous infusion of SAM was previously reported in healthy voluntarees12, we decided to investigate the cytotoxic effect of SAM for concentrations close to 211 M using the MTT test. A significant dose dependent reduction of the cells viability was observed with SAM 200M (62,74% viable cells) and SAM 300M (53.32% viable cells), (Figure 2). The Apoptosis assay after 24 hours of treatment with SAM showed no differences in the percentages of apoptotic cells between the OCI-AML3 cells treated with SAM 300-500-2500 M and the untreated cells (data not shown). After 72 hours, only a minimal effect on the amount of apoptotic cells was obtained, while a clear dose dependent increase in the proportion of dead cells was noted (Figure 3), confirming the results of the aforementioned MTT tests. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/004978v1_fig1.gif" ALT="Figure 1"> View larger version (12K): [email protected]@23bd30org.highwire.dtl.DTLVardef@59a9c5org.highwire.dtl.DTLVardef@98e377_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO MTT assay after 24 h exposure of OCI-AML3 cells to SAM at 0.5 mM, 2.5 mM and 10 mM. CN= negative control, untreated cells. SAM=S-Adenosylmethionine. Percentages of viable cells are reported. Both SAM treated cells and CN were tested in triplicate samples. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/004978v1_fig2.gif" ALT="Figure 2"> View larger version (16K): [email protected]@17e1d00org.highwire.dtl.DTLVardef@a213c5org.highwire.dtl.DTLVardef@c01c13_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO MTT assay after 24 h exposure of OCI-AML3 cells to SAM at 200 M (0.2mM), 300 M, 400 M, 500 M, 1000 M, 2500M. CN=negative control, untreated cells. SAM=S-Adenosylmethionine. Percentages of viable cells are reported. Both SAM treated cells and CN were tested in triplicate samples. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/004978v1_fig3.gif" ALT="Figure 3"> View larger version (31K): [email protected]@1825707org.highwire.dtl.DTLVardef@1f99a6org.highwire.dtl.DTLVardef@a08020_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 3.C_FLOATNO Percentages of Living, Dead and Apoptotic OCI-AML3 cells assessed by Tali image based cytometer after 72 hours treatment with different concentrations of SAM, and after 72 hours in medium (CN=negative control). Both SAM treated cells and CN were tested in duplicate samples. C_FIG ConclusionsSAM showed remarkable in vitro cytotoxic activity on OCI-AML3 cells at concentrations similar to those achievable in humans after intravenous administration. SAM is not able to induce apoptosis of OCI-AML3 cells in vitro after 72 hours of treatment. However, the increase in the amount of dead cells after SAM treatment may be due to mechanisms other than apoptosis. In order to verify if the observed cytotoxicity was mediated by the enzymatic activity of DNMT3A, we planned to repeat the cytotoxicity assays after DNMT3A silencing. The in vivo antineoplastic effect of SAM could be assessed in NOD/SCID mice engrafted with OCI-AML3 cells. Authors contributionKAvH wrote the study rationale, designed the study, interpreted the data and wrote the article; IP revised the article, MM and BDS planned and interpreted the experiments and BDS performed the experiments.
null
biorxiv
10.1101/005090
Cosi2 : An efficient simulator of exact and approximate coalescent with selection
Ilya Shlyakhter;Pardis C. Sabeti;Stephen F. Schaffner;
Ilya Shlyakhter
Broad Institute, Harvard University
2014-05-14
1
New Results
cc_no
Genetics
https://www.biorxiv.org/content/early/2014/05/14/005090.source.xml
MotivationEfficient simulation of population genetic samples under a given demographic model is a prerequisite for many analyses. Coalescent theory provides an efficient framework for such simulations, but simulating longer regions and higher recombination rates remains challenging. Simulators based on a Markovian approximation to the coalescent scale well, but do not support simulation of selection. Gene conversion is not supported by any published coalescent simulators that support selection.\n\nResultsWe describe cosi2, an efficient simulator that supports both exact and approximate coalescent simulation with positive selection. cosi2 improves on the speed of existing exact simulators, and permits further speedup in approximate mode while retaining support for selection. cosi2 supports a wide range of demographic scenarios including recombination hot spots, gene conversion, population size changes, population structure and migration.\n\ncosi2 implements coalescent machinery efficiently by tracking only a small subset of the Ancestral Recombination Graph, sampling only relevant recombination events, and using augmented skip lists to represent tracked genetic segments. To preserve support for selection in approximate mode, the Markov approximation is implemented not by moving along the chromosome but by performing a standard backwards-in-time coalescent simulation while restricting coalescence to node pairs with overlapping or near-overlapping genetic material. We describe the algorithms used by cosi2 and present comparisons with existing selection simulators.\n\nAvailabilityA free C++ implementation of cosi2 is available at http://broadinstitute.org/[~]ilya/cosi2.\n\[email protected]
10.1093/bioinformatics/btu562
biorxiv
10.1101/005124
When genomes collide: multiple modes of germline misregulation in a dysgenic syndrome of Drosophila virilis
Mauricio A. Galdos;Alexandra A. Erwin;Michelle L. Wickersheim;Chris C. Harrison;Kendra D. Marr;Justin Blumenstiel;
Justin Blumenstiel
University of Kansas
2014-05-13
1
New Results
cc_by
Genetics
https://www.biorxiv.org/content/early/2014/05/13/005124.source.xml
In sexually reproducing species the union of gametes that are not closely related can result in genomic incompatibility. Hybrid dysgenic syndromes represent a form of genomic incompatibility that can arise when transposable element (TE) abundance differs between two parents. When TEs lacking in the female parent are transmitted paternally, a lack of corresponding silencing small RNAs (piRNAs) transmitted through the female germline can lead to TE mobilization in progeny. The epigenetic nature of this phenomenon is demonstrated by the fact that genetically identical females of the reciprocal cross are normal. Here we show that in the hybrid dysgenic syndrome of Drosophila virilis, an excess of paternally inherited TE families leads not only to increased expression of these TEs, but also coincides with derepression of TEs in equal abundance within parents. Moreover, TE derepression is stable as flies age and associated with piRNA biogenesis defects for only some TEs. At the same time, TE activation is associated with a genome wide shift in the distribution of endogenous gene expression and an increase in abundance of off-target genic piRNAs. To identify regions of the maternal genome that most protect against dysgenesis, we performed an F3 backcross analysis. We find that pericentric regions play a dominant role in maternal protection. This F3 backcross approach additionally allowed us to clarify the properties of genic paramutation in D. virilis. Overall, results support a model in which early germline events in dysgenesis establish a chronic, stable state of mis-expression that is maintained through adulthood.\n\nSuch early events in the germline that are mediated by parent-of-origin effects may be important in determining patterns of gene expression in natural populations.\n\nAuthor SummaryTransposable elements (TE) are selfish elements that code for the function of copying themselves. More than half the human genome is comprised of such elements. Studies in the fruit flies Drosophila melanogaster and D. virilis have been important in demonstrating a role for RNA silencing by piwi-interacting RNAs (piRNAs) in protecting the genome against these harmful elements. These small RNAs are capable of recognizing TE mRNAs and mediating their destruction by Argonaute proteins. They are also transmitted by the female germline to offspring in order to maintain a stable genome across generations. When males carrying a particular TE family are crossed with females lacking the element, the mother is unable to provide genome defense via complementary piRNAs that target the element. This leads to excess TE activation in the germline and sterility. This phenomenon is known as hybrid dysgenesis. In this article we characterize the genomic landscape of TE destabilization that occurs in hybrid dysgenesis in D. virilis. Previous studies had demonstrated that multiple TEs mobilized during hybrid dysgenesis. We demonstrate that this mobilization of multiple TEs is associated with activation of additional TEs in the germline. In addition, we find that TE activation leads to the production of off-target genic piRNAs that cause reduced expression of highly expressed genes. Finally, we show that genic off-target effects of piRNA silencing can contribute to parent-of-origin effects on gene expression. Similar phenomena may influence patterns of gene expression in the germline of natural populations.
null
biorxiv
10.1101/005181
A new insight for the screening of potential β-lactamase inhibitors
Vijai Singh;Dharmendra Kumar Chaudhary;
Vijai Singh
Department of Biotechnology, Invertis University, Bareilly- Lucknow NH-24, Bareilly 243123, India
2014-05-14
1
New Results
cc_by
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/14/005181.source.xml
The {beta}-lactamase produces by Aeromonas hydrophila which enables to hydrolyze and inactivate {beta}- lactam ring of antibiotics. The homology modeling was used to generate the 3-D model of {beta}-lactamase by using known template 3-D structure. The stereochemical quality and torsion angle of 3-D model were validated. Total eleven effective drugs have been selected and targeted the active amino acid residues in {beta}-lactamase. The drugs were derivative of {beta}-lactam ring antibiotics and screening was made by docking. Out of 11 drugs, 3 drugs (Ampicillin, Astreonam and Sultamicillin) were found to be more potent on the basis of robust binding energy between protein-drug interactions. Additionally, homology of {beta}-lactamase of A. hydrophila resembled with other pathogenic bacteria that used for phylogeny analysis. These findings suggest a new insight for better understanding and useful for designing of novel potent drugs.
null
biorxiv
10.1101/005181
A new insight for the screening of potential β-lactamase inhibitors
Vijai Singh;Dharmendra Kumar Chaudhary;
Vijai Singh
Department of Biotechnology, Invertis University, Bareilly- Lucknow NH-24, Bareilly 243123, India
2014-05-15
2
New Results
cc_by
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/15/005181.source.xml
The {beta}-lactamase produces by Aeromonas hydrophila which enables to hydrolyze and inactivate {beta}- lactam ring of antibiotics. The homology modeling was used to generate the 3-D model of {beta}-lactamase by using known template 3-D structure. The stereochemical quality and torsion angle of 3-D model were validated. Total eleven effective drugs have been selected and targeted the active amino acid residues in {beta}-lactamase. The drugs were derivative of {beta}-lactam ring antibiotics and screening was made by docking. Out of 11 drugs, 3 drugs (Ampicillin, Astreonam and Sultamicillin) were found to be more potent on the basis of robust binding energy between protein-drug interactions. Additionally, homology of {beta}-lactamase of A. hydrophila resembled with other pathogenic bacteria that used for phylogeny analysis. These findings suggest a new insight for better understanding and useful for designing of novel potent drugs.
null
biorxiv
10.1101/005165
qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots
Stephen D. Turner;
Stephen D. Turner
University of Virginia
2014-05-14
1
New Results
cc_by_nc
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/14/005165.source.xml
SummaryGenome-wide association studies (GWAS) have identified thousands of human trait-associated single nucleotide polymorphisms. Here, I describe a freely available R package for visualizing GWAS results using Q-Q and manhattan plots. The qqman package enables the flexible creation of manhattan plots, both genome-wide and for single chromosomes, with optional highlighting of SNPs of interest.\n\nAvailabilityqqman is released under the GNU General Public License, and is freely available on the Comprehensive R Archive Network (http://cran.r-project.org/package=qqman). The source code is available on GitHub (https://github.com/stephenturner/qqman).\n\[email protected]
null
biorxiv
10.1101/005207
RNA-seq gene profiling - a systematic empirical comparison
Nuno A Fonseca;John A Marioni;Alvis Brazma;
Alvis Brazma
EMBL-EBI
2014-05-14
1
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/14/005207.source.xml
Accurately quantifying gene expression levels is a key goal of experiments using RNA-sequencing to assay the transcriptome. This typically requires aligning the short reads generated to the genome or transcriptome before quantifying expression of pre-defined sets of genes. Differences in the alignment/quantification tools can have a major effect upon the expression levels found with important consequences for biological interpretation. Here we address two main issues: do different analysis pipelines affect the gene expression levels inferred from RNA-seq data? And, how close are the expression levels inferred to the \"true\" expression levels?\n\nWe evaluate fifty gene profiling pipelines in experimental and simulated data sets with different characteristics (e.g, read length and sequencing depth). In the absence of knowledge of the ground truth in real RNAseq data sets, we used simulated data to assess the differences between the \"true\" expression and those reconstructed by the analysis pipelines. Even though this approach does not take into account all known biases present in RNAseq data, it still allows to estimate the accuracy of the gene expression values inferred by different analysis pipelines. The results show that i) overall there is a high correlation between the expression levels inferred by the best pipelines and the true quantification values; ii) the error in the estimated gene expression values can vary considerably across genes; and iii) a small set of genes have expression estimates with consistently high error (across data sets and methods). Finally, although the mapping software is important, the quantification method makes a greater difference to the results.
10.1371/journal.pone.0107026
biorxiv
10.1101/005207
RNA-seq gene profiling - a systematic empirical comparison
Nuno A Fonseca;John A Marioni;Alvis Brazma;
Alvis Brazma
EMBL-EBI
2014-05-29
2
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/29/005207.source.xml
Accurately quantifying gene expression levels is a key goal of experiments using RNA-sequencing to assay the transcriptome. This typically requires aligning the short reads generated to the genome or transcriptome before quantifying expression of pre-defined sets of genes. Differences in the alignment/quantification tools can have a major effect upon the expression levels found with important consequences for biological interpretation. Here we address two main issues: do different analysis pipelines affect the gene expression levels inferred from RNA-seq data? And, how close are the expression levels inferred to the \"true\" expression levels?\n\nWe evaluate fifty gene profiling pipelines in experimental and simulated data sets with different characteristics (e.g, read length and sequencing depth). In the absence of knowledge of the ground truth in real RNAseq data sets, we used simulated data to assess the differences between the \"true\" expression and those reconstructed by the analysis pipelines. Even though this approach does not take into account all known biases present in RNAseq data, it still allows to estimate the accuracy of the gene expression values inferred by different analysis pipelines. The results show that i) overall there is a high correlation between the expression levels inferred by the best pipelines and the true quantification values; ii) the error in the estimated gene expression values can vary considerably across genes; and iii) a small set of genes have expression estimates with consistently high error (across data sets and methods). Finally, although the mapping software is important, the quantification method makes a greater difference to the results.
10.1371/journal.pone.0107026
biorxiv
10.1101/005207
RNA-seq gene profiling - a systematic empirical comparison
Nuno A Fonseca;John A Marioni;Alvis Brazma;
Alvis Brazma
EMBL-EBI
2014-07-16
3
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/07/16/005207.source.xml
Accurately quantifying gene expression levels is a key goal of experiments using RNA-sequencing to assay the transcriptome. This typically requires aligning the short reads generated to the genome or transcriptome before quantifying expression of pre-defined sets of genes. Differences in the alignment/quantification tools can have a major effect upon the expression levels found with important consequences for biological interpretation. Here we address two main issues: do different analysis pipelines affect the gene expression levels inferred from RNA-seq data? And, how close are the expression levels inferred to the \"true\" expression levels?\n\nWe evaluate fifty gene profiling pipelines in experimental and simulated data sets with different characteristics (e.g, read length and sequencing depth). In the absence of knowledge of the ground truth in real RNAseq data sets, we used simulated data to assess the differences between the \"true\" expression and those reconstructed by the analysis pipelines. Even though this approach does not take into account all known biases present in RNAseq data, it still allows to estimate the accuracy of the gene expression values inferred by different analysis pipelines. The results show that i) overall there is a high correlation between the expression levels inferred by the best pipelines and the true quantification values; ii) the error in the estimated gene expression values can vary considerably across genes; and iii) a small set of genes have expression estimates with consistently high error (across data sets and methods). Finally, although the mapping software is important, the quantification method makes a greater difference to the results.
10.1371/journal.pone.0107026
biorxiv
10.1101/005215
Generation of Aggregates of Mouse ES Cells that Show Symmetry Breaking, Polarisation and Emergent Collective Behaviour in vitro.
Peter Baillie-Johnson;Susanne C van den Brink;Tina Balayo;David A Turner;Alfonso Martinez Arias;
David A Turner
University of Cambridge
2014-05-15
1
New Results
cc_by
Developmental Biology
https://www.biorxiv.org/content/early/2014/05/15/005215.source.xml
Dissociated mouse embryonic stem (ES) cells were cultured to form aggregates in small volumes of basal medium in U-bottomed, non tissue-culture-treated 96-well plates and subsequently maintained in suspension culture. After growth for 48 hours, the aggregates are competent to respond to ubiquitous experimental signals which result in their symmetry-breaking and generation of defined polarised structures by 96 hours. It is envisaged that this system can be applied both to the study of early developmental events and more broadly to the processes of self-organisation and cellular decision-making. It may also provide a suitable niche for the generation of cell types present in the embryo but unobtainable from conventional adherent culture.
10.3791/53252
biorxiv
10.1101/005215
Generation of Aggregates of Mouse ES Cells that Show Symmetry Breaking, Polarisation and Emergent Collective Behaviour in vitro.
Peter Baillie-Johnson;Susanne C van den Brink;Tina Balayo;David A Turner;Alfonso Martinez Arias;
David A Turner
University of Cambridge
2014-05-19
2
New Results
cc_by
Developmental Biology
https://www.biorxiv.org/content/early/2014/05/19/005215.source.xml
Dissociated mouse embryonic stem (ES) cells were cultured to form aggregates in small volumes of basal medium in U-bottomed, non tissue-culture-treated 96-well plates and subsequently maintained in suspension culture. After growth for 48 hours, the aggregates are competent to respond to ubiquitous experimental signals which result in their symmetry-breaking and generation of defined polarised structures by 96 hours. It is envisaged that this system can be applied both to the study of early developmental events and more broadly to the processes of self-organisation and cellular decision-making. It may also provide a suitable niche for the generation of cell types present in the embryo but unobtainable from conventional adherent culture.
10.3791/53252
biorxiv
10.1101/005140
Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory
Mehdi Keramati;Boris Gutkin;
Mehdi Keramati
Group for Neural Theory, INSERM U960, Ecole Normale Supérieure, Paris, France.
2014-05-14
1
New Results
cc_by_nc_nd
Neuroscience
https://www.biorxiv.org/content/early/2014/05/14/005140.source.xml
Efficient regulation of internal homeostasis and defending it against perturbations requires complex behavioral strategies. However, the computational principles mediating brains homeostatic regulation of reward and associative learning remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behavior is modulated by the internal state of the animal. The theory proves that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further give a formal basis for temporal discounting of reward. It also explains how animals learn to act predictively to preclude prospective homeostatic challenges, and attributes a normative computational role to the modulation of midbrain dopaminergic activity by hypothalamic signals.
10.7554/eLife.04811
biorxiv
10.1101/005140
Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory
Mehdi Keramati;Boris Gutkin;
Mehdi Keramati
Group for Neural Theory, INSERM U960, Ecole Normale Supérieure, Paris, France.
2014-06-05
2
New Results
cc_by_nc_nd
Neuroscience
https://www.biorxiv.org/content/early/2014/06/05/005140.source.xml
Efficient regulation of internal homeostasis and defending it against perturbations requires complex behavioral strategies. However, the computational principles mediating brains homeostatic regulation of reward and associative learning remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behavior is modulated by the internal state of the animal. The theory proves that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further give a formal basis for temporal discounting of reward. It also explains how animals learn to act predictively to preclude prospective homeostatic challenges, and attributes a normative computational role to the modulation of midbrain dopaminergic activity by hypothalamic signals.
10.7554/eLife.04811
biorxiv
10.1101/005173
Locus architecture affects mRNA expression levels in Drosophila embryos
Tara Lydiard-Martin;Meghan Bragdon;Kelly B Eckenrode;Zeba Wunderlich;Angela H DePace;
Angela H DePace
Harvard University
2014-05-14
1
New Results
cc_by_nc_nd
Systems Biology
https://www.biorxiv.org/content/early/2014/05/14/005173.source.xml
Structural variation in the genome is common due to insertions, deletions, duplications and rearrangements. However, little is known about the ways structural variants impact gene expression. Developmental genes are controlled by multiple regulatory sequence elements scattered over thousands of bases; developmental loci are therefore a good model to test the functional impact of structural variation on gene expression. Here, we measured the effect of rearranging two developmental enhancers from the even-skipped (eve) locus in Drosophila melanogaster blastoderm embryos. We systematically varied orientation, order, and spacing of the enhancers in transgenic reporter constructs and measured expression quantitatively at single cell resolution in whole embryos to detect changes in both level and position of expression. We found that the position of expression was robust to changes in locus organization, but levels of expression were highly sensitive to the spacing between enhancers and order relative to the promoter. Our data demonstrate that changes in locus architecture can dramatically impact levels of gene expression. To quantitatively predict gene expression from sequence, we must therefore consider how information is integrated both within enhancers and across gene loci.
null
biorxiv
10.1101/005231
SraTailor: GUI software for visualizing high-throughput sequence read archives
Shinya Oki;Kazumitsu Maehara;Yasuyuki Ohkawa;Chikara Meno;
Chikara Meno
Kyushu university
2014-05-16
1
New Results
cc_by_nc
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/16/005231.source.xml
Raw high-throughput sequence data are deposited in public databases as SRAs (Sequence Read Archives) and are publically available to every researcher. However, in order to graphically visualize the sequence data of interest, the corresponding SRAs must be downloaded and converted into BigWig format through complicated command-line processing. This task requires users to possess skill with script languages and sequence data processing, a requirement that prevents a wide range of biologists from exploiting SRAs. To address these challenges, we developed SraTailor, a GUI (Graphical User Interface) software package that automatically converts an SRA into a BigWig-formatted file. Simplicity of use is one of the most notable features of SraTailor: entering an accession number of an SRA and clicking the mouse are the only steps required in order to obtain BigWig-formatted files and to graphically visualize the extents of reads at given loci. SraTailor is also able to make peak calls and files of other formats, and the software also accepts various command-line-like options. Therefore, this software makes SRAs fully exploitable by a wide range of biologists. SraTailor is freely available at http://www.dev.med.kyushu-u.ac.jp/sra_tailor/.
10.1111/gtc.12190
biorxiv
10.1101/005223
Strategic Social Learning and the Population Dynamics of Human Behavior: The Game of Go
Bret A Beheim;Calvin Thigpen;Richard McElreath;
Bret A Beheim
University of New Mexico
2014-05-16
1
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/16/005223.source.xml
Human culture is widely believed to undergo evolution, via mechanisms rooted in the nature of human cognition. A number of theories predict the kinds of human learning strategies, as well as the population dynamics that result from their action. There is little work, however, that quantitatively examines the evidence for these strategies and resulting cultural evolution within human populations. One of the obstacles is the lack of individual-level data with which to link transmission events to larger cultural dynamics. Here, we address this problem with a rich quantitative database from the East Asian board game known as Go. We draw from a large archive of Go games spanning the last six decades of professional play, and find evidence that the evolutionary dynamics of particular cultural variants are driven by a mix of individual and social learning processes. Particular players vary dramatically in their sensitivity to population knowledge, which also varies by age and nationality. The dynamic patterns of opening Go moves are consistent with an ancient, ongoing arms race within the game itself.
10.1016/j.evolhumbehav.2014.04.001
biorxiv
10.1101/005223
Strategic Social Learning and the Population Dynamics of Human Behavior: The Game of Go
Bret A Beheim;Calvin Thigpen;Richard McElreath;
Bret A Beheim
University of New Mexico
2014-05-19
2
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/19/005223.source.xml
Human culture is widely believed to undergo evolution, via mechanisms rooted in the nature of human cognition. A number of theories predict the kinds of human learning strategies, as well as the population dynamics that result from their action. There is little work, however, that quantitatively examines the evidence for these strategies and resulting cultural evolution within human populations. One of the obstacles is the lack of individual-level data with which to link transmission events to larger cultural dynamics. Here, we address this problem with a rich quantitative database from the East Asian board game known as Go. We draw from a large archive of Go games spanning the last six decades of professional play, and find evidence that the evolutionary dynamics of particular cultural variants are driven by a mix of individual and social learning processes. Particular players vary dramatically in their sensitivity to population knowledge, which also varies by age and nationality. The dynamic patterns of opening Go moves are consistent with an ancient, ongoing arms race within the game itself.
10.1016/j.evolhumbehav.2014.04.001
biorxiv
10.1101/005256
A putative antiviral role of plant cytidine deaminases
Susana Martín;José M. Cuevas;Ana Grande-Pérez;Santiago F. Elena;
Santiago F. Elena
IBMCP (CSIC-UPV)
2014-05-16
1
New Results
cc_by_nc_nd
Microbiology
https://www.biorxiv.org/content/early/2014/05/16/005256.source.xml
A mechanism of innate antiviral immunity operating against viruses infecting mammalian cells has been described during the last decade. Host cytidine deaminases (e.g., APOBEC3 proteins) edit viral genomes giving raise to hypermutated nonfunctional viruses; consequently, viral fitness is reduced through lethal mutagenesis. By contrast, sub-lethal hypermutagenesis may contribute to virus evolvability by increasing population diversity. To prevent genome editing, some viruses have evolved proteins that mediate APOBEC3 degradation. The model plant Arabidopsis thaliana encodes for nine cytidine deaminases (AtCDAs), raising the question of whether deamination is an antiviral mechanism in plants as well. Here we tested the effects of AtCDAs expression on the pararetrovirus Cauliflower mosaic virus (CaMV). We show that A. thaliana AtCDA1 gene product exerts a mutagenic activity, which indeed generates a negative correlation between the level of AtCDA1 expression and CaMV accumulation in the plant, suggesting that deamination may also work as an antiviral mechanism in plants.
10.12688/f1000research.11111.2
biorxiv
10.1101/005264
Automation and Evaluation of the SOWH Test with SOWHAT
Samuel H. Church;Joseph F. Ryan;Casey W. Dunn;
Samuel H. Church
Brown University
2014-05-19
1
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/19/005264.source.xml
The Swofford-Olsen-Waddell-Hillis (SOWH) test is a method to evaluate incongruent phylogenetic topologies. It is used, for example, when an investigator wishes to know if the maximum likelihood tree recovered in their analysis is significantly different than an alternative phylogenetic hypothesis. The SOWH test compares the observed difference in likelihood between the topologies to a null distribution of differences in likelihood generated by parametric resampling. The SOWH test is a well-established and important phylogenetic method, but it can be difficult to implement and its sensitivity to various factors is not well understood. We wrote SOWHAT, a program that automates the SOWH test. In test analyses, we find that variation in parameter estimation as well as the use of a more complex model of parameter estimation have little impact on results, but that results can be inconsistent when an insufficient number of replicates are used to estimate the null distribution. We provide methods of analyzing the sampling as well as a simple stopping criteria for sufficient bootstrap replicates, which increase the overall reliability of the approach. Applications of the SOWH test should include explicit evaluations of sampling adequacy. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.
10.1093/sysbio/syv055
biorxiv
10.1101/005264
Automation and Evaluation of the SOWH Test with SOWHAT
Samuel H. Church;Joseph F. Ryan;Casey W. Dunn;
Samuel H. Church
Brown University
2015-05-07
2
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2015/05/07/005264.source.xml
The Swofford-Olsen-Waddell-Hillis (SOWH) test is a method to evaluate incongruent phylogenetic topologies. It is used, for example, when an investigator wishes to know if the maximum likelihood tree recovered in their analysis is significantly different than an alternative phylogenetic hypothesis. The SOWH test compares the observed difference in likelihood between the topologies to a null distribution of differences in likelihood generated by parametric resampling. The SOWH test is a well-established and important phylogenetic method, but it can be difficult to implement and its sensitivity to various factors is not well understood. We wrote SOWHAT, a program that automates the SOWH test. In test analyses, we find that variation in parameter estimation as well as the use of a more complex model of parameter estimation have little impact on results, but that results can be inconsistent when an insufficient number of replicates are used to estimate the null distribution. We provide methods of analyzing the sampling as well as a simple stopping criteria for sufficient bootstrap replicates, which increase the overall reliability of the approach. Applications of the SOWH test should include explicit evaluations of sampling adequacy. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.
10.1093/sysbio/syv055
biorxiv
10.1101/005264
Automation and Evaluation of the SOWH Test with SOWHAT
Samuel H. Church;Joseph F. Ryan;Casey W. Dunn;
Samuel H. Church
Brown University
2015-06-15
3
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2015/06/15/005264.source.xml
The Swofford-Olsen-Waddell-Hillis (SOWH) test is a method to evaluate incongruent phylogenetic topologies. It is used, for example, when an investigator wishes to know if the maximum likelihood tree recovered in their analysis is significantly different than an alternative phylogenetic hypothesis. The SOWH test compares the observed difference in likelihood between the topologies to a null distribution of differences in likelihood generated by parametric resampling. The SOWH test is a well-established and important phylogenetic method, but it can be difficult to implement and its sensitivity to various factors is not well understood. We wrote SOWHAT, a program that automates the SOWH test. In test analyses, we find that variation in parameter estimation as well as the use of a more complex model of parameter estimation have little impact on results, but that results can be inconsistent when an insufficient number of replicates are used to estimate the null distribution. We provide methods of analyzing the sampling as well as a simple stopping criteria for sufficient bootstrap replicates, which increase the overall reliability of the approach. Applications of the SOWH test should include explicit evaluations of sampling adequacy. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.
10.1093/sysbio/syv055
biorxiv
10.1101/005322
Adaptation to a novel predator in Drosophila melanogaster: How well are we able to predict evolutionary responses?
Michael DeNieu;William Pitchers;Ian Dworkin;
Ian Dworkin
Michigan State University
2014-05-19
1
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/19/005322.source.xml
Evolutionary theory is sufficiently well developed to allow for short-term prediction of evolutionary trajectories. In addition to the presence of heritable variation, prediction requires knowledge of the form of natural selection on relevant traits. While many studies estimate the form of natural selection, few examine the degree to which traits evolve in the predicted direction. In this study we examine the form of natural selection imposed by mantid predation on wing size and shape in the fruitfly, Drosophila melanogaster. We then evolve populations of D. melanogaster under predation pressure, and examine the extent to which wing size and shape have responded in the predicted direction. We demonstrate that wing form partially evolves along the predicted vector from selection, more so than for control lineages. Furthermore, we re-examined phenotypic selection after [~]30 generations of experimental evolution. We observed that the magnitude of selection on wing size and shape was diminished in populations evolving with mantid predators, while the direction of the selection vector differed from that of the ancestral population for shape. We discuss these findings in the context of the predictability of evolutionary responses, and the need for fully multivariate approaches.
null
biorxiv
10.1101/005314
Phylogenetic confidence intervals for the optimal trait value
Krzysztof Bartoszek;Serik Sagitov;
Krzysztof Bartoszek
Department of Mathematics, Uppsala University
2014-05-19
1
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/19/005314.source.xml
We consider a stochastic evolutionary model for a phenotype developing amongst n related species with unknown phylogeny. The unknown tree is modelled by a Yule process conditioned on n contemporary nodes. The trait value is assumed to evolve along lineages as an Ornstein-Uhlenbeck process. As a result, the trait values of the n species form a sample with dependent observations. We establish three limit theorems for the sample mean corresponding to three domains for the adaptation rate. In the case of fast adaptation, we show that for large n the normalized sample mean is approximately normally distributed. Using these limit theorems, we develop novel confidence interval formulae for the optimal trait value.
10.1017/s0021900200113117
biorxiv
10.1101/005314
Phylogenetic confidence intervals for the optimal trait value
Krzysztof Bartoszek;Serik Sagitov;
Krzysztof Bartoszek
Department of Mathematics, Uppsala University
2014-11-10
2
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/11/10/005314.source.xml
We consider a stochastic evolutionary model for a phenotype developing amongst n related species with unknown phylogeny. The unknown tree is modelled by a Yule process conditioned on n contemporary nodes. The trait value is assumed to evolve along lineages as an Ornstein-Uhlenbeck process. As a result, the trait values of the n species form a sample with dependent observations. We establish three limit theorems for the sample mean corresponding to three domains for the adaptation rate. In the case of fast adaptation, we show that for large n the normalized sample mean is approximately normally distributed. Using these limit theorems, we develop novel confidence interval formulae for the optimal trait value.
10.1017/s0021900200113117
biorxiv
10.1101/005298
Ultra fast tissue staining with chemical tags
Johannes Kohl;Julian Ng;Sebastian Cachero;Michael-John Dolan;Ben Sutcliffe;Daniel Krüger;Shahar Frechter;Gregory SXE Jefferis;
Gregory SXE Jefferis
MRC Laboratory of Molecular Biology
2014-05-19
1
New Results
cc_by_nd
Neuroscience
https://www.biorxiv.org/content/early/2014/05/19/005298.source.xml
Genetically encoded fluorescent proteins and immunostainings are widely used to detect cellular or sub-cellular structures in thick biological samples. However, each approach suffers from limitations, including low signal and limited spectral flexibility or slow speed, poor penetration and high background, respectively. Here we overcome these limitations by using transgenically expressed chemical tags for rapid, even and low-background labeling of thick biological tissues. We construct a platform of widely applicable transgenic Drosophila reporter lines, demonstrating that chemical labeling can accelerate staining of whole-mount fly brains by a factor of 100x. Together, this tag-based approach drastically improves the speed and specificity of labeling genetically marked cells in intact and/or thick biological samples.
null
biorxiv
10.1101/005397
Differences in sensitivity to EGFR inhibitors could be explained by described biochemical differences between oncogenic Ras mutants
Edward C Stites;
Edward C Stites
Washington University School of Medicine
2014-05-21
1
New Results
cc_no
Cancer Biology
https://www.biorxiv.org/content/early/2014/05/21/005397.source.xml
Emerging data suggest different activating Ras mutants may have different biological behaviors. The most striking example may be in colon cancer, where activating KRAS mutations generally indicate a lack of benefit to treatment with EGFR inhibitors, although the activating KRAS G13D mutation appears to be an exception. As KRAS G13D generally shares the same biochemical defects as the other oncogenic KRAS mutants, a mechanism for differential sensitivity is not apparent. Here, a previously developed mathematical model of Ras mutant signaling is used to investigate this problem. The purpose of the analysis is to determine whether differential response is consistent with known mechanisms of Ras signaling, and to determine if any known features of Ras mutants provide an explanation for differential sensitivity. Computational analysis of the mathematical model finds that differential response to upstream inhibition between cancers with different Ras mutants is indeed consistent with known mechanisms of Ras biology. Moreover, model analysis demonstrates that the subtle biochemical differences between G13D and G12D (and G12V) mutants are sufficient to enable differential response to upstream inhibition. Simulations suggest that wild-type Ras within the G13D mutant context is more effectively inhibited by upstream inhibitors than when it is in the G12D or G12V contexts. This difference is a consequence of an elevated Km for the G13D mutant. The identification of a single parameter that influences sensitivity is significant in that it suggests an approach to evaluate other, less common, Ras mutations for their anticipated response to upstream inhibition.
null
biorxiv
10.1101/005363
Sperm should evolve to make female meiosis fair.
Yaniv Brandvain;Graham Coop;
Yaniv Brandvain
University of Minnesota - Twin Cities
2014-05-21
1
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/21/005363.source.xml
Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.
10.1111/evo.12621
biorxiv
10.1101/005363
Sperm should evolve to make female meiosis fair.
Yaniv Brandvain;Graham Coop;
Yaniv Brandvain
University of Minnesota - Twin Cities
2014-05-22
2
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/22/005363.source.xml
Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.
10.1111/evo.12621
biorxiv
10.1101/005363
Sperm should evolve to make female meiosis fair.
Yaniv Brandvain;Graham Coop;
Yaniv Brandvain
University of Minnesota - Twin Cities
2014-07-28
3
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/07/28/005363.source.xml
Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.
10.1111/evo.12621
biorxiv
10.1101/005363
Sperm should evolve to make female meiosis fair.
Yaniv Brandvain;Graham Coop;
Yaniv Brandvain
University of Minnesota - Twin Cities
2014-12-26
4
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/12/26/005363.source.xml
Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.
10.1111/evo.12621
biorxiv
10.1101/005371
IVT-seq reveals extreme bias in RNA-sequencing
Nicholas F Lahens;Ibrahim Halil Kavakli;Ray Zhang;Katharina Hayer;Michael B Black;Hannah Dueck;Angel Pizarro;Junhyong Kim;Rafael A Irizarry;Russell S Thomas;Gregory R Grant;John B Hogenesch;
John B Hogenesch
University of Pennsylvania
2014-05-21
1
New Results
cc_by
Genomics
https://www.biorxiv.org/content/early/2014/05/21/005371.source.xml
BackgroundRNA sequencing (RNA-seq) is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value.\n\nResultsHere we present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of > 1000 in vitro transcribed (IVT) RNAs from a full-length human cDNA library and sequenced them with poly-A and total RNA-seq, the most common protocols. Because each cDNA is full length and we show IVT is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find [~]50% of transcripts have > 2-fold and [~]10% have > 10-fold differences in within-transcript sequence coverage. Strikingly, we also find > 6% of transcripts have regions of high, unpredictable sequencing coverage, where the same transcript varies dramatically in coverage between samples, confounding accurate determination of their expression. To get at causal factors, we used a combination of experimental and computational approaches to show that rRNA depletion is responsible for the most significant variability in coverage and that several sequence determinants also strongly influence representation.\n\nConclusionsIn sum, these results show the utility of IVT-seq in promoting better understanding of bias introduced by RNA-seq and suggest caution in its interpretation. Furthermore, we find that rRNA-depletion is responsible for substantial, unappreciated biases in coverage. Perhaps most importantly, these coverage biases introduced during library preparation suggest exon level expression analysis may be inadvisable.
10.1186/gb-2014-15-6-r86
biorxiv
10.1101/005355
Inference of phenotype-defining functional modules of protein families for microbial plant biomass degraders
Sebastian Gil Anthony Konietzny;Phillip Byron Pope;Aaron Weimann;Alice Carolyn McHardy;
Alice Carolyn McHardy
Heinrich-Heine-University Düsseldorf
2014-05-21
1
New Results
cc_no
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/21/005355.source.xml
BackgroundEfficient industrial processes for converting plant lignocellulosic materials into biofuels are a key challenge in global efforts to use alternative energy sources to fossil fuels. Novel cellulolytic enzymes have been discovered from microbial genomes and metagenomes of microbial communities. However, the identification of relevant genes without known homologs, and elucidation of the lignocellulolytic pathways and protein complexes for different microorganisms remain a challenge.\n\nResultsWe describe a new computational method for the targeted discovery of functional modules of plant biomass-degrading protein families based on their co-occurrence patterns across genomes and metagenome datasets, and the strength of association of these modules with the genomes of known degraders. From more than 6.4 million family annotations for 2884 microbial genomes and 332 taxonomic bins from 18 metagenomes, we identified five functional modules that are distinctive for plant biomass degraders, which we call plant biomass degradation modules (PDMs). These modules incorporated protein families involved in the degradation of cellulose, hemicelluloses and pectins, structural components of the cellulosome and additional families with potential functions in plant biomass degradation. The PDMs could be linked to 81 gene clusters in genomes of known lignocellulose degraders, including previously described clusters of lignocellulolytic genes. On average, 70% of the families of each PDM mapped to gene clusters in known degraders, which served as an additional confirmation of their functional relationships. The presence of a PDM in a genome or taxonomic metagenome bin allowed us to predict an organisms ability for plant biomass degradation accurately. For 15 draft genomes of a cow rumen metagenome, we validated by cross-linking with confirmed cellulolytic enzymes that the PDMs identified plant biomass degraders within a complex microbial community.\n\nConclusionsFunctional modules of protein families that realize different aspects of plant cell wall degradation can be inferred from co-occurrence patterns across (meta)genomes with a probabilistic topic model. The PDMs represent a new resource of protein families and candidate genes implicated in microbial plant biomass degradation. They can be used to predict the ability to degrade plant biomass for a genome or taxonomic bin. The method would also be suitable for characterizing other microbial phenotypes.
10.1186/s13068-014-0124-8
biorxiv
10.1101/005330
The distribution of deleterious genetic variation in human populations
Kirk E Lohmueller;
Kirk E Lohmueller
UCLA
2014-05-21
1
New Results
cc_by_nc_nd
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/21/005330.source.xml
Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, numbers of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load may not differ across populations, and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.
10.1016/j.gde.2014.09.005
biorxiv
10.1101/005348
Inferring human population size and separation history from multiple genome sequences
Stephan Schiffels;Richard Durbin;
Richard Durbin
Sanger Institute
2014-05-21
1
New Results
cc_by_nc_nd
Genetics
https://www.biorxiv.org/content/early/2014/05/21/005348.source.xml
The availability of complete human genome sequences from populations across the world has given rise to new population genetic inference methods that explicitly model their ancestral relationship under recombination and mutation. So far, application of these methods to evolutionary history more recent than 20-30 thousand years ago and to population separations has been limited. Here we present a new method that overcomes these shortcomings. The Multiple Sequentially Markovian Coalescent (MSMC) analyses the observed pattern of mutations in multiple individuals, focusing on the first coalescence between any two individuals. Results from applying MSMC to genome sequences from nine populations across the world suggest that the genetic separation of non-African ancestors from African Yoruban ancestors started long before 50,000 years ago, and give information about human population history as recently as 2,000 years ago, including the bottleneck in the peopling of the Americas, and separations within Africa, East Asia and Europe.
10.1038/ng.3015
biorxiv
10.1101/005348
Inferring human population size and separation history from multiple genome sequences
Stephan Schiffels;Richard Durbin;
Richard Durbin
Sanger Institute
2014-05-23
2
New Results
cc_by_nc_nd
Genetics
https://www.biorxiv.org/content/early/2014/05/23/005348.source.xml
The availability of complete human genome sequences from populations across the world has given rise to new population genetic inference methods that explicitly model their ancestral relationship under recombination and mutation. So far, application of these methods to evolutionary history more recent than 20-30 thousand years ago and to population separations has been limited. Here we present a new method that overcomes these shortcomings. The Multiple Sequentially Markovian Coalescent (MSMC) analyses the observed pattern of mutations in multiple individuals, focusing on the first coalescence between any two individuals. Results from applying MSMC to genome sequences from nine populations across the world suggest that the genetic separation of non-African ancestors from African Yoruban ancestors started long before 50,000 years ago, and give information about human population history as recently as 2,000 years ago, including the bottleneck in the peopling of the Americas, and separations within Africa, East Asia and Europe.
10.1038/ng.3015
biorxiv
10.1101/003905
LIMIX: genetic analysis of multiple traits
Christoph Lippert;Francesco Paolo Casale;Barbara Rakitsch;Oliver Stegle;
Christoph Lippert
Microsoft Research
2014-05-21
1
New Results
cc_by
Genetics
https://www.biorxiv.org/content/early/2014/05/21/003905.source.xml
Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to flexibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix.
null
biorxiv
10.1101/003905
LIMIX: genetic analysis of multiple traits
Christoph Lippert;Francesco Paolo Casale;Barbara Rakitsch;Oliver Stegle;
Christoph Lippert
Microsoft Research
2014-05-22
2
New Results
cc_by
Genetics
https://www.biorxiv.org/content/early/2014/05/22/003905.source.xml
Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to flexibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix.
null
biorxiv
10.1101/005439
Profiling direct mRNA-microRNA interactions using synthetic biotinylated microRNA-duplexes
Shivangi Wani;Nicole Cloonan;
Nicole Cloonan
QIMR Berghofer Medical Research Institute
2014-05-22
1
Confirmatory Results
cc_by_nc_nd
Genomics
https://www.biorxiv.org/content/early/2014/05/22/005439.source.xml
MicroRNAs (miRNAs) are predominantly negative regulators of gene expression that act through the RNA-induced Silencing Complex (RISC) to suppress the translation of protein coding mRNAs. Despite intense study of these regulatory molecules, the specific molecular functions of most miRNAs remain unknown, largely due to the challenge of accurately identifying miRNA targets. Reporter gene assays can determine direct interactions, but are laborious and do not scale to genome-wide screens. Genomic scale methods such as HITS-CLIP do not preserve the direct interactions, and rely on computationally derived predictions of interactions that are plagued by high false positive rates. Here we describe a protocol for the isolation of direct targets of a mature miRNA, using synthetic biotinylated miRNA duplexes. This approach allows sensitive and specific detection of miRNA-mRNA interactions, isolating high quality mRNA suitable for analysis by microarray or RNAseq.
null
biorxiv
10.1101/005413
A genome-wide analysis of Cas9 binding specificity using ChIP-seq and targeted sequence capture
Henriette O'Geen;Isabelle M. Henry;Mital S. Bhakta;Joshua F. Meckler;David J. Segal;
David J. Segal
University of California, Davis
2014-05-22
1
New Results
cc_no
Molecular Biology
https://www.biorxiv.org/content/early/2014/05/22/005413.source.xml
Clustered regularly interspaced short palindromic repeat (CRISPR) RNA-guided nucleases have gathered considerable excitement as a tool for genome engineering. However, questions remain about the specificity of their target site recognition. Most previous studies have examined predicted off-target binding sites that differ from the perfect target site by one to four mismatches, which represent only a subset of genomic regions. Here, we use ChIP-seq to examine genome-wide CRISPR binding specificity at gRNA-specific and gRNA-independent sites. For two guide RNAs targeting the murine Snurf gene promoter, we observed very high binding specificity at the intended target site while off-target binding was observed at 2- to 6-fold lower intensities. We also identified significant gRNA-independent off-target binding. Interestingly, we found that these regions are highly enriched in the PAM site, a sequence required for target site recognition by CRISPR. To determine the relationship between Cas9 binding and endonuclease activity, we used targeted sequence capture as a high-throughput approach to survey a large number of the potential off-target sites identified by ChIP-seq or computational prediction. A high frequency of indels was observed at both target sites and one off-target site, while no cleavage activity could be detected at other ChIP-bound regions. Our data is consistent with recent finding that most interactions between the CRISPR nuclease complex and genomic PAM sites are transient and do not lead to DNA cleavage. The interactions are stabilized by gRNAs with good matches to the target sequence adjacent to the PAM site, resulting in target cleavage activity.
10.1093/nar/gkv137
biorxiv
10.1101/005405
Powerful tests for multi-marker association analysis using ensemble learning
Badri Padhukasahasram;Chandan K Reddy;L. Keoki Williams;
Badri Padhukasahasram
Henry Ford Health System
2014-05-23
1
New Results
cc_no
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/23/005405.source.xml
Multi-marker approaches are currently gaining a lot of interest in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene and pathway based association tests are increasingly being viewed as useful complements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants. A major drawback of single-marker based methods is that they do not consider pairwise and higher-order interactions between genetic variants. Here, we describe novel tests for multi-marker association analyses that are based on phenotype predictions obtained from machine learning algorithms. Instead of utilizing only a linear or logistic regression model, we propose the use of ensembles of diverse machine learning algorithms for constructing such association tests. As the true mathematical relationship between a phenotype and any group of genetic and clinical variables is unknown in advance and may be complex, such a strategy gives us a general and flexible framework to approximate this relationship across different sets of SNPs. We show how phenotype prediction obtained from ensemble learning algorithms can be used for constructing tests for the joint association of multiple variants. We first apply our method to simulated datasets to demonstrate its power and correctness. Then, we apply our method to previously studied asthma-related genes in two independent asthma cohorts to conduct association tests.
10.1371/journal.pone.0143489
biorxiv
10.1101/005405
Powerful tests for multi-marker association analysis using ensemble learning
Badri Padhukasahasram;Chandan K Reddy;L. Keoki Williams;
Badri Padhukasahasram
Henry Ford Health System
2014-06-13
2
New Results
cc_no
Bioinformatics
https://www.biorxiv.org/content/early/2014/06/13/005405.source.xml
Multi-marker approaches are currently gaining a lot of interest in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene and pathway based association tests are increasingly being viewed as useful complements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants. A major drawback of single-marker based methods is that they do not consider pairwise and higher-order interactions between genetic variants. Here, we describe novel tests for multi-marker association analyses that are based on phenotype predictions obtained from machine learning algorithms. Instead of utilizing only a linear or logistic regression model, we propose the use of ensembles of diverse machine learning algorithms for constructing such association tests. As the true mathematical relationship between a phenotype and any group of genetic and clinical variables is unknown in advance and may be complex, such a strategy gives us a general and flexible framework to approximate this relationship across different sets of SNPs. We show how phenotype prediction obtained from ensemble learning algorithms can be used for constructing tests for the joint association of multiple variants. We first apply our method to simulated datasets to demonstrate its power and correctness. Then, we apply our method to previously studied asthma-related genes in two independent asthma cohorts to conduct association tests.
10.1371/journal.pone.0143489
biorxiv
10.1101/005470
Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture
Homayun Mehrabani;Neil Ray;Kyle Tse;Dennis Evangelista;
Dennis Evangelista
University of North Carolina at Chapel Hill
2014-05-24
1
New Results
cc_no
Biophysics
https://www.biorxiv.org/content/early/2014/05/24/005470.source.xml
Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g. Antarctic anchor ice), or in environments with moisture and cold air (e.g. plants, intertidal) begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We screened biological and artifical samples for ice formation and accretion in submerged conditions using previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. It appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri) slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli). The geometric dimensions of the features have only a small ([~]6%) effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and coatings, and their interaction with surface pattern.
10.7717/peerj.588
biorxiv
10.1101/005470
Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture
Homayun Mehrabani;Neil Ray;Kyle Tse;Dennis Evangelista;
Dennis Evangelista
University of North Carolina at Chapel Hill
2014-06-26
2
New Results
cc_no
Biophysics
https://www.biorxiv.org/content/early/2014/06/26/005470.source.xml
Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g. Antarctic anchor ice), or in environments with moisture and cold air (e.g. plants, intertidal) begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We screened biological and artifical samples for ice formation and accretion in submerged conditions using previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. It appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri) slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli). The geometric dimensions of the features have only a small ([~]6%) effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and coatings, and their interaction with surface pattern.
10.7717/peerj.588
biorxiv
10.1101/005504
The methylome of the human frontal cortex across development
Andrew E Jaffe;Yuan Gao;Ran Tao;Thomas M Hyde;Daniel R Weinberger;Joel E Kleinman;
Andrew E Jaffe
Lieber Institute for Brain Development
2014-05-26
1
New Results
cc_by_nc_nd
Developmental Biology
https://www.biorxiv.org/content/early/2014/05/26/005504.source.xml
DNA methylation (DNAm) plays an important role in epigenetic regulation of gene expression, orchestrating tissue differentiation and development during all stages of mammalian life. This epigenetic control is especially important in the human brain, with extremely dynamic gene expression during fetal and infant life, and becomes progressively more stable at later periods of development. We characterized the epigenetic state of the developing and aging human frontal cortex in post-mortem tissue from 351 individuals across the lifespan using the Illumina 450k DNA methylation microarray. The largest changes in the methylome occur at birth at varying spatial resolutions - we identify 359,087 differentially methylated loci, which form 23,732 significant differentially methylated regions (DMRs). There were also 298 regions of long-range changes in DNAm, termed \"blocks\", associated with birth that strongly overlap previously published colon cancer \"blocks\". We then identify 55,439 DMRs associated with development and aging, of which 61.9% significantly associate with nearby gene expression levels. Lastly, we find enrichment of genomic loci of risk for schizophrenia and several other common diseases among these developmental DMRs. These data, integrated with existing genetic and transcriptomic data, create a rich genomic resource across brain development.
10.1038/nn.4181
biorxiv
10.1101/005504
The methylome of the human frontal cortex across development
Andrew E Jaffe;Yuan Gao;Ran Tao;Thomas M Hyde;Daniel R Weinberger;Joel E Kleinman;
Andrew E Jaffe
Lieber Institute for Brain Development
2014-05-27
2
New Results
cc_by_nc_nd
Developmental Biology
https://www.biorxiv.org/content/early/2014/05/27/005504.source.xml
DNA methylation (DNAm) plays an important role in epigenetic regulation of gene expression, orchestrating tissue differentiation and development during all stages of mammalian life. This epigenetic control is especially important in the human brain, with extremely dynamic gene expression during fetal and infant life, and becomes progressively more stable at later periods of development. We characterized the epigenetic state of the developing and aging human frontal cortex in post-mortem tissue from 351 individuals across the lifespan using the Illumina 450k DNA methylation microarray. The largest changes in the methylome occur at birth at varying spatial resolutions - we identify 359,087 differentially methylated loci, which form 23,732 significant differentially methylated regions (DMRs). There were also 298 regions of long-range changes in DNAm, termed \"blocks\", associated with birth that strongly overlap previously published colon cancer \"blocks\". We then identify 55,439 DMRs associated with development and aging, of which 61.9% significantly associate with nearby gene expression levels. Lastly, we find enrichment of genomic loci of risk for schizophrenia and several other common diseases among these developmental DMRs. These data, integrated with existing genetic and transcriptomic data, create a rich genomic resource across brain development.
10.1038/nn.4181
biorxiv
10.1101/005546
Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis
Matteo Carrara;Josephine Lum;Francesca Cordero;Marco Beccuti;Michael Poidinger;Susanna Donatelli;Raffaele A Calogero;Francesca Zolezzi;
Raffaele A Calogero
Department of Molecular Biotechnology and Health Sciences, University of Torino
2014-05-26
1
New Results
cc_by_nd
Genomics
https://www.biorxiv.org/content/early/2014/05/26/005546.source.xml
BackgroundRNAseq provides remarkable power in the area of biomarkers discovery and disease stratification. The main technical steps affecting the results of RNAseq experiments are Library Sample Preparation (LSP) and Bioinformatics Analysis (BA). At the best of our knowledge, a comparative evaluation of the combined effect of LSP and BA was never considered and it might represent a valuable knowledge to optimize alternative splicing detection, which is a challenging task due to moderate fold change differences to be detected within a complex isoforms background.\n\nResultsDifferent LSPs (TruSeq unstranded/stranded, ScriptSeq, NuGEN) allow the detection of a large common set of isoforms. However, each LSP also detects a smaller set of isoforms, which are characterized both by lower coverage and lower FPKM than that observed for the common ones among LSPs. This characteristic is particularly critical in case of low input RNA NuGEN v2 LSP.\n\nThe effect on statistical detection of alternative splicing considering low input LSP (NuGEN v2) with respect to high input LSP (TruSeq) on statistical detection of alternative splicing was studied using a benchmark dataset, in which both synthetic reads and reads generated from high (TruSeq) and low input (NuGEN) LSPs were spiked-in. Statistical detection of alternative splicing (AltDE) was done using prototypes of BA for isoform-reconstruction (Cuffdiff) and exon-level analysis (DEXSeq). Exon-level analysis performs slightly better than isoform-reconstruction approach although at most only 50% of the spiked-in transcripts are detected. Both isoform-reconstruction and exon-level analysis performances improve by rising the number of input reads.\n\nConclusionData, derived from NuGEN v2, are not the ideal input for AltDE, specifically when exon-level approach is used. It is notable that ribosomal depletion, with respect to polyA+ selection, reduces the amount of coding mappable reads resulting detrimental in the case of AltDE. Furthermore, we observed that both isoform-reconstruction and exon-level analysis performances are strongly dependent on the number of input reads.
10.1186/1471-2105-16-S9-S2
biorxiv
10.1101/005462
Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences
Vincenza Colonna;Qasim Ayub;Yuan Chen;Luca Pagani;Pierre Luisi;Marc Pybus;Erik Garrison;Yali Xue;Chris Tyler-Smith;
Vincenza Colonna
The Wellcome Trust Sanger Institute
2014-05-23
1
New Results
cc_by_nc
Genomics
https://www.biorxiv.org/content/early/2014/05/23/005462.source.xml
BackgroundPopulation differentiation has proved to be effective for identifying loci under geographically-localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes.\n\nResultsWe demonstrate that while sites of low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively.\n\nConclusionsWe have identified known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.
10.1186/gb-2014-15-6-r88
biorxiv
10.1101/005462
Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences
Vincenza Colonna;Qasim Ayub;Yuan Chen;Luca Pagani;Pierre Luisi;Marc Pybus;Erik Garrison;Yali Xue;Chris Tyler-Smith;
Vincenza Colonna
The Wellcome Trust Sanger Institute
2014-05-27
2
New Results
cc_by_nc
Genomics
https://www.biorxiv.org/content/early/2014/05/27/005462.source.xml
BackgroundPopulation differentiation has proved to be effective for identifying loci under geographically-localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes.\n\nResultsWe demonstrate that while sites of low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively.\n\nConclusionsWe have identified known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.
10.1186/gb-2014-15-6-r88
biorxiv
10.1101/005553
Differential stoichiometry among core ribosomal proteins
Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;
Nikolai Slavov
Harvard University
2014-05-26
1
New Results
cc_by_nc_nd
Systems Biology
https://www.biorxiv.org/content/early/2014/05/26/005553.source.xml
Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.
10.1016/j.celrep.2015.09.056
biorxiv
10.1101/005553
Differential stoichiometry among core ribosomal proteins
Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;
Nikolai Slavov
Harvard University
2015-01-28
2
New Results
cc_by_nc_nd
Systems Biology
https://www.biorxiv.org/content/early/2015/01/28/005553.source.xml
Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.
10.1016/j.celrep.2015.09.056
biorxiv
10.1101/005553
Differential stoichiometry among core ribosomal proteins
Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;
Nikolai Slavov
Harvard University
2015-07-20
3
New Results
cc_by_nc_nd
Systems Biology
https://www.biorxiv.org/content/early/2015/07/20/005553.source.xml
Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.
10.1016/j.celrep.2015.09.056
biorxiv
10.1101/005553
Differential stoichiometry among core ribosomal proteins
Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;
Nikolai Slavov
Harvard University
2015-09-19
4
New Results
cc_by_nc_nd
Systems Biology
https://www.biorxiv.org/content/early/2015/09/19/005553.source.xml
Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.
10.1016/j.celrep.2015.09.056
biorxiv
10.1101/005587
Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling
Ramon Diaz-Uriarte;
Ramon Diaz-Uriarte
Dept. Biochemistry, Universidad Autonoma de Madrid, and IIBM Alberto Sols (UAM-CSIC), Madrid, Spain
2014-05-27
1
New Results
cc_by
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/27/005587.source.xml
Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.
10.1186/s12859-015-0466-7
biorxiv
10.1101/005587
Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling
Ramon Diaz-Uriarte;
Ramon Diaz-Uriarte
Dept. Biochemistry, Universidad Autonoma de Madrid, and IIBM Alberto Sols (UAM-CSIC), Madrid, Spain
2014-06-03
2
New Results
cc_by
Bioinformatics
https://www.biorxiv.org/content/early/2014/06/03/005587.source.xml
Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.
10.1186/s12859-015-0466-7
biorxiv
10.1101/005587
Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling
Ramon Diaz-Uriarte;
Ramon Diaz-Uriarte
Dept. Biochemistry, Universidad Autonoma de Madrid, and IIBM Alberto Sols (UAM-CSIC), Madrid, Spain
2014-06-12
3
New Results
cc_by
Bioinformatics
https://www.biorxiv.org/content/early/2014/06/12/005587.source.xml
Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.
10.1186/s12859-015-0466-7
biorxiv
10.1101/005587
Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling
Ramon Diaz-Uriarte;
Ramon Diaz-Uriarte
Dept. Biochemistry, Universidad Autonoma de Madrid, and IIBM Alberto Sols (UAM-CSIC), Madrid, Spain
2014-06-22
4
New Results
cc_by
Bioinformatics
https://www.biorxiv.org/content/early/2014/06/22/005587.source.xml
Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.
10.1186/s12859-015-0466-7
biorxiv
10.1101/005512
Dynamics of a combined medea-underdominant population transformation system
Chaitanya Gokhale;Richard Guy Reeves;Floyd A Reed;
Chaitanya Gokhale
Massey University
2014-05-27
1
New Results
cc_by_nc
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/27/005512.source.xml
BackgroundTransgenic constructs intended to be stably established at high frequencies in wild populations have been demonstrated to \"drive\" from low frequencies in experimental insect populations. Linking such population transformation constructs to genes which render them unable to transmit pathogens could eventually be used to stop the spread of vector-borne diseases like malaria and dengue.\n\nResultsGenerally, population transformation constructs with only a single transgenic drive mechanism have been envisioned. Using a theoretical modelling approach we describe the predicted properties of a construct combining autosomal Medea and underdominant population transformation systems. We show that when combined they can exhibit synergistic properties which in broad circumstances surpass those of the single systems.\n\nConclusionWith combined systems, intentional population transformation and its reversal can be achieved readily. Combined constructs also enhance the capacity to geographically restrict transgenic constructs to targeted populations. It is anticipated that these properties are likely to be of particular value in attracting regulatory approval and public acceptance of this novel technology.
10.1186/1471-2148-14-98
biorxiv
10.1101/005512
Dynamics of a combined medea-underdominant population transformation system
Chaitanya Gokhale;Richard Guy Reeves;Floyd A Reed;
Chaitanya Gokhale
Massey University
2014-05-28
2
New Results
cc_by_nc
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/28/005512.source.xml
BackgroundTransgenic constructs intended to be stably established at high frequencies in wild populations have been demonstrated to \"drive\" from low frequencies in experimental insect populations. Linking such population transformation constructs to genes which render them unable to transmit pathogens could eventually be used to stop the spread of vector-borne diseases like malaria and dengue.\n\nResultsGenerally, population transformation constructs with only a single transgenic drive mechanism have been envisioned. Using a theoretical modelling approach we describe the predicted properties of a construct combining autosomal Medea and underdominant population transformation systems. We show that when combined they can exhibit synergistic properties which in broad circumstances surpass those of the single systems.\n\nConclusionWith combined systems, intentional population transformation and its reversal can be achieved readily. Combined constructs also enhance the capacity to geographically restrict transgenic constructs to targeted populations. It is anticipated that these properties are likely to be of particular value in attracting regulatory approval and public acceptance of this novel technology.
10.1186/1471-2148-14-98
biorxiv
10.1101/005603
Reconstructing Austronesian population history in Island Southeast Asia
Mark Lipson;Po-Ru Loh;Nick Patterson;Priya Moorjani;Ying-Chin Ko;Mark Stoneking;Bonnie Berger;David Reich;
David Reich
Harvard Medical School
2014-05-27
1
New Results
cc_by_nc_nd
Genetics
https://www.biorxiv.org/content/early/2014/05/27/005603.source.xml
Austronesian languages are spread across half the globe, from Easter Island to Madagascar. Evidence from linguistics and archaeology indicates that the \"Austronesian expansion,\" which began 4-5 thousand years ago, likely had roots in Taiwan, but the ancestry of present-day Austronesian-speaking populations remains controversial. Here, focusing primarily on Island Southeast Asia, we analyze genome-wide data from 56 populations using new methods for tracing ancestral gene flow. We show that all sampled Austronesian groups harbor ancestry that is more closely related to aboriginal Taiwanese than to any present-day mainland population. Surprisingly, western Island Southeast Asian populations have also inherited ancestry from a source nested within the variation of present-day populations speaking Austro-Asiatic languages, which have historically been nearly exclusive to the mainland. Thus, either there was once a substantial Austro-Asiatic presence in Island Southeast Asia, or Austronesian speakers migrated to and through the mainland, admixing there before continuing to western Indonesia.
10.1038/ncomms5689
biorxiv
10.1101/005454
Novel Natural Product Discovery from Marine Sponges and their Obligate Symbiotic Organisms
Regina Monaco;Rena Quinlan;
Regina Monaco
Hunter College
2014-05-24
1
Confirmatory Results
cc_by_nd
Pharmacology and Toxicology
https://www.biorxiv.org/content/early/2014/05/24/005454.source.xml
Discovery of novel natural products is an accepted method for the elucidation of pharmacologically active molecules and drug leads. Best known sources for such discovery have been terrestrial plants and microbes, accounting for about 85% of the approved natural products in pharmaceutical use (1), and about 60% of approved pharmaceuticals and new drug applications annually (2). Discovery in the marine environment has lagged due to the difficulty of exploration in this ecological niche. Exploration began in earnest in the 1950s, after technological advances such as scuba diving allowed collection of marine organisms, primarily at a depth to about 15m.\n\nNatural products from filter feeding marine invertebrates and in particular, sponges, have proven to be a rich source of structurally unique pharmacologically active compounds, with over 16,000 molecules isolated thus far (3, 1) and a continuing pace of discovery at hundreds of novel bioactive molecules per year. All classes of pharmaceuticals have been represented in this discovery process, including antiprotazoals, pesticides, TGF-beta inhibitors, cationic channel blockers, anticancer, cytotoxic, antiviral, anti-inflammatory and antibacterial compounds. Important biosynthetic pathways found in sponges which give rise to these compounds include the terpenoid (4), fatty acid, polyketoid, quinone reductase, alkaloid, isoprenoid (5), and non-ribosomal protein synthase pathways.
null
biorxiv
10.1101/005538
Hip and knee kinematics display complex and time-varying sagittal kinematics during repetitive stepping: Implications for design of a functional fatigue model of the knee extensors and flexors
Corey Scholes;Michael McDonald;Anthony Parker;
Corey Scholes
Sydney Orthopaedic Research Institute
2014-05-26
1
New Results
cc_by_nc_nd
Physiology
https://www.biorxiv.org/content/early/2014/05/26/005538.source.xml
The validity of fatigue protocols involving multi-joint movements, such as stepping, has yet to be clearly defined. Although surface electromyography can monitor the fatigue state of individual muscles, the effects of joint angle and velocity variation on signal parameters are well established. Therefore, the aims of this study were to i) describe sagittal hip and knee kinematics during repetitive stepping ii) identify periods of high inter-trial variability and iii) determine within-test reliability of hip and knee kinematic profiles. A group of healthy men (N = 15) ascended and descended from a knee-high platform wearing a weighted vest (10%BW) for 50 consecutive trials. The hip and knee underwent rapid flexion and extension during step ascent and descent. Variability of hip and knee velocity peaked between 20-40% of the ascent phase and 80-100% of the descent. Significant (p<0.05) reductions in joint range of motion and peak velocity during step ascent were observed, while peak flexion velocity increased during descent. Healthy individuals use complex hip and knee motion to negotiate a knee-high step with kinematic patterns varying across multiple repetitions. These findings have important implications for future studies intending to use repetitive stepping as a fatigue model for the knee extensors and flexors.
null
biorxiv
10.1101/005496
Different profile of transcriptome between wheat Yunong 201 and its high-yield mutant Yunong 3114
Feng Chen;Zhongdong Dong;Ning Zhang;Xiangfen Zhang;Dangqun Cui;
Feng Chen
Henan Agricultural University
2014-05-27
1
New Results
cc_by_nc
Plant Biology
https://www.biorxiv.org/content/early/2014/05/27/005496.source.xml
Wheat is one of the most important crops in the world. With the exponentially increasing population and the need for ever increased food and feed production, an increased yield of wheat grain (as well as rice, maize and other grains) will be critical. Modern technologies are utilized to assist breeding programs. Such as the transcriptome sequencing, which greatly improves our genetic understanding, provides a platform for functional genomics research on crops. Herein, to get an overview of transcriptome characteristics of Yunong 3114, which is screened from the EMS mutagenized population of, a high quality Chinese winter noodle wheat, due to its different plant architecture as well as larger kernel size and higher grain weight, a high-throughput RNA sequencing based on next generation sequencing technology (Illumina) were performed. These unigenes were annotated by Blastx alignment against the NCBI non-redundant (nr), Clusters of orthologous groups (COG), gene orthology (GO), and the Kyoto Encyclopedia of Genesand Genomes (KEGG) databases. The 90.96% of the unigenes matched with protein in the NCBI nr database. Functional analysis identified that changes in several GO categories, including recognition of pollen, apoptotic process, defense response, receptor activity, protein kinase activity, DNA integration and so forth, played crucial roles in the high-yield characteristics of the mutant. Real-time PCR analysis revealed that the recognition of pollen related gene GsSRK is significantly up-regulated in Yunong 3114. In addition, alternative splicing (AS) analysis results indicated that mutation influence AS ratio, especially the retained introns, including the pollen related genes. Furthermore, the digital gene expression spectrum (DGE) profiling data provides comprehensive information at the transcriptional level that facilitates our understanding of the molecular mechanisms of various physiological aspects including development and high-yield of wheat. Together, these studies substantially increase our knowledge of potential genes and pathways for the genetic improvement of wheat and provide new insights into the yield and breeding strategies.
null
biorxiv
10.1101/005611
A comparative study of techniques for differential expression analysis on RNA-Seq data
Zong Hong Zhang;Dhanisha J. Jhaveri;Vikki M. Marshall;Denis C. Bauer;Janette Edson;Ramesh K. Narayanan;Gregory J. Robinson;Andreas E. Lundberg;Perry F. Bartlett;Naomi R. Wray;Qiongyi Zhao;
Qiongyi Zhao
The University of Queensland, Queensland Brain Institute
2014-05-28
1
New Results
cc_by_nc_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/28/005611.source.xml
Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs) between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.
10.1371/journal.pone.0103207
biorxiv
10.1101/005579
Lighter: fast and memory-efficient error correction without counting
Li Song;Liliana Florea;Ben Langmead;
Ben Langmead
Johns Hopkins University
2014-05-27
1
New Results
cc_by_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/05/27/005579.source.xml
Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.
10.1186/s13059-014-0509-9
biorxiv
10.1101/005579
Lighter: fast and memory-efficient error correction without counting
Li Song;Liliana Florea;Ben Langmead;
Ben Langmead
Johns Hopkins University
2014-08-07
2
New Results
cc_by_nd
Bioinformatics
https://www.biorxiv.org/content/early/2014/08/07/005579.source.xml
Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.
10.1186/s13059-014-0509-9
biorxiv
10.1101/005645
Artificially inducing close apposition of endoplasmic reticulum and mitochondria induces mitochondrial fragmentation.
Victoria J Miller;David J Stephens;
David J Stephens
University of Bristol
2014-05-28
1
New Results
cc_by_nc
Cell Biology
https://www.biorxiv.org/content/early/2014/05/28/005645.source.xml
Cycles of mitochondrial fission and fission are essential for normal cell physiology. Defects in the machinery controlling these processes lead to neurodegenerative disease. While we are beginning to understand the machinery that drives fission, our knowledge of the spatial and temporal control of this event is lacking. Here we use a rapamycin-inducible heterodimerization system comprising both ER and mitochondrial transmembrane components to bring the ER membrane into close physical proximity with mitochondria. We show that this artificial apposition of membranes is sufficient to cause rapid mitochondrial fragmentation. Resulting mitochondrial fragments are shown to be distinct entities using fluorescence recovery after photobleaching. We also show that these fragments retain a mitochondrial membrane potential. In contrast, inducible tethering of the peripheral ER exit site protein TFG does not cause mitochondrial fragmentation suggesting that very close apposition of the two membranes is required.
null
biorxiv
10.1101/005652
Cis-regulatory elements and human evolution
Adam Siepel;Leonardo Arbiza;
Adam Siepel
Cornell University
2014-05-28
1
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/28/005652.source.xml
Modification of gene regulation has long been considered an important force in human evolution, particularly through changes to cis-regulatory elements (CREs) that function in transcriptional regulation. For decades, however, the study of cis-regulatory evolution was severely limited by the available data. New data sets describing the locations of CREs and genetic variation within and between species have now made it possible to study CRE evolution much more directly on a genome-wide scale. Here, we review recent research on the evolution of CREs in humans based on large-scale genomic data sets. We consider inferences based on primate divergence,human polymorphism, and combinations of divergence and polymorphism. We then consider "new frontiers" in this field stemming from recent research on transcriptional regulation.
10.1016/j.gde.2014.08.011
biorxiv
10.1101/005561
Quantifying the effects of anagenetic and cladogenetic evolution
Krzysztof Bartoszek;
Krzysztof Bartoszek
Uppsala University
2014-05-28
1
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/05/28/005561.source.xml
An ongoing debate in evolutionary biology is whether phenotypic change occurs predominantly around the time of speciation or whether it instead accumulates gradually over time. In this work I propose a general framework incorporating both types of change, quantify the effects of speciational change via the correlation between species and attribute the proportion of change to each type. I discuss results of parameter estimation of Hominoid body size in this light. I derive mathematical formulae related to this problem, the probability generating functions of the number of speciation events along a randomly drawn lineage and from the most recent common ancestor of two randomly chosen tip species for a conditioned Yule tree. Additionally I obtain in closed form the variance of the distance from the root to the most recent common ancestor of two randomly chosen tip species.
10.1016/j.mbs.2014.06.002
biorxiv
10.1101/005561
Quantifying the effects of anagenetic and cladogenetic evolution
Krzysztof Bartoszek;
Krzysztof Bartoszek
Uppsala University
2014-11-10
2
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/11/10/005561.source.xml
An ongoing debate in evolutionary biology is whether phenotypic change occurs predominantly around the time of speciation or whether it instead accumulates gradually over time. In this work I propose a general framework incorporating both types of change, quantify the effects of speciational change via the correlation between species and attribute the proportion of change to each type. I discuss results of parameter estimation of Hominoid body size in this light. I derive mathematical formulae related to this problem, the probability generating functions of the number of speciation events along a randomly drawn lineage and from the most recent common ancestor of two randomly chosen tip species for a conditioned Yule tree. Additionally I obtain in closed form the variance of the distance from the root to the most recent common ancestor of two randomly chosen tip species.
10.1016/j.mbs.2014.06.002
biorxiv
10.1101/005629
Extensive Regulation of Metabolism and Growth during the Cell Division Cycle
Nikolai Slavov;David Botstein;Amy Caudy;
Nikolai Slavov
Harvard University
2014-05-28
1
New Results
cc_by_nc_nd
Systems Biology
https://www.biorxiv.org/content/early/2014/05/28/005629.source.xml
Yeast cells grown in culture can spontaneously synchronize their respiration, metabolism, gene expression and cell division. Such metabolic oscillations in synchronized cultures reflect single-cell oscillations, but the relationship between the oscillations in single cells and synchronized cultures is poorly understood. To understand this relationship and the coordination between metabolism and cell division, we collected and analyzed DNA-content, gene-expression and physiological data, at hundreds of time-points, from cultures metabolically-synchronized at different growth rates, carbon sources and biomass densities. The data enabled us to extend and generalize our mechanistic model, based on ensemble average over phases (EAP), connecting the population-average gene-expression of asynchronous cultures to the gene-expression dynamics in the single-cells comprising the cultures. The extended model explains the carbon-source specific growth-rate responses of hundreds of genes. Our physiological data demonstrate that the frequency of metabolic cycling in synchronized cultures increases with the biomass density, suggesting that this cycling is an emergent behavior, resulting from the entraining of the single-cell metabolic cycle by a quorum-sensing mechanism, and thus underscoring the difference between metabolic cycling in single cells and in synchronized cultures. Measurements of constant levels of residual glucose across metabolically synchronized cultures indicate that storage carbohydrates are required to fuel not only the G1/S transition of the division cycle but also the metabolic cycle. Despite the large variation in profiled conditions and in the scale of their dynamics, most genes preserve invariant dynamics of coordination with each other and with the rate of oxygen consumption. Similarly, the G1/S transition always occurs at the beginning, middle or end of the high oxygen consumption phases, analogous to observations in human and drosophila cells. These results highlight evolutionary conserved coordination among metabolism, cell growth and division.
null
biorxiv
10.1101/005637
Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia
Simone Ecker;Vera Pancaldi;Daniel Rico;Alfonso Valencia;
Vera Pancaldi
Spanish National Cancer Research Centre (CNIO)
2014-05-29
1
New Results
cc_by_nc
Cancer Biology
https://www.biorxiv.org/content/early/2014/05/29/005637.source.xml
BackgroundChronic Lymphocytic Leukemia (CLL) presents two subtypes which have drastically different clinical outcomes. So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.\n\nResultsWe propose to use gene expression variability across patients to investigate differences between the two CLL subtypes. We find that the most aggressive type of this disease shows higher variability of gene expression across patients and we elaborate on this observation to produce a method that classifies patients into clinical subtypes. Finally, we find that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication, probably related to faster progression of this disease subtype.\n\nConclusionsThere are strong relations between disease subtype and gene expression variability linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.
10.1186/s13073-014-0125-z
biorxiv
10.1101/005637
Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia
Simone Ecker;Vera Pancaldi;Daniel Rico;Alfonso Valencia;
Vera Pancaldi
Spanish National Cancer Research Centre (CNIO)
2014-07-09
2
New Results
cc_by_nc
Cancer Biology
https://www.biorxiv.org/content/early/2014/07/09/005637.source.xml
BackgroundChronic Lymphocytic Leukemia (CLL) presents two subtypes which have drastically different clinical outcomes. So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.\n\nResultsWe propose to use gene expression variability across patients to investigate differences between the two CLL subtypes. We find that the most aggressive type of this disease shows higher variability of gene expression across patients and we elaborate on this observation to produce a method that classifies patients into clinical subtypes. Finally, we find that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication, probably related to faster progression of this disease subtype.\n\nConclusionsThere are strong relations between disease subtype and gene expression variability linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.
10.1186/s13073-014-0125-z
biorxiv
10.1101/005637
Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia
Simone Ecker;Vera Pancaldi;Daniel Rico;Alfonso Valencia;
Vera Pancaldi
Spanish National Cancer Research Centre (CNIO)
2014-09-03
3
New Results
cc_by_nc
Cancer Biology
https://www.biorxiv.org/content/early/2014/09/03/005637.source.xml
BackgroundChronic Lymphocytic Leukemia (CLL) presents two subtypes which have drastically different clinical outcomes. So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.\n\nResultsWe propose to use gene expression variability across patients to investigate differences between the two CLL subtypes. We find that the most aggressive type of this disease shows higher variability of gene expression across patients and we elaborate on this observation to produce a method that classifies patients into clinical subtypes. Finally, we find that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication, probably related to faster progression of this disease subtype.\n\nConclusionsThere are strong relations between disease subtype and gene expression variability linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.
10.1186/s13073-014-0125-z
biorxiv
10.1101/005686
Cancer-associated recurrent mutations in RNase III domains of DICER1
Bülent Arman Aksoy;Anders Jacobsen;Robert J Fieldhouse;William Lee;Emek Demir;Giovanni Ciriello;Nikolaus Schultz;Debora S Marks;Chris Sander;
Bülent Arman Aksoy
Computational Biology Center, Memorial Sloan-Kettering Cancer Center
2014-05-29
1
New Results
cc_no
Cancer Biology
https://www.biorxiv.org/content/early/2014/05/29/005686.source.xml
Mutations in the RNase IIIb domain of DICER1 are known to disrupt processing of 5p-strand pre-miRNAs and these mutations have previously been associated with cancer. Using data from the Cancer Genome Atlas project, we show that these mutations are recurrent across four cancer types and that a previously uncharacterized recurrent mutation in the adjacent RNase IIIa domain also disrupts 5p-strand miRNA processing. Analysis of the downstream effects of the resulting imbalance 5p/3p shows a statistically significant effect on the expression of mRNAs targeted by major conserved miRNA families. In summary, these mutations in DICER1 lead to an imbalance in miRNA strands, which has an effect on mRNA transcript levels that appear to contribute to the oncogenesis.
null
biorxiv
10.1101/005686
Cancer-associated recurrent mutations in RNase III domains of DICER1
Bülent Arman Aksoy;Anders Jacobsen;Robert J Fieldhouse;William Lee;Emek Demir;Giovanni Ciriello;Nikolaus Schultz;Debora S Marks;Chris Sander;
Bülent Arman Aksoy
Computational Biology Center, Memorial Sloan-Kettering Cancer Center
2014-09-12
2
New Results
cc_no
Cancer Biology
https://www.biorxiv.org/content/early/2014/09/12/005686.source.xml
Mutations in the RNase IIIb domain of DICER1 are known to disrupt processing of 5p-strand pre-miRNAs and these mutations have previously been associated with cancer. Using data from the Cancer Genome Atlas project, we show that these mutations are recurrent across four cancer types and that a previously uncharacterized recurrent mutation in the adjacent RNase IIIa domain also disrupts 5p-strand miRNA processing. Analysis of the downstream effects of the resulting imbalance 5p/3p shows a statistically significant effect on the expression of mRNAs targeted by major conserved miRNA families. In summary, these mutations in DICER1 lead to an imbalance in miRNA strands, which has an effect on mRNA transcript levels that appear to contribute to the oncogenesis.
null
biorxiv
10.1101/005660
Practopoiesis: Or how life fosters a mind
Danko Nikolic;
Danko Nikolic
Max Planck Institute for Brain Research
2014-05-29
1
New Results
cc_no
Neuroscience
https://www.biorxiv.org/content/early/2014/05/29/005660.source.xml
The mind is a biological phenomenon. Thus, biological principles of organization should also be the principles underlying mental operations. Practopoiesis states that the key for achieving intelligence through adaptation is an arrangement in which mechanisms laying a lower level of organization, by their operations and interaction with the environment, enable creation of mechanisms lying at a higher level of organization. When such an organizational advance of a system occurs, it is called a traverse. A case of traverse is when plasticity mechanisms (at a lower level of organization), by their operations, create a neural network anatomy (at a higher level of organization). Another case is the actual production of behavior by that network, whereby the mechanisms of neuronal activity operate to create motor actions. Practopoietic theory explains why the adaptability of a system increases with each increase in the number of traverses. With a larger number of traverses, a system can be relatively small and yet, produce a higher degree of adaptive/intelligent behavior than a system with a lower number of traverses. The present analyses indicate that the two well-known traverses--neural plasticity and neural activity--are not sufficient to explain human mental capabilities. At least one additional traverse is needed, which is named anapoiesis for its contribution in reconstructing knowledge e.g., from long-term memory into working memory. The conclusions bear implications for brain theory, the mind-body explanatory gap, and developments of artificial intelligence technologies.
10.1016/j.jtbi.2015.03.003
biorxiv
10.1101/005660
Practopoiesis: Or how life fosters a mind
Danko Nikolic;
Danko Nikolic
Max Planck Institute for Brain Research
2015-01-27
2
New Results
cc_no
Neuroscience
https://www.biorxiv.org/content/early/2015/01/27/005660.source.xml
The mind is a biological phenomenon. Thus, biological principles of organization should also be the principles underlying mental operations. Practopoiesis states that the key for achieving intelligence through adaptation is an arrangement in which mechanisms laying a lower level of organization, by their operations and interaction with the environment, enable creation of mechanisms lying at a higher level of organization. When such an organizational advance of a system occurs, it is called a traverse. A case of traverse is when plasticity mechanisms (at a lower level of organization), by their operations, create a neural network anatomy (at a higher level of organization). Another case is the actual production of behavior by that network, whereby the mechanisms of neuronal activity operate to create motor actions. Practopoietic theory explains why the adaptability of a system increases with each increase in the number of traverses. With a larger number of traverses, a system can be relatively small and yet, produce a higher degree of adaptive/intelligent behavior than a system with a lower number of traverses. The present analyses indicate that the two well-known traverses--neural plasticity and neural activity--are not sufficient to explain human mental capabilities. At least one additional traverse is needed, which is named anapoiesis for its contribution in reconstructing knowledge e.g., from long-term memory into working memory. The conclusions bear implications for brain theory, the mind-body explanatory gap, and developments of artificial intelligence technologies.
10.1016/j.jtbi.2015.03.003
biorxiv
10.1101/005694
The genetic basis of energy conservation in the sulfate-reducing bacterium Desulfovibrio alaskensis G20
Morgan Price;Jayashree Ray;Kelly M Wetmore;Jennifer V. Kuehl;Stefan Bauer;Adam M Deutschbauer;Adam P Arkin;
Morgan Price
Lawrence Berkeley Lab
2014-05-31
1
New Results
cc_by
Genetics
https://www.biorxiv.org/content/early/2014/05/31/005694.source.xml
Sulfate-reducing bacteria play major roles in the global carbon and sulfur cycles, but it remains unclear how reducing sulfate yields energy. To determine the genetic basis of energy conservation, we measured the fitness of thousands of pooled mutants of Desulfovibrio alaskensis G20 during growth in 12 different combinations of electron donors and acceptors. We show that ion pumping by the ferredoxin:NADH oxidoreductase Rnf is required whenever substrate-level phosphorylation is not possible. The uncharacterized complex Hdr/flox-1 (Dde_1207:13) is sometimes important alongside Rnf and may perform an electron bifurcation to generate more reduced ferredoxin from NADH to allow further ion pumping. Similarly, during the oxidation of malate or fumarate, the electron-bifurcating transhydrogenase NfnAB-2 (Dde_1250:1) is important and may generate reduced ferredoxin to allow additional ion pumping by Rnf. During formate oxidation, the periplasmic [NiFeSe] hydrogenase HysAB is required, which suggests that hydrogen forms in the periplasm, diffuses to the cytoplasm, and is used to reduce ferredoxin, thus providing a substrate for Rnf. During hydrogen utilization, the transmembrane electron transport complex Tmc is important and may move electrons from the periplasm into the cytoplasmic sulfite reduction pathway. Finally, mutants of many other putative electron carriers have no clear phenotype, which suggests that they are not important under our growth conditions.
10.3389/fmicb.2014.00577
biorxiv
10.1101/005736
Phylogenetic Identification and Functional Characterization of Orthologs and Paralogs across Human, Mouse, Fly, and Worm
Yi-Chieh Wu;Mukul S Bansal;Matthew D Rasmussen;Javier Herrero;Manolis Kellis;
Manolis Kellis
Massachusetts Institute of Technology
2014-05-31
1
New Results
cc_by_nc_nd
Genomics
https://www.biorxiv.org/content/early/2014/05/31/005736.source.xml
Model organisms can serve the biological and medical community by enabling the study of conserved gene families and pathways in experimentally-tractable systems. Their use, however, hinges on the ability to reliably identify evolutionary orthologs and paralogs with high accuracy, which can be a great challenge at both small and large evolutionary distances. Here, we present a phylogenomics-based approach for the identification of orthologous and paralogous genes in human, mouse, fly, and worm, which forms the foundation of the comparative analyses of the modENCODE and mouse ENCODE projects. We study a median of 16,101 genes across 2 mammalian genomes (human, mouse), 12 Drosophila genomes, 5 Caenorhabditis genomes, and an outgroup yeast genome, and demonstrate that accurate inference of evolutionary relationships and events across these species must account for frequent gene-tree topology errors due to both incomplete lineage sorting and insufficient phylogenetic signal. Furthermore, we show that integration of two separate phylogenomic pipelines yields increased accuracy, suggesting that their sources of error are independent, and finally, we leverage the resulting annotation of homologous genes to study the functional impact of gene duplication and loss in the context of rich gene expression and functional genomic datasets of the modENCODE, mouse ENCODE, and human ENCODE projects.
null
biorxiv
10.1101/005728
Boymaw, Overexpressed in Brains with Major Psychiatric Disorders, May Encode a Small Protein to Inhibit Mitochondrial Function and Protein Translation
Baohu Ji;Minjung Kim;Kerin Higa;Xianjin Zhou;
Xianjin Zhou
University of California San Diego
2014-05-31
1
New Results
cc_by
Neuroscience
https://www.biorxiv.org/content/early/2014/05/31/005728.source.xml
The t(1,11) chromosome translocation co-segregates with major psychiatric disorders in a large Scottish family. The translocation disrupts the DISC1 and Boymaw (DISC1FP1) genes on chromosomes 1 and 11, respectively. After translocation, two fusion genes are generated. Our recent studies found that the DISC1-Boymaw fusion protein is localized in mitochondria and inhibits oxidoreductase activity, rRNA expression, and protein translation. Mice carrying the DISC1-Boymaw fusion genes display intermediate behavioral phenotypes related to major psychiatric disorders. Here, we report that the Boymaw gene encodes a small protein predominantly localized in mitochondria. The Boymaw protein inhibits oxidoreductase activity, rRNA expression, and protein translation in the same way as the DISC1-Boymaw fusion protein. Interestingly, Boymaw expression is up-regulated by different stressors at RNA and/or protein translational levels. In addition, we found that Boymaw RNA expression is significantly increased in the postmortem brains of patients with major psychiatric disorders. Our studies therefore suggest that the Boymaw gene is a potential susceptibility gene for major psychiatric disorders in both the Scottish t(1,11) family and the general population of patients.
10.1002/ajmg.b.32311
biorxiv
10.1101/005710
Inhibition of protein translation by the DISC1-Boymaw fusion gene from a Scottish family with major psychiatric disorders
Baohu Ji;Kerin Higa;Minjung Kim;Lynn Zhou;Jared Young;Mark Geyer;Xianjin Zhou;
Xianjin Zhou
University of California, San Diego
2014-05-31
1
New Results
cc_by
Neuroscience
https://www.biorxiv.org/content/early/2014/05/31/005710.source.xml
The t(1; 11) translocation appears to be the causal genetic lesion with 70% penetrance for schizophrenia, major depression, and other psychiatric disorders in a Scottish family. Molecular studies identified the disruption of the DISC1 (disrupted-in-schizophrenia 1) gene by chromosome translocation at chromosome 1q42. Our previous studies, however, revealed that the translocation also disrupted another gene, Boymaw (also termed DISC1FP1), on chromosome 11. After translocation, two fusion genes (the DISC1-Boymaw (DB7) and the Boymaw-DISC1 (BD13)) are generated between the DISC1 and Boymaw genes. In the present study, we report that expression of the DB7 fusion gene inhibits both intracellular NADH oxidoreductase activities and protein translation. We generated humanized DISC1-Boymaw mice with gene targeting to examine the in vivo functions of the fusion genes. Consistent with the in vitro studies on the DB7 fusion gene, protein translation activity is decreased in the hippocampus and in cultured primary neurons from the brains of the humanized mice. Expression of Gad67, Nmdar1, and Psd95 proteins are also reduced. The humanized mice display prolonged and increased responses to the NMDA receptor antagonist, ketamine, on various mouse genetic backgrounds. Abnormal information processing of acoustic startle and depressive-like behaviors are also observed. In addition, the humanized mice display abnormal erythropoiesis, which was reported to associate with depression in humans. Expression of the DB7 fusion gene may reduce protein translation to impair brain functions and thereby contribute to the pathogenesis of major psychiatric disorders.
10.1093/hmg/ddu285
biorxiv
10.1101/005702
High-throughput functional annotation of influenza A virus genome at single-nucleotide resolution
Nicholas C. Wu;Arthur P. Young;Laith Q. Al-Mawsawi;C. Anders Olson;Jun Feng;Hangfei Qi;Shu-Hwa Chen;I-Hsuan Lu;Chung-Yen Lin;Robert G. Chin;Harding H. Luan;Nguyen Nguyen;Stanley F. Nelson;Xinmin Li;Ting-Ting Wu;Ren Sun;
Ren Sun
University of California, Los Angeles
2014-05-31
1
New Results
cc_by
Systems Biology
https://www.biorxiv.org/content/early/2014/05/31/005702.source.xml
A novel genome-wide genetics platform is presented in this study, which permits functional interrogation of all point mutations across a viral genome in parallel. Here we generated the first fitness profile of individual point mutations across the influenza virus genome. Critical residues on the viral genome were systematically identified, which provided a collection of subdomain data informative for structure-function studies and for effective rational drug and vaccine design. Our data was consistent with known, well-characterized structural features. In addition, we have achieved a validation rate of 68% for severely attenuated mutations and 94% for neutral mutations. The approach described in this study is applicable to other viral or microbial genomes where a means of genetic manipulation is available.
null
biorxiv
10.1101/005249
A field test for frequency-dependent selection on mimetic colour patterns in Heliconius butterflies
Patricio Alejandro Salazar Carrión;Martin Stevens;Robert T. Jones;Imogen Ogilvie;Chris Jiggins;
Patricio Alejandro Salazar Carri?n
Universidad Tecnol?gica Indoam?rica
2014-06-02
1
Contradictory Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/06/02/005249.source.xml
Mullerian mimicry, the similarity among unpalatable species, is thought to evolve by frequency-dependent selection. Accordingly, phenotypes that become established in an area are positively selected because predators have learnt to avoid these forms, while introduced phenotypes are eliminated because predators have not yet learnt to associate these other forms with unprofitability. We tested this prediction in two areas where different colour morphs of the mimetic species Heliconius erato and H. melpomene have become established, as well as in the hybrid zone between these morphs. In each area we tested for selection on three colour patterns: the two parental and the most common hybrid. We recorded bird predation on butterfly models with paper wings, matching the appearance of each morph to bird vision, and plasticine bodies. We did not detect differences in survival between colour morphs, but all morphs were more highly attacked in the hybrid zone. This finding is consistent with recent evidence from controlled experiments with captive birds, which suggest that the effectiveness of warning signals decreases when a large signal diversity is available to predators. This is likely to occur in the hybrid zone where over twenty hybrid phenotypes coexist.
null
biorxiv
10.1101/005835
Bacillus Calmette-Guerin infection in NADPH oxidase deficiency: defective mycobacterial sequestration and granuloma formation
Christine Deffert;Michela G. Schäppi;Jean-Claude Pache;Julien Cachat;Dominique Vesin;Ruth Bisig;Xiaojuan Ma Mulone;Tiina Kelkka;Rikard Holmdahl;Irene Garcia;Maria L. Olleros;Karl-Heinz Krause;
Christine Deffert
Medical Faculty and University of Geneva
2014-06-03
1
New Results
cc_no
Microbiology
https://www.biorxiv.org/content/early/2014/06/03/005835.source.xml
Patients with chronic granulomatous disease (CGD) lack generation of reactive oxygen species (ROS) through the phagocyte NADPH oxidase NOX2. CGD is an immune deficiency that leads to frequent infections with certain pathogens; this is well documented for S. aureus and A. fumigatus, but less clear for mycobacteria. We therefore performed an extensive literature search which yielded 297 cases of CGD patients with mycobacterial infections; M.bovis BCG was most commonly recovered (74%). The relationship between NOX2 deficiency and BCG infection however has never been studied in a mouse model. We therefore investigated BCG infection in three different mouse models of CGD: Ncf1 mutants in two different genetic backgrounds and NOX2 knock-out mice. In addition we investigated a macrophage-specific rescue (transgenic expression of Ncf1 under the control of the CD68 promoter). Wild type mice did not develop severe disease upon BCG injection. In contrast, all three types of CGD mice were highly susceptible to BCG, as witnessed by a severe weight loss, development of hemorrhagic pneumonia, and a high mortality ([~] 50%). Rescue of NOX2 activity in macrophages restored BCG resistance, similar as seen in wild-type mice. Granulomas from mycobacteria-infected wild type mice generated ROS, while granulomas from CGD mice did not. Bacterial load in CGD mice was only moderately increased, suggesting that it was not crucial for the observed phenotype. CGD mice responded with massively enhanced cytokine release (TNF-, IFN-{gamma}, IL-17 and IL-12) to BCG infection, which might account for severity of the disease. Finally, in wild-type mice, macrophages formed clusters and restricted mycobacteria to granulomas, while macrophages and mycobacteria were diffusely distributed in lung tissue from CGD mice. Our results demonstrate that lack of the NADPH oxidase leads to a markedly increased severity of BCG infection through mechanisms including increased cytokine production and impaired granuloma formation.
10.1371/journal.ppat.1004325
biorxiv
10.1101/005793
How the tortoise beats the hare: Slow and steady adaptation in structured populations suggests a rugged fitness landscape in bacteria
Joshua R. Nahum;Peter Godfrey-Smith;Brittany N. Harding;Joseph H. Marcus;Jared Carlson-Stevermer;Benjamin Kerr;
Joshua R. Nahum
Michigan State University
2014-06-03
1
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/06/03/005793.source.xml
AbstractIn the context of Wrights adaptive landscape, genetic epistasis can yield a multipeaked or \"rugged\" topography. In an unstructured population, a lineage with selective access to multiple peaks is expected to rapidly fix on one, which may not be the highest peak. Contrarily, beneficial mutations in a population with spatially restricted migration take longer to fix, allowing distant parts of the population to explore the landscape semi-independently. Such a population can simultaneous discover multiple peaks and the genotype at the highest discovered peak is expected to fix eventually. Thus, structured populations sacrifice initial speed of adaptation for breadth of search. As in the Tortoise-Hare fable, the structured population (Tortoise) starts relatively slow, but eventually surpasses the unstructured population (Hare) in average fitness. In contrast, on single-peak landscapes (e.g., systems lacking epistasis), all uphill paths converge. Given such \"smooth\" topography, breadth of search is devalued, and a structured population only lags behind an unstructured population in average fitness (ultimately converging). Thus, the Tortoise-Hare pattern is an indicator of ruggedness. After verifying these predictions in simulated populations where ruggedness is manipulable, we then explore average fitness in metapopulations of Escherichia coli. Consistent with a rugged landscape topography, we find a Tortoise-Hare pattern. Further, we find that structured populations accumulate more mutations, suggesting that distant peaks are higher. This approach can be used to unveil landscape topography in other systems, and we discuss its application for antibiotic resistance, engineering problems, and elements of Wrights Shifting Balance Process.\n\nSignificance StatementAdaptive landscapes are a way of describing how mutations interact with each other to produce fitness. If an adaptive landscape is rugged, organisms achieve higher fitness with more difficulty because the mutations to reach high fitness genotypes may not be always beneficial. By evolving populations of Escherichia coli with different degrees of spatial structure, we identified a Tortoise-Hare pattern, where structured populations were initially slower, but overtook less structured populations in mean fitness. These results, combined with genetic sequencing and computational simulation, indicate this bacterial adaptive landscape is rugged. Our findings address one of the most enduring questions in evolutionary biology, in addition to, providing insight into how evolution may influence medicine and engineering.
10.1073/pnas.1410631112
biorxiv
10.1101/005819
Natural variation in teosinte at the domestication locus teosinte branched1 (tb1)
Laura Vann;Thomas Kono;Tanja Pyha ̈j ̈arvi;Matthew B Hufford;Jeffrey Ross-Ibarra;
Jeffrey Ross-Ibarra
University of California, Davis
2014-06-03
1
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/06/03/005819.source.xml
Premise of the studyThe teosinte branched1 (tb1) gene is a major QTL controlling branching differences between maize and its wild progenitor, teosinte. The insertion of a transposable element (Hopscotch) upstream of tb1 is known to enhance the genes expression, causing reduced tillering in maize. Observations of the maize tb1 allele in teosinte and estimates of an insertion age of the Hopscotch that predates domestication led us to investigate its prevalence and potential role in teosinte.\n\nMethodsPrevalence of the Hopscotch element was assessed across an Americas-wide sample of 837 maize and teosinte individuals using a co-dominant PCR assay. Population genetic summaries were calculated for a subset of individuals from four teosinte populations in central Mexico. Phenotypic data were also collected using seed from a single teosinte population where Hopscotch was found segregating at high frequency.\n\nKey resultsGenotyping results indicate the Hopscotch element is found in a number of teosinte populations and linkage disequilibrium near tb1 does not support recent introgression from maize. Population genetic signatures are consistent with selection on this locus revealing a potential ecological role for Hopscotch in teosinte, but a greenhouse experiment does not detect a strong association between tb1 and tillering in teosinte.\n\nConclusionsOur findings suggest the role of Hopscotch differs between maize and teosinte. Future work should assess tb1 expression levels in teosinte with and without the Hopscotch and more comprehensively phenotype teosinte to assess the ecological significance of the Hopscotch insertion and, more broadly, the tb1 locus in teosinte.
10.7717/peerj.900
biorxiv
10.1101/005819
Natural variation in teosinte at the domestication locus teosinte branched1 (tb1)
Laura Vann;Thomas Kono;Tanja Pyha ̈j ̈arvi;Matthew B Hufford;Jeffrey Ross-Ibarra;
Jeffrey Ross-Ibarra
University of California, Davis
2014-09-11
2
New Results
cc_by
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/09/11/005819.source.xml
Premise of the studyThe teosinte branched1 (tb1) gene is a major QTL controlling branching differences between maize and its wild progenitor, teosinte. The insertion of a transposable element (Hopscotch) upstream of tb1 is known to enhance the genes expression, causing reduced tillering in maize. Observations of the maize tb1 allele in teosinte and estimates of an insertion age of the Hopscotch that predates domestication led us to investigate its prevalence and potential role in teosinte.\n\nMethodsPrevalence of the Hopscotch element was assessed across an Americas-wide sample of 837 maize and teosinte individuals using a co-dominant PCR assay. Population genetic summaries were calculated for a subset of individuals from four teosinte populations in central Mexico. Phenotypic data were also collected using seed from a single teosinte population where Hopscotch was found segregating at high frequency.\n\nKey resultsGenotyping results indicate the Hopscotch element is found in a number of teosinte populations and linkage disequilibrium near tb1 does not support recent introgression from maize. Population genetic signatures are consistent with selection on this locus revealing a potential ecological role for Hopscotch in teosinte, but a greenhouse experiment does not detect a strong association between tb1 and tillering in teosinte.\n\nConclusionsOur findings suggest the role of Hopscotch differs between maize and teosinte. Future work should assess tb1 expression levels in teosinte with and without the Hopscotch and more comprehensively phenotype teosinte to assess the ecological significance of the Hopscotch insertion and, more broadly, the tb1 locus in teosinte.
10.7717/peerj.900
biorxiv
10.1101/005751
Genomic, transcriptomic and phenomic variation reveals the complex adaptation of modern maize breeding
Haijun Liu;Xiaqing Wang;Marilyn Warburton;Weiwei Wen;Minliang Jin;Min Deng;Jie Liu;Hao Tong;Qingchun Pan;Xiaohong Yang;Jianbing Yan;
Jianbing Yan
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University
2014-06-03
1
New Results
cc_no
Evolutionary Biology
https://www.biorxiv.org/content/early/2014/06/03/005751.source.xml
The temperate-tropical division of early maize germplasm to different agricultural environments was arguably the greatest adaptation process associated with the success and near ubiquitous importance of global maize production. Deciphering this history is challenging, but new insight has been gained from the genomic, transcriptomic and phenotypic variation collected from 368 diverse temperate and tropical maize inbred lines in this study. This is the first attempt to systematically explore the mechanisms of the adaptation process. Our results indicated that divergence between tropical and temperate lines seem occur 3,400-6,700 years ago. A number of genomic selection signals and transcriptomic variants including differentially expressed individual genes and rewired co-expression networks of genes were identified. These candidate signals were found to be functionally related to stress response and most were associated with directionally selected traits, which may have been an advantage under widely varying environmental conditions faced by maize as it was migrated away from its domestication center. Its also clear in our study that such stress adaptation could involve evolution of protein-coding sequences as well as transcriptome-level regulatory changes. This latter process may be a more flexible and dynamic way for maize to adapt to environmental changes over this dramatically short evolutionary time frame.
10.1016/j.molp.2015.01.016
biorxiv
10.1101/005892
Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits
Darren Kessner;John Novembre;
John Novembre
University of Chicago
2014-06-04
1
New Results
cc_no
Genomics
https://www.biorxiv.org/content/early/2014/06/04/005892.source.xml
Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTLs) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides produces qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTLs under selection impacts the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50-100%) can be explained by detected QTLs in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.
10.1534/genetics.115.175075
biorxiv
10.1101/005900
Complete plastid genome assembly of invasive plant, Centaurea diffusa
Kathryn G Turner;Christopher J Grassa;
Kathryn G Turner
University of British Columbia
2014-06-04
1
New Results
cc_by_nc
Genomics
https://www.biorxiv.org/content/early/2014/06/04/005900.source.xml
New genomic tools are needed to elucidate the evolution of invasive, non-model organisms. Here we present the completed plastome assembly for the problematic invasive weed, Centaurea diffusa. This new tool represents a significant contribution to future studies of the ecological genomics of invasive plants, particularly this weedy genus, and studies of the Asteraceae in general.
null
biorxiv