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10.1101/002410

Broadly tuned and respiration-independent inhibition in the olfactory bulb of awake mice

Brittany N Cazakoff;Billy Y B Lau;Kerensa L Crump;Heike Demmer;Stephen David Shea;

Stephen David Shea

Cold Spring Harbor Laboratory

2014-02-06

New Results

cc_by_nc_nd

Neuroscience

https://www.biorxiv.org/content/early/2014/02/06/002410.source.xml

Olfactory representations are shaped by both brain state and respiration; however, the interaction and circuit substrates of these influences are poorly understood. Granule cells (GCs) in the main olfactory bulb (MOB) are presumed to sculpt activity that reaches the olfactory cortex via inhibition of mitral/tufted cells (MTs). GCs may potentially sparsen ensemble activity by facilitating lateral inhibition among MTs, and/or they may enforce temporally-precise activity locked to breathing. Yet, the selectivity and temporal structure of GC activity during wakefulness are unknown. We recorded GCs in the MOB of anesthetized and awake mice and reveal pronounced state-dependent features of odor coding and temporal patterning. Under anesthesia, GCs exhibit sparse activity and are strongly and synchronously coupled to the respiratory cycle. Upon waking, GCs desynchronize, broaden their odor responses, and typically fire without regard for the respiratory rhythm. Thus during wakefulness, GCs exhibit stronger odor responses with less temporal structure. Based on these observations, we propose that during wakefulness GCs likely predominantly shape MT odor responses through broadened lateral interactions rather than respiratory synchronization.

10.1038/nn.3669

biorxiv

10.1101/002469

Automated ensemble assembly and validation of microbial genomes

Sergey Koren;Todd J Treangen;Christopher M Hill;Mihai Pop;Adam M Phillippy;

Sergey Koren

National Biodefense Analysis and Countermeasures Center

2014-02-07

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/07/002469.source.xml

BackgroundThe continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis; this is a labor-intensive process that is often impossible or unfeasible.\n\nResultsTo encourage best practices supported by the community, we present iMetAMOS, an automated ensemble assembly pipeline; iMetAMOS encapsulates the process of running, validating, and selecting a single assembly from multiple assemblies. iMetAMOS packages several leading open-source tools into a single binary that automates parameter selection and execution of multiple assemblers, scores the resulting assemblies based on multiple validation metrics, and annotates the assemblies for genes and contaminants. We demonstrate the utility of the ensemble process on 225 previously unassembled Mycobacterium tuberculosis genomes as well as a Rhodobacter sphaeroides benchmark dataset. On these real data, iMetAMOS reliably produces validated assemblies and identifies potential contamination without user intervention. In addition, intelligent parameter selection produces assemblies of R. sphaeroides that exceed the quality of those from the GAGE-B evaluation, affecting the relative ranking of some assemblers.\n\nConclusionsEnsemble assembly with iMetAMOS provides users with multiple, validated assemblies for each genome. Although computationally limited to small or mid-sized genomes, this approach is the most effective and reproducible means for generating high-quality assemblies and enables users to select an assembly best tailored to their specific needs.

10.1186/1471-2105-15-126

biorxiv

10.1101/002501

Within the fortress: A specialized parasite of ants is not evicted

Emilia S. Gracia;Charissa de Bekker;Jim Russell;Kezia Manlove;Ephraim Hanks;David P. Hughes;

Emilia S. Gracia

Pennsylvania State University

2014-02-07

New Results

cc_no

Ecology

https://www.biorxiv.org/content/early/2014/02/07/002501.source.xml

Every level of biological organization from cells to societies require that composing units come together to form parts of a bigger unit (1). Our knowledge of how behavioral manipulating parasites change social interactions between social hosts is limited. Here we use an endoparasite to observe changes in social interactions between infected and healthy ants, using trophallaxis (liquid food exchange) and spatial data as proxies for food sharing and social segregation. We found no change in trophallaxis (p-value = 0.5156). By using K-function and nearest neighbor analyses we did see a significant difference in spatial segregation on day 3 (less than 8 millimeters; p-value < 0.05). These results suggest healthy individuals are unable to detect the parasite within the host.

biorxiv

10.1101/002501

Within the fortress: A specialized parasite of ants is not evicted

Emilia S. Gracia;Charissa de Bekker;Jim Russell;Kezia Manlove;Ephraim Hanks;David P. Hughes;

Emilia S. Gracia

Pennsylvania State University

2014-02-12

New Results

cc_no

Ecology

https://www.biorxiv.org/content/early/2014/02/12/002501.source.xml

Every level of biological organization from cells to societies require that composing units come together to form parts of a bigger unit (1). Our knowledge of how behavioral manipulating parasites change social interactions between social hosts is limited. Here we use an endoparasite to observe changes in social interactions between infected and healthy ants, using trophallaxis (liquid food exchange) and spatial data as proxies for food sharing and social segregation. We found no change in trophallaxis (p-value = 0.5156). By using K-function and nearest neighbor analyses we did see a significant difference in spatial segregation on day 3 (less than 8 millimeters; p-value < 0.05). These results suggest healthy individuals are unable to detect the parasite within the host.

biorxiv

10.1101/002527

Investigating speciation in face of polyploidization: what can we learn from approximate Bayesian computation approach?

Camille Roux;John Pannell;

Camille Roux

University of Lausanne

2014-02-09

New Results

cc_by

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/09/002527.source.xml

Despite its importance in the diversification of many eucaryote clades, particularly plants, detailed genomic analysis of polyploid species is still in its infancy, with published analysis of only a handful of model species to date. Fundamental questions concerning the origin of polyploid lineages (e.g., auto- vs. allopolyploidy) and the extent to which polyploid genomes display disomic vs. polysomic vs. heterosomic inheritance are poorly resolved for most polyploids, not least because they have hitherto required detailed karyotypic analysis or the analysis of allele segregation at multiple loci in pedigrees or artificial crosses, which are often not practical for non-model species. However, the increasing availability of sequence data for non-model species now presents an opportunity to apply established approaches for the evolutionary analysis of genomic data to polyploid species complexes. Here, we ask whether approximate Bayesian computation (ABC), applied to sequence data produced by next-generation sequencing technologies from polyploid taxa, allows correct inference of the evolutionary and demographic history of polyploid lineages and their close relatives. We use simulations to investigate how the number of sampled individuals, the number of surveyed loci and their length affect the accuracy and precision of evolutionary and demographic inferences by ABC, including the mode of polyploidisation, mode of inheritance of polyploid taxa, the relative timing of genome duplication and speciation, and effective populations sizes of contributing lineages. We also apply the ABC framework we develop to sequence data from diploid and polyploidy species of the plant genus Capsella, for which we infer an allopolyploid origin for tetra C. bursa-pastoris {approx} 90,000 years ago. In general, our results indicate that ABC is a promising and powerful method for uncovering the origin and subsequent evolution of polyploid species.

biorxiv

10.1101/002493

The roles of standing genetic variation and evolutionary history in determining the evolvability of anti-predator strategies

Jordan Fish;Daniel R O'Donnell;Abhijna Parigi;Ian Dworkin;Aaron P Wagner;

Daniel R O'Donnell

Michigan State University

2014-02-07

New Results

cc_by_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/07/002493.source.xml

Standing genetic variation and the historical environment in which that variation arises (evolutionary history) are both potentially significant determinants of a populations capacity for evolutionary response to a changing environment. We evaluated the relative importance of these two factors in influencing the evolutionary trajectories in the face of sudden environmental change. We used the open-ended digital evolution software Avida to examine how historic exposure to predation pressures, different levels of genetic variation, and combinations of the two, impact anti-predator strategies and competitive abilities evolved in the face of threats from new, invasive, predator populations. We show that while standing genetic variation plays some role in determining evolutionary responses, evolutionary history has the greater influence on a populations capacity to evolve effective anti-predator traits. This adaptability likely reflects the relative ease of repurposing existing, relevant genes and traits, and the broader potential value of the generation and maintenance of adaptively flexible traits in evolving populations.

10.1371/journal.pone.0100163

biorxiv

10.1101/002485

Epistasis within the MHC contributes to the genetic architecture of celiac disease

Ben Goudey;Gad Abraham;Eder Kikianty;Qiao Wang;Dave Rawlinson;Fan Shi;Izhak Haviv;Linda Stern;Adam Kowalczyk;Michael Inouye;

Michael Inouye

Centre for Systems Genomics, School of BioSciences, University of Melbourne

2014-02-07

New Results

cc_by

Genomics

https://www.biorxiv.org/content/early/2014/02/07/002485.source.xml

Epistasis has long been thought to contribute to the genetic aetiology of complex diseases, yet few robust epistatic interactions in humans have been detected. We have conducted exhaustive genome-wide scans for pairwise epistasis in five independent celiac disease (CD) case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 20 significant epistatic signals within the HLA region which achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD epistatic signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkins lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for epistatic variants outside the MHC was not observed. Both within and between European populations, we observed striking consistency of epistatic models and epistatic model distribution. Within the UK population, models of CD based on both epistatic and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. Models of only epistatic pairs or additive single-SNPs showed similar levels of CD variance explained, indicating the existence of a substantial overlap of additive and epistatic components. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

biorxiv

10.1101/002485

Epistasis within the MHC contributes to the genetic architecture of celiac disease

Ben Goudey;Gad Abraham;Eder Kikianty;Qiao Wang;Dave Rawlinson;Fan Shi;Izhak Haviv;Linda Stern;Adam Kowalczyk;Michael Inouye;

Michael Inouye

Centre for Systems Genomics, School of BioSciences, University of Melbourne

2014-02-20

New Results

cc_by

Genomics

https://www.biorxiv.org/content/early/2014/02/20/002485.source.xml

Epistasis has long been thought to contribute to the genetic aetiology of complex diseases, yet few robust epistatic interactions in humans have been detected. We have conducted exhaustive genome-wide scans for pairwise epistasis in five independent celiac disease (CD) case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 20 significant epistatic signals within the HLA region which achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD epistatic signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkins lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for epistatic variants outside the MHC was not observed. Both within and between European populations, we observed striking consistency of epistatic models and epistatic model distribution. Within the UK population, models of CD based on both epistatic and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. Models of only epistatic pairs or additive single-SNPs showed similar levels of CD variance explained, indicating the existence of a substantial overlap of additive and epistatic components. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

biorxiv

10.1101/002485

Epistasis within the MHC contributes to the genetic architecture of celiac disease

Ben Goudey;Gad Abraham;Eder Kikianty;Qiao Wang;Dave Rawlinson;Fan Shi;Izhak Haviv;Linda Stern;Adam Kowalczyk;Michael Inouye;

Michael Inouye

Centre for Systems Genomics, School of BioSciences, University of Melbourne

2014-05-29

New Results

cc_by

Genomics

https://www.biorxiv.org/content/early/2014/05/29/002485.source.xml

Epistasis has long been thought to contribute to the genetic aetiology of complex diseases, yet few robust epistatic interactions in humans have been detected. We have conducted exhaustive genome-wide scans for pairwise epistasis in five independent celiac disease (CD) case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 20 significant epistatic signals within the HLA region which achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD epistatic signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkins lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for epistatic variants outside the MHC was not observed. Both within and between European populations, we observed striking consistency of epistatic models and epistatic model distribution. Within the UK population, models of CD based on both epistatic and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. Models of only epistatic pairs or additive single-SNPs showed similar levels of CD variance explained, indicating the existence of a substantial overlap of additive and epistatic components. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

biorxiv

10.1101/002485

Epistasis within the MHC contributes to the genetic architecture of celiac disease

Ben Goudey;Gad Abraham;Eder Kikianty;Qiao Wang;Dave Rawlinson;Fan Shi;Izhak Haviv;Linda Stern;Adam Kowalczyk;Michael Inouye;

Michael Inouye

Centre for Systems Genomics, School of BioSciences, University of Melbourne

2015-08-11

New Results

cc_by

Genomics

https://www.biorxiv.org/content/early/2015/08/11/002485.source.xml

Epistasis has long been thought to contribute to the genetic aetiology of complex diseases, yet few robust epistatic interactions in humans have been detected. We have conducted exhaustive genome-wide scans for pairwise epistasis in five independent celiac disease (CD) case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 20 significant epistatic signals within the HLA region which achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD epistatic signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkins lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for epistatic variants outside the MHC was not observed. Both within and between European populations, we observed striking consistency of epistatic models and epistatic model distribution. Within the UK population, models of CD based on both epistatic and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. Models of only epistatic pairs or additive single-SNPs showed similar levels of CD variance explained, indicating the existence of a substantial overlap of additive and epistatic components. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

biorxiv

10.1101/002337

Metabolic composition of anode community predicts electrical power in microbial fuel cells

Andre Gruning;Nelli J Beecroft;Claudio Avignone-Rossa;

Andre Gruning

University of Surrey

2014-02-07

New Results

cc_by_nc_nd

Microbiology

https://www.biorxiv.org/content/early/2014/02/07/002337.source.xml

Microbial Fuel Cells (MFCs) are a promising technology for organic waste treatment and sustainable bioelectricity production. Inoculated with natural communities, they present a complex microbial ecosystem with syntrophic interactions between microbes with different metabolic capabilities. From this point of view, they are similar to anaerobic digesters, however with methanogenesis replaced by anaerobic respiration with the anode as terminal electron acceptor. Bio-electrochemically they are similar to classical fuel cells where however the electrogenic redox reaction is part of the microbial metabolism rather than mediated by an inorganic catalyst.\n\nIn this paper, we analyse how electric power production in MFCs depends on the composition of the anodic biofilm in terms of metabolic capabilities of identified sets of species. MFCs were started with a natural inoculum and continuously fed with sucrose, a fermentable carbohydrate. The composition of the community, power and other environmental data were sampled over a period of a few weeks during the maturation of the anodic biofilm, and the community composition was determined down to the species level including relevant metabolic capabilities.\n\nOur results support the hypothesis that an MFCs with natural inoculum and fermentable feedstock is essentially a two stage system with fermentation followed by anode-respiration. Our results also show that under identical starting and operating conditions, MFCs with comparable power output can develop different anodic communities with no particular species dominant across all replicas. It is only important for good power production that all cells contain a sufficient fraction of low-potential anaerobic respirators, that is respirators that can use terminal electron acceptors with a low redox potential. We conclude with a number of hypotheses and recommendations for the operation of MFCs to ensure good electric yield.

10.1007/s00248-014-0518-y

biorxiv

10.1101/002550

Noradrenergic plasticity of olfactory sensory neuron inputs to the main olfactory bulb

Dennis Eckmeier;Stephen David Shea;

Stephen David Shea

Cold Spring Harbor Laboratory

2014-02-09

New Results

cc_by_nc_nd

Neuroscience

https://www.biorxiv.org/content/early/2014/02/09/002550.source.xml

Sensory responses are modulated throughout the nervous system by internal factors including attention, experience, and brain state. This is partly due to fluctuations in neuromodulatory input from regions such as the noradrenergic locus coeruleus (LC) in the brainstem. LC activity changes with arousal and modulates sensory processing, cognition and memory. The main olfactory bulb (MOB) is richly targeted by LC fibers and noradrenaline profoundly influences MOB circuitry and odor-guided behavior. Noradrenaline-dependent plasticity affects the output of the MOB. However, it is unclear whether noradrenergic plasticity includes modulation in the glomerular layer, the site of input to the MOB. Noradrenergic terminals are found in the glomerular layer, but noradrenaline receptor activation does not seem to acutely modulate olfactory sensory neuron terminals in vitro. We investigated whether noradrenaline induces plasticity at the glomerulus. We used wide-field optical imaging to measure changes in odor responses following electrical stimulation of locus coeruleus in anesthetized mice. Surprisingly, the odor-evoked intrinsic optical signals at the glomerulus were persistently weakened after LC activation. Calcium imaging selectively from olfactory sensory neurons confirmed that this effect was due to a uniform gain suppression of presynaptic input, and did not require exposure to a stimulus during the LC activation. Finally, noradrenaline antagonists prevented glomerular suppression. We conclude that noradrenaline release from LC has persistent effects on odor processing already at the first synapse of the main olfactory system. This mechanism could contribute to arousal-dependent memories.

10.1523/JNEUROSCI.0551-14.2014

biorxiv

10.1101/002550

Noradrenergic plasticity of olfactory sensory neuron inputs to the main olfactory bulb

Dennis Eckmeier;Stephen David Shea;

Stephen David Shea

Cold Spring Harbor Laboratory

2014-08-12

New Results

cc_by_nc_nd

Neuroscience

https://www.biorxiv.org/content/early/2014/08/12/002550.source.xml

Sensory responses are modulated throughout the nervous system by internal factors including attention, experience, and brain state. This is partly due to fluctuations in neuromodulatory input from regions such as the noradrenergic locus coeruleus (LC) in the brainstem. LC activity changes with arousal and modulates sensory processing, cognition and memory. The main olfactory bulb (MOB) is richly targeted by LC fibers and noradrenaline profoundly influences MOB circuitry and odor-guided behavior. Noradrenaline-dependent plasticity affects the output of the MOB. However, it is unclear whether noradrenergic plasticity includes modulation in the glomerular layer, the site of input to the MOB. Noradrenergic terminals are found in the glomerular layer, but noradrenaline receptor activation does not seem to acutely modulate olfactory sensory neuron terminals in vitro. We investigated whether noradrenaline induces plasticity at the glomerulus. We used wide-field optical imaging to measure changes in odor responses following electrical stimulation of locus coeruleus in anesthetized mice. Surprisingly, the odor-evoked intrinsic optical signals at the glomerulus were persistently weakened after LC activation. Calcium imaging selectively from olfactory sensory neurons confirmed that this effect was due to a uniform gain suppression of presynaptic input, and did not require exposure to a stimulus during the LC activation. Finally, noradrenaline antagonists prevented glomerular suppression. We conclude that noradrenaline release from LC has persistent effects on odor processing already at the first synapse of the main olfactory system. This mechanism could contribute to arousal-dependent memories.

10.1523/JNEUROSCI.0551-14.2014

biorxiv

10.1101/002576

Sashimi plots: Quantitative visualization of alternative isoform expression from RNA-seq data

Yarden Katz;Eric T Wang;Jacob Stilterra;Schraga Schwartz;Bang Wong;Helga Thorvaldsdóttir;James T Robinson;Jill P Mesirov;Edoardo M Airoldi;Christopher B Burge;

Christopher B Burge

MIT

2014-02-11

New Results

cc_no

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/11/002576.source.xml

To the Editor: To the Editor: Software documentation and... References Analysis of RNA sequencing (RNA-Seq) data revealed that the vast majority of human genes express multiple mRNA isoforms, produced by alternative pre-mRNA splicing and other mechanisms, and that most alternative isoforms vary in expression between human tissues (Pan et al., 2008; Wang et al., 2008). As RNA-Seq datasets grow in size, it remains challenging to visualize isoform expression across multiple samples. We present Sashimi plots, a quantitative multi-sample visualization of RNA-Seq reads aligned to gene annotations, which enables quantitative comparison of isoform usage across samples or experimental conditions. Given an input annotation and spliced alignments of reads from a sample, a region of interest is visualized in a Sashimi plot as follows: (i) alignments in ...

10.1093/bioinformatics/btv034

biorxiv

10.1101/002519

Social, spatial and temporal segregation in an ant society

Lauren E Quevillon;Ephraim M Hanks;Shweta Bansal;David P Hughes;

Lauren E Quevillon

Penn State University

2014-02-11

New Results

cc_by_nc_nd

Ecology

https://www.biorxiv.org/content/early/2014/02/11/002519.source.xml

Introduction Introduction Results Discussion Methods References Sociality can be risky. A chief cost of social living is increased transmission of infectious diseases, due to higher population densities combined with greater contact between susceptible and infected individuals (1,2,3,4). This greater encounter rate has led to a growing interest in the role of social contact structure in infectious disease transmission (5,6,7,8,9,10,11) To capture the dynamics of disease spread within dense groups, epidemiological models are shifting from the principle of mass action, in which infected and susceptible individuals are assumed to mix randoml ...

biorxiv

10.1101/002584

Estimating the evolution of human life history traits in age-structured populations

Ryan Baldini;

Ryan Baldini

UC Davis

2014-02-11

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/11/002584.source.xml

I propose a method that estimates the selection response of all vital rates in an age-structured population. I assume that vital rates are determined by the additive genetic contributions of many loci. The method uses all relatedness information in the sample to inform its estimates of genetic parameters, via an MCMC Bayesian framework. One can use the results to estimate the selection response of any life history trait that is a function of the vital rates, including the age at first reproduction, total lifetime fertility, survival to adulthood, and others. This method closely ties the empirical analysis of life history evolution to dynamically complete models of natural selection, and therefore enjoys some theoretical advantages over other methods. I demonstrate the method on a simulated model of evolution with two age classes. Finally I discuss how the method can be extended to more complicated cases.

biorxiv

10.1101/002584

Estimating the evolution of human life history traits in age-structured populations

Ryan Baldini;

Ryan Baldini

UC Davis

2014-02-19

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/19/002584.source.xml

I propose a method that estimates the selection response of all vital rates in an age-structured population. I assume that vital rates are determined by the additive genetic contributions of many loci. The method uses all relatedness information in the sample to inform its estimates of genetic parameters, via an MCMC Bayesian framework. One can use the results to estimate the selection response of any life history trait that is a function of the vital rates, including the age at first reproduction, total lifetime fertility, survival to adulthood, and others. This method closely ties the empirical analysis of life history evolution to dynamically complete models of natural selection, and therefore enjoys some theoretical advantages over other methods. I demonstrate the method on a simulated model of evolution with two age classes. Finally I discuss how the method can be extended to more complicated cases.

biorxiv

10.1101/002428

Evidence for widespread positive and negative selection in coding and conserved noncoding regions of Capsella grandiflora

Robert J Williamson;Emily B Josephs;Adrian E Platts;Khaled M Hazzouri;Annabelle Haudry;Mathieu Blanchette;Stephen I Wright;

Emily B Josephs

University of Toronto

2014-02-10

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/10/002428.source.xml

The extent that both positive and negative selection vary across different portions of plant genomes remains poorly understood. Here, we sequence whole genomes of 13 Capsella grandiflora individuals and quantify the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we show that selection is strong in coding regions, but weak in most noncoding regions, with the exception of 5’ and 3’ untranslated regions (UTRs). However, estimates of selection in noncoding regions conserved across the Brassicaceae family show strong signals of selection. Additionally, we see reductions in neutral diversity around functional substitutions in both coding and conserved noncoding regions, indicating recent selective sweeps at these sites. Finally, using expression data from leaf tissue we show that genes that are more highly expressed experience stronger negative selection but comparable levels of positive selection to lowly expressed genes. Overall, we observe widespread positive and negative selection in coding and regulatory regions, but our results also suggest that both positive and negative selection in plant noncoding sequence are considerably rarer than in animal genomes.

10.1371/journal.pgen.1004622

biorxiv

10.1101/002428

Evidence for widespread positive and negative selection in coding and conserved noncoding regions of Capsella grandiflora

Robert J Williamson;Emily B Josephs;Adrian E Platts;Khaled M Hazzouri;Annabelle Haudry;Mathieu Blanchette;Stephen I Wright;

Emily B Josephs

University of Toronto

2014-06-09

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/06/09/002428.source.xml

The extent that both positive and negative selection vary across different portions of plant genomes remains poorly understood. Here, we sequence whole genomes of 13 Capsella grandiflora individuals and quantify the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we show that selection is strong in coding regions, but weak in most noncoding regions, with the exception of 5’ and 3’ untranslated regions (UTRs). However, estimates of selection in noncoding regions conserved across the Brassicaceae family show strong signals of selection. Additionally, we see reductions in neutral diversity around functional substitutions in both coding and conserved noncoding regions, indicating recent selective sweeps at these sites. Finally, using expression data from leaf tissue we show that genes that are more highly expressed experience stronger negative selection but comparable levels of positive selection to lowly expressed genes. Overall, we observe widespread positive and negative selection in coding and regulatory regions, but our results also suggest that both positive and negative selection in plant noncoding sequence are considerably rarer than in animal genomes.

10.1371/journal.pgen.1004622

biorxiv

10.1101/002725

Spectacle: Faster and more accurate chromatin state annotation using spectral learning

Jimin Song;Kevin C Chen;

Kevin C Chen

Rutgers University

2014-02-14

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/14/002725.source.xml

Recently, a wealth of epigenomic data has been generated by biochemical assays and next-generation sequencing (NGS) technologies. In particular, histone modification data generated by the ENCODE project and other large-scale projects show specific patterns associated with regulatory elements in the human genome. It is important to build a unified statistical model to decipher the patterns of multiple histone modifications in a cell type to annotate chromatin states such as transcription start sites, enhancers and transcribed regions rather than to map histone modifications individually to regulatory elements.\n\nSeveral genome-wide statistical models have been developed based on hidden Markov models (HMMs). These methods typically use the Expectation-Maximization (EM) algorithm to estimate the parameters of the model. Here we used spectral learning, a state-of-the-art parameter estimation algorithm in machine learning. We found that spectral learning plus a few (up to five) iterations of local optimization of the likelihood outper-forms the standard EM algorithm. We also evaluated our software implementation called Spectacle on independent biological datasets and found that Spectacle annotated experimentally defined functional elements such as enhancers significantly better than a previous state-of-the-art method.\n\nSpectacle can be downloaded from https://github.com/jiminsong/Spectacle.

biorxiv

10.1101/002725

Spectacle: Faster and more accurate chromatin state annotation using spectral learning

Jimin Song;Kevin C Chen;

Kevin C Chen

Rutgers University

2014-03-09

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/03/09/002725.source.xml

Recently, a wealth of epigenomic data has been generated by biochemical assays and next-generation sequencing (NGS) technologies. In particular, histone modification data generated by the ENCODE project and other large-scale projects show specific patterns associated with regulatory elements in the human genome. It is important to build a unified statistical model to decipher the patterns of multiple histone modifications in a cell type to annotate chromatin states such as transcription start sites, enhancers and transcribed regions rather than to map histone modifications individually to regulatory elements.\n\nSeveral genome-wide statistical models have been developed based on hidden Markov models (HMMs). These methods typically use the Expectation-Maximization (EM) algorithm to estimate the parameters of the model. Here we used spectral learning, a state-of-the-art parameter estimation algorithm in machine learning. We found that spectral learning plus a few (up to five) iterations of local optimization of the likelihood outper-forms the standard EM algorithm. We also evaluated our software implementation called Spectacle on independent biological datasets and found that Spectacle annotated experimentally defined functional elements such as enhancers significantly better than a previous state-of-the-art method.\n\nSpectacle can be downloaded from https://github.com/jiminsong/Spectacle.

biorxiv

10.1101/002642

A reassessment of consensus clustering for class discovery

Yasin Şenbabaoğlu;George Michailidis;Jun Z Li;

Jun Z Li

University of Michigan Ann Arbor

2014-02-14

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/14/002642.source.xml

Consensus clustering (CC) is an unsupervised class discovery method widely used to study sample heterogeneity in high-dimensional datasets. It calculates \"consensus rate\" between any two samples as how frequently they are grouped together in repeated clustering runs under a certain degree of random perturbation. The pairwise consensus rates form a between-sample similarity matrix, which has been used (1) as a visual proof that clusters exist, (2) for comparing stability among clusters, and (3) for estimating the optimal number (K) of clusters. However, the sensitivity and specificity of CC have not been systemically studied. To assess its performance, we investigated the most common implementations of CC; and compared CC with other popular methods that also focus on cluster stability and estimation of K. We evaluated these methods using simulated datasets with either known structure or known absence of structure. Our results showed that (1) CC was able to divide randomly generated unimodal data into pre-specified numbers of clusters, and was able to show apparent stability of these chance partitions of known cluster-less data; (2) for data with known structure, the proportion of ambiguously clustered (PAC) pairs infers the known number of clusters more reliably than several commonly used K estimating methods; and (3) validation of the optimal K by choosing the most discriminant genes from the discovery cohort and applying them in an independent cohort often exaggerates the confidence in K due to inherent gene-gene correlations among the selected genes. While these results do not yet prove that any of the published studies using CC has generated false positive findings, they show that datasets with subtle or no structure are fully capable of producing strong evidence of consensus clustering. We therefore recommend caution is using CC in class discovery and validation.

10.1038/srep06207

biorxiv

10.1101/002642

A reassessment of consensus clustering for class discovery

Yasin Şenbabaoğlu;George Michailidis;Jun Z Li;

Jun Z Li

University of Michigan Ann Arbor

2014-02-15

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/15/002642.source.xml

Consensus clustering (CC) is an unsupervised class discovery method widely used to study sample heterogeneity in high-dimensional datasets. It calculates \"consensus rate\" between any two samples as how frequently they are grouped together in repeated clustering runs under a certain degree of random perturbation. The pairwise consensus rates form a between-sample similarity matrix, which has been used (1) as a visual proof that clusters exist, (2) for comparing stability among clusters, and (3) for estimating the optimal number (K) of clusters. However, the sensitivity and specificity of CC have not been systemically studied. To assess its performance, we investigated the most common implementations of CC; and compared CC with other popular methods that also focus on cluster stability and estimation of K. We evaluated these methods using simulated datasets with either known structure or known absence of structure. Our results showed that (1) CC was able to divide randomly generated unimodal data into pre-specified numbers of clusters, and was able to show apparent stability of these chance partitions of known cluster-less data; (2) for data with known structure, the proportion of ambiguously clustered (PAC) pairs infers the known number of clusters more reliably than several commonly used K estimating methods; and (3) validation of the optimal K by choosing the most discriminant genes from the discovery cohort and applying them in an independent cohort often exaggerates the confidence in K due to inherent gene-gene correlations among the selected genes. While these results do not yet prove that any of the published studies using CC has generated false positive findings, they show that datasets with subtle or no structure are fully capable of producing strong evidence of consensus clustering. We therefore recommend caution is using CC in class discovery and validation.

10.1038/srep06207

biorxiv

10.1101/002642

A reassessment of consensus clustering for class discovery

Yasin Şenbabaoğlu;George Michailidis;Jun Z Li;

Jun Z Li

University of Michigan Ann Arbor

2014-03-11

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/03/11/002642.source.xml

Consensus clustering (CC) is an unsupervised class discovery method widely used to study sample heterogeneity in high-dimensional datasets. It calculates \"consensus rate\" between any two samples as how frequently they are grouped together in repeated clustering runs under a certain degree of random perturbation. The pairwise consensus rates form a between-sample similarity matrix, which has been used (1) as a visual proof that clusters exist, (2) for comparing stability among clusters, and (3) for estimating the optimal number (K) of clusters. However, the sensitivity and specificity of CC have not been systemically studied. To assess its performance, we investigated the most common implementations of CC; and compared CC with other popular methods that also focus on cluster stability and estimation of K. We evaluated these methods using simulated datasets with either known structure or known absence of structure. Our results showed that (1) CC was able to divide randomly generated unimodal data into pre-specified numbers of clusters, and was able to show apparent stability of these chance partitions of known cluster-less data; (2) for data with known structure, the proportion of ambiguously clustered (PAC) pairs infers the known number of clusters more reliably than several commonly used K estimating methods; and (3) validation of the optimal K by choosing the most discriminant genes from the discovery cohort and applying them in an independent cohort often exaggerates the confidence in K due to inherent gene-gene correlations among the selected genes. While these results do not yet prove that any of the published studies using CC has generated false positive findings, they show that datasets with subtle or no structure are fully capable of producing strong evidence of consensus clustering. We therefore recommend caution is using CC in class discovery and validation.

10.1038/srep06207

biorxiv

10.1101/002675

Non-specificity of Pitstop 2 in clathrin-mediated endocytosis

Anna K Willox;Yasmina M.E. Sahraoui;Stephen J Royle;

Stephen J Royle

University of Warwick

2014-02-13

New Results

cc_by

Cell Biology

https://www.biorxiv.org/content/early/2014/02/13/002675.source.xml

Small molecule inhibitors of clathrin-mediated endocytosis are highly desired for the dissection of membrane trafficking pathways in the lab and for potential use as anti-infectives in the clinic. One inhibition strategy is to prevent clathrin from contacting adaptor proteins so that clathrin-mediated endocytosis cannot occur. \"Pitstop\" compounds have been developed which block only one of the four functional interaction sites on the N-terminal domain of clathrin heavy chain. Despite this limitation, Pitstop 2 causes profound inhibition of clathrin-mediated endocytosis. In this study, we probed for non-specific activity of Pitstop 2 by examining its action in cells expressing clathrin heavy chain harbouring mutations in the N-terminal domain interaction sites. We conclude that the inhibition observed with this compound is due to non-specificity, i.e. it causes inhibition away from its proposed mode of action. We recommend that these compounds be used with caution in cells and that they should not be used to conclude anything of the function of clathrins N-terminal domain.

10.1242/bio.20147955

biorxiv

10.1101/002675

Non-specificity of Pitstop 2 in clathrin-mediated endocytosis

Anna K Willox;Yasmina M.E. Sahraoui;Stephen J Royle;

Stephen J Royle

University of Warwick

2014-04-15

New Results

cc_by

Cell Biology

https://www.biorxiv.org/content/early/2014/04/15/002675.source.xml

Small molecule inhibitors of clathrin-mediated endocytosis are highly desired for the dissection of membrane trafficking pathways in the lab and for potential use as anti-infectives in the clinic. One inhibition strategy is to prevent clathrin from contacting adaptor proteins so that clathrin-mediated endocytosis cannot occur. \"Pitstop\" compounds have been developed which block only one of the four functional interaction sites on the N-terminal domain of clathrin heavy chain. Despite this limitation, Pitstop 2 causes profound inhibition of clathrin-mediated endocytosis. In this study, we probed for non-specific activity of Pitstop 2 by examining its action in cells expressing clathrin heavy chain harbouring mutations in the N-terminal domain interaction sites. We conclude that the inhibition observed with this compound is due to non-specificity, i.e. it causes inhibition away from its proposed mode of action. We recommend that these compounds be used with caution in cells and that they should not be used to conclude anything of the function of clathrins N-terminal domain.

10.1242/bio.20147955

biorxiv

10.1101/002626

Production of systemically circulating Hedgehog by the intestine couples nutrition to growth and development

Jonathan Rodenfels;Oksana Lavrynenko;Sophie Ayciriex;Julio L Sampaio;Maria Carvalho;Andrej Shevchenko;Suzanne Eaton;

Suzanne Eaton

Max-Planck-Institute for Cell Biology and Genetics

2014-02-14

New Results

cc_no

Developmental Biology

https://www.biorxiv.org/content/early/2014/02/14/002626.source.xml

In Drosophila larvae, growth and developmental timing are regulated by nutrition in a tightly coordinated fashion. The networks that couple these processes are far from understood. Here, we show that the intestine responds to nutrient availability by regulating production of a circulating lipoprotein associated form of the signaling protein Hedgehog (Hh). Levels of circulating Hh tune the rates of growth and developmental timing in a coordinated fashion. Circulating Hh signals to the fat body to control larval growth. It regulates developmental timing by controlling ecdysteroid production in the prothoracic gland. Circulating Hh is especially important during starvation, when it is also required for mobilization of fat body triacylglycerol (TAG) stores. Thus, we demonstrate that Hh, previously known only for its local morphogenetic functions, also acts as a lipoprotein-associated endocrine hormone, coordinating the response of multiple tissues to nutrient availability.

10.1101/gad.249763.114

biorxiv

10.1101/002626

Production of systemically circulating Hedgehog by the intestine couples nutrition to growth and development

Jonathan Rodenfels;Oksana Lavrynenko;Sophie Ayciriex;Julio L Sampaio;Maria Carvalho;Andrej Shevchenko;Suzanne Eaton;

Suzanne Eaton

Max-Planck-Institute for Cell Biology and Genetics

2014-07-29

New Results

cc_no

Developmental Biology

https://www.biorxiv.org/content/early/2014/07/29/002626.source.xml

In Drosophila larvae, growth and developmental timing are regulated by nutrition in a tightly coordinated fashion. The networks that couple these processes are far from understood. Here, we show that the intestine responds to nutrient availability by regulating production of a circulating lipoprotein associated form of the signaling protein Hedgehog (Hh). Levels of circulating Hh tune the rates of growth and developmental timing in a coordinated fashion. Circulating Hh signals to the fat body to control larval growth. It regulates developmental timing by controlling ecdysteroid production in the prothoracic gland. Circulating Hh is especially important during starvation, when it is also required for mobilization of fat body triacylglycerol (TAG) stores. Thus, we demonstrate that Hh, previously known only for its local morphogenetic functions, also acts as a lipoprotein-associated endocrine hormone, coordinating the response of multiple tissues to nutrient availability.

10.1101/gad.249763.114

biorxiv

10.1101/002626

Production of systemically circulating Hedgehog by the intestine couples nutrition to growth and development

Jonathan Rodenfels;Oksana Lavrynenko;Sophie Ayciriex;Julio L Sampaio;Maria Carvalho;Andrej Shevchenko;Suzanne Eaton;

Suzanne Eaton

Max-Planck-Institute for Cell Biology and Genetics

2014-11-03

New Results

cc_no

Developmental Biology

https://www.biorxiv.org/content/early/2014/11/03/002626.source.xml

In Drosophila larvae, growth and developmental timing are regulated by nutrition in a tightly coordinated fashion. The networks that couple these processes are far from understood. Here, we show that the intestine responds to nutrient availability by regulating production of a circulating lipoprotein associated form of the signaling protein Hedgehog (Hh). Levels of circulating Hh tune the rates of growth and developmental timing in a coordinated fashion. Circulating Hh signals to the fat body to control larval growth. It regulates developmental timing by controlling ecdysteroid production in the prothoracic gland. Circulating Hh is especially important during starvation, when it is also required for mobilization of fat body triacylglycerol (TAG) stores. Thus, we demonstrate that Hh, previously known only for its local morphogenetic functions, also acts as a lipoprotein-associated endocrine hormone, coordinating the response of multiple tissues to nutrient availability.

10.1101/gad.249763.114

biorxiv

10.1101/002634

mangal - making ecological network analysis simple

Timothée E Poisot;Benjamin Baiser;Jennifer A Dunne;Sonia Kéfi;Francois Massol;Nicolas Mouquet;Tamara N Romanuk;Daniel B Stouffer;Spencer A Wood;Dominique Gravel;

Timothée E Poisot

Université du Québec à Rimouski

2014-02-12

New Results

cc_by

Ecology

https://www.biorxiv.org/content/early/2014/02/12/002634.source.xml

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package (rmangal) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

10.1111/ecog.00976

biorxiv

10.1101/002634

mangal - making ecological network analysis simple

Timothée E Poisot;Benjamin Baiser;Jennifer A Dunne;Sonia Kéfi;Francois Massol;Nicolas Mouquet;Tamara N Romanuk;Daniel B Stouffer;Spencer A Wood;Dominique Gravel;

Timothée E Poisot

Université du Québec à Rimouski

2014-09-30

New Results

cc_by

Ecology

https://www.biorxiv.org/content/early/2014/09/30/002634.source.xml

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package (rmangal) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

10.1111/ecog.00976

biorxiv

10.1101/002634

mangal - making ecological network analysis simple

Timothée E Poisot;Benjamin Baiser;Jennifer A Dunne;Sonia Kéfi;Francois Massol;Nicolas Mouquet;Tamara N Romanuk;Daniel B Stouffer;Spencer A Wood;Dominique Gravel;

Timothée E Poisot

Université du Québec à Rimouski

2015-02-24

New Results

cc_by

Ecology

https://www.biorxiv.org/content/early/2015/02/24/002634.source.xml

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package (rmangal) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

10.1111/ecog.00976

biorxiv

10.1101/002683

Evolutionary rates for multivariate traits: the role of selection and genetic variation

William Pitchers;Jason B. Wolf;Tom Tregenza;John Hunt;Ian Dworkin;

Ian Dworkin

Michigan State University

2014-02-14

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/14/002683.source.xml

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders equation [Formula], which predicts evolutionary change for a suite of phenotypic traits [Formula] as a product of directional selection acting on them ({beta}) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and {beta} to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are in part due to genetic architecture. We find evidence some evidence that sexually selected traits exhibit faster rates of evolution compared to life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

10.1098/rstb.2013.0252

biorxiv

10.1101/002683

Evolutionary rates for multivariate traits: the role of selection and genetic variation

William Pitchers;Jason B. Wolf;Tom Tregenza;John Hunt;Ian Dworkin;

Ian Dworkin

Michigan State University

2014-02-14

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/14/002683.source.xml

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders equation [Formula], which predicts evolutionary change for a suite of phenotypic traits [Formula] as a product of directional selection acting on them ({beta}) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and {beta} to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are in part due to genetic architecture. We find evidence some evidence that sexually selected traits exhibit faster rates of evolution compared to life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

10.1098/rstb.2013.0252

biorxiv

10.1101/002683

Evolutionary rates for multivariate traits: the role of selection and genetic variation

William Pitchers;Jason B. Wolf;Tom Tregenza;John Hunt;Ian Dworkin;

Ian Dworkin

Michigan State University

2014-05-05

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/05/05/002683.source.xml

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders equation [Formula], which predicts evolutionary change for a suite of phenotypic traits [Formula] as a product of directional selection acting on them ({beta}) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and {beta} to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are in part due to genetic architecture. We find evidence some evidence that sexually selected traits exhibit faster rates of evolution compared to life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

10.1098/rstb.2013.0252

biorxiv

10.1101/002709

Differential gene expression and alternative splicing in insect immune specificity

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Eamonn Mallon

University of Leicester

2014-02-14

New Results

cc_by_nc

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/14/002709.source.xml

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

10.1186/1471-2164-15-1031

biorxiv

10.1101/002709

Differential gene expression and alternative splicing in insect immune specificity

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Eamonn Mallon

University of Leicester

2014-02-15

New Results

cc_by_nc

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/15/002709.source.xml

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

10.1186/1471-2164-15-1031

biorxiv

10.1101/002709

Differential gene expression and alternative splicing in insect immune specificity

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Eamonn Mallon

University of Leicester

2014-03-12

New Results

cc_by_nc

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/03/12/002709.source.xml

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

10.1186/1471-2164-15-1031

biorxiv

10.1101/002709

Differential gene expression and alternative splicing in insect immune specificity

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Eamonn Mallon

University of Leicester

2014-04-30

New Results

cc_by_nc

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/04/30/002709.source.xml

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

10.1186/1471-2164-15-1031

biorxiv

10.1101/002709

Differential gene expression and alternative splicing in insect immune specificity

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Eamonn Mallon

University of Leicester

2014-06-30

New Results

cc_by_nc

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/06/30/002709.source.xml

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

10.1186/1471-2164-15-1031

biorxiv

10.1101/002600

Cell specific eQTL analysis without sorting cells

Harm-Jan Westra;Danny Arends;Tõnu Esko;Marjolein J. Peters;Claudia Schurmann;Katharina Schramm;Johannes Kettunen;Hanieh Yaghootkar;Benjamin Fairfax;Anand Kumar Andiappan;Yang Li;Jingyuan Fu;Juha Karjalainen;Mathieu Platteel;Marijn Visschedijk;Rinse Weersma;Silva Kasela;Lili Milani;Liina Tserel;Pärt Peterson;Eva Reinmaa;Albert Hofman;André G. Uitterlinden;Fernando Rivadeneira;Georg Homuth;Astrid Petersmann;Roberto Lorbeer;Holger Prokisch;Thomas Meitinger;Christian Herder;Michael Roden;Harald Grallert;Samuli Ripatti;Markus Perola;Adrew R. Wood;David Melzer;Luigi Ferrucci;Andrew B. Singleton;Dena

Lude Franke

2014-02-12

New Results

cc_by_nc_nd

Genetics

https://www.biorxiv.org/content/early/2014/02/12/002600.source.xml

Expression quantitative trait locus (eQTL) mapping on tissue, organ or whole organism data can detect associations that are generic across cell types. We describe a new method to focus upon specific cell types without first needing to sort cells. We applied the method to whole blood data from 5,683 samples and demonstrate that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils.

10.1371/journal.pgen.1005223

biorxiv

10.1101/002667

The immunologic V-gene repertoire in mammals

David N Olivieri;Bernardo von Haeften;Christian Sánchez-Espinel;Francisco Gambón-Deza;

David N Olivieri

Universidad de Vigo; School of Computer Science (Spain)

2014-02-13

New Results

cc_no

Immunology

https://www.biorxiv.org/content/early/2014/02/13/002667.source.xml

From recent whole genome shotgun data of 48 mammalian species, we have used our software VgenExtractor to obtain the functional V-gene sequence repertoire in order to conduct comparative phylogenetic studies. These studies reveal a large variation in the number of V-genes across mammalian species, ranging from a mere 36 V-genes in dolphins to nearly 600 V-genes in rats. Monotremes and marsupials are the only mammals possessing an additional locus, the TRMV, apart from the seven common loci found in mammals. Also, we show evidence for the loss of the light chain loci, specifically the V{kappa} chain in one microbat, and the V{lambda} chain in one rodent species. Finally, we suggest different features related to the evolution of immunoglobulin and T cell receptor loci, where frequent sequence duplications are seen in the former, while preserved and undiversified lineages are observed in the latter. All the V-gene sequences described in this study are available in the public database repository vgenerepertoire.org.

biorxiv

10.1101/002618

Genomic V-gene repertoire in reptiles

David N Olivieri;Bernardo von Haeften;Christian Sánchez-Espinel;Jose Faro;Francisco Gambón-Deza;

David N Olivieri

Universidad de Vigo; School of Computer Science (Spain)

2014-02-12

New Results

cc_no

Immunology

https://www.biorxiv.org/content/early/2014/02/12/002618.source.xml

Reptiles and mammals diverged over 300 million years ago, creating two parallel evolutionary lineages amongst terrestrial vertebrates. In reptiles, two main evolutionary lines emerged, one gave rise to Squamata, while the other gave rise to Testudines, Crocodylia and birds. In this study, we determined the genomic variable (V)-gene repertoire in reptiles corresponding to the three main immunoglobulin (Ig) loci and the four main T-cell receptor (TCR) loci. We show that squamata lack the TCR{gamma} /{delta} genes and snakes lack the V{kappa} genes. In representative species of testudines and crocodiles, the seven major Ig and TCR loci are maintained. As in mammals, genes of the Ig loci can be grouped into well-defined clans through a multi-species phylogenetic analysis. We show that the reptile VH and V{lambda} genes are distributed amongst the established mammalian clans, while their V{kappa} genes are found within a single clan, nearly exclusive from the mammalian sequences. The reptile and mammal V-genes of the TRA locus cluster into six common evolutionary clans. In contrast, the reptile V-genes from the TRB locus cluster into three clans, which have few mammalian members. In this locus, the V-gene sequences from mammals appear to have undergone different evolutionary diversification processes that occurred outside these shared reptile clans.

10.1007/s00251-014-0784-3

biorxiv

10.1101/002691

Neuroanatomical diversity of corpus callosum and brain volume in the Autism Brain Imaging Data Exchange (Abide) project

Aline Lefebvre;Anita Beggiato;Thomas Bourgeron;Roberto Toro;

Roberto Toro

Institut Pasteur

2014-02-14

Contradictory Results

cc_by_nc_nd

Neuroscience

https://www.biorxiv.org/content/early/2014/02/14/002691.source.xml

The corpus callosum - the main pathway for long-distance inter-hemispheric integration in the human brain - has been frequently reported to be smaller among autistic patients compared with non-autistic controls. We conducted a meta-analysis of the literature which suggested a statistically significant difference. However, the studies included were heavily underpowered: on average only 20% power to detect differences of 0.3 standard deviations, which makes it difficult to establish the reality of such a difference. We therefore studied the size of the corpus callosum among 694 subjects (328 patients, 366 controls) from the Abide cohort. Despite having achieved 99% power to detect statistically significant differences of 0.3 standard deviations, we did not observe any. To better understand the neuroanatomical diversity of the corpus callosum, and the possible reasons for the previous findings, we analysed the relationship between its size, the size of the brain, intracranial volume and intelligence scores. The corpus callosum appeared to scale non-linearly with brain size, with large brains having a proportionally smaller corpus callosum. Additionally, intelligence scores correlated with brain volume among controls but the correlation was significantly weaker among patients. We used simulations to determine to which extent these two effects could lead to artefactual differences in corpus callosum size within populations. We observed that, were there a difference in brain volume between cases and controls, normalising corpus callosum size by brain volume would not eliminate the brain volume effect, but adding brain volume as a covariate in a linear model would. Finally, we observed that because of the weaker correlation of intelligence scores and brain volume among patients, matching populations by intelligence scores could result in a bias towards including more patients with large brain volumes, inducing an artificial difference. Overall, our results highlight the necessity for open data sharing efforts such as Abide to provide a more solid ground for the discovery of neuroimaging biomarkers, within the context of the wide human neuroanatomical diversity.

10.1016/j.biopsych.2015.02.010

biorxiv

10.1101/002691

Neuroanatomical diversity of corpus callosum and brain volume in the Autism Brain Imaging Data Exchange (Abide) project

Aline Lefebvre;Anita Beggiato;Thomas Bourgeron;Roberto Toro;

Roberto Toro

Institut Pasteur

2014-02-15

Contradictory Results

cc_by_nc_nd

Neuroscience

https://www.biorxiv.org/content/early/2014/02/15/002691.source.xml

The corpus callosum - the main pathway for long-distance inter-hemispheric integration in the human brain - has been frequently reported to be smaller among autistic patients compared with non-autistic controls. We conducted a meta-analysis of the literature which suggested a statistically significant difference. However, the studies included were heavily underpowered: on average only 20% power to detect differences of 0.3 standard deviations, which makes it difficult to establish the reality of such a difference. We therefore studied the size of the corpus callosum among 694 subjects (328 patients, 366 controls) from the Abide cohort. Despite having achieved 99% power to detect statistically significant differences of 0.3 standard deviations, we did not observe any. To better understand the neuroanatomical diversity of the corpus callosum, and the possible reasons for the previous findings, we analysed the relationship between its size, the size of the brain, intracranial volume and intelligence scores. The corpus callosum appeared to scale non-linearly with brain size, with large brains having a proportionally smaller corpus callosum. Additionally, intelligence scores correlated with brain volume among controls but the correlation was significantly weaker among patients. We used simulations to determine to which extent these two effects could lead to artefactual differences in corpus callosum size within populations. We observed that, were there a difference in brain volume between cases and controls, normalising corpus callosum size by brain volume would not eliminate the brain volume effect, but adding brain volume as a covariate in a linear model would. Finally, we observed that because of the weaker correlation of intelligence scores and brain volume among patients, matching populations by intelligence scores could result in a bias towards including more patients with large brain volumes, inducing an artificial difference. Overall, our results highlight the necessity for open data sharing efforts such as Abide to provide a more solid ground for the discovery of neuroimaging biomarkers, within the context of the wide human neuroanatomical diversity.

10.1016/j.biopsych.2015.02.010

biorxiv

10.1101/002659

Synthesis and patterning of tunable multiscale materials with engineered cells

Allen Y Chen;Urartu O.S. Seker;Michelle Y Lu;Robert J Citorik;Timothy Lu;

Timothy Lu

Massachusetts Institute of Technology

2014-02-14

New Results

cc_no

Synthetic Biology

https://www.biorxiv.org/content/early/2014/02/14/002659.source.xml

A major challenge in materials science is to create self-assembling, functional, and environmentally responsive materials which can be patterned across multiple length scales. Natural biological systems, such as biofilms, shells, and skeletal tissues, implement dynamic regulatory programs to assemble complex multiscale materials comprised of living and non-living components1-9. Such systems can provide inspiration for the design of heterogeneous functional systems which integrate biotic and abiotic materials via hierarchical self-assembly. Here, we present a synthetic-biology platform for synthesizing and patterning self-assembled functional amyloid materials across multiple length scales with bacterial biofilms. We engineered Escherichia coli curli amyloid production under the tight control of synthetic regulatory circuits and interfaced amyloids with inorganic materials to create a biofilm-based electrical switch whose conductance can be selectively toggled by specific environmental signals. Furthermore, we externally tuned synthetic biofilms to build nanoscale amyloid biomaterials with different structure and composition through the controlled expression of their constituent subunits with artificial gene circuits. By using synthetic cell-cell communication, our engineered biofilms can also autonomously manufacture dynamic materials whose structure and composition change with time. In addition, we show that by combining subunit-level protein engineering, controlled genetic expression of self-assembling subunit proteins, and macroscale spatial gradients, synthetic biofilms can pattern protein biomaterials across multiple length scales. This work lays a foundation for synthesizing, patterning, and controlling composite materials with engineered biological systems. We envision that this approach can be expanded to other cellular and biomaterials contexts for the construction of self-organizing, environmentally responsive, and tunable multiscale composite materials with heterogeneous functionalities.

10.1038/nmat3912

biorxiv

10.1101/002659

Synthesis and patterning of tunable multiscale materials with engineered cells

Allen Y Chen;Urartu O.S. Seker;Michelle Y Lu;Robert J Citorik;Timothy Lu;

Timothy Lu

Massachusetts Institute of Technology

2014-03-27

New Results

cc_no

Synthetic Biology

https://www.biorxiv.org/content/early/2014/03/27/002659.source.xml

A major challenge in materials science is to create self-assembling, functional, and environmentally responsive materials which can be patterned across multiple length scales. Natural biological systems, such as biofilms, shells, and skeletal tissues, implement dynamic regulatory programs to assemble complex multiscale materials comprised of living and non-living components1-9. Such systems can provide inspiration for the design of heterogeneous functional systems which integrate biotic and abiotic materials via hierarchical self-assembly. Here, we present a synthetic-biology platform for synthesizing and patterning self-assembled functional amyloid materials across multiple length scales with bacterial biofilms. We engineered Escherichia coli curli amyloid production under the tight control of synthetic regulatory circuits and interfaced amyloids with inorganic materials to create a biofilm-based electrical switch whose conductance can be selectively toggled by specific environmental signals. Furthermore, we externally tuned synthetic biofilms to build nanoscale amyloid biomaterials with different structure and composition through the controlled expression of their constituent subunits with artificial gene circuits. By using synthetic cell-cell communication, our engineered biofilms can also autonomously manufacture dynamic materials whose structure and composition change with time. In addition, we show that by combining subunit-level protein engineering, controlled genetic expression of self-assembling subunit proteins, and macroscale spatial gradients, synthetic biofilms can pattern protein biomaterials across multiple length scales. This work lays a foundation for synthesizing, patterning, and controlling composite materials with engineered biological systems. We envision that this approach can be expanded to other cellular and biomaterials contexts for the construction of self-organizing, environmentally responsive, and tunable multiscale composite materials with heterogeneous functionalities.

10.1038/nmat3912

biorxiv

10.1101/002717

Immune stimulation reduces sleep and memory ability in Drosophila melanogaster

Eamonn Mallon;Akram Alghamdi;Robert Holdbrook;Ezio Rosato;

Eamonn Mallon

University of Leicester

2014-02-14

New Results

cc_by_nc

Zoology

https://www.biorxiv.org/content/early/2014/02/14/002717.source.xml

Psychoneuroimmunology studies the increasing number of connections between neurobiology and immunology. We establish Drosophila melanogaster as a tractable model in this field by demonstrating the effects of the immune response on two fundamental behaviours: sleep and memory ability.\n\nWe used the Geneswitch system to upregulate peptidoglycan receptor protein (PGRP) expression, thereby stimulating the immune system in the absence of infection. Geneswitch was activated by feeding the steroid RU486, to the flies. Importantly, by stimulating the immune system of adult flies in the absence of infection we have avoided the added complications of developmental and disease effects that have confounded other studies. We used an aversive classical conditioning paradigm to quantify memory and measures of activity to infer sleep.\n\nImmune stimulated flies exhibited reduced levels of sleep, which could not be explained by a generalised increase in waking activity. The effects on sleep were more pronounced for day compared to night sleep. Immune stimulated flies also showed a reduction in memory abilities.\n\nThese are important results as they establish Drosophila as a model for immune-neural interactions and provide a possible role for sleep in the interplay between the immune response and memory.

10.7717/peerj.434

biorxiv

10.1101/002717

Immune stimulation reduces sleep and memory ability in Drosophila melanogaster

Eamonn Mallon;Akram Alghamdi;Robert Holdbrook;Ezio Rosato;

Eamonn Mallon

University of Leicester

2014-03-12

New Results

cc_by_nc

Zoology

https://www.biorxiv.org/content/early/2014/03/12/002717.source.xml

Psychoneuroimmunology studies the increasing number of connections between neurobiology and immunology. We establish Drosophila melanogaster as a tractable model in this field by demonstrating the effects of the immune response on two fundamental behaviours: sleep and memory ability.\n\nWe used the Geneswitch system to upregulate peptidoglycan receptor protein (PGRP) expression, thereby stimulating the immune system in the absence of infection. Geneswitch was activated by feeding the steroid RU486, to the flies. Importantly, by stimulating the immune system of adult flies in the absence of infection we have avoided the added complications of developmental and disease effects that have confounded other studies. We used an aversive classical conditioning paradigm to quantify memory and measures of activity to infer sleep.\n\nImmune stimulated flies exhibited reduced levels of sleep, which could not be explained by a generalised increase in waking activity. The effects on sleep were more pronounced for day compared to night sleep. Immune stimulated flies also showed a reduction in memory abilities.\n\nThese are important results as they establish Drosophila as a model for immune-neural interactions and provide a possible role for sleep in the interplay between the immune response and memory.

10.7717/peerj.434

biorxiv

10.1101/002782

Large-scale non-targeted metabolomic profiling in three human population-based studies

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Erik Ingelsson

Uppsala University

2014-02-17

New Results

cc_by_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/17/002782.source.xml

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

biorxiv

10.1101/002782

Large-scale non-targeted metabolomic profiling in three human population-based studies

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Erik Ingelsson

Uppsala University

2014-02-19

New Results

cc_by_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/19/002782.source.xml

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

biorxiv

10.1101/002782

Large-scale non-targeted metabolomic profiling in three human population-based studies

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Erik Ingelsson

Uppsala University

2015-05-28

New Results

cc_by_nd

Bioinformatics

https://www.biorxiv.org/content/early/2015/05/28/002782.source.xml

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

biorxiv

10.1101/002782

Large-scale non-targeted metabolomic profiling in three human population-based studies

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Erik Ingelsson

Uppsala University

2015-11-12

New Results

cc_by_nd

Bioinformatics

https://www.biorxiv.org/content/early/2015/11/12/002782.source.xml

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

biorxiv

10.1101/002766

A Novel Approach for Multi-Domain and Multi-Gene Family Identification Provides Insights into Evolutionary Dynamics of Disease Resistance Genes in Core Eudicot Plants

Johannes A. Hofberger;Beifei Zhou;Haibao Tang;Jonathan DG Jones;M. Eric Schranz;

M. Eric Schranz

Wageningen University & Research Center

2014-02-17

New Results

cc_by

Genomics

https://www.biorxiv.org/content/early/2014/02/17/002766.source.xml

Recent advances in DNA sequencing techniques resulted in more than forty sequenced plant genomes representing a diverse set of taxa of agricultural, energy, medicinal and ecological importance. However, gene family curation is often only inferred from DNA sequence homology and lacks insights into evolutionary processes contributing to gene family dynamics. In a comparative genomics framework, we integrated multiple lines of evidence provided by gene synteny, sequence homology and protein-based Hidden Markov Modelling to extract homologous super-clusters composed of multi-domain resistance (R)-proteins of the NB-LRR type (for NUCLEOTIDE BINDING/LEUCINE-RICH REPEATS), that are involved in plant innate immunity. To assess the diversity of R-proteins within and between species, we screened twelve eudicot plant genomes including six major crops and found a total of 2,363 NB-LRR genes. Our curated R-proteins set shows a 50% average for tandem duplicates and a 22% fraction of gene copies retained from ancient polyploidy events (ohnologs). We provide evidence for strong positive selection acting on all identified genes and show significant differences in molecular evolution rates (Ka/Ks-ratio) among tandem- (mean = 1.59), ohnolog (mean = 1.36) and singleton (mean = 1.22) R-gene duplicates. To foster the process of gene-edited plant breeding, we report species-specific presence/absence of all 140 NB-LRR genes present in the model plant Arabidopsis and describe four distinct clusters of NB-LRR \"gatekeeper\" loci sharing syntelogs across all analyzed genomes. In summary, we designed and implemented an easy-to-follow computational framework for super-gene family identification, and provide the most curated set of NB-LRR genes whose genetic versatility among twelve lineages can underpin crop improvement.

10.1186/1471-2164-15-966

biorxiv

10.1101/002741

Fluorescent sensors for activity and regulation of the nitrate transceptor CHL1/NRT1.1 and oligopeptide transporters

Cheng Hsun Ho;Wolf B. Frommer;

Wolf B. Frommer

Carnegie Institution for Science

2014-02-18

New Results

cc_by_nc

Cell Biology

https://www.biorxiv.org/content/early/2014/02/18/002741.source.xml

To monitor nitrate and peptide transport activity in vivo, we converted the dual-affinity nitrate transceptor CHL1/NRT1.1/NPF6.3 and four related oligopeptide transporters PTR1, 2, 4 and 5 into fluorescence activity sensors (NiTrac1, PepTrac). Substrate addition to yeast expressing transporter fusions with yellow fluorescent protein and mCerulean triggered substrate-dependent donor quenching or resonance energy transfer. Fluorescence changes were nitrate/peptide-specific, respectively. Like CHL1, NiTrac1 had biphasic kinetics. Mutation of T101A eliminated high-affinity transport and blocked the fluorescence response to low nitrate. NiTrac was used for characterizing side chains considered important for substrate interaction, proton coupling, and regulation. We observed a striking correlation between transport activity and sensor output. Coexpression of NiTrac with known calcineurin-like proteins (CBL1, 9; CIPK23) and candidates identified in an interactome screen (CBL1, KT2, WNKinase 8) blocked NiTrac1 responses, demonstrating the suitability for in vivo analysis of activity and regulation. The new technology is applicable in plant and medical research.

10.7554/eLife.01917.001

biorxiv

10.1101/002790

ESCRT-0 is not required for ectopic Notch activation and tumor suppression in Drosophila

Emiliana Tognon;Nadine Wollscheid;Katia Cortese;Carlo Tacchetti;thomas vaccari;

thomas vaccari

IFOM, Istituto FIRC di Oncologia Molecolare

2014-02-18

New Results

cc_by_nc_nd

Developmental Biology

https://www.biorxiv.org/content/early/2014/02/18/002790.source.xml

Multivesicular endosome (MVE) sorting depends on proteins of the Endosomal Sorting Complex Required for Transport (ESCRT) family. These are organized in four complexes (ESCRT-0, -I, -II, -III) that act in a sequential fashion to deliver ubiquitylated cargoes into the internal luminal vesicles (ILVs) of the MVE. Drosophila genes encoding ESCRT-I, -II, -III components function in sorting signaling receptors, including Notch and the JAK/STAT signaling receptor Domeless. Loss of ESCRT-I, -II, -III in Drosophila epithelia causes altered signaling and cell polarity, suggesting that ESCRTs genes are tumor suppressors. However, the nature of the tumor suppressive function of ESCRTs, and whether tumor suppression is linked to receptor sorting is unclear. Unexpectedly, a null mutant in Hrs, encoding one of components of the ESCRT-0 complex, which acts upstream of ESCRT-I, -II, -III in MVE sorting is dispensable for tumor suppression. Here, we report that two Drosophila epithelia lacking activity of Stam, the other known components of the ESCRT-0 complex, or of both Hrs and Stam fail to degrade signaling receptors. However, mutant tissue surprisingly maintains normal apico-basal polarity and proliferation control and does not display ectopic Notch signaling activation, unlike cells that lack ESCRT-I, -II, -III activity. Overall, our in vivo data indicate that the ESCRT-0 complex plays no crucial role in regulation of tumor suppression, and suggest re-evaluation of the relationship of signaling modulation in endosomes and tumorigenesis.

10.1371/journal.pone.0093987

biorxiv

10.1101/002808

Migration and interaction in a contact zone: mtDNA variation among Bantu-speakers in southern Africa

Chiara Barbieri;Mário Vicente;Sandra Oliveira;Koen Bostoen;Jorge Rocha;Mark Stoneking;Brigitte Pakendorf;

Chiara Barbieri

Department of Evolutionary Genetics, MPI for Evolutionary Anthropology, Leipzig, Germany, 04103

2014-02-18

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/18/002808.source.xml

Bantu speech communities expanded over large parts of sub-Saharan Africa within the last 4000-5000 years, reaching different parts of southern Africa 1200-2000 years ago. The Bantu languages subdivide in several major branches, with languages belonging to the Eastern and Western Bantu branches spreading over large parts of Central, Eastern, and Southern Africa. There is still debate whether this linguistic divide is correlated with a genetic distinction between Eastern and Western Bantu speakers. During their expansion, Bantu speakers would have come into contact with diverse local populations, such as the Khoisan hunter-gatherers and pastoralists of southern Africa, with whom they may have intermarried. In this study, we analyze complete mtDNA genome sequences from over 900 Bantu-speaking individuals from Angola, Zambia, Namibia, and Botswana to investigate the demographic processes at play during the last stages of the Bantu expansion. Our results show that most of these Bantu-speaking populations are genetically very homogenous, with no genetic division between speakers of Eastern and Western Bantu languages. Most of the mtDNA diversity in our dataset is due to different degrees of admixture with autochthonous populations. Only the pastoralist Himba and Herero stand out due to high frequencies of particular L3f and L3d lineages; the latter are also found in the neighboring Damara, who speak a Khoisan language and were foragers and small-stock herders. In contrast, the close cultural and linguistic relatives of the Herero and Himba, the Kuvale, are genetically similar to other Bantu-speakers. Nevertheless, as demonstrated by resampling tests, the genetic divergence of Herero, Himba, and Kuvale is compatible with a common shared ancestry with high levels of drift and differential female admixture with local pre-Bantu populations.

10.1371/journal.pone.0099117

biorxiv

10.1101/002816

Widespread signals of convergent adaptation to high altitude in Asia and America

Matthieu Foll;Oscar E. Gaggiotti;Josephine T. Daub;Alexandra Vatsiou;Laurent Excoffier;

Matthieu Foll

École Polytechnique Fédérale de Lausanne (EPFL)

2014-02-19

New Results

cc_by_nc_nd

Genetics

https://www.biorxiv.org/content/early/2014/02/19/002816.source.xml

Living at high-altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can be also due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

10.1016/j.ajhg.2014.09.002

biorxiv

10.1101/002816

Widespread signals of convergent adaptation to high altitude in Asia and America

Matthieu Foll;Oscar E. Gaggiotti;Josephine T. Daub;Alexandra Vatsiou;Laurent Excoffier;

Matthieu Foll

École Polytechnique Fédérale de Lausanne (EPFL)

2014-02-19

New Results

cc_by_nc_nd

Genetics

https://www.biorxiv.org/content/early/2014/02/19/002816.source.xml

Living at high-altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can be also due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

10.1016/j.ajhg.2014.09.002

biorxiv

10.1101/002816

Widespread signals of convergent adaptation to high altitude in Asia and America

Matthieu Foll;Oscar E. Gaggiotti;Josephine T. Daub;Alexandra Vatsiou;Laurent Excoffier;

Matthieu Foll

École Polytechnique Fédérale de Lausanne (EPFL)

2014-09-26

New Results

cc_by_nc_nd

Genetics

https://www.biorxiv.org/content/early/2014/09/26/002816.source.xml

Living at high-altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can be also due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

10.1016/j.ajhg.2014.09.002

biorxiv

10.1101/002881

A GWAS platform built on iPlant cyber-infrastructure

Liya Wang;Doreen Ware;Carol Lushbough;Nirav Merchant;Lincoln Stein;

Liya Wang

Cold Spring Harbor Labs

2014-02-20

Confirmatory Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/20/002881.source.xml

We demonstrated a flexible Genome-Wide Association Study (GWAS) platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large scale study of both genotype and phenotype data on clusters. End users can add their own analysis tools, and create customized analysis workflows through the graphical user interfaces in both iPlant Discovery Environment and BioExtract server.

10.1002/cpe.3236

biorxiv

10.1101/002824

HTSeq - A Python framework to work with high-throughput sequencing data

Simon Anders;Paul Theodor Pyl;Wolfgang Huber;

Simon Anders

European Molecular Biology Laboratory

2014-02-20

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/20/002824.source.xml

MotivationA large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed.\n\nResultsWe present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.\n\nAvailabilityHTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index https://pypi.python.org/pypi/HTSeq.\n\[email protected]

10.1093/bioinformatics/btu638

biorxiv

10.1101/002824

HTSeq - A Python framework to work with high-throughput sequencing data

Simon Anders;Paul Theodor Pyl;Wolfgang Huber;

Simon Anders

European Molecular Biology Laboratory

2014-08-19

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/08/19/002824.source.xml

MotivationA large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed.\n\nResultsWe present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.\n\nAvailabilityHTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index https://pypi.python.org/pypi/HTSeq.\n\[email protected]

10.1093/bioinformatics/btu638

biorxiv

10.1101/002832

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael I Love;Wolfgang Huber;Simon Anders;

Simon Anders

European Molecular Biology Laboratory

2014-02-19

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/19/002832.source.xml

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

10.1186/s13059-014-0550-8

biorxiv

10.1101/002832

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael I Love;Wolfgang Huber;Simon Anders;

Simon Anders

European Molecular Biology Laboratory

2014-05-27

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/05/27/002832.source.xml

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

10.1186/s13059-014-0550-8

biorxiv

10.1101/002832

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael I Love;Wolfgang Huber;Simon Anders;

Simon Anders

European Molecular Biology Laboratory

2014-11-17

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/11/17/002832.source.xml

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

10.1186/s13059-014-0550-8

biorxiv

10.1101/002899

An experimentally determined evolutionary model dramatically improves phylogenetic fit

Jesse D Bloom;

Jesse D Bloom

Fred Hutchinson Cancer Research Center

2014-02-20

New Results

cc_by

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/20/002899.source.xml

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

10.1093/molbev/msu173

biorxiv

10.1101/002899

An experimentally determined evolutionary model dramatically improves phylogenetic fit

Jesse D Bloom;

Jesse D Bloom

Fred Hutchinson Cancer Research Center

2014-03-02

New Results

cc_by

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/03/02/002899.source.xml

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

10.1093/molbev/msu173

biorxiv

10.1101/002899

An experimentally determined evolutionary model dramatically improves phylogenetic fit

Jesse D Bloom;

Jesse D Bloom

Fred Hutchinson Cancer Research Center

2014-03-05

New Results

cc_by

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/03/05/002899.source.xml

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

10.1093/molbev/msu173

biorxiv

10.1101/002899

An experimentally determined evolutionary model dramatically improves phylogenetic fit

Jesse D Bloom;

Jesse D Bloom

Fred Hutchinson Cancer Research Center

2014-04-27

New Results

cc_by

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/04/27/002899.source.xml

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

10.1093/molbev/msu173

biorxiv

10.1101/002873

Mapping the structure of drosophilid behavior

Gordon J Berman;Daniel M Choi;William Bialek;Joshua W Shaevitz;

Joshua W Shaevitz

Princeton University

2014-02-20

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/20/002873.source.xml

Most animals possess the ability to actuate a vast diversity of movements, ostensibly constrained only by morphology and physics. In practice, however, a frequent assumption in behavioral science is that most of an animals activities can be described in terms of a small set of stereotyped motifs. Here we introduce a method for mapping the behavioral space of organisms, relying only upon the underlying structure of postural movement data to organize and classify behaviors. We find that six different drosophilid species each perform a mix of non-stereotyped actions and over one hundred hierarchically-organized, stereotyped behaviors. Moreover, we use this approach to compare these species behavioral spaces, systematically identifying subtle behavioral differences between closely-related species.

10.1098/rsif.2014.0672

biorxiv

10.1101/002865

No evidence that natural selection has been less effective at removing deleterious mutations in Europeans than in West Africans

Ron Do;Daniel Balick;Heng Li;Ivan Adzhubei`;Shamil Sunyaev;David Reich;

David Reich

Department of Genetics, Harvard Medical School, Boston, MA 02115

2014-02-20

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/20/002865.source.xml

Non-African populations have experienced major bottlenecks in the time since their split from West Africans, which has led to the hypothesis that natural selection to remove weakly deleterious mutations may have been less effective in non-Africans. To directly test this hypothesis, we measure the per-genome accumulation of deleterious mutations across diverse humans. We fail to detect any significant differences, but find that archaic Denisovans accumulated non-synonymous mutations at a higher rate than modern humans, consistent with the longer separation time of modern and archaic humans. We also revisit the empirical patterns that have been interpreted as evidence for less effective removal of deleterious mutations in non-Africans than in West Africans, and show they are not driven by differences in selection after population separation, but by neutral evolution.

10.1038/ng.3186

biorxiv

10.1101/002956

Functional normalization of 450k methylation array data improves replication in large cancer studies

Jean-Philippe Fortin;Aurelie Labbe;Mathieu Lemire;Brent W. Zanke;Thomas J. Hudson;Elana J. Fertig;Celia M.T. Greenwood;Kasper D. Hansen;

Kasper D. Hansen

Johns Hopkins University

2014-02-23

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/23/002956.source.xml

We propose an extension to quantile normalization which removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using datasets from The Cancer Genome Atlas and a large case-control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.

10.1186/s13059-014-0503-2

biorxiv

10.1101/002931

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

Brendan Bulik-Sullivan;Po-Ru Loh;Hilary Finucane;Stephan Ripke;Jian Yang;Schizophrenia Working Group Psychiatric Genomics Consortium;Nick Patterson;Mark J Daly;Alkes L Price;Benjamin M Neale;

Benjamin M Neale

Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital

2014-02-21

New Results

cc_no

Genomics

https://www.biorxiv.org/content/early/2014/02/21/002931.source.xml

Both polygenicity1,2 (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification3, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control4-14. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

10.1038/ng.3211

biorxiv

10.1101/002923

Spatial Information in Large-Scale Neural Recordings

Thaddeus R Cybulski;Joshua I Glaser;Adam H Marblestone;Bradley M Zamft;Edward S Boyden;George M Church;Konrad P Kording;

Thaddeus R Cybulski

Northwestern University

2014-02-21

New Results

cc_no

Neuroscience

https://www.biorxiv.org/content/early/2014/02/21/002923.source.xml

A central issue in neural recording is that of distinguishing the activities of many neurons. Here, we develop a framework, based on Fisher information, to quantify how separable a neurons activity is from the activities of nearby neurons. We (1) apply this framework to model information flow and spatial distinguishability for several electrical and optical neural recording methods, (2) provide analytic expressions for information content, and (3) demonstrate potential applications of the approach. This method generalizes to many recording devices that resolve objects in space and thus may be useful in the design of next-generation scalable neural recording systems.

10.3389/fncom.2014.00172

biorxiv

10.1101/002907

Population diversification in a yeast metabolic program promotes anticipation of environmental shifts

Ophelia S Venturelli;Ignacio Zuleta;Richard M Murray;Hana El-Samad;

Hana El-Samad

University of California San Francisco

2014-02-21

New Results

cc_by_nc_nd

Systems Biology

https://www.biorxiv.org/content/early/2014/02/21/002907.source.xml

Delineating the strategies by which cells contend with combinatorial changing environments is crucial for understanding cellular regulatory organization. When presented with two carbon sources, microorganisms first consume the carbon substrate that supports the highest growth rate (e.g. glucose) and then switch to the secondary carbon source (e.g. galactose), a paradigm known as the Monod model. Sequential sugar utilization has been attributed to transcriptional repression of the secondary metabolic pathway, followed by activation of this pathway upon depletion of the preferred carbon source. In this work, we challenge this notion. Although Saccharomyces cerevisiae cells consume glucose before galactose, we demonstrate that the galactose regulatory pathway is activated in a fraction of the cell population hours before glucose is fully consumed. This early activation reduces the time required for the population to transition between the two metabolic programs and provides a fitness advantage that might be crucial in competitive environments. Importantly, these findings define a new paradigm for the response of microbial populations to combinatorial carbon sources.

10.1371/journal.pbio.1002042

biorxiv

10.1101/002972

Efficient synergistic single-cell genome assembly

Narjes S. Movahedi;Zeinab Taghavi;Mallory Embree;Harish Nagarajan;Karsten Zengler;Hamidreza Chitsaz;

Hamidreza Chitsaz

Wayne State University

2014-02-24

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/24/002972.source.xml

As the vast majority of all microbes are unculturable, single-cell sequencing has become a significant method to gain insight into microbial physiology. Single-cell sequencing methods, currently powered by multiple displacement genome amplification (MDA), have passed important milestones such as finishing and closing the genome of a prokaryote. However, the quality and reliability of genome assemblies from single cells are still unsatisfactory due to uneven coverage depth and the absence of scattered chunks of the genome in the final collection of reads caused by MDA bias. In this work, our new algorithm Hybrid De novo Assembler (HyDA) demonstrates the power of co-assembly of multiple single-cell genomic data sets through significant improvement of the assembly quality in terms of predicted functional elements and length statistics. Co-assemblies contain significantly more base pairs and protein coding genes, cover more subsystems, and consist of longer contigs compared to individual assemblies by the same algorithm as well as state-of-the-art single-cell assemblers SPAdes and IDBA-UD. Hybrid De novo Assembler (HyDA) is also able to avoid chimeric assemblies by detecting and separating shared and exclusive pieces of sequence for input data sets. By replacing one deep single-cell sequencing experiment with a few single-cell sequencing experiments of lower depth, the co-assembly method can hedge against the risk of failure and loss of the sample, without significantly increasing sequencing cost. Application of the single-cell coassembler HyDA to the study of three uncultured members of an alkane-degrading methanogenic community validated the usefulness of the co-assembly concept.

10.3389/fbioe.2016.00042

biorxiv

10.1101/002964

T-lex2: genotyping, frequency estimation and re-annotation of transposable elements using single or pooled next-generation sequencing data

Anna-Sophie Fiston-Lavier;Maite G. Barrón;Dmitri A. Petrov;Josefa González;

Anna-Sophie Fiston-Lavier

Institut des Sciences de l'Evolution-UMR5554 CNRS-Université Montpellier 2

2014-02-24

New Results

cc_by_nc_nd

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/24/002964.source.xml

Transposable elements (TEs) are the most active, diverse and ancient component in a broad range of genomes. As such, a complete understanding of genome function and evolution cannot be achieved without a thorough understanding of TE impact and biology. However, in-depth analyses of TEs still represent a challenge due to the repetitive nature of these genomic entities. In this work, we present a broadly applicable and flexible tool: T-lex2. T-lex2 is the only available software that allows routine,automatic, and accurate genotyping of individual TE insertions and estimation of their population frequencies both using individual strain and pooled next-generation sequencing (NGS) data. Furthermore, T-lex2 also assesses the quality of the calls allowing the identification of miss-annotated TEs and providing the necessary information to re-annotate them. Although we tested the fidelity of T-lex2 using the high quality Drosophila melanogaster genome, the flexible and customizable design of T-lex2 allows running it in any genome and for any type of TE insertion. Overall, T-lex2 represents a significant improvement in our ability to analyze the contribution of TEs to genome function and evolution as well as learning about the biology of TEs. T-lex2 is freely available online at http://petrov.stanford.edu/cgi-bin/Tlex.html.

10.1093/nar/gku1250

biorxiv

10.1101/002964

T-lex2: genotyping, frequency estimation and re-annotation of transposable elements using single or pooled next-generation sequencing data

Anna-Sophie Fiston-Lavier;Maite G. Barrón;Dmitri A. Petrov;Josefa González;

Anna-Sophie Fiston-Lavier

Institut des Sciences de l'Evolution-UMR5554 CNRS-Université Montpellier 2

2014-09-16

New Results

cc_no

Bioinformatics

https://www.biorxiv.org/content/early/2014/09/16/002964.source.xml

Transposable elements (TEs) are the most active, diverse and ancient component in a broad range of genomes. As such, a complete understanding of genome function and evolution cannot be achieved without a thorough understanding of TE impact and biology. However, in-depth analyses of TEs still represent a challenge due to the repetitive nature of these genomic entities. In this work, we present a broadly applicable and flexible tool: T-lex2. T-lex2 is the only available software that allows routine,automatic, and accurate genotyping of individual TE insertions and estimation of their population frequencies both using individual strain and pooled next-generation sequencing (NGS) data. Furthermore, T-lex2 also assesses the quality of the calls allowing the identification of miss-annotated TEs and providing the necessary information to re-annotate them. Although we tested the fidelity of T-lex2 using the high quality Drosophila melanogaster genome, the flexible and customizable design of T-lex2 allows running it in any genome and for any type of TE insertion. Overall, T-lex2 represents a significant improvement in our ability to analyze the contribution of TEs to genome function and evolution as well as learning about the biology of TEs. T-lex2 is freely available online at http://petrov.stanford.edu/cgi-bin/Tlex.html.

10.1093/nar/gku1250

biorxiv

10.1101/002980

Genetic drift suppresses bacterial conjugation in spatially structured populations

Peter D. Freese;Kirill S. Korolev;Jose I Jimenez;Irene A. Chen;

Irene A. Chen

Univ. of California - Santa Barbara

2014-02-24

New Results

cc_by_nc

Biophysics

https://www.biorxiv.org/content/early/2014/02/24/002980.source.xml

Conjugation is the primary mechanism of horizontal gene transfer that spreads antibiotic resistance among bacteria. Although conjugation normally occurs in surface-associated growth (e.g., biofilms), it has been traditionally studied in well-mixed liquid cultures lacking spatial structure, which is known to affect many evolutionary and ecological processes. Here we visualize spatial patterns of gene transfer mediated by F plasmid conjugation in a colony of Escherichia coli growing on solid agar, and we develop a quantitative understanding by spatial extension of traditional mass-action models. We found that spatial structure suppresses conjugation in surface-associated growth because strong genetic drift leads to spatial isolation of donor and recipient cells, restricting conjugation to rare boundaries between donor and recipient strains. These results suggest that ecological strategies, such as enforcement of spatial structure and enhancement of genetic drift, could complement molecular strategies in slowing the spread of antibiotic resistance genes.

10.1016/j.bpj.2014.01.012

biorxiv

10.1101/002998

Extensive translation of small ORFs revealed by polysomal ribo-Seq

Julie L Aspden;Ying Chen Eyre-Walker;Rose J. Phillips;Michele Brocard;Unum Amin;Juan Couso;

Juan Couso

University of Sussex

2014-02-24

New Results

cc_no

Genomics

https://www.biorxiv.org/content/early/2014/02/24/002998.source.xml

Thousands of small Open Reading Frames (smORFs) encoding small peptides of fewer than 100 amino acids exist in our genomes. Examples of functional smORFs have been characterised in a few species but the actual number of translated smORFs, and their molecular, functional and evolutionary features are not known. Here we present a genome-wide assessment of smORF translation by ribosomal profiling of polysomal fractions. This polysomal ribo-Seq suggests that smORFs are translated at the same level and in the same relative numbers (80%) as normal proteins. The smORF peptides appear widely conserved, show activity in cells, and display a putative amino acid signature. These findings reinforce the idea that smORFs are an abundant and fundamental genome component, displaying features usually attributed to canonical proteins, including high translation levels, biological function, amino acid sequence specificity and cross-species conservation.

biorxiv

10.1101/003053

A tug-of-war between driver and passenger mutations in cancer and other adaptive processes

Christopher Dennis McFarland;Leonid A Mirny;Kirill S Korolev;

Leonid A Mirny

Massachusetts Institute of Technology

2014-02-26

New Results

cc_by

Cancer Biology

https://www.biorxiv.org/content/early/2014/02/26/003053.source.xml

Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few driver mutations occur alongside thousands of random passenger mutations--a natural consequence of cancers elevated mutation rate. Some passengers can be deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression that is described by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers meltdown. We find support for the model in cancer age-incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to rationalize successes and failures of different treatment strategies. We find that a tumors load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. The collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by both current and future therapies.

10.1073/pnas.1404341111

biorxiv

10.1101/003004

Neanderthals had our de novo genes.

John Stewart Taylor;

John Stewart Taylor

Department of Biology, University of Victoria, Victoria, BC, Canada

2014-02-25

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/25/003004.source.xml

Gene duplication provides a profusion of raw material for evolutionary innovation (Lynch and Conery, 2000). While most duplicates rapidly become unrecognizable some, e.g., those that are immediately useful or those that after a period of relaxed selection gain unique roles, are retained and thereby expand a genomes protein-coding repertoire. Ohno (1970) famously remarked that without gene duplication, the creation of metazoans, vertebrates, and mammals from unicellular organisms would have been impossible. Such big leaps in evolution, he argued, required the creation of new gene loci with previously nonexistent functions (Taylor and Raes, 2004). Recently, another source of new genes has been recognized: Though rare, it seems clear that new genes can emerge from formerly non-coding DNA, the de novo protein coding genes (Zhao et al., 2014, and references therein).\n\nIn 2009 Knowles ...

10.1007/s00239-014-9628-x

biorxiv

10.1101/003012

Genetic drift opposes mutualism during spatial population expansion

Melanie JI Mueller;Beverly I Neugeboren;David R Nelson;Andrew W Murray;

Melanie JI Mueller

Harvard University

2014-02-25

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/02/25/003012.source.xml

Mutualistic interactions benefit both partners, promoting coexistence and genetic diversity. Spatial structure can promote cooperation, but spatial expansions may also make it hard for mutualistic partners to stay together, since genetic drift at the expansion front creates regions of low genetic and species diversity. To explore the antagonism between mutualism and genetic drift, we grew cross-feeding strains of the budding yeast S. cerevisiae on agar surfaces as a model for mutualists undergoing spatial expansions. By supplying varying amounts of the exchanged nutrients, we tuned strength and symmetry of the mutualistic interaction. Strong mutualism suppresses genetic demixing during spatial expansions and thereby maintains diversity, but weak or asymmetric mutualism is overwhelmed by genetic drift even when mutualism is still beneficial, slowing growth and reducing diversity. Theoretical modeling using experimentally measured parameters predicts the size of demixed regions and how strong mutualism must be to survive a spatial expansion.

10.1073/pnas.1313285111

biorxiv

10.1101/003087

Chromatin Loops as Allosteric Modulators of Enhancer-Promoter Interactions

Boryana Doyle;Geoffrey Fudenberg;Maxim Imakaev;Leonid Mirny;

Leonid Mirny

MIT

2014-02-26

New Results

cc_no

Biophysics

https://www.biorxiv.org/content/early/2014/02/26/003087.source.xml

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.\n\nAuthor SummaryIn eukaryotes, enhancers directly contact promoters over large genomic distances to regulate gene expression. Characterizing the principles underlying these long-range enhancer-promoter contacts is crucial for a full understanding of gene expression. Recent experimental mapping of chromosomal interactions by the Hi-C method shows an intricate network of local looping interactions surrounding enhancers and promoters. We model a region of chromatin fiber as a long polymer and study how the formation of loops between certain regulatory elements can insulate or facilitate enhancer-promoter interactions. We find 2-5 fold insulation or facilitation, depending on the location of looping elements relative to an enhancer-promoter pair. These effects originate from the polymer nature of chromatin, without requiring additional mechanisms beyond the formation of a chromatin loop. Our findings suggest that loop-mediated gene regulation by elements in the vicinity of an enhancer-promoter pair can be understood as an allosteric effect. This highlights the complex effects that local chromatin organization can have on gene regulation.

10.1371/journal.pcbi.1003867

biorxiv

10.1101/003087

Chromatin Loops as Allosteric Modulators of Enhancer-Promoter Interactions

Boryana Doyle;Geoffrey Fudenberg;Maxim Imakaev;Leonid Mirny;

Leonid Mirny

MIT

2014-11-24

New Results

cc_no

Biophysics

https://www.biorxiv.org/content/early/2014/11/24/003087.source.xml

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.\n\nAuthor SummaryIn eukaryotes, enhancers directly contact promoters over large genomic distances to regulate gene expression. Characterizing the principles underlying these long-range enhancer-promoter contacts is crucial for a full understanding of gene expression. Recent experimental mapping of chromosomal interactions by the Hi-C method shows an intricate network of local looping interactions surrounding enhancers and promoters. We model a region of chromatin fiber as a long polymer and study how the formation of loops between certain regulatory elements can insulate or facilitate enhancer-promoter interactions. We find 2-5 fold insulation or facilitation, depending on the location of looping elements relative to an enhancer-promoter pair. These effects originate from the polymer nature of chromatin, without requiring additional mechanisms beyond the formation of a chromatin loop. Our findings suggest that loop-mediated gene regulation by elements in the vicinity of an enhancer-promoter pair can be understood as an allosteric effect. This highlights the complex effects that local chromatin organization can have on gene regulation.

10.1371/journal.pcbi.1003867

biorxiv

10.1101/003095

On a solution of the biodiversity paradox and a competitive coexistence principle

Lev V. Kalmykov;Vyacheslav L. Kalmykov;

Vyacheslav L. Kalmykov

Institute of Cell Biophysics of the Russian Academy of Sciences

2014-02-27

New Results

cc_no

Ecology

https://www.biorxiv.org/content/early/2014/02/27/003095.source.xml

The biodiversity paradox is the central problem in theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. This contradiction is the key subject of the long-standing and continuing biodiversity debates. The paradox impedes our insights into biodiversity conservation. Previously we proved that due to a soliton-like behaviour of population waves complete competitors can indefinitely coexist in one closed homogeneous habitat on one and the same limiting resource under constant conditions of environment, without any trade-offs and cooperations. As this fact violates the known formulations of the competitive exclusion principle we have reformulated the principle. Here we explain why this reformulation of the principle results in a solution of the biodiversity paradox. In addition, we generalize the competitive exclusion principle. Reasoning by contradiction, we formulate a generalized principle of competitive coexistence. These principles expand theoretical basis for biodiversity conservation and sustainable development.

biorxiv

10.1101/003061

DNA methylation modulates transcription factor occupancy chiefly at sites of high intrinsic cell-type variability

Matthew Maurano;Hao Wang;Sam John;Anthony Shafer;Theresa Canfield;Kristen Lee;John A Stamatoyannopoulos;

Matthew Maurano

University of Washington

2014-02-27

New Results

cc_by

Genomics

https://www.biorxiv.org/content/early/2014/02/27/003061.source.xml

The nuclear genome of every cell harbors millions of unoccupied transcription factor (TF) recognition sequences that harbor methylated cytosines. Although DNA methylation is commonly invoked as a repressive mechanism, the extent to which it actively silences specific TF occupancy sites is unknown. To define the role of DNA methylation in modulating TF binding, we quantified the effect of DNA methyltransferase abrogation on the occupancy patterns of a ubiquitous TF capable of autonomous binding to its target sites in chromatin (CTCF). Here we show that the vast majority of unoccupied, methylated CTCF recognition sequences remain unbound upon depletion of DNA methylation. Rather, methylation-regulated binding is restricted to a small fraction of elements that exhibit high intrinsic variability in CTCF occupancy across cell types. Our results suggest that DNA methylation is not a major groundskeeper of genomic transcription factor occupancy landscapes, but rather a specialized mechanism for stabilizing epigenetically labile sites.

biorxiv

10.1101/003111

Genomic Repeat Element Analyzer for Mammals (GREAM)

Darshan S Chandrashekar;Poulami Dey;Kshitish K Acharya;

Kshitish K Acharya

Institute of Bioinformatics and Applied Biotechnology (IBAB)

2014-02-28

New Results

cc_no

Bioinformatics

https://www.biorxiv.org/content/early/2014/02/28/003111.source.xml

Background: Understanding the mechanism behind the transcriptional regulation of genes is still a challenge. Recent findings indicate that the genomic repeat elements (such as LINES, SINES and LTRs) could play an important role in the transcription control. Hence, it is important to further explore the role of genomic repeat elements in the gene expression regulation, and perhaps in other molecular processes. Although many computational tools exists for repeat element analysis, almost all of them simply identify and/or classifying the genomic repeat elements within query sequence(s); none of them facilitate identification of repeat elements that are likely to have a functional significance, particularly in the context of transcriptional regulation.\n\nResult: We developed the Genomic Repeat Element Analyzer for Mammals (GREAM) to allow gene-centric analysis of genomic repeat elements in 17 mammalian species, and validated it by comparing with some of the existing experimental data. The output provides a categorized list of the specific type of transposons, retro-transposons and other genome-wide repeat elements that are statistically over-represented across specific neighborhood regions of query genes. The position and frequency of these elements, within the specified regions, are displayed as well. The tool also offers queries for position-specific distribution of repeat elements within chromosomes. In addition, GREAM facilitates the analysis of repeat element distribution across the neighborhood of orthologous genes.\n\nConclusion: GREAM allows researchers to short-list the potentially important repeat elements, from the genomic neighborhood of genes, for further experimental analysis. GREAM is free and available for all at http://resource.ibab.ac.in/GREAM/

biorxiv

10.1101/003137

A novel inference of the fundamental biodiversity number for multiple immigration-limited communities

Champak Beeravolu Reddy;François Munoz;Pierre Couteron;

Champak Beeravolu Reddy

Centre de Biologie pour la Gestion des Populations

2014-02-28

New Results

cc_no

Ecology

https://www.biorxiv.org/content/early/2014/02/28/003137.source.xml

Neutral community theory postulates a fundamental quantity, {theta}, which reflects the species diversity on a regional scale. While the recent genealogical formulation of community dynamics has considerably enhanced quantitative neutral ecology, its inferential aspects have remained computationally prohibitive. Here, we make use of a generalized version of the original two-level hierarchical framework in order to define a novel estimator for{theta} ;, which proves to be computationally efficient and robust when tested on a wide range of simulated neutral communities. Estimating{theta} ; from field data is also illustrated using two tropical forest datasets consisting of spatially separated permanent field plots. Preliminary results also reveal that our inferred regional diversity parameter based on community dynamics may be linked to widely used ordination techniques in ecology. This paper essentially paves the way for future work dealing with the parameter inference of neutral communities with respect to their spatial scale and structure.

biorxiv

10.1101/003145

High Bacterial Load Predicts Poor Outcomes in Patients with Idiopathic Pulmonary Fibrosis

Philip Molyneaux;Michael Cox;Saffron Willis-Owen;Kirsty Russell;Patrick Mallia;Anne-Marie Russell;Sebastian Johnston;Athol Wells;William Cookson;Toby Maher;Miriam Moffatt;

Philip Molyneaux

Imperial College

2014-02-28

New Results

cc_no

Microbiology

https://www.biorxiv.org/content/early/2014/02/28/003145.source.xml

BackgroundRepetitive alveolar damage and aberrant repair may be important in the development of the fatal condition Idiopathic Pulmonary Fibrosis (IPF). The role played by microorganisms in this cycle is unknown.\n\nMethodsWe consecutively enrolled patients diagnosed with IPF according to international criteria together with healthy smokers, non-smokers and subjects with moderate Chronic Obstructive Pulmonary Disease (COPD) as controls. Subjects underwent bronchoalveolar lavage (BAL) from which genomic DNA was isolated. The V3-V5 region of the bacterial 16S rRNA gene was amplified, allowing quantification of bacterial load and identification of communities by 16S rRNA qPCR and pyrosequencing.\n\nResultsOur 65 IPF patients had 3.9x109 copies of the 16S rRNA gene per ml of BAL, two-fold more than the 1.8x109 copies in 44 sex- and smoking-matched controls (P<0.0001). Baseline BAL bacterial burden predicted Forced Vital Capacity (FVC) decline (P=0.02). Patients in the highest tertile of bacterial burden were at a higher risk of mortality compared to subjects in the lowest tertile (hazard ratio 4.59 (95% CI, 1.05-20); P=0.04).\n\nSequencing yielded 912,883 high quality reads from all subjects. Operational Taxonomic Units (OTUs) representing Haemophilus, Streptococcus, Neisseria and Veillonella were 1.5 to 3.5 fold more abundant in cases than controls (P<0.05). Regression analyses indicated that these specific OTUs as well as bacterial burden associated independently with IPF.\n\nConclusionsIPF is characterised by an increased bacterial burden in BAL that predicts decline in lung function and death. Clinical trials of antimicrobial therapy may determine if microbial burden is causal or not in IPF progression.

biorxiv

10.1101/003129

A Genetic Screen Identifies Two Novel Rice Cysteine-rich Receptor-like Kinases That Are Required for the Rice NH1-mediated Immune Response

Mawsheng Chern;Rebecca Bart;Wei Bai;Deling Ruan;Wing Hoi Sze-To;Canlas Patrick;Rashmi Jain;Xuewei Chen;Pamela Ronald;

Pamela Ronald

UC Davis

2014-02-28

New Results

cc_no

Plant Biology

https://www.biorxiv.org/content/early/2014/02/28/003129.source.xml

Over-expression of rice NH1 (NH1ox), the ortholog of Arabidopsis NPR1, confers immunity to bacterial and fungal pathogens and induces the appearance of necrotic lesions due to activation of defense genes at the pre-flowering stage. This lesion-mimic phenotype can be enhanced by the application of benzothiadiazole (BTH). To identify genes regulating these responses, we screened a fast neutron-irradiated NH1ox rice population. We identified one mutant, called sn11 (suppressor of NH1-mediated lesion-mimic 1), which is impaired both in BTH-induced necrotic lesion formation and in the immune response. Using a comparative genome hybridization approach employing rice whole genome tiling array, we identified 11 genes associated with the sn11 phenotype. Transgenic analysis revealed that RNA interference of two of the genes, encoding previously uncharacterized cysteine-rich receptor-like kinases (CRK6 and CRK10), re-created the sn11 phenotype. Elevated expression of CRK10 using an inducible expression system resulted in enhanced immunity. Quantitative PCR revealed that BTH treatment and elevated levels of rice NH1 and its paralog NH3 induced expression of CRK10 and CRK6 RNA. These results indicate that CRK6 and CRK10 are required for the BTH-activated immune response mediated by NH1.

biorxiv

10.1101/003103

Effect of alternating red and blue light irradiation generated by light emitting diodes on the growth of leaf lettuce

Akihiro Shimokawa;Yuki Tonooka;Misato Matsumoto;Hironori Ara;Hiroshi Suzuki;Naoki Yamauchi;Masayoshi Shigyo;

Masayoshi Shigyo

Faculty of Agriculture, Yamaguchi University

2014-02-28

New Results

cc_no

Plant Biology

https://www.biorxiv.org/content/early/2014/02/28/003103.source.xml

Because global climate change has made agricultural supply unstable, plant factories are expected to be a safe and stable means of food production. As the light source of a plant factory or controlled greenhouse, the light emitting diode (LED) is expected to solve cost problems and promote plant growth efficiently. In this study, we examined the light condition created by using monochromatic red and blue LEDs, to provide both simultaneous and alternating irradiation to leaf lettuce. The result was that simultaneous red and blue irradiation promoted plant growth more effectively than monochromatic and fluorescent light irradiation. Moreover, alternating red and blue light accelerated plant growth significantly even when the total light intensity per day was the same as with simultaneous irradiation. The fresh weight in altering irradiation was almost two times higher than with fluorescent light and about 1.6 times higher than with simultaneous irradiation. The growth-promoting effect of alternating irradiation of red and blue light was observed in different cultivars. From the results of experiments, we offer a novel plant growth method named \"Shigyo Method\", the core concept of which is the alternating irradiation of red and blue light.

biorxiv

10.1101/003152

Complementation of a temperature sensitive Escherichia coli rpoD mutation using Lactobacillus sigma factors

James Winkler;Katy Kao;

Katy Kao

Texas A&M University

2014-03-02

New Results

cc_by_nc

Synthetic Biology

https://www.biorxiv.org/content/early/2014/03/02/003152.source.xml

Housekeeping sigma factors in the{sigma} 70 family, as components of the RNA polymerase holoenzyme, are responsible for regulating transcription of genes related to vegetative growth. While these factors are well understood in model organisms such as Escherichia coli and Bacillus subtilis, little experimental work has focused on the sigma factors in members of the Lactobacillus genus such as Lactobacillus brevis and Lactobacillus plantarum. This study evaluates the ability of putative{sigma} 70 proteins from L. brevis ([Formula]) and L. plantarum ([Formula]) to complement a temperature sensitive mutation in the E. coli 285c{sigma} 70 protein. This report is the first to show that these heterologous sigma factors were capable of restoring the viability of E. coli 285c for growth at 40-43.5 {degrees}C, indicating the [Formula] and [Formula] are capable of initiating transcription in a complex with the E. coli 285c RNA polymerase. These heterologous sigma factors may therefore be useful for improving biochemical knowledge of the sigma factor family or for use in the expression of hetereologous genomic libraries.

biorxiv

10.1101/003178

DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent

Graham Jones;Bengt Oxelman;

Graham Jones

Gothenburg University

2014-03-03

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/03/03/003178.source.xml

MotivationThe multispecies coalescent model provides a formal framework for the assignment of individual organisms to species, where the species are modeled as the branches of the species tree. None of the available approaches so far have simultaneously co-estimated all the relevant parameters in the model, without restricting the parameter space by requiring a guide tree and/or prior assignment of individuals to clusters or species.\n\nResultsWe present DISSECT, which explores the full space of possible clusterings of individuals and species tree topologies in a Bayesian framework. It uses an approximation to avoid the need for reversible-jump MCMC, in the form of a prior that is a modification of the birth-death prior for the species tree. It incorporates a spike near zero in the density for node heights. The model has two extra parameters: one controls the degree of approximation, and the second controls the prior distribution on the numbers of species. It is implemented as part of BEAST and requires only a few changes from a standard *BEAST analysis. The method is evaluated on simulated data and demonstrated on an empirical data set. The method is shown to be insensitive to the degree of approximation, but quite sensitive to the second parameter, suggesting that large numbers of sequences are needed to draw firm conclusions.\n\nAvailabilityhttp://code.google.com/p/beast-mcmc/, http://www.indriid.com/dissectinbeast.html\n\[email protected], www.indriid.com\n\nSupplementary informationSupplementary material is available.

10.1093/bioinformatics/btu770

biorxiv

10.1101/003178

DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent

Graham Jones;Bengt Oxelman;

Graham Jones

Gothenburg University

2014-12-11

New Results

cc_by_nc_nd

Evolutionary Biology

https://www.biorxiv.org/content/early/2014/12/11/003178.source.xml

MotivationThe multispecies coalescent model provides a formal framework for the assignment of individual organisms to species, where the species are modeled as the branches of the species tree. None of the available approaches so far have simultaneously co-estimated all the relevant parameters in the model, without restricting the parameter space by requiring a guide tree and/or prior assignment of individuals to clusters or species.\n\nResultsWe present DISSECT, which explores the full space of possible clusterings of individuals and species tree topologies in a Bayesian framework. It uses an approximation to avoid the need for reversible-jump MCMC, in the form of a prior that is a modification of the birth-death prior for the species tree. It incorporates a spike near zero in the density for node heights. The model has two extra parameters: one controls the degree of approximation, and the second controls the prior distribution on the numbers of species. It is implemented as part of BEAST and requires only a few changes from a standard *BEAST analysis. The method is evaluated on simulated data and demonstrated on an empirical data set. The method is shown to be insensitive to the degree of approximation, but quite sensitive to the second parameter, suggesting that large numbers of sequences are needed to draw firm conclusions.\n\nAvailabilityhttp://code.google.com/p/beast-mcmc/, http://www.indriid.com/dissectinbeast.html\n\[email protected], www.indriid.com\n\nSupplementary informationSupplementary material is available.

10.1093/bioinformatics/btu770

biorxiv

10.1101/003160

Conditions for the validity of SNP-based heritability estimation

James J Lee;Carson C Chow;

Carson C Chow

NIDDK, NIH

2014-03-03

New Results

cc_by_nd

Genetics

https://www.biorxiv.org/content/early/2014/03/03/003160.source.xml

The heritability of a trait (h2) is the proportion of its population variance caused by genetic differences, and estimates of this parameter are important for interpreting the results of genome-wide association studies (GWAS). In recent years, researchers have adopted a novel method for estimating a lower bound on heritability directly from GWAS data that uses realized genetic similarities between nominally unrelated individuals. The quantity estimated by this method is purported to be the contribution to heritability that could in principle be recovered from association studies employing the given panel of SNPs [Formula] Thus far the validity of this approach has mostly been tested empirically. Here, we provide a mathematical explication and show that the method should remain a robust means of obtaining [Formula] under circumstances wider than those under which it has so far been derived.

10.1007/s00439-014-1441-5

biorxiv

10.1101/003160

Conditions for the validity of SNP-based heritability estimation

James J Lee;Carson C Chow;

Carson C Chow

NIDDK, NIH

2014-03-04

New Results

cc_by_nd

Genetics

https://www.biorxiv.org/content/early/2014/03/04/003160.source.xml

The heritability of a trait (h2) is the proportion of its population variance caused by genetic differences, and estimates of this parameter are important for interpreting the results of genome-wide association studies (GWAS). In recent years, researchers have adopted a novel method for estimating a lower bound on heritability directly from GWAS data that uses realized genetic similarities between nominally unrelated individuals. The quantity estimated by this method is purported to be the contribution to heritability that could in principle be recovered from association studies employing the given panel of SNPs [Formula] Thus far the validity of this approach has mostly been tested empirically. Here, we provide a mathematical explication and show that the method should remain a robust means of obtaining [Formula] under circumstances wider than those under which it has so far been derived.

10.1007/s00439-014-1441-5

biorxiv

10.1101/003186

Does ‘information control the living state’?

Rodrick Wallace;

Rodrick Wallace

The New York State Psychiatric Institute

2014-03-04

New Results

cc_by_nc_nd

Biophysics

https://www.biorxiv.org/content/early/2014/03/04/003186.source.xml

We generalize the recently-uncovered Data Rate Theorem in the context of cognitive systems having a dual information source, including those of the living state that is particularly characterized by cognition at every scale and level of organization. The unification of information theory and control theory via the Data Rate Theorem is not additive, but synergistic, generating new statistical tools that greatly constrain the possible dynamics of that state. Thus, in addition to providing novel conceptual approaches, this emerging body of theory permits construction of models that, like those of regression analysis, can provide benchmarks against which to compare experimental or observational data.

biorxiv

10.1101/003210

Detecting translational regulation by change point analysis of ribosome profiling datasets

Anze Zupanic;Catherine Meplan;Sushma N Grellscheid;John C Mathers;Tom BL Kirkwood;John E Hesketh;Daryl P Shanley;

Daryl P Shanley

Institute for Ageing and Health, Newcastle University

2014-03-05

New Results

cc_by

Bioinformatics

https://www.biorxiv.org/content/early/2014/03/05/003210.source.xml

Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and gene isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new gene isoforms.

10.1261/rna.045286.114

biorxiv