The extent of translational control of gene expression in mammalian tissues remains largely unknown. Here we perform genome-wide RNA sequencing and ribosome profiling in heart and liver tissues to investigate strain-specific translational regulation in the spontaneously hypertensive rat (SHR/Ola). For the most part, transcriptional variation is equally apparent at the translational level and there is limited evidence of translational buffering. Remarkably, we observe hundreds of strain-specific differences in translation, almost doubling the number of differentially expressed genes. The integration of genetic, transcriptional and translational data sets reveals distinct signatures in 3′UTR variation, RNA-binding protein motifs and miRNA expression associated with translational regulation of gene expression. We show that a large number of genes associated with heart and liver traits in human genome-wide association studies are primarily translationally regulated. Capturing interindividual differences in the translated genome will lead to new insights into the genes and regulatory pathways underlying disease phenotypes. To what extent translational control can contribute to global gene expression patterns in the disease state is poorly defined. Here the authors conduct genome-wide RNA-seq and ribosome profiling in a rat model of hypertension and uncover altered translation patterns in disease associated genes. Heritable RNA expression phenotypes have been studied extensively146789Lx reference strain (n=5) and the SHR/Ola (n=5), a widely studied model of cardiovascular and metabolic disease traits213141516To obtain quantitative measurements of translation, we adapted ribosome profiling procedures11Ribosome profiling of disease tissue reveals widespread interindividual regulation of translation that shapes the molecular landscape of the cardiometabolic phenotype of the SHR/Ola rat. Ribo-seq data are a better proxy for protein levels compared with RNA-seq data and expose almost twice as many differences in gene expression between strains. The integration of transcriptional and post-transcriptional control of gene expression identifies distinct molecular signatures and reveals the contribution of genetic variation, microRNAs (miRNAs) and RNA-binding proteins (RBPs) to translational regulation. Many genes associated with cardiac and hepatic traits in humans are translationally, and not transcriptionally, regulated in disease tissue.in vivo snapshots of active translation. To distinguish translational from transcriptional regulation of gene expression, we integrated two distinct RNA-seq experiments: one polyA-selected data set (RNA-seq1) and one ribosomal RNA (rRNA)-depleted data set (RNA-seq2), which was generated in parallel to ribosome profiling from the identical tissue lysate. To adjust for variation in sequencing depth across technologies, mappability and fragment size, we matched the read length and the number of uniquely aligning reads located within exons for all data sets ; (ii) buffered RNA expression differences that were not detected on the level of translation but were present in both RNA-seq experiments ; (iii) reinforced strain-specific differences that were not detected in either RNA-seq experiments but were apparent at the translational level and thus exclusive to ribosome profiling data .We compared differences in messenger RNA (mRNA) levels to variation in RPF abundances between strains . Three cWhereas in yeast a variable extent of translational buffering was observed2223heart=1.09; slopeliver=0.97). Overall, the majority of RNA expression differences in tissues are associated with equal variation in RPF abundance of the same magnitude and direction.We then quantified the amount of translational regulation by calculating the slopes (standardized major-axis estimation)only genes were significantly greater than RNA+RIBO slopes  for both tissues, indicating reinforced strain differences that arise through post-transcriptional control.The slopes for the RIBOLx rat strainsTo assess whether genome-wide strain-specific differences in RPF abundance were indeed reflected on the proteome, we integrated two mass-spectrometry based quantitative proteome data sets from liver of SHR/Ola and BN-only), not detected by RNA expression profiling, was found to account for significant differences in protein abundances across strains (P<1e−4). Ribo-seq data effectively revealed additional variation in gene usage that explains protein levels  that affect the abundance of a gene product. However, consequences of events that occur in later stages are not expected to be evident in preceding stages. In particular, translation levels reflect both transcriptional and translational regulation events, whereas transcript levels only reflect transcriptional—and not translational—regulation events. Therefore, when comparing RNA levels and protein levels conditioning on the translation levels, we would expect no additional information about the protein levels to be present in the RNA and thus they should be conditionally independent. On the other hand, when comparing translation levels and protein levels conditioning on the RNA levels, we would still expect dependences between translation levels and protein levels due to translational regulation events. We first tested the conditional independence between RNA and protein levels, given the Ribo-seq data using partial correlationsn levels .only genes , reducing the inter-strain variation in gene expression. In addition, RNAonly genes were translated at a low efficiency (only genes possess significantly longer 3′untranslated regions (UTRs) , which has been implicated previously with low TE28For 25% of differentially transcribed genes across both tissues, we did not detect strain-specific differences in RPF abundances. This can in part be explained by translational buffering of RNA expression differences for these RNAficiency , resultiLx and SHR/Ola strainsχ2-test; Pheart<2.2e−16; in liver: 106 out of 238; Pliver<2.2e−16; see also only events that do not overlap with eQTLs and yet affect protein abundance in the parental strains (It is a matter of debate how well inherited RNA expression traits (eQTLs) are mirrored by the proteome and how much post-transcriptional processes contribute. Previous studies suggested that ∼32–35% of eQTLs lead to inherited differences in protein abundance107 strains . These pcis-regulatory elements. We tested whether known motifs of RBPs are more often altered by sequence variants in the 3′UTR of RIBOonly genes compared with genes that did not undergo translational regulation (RNA+RIBO). The binding sites of known translational regulators such as CPEB3 (ref. Pcorrected=0.026) were significantly enriched for genetic variation, but the analysis also suggested a role for splicing factors such as SF3B4  as well as other factors in translation by binding to cis-regulatory elements  density in the 3′UTR of genes under translational control , suggestEB3 ref.  (Wilcoxoelements .n=4) and BN-Lx rat strains (n=4). Binding sites for differentially transcribed miRNAs (FDR<0.05) were enriched in the 3′UTRs of differentially translated (RIBOonly) genes when compared with differentially transcribed (RNA+RIBO) genes  and ‘hypertrophic cardiomyopathy' in the heart   . These fMyh6 (GWAS candidate gene for heart rate)Acadl (GWAS candidate gene for metabolite levels and implicated in hepatic insulin resistance)37Genome-wide association studies (GWASs) revealed numerous genes associated with common complex diseasesLx and SHR/Ola male rats between 0900 and 1000 hours and immediately snap frozen in liquid nitrogenad libitum in an air-conditioned animal facility at the Czech Academy of Sciences, Prague, Czech Republic. All experimental procedures were carried out in accordance with the European Union National Guidelines and the Animal Protection Law of the Czech Republic (311/1997) and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague.Heart and liver tissues for the experiments described in this study were harvested from 6-week-old unfasted BN-−1 DNase I and nuclease-free H2O to final volume). To impede post-lysis translation, the lysis buffer was supplemented with cycloheximide (Sigma), previously dissolved in EtOH, at a final concentration of 0.1 mg ml−1. The tissue was homogenized further by repeatedly passing the lysate through a 21-gauge syringe needle. For complete lysis, the samples were kept on ice for 10 min and subsequently centrifuged at 20,000g to precipitate cell debris.For each animal ∼100 mg of frozen tissue were pulverized manually under liquid nitrogen and lysed in 1 ml lysis buffer , 1% Triton X-100, 0.1% NP-40, 1 mM dithiothreitol, 10 U mlTo accurately dissect translation and transcription, we prepared both Ribo-seq and RNA-seq libraries for each biological replicate from the identical lysate. Ribosome footprints were generated by treating part of the lysate with proprietary ARTseq nuclease (Epicentre). We then purified monosomes through Sephacryl S400 columns  and extracted RPFs with phenol chloroform. Ribosomal RNA was removed using the RiboZero Gold Magnetic Kit (Epicentre) before polyacrylamide gel electrophoresis (PAGE) purification. Sequencing adapters were ligated before the samples were retrotranscribed and again PAGE purified. Circularized complementary DNA (cDNA) templates were amplified with 12 PCR cycles, using Phusion polymerase (NEB). Following an additional native PAGE purification (8% TBE gel) step, libraries were quantified using the Qubit fluorometer, while the quality and average fragment size were estimated at the Bioanalyzer . If not described otherwise, steps of the library generation were performed according to the mammalian ARTseq kit.Barcodes were used to perform multiplex sequencing and create sequencing pools containing at least eight different samples and always an equal amount of both RNA and RPF libraries. We then sequenced sample pools on several lanes on the HiSeq 2000 platform using 50-bp sequencing chemistry to reduce barcode-, lane- or slide-related bias in the sequencing data.Lx and SHR/Ola strains To assess mRNA levels, we analysed a polyA-selected RNA-seq data set, termed ‘RNA-seq1', of the BN-http://hannonlab.cshl.edu/fastx_toolkit/), retaining reads of 20 nt or longer post-clipping length: fastx_clipper -a 5′-AGATCGGAAGAGCACACGTCT-3′ -l 20 -n -v -Q33 followed by fastx_trimmer -Q33 -f 1.Raw sequencing data were demultiplexed with the CASAVA 1.8 pipeline and the 3′-end adapter was removed using the FASTX-toolkit  and read length to ensure that exclusive characteristics of Ribo-seq or RNA-seq experiments reflect true biological processes and not technical properties of the different methods.To assess the quality of the Ribo-seq data sets, we calculated the length-normalized, genome-wide average expression of the UTR and coding regions. For each library, we counted the number of reads mapping to either 5′UTR, Coding Sequence or 3′UTR and normalized it by the total length of the respective feature and the library size. Ribosome footprints of the heart and liver were distributed across gene bodies as expectedP≤0.01).To quantify expression of genes, we first assigned uniquely mapping reads to their genomic feature (Ensembl database release 72 ref. ) and treP≤0.01). Differential RNA expression of these genes is promoted to the translational level and has a direct effect on protein synthesis. (ii) RNAonly: are buffered genes that do not exhibit significant inter-strain variation on the translational level but that were detected as differentially transcribed in both RNA-seq experiments (Bonferroni adj. P≤0.01). Translational regulation counteracts changes on the RNA level and buffers differences in between the strains. (iii) RIBOonly: indicates reinforced and translationally induced strain-specific differences, which are exclusive to Ribo-seq and cannot be detected in either of the two RNA-seq experiments (Bonferroni adj. P≤0.01). Ribosome profiling can reveal differential usage of genes that is either not present or under-represented in RNA expression data sets.To determine the relationship of transcriptional and translational regulation, we defined three groups of genes: (i) RNA+RIBO: denotes forwarded significant differences in expression across strains that are detectable in both RNA-seq experiments as well as in the Ribo-seq data  and polyadenylated transcripts (RNA-seq1).RNA-seq2 serves as a technical control for Ribo-seq. The libraries were created in parallel from the identical tissue lysate with a procedure very similar to Ribo-seq. However, ribosomes occupy mostly processed transcripts, whereas total RNA-seq also contains nuclear RNA. Thus we also used RNA-seq1 (PolyA-selected RNA-seq) as a control data set to determine whether processed transcripts are differentially expressed on the RNA level.Lx. RNA fold changes are the average of RNA-seq1 and RNA-seq2. To assess whether RNA-seq and Ribo-seq fold changes correlate significantly on a global scale, we computed the Pearson's correlation for both tissues (P<1e−4).For each data set, we also calculated fold changes of normalized read counts per gene for SHR/Ola over BN-only, RNA+RIBO and RIBOonly gene sets, we computed the slopes of three linear models:Comparing RNA-seq and Ribo-seq fold changes uncovers the extent of translational regulation for each gene. When differences on the RNA level induce equivalent changes in the ribosome occupancy, no translational regulation is present and strain-specific differences are promoted across regulatory layers. An increase or decrease of fold changes across data sets indicates translational reinforcement or buffering. To estimate the extent of translational regulation for the RNAusing the major-axis estimation methodLx and SHR/Ola using liquid chromatography-tandem mass spectrometry (LC-MS/MS) as reported by Low et al.Global protein abundances were estimated in the liver of BN-t-distributionWe consider the three random variables ‘RNA', ‘Ribo' and ‘protein'. For each strain we tested all pairs of the three variables ‘RNA', ‘Ribo' and ‘protein' for conditional independence, given the third variable. Intuitively, conditional independence between ‘RNA' and ‘protein' conditional on ‘Ribo' means that knowledge about ‘RNA' is irrelevant for knowledge about ‘protein' if we know ‘Ribo'. We assume that tuples  follow a multivariate Gaussian distribution. Then the conditional distribution of two variables, given the third, is a bivariate Gaussian distribution, with the partial correlation coefficient describing the relation between the two variables. In this model, conditional independence is equivalent to a zero partial correlation coefficient. Partial correlation coefficients can be obtained from the inverse of the covariance matrix or by correlating the residuals obtained by regressing each of the two variables against the third. Here we used the second approach and tested the significance of the partial correlation coefficient using the only) in the liver and were also quantified by MS in both strains. Translationally induced strain-specific differences resulted in significant concordant changes  on the protein level  as the ratio of normalized Ribo-seq reads in the CDS over normalized RNA-seq reads (average of RNA-seq1 and RNA-seq2) in the CDS, thus avoiding the length of UTRs to influence our calculation. Ribo-seq and RNA-seq data cover different parts of genes making it necessary to focus on the CDS, a region covered by both methodologies, when performing quantitative comparisons across both technologies.The TE score was calculated for the different gene groups (RNAWe determined the length and position of UTRs as annotated by the Ensembl release 72 databaseonly) or Ribo-seq (RNA+RIBO and RIBOonly). We identified a significant over-representation of KEGGPadjusted≤0.01; Bonferroni) enriched according to a hypergeometric test. All pathways listed by the KEGG database (as of 21 March 2011) were tested for a significant over-representation of differentially expressed genes. Pathways were either detected using both methodologies (black), or exclusively enriched in either Ribo-seq (red) or RNA-seq (blue) data  data .To test for differential miRNA expression, we analysed four biological replicates of each strain. Total RNA was extracted from the left ventricle tissue using the mirVana miRNA Isolation kit (Life Technologies). RNA was quantified and the quality assessed using Agilent's Bioanalyzer. To enrich for 15–35-bp small RNAs, 10 μg total RNA was purified on 15% denaturing PAA gel (7 M urea). Small RNA libraries were prepared using the SOLiD Total RNA-Seq kit (Life Technologies) following the manufacturer's guidelines. After adapter ligation, cDNA was purified using the MinElute PCR Purification kit (Qiagen) and size selected on a 10% TBE-urea gel. cDNA fragments were then amplified using barcoded primers for multiplex sequencing. The final cDNA libraries were quantified using the Qubit fluorometer, library sizes were assessed with the DNA 1,000 kit (Agilent) and sequencing was carried out on a SOLiD 3 system.Lx and SHR/Ola using a generalized linear model with the quasi-Poisson family. The FDR was controlled using the Benjamini–Hochberg procedureonly) were more often predicted targetsAdapter-clipped reads were mapped against rn4 with Bowtie5152i and marker j, we computed the likelihood ratio statistic of the full model containing the genotype variable against a null model containing only an intercept term. To determine the significance of likelihood ratio statistic scores while accounting for linkage disequilibrium, we used a permutation strategy. Finally, we adjusted the QTL P values for multiple testing using the Benjamini–Hochberg methodTo identify loci that determine RNA expression levels and the respective target genes, we previously performed an eQTL study for both tissues based on RNA-seq data of the HxB/BxH recombinant inbred panelχ2-test. As expected, we found a strong enrichment of eQTLs for differentially expressed genes on the RNA level in the founder strains (only) were not enriched for eQTLs, thus representing a layer of regulation not captured by RNA expression-based linkage studies.We then compared the classification of genes based on differential translation and transcription to the set of genes that have eQTL using the  strains . Genes t strains . Genes ponly) genes as compared with SNPs in 3′UTR of genes that were regulated on both levels (RNA+RIBO), we first obtained 50 bp of flanking sequences for all SNPs located in all 3′UTR regions subject to the integrated analysis in each tissue. For each position weight matrix from the Hughes RBP databaseonly genes and SNPs in RNA+RIBO genes. We tested for each position weight matrix whether the absolute value of the log ratio of binding P values was larger in the RIBOonly group compared with the RNA+RIBO group using a one-sided Wilcoxon–Mann–Whitney test. Finally, we adjusted these P values for multiple testing using the Benjamini–Hochberg methodTo determine whether the binding sites of expressed RNA-RBPs were preferentially altered by SNPs in 3′UTRs of translationally regulated . After DNase I (Ambion) treatment at 37 °C for 20 min, RNA was purified using the RNeasy Mini kit (Qiagen). First-strand cDNA synthesis was performed using random primers and Superscript II reverse transcriptase (Life Technologies).To estimate RNA expression of genes, quantitative PCRs were performed using the Power Sybr Green mix (Applied Biosystems) and primers listed in Ct method and normalized to Polr2a (heart samples) or Tbp (liver samples). Differential RNA expression was tested using the nonparametric Mann–Whitney test.We included five biological replicates for each strain and tissue and performed four technical replicates per sample. Expression levels were calculated using the ΔΔg for 10 min at 4 °C. Total protein concentration was estimated using the BCA protein assay kit (Pierce). Proteins were resolved on 4–12% Bis-Tris Novex gels (Life Technologies) under reducing conditions and then transferred on polyvinylidene difluoride membranes (Millipore). To block for unspecific sites, membranes were incubated with 5% non-fat dry milk in PBS-T . Primary antibody incubations in 5% non-fat dry milk in PBS-T were performed overnight at 4 °C. The following primary antibody dilutions were used: 1:100 Ctps1 , 1:1,000 Fads1 , 1:200 Fes , 1:1,000 Gja1 , 1:2,000 Maoa , 1:500 Mrpl48 , 1:200 Myh6 , 1:1,000 Myh7 , 1:1,000 Ppia  and 1:2,000 Vinculin  as the loading control.Protein extracts were obtained by lysing pulverized left ventricle or liver tissue in RIPA buffer  supplemented with a protease inhibitors cocktail (Roche) on ice for 30 min. Samples were centrifuged at 20,000Secondary horseradish peroxidase-conjugated antibodies anti-goat , anti-rabbit  or anti-mouse  were used at a dilution of 1:2,000. Membranes were developed using the chemiluminescent detection method. Results are summarized in Accession codes: Data are available via the European Nucleotide Archive  under accession number (PRJEB7498).How to cite this article: Schafer, S. et al. Translational regulation shapes the molecular landscape of complex disease phenotypes. Nat. Commun. 6:7200 doi: 10.1038/ncomms8200 (2015).Supplementary Figures 1-8 and Supplementary Tables 1-7Differentially expressed genes in the rat heart. Comparison of gene expression levels between SHR/Ola and BN-Lx rat strains using both RNA-seq and Ribo-seq data reveals genes under three different modes of gene expression regulation in the heart. Genes differentially expressed on the RNA level were either buffered through translation  or the variation in expression was also detected in the translational level . We also detected hundreds of genes under translational control that were not regulated on the RNA at genome-wide significance .Differentially expressed genes in the rat liver. Comparison of gene expression levels between SHR/Ola and BN-Lx rat strains using both RNA-seq and Ribo-seq data reveals genes under three different modes of gene expression regulation in the liver. Genes differentially expressed on the RNA level were either buffered through translation  or the variation in expression was also detected in the translational level . We also detected hundreds of genes under translational control that were not regulated on the RNA at genome-wide significance .KEGG enrichment analysis for differentially used genes in heart. All differentially expressed genes detected in either Ribo-seq or RNA-seq datasets were tested for significant  enrichment of KEGG6 pathways using webGestalt7. The colors indicate wether an enrichment was detected with both technologies (black), only considering Ribo-seq (red) or only with RNA-seq (blue).KEGG enrichment analysis for differentially used genes in liver. All differentially expressed genes detected in either Ribo-seq or RNA-seq datasets were tested for significant  enrichment of KEGG6 pathways using webGestalt7. The colors indicate wether an enrichment was detected with both technologies (black), only considering Ribo-seq (red) or only RNA-seq (blue) data.Detailed KEGG pathways enriched for differentially expressed genes in the liver and heart between SHR/Ola and BN-Lx. All differentially expressed genes detected by either Ribo-seq or RNA-seq datasets were tested for significant  enrichment of KEGG6 pathways using webGestalt7. Individual genes that are members of each pathway are listed for each analysis: Heart RNA-seq; Heart Ribo-seq; Liver RNA-seq and Liver Ribo-seq.


Bovine leukemia virus (BLV), a B-lymphotropic oncogenic retrovirus sharing common biological and structural features with the human T-cell leukemia virus I and II (HTLV-I and II), is the etiologic agent of enzootic bovine leucosis. One major feature of the BLV infection is the absence of viremia. It is widely accepted that BLV latency, due to the RN! polymerase II 5’-LTR-driven transcriptional and epigenetic repression is a viral strategy to escape from the host immune system and allow tumor development. Recently, it has been demonstrated by deep sequencing and bioinformatics analysis that the BLV genome encodes a cluster of micro-RNAs which is predicted to be transcribed by RNA polymerase III suggesting that the silencing dogma in BLV transcriptional regulation is only partially correct. Here, we demonstrated by chromatin immunoprecipitation assays that BLV miRNAs were indeed transcribed in vivo by RNA polymerase III through a type II RNAPIII promoter similar to the one directing tRNAs transcription. We also showed that an activating epigenetic environment surrounds the miRNAs cluster. Overall, our results provide new insights into a better understanding of the molecular mechanisms regulating gene expression of oncogenic retroviruses.


This study investigated the influence of the nature of oligonucleotides on the abilities to form antiparallel and parallel duplexes. Base pairing of homopurine DNA, 2’-O-MeRNA and RNA oligonucleotides with respective homopyrimidine DNA, 2’-O-MeRNA and RNA as well as chimeric oligonucleotides containing LNA resulted in the formation of 18 various duplexes. UV melting, circular dichroism and fluorescence studies revealed the influence of nucleotide composition on duplex structure and thermal stability depending on the buffer pH value. Most duplexes simultaneously adopted both orientations. However, at pH 5.0, parallel duplexes were more favorable. Moreover, the presence of LNA nucleotides within a homopyrimidine strand favored the formation of parallel duplexes. DNA exists as a right-handed, double-stranded structure, which is classified as a B helix. RNA also appears as a right-handed structure (A helix). However, in native RNA, double-stranded helical regions are short (on average 5–7 base pairs long). Moreover, RNA contains many structural motifs disrupting its helical structure, such as various types of single and multinucleotide mismatches, internal loops, hairpins, bulge loops, terminal unpaired regions and multibranch . Some spInteracting strands in helical DNA and RNA exist in antiparallel orientation (5’-3’/3’-5’), and they are stabilized by Watson-Crick hydrogen bonds as well as intra- and/or inter-strand stacking interactions. Conversely, DNA and RNA can adopt a parallel-stranded (5’-3’/5’-3’) structure, which is an unusual duplex form .Pattabiraman suggested that the formation of parallel DNA duplexes occurs by reverse Watson-Crick base pairs, also called Donohue base pairs, and they confirmed the formation of this structure by Raman spectroscopy, NMR spectroscopy and chemical methylation . At neutDrosophila melanogaster genome [lon gene in E. coli [Interestingly, parallel-stranded purine-pyrimidine stretches have been found in different genomes, and these stretches may have an evolutionary role . For exar genome . Such pa E. coli . Moreove E. coli –16. Para E. coli , 18.i.e., 2’-O-MeRNA or locked nucleic acid) [There have been several theoretical and experimental reports on the formation of parallel DNA duplexes, but there has been no data reported on parallel structures of natural and modified RNA/RNA and DNA/RNA duplexes. Parallel duplexes have been characterized by thermodynamic and spectroscopic analysis as well as by a variety of chemical and biochemical methods –22. As nic acid) , 29.This study presents the thermodynamic and structural details of a series of unmodified and modified DNA, 2’-O-MeRNA and RNA homo- and heteroduplexes. A homoduplex is a duplex that is formed by the same type of strands , whereas a heteroduplex is a duplex formed by various types of strands . The model duplexes were designed accordingly to previously published paper . The parAll oligonucleotides were synthesized on a MerMade12 (BioAutomation) synthesizer using standard phosphoramidite chemistry . CommercM-1 vs. ln(CT/4) plots was within 15% of the value derived from averaging the fits to individual melting curves as expected if the two-state model is reasonable.Oligonucleotides were melted in a buffer containing 40 mM boric acid, 40 mM phosphoric acid, 40 mM acetic acid and 100 mM sodium chloride adjusted to pH 5.0 or 7.0 with 0.2 M sodium hydroxide (Robinson Britton buffer) . OligonuCD spectra were recorded using a JASCO J-815 spectropolarimeter at 4°C in 0.2 cm path length quartz cuvettes. The oligonucleotides were dissolved in RB buffer (pH 5.0 or 7.0) to achieve 4.4 μM sample concentration. Before the measurement, the samples were denatured for 2 min at 90°C, slowly cooled at room temperature and incubated at 4°C overnight. The measurements were taken in triplicate in the 200–350 nm wavelength range with a 1 nm data interval. The CD curves were established as an average of three CD scans. The spectrum of the buffer was subtracted, and the results were converted into molar ellipticity per nucleotide (Δε).i.e., steady-state and time-resolved fluorescence measurements, were performed.To determine the relative orientation of the strands in the duplex, the energy transfer between FAM and TAMRA was measured. Two types of fluorescence experiments, Each duplex was dissolved in RB buffer to achieve a 4.4 μM sample concentration. All samples were denatured at 90°C for 2 min and then slowly cooled to room temperature overnight. All measurements were carried out in the 450–650 nm wavelength range with a 1.5 nm data interval. FRET assays were performed at 10°C. Steady-state fluorescence spectra were measured and imaged using a FluoTime 300 EasyTau spectrometer .τD, τDA) for DNA and RNA duplexes were calculated using the Lorentzian lifetime distribution model with reconvolution. The quality of the fit was judged on the basis of the chi-squared parameter (understood as χ2 ≤ 1.2).All samples were prepared as described above for the steady-state fluorescence measurements and were performed with excitation at 440 nm. FRET assays were performed at 10°C. Fluorescence decays were measured by the time-correlated single photon counting technique (TCSPC) using a FluoTime 300 EasyTau spectrometer (PicoQuant). Fluorescence decay curves were analyzed using FluoFit Analysis software (PicoQuant). The values of lifetimes (Tm–1 versus lnCT/4). The two-state transition was assumed to be valid for duplexes in which the agreement in ΔH° values of the two methods is within 15%. The error-weighted (standard deviation) average of the data obtained by the two methods was calculated and reported in Thermodynamic parameters were calculated, using the program MeltWin 3.5, by two methods: (i) from fits of individual melting curves at nine different duplex concentrations, (ii) plots of reciprocal melting temperatures (Thermodynamic data for model DNA and RNA duplexes are summarized in M vs ln CT/4). Presence of three LNA-cytidine residues enhances stabilities of duplexes in range of 1.8–2.7 kcal/mol, both in buffer pH 5.0 and 7.0. The exception was duplex D2 at pH 7.0 where LNA residues diminished stability by 0.6 kcal/mol  between maximum peak at 220 nm and minimum peak at 210 nm  form helices which deviate from a canonical A-RNA and B-DNA structures. It is probably due to the formation of helix A and B intermediate structures. The reduction of ellipticity peaks ca. 260 nm in buffer pH 5.0 (except D3) in comparison to physiological pH was observed. Moreover, CD studies revealed some different patterns of CD curves depending on presence of LNA modification.In order to confirm that the model duplexes adopt a parallel orientation the efficiency of fluorescence resonance energy transfer (FRET) between 5,6-carboxyfluorescein (FAM) and 5-carboxytetramethylrhodamine (TAMRA) terminally attached to the 5’-end of the homopurine and homopyrimidine oligonucleotides, respectively, was studied. Common fluorophores pair, FAM as the donor (excitation at 494 nm and emission at 520 nm) and TAMRA as the acceptor (excitation at 565 nm and emission at 580 nm), also called the quencher was used . In thisE)  .R0) is the distance at which energy transfer efficiency is 50%. The R0 for FAM-TAMRA transfer was found to be 54±1 Å [D is the fluorescence lifetime of donor (i.e. the measured lifetime of donor in the absence of acceptor), τDA is the fluorescence lifetime of donor with acceptor (i.e. the measured lifetime of donor in the presence of acceptor).Förster distance  in model duplexes was calculated from the energy transfer efficiency (E) and is given by the following equation:R0 is the Förster distance, E is the FRET efficiency [The distance between donor and acceptor fluorophores  are only reliable when R is within a factor of 2 of R0. If R is twice the Förster distance (R = 2R0) then the transfer efficiency is 1.54%, and if R = 0.5R0 then the efficiency is 98.5%. In other words, it is rather difficult to precisely calculate the distance when R is outside the 0.5R < R0 < 2R region due to much weaker dependence of R on the extremely low or high transfer efficiencies.Because E)  for D1, D5 and D7-D18 duplexes at pH 5.0 and D1-D4 as well as D8-D18 duplexes at pH 7.0, and the second one containing duplexes D2-D4 and D6 at pH 5.0 and D5-D6 at pH 7.0 that the values of E is outside the limits of confidence (understood as 27Å˃R˃108Å). The fluorescence lifetimes of duplexes with a homopurine DNA strand are almost the same as a control probe (S1) under all pH conditions. However, duplexes containing homopurine RNA strand show shorter lifetimes resulting in a high FRET efficiency at both pH values. These results confirm a parallel orientation of the strands in duplexes D7-D18. Interestingly, the presence of three LNA nucleotides within DNA as well as RNA strand causes decrease of fluorescence lifetimes at acidic pH for RNA/DNA-LNA (1.4 ns), RNA/RNA-LNA (1.2 ns), RNA/2’-O-Me RNA-LNA (0.6 ns) as well as 2’-O-Me RNA/DNA-LNA (1.0 ns) and 2’-O-Me RNA/RNA-LNA (0.5 ns) in comparison to duplexes without LNA moieties i.e. D7 (1.8 ns), D9 (1.6 ns), D11 (0.7 ns), D13 (1.3 ns) and D15 (0.9 ns), respectively. Similar behavior is also observed for LNA-modified duplexes at pH 7.0 what might be due to a higher thermal stability of these structures.In general, all duplexes can be divided in two groups depending on the FRET efficiency (E) . The firDue to the fact that FRET parameters calculated based on time-resolved fluorescence measurements  are consBased on the thermodynamic parameters, it was observed that stability of DNA homo- and heteroduplexes are lower than respective 2’-O-Me RNA and RNA duplexes. Moreover, the results indicate that presence of LNA within DNA, RNA and 2’-O-Me RNA duplexes enhances their thermal stability and the strongest stabilities enhancement was observed for latter ones . These r37) oscillates between 1.6 and 5.4 kcal/mol. When purine strands were RNA (D7-D12) or 2’-O-Me RNA (D13-D18), both homo- and heteroduplexes performed very similar thermodynamic stabilities (except D17 and D18) in both buffers. In most cases, RNA and 2’-O-Me RNA homo- and heteroduplexes (D13-D18) are less stable at pH 5.0 than at pH 7.0. This difference of stabilities ranges between 0.3 and 0.9 kcal/mol. The exceptions concern duplexes D17 and D18 where differences of the thermodynamic stabilities were 1.9 and 1.4 kcal/mol, respectively. For D14 only, it was observed more favorable stability  in acidic condition. Furthermore, presence of LNA moieties within one strand of DNA and RNA duplexes enhance their thermodynamic stability. Additionally, when LNA units were introduced in the 2’-O-Me RNA strand, the stabilizing effect was measurably stronger. These results are in accordance with data in the literature [Analysis of thermodynamic stabilities of the same duplexes in buffers pH 5.0 and 7.0 indicated that DNA homo- and heteroduplexes are more stable at pH 5.0, however, the melting process is non two-state , D1-D6. terature , 38, 39.The influence of transition from antiparallel to parallel orientation in RNA and 2’-O-Me RNA duplexes on their thermodynamic stability was not reported. It is postulated that parallel duplex is formed by reverse Watson-Crick pairs and such base pairs was confirmed by NMR and Raman spectroscopies and chemical methylation . DiffereReported herein data showed that parallel DNA duplexes are more stable than antiparallel whereas stability of RNA and 2’-O-Me RNA based duplexes was very similar in both buffers. Topology of DNA and RNA duplexes is different and possibly observed thermodynamic properties correspond to those differences.1/2) maximum peak at 220 nm and minimum peak at 210 nm indicates that these values are lower (more negative) at pH 5.0 than at pH 7.0 for all analyzed duplexes (Comparison of CD spectra of DNA (D1) and RNA (D9) homoduplexes at pH 5.0 and 7.0 reveals differences which are related with B and A helix geometry, respectively . It indiduplexes .Sugimoto published CD spectra of duplexes D1 and D2, and postulate that negative value of peak at 210 nm (Sugimoto reported this peak as 218 nm) is due to the parallel orientation of DNA duplexes . CD speci.e. steady-state and time-resolved fluorescence methods. Obtained results revealed that fluorescence intensities and lifetimes of duplexes containing homopurine DNA strand do not change at pH 5.0 and 7.0.Various FRET-based techniques are commonly used to determine molecular distances and interactions within labeled nucleic acid systems . FluoresFRET parameters for all DNA complexes are virtually identical and this indicates mostly antiparallel orientation of the strands , D1-D6. i.e. calculated distances) shown in It must be emphasized that although theoretical values of FRET efficiencies were calculated based on lifetime measurements, in practice, many fluorescence decays are more complex. Excited molecules are often in an inhomogeneous environment and quenching processes can lead to multiexponential decay behavior. Moreover, the influence of any event on the distance between donor and acceptor molecules will affect the resonance energy transfer rate. Therefore, the numbers Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S1 Table−4 M oligomer concentration. Values in parenthesis concerns stabilities calculated form fitting melting curves whereas the values above were derived from correlation of melting temperature and duplex concentration.a—solution: 40 mM boric acid, 40 mM phosphoric acid, 40 mM acetic acid, and 100 mM sodium chloride, pH 5.0 and pH 7.0; b—calculated for 10(DOC)Click here for additional data file.


Caenorhabditis elegans and closely related nematodes, piRNAs are absent in all other nematode lineages. We found that there are at least two evolutionarily distinct mechanisms that compensate for the absence of piRNAs, both involving RNA-dependent RNA polymerases (RdRPs). Whilst one pathway is unique to nematodes, the second involves Dicer-dependent RNA-directed DNA methylation, hitherto unknown in animals, and bears striking similarity to transposon-control mechanisms in fungi and plants. Our results highlight the rapid, context-dependent evolution of small RNA pathways and suggest piRNAs in animals may have replaced an ancient eukaryotic RNA-dependent RNA polymerase pathway to control transposable elements.Small RNA pathways act at the front line of defence against transposable elements across the Eukaryota. In animals, Piwi interacting small RNAs (piRNAs) are a crucial arm of this defence. However, the evolutionary relationships among piRNAs and other small RNA pathways targeting transposable elements are poorly resolved. To address this question we sequenced small RNAs from multiple, diverse nematode species, producing the first phylum-wide analysis of how small RNA pathways evolve. Surprisingly, despite their prominence in  A survey of the nematode phylum reveals loss of the Piwi/piRNA pathway in several lineages, but RNA-dependent RNA polymerases control transposable elements in its absence. Caenorhabditis elegans—as the starting point. Surprisingly we found that the piRNA pathway has been completely lost in all groups of nematodes bar those most closely related to C. elegans. This finding raises the intriguing question of how these nematodes are able to control transposable element mobilization without piRNAs. We discovered that there are other small RNA pathways that target transposable elements in these nematodes, employing RNA-dependent RNA polymerases in order to make small RNAs antisense to transposable elements. Intriguingly, the most ancient of these mechanisms, found in the most basal nematodes, is a Dicer-dependent RNA-directed DNA methylation pathway. This pathway shares strong similarity to transposon-silencing mechanisms in plants and fungi, suggesting that it might have been present in an ancient common ancestor of all eukaryotes. Our results highlight the rapid evolution of small RNA pathways and demonstrate the importance of examining molecular pathways in detail across a range of evolutionary distances.Transposable elements are segments of DNA that have the ability to copy themselves independently of the host genome and thus pose a severe threat to the integrity of the genome. Organisms have evolved mechanisms to restrict the spread of transposable elements, with small RNA molecules being one of the most important defense mechanisms. In animals, the predominant small RNA transposon-silencing mechanism is the piRNA pathway, which appears to be widely conserved. However, little is known about how small RNA pathways that target transposons evolve. In order to study this question we investigated small RNA pathways across the nematode phylum, using a well-studied model organism—the nematode  Drosophila melanogaster, Danio rerio, Mus musculus, and the nematode C. elegans [Transposable elements are found in almost all eukaryotic genomes, and present a severe threat to the integrity of the germline and the survival of the species. Consequently, organisms have evolved robust pathways to silence the expression of transposable elements and restrict their spread –3. Small elegans ,5. Along elegans ,6,7. HowC. elegans, in which extensive studies of small RNAs have been undertaken. C. elegans possesses several classes of small RNAs, most of which are conserved. In C. elegans as in other organisms microRNAs (miRNAs) are transcribed from individual genomic loci to form hairpins that are processed by the activity of Dicer to produce mature miRNAs. The sequences of many C. elegans miRNAs are highly conserved all the way to humans and they have important functions in regulating key developmental transitions [The best understood nematode is the model organism nsitions C. elegans genome encodes two members of the Piwi subfamily of Argonautes, PRG-1 and PRG-2. The prg-2 gene is the result of a recent gene duplication and does not appear to function directly in the piRNA pathway, but prg-1 encodes a functional protein, which is expressed in the germline and binds to piRNAs [C. elegans piRNAs have some important differences to piRNAs in other animals. In C. elegans the 5′ U bias common to most animal piRNAs is conserved; however, they are they are only 21 nt long as opposed to the 26–30 nt more common in M. musculus and D. melanogaster [M. musculus and D. melanogaster that are processed to give rise to multiple piRNAs per genomic locus [C. elegans are associated with an upstream sequence motif [The o piRNAs ,10. Howenogaster ,10. In anogaster ,12, as oic locus ,13. The ce motif ,10,14.C. elegans piRNAs also differ from D. melanogaster and M. musculus piRNAs owing to their different mechanism of target silencing. piRNA-mediated silencing does not involve the direct cleavage of targets by the Slicer endonuclease domain of PRG-1. Instead, piRNAs silence their targets by initiating the synthesis of an abundant class of small interfering RNAs (siRNAs) through an RNA-dependent RNA polymerase (RdRP) [C. elegans RdRPs RRF-1 and EGO-1 are required for 22G-RNA biogenesis, with the RRF-2 RdRP being dispensable [C. elegans RdRP, RRF-3 is required instead for the production of another class of small RNAs, the 26G-RNAs, which have a 5′ monophosphate [e (RdRP) ,15. These (RdRP) ,17. Impoe (RdRP) ,17. The pensable . The fouhosphate . It remahosphate .C. elegans piRNAs have a similar function to those in other organisms, as they target transposable elements for silencing [C. elegans prg-1 mutants show fertility defects [C. elegans piRNA pathway represents an interesting example of where a conserved central core (the Piwi/piRNA complex) has acquired different upstream and downstream components whilst retaining its ancestral function.Despite divergence in biogenesis and silencing mechanisms, ilencing ,15. Addi defects , meaningC. elegans as a basis to guide an examination of small RNAs and the proteins that bind to them across the known diversity of the phylum Nematoda , small RNAs targeting transposons are produced by a different RNA dependent RNA polymerase pathway, in this case acting processively to generate dsRNA that is then processed by Dicer into small RNAs. This pathway also involves DNA methylation of transposable elements thus displays similarity to the RNA directed DNA methylation pathway found in plants and fungi. Our results provide a clear example of the rapid diversification of molecular pathways involved in silencing repetitive elements but at the same time identify hitherto unknown conservation at the core of the eukaryotic small RNA machinery.In order to gain further insight into how piRNAs evolve in the context of other small RNA pathways, we used Nematoda . Our anaC. elegans is in clade V) [C. elegans [C. elegans include miRNAs and piRNAs . We focussed on miRNA families that are conserved in at least two out of C. elegans, D. melanogaster, and Homo sapiens as likely ancestral bilaterian miRNAs. The majority were conserved across all the species we examined, and only two of these miRNAs were apparently lost in all nematodes profiled; however, there were isolated examples of species-specific losses of miRNAs, suggesting that their conservation amongst bilaterians is not universal , Globodera pallida (clade IV), and Nippostrongylus brasiliensis (clade V), as the life cycles of these species permitted collection of the required life stages. Broadly, these nematodes all showed similar developmental miRNA expression dynamics to C. elegans with correlation between expression changes in C. elegans and other nematodes better for more closely related nematodes  . Our sam elegans ,10. We fd piRNAs .. To assvels see . By thiss miRNAs , with thniversal . Additioes Figs.  and S2. C. elegans, piRNAs are 21 nt long and start with a uracil (U) also referred to as 21U-RNAs [C. elegans are clustered in the genome and are associated with a defined upstream sequence motif [Caenorhabditis nematodes and in Pristionchus pacificus [C. elegans core motif upstream of 21U-RNAs in Haemonchus contortus [N. brasiliensis  [Panagrellus redivivus (clade IV) [We next investigated piRNAs. In 21U-RNAs ,10,14. Mce motif ,10. Prevacificus . Since tontortus  (clade Viliensis . Thus thur study . Moreoveur study . Thus weade III)  and the lade IV) . Given tC. elegans   pathway, as defined in  elegans . We founematodes  despite nogaster . Strikinnogaster , which s elegans –33. Furtlade II) . This dietect it .. To tesalis set ..D. melanogaster Piwi in all the nematode species we tested. We then constructed a maximum-likelihood phylogenetic tree of these proteins, spiking in the known Piwi proteins from mammals as well as C. elegans ALG-1 and D. melanogaster AGO as examples of members of the Ago subfamily, responsible for Dicer-dependent small RNA binding [In order to test whether an independent approach could reproduce the loss of PRG-1 in non-clade V nematodes we used phmmer to find the highest scoring homologue of  binding . Whilst D. melanogaster than to nematodes [Hypsibius dujardini showing a strong 5′ U bias and with a modal length of 26 nt  and G. pallida (clade IV). These small RNAs had a modal length of 22 nt in B. malayi and 22–26 nt in G. pallida  (Romanomeris culicivorax (clade I), Enoplus brevis (clade II), or Odontophora rectangula (clade II)  , Romanomlade II) .. This sC. elegans, the RdRPs RRF-1, EGO-1, and RRF-2 generate 22G-RNAs whereas the RdRP RRF-3 is required for a separate small RNA pathway involving Dicer [Neospora crassa, and viral RdRPs [To examine this analysis further we examined the conservation of RdRPs in nematodes. In ng Dicer . We idenng Dicer . Althougng Dicer , there aal RdRPs . In vitral RdRPs ,40, althal RdRPs . It is tB. malayi and G. pallida both had abundant 5′ triphosphate RNAs aligning to transposons . In B. malayi the antisense bias was greater for 22G-RNAs than for non 22G-RNA sequences, whilst in G. pallida the antisense bias was seen for 20–26 nt long 5′ triphosphorylated G-RNAs . This finding suggests that transposon silencing is mediated by RdRPs in species other than C. elegans, even though these species lack piRNAs.Having established that 22G-RNA RdRP products are conserved in clades III–V we tested whether they could be important in defence against transposable elements in nematodes lacking piRNAs. We identified potential transposable element sequences in the nematode genomes with RepeatMasker, and aligned small RNAs to them to identify potential siRNAs. nsposons ; S6 Fig.B. malayi and G. pallida . Several features of these sequences suggest that they are of an evolutionary distinct origin to the piRNAs found in either C. elegans or D. melanogaster. First, piRNAs are made by Dicer-independent mechanisms [T. spiralis small RNAs showed a two nt 3′ overhang consistent with their being the product of Dicer activity on dsRNA , such that clusters with >10 times the mean density of small RNAs genome-wide are virtually absent . In surveying the diversity of small RNAs within Nematoda, we found evidence of both the ancestral Dicer/RdRP pathway and the piRNA pathway. In addition a unique non-processive RdRP activity evolved, responsible for generation of a novel class of small RNAs—the 22G-RNAs. We predict that similar diversity is likely to be evident across other animal phyla—indeed, evidence exists for RdRPs in some arthropods [We suggest that RNA-directed DNA methylation involving Dicer and RdRP activity is an ancestral transposon silencing mechanism for eukaryotes . This sythropods —underlinC. elegans was grown according to standard procedures [G. pallida were collected as described [T. spiralis adults and L1 were isolated according to standard procedures. N. brasiliensis adults were isolated from rodents and L1 larvae were collected from fecal matter according to standard procedures. E. brevis were collected from soil filtrates in Sylt, Germany with assistance from Werner Armonies (Alfred Wegener Research Station) and O. rectangula were collected from sand filtrates in Vancouver, Canada. In both cases collected nematodes were stored for transport in 1 ml RNA Later. P. varius were collected by placing infected crickets in water and frozen at −80°C for RNA extraction.ocedures . G. pallescribed . T. spirRNA was extracted using Trizol according to standard procedures. RNA Following RNA isolation, RNA was treated with 20U 5′ polyphosphatase (Epicenter) for 30 min to remove 5′ triphosphates and allow 5′ independent library construction or used directly for 5′ dependent library construction .. To tesAll small RNA libraries were made with the Illumina Truseq method according to the manufacturer’s instructions.Fasta files with one sequence for each read were generated by using Cutadapt (v1) to trim adapters and a custom Perl script to convert fastq into fasta files. Small RNAs of between 15 and 33 nt were then selected using a custom script written in Perl. In the absence of genome sequence, a custom script written in Perl was used to collect the length and first nucleotide of all species and tabulate this information. The output was read into R to generate barplots. To carry out alignments, to various genomes or transposon sequences from RepeatMasker predictions, we used Bowtie  with parC. elegans proteins across the nematode phylum, the predicted proteome from each species analysed was downloaded as a fasta file from the sources indicated in D. melanogaster proteome from Flybase (www.flybase.org). Formatdb was then run on each species separately to create individual databases. The C. elegans predicted proteome was used as input and blastp was run separately against each database. This generated output files that were filtered using a custom Perl script running in the BioPerl environment to select the best blast hit for each C. elegans protein for each database tested. In order to select the best hit, the bit score was divided by the length of the input sequence, as this method is more reliable than using the e-value [D. melanogaster appeared to have lost fewer proteins than all other non-clade V nematodes. This did not occur once in any of the simulations, thus giving an estimated p-value of <1e−4. For identification of selected RNAi proteins in E. brevis and H. dujardini, transcriptome databases from the draft transcriptomes were built using Formatdb and tblastn was used with C. elegans proteins. The best hit for selected proteins was then tested by reciprocal blast against C. elegans proteins to test for orthology.In order to interrogate protein evolution we independently developed a method similar to those used for similar analyses . To test e-value . To drawD. melanogaster Piwi. C. elegans RRF-1 and C. elegans RRF-3 to identify the best hit of each in the nematode genomes. The sequences were aligned using Muscle using 16 iterations and the alignment was refined with Gblocks 0.91b using default parameters. Phylogeny was obtained using PhyML using the Blosum62 substitution matrix [To construct phylogenetic trees of Piwi and RdRP proteins we used separate runs of phmmer with n matrix .T. spiralis, which may have differences to the isolate used by Gao and colleagues [To test for DNA methylation in our strain of lleagues , we purilleagues  and sequlleagues .We took DNA methylated genes (including transposon coding sequences) as defined  and idenS1 Data(TXT)Click here for additional data file.S2 Data(TXT)Click here for additional data file.S3 Data(DOCX)Click here for additional data file.S4 Data(ZIP)Click here for additional data file.S1 FigC. elegans).(A) 5′ dependent library preparation only allows RNAs with 5′ monophosphates to be ligated to adapters. It thus allows sequencing of Dicer products (both miRNAs and siRNAs) and mature piRNAs.(B) 5′ independent library preparation allows both 5′ triphosphate and 5′ monophosphate species to be ligated to adapters and thus enables sequencing of RNA dependent RNA polymerase products (22G-RNAs in (PDF)Click here for additional data file.S2 FigC. elegans. (B–D) Developmental expression changes of miRNAs in nematode species compared to that of the homologous miRNA in C. elegans, with the Spearman’s rank correlation coefficient shown for each species.(A) Mean miRNA conservation across eight nematode species is plotted against expression of the miRNA in adult (PDF)Click here for additional data file.S3 FigH. dujardini, showing longer sequences with a 5′ U bias, putative piRNAs. (B) Putative H. dujardini piRNAs show a prominent ten nucleotide overlap, with the tenth nucleotide of the 5′-most piRNA showing a bias towards (A), consistent with ping-pong amplification.  5′ monophosphate and 5′ triphosphate small RNA sequencing from P. varius (Nematomorpha) showing absence of longer 5′ U species and no evidence of 5′ triphosphorylated small RNAs.(A) 5′ monophosphate small RNAs in the tardigrade (PDF)Click here for additional data file.S4 FigP. pacificus (clade V). (C) 5′ mono and triphosphate sequencing of small RNAs from N. brasiliensis (clade V).  5′ monophosphate only (D) and 5′ mono and triphosphate (E) sequencing of small RNAs from E. brevis (clade II) collected from Sylt in Germany. (F) 5′ mono and triphosphate sequencing of small RNAs from O. rectangula (clade II) collected from Vancouver in Canada.  5′ monophosphate only (G) and 5′ mono and triphosphate (H) sequencing of small RNAs from R. culicivorax (clade I). (I) Collapsing the R. culicivorax sequences so that only unique sequences are represented removes the prominent 26T peak; this represents one abundant sequence and is thus not likely to be a piRNA, consistent with the absence of PRG-1/Piwi in this species. 5′ monophosphate only (A) and 5′ mono and triphosphate (B) sequencing of small RNAs from (PDF)Click here for additional data file.S5 FigC. elegans PRG-1 compared to the median and interquartile range of the best hit for all C. elegans proteins. Members of the Piwi subfamily are shown in red  Blastp score in bits/length for the best hit to  red see  and memb red see . (B) His(PDF)Click here for additional data file.S6 FigG. pallida. (B) Collapsing to unique sequences retains the bias towards antisense orientation in both G. pallida and B. malayi.  5′ monophosphate only sequencing shows evidence of 23 nt 5′ monophosphate small RNAs aligning antisense to transposon sequences in both B. malayi (C) and G. pallida (D), indicating that Dicer recognises transposons in these organisms.(A) 5′ mono and 5′ triphosphate sequencing demonstrates that 22–26 nt triphosphorylated small RNAs align predominantly antisense to transposons in (PDF)Click here for additional data file.S7 Fig(A) Dicer cleavage of dsRNA originating from transcription of transposon sequences could feed into the small RNA pathway. (B) RNA dependent RNA polymerase could generate long dsRNA using the transposon sequence as a template, which would then be processed by Dicer to generate siRNAs.(PDF)Click here for additional data file.S8 FigC. elegans 21U-RNAs are specifically protected against oxidation whilst T. spiralis 23–25 nt siRNAs are lost following oxidation. The peak at 28–30 nt in T. spiralis reflects two abundant ribosomal RNA sequences as shown by its loss upon collapsing the sequence data to unique sequences (far right hand panel).  Cluster analysis across the genome shows that regions with high density of piRNAs found in C. elegans and D. melanogaster are not found for T. spiralis 23–25 nt siRNAs. (B) Shows genome-wide distribution of T. spiralis 23–25 nt siRNAs, C. elegans piRNAs, and D. melanogaster piRNAs. Reads are binned in 100 kb windows across the genome and coloured by contigs or chromosomes according to the genome assembly, with the contigs or chromosomes sorted in order of the total number of small RNAs mapping to them. (C) Shows the cumulative fraction of sequences in (B) that are found in regions with greater than or equal to the density indicated on the x-axis. C. elegans and D. melanogaster both have more sequences mapping to higher density regions than T. spiralis does.(A) Sequencing of small RNAs following treatment with 200 mM sodium periodate compared to control samples shows that (PDF)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


In eukaryotic normal diploid cells, transcription must be accomplished in an efficient and faithful manner. The three nuclear RNA polymerases, transcription factors, chromatin regulators, and signaling pathways are among the key components that control gene expression. The molecular mechanisms by which these regulators control expression of individual genes have been studied extensively and are reviewed elsewhere ,2. RecenIn this issue of Cell & Bioscience, we have provided some evidences that deregulation of ribosomal gene (rDNA) transcription is a feature of cancer and other human disorders . Criticaet al. presented in their review entitled “Perturbations at the ribosomal genes loci are at the centre of cellular dysfunction and human disease” multiple aspects of rDNA functions. These functions not only include the relationship between RNA polymerase I (Pol I) transcription and proliferative property, but also the role of Pol I transcription in mediating heterochromatin structure and function, global gene expression and DNA damage response. Their review casts nucleolus as a central hub for coordination of stress responses. Notably, deregulation of Pol I transcription is required for malignant transformation and can be targeted with small molecule inhibitors to treat cancer [Diesch t cancer .et al. reviewed the principles and techniques of the recent NGS-based studies that link RNA editing to various aspects of post-transcriptional RNA processing, alternative splicing, transcript stability and localization. Their review also pointed out the possibility that NGS data may be applied for further interrogation of the “RNA editing codes”, at which functional outcome could be explored in a global manner [Liu and associates summarized current technological advances in genomics methods in the study of functional impact of RNA editing and the adenosine deaminse acting on RNA (ADAR) family of enzymes on the regulation of gene expression in their review. In the past few years, research in the field of A-to-I RNA editing has been accelerated dramatically by the development of next generation sequencing (NGS) technology, which has expanded the landscape of RNA editome as well as our understanding of its regulation. Liu l manner .et al. emphasized on the transcriptional activity of HIF-α modulated by the histone methyltransferase G9a mediated methylation of non-histone proteins such as Reptin and Pontin in hypoxia. This review provides useful information for future therapeutic potentials by targeting the methylation of non-histone proteins under hypoxic conditions [Baxter and colleagues systematically reviewed the alterations and mechanisms of DNA methylation and histone modifications in cancer. They described major findings on DNA demethylation resulting from replication-dependent passive dilution of 5-methylcytosine and active DNA demethylation catalyzed by Ten-eleven translocation (TET) family proteins. Baxter nditions .DNMT genes by p53, RB and FOXO3a transcriptional regulators and corepressors. Interestingly, overexpressed MDM2 may induce DNMT1, DNMT3A, and DNMT3B expression by negative control over p53, RB and FOXO3a. In addition, the low expressions of miRNAs 29 s, 143, 148a and 152 are associated with overexpression of DNMTs in various cancers. In this review, several important post-translational modifications including acetylation and phosphorylation in the control of protein stability and activity of the DNMTs especially DNMT1 are discussed [Lin and Wang evaluated in their review entitled “Dysregulated transcriptional and post-translational control of DNA methyltrasferases in cancer” the deregulation mechanisms of DNMTs. They focused on the transcriptional repression controls on Due to the broad nature of transcriptional regulation and its misregulation in diseases, it is not our intention to cover all major aspects of this active research area in this single issue. However, we hope that these articles provide readers with insightful information of how alterations of Pol I transcription, RNA editing, non-histone methylation, and DNA methylation regulations may be used as disease biomarkers and for targeted therapies.


In vitro, these proteins were found to hydrolyze the enamine/imine intermediates generated from serine or threonine, and were renamed Reactive Intermediate Deaminase A (RidA). RidA was recently discovered in Arabidopsis thaliana, and by deaminating the toxic enamine/imine intermediates, it prevents the inactivation of many functionally important pyridoxal 5′-phosphate (PLP)-containing enzymes in plants such as branched-chain aminotransferase BCAT (IlvE). In this study, we determined the crystal structure of Arabidopsis thaliana RidA in the apo form, as well as RidA complexed with the ligand pyruvate. RidA forms the trimeric, barrel-like quaternary structure and inter-subunit cavities, and resembles most RidA family members. Each pyruvate molecule binds to the interface between two subunits, and the recognition of pyruvate is achieved by the interactions with R165 and T167. From sequence alignment and structural superposition, we identified a series of key residues responsible for the trimer assembly, whose importance was confirmed by enzymatic assays. This study provides structural insight into RidA functions in plants.The YjgF/YER057c/UK114 family proteins are highly conserved across all three domains of life, and most of them currently have no clearly defined biological roles.  Escherichia coli, yeast, and goat respectively. These small proteins (~15 kDa) are found across all three domains of life with a signature of 6–9 conserved amino acids, and to date, hundreds of putative members have been identified by bioinformatic analyses. They appear to play important roles in highly diverse biological processes, many of which are poorly understood despite their universal presence12456Salmonella enterica was found to deaminate the enamine/imine intermediates generated by pyridoxal 5′-phosphate (PLP)-dependent serine/threonine dehydratases, and was renamed RidA (reactive intermediate/imine deaminase A)9The YjgF/YER057c/UK114 proteins were named after proteins YjgF, YER057c, and UK114, which were found in roteins ~ kDa are Arabidopsis thaliana and maizeArabidopsis thaliana RidA (AtRidA) is targeted to chloroplasts. By converting the reactive enamine/imines to harmless 2-oxoacids, RidA preempts damage to BCAT3 and ensures that the isoleucine biosynthesis can proceed.In 2014, RidA proteins were identified in A recent phylogenetic analysis suggested that RidA could be divided into seven subfamilies (Rid1 to Rid7) besides the archetypal RidA subfamily. These subfamilies are generally found in bacteria, and coexist with each other in the same organism including RidA. The Rid1 to Rid3 subfamilies contain a conserved arginine residue known to be essential for the imine-hydrolyzing activity in the archetypal RidA and Rid2 subfamilies. By contrast, the Rid4 to Rid7 subfamilies appear not to hydrolyze imines, and their functions are yet to be identifiedEscherichia coli TdcF in complexes with a variety of ligands including 2-oxobutanoate were solved, which provided great insight into the substrate recognition mechanism of RidA family of proteins1820A few crystal structures have been reported for the YjgF family proteins 18192021In this study, we determined the crystal structures of apo-AtRidA and its complex with pyruvate, and analyzed its structural basis for ligand recognition. AtRidA retains the typical domain as observed in many other RidA members. Using sequence alignment and structural superposition methods, we identified critical residues for trimer assembly as well as catalysis, and their importance to enzyme functions was evaluated by size-exclusion chromatography analyses and enzymatic assays.The N-terminus of RidA is predicted to harbor a disordered region, which may function as a transit peptide targeting RidA to chloroplastsHomo sapiens (PDB code 1ONI)Capra hircus (PDB code 1NQ3)Pyrococcus horikoshii , and a putative endoribonuclease l-PSP from Entamoeba histolytica  respectively. AtRidA-S68 shares ~54% sequence identity with its closest structural neighbor hp14.5, with a root-mean-square deviation (RMSD) of 0.71 Å over 107 Cα atoms  by the deamination activities of RidA. The intermediates are highly unstable and have short lifetimes, which are unsuitable for crystallization. Therefore we tried both 2-oxoacid products for cocrystallization studies, and we obtained the complex structure of AtRidA bound by pyruvate.P1. After structure determination, we found that there were three monomers present in the asymmetric unit. In each monomer of the final model, residues S80-L187 are resolved without internal disorder. The three monomers within the asymmetric unit form the trimeric barrel, which is almost identical to that formed by the apoprotein, with an RMSD of only 0.27 Å  was amplified from Arabidopsis cDNA. After double digestion by the NdeI and XhoI restriction enzymes, the PCR product was ligated into a modified pET-28a (+) vector (Novagen) vector with an engineered PreScission protease cleavage site (recognition peptide LEVLFQGP) preceding the His6-tag. For crystallization purposes, N-terminal truncated fragments with various lengths were cloned into pET-28a (+) using the same sites. The primers used in this study were shown in Escherichia coli strain BL21 (DE3) cells. To overexpress the protein, 10 ml overnight culture was used to inoculate 1 L fresh culture medium containing 30 μg/ml kanamycin and grown at 37 °C until the log phase was reached (OD600 = 0.8). The expression of RidA-S68 was induced by isopropyl β-D-1-thiogalactopyranoside (IPTG) at a final concentration of 0.2 mM, at 25 °C for 18 hours.The full-length Cells were harvested by centrifugation at 3,030 g for 20 min at 4 °C, and resuspended in pre-chilled nickel-nitrilotriacetic acid (Ni–NTA) buffer A  and 1 mM β-mercaptoethanol) before lysis. The cells were disrupted by sonication, and the supernatant was collected by centrifugation at 23,500 g for 60 min at 4 °C. The supernatant was mixed with the pre-equilibrated Ni–NTA affinity resin (Qiagen) at 4 °C for 1 h. The bound protein was washed with 10 column volumes of buffer A, and the target protein was then eluted with Ni-NTA buffer B, which contains the same components of buffer A plus 250 mM imidazole. The his6-tag at the N-terminus was cleaved off by treating with the PreScission protease overnight in the presence of 5 mM β-mercaptoethanol, and the reaction mix was subsequently applied onto a Histrap column  to remove uncut protein. The unbound portion was pooled, dialyzed to a buffer containing 20 mM Tris-HCl (pH 8.0), 150 mM NaCl and 1 mM DTT for two hours. The protein was further concentrated to 10 mg/ml, then flash frozen in liquid nitrogen and stored at −80 °C.Arabidopsis thaliana threonine dehydratase was described in a previous referenceAll point mutations for RidA activity assays were created by QuikChange. The RidA-S68/pET28a (+) plasmid (the fragment represents residues S68–L187) was used as the template. All mutations were confirmed by DNA sequencing and the integrity of the expressed proteins was assayed by a Superdex 75 size-exclusion column. 10% (v/v) glycerol was added to the purified mutants before they were flash frozen. The cloning, expression and purification of H3 and the crystal diffracted to 2.0 Å resolution with a completeness of 99.87%. Cell content analysis suggested that each asymmetric unit contains one monomer. To solve the structure, coordinates of a putative endoribonuclease (TM0215) structure (PDB entry 2B33) were used as the search model for molecular replacement. The initial model was extended by PHENIX using the autobuild optionfree = 21.2%) for the final model, which was validated by SFCHECK and Molprobity29P1. The crystal diffracted to 2.3 Å resolution and each asymmetric unit contains three monomers. The R factor was 20.4% (Rfree = 23.8%) for the final model. The Ramachandran plots of the final models have 96.2%, 3.8%, 0% residues in the most favorable, generously allowed and disallowed region for the apoenzyme. The data collection and refinement statistics are listed in http://www.pymol.org). The secondary structure of RidA-S68 was prepared by ESPriptAmong the several constructs we tested, the RidA-S68 construct allowed us to produce diffracting crystals. Crystals were obtained using the sitting drop vapor diffusion method in a 96-well plate after ten days at 25 °C. The reservoir solution contains 18% PEG 3350, 0.1 M MES, pH 6.0. The crystals of RidA with ligand pyruvate were obtained by soaking the crystals of the apoprotein with 20 mM pyruvate for 1 hour. The best crystals were transferred to a cryo-protectant solution (20% (v/v) glycerol plus the reservoir solution) and were flash frozen in liquid nitrogen. Native data for AtRidA in the apo form or in complex with pyruvate were collected from frozen crystals at −173 °C using an in-house Oxford Diffraction Xcalibur Nova diffractometer. The data were processed and scaled using CrysAlisPro  and SCALA from the CCP4 suiteet al.no RidA − Amut)/(Ano RidA − ARidA WT) * 100%, where Ano RidA, ARidA and ARidA WT are the absorbance values at 248 nm in the absence of the enzyme, in the presence of the RidA mutants and the RidA WT at the time point 90 s, respectively.The activity assays followed a previous protocol described by Niehaus Accession codes: The atomic coordinates and structure factors have been deposited in the Protein Data Bank with accession numbers 5HP7 and 5HP8 for the apo and complex structure of AtRidA respectively.How to cite this article: Liu, X. et al. Crystal structures of RidA, an important enzyme for the prevention of toxic side products. Sci. Rep.6, 30494; doi: 10.1038/srep30494 (2016).


Lying is a common occurrence in social interactions, but what predicts whether an individual will tell a lie? While previous studies have focused on personality factors, here we asked whether lying tendencies might be transmitted through social networks. Using an international sample of 1,687 socially connected pairs, we investigated whether lying tendencies were related in socially connected individuals, and tested two moderators of observed relationships. Participants recruited through a massive open online course reported how likely they would be to engage in specific lies; a friend or relative responded to the same scenarios independently. We classified lies according to their beneficiary , and their directness (lies of commission vs. omission), resulting in four unique lying categories. Regression analyses showed that antisocial commission, antisocial omission, and prosocial commission lying tendencies were all uniquely related in connected pairs, even when the analyses were limited to pairs that were not biologically related. For antisocial lies of commission, these relationships were strongest, and were moderated by amount of time spent together. Randomly paired individuals from the same countries were also related in their antisocial commission lying tendencies, signifying country-level norms. Our results indicate that a person's lying tendencies can be predicted by the lying tendencies of his or her friends and family members. In all verbal interactions, people must negotiate their desire to tell the truth with their desire to benefit themselves and their desire to please others. When these competing forces come into conflict, one way to resolve the tension is to lie. We define lies as statements intended to mislead others Existing research exploring what leads people to lie in daily life has focused on personality factors. This research has produced mixed results, with early research finding that low anxiety predicts lying Are certain types of lying more likely than others to be related among individuals from the same social networks? Perhaps the most common classification of lying distinguishes between antisocial lying  and prosocial lying  By one line of reasoning, individuals may be attuned to the prosocial lying behavior of others with whom they interact. Scholars have suggested that two fundamental principles guide human communication: the principle of quality – that is, relaying information that is truthful – and the principle of general cooperation – that is, maintaining amiable relationships An alternative yet non-exclusive possibility is that individuals are attuned to others' antisocial lying behavior. Gino, Ayal, and Ariely found that observing an obvious display of dishonesty increased participants' own dishonest behavior In addition, cross-cultural experiments in economics point to cultural differences in norms for antisocial behavior. Cooperative behavior in a public goods game has been found to vary substantially across cultures Another important distinction in considering lying tendencies in social networks concerns the directness of lies. We distinguish between lies of commission, which involve directly stating something the speaker knows to be false, and lies of omission, which lead the listener to a false belief without directly stating something known to be false. This distinction resembles the two principle factors identified by Phillips, Meek, and Vendemia in their investigation of the underlying structure of deceptive behavior We presented participants with a survey involving specific, everyday scenarios that might invoke dishonesty, and asked them how likely they would be to lie in these scenarios. Given the inherent difficulties of measuring everyday lies directly, survey methods are commonly used to assess individual lying tendencies In order to investigate whether individuals in social networks have similar lying tendencies, we studied pairs of individuals who were in some way connected to one another. By recruiting students through a massive open online course (MOOC), and inviting them to share the survey with a friend or family member, we obtained a large international sample of connected pairs of individuals who completed the survey independently.Our first research question was whether individuals' lying tendencies could be predicted by the lying tendencies of their friends, partners, and family members, for four specific lying tendencies . Our second research question was whether social transmission was a plausible explanation for any observed relationships. To address the second question, we asked participants to indicate whether they were biologically related to their connection, so that we could compare effects for biologically related and non-biologically related pairs. We also asked each individual to report the closeness of their relationship, as well as the amount of time they spent with the other person, in order to assess whether these variables moderated social transmission. Another question of interest was whether relatedness in lying tendencies differed for specific relationships . Lastly, we explored the reach of social transmission by analyzing whether lying tendencies were related among individuals from the same countries.The study protocol was approved by Duke University's Institutional Review Board for research with human subjects. All participants indicated their consent to participate after reading the approved consent form. In accordance with the ethics protocol, those enrolled in an online course provided consent at the beginning of the course, and those not enrolled provided consent at the time of the survey.Survey participants were recruited via a massive open online course (MOOC) in behavioral economics. During Week 3 of the course, enrolled students were invited to take the survey themselves, and to forward the survey link to someone they knew – a friend, acquaintance or family member. We provided students with an email script, including a link to the survey, to invite this person of their choosing to complete the survey. The decision of who to invite was left to each individual student.Participants were provided a randomized ID code to include in the email to their friend or family member. Both parties were instructed to include this ID code in their survey, which allowed us to link the MOOC students' data with their friends'/family members' data, in pairs.Initially, 4685 MOOC students, and 3850 of their friends or family members completed the survey. However, only participants for whom at least one other participant entered an identical ID code were included in our final sample. We also excluded participants for failing to respond to all questions in a given category, and for entering impossible values in an earlier task. Forty-seven MOOC students had multiple contacts complete the survey; for these participants, we selected the first survey that was submitted with the identical ID code in order to ensure that no participant was represented in more than one pair.This filtering process left us with a sample of 1,973 pairs of participants. Of these, we excluded participants whose responses regarding their relationship to one another did not match.  Two hundred forty-five participant pairs (12.4%) were excluded for non-matching responses regarding their relationship, and 83 (4.2%) were excluded for non-matching responses to whether they were biologically related (42 of these exclusions were redundant). After excluding these pairs, we were left with a final sample of 1,687 participant pairs from 94 countries.All participants completed the survey on their own time over the World Wide Web, as part of a larger survey. Participants answered 16 questions regarding how likely they would be to lie in various hypothetical scenarios. The question scenarios represented four distinct categories of lying: lying by antisocial commission , lying by antisocial omission, , lying by prosocial commission , and lying by prosocial omission  They then indicated whether they were biologically related to this person. Next, they were asked to indicate the number of waking hours per week they spent with the person (either in person or on the phone). Finally, they indicated how close they felt to the other person by selecting the appropriate diagram from the Inclusion of Other in the Self scale To examine relationships across the different types of lying behavior, we first created lying indexes for each of the four types of lying by computing the average of the four items of each type. Thus, each participant had a single index for antisocial lying by commission, antisocial lying by omission, prosocial lying by commission, and prosocial lying by omission.We then paired the data from MOOC participants with the data from their chosen friends or relatives. This allowed us to test whether the MOOC participants' lying indexes predicted the lying indexes of their friends and relatives, and vice versa, using multiple linear regression analyses.We labeled the MOOC student in each pair as P1, and the friend or relative who received the survey from a MOOC student as P2. β = .196, p<.001), while the other three subscales' betas were not. When P1 antisocial omission scores were entered as the dependent variable, the beta coefficient for P2 antisocial commission scores was significant , while the other three subscales' betas were not. Similarly, when P1 prosocial commission scores were entered as the dependent variable, the beta coefficient for P2 prosocial commission scores was significant , while other three subscales' betas were not. Lastly, in contrast to the other subscales, when we entered P1 prosocial omission scores as the dependent variable, none of the P2 subscales were significant predictor variables.Our first research question was whether participants' lying tendencies predicted the lying tendencies of their connections, for four distinct types of lies: antisocial commission, antisocial omission, prosocial commission, and prosocial omission. We ran four regression analyses, entering each P1 subscale one at a time as the dependent variable, with the four P2 subscales entered as independent variables see . When P1ps<.001), and a similar overall pattern of results  or were not  biologically related (leaving out one pair where both participants indicated “I don't know”). We re-ran the same series of regression analyses  on each subsample. In general, our observed effects held across biologically and non-biologically related pairs , antisocial omission , and prosocial commission ; similar effects were observed in the replication regression analyses. Although beta values were somewhat higher for biologically related pairs , when we compared these values by entering biological relationship as a dummy variable, interacting it with the predictors and including these terms in the original regression analyses, we found that the differences in beta values were not significant. The only exception was for prosocial commission, where the beta value was significantly higher for biologically related pairs in the replication analysis (p = .03), but not in the original analysis (p = .10). Overall, these results suggest that similarities in lying tendencies cannot be fully explained by genetic relatedness.To test for whether the observed effects were significant in socially connected pairs who did not share genetic material, we next divided our sample according to whether individuals indicated that they were  how much time they spent with that person (indicated on a drop-down menu with six options ranging from less than 1 hour/week to 20+ hours/week), and 2) how close participants' felt to the other person who completed the survey , and for P2 scores predicting P1 scores . In contrast, time spent together did not moderate the antisocial omission or prosocial commission relationships . Though we cannot draw strong conclusions from correlational data, these findings are in line with a social transmission explanation of the observed relationships in antisocial commission lying tendencies.Following this procedure for time spent together, we observed a moderating effect on the antisocial commission relationship; examination of conditional effects revealed that the more time pairs spent together, the more strongly antisocial commission lying tendencies were related. This effect was significant for P2 antisocial commission scores predicting P1 antisocial commission scores , but the reverse moderation was not significant . In addition, we found that relationship closeness had a marginally significant moderating effect on the regression of P1 prosocial commission scores on P2 prosocial commission scores , though the reverse moderation was again not significant . Relationship closeness did not moderate the antisocial omission relationships .The evidence for moderation of relationship closeness was less clear. We found relationship closeness to significantly moderate the regression of P2 antisocial commission scores on P1 antisocial commission scores  for participant pairs in each relationship category. N = 220) were significantly related in their tendencies to tell prosocial lies of commission , but were not significantly related in their tendencies to tell antisocial lies of commission. Cavalli-Sforza and colleagues distinguished between three types of cultural transmission : horizontal transmission, i.e. transmission individuals of the same generation; vertical transmission, i.e. transmission from parent to child; and oblique transmission, i.e. transmission from individuals of an older generation to individuals of a younger generation We first ran the regression analyses on parent-child pairs. Parents and children  beta values for the matched subscales of their children (P1) and child subscale beta values (P1) for the matched subscales of their parents (P2), and then computed the differences between these values see . While tN = 200) were significantly related in their tendencies to tell antisocial lies of commission, but not in any other lying tendencies. We repeated the analysis described in the paragraph above for older and younger siblings . The beta value was 0.044 units higher for older siblings' scores predicting younger siblings' scores than vice versa, suggesting that younger children may learn more from their older siblings than the other way around.In contrast to our parent-child pairs, siblings  and unmarried romantic partners (N = 256) were both significantly related in their tendencies to tell antisocial lies of commission (ps<.01); the predictive relationships for prosocial lies of commission were significant in one direction (ps<.01) but not the other (ps>.07). Examining the regressions for friend pairs (N = 466), P1 antisocial commission scores predicted P2 antisocial commission scores (p = .02) but the reverse relationship was not significant (p = .15). Antisocial omission scores were predictive in both directions at a significant threshold of p<.05. Finally, for colleagues (N = 54), no beta values were significant for corresponding subscales scores; however, statistical power was compromised for colleagues due to the small sample size.Among non-biologically related pairs, we observed related lying tendencies in spouses, in romantic partners, and in friends. Spouses , and vice versa . None of the other beta coefficients were significant in these regression analyses. Thus, similarity in antisocial lying tendencies appears to reach across a country, suggesting cultural norms for this type of verbal dishonesty.Beyond examining the relatedness of lying behavior across various first-degree relationships, our dataset allowed us to ask whether similarity in lying tendencies extends to a whole society. We tested whether individuals from the same countries were related in their lying behaviors. Participants were grouped by country of citizenship, and then randomly shuffled within countries, so that each participant was paired with another random participant from his or her country.  We then re-ran the eight regression analyses from N = 1,761) were more likely to tell prosocial lies of commission than men ; this difference was significant for both P1   = −5.650, p<.001) and P2   = −7.999, p<.001) participant samples. There were no gender differences for any of the other types of lying, with the exception of P1 men reporting slightly higher likelihood of telling prosocial lies of omission than P1 women   = 3.155, p = .002). P2 men and women did not differ in their prosocial lying by omission (p>.99).Previous research has found that women are more likely to tell prosocial lies than men ps>.10). Comparing relatedness among female-only (N = 391) and male-only (N = 230) pairs across the four subscales, antisocial omission tendencies were more strongly related in male-only pairs (t(614)  = −2.408, p = .02 in one direction, t(614)  = −2.068, p = .04 in other direction). The strengths of the relationships did not significantly differ between female-only and male-only pairs for the other lying tendencies.In spite of a higher overall level of prosocial commission lying in women, prosocial commission lying was not related in female-only pairs  friend pairs. Antisocial omission tendencies were significantly related in parent-child and friend pairs. Finally, prosocial lying tendencies were significantly related in parent-child pairs (in both directions), spousal pairs (in one direction), and romantic partner pairs (in one direction). Although women were more likely to tell prosocial lies of commission than men, as others have observed We approached this study with the question of whether lying tendencies spread through social transmission. We found evidence that individuals from the same social networks are related in their lying tendencies, with particularly strong and consistent relationships for tendencies to tell antisocial lies of commission. Of course, if individuals within social networks are related in their tendencies to tell antisocial lies, prosocial lies, or both types of lies, social transmission is only one potential explanation. Causality could also apply in reverse; that is, individuals with similar lying tendencies may choose to affiliate or gravitate toward the same social contexts. For example, individuals with higher tendencies to tell antisocial lies may be drawn to similar pastimes, or may be drawn to one another as romantic partners. While selection effects would not apply biologically related family pairs, in these pairs, observed effects may be due to genetic predispositions rather than social influence. Furthermore, whether or not individuals are biologically related, similarity in lying tendencies could be explained by a third variable, such as personality profiles.Further research is needed to illuminate the extent to which social transmission is a likely explanation for the observed similarities in lying tendencies. Evidence supporting social transmission was strongest for antisocial commission, as moderation analyses showed that the more time individuals spent together, the more strongly their antisocial commission lying tendencies were related. Furthermore, assuming that citizenship is relatively intransient, the finding that randomly paired citizens from the same country show related antisocial commission lying tendencies is difficult to explain with selection effects. However, social transmission, if it extends beyond local networks, could explain cultural standards of dishonesty Our findings suggest several additional avenues for future research. First, we found that parents and children showed a unique constellation of related lying tendencies, with the strongest similarity for prosocial commission. Although we did not find strong evidence that parents' tendencies were more predictive of their children's tendencies than vice versa, it is worth noting that the present sample consisted entirely of adults. Conceivably, the nature (and degree) of the relationships between parents' and children's lying tendencies may evolve as young children mature and gain independence from their parents, raising interesting questions for developmental or longitudinal research. The degree to which parent-child (and sibling) similarities reflect genetics vs. social transmission might also be explored. Second, given the observed  relationships for prosocial commission lying tendencies in individuals who were married or romantically involved, future research might also explore how prosocial lying impacts relationship outcomes. Third, our data imply that tendencies to tell lies of commission may be more coherent than tendencies to tell lies of omission. Previous research has pointed to heterogeneity in whether acts of omission are considered immoral The pattern of results we observed across different relationships presents a somewhat complicated picture of the potential transmission of lying. Antisocial commission lying tendencies were significantly related across most, but not all relationship pairs. In some cases, lying tendencies were related in one analysis (e.g. P1 scores predicting P2 scores) but not in the reverse analysis (e.g. P2 scores predicting P1 scores). Given that three of the four lying tendencies were significantly related in the larger subsamples of biologically related and non-biologically related pairs, it is difficult to say whether non-significant findings for specific relationship pairs reflect true null effects or insufficient power for detecting true effects. However, we believe the results of this study are ripe for generating testable theories regarding how and when social transmission of dishonesty operates.If different types of dishonesty indeed spread through social transmission, experiments can help to shed light on the mechanics behind these processes. For example, if social transmission occurs for antisocial lying, what role does communication play in this process? Is face-to-face communication necessary for social transmission, or can it also occur through online social networking mediums? To address such questions experimentally, researchers might instill prosocial or antisocial values in certain individuals within lab-based social networks, manipulate the nature of communication that is possible these social networks, and measure the adoption of instilled values by others in the networks.The question of how dishonesty spreads through social networks is relevant to relationships, organizations, and society at large. Individuals may not consider that their own minor lies contribute to a broader culture of dishonesty. Our findings are noteworthy given that honesty has been identified as a universal value File S1Lying Tendencies Survey.(DOCX)Click here for additional data file.File S2Main Regression Analyses. Linear regression analyses for P2 subscale scores predicting each P1 subscale, and for P1 subscale scores predicting each P2 subscale.(DOCX)Click here for additional data file.File S3Moderation Regression Analyses. Linear regression analyses testing for moderation effects between each of two variables of interest (time spent together and relationship closeness) and each of the three subscales that showed significant relationships between P1 and P2 pairs in the main regression analyses . A significant interaction term indicates moderation.(DOCX)Click here for additional data file.File S4Parent-Child and Sibling Regression Betas. Summary of beta values from linear regression analyses in which parent subscales are predictors for child subscales and vice versa, or older sibling subscales are predictors for younger sibling subscales and vice versa. The original eight regression analyses were run on parent-child pairs and on older sibling-younger sibling pairs. The tables below present beta values from one subscale  predicting beta values from that same subscale  when the four subscales were entered together as predictors. The differences in beta values are also reported.(DOCX)Click here for additional data file.