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Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10−14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner’s Curse (p < 10−16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium. [ABSTRACT FROM AUTHOR]

The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict) originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRS) are designed to serve as single summary measures that are easy to construct, condensing information from a large number of genetic variants associated with a disease. They have been used for stratification and prediction of disease risk. The primary focus of this paper is to demonstrate how we can combine PRS and electronic health records data to better understand the shared and unique genetic architecture and etiology of disease subtypes that may be both related and heterogeneous. PRS construction strategies often depend on the purpose of the study, the available data/summary estimates, and the underlying genetic architecture of a disease. We consider several choices for constructing a PRS using data obtained from various publicly-available sources including the UK Biobank and evaluate their abilities to predict not just the primary phenotype but also secondary phenotypes derived from electronic health records (EHR). This study was conducted using data from 30,702 unrelated, genotyped patients of recent European descent from the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort within Michigan Medicine. We examine the three most common skin cancer subtypes in the USA: basal cell carcinoma, cutaneous squamous cell carcinoma, and melanoma. Using these PRS for various skin cancer subtypes, we conduct a phenome-wide association study (PheWAS) within the MGI data to evaluate PRS associations with secondary traits. PheWAS results are then replicated using population-based UK Biobank data and compared across various PRS construction methods. We develop an accompanying visual catalog called PRSweb that provides detailed PheWAS results and allows users to directly compare different PRS construction methods. [ABSTRACT FROM AUTHOR]

Facial attractiveness is a complex human trait of great interest in both academia and industry. Literature on sociological and phenotypic factors associated with facial attractiveness is rich, but its genetic basis is poorly understood. In this paper, we conducted a genome-wide association study to discover genetic variants associated with facial attractiveness using 4,383 samples in the Wisconsin Longitudinal Study. We identified two genome-wide significant loci, highlighted a handful of candidate genes, and demonstrated enrichment for heritability in human tissues involved in reproduction and hormone synthesis. Additionally, facial attractiveness showed strong and negative genetic correlations with BMI in females and with blood lipids in males. Our analysis also suggested sex-specific selection pressure on variants associated with lower male attractiveness. These results revealed sex-specific genetic architecture of facial attractiveness and provided fundamental new insights into its genetic basis. [ABSTRACT FROM AUTHOR]

The BARD1 protein, which heterodimerizes with BRCA1, is encoded by a known breast cancer susceptibility gene. While several BARD1 variants have been identified as pathogenic, many more missense variants exist that do not occur frequently enough to assign a clinical risk. In this paper, whole exome sequencing of over 10,000 cancer samples from 33 cancer types identified from somatic mutations and loss of heterozygosity in tumors 76 potentially cancer-associated BARD1 missense and truncation variants. These variants were tested in a functional assay for homology-directed repair (HDR), as HDR deficiencies have been shown to correlate with clinical pathogenicity for BRCA1 variants. From these 76 variants, 4 in the ankyrin repeat domain and 5 in the BRCT domain were found to be non-functional in HDR. Two known benign variants were found to be functional in HDR, and three known pathogenic variants were non-functional, supporting the notion that the HDR assay can be used to predict the clinical risk of BARD1 variants. The identification of HDR-deficient variants in the ankyrin repeat domain indicates there are DNA repair functions associated with this domain that have not been closely examined. In order to examine whether BARD1-associated loss of HDR function results in DNA damage sensitivity, cells expressing non-functional BARD1 variants were treated with ionizing radiation or cisplatin. These cells were found to be more sensitive to DNA damage, and variations in the residual HDR function of non-functional variants did not correlate with variations in sensitivity. These findings improve the understanding of BARD1 functional domains in DNA repair and support that this functional assay is useful for predicting the cancer association of BARD1 variants. [ABSTRACT FROM AUTHOR]

Cell intercalation is a highly directed cell rearrangement that is essential for animal morphogenesis. As such, intercalation requires orchestration of cell polarity across the plane of the tissue. CDC-42 is a Rho family GTPase with key functions in cell polarity, yet its role during epithelial intercalation has not been established because its roles early in embryogenesis have historically made it difficult to study. To circumvent these early requirements, in this paper we use tissue-specific and conditional loss-of-function approaches to identify a role for CDC-42 during intercalation of the Caenorhabditis elegans dorsal embryonic epidermis. CDC-42 activity is enriched in the medial tips of intercalating cells, which extend as cells migrate past one another. Moreover, CDC-42 is involved in both the efficient formation and orientation of cell tips during cell rearrangement. Using conditional loss-of-function we also show that the PAR complex functions in tip formation and orientation. Additionally, we find that the sole C. elegans Eph receptor, VAB-1, functions during this process in an Ephrin-independent manner. Using epistasis analysis, we find that vab-1 lies in the same genetic pathway as cdc-42 and is responsible for polarizing CDC-42 activity to the medial tip. Together, these data establish a previously uncharacterized role for polarized CDC-42, in conjunction with PAR-6, PAR-3 and an Eph receptor, during epithelial intercalation. [ABSTRACT FROM AUTHOR]

Whether codon usage fine-tunes mRNA translation in mammals remains controversial, with recent papers suggesting that production of proteins in specific Gene Ontological (GO) pathways can be regulated by actively modifying the codon and anticodon pools in different cellular conditions. In this work, we compared the sequence content of genes in specific GO categories with the exonic genome background. Although a substantial fraction of variability in codon usage could be explained by random sampling, almost half of GO sets showed more variability in codon usage than expected by chance. Nevertheless, by quantifying translational efficiency in healthy and cancerous tissues in human and mouse, we demonstrated that a given tRNA pool can equally well translate many different sets of mRNAs, irrespective of their cell-type specificity. This disconnect between variations in codon usage and the stability of translational efficiency is best explained by differences in GC content between gene sets. GC variation across the mammalian genome is most likely a result of the interplay between genome repair and gene duplication mechanisms, rather than selective pressures caused by codon-driven translational rates. Consequently, codon usage differences in mammalian transcriptomes are most easily explained by well-understood mutational biases acting on the underlying genome. [ABSTRACT FROM AUTHOR]

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants. [ABSTRACT FROM AUTHOR]

Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn’s disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of pervasive small but replicating effects in CD and SZ on genomic control and power. Finally, we conclude that, despite having very similar estimates of variance explained by genotyped SNPs, CD and SZ have a broadly dissimilar genetic architecture, due to differing mean effect size and proportion of non-null loci. [ABSTRACT FROM AUTHOR]

Species often encounter, and adapt to, many patches of similar environmental conditions across their range. Such adaptation can occur through convergent evolution if different alleles arise in different patches, or through the spread of shared alleles by migration acting to synchronize adaptation across the species. The tension between the two reflects the constraint imposed on evolution by the underlying genetic architecture versus how effectively selection and geographic isolation act to inhibit the geographic spread of locally adapted alleles. This paper studies the balance between these two routes to adaptation in a model of continuous environments with patchy selection pressures. We address the following questions: How long does it take for a novel allele to appear in a patch where it is locally adapted through mutation? Or, through migration from another, already adapted patch? Which is more likely to occur, as a function of distance between the patches? What population genetic signal is left by the spread of migrant alleles? To answer these questions we examine the family structure underlying migration–selection equilibrium surrounding an already adapted patch, treating those rare families that reach new patches as spatial branching processes. A main result is that patches further apart than a critical distance will likely evolve independent locally adapted alleles; this distance is proportional to the spatial scale of selection (, where σ is the dispersal distance and sm is the selective disadvantage of these alleles between patches), and depends linearly on log(sm/μ), where μ is the mutation rate. This provides a way to understand the role of geographic separation between patches in promoting convergent adaptation and the genomic signals it leaves behind. We illustrate these ideas using the convergent evolution of cryptic coloration in the rock pocket mouse, Chaetodipus intermedius, as an empirical example. [ABSTRACT FROM AUTHOR]

Methods for detecting the genomic signatures of natural selection have been heavily studied, and they have been successful in identifying many selective sweeps. For most of these sweeps, the favored allele remains unknown, making it difficult to distinguish carriers of the sweep from non-carriers. In an ongoing selective sweep, carriers of the favored allele are likely to contain a future most recent common ancestor. Therefore, identifying them may prove useful in predicting the evolutionary trajectory—for example, in contexts involving drug-resistant pathogen strains or cancer subclones. The main contribution of this paper is the development and analysis of a new statistic, the Haplotype Allele Frequency (HAF) score. The HAF score, assigned to individual haplotypes in a sample, naturally captures many of the properties shared by haplotypes carrying a favored allele. We provide a theoretical framework for computing expected HAF scores under different evolutionary scenarios, and we validate the theoretical predictions with simulations. As an application of HAF score computations, we develop an algorithm (PreCIOSS: Predicting Carriers of Ongoing Selective Sweeps) to identify carriers of the favored allele in selective sweeps, and we demonstrate its power on simulations of both hard and soft sweeps, as well as on data from well-known sweeps in human populations. [ABSTRACT FROM AUTHOR]

Phylogeographic methods aim to infer migration trends and the history of sampled lineages from genetic data. Applications of phylogeography are broad, and in the context of pathogens include the reconstruction of transmission histories and the origin and emergence of outbreaks. Phylogeographic inference based on bottom-up population genetics models is computationally expensive, and as a result faster alternatives based on the evolution of discrete traits have become popular. In this paper, we show that inference of migration rates and root locations based on discrete trait models is extremely unreliable and sensitive to biased sampling. To address this problem, we introduce BASTA (BAyesian STructured coalescent Approximation), a new approach implemented in BEAST2 that combines the accuracy of methods based on the structured coalescent with the computational efficiency required to handle more than just few populations. We illustrate the potentially severe implications of poor model choice for phylogeographic analyses by investigating the zoonotic transmission of Ebola virus. Whereas the structured coalescent analysis correctly infers that successive human Ebola outbreaks have been seeded by a large unsampled non-human reservoir population, the discrete trait analysis implausibly concludes that undetected human-to-human transmission has allowed the virus to persist over the past four decades. As genomics takes on an increasingly prominent role informing the control and prevention of infectious diseases, it will be vital that phylogeographic inference provides robust insights into transmission history. [ABSTRACT FROM AUTHOR]

Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistent across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 × 10-22). [ABSTRACT FROM AUTHOR]

Results from Genome-Wide Association Studies (GWAS) have shown that complex diseases are often affected by many genetic variants with small or moderate effects. Identifications of these risk variants remain a very challenging problem. There is a need to develop more powerful statistical methods to leverage available information to improve upon traditional approaches that focus on a single GWAS dataset without incorporating additional data. In this paper, we propose a novel statistical approach, GPA (Genetic analysis incorporating Pleiotropy and Annotation), to increase statistical power to identify risk variants through joint analysis of multiple GWAS data sets and annotation information because: (1) accumulating evidence suggests that different complex diseases share common risk bases, i.e., pleiotropy; and (2) functionally annotated variants have been consistently demonstrated to be enriched among GWAS hits. GPA can integrate multiple GWAS datasets and functional annotations to seek association signals, and it can also perform hypothesis testing to test the presence of pleiotropy and enrichment of functional annotation. Statistical inference of the model parameters and SNP ranking is achieved through an EM algorithm that can handle genome-wide markers efficiently. When we applied GPA to jointly analyze five psychiatric disorders with annotation information, not only did GPA identify many weak signals missed by the traditional single phenotype analysis, but it also revealed relationships in the genetic architecture of these disorders. Using our hypothesis testing framework, statistically significant pleiotropic effects were detected among these psychiatric disorders, and the markers annotated in the central nervous system genes and eQTLs from the Genotype-Tissue Expression (GTEx) database were significantly enriched. We also applied GPA to a bladder cancer GWAS data set with the ENCODE DNase-seq data from 125 cell lines. GPA was able to detect cell lines that are biologically more relevant to bladder cancer. The R implementation of GPA is currently available at . [ABSTRACT FROM AUTHOR]

Associations between the level of single transcripts and single corresponding genetic variants, expression single nucleotide polymorphisms (eSNPs), have been extensively studied and reported. However, most expression traits are complex, involving the cooperative action of multiple SNPs at different loci affecting multiple genes. Finding these cooperating eSNPs by exhaustive search has proven to be statistically challenging. In this paper we utilized availability of sequencing data with transcriptional profiles in the same cohorts to identify two kinds of usual suspects: eSNPs that alter coding sequences or eSNPs within the span of transcription factors (TFs). We utilize a computational framework for considering triplets, each comprised of a SNP and two associated genes. We examine pairs of triplets with such cooperating source eSNPs that are both associated with the same pair of target genes. We characterize such quartets through their genomic, topological and functional properties. We establish that this regulatory structure of cooperating quartets is frequent in real data, but is rarely observed in permutations. eSNP sources are mostly located on different chromosomes and away from their targets. In the majority of quartets, SNPs affect the expression of the two gene targets independently of one another, suggesting a mutually independent rather than a directionally dependent effect. Furthermore, the directions in which the minor allele count of the SNP affects gene expression within quartets are consistent, so that the two source eSNPs either both have the same effect on the target genes or both affect one gene in the opposite direction to the other. Same-effect eSNPs are observed more often than expected by chance. Cooperating quartets reported here in a human system might correspond to bi-fans, a known network motif of four nodes previously described in model organisms. Overall, our analysis offers insights regarding the fine motif structure of human regulatory networks. [ABSTRACT FROM AUTHOR]

Modern genetic mapping is plagued by the “missing heritability” problem, which refers to the discordance between the estimated heritabilities of quantitative traits and the variance accounted for by mapped causative variants. One major potential explanation for the missing heritability is allelic heterogeneity, in which there are multiple causative variants at each causative gene with only a fraction having been identified. The majority of genome-wide association studies (GWAS) implicitly assume that a single SNP can explain all the variance for a causative locus. However, if allelic heterogeneity is prevalent, a substantial amount of genetic variance will remain unexplained. In this paper, we take a haplotype-based mapping approach and quantify the number of alleles segregating at each locus using a large set of 7922 eQTL contributing to regulatory variation in the Drosophila melanogaster female head. Not only does this study provide a comprehensive eQTL map for a major community genetic resource, the Drosophila Synthetic Population Resource, but it also provides a direct test of the allelic heterogeneity hypothesis. We find that 95% of cis-eQTLs and 78% of trans-eQTLs are due to multiple alleles, demonstrating that allelic heterogeneity is widespread in Drosophila eQTL. Allelic heterogeneity likely contributes significantly to the missing heritability problem common in GWAS studies. [ABSTRACT FROM AUTHOR]

DNA:RNA hybrid formation is emerging as a significant cause of genome instability in biological systems ranging from bacteria to mammals. Here we describe the genome-wide distribution of DNA:RNA hybrid prone loci in Saccharomyces cerevisiae by DNA:RNA immunoprecipitation (DRIP) followed by hybridization on tiling microarray. These profiles show that DNA:RNA hybrids preferentially accumulated at rDNA, Ty1 and Ty2 transposons, telomeric repeat regions and a subset of open reading frames (ORFs). The latter are generally highly transcribed and have high GC content. Interestingly, significant DNA:RNA hybrid enrichment was also detected at genes associated with antisense transcripts. The expression of antisense-associated genes was also significantly altered upon overexpression of RNase H, which degrades the RNA in hybrids. Finally, we uncover mutant-specific differences in the DRIP profiles of a Sen1 helicase mutant, RNase H deletion mutant and Hpr1 THO complex mutant compared to wild type, suggesting different roles for these proteins in DNA:RNA hybrid biology. Our profiles of DNA:RNA hybrid prone loci provide a resource for understanding the properties of hybrid-forming regions in vivo, extend our knowledge of hybrid-mitigating enzymes, and contribute to models of antisense-mediated gene regulation. A summary of this paper was presented at the 26th International Conference on Yeast Genetics and Molecular Biology, August 2013. [ABSTRACT FROM AUTHOR]

Cockayne syndrome is an inherited premature aging disease associated with numerous developmental and neurological defects, and mutations in the gene encoding the CSB protein account for the majority of Cockayne syndrome cases. Accumulating evidence suggests that CSB functions in transcription regulation, in addition to its roles in DNA repair, and those defects in this transcriptional activity might contribute to the clinical features of Cockayne syndrome. Transcription profiling studies have so far uncovered CSB-dependent effects on gene expression; however, the direct targets of CSB's transcriptional activity remain largely unknown. In this paper, we report the first comprehensive analysis of CSB genomic occupancy during replicative cell growth. We found that CSB occupancy sites display a high correlation to regions with epigenetic features of promoters and enhancers. Furthermore, we found that CSB occupancy is enriched at sites containing the TPA-response element. Consistent with this binding site preference, we show that CSB and the transcription factor c-Jun can be found in the same protein-DNA complex, suggesting that c-Jun can target CSB to specific genomic regions. In support of this notion, we observed decreased CSB occupancy of TPA-response elements when c-Jun levels were diminished. By modulating CSB abundance, we found that CSB can influence the expression of nearby genes and impact nucleosome positioning in the vicinity of its binding site. These results indicate that CSB can be targeted to specific genomic loci by sequence-specific transcription factors to regulate transcription and local chromatin structure. Additionally, comparison of CSB occupancy sites with the MSigDB Pathways database suggests that CSB might function in peroxisome proliferation, EGF receptor transactivation, G protein signaling and NF-κB activation, shedding new light on the possible causes and mechanisms of Cockayne syndrome. [ABSTRACT FROM AUTHOR]

Sporadic evidence suggests Notch is involved in cell adhesion. However, the underlying mechanism is unknown. Here I have investigated an epithelial remodeling process in the Drosophila eye in which two primary pigment cells (PPCs) with a characteristic ‘kidney’ shape enwrap and eventually isolate a group of cone cells from inter-ommatidial cells (IOCs). This paper shows that in the developing Drosophila eye the ligand Delta was transcribed in cone cells and Notch was activated in the adjacent PPC precursors. In the absence of Notch, emerging PPCs failed to enwrap cone cells, and hibris (hbs) and sns, two genes coding for adhesion molecules of the Nephrin group that mediate preferential adhesion, were not transcribed in PPC precursors. Conversely, activation of Notch in single IOCs led to ectopic expression of hbs and sns. By contrast, in a single IOC that normally transcribes rst, a gene coding for an adhesion molecule of the Neph1 group that binds Hbs and Sns, activation of Notch led to a loss of rst transcription. In addition, in a Notch mutant where two emerging PPCs failed to enwrap cone cells, expression of hbs in PPC precursors restored the ability of these cells to surround cone cells. Further, expression of hbs or rst in a single rst- or hbs-expressing cell, respectively, led to removal of the counterpart from the membrane within the same cell through cis-interaction and forced expression of Rst in all hbs-expressing PPCs strongly disrupted the remodeling process. Finally, a loss of both hbs and sns in single PPC precursors led to constriction of the apical surface that compromised the ‘kidney’ shape of PPCs. Taken together, these results indicate that cone cells utilize Notch signaling to instruct neighboring PPC precursors to surround them and Notch controls the remodeling process by differentially regulating four adhesion genes. [ABSTRACT FROM AUTHOR]

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. [ABSTRACT FROM AUTHOR]

Discriminating self and non-self is a universal requirement of immune systems. Adaptive immune systems in prokaryotes are centered around repetitive loci called CRISPRs (clustered regularly interspaced short palindromic repeat), into which invader DNA fragments are incorporated. CRISPR transcripts are processed into small RNAs that guide CRISPR-associated (Cas) proteins to invading nucleic acids by complementary base pairing. However, to avoid autoimmunity it is essential that these RNA-guides exclusively target invading DNA and not complementary DNA sequences (i.e., self-sequences) located in the host's own CRISPR locus. Previous work on the Type III-A CRISPR system from Staphylococcus epidermidis has demonstrated that a portion of the CRISPR RNA-guide sequence is involved in self versus non-self discrimination. This self-avoidance mechanism relies on sensing base pairing between the RNA-guide and sequences flanking the target DNA. To determine if the RNA-guide participates in self versus non-self discrimination in the Type I-E system from Escherichia coli we altered base pairing potential between the RNA-guide and the flanks of DNA targets. Here we demonstrate that Type I-E systems discriminate self from non-self through a base pairing-independent mechanism that strictly relies on the recognition of four unchangeable PAM sequences. In addition, this work reveals that the first base pair between the guide RNA and the PAM nucleotide immediately flanking the target sequence can be disrupted without affecting the interference phenotype. Remarkably, this indicates that base pairing at this position is not involved in foreign DNA recognition. Results in this paper reveal that the Type I-E mechanism of avoiding self sequences and preventing autoimmunity is fundamentally different from that employed by Type III-A systems. We propose the exclusive targeting of PAM-flanked sequences to be termed a target versus non-target discrimination mechanism. [ABSTRACT FROM AUTHOR]

Gene expression data, in conjunction with information on genetic variants, have enabled studies to identify expression quantitative trait loci (eQTLs) or polymorphic locations in the genome that are associated with expression levels. Moreover, recent technological developments and cost decreases have further enabled studies to collect expression data in multiple tissues. One advantage of multiple tissue datasets is that studies can combine results from different tissues to identify eQTLs more accurately than examining each tissue separately. The idea of aggregating results of multiple tissues is closely related to the idea of meta-analysis which aggregates results of multiple genome-wide association studies to improve the power to detect associations. In principle, meta-analysis methods can be used to combine results from multiple tissues. However, eQTLs may have effects in only a single tissue, in all tissues, or in a subset of tissues with possibly different effect sizes. This heterogeneity in terms of effects across multiple tissues presents a key challenge to detect eQTLs. In this paper, we develop a framework that leverages two popular meta-analysis methods that address effect size heterogeneity to detect eQTLs across multiple tissues. We show by using simulations and multiple tissue data from mouse that our approach detects many eQTLs undetected by traditional eQTL methods. Additionally, our method provides an interpretation framework that accurately predicts whether an eQTL has an effect in a particular tissue. [ABSTRACT FROM AUTHOR]

Nonreplicating type I uracil auxotrophic mutants of Toxoplasma gondii possess a potent ability to activate therapeutic immunity to established solid tumors by reversing immune suppression in the tumor microenvironment. Here we engineered targeted deletions of parasite secreted effector proteins using a genetically tractable Δku80 vaccine strain to show that the secretion of specific rhoptry (ROP) and dense granule (GRA) proteins by uracil auxotrophic mutants of T. gondii in conjunction with host cell invasion activates antitumor immunity through host responses involving CD8α+ dendritic cells, the IL-12/interferon-gamma (IFN-γ) TH1 axis, as well as CD4+ and CD8+ T cells. Deletion of parasitophorous vacuole membrane (PVM) associated proteins ROP5, ROP17, ROP18, ROP35 or ROP38, intravacuolar network associated dense granule proteins GRA2 or GRA12, and GRA24 which traffics past the PVM to the host cell nucleus severely abrogated the antitumor response. In contrast, deletion of other secreted effector molecules such as GRA15, GRA16, or ROP16 that manipulate host cell signaling and transcriptional pathways, or deletion of PVM associated ROP21 or GRA3 molecules did not affect the antitumor activity. Association of ROP18 with the PVM was found to be essential for the development of the antitumor responses. Surprisingly, the ROP18 kinase activity required for resistance to IFN-γ activated host innate immunity related GTPases and virulence was not essential for the antitumor response. These data show that PVM functions of parasite secreted effector molecules, including ROP18, manipulate host cell responses through ROP18 kinase virulence independent mechanisms to activate potent antitumor responses. Our results demonstrate that PVM associated rhoptry effector proteins secreted prior to host cell invasion and dense granule effector proteins localized to the intravacuolar network and host nucleus that are secreted after host cell invasion coordinately control the development of host immune responses that provide effective antitumor immunity against established ovarian cancer. [ABSTRACT FROM AUTHOR]

Recent advances in sequencing technologies have enabled the production of massive amounts of data on somatic mutations from cancer genomes. These data have led to the detection of characteristic patterns of somatic mutations or “mutation signatures” at an unprecedented resolution, with the potential for new insights into the causes and mechanisms of tumorigenesis. Here we present new methods for modelling, identifying and visualizing such mutation signatures. Our methods greatly simplify mutation signature models compared with existing approaches, reducing the number of parameters by orders of magnitude even while increasing the contextual factors (e.g. the number of flanking bases) that are accounted for. This improves both sensitivity and robustness of inferred signatures. We also provide a new intuitive way to visualize the signatures, analogous to the use of sequence logos to visualize transcription factor binding sites. We illustrate our new method on somatic mutation data from urothelial carcinoma of the upper urinary tract, and a larger dataset from 30 diverse cancer types. The results illustrate several important features of our methods, including the ability of our new visualization tool to clearly highlight the key features of each signature, the improved robustness of signature inferences from small sample sizes, and more detailed inference of signature characteristics such as strand biases and sequence context effects at the base two positions 5′ to the mutated site. The overall framework of our work is based on probabilistic models that are closely connected with “mixed-membership models” which are widely used in population genetic admixture analysis, and in machine learning for document clustering. We argue that recognizing these relationships should help improve understanding of mutation signature extraction problems, and suggests ways to further improve the statistical methods. Our methods are implemented in an R package pmsignature () and a web application available at . [ABSTRACT FROM AUTHOR]

Adaptive mutation refers to the continuous outgrowth of new mutants from a non-dividing cell population during selection, in apparent violation of the neo-Darwinian principle that mutation precedes selection. One explanation is that of retromutagenesis, in which a DNA lesion causes a transcriptional mutation that yields a mutant protein, allowing escape from selection. This enables a round of DNA replication that establishes heritability. Because the model requires that gene expression precedes DNA replication, it predicts that during selection, new mutants will arise from damage only to the transcribed DNA strand. As a test, we used a lacZ amber mutant of Escherichia coli that can revert by nitrous acid-induced deamination of adenine residues on either strand of the TAG stop codon, each causing different DNA mutations. When stationary-phase, mutagenized cells were grown in rich broth before being plated on lactose-selective media, only non-transcribed strand mutations appeared in the revertants. This result was consistent with the known high sensitivity to deamination of the single-stranded DNA in a transcription bubble, and it provided an important control because it demonstrated that the genetic system we would use to detect transcribed-strand mutations could also detect a bias toward the non-transcribed strand. When residual lacZ transcription was blocked beforehand by catabolite repression, both strands were mutated about equally, but if revertants were selected immediately after nitrous acid exposure, transcribed-strand mutations predominated among the revertants, implicating retromutagenesis as the mechanism. This result was not affected by gene orientation. Retromutagenesis is apt to be a universal method of evolutionary adaptation, which enables the emergence of new mutants from mutations acquired during counterselection rather than beforehand, and it may have roles in processes as diverse as the development of antibiotic resistance and neoplasia. [ABSTRACT FROM AUTHOR]

Type-III protein secretion systems are utilized by gram-negative pathogens to secrete building blocks of the bacterial flagellum, virulence effectors from the cytoplasm into host cells, and structural subunits of the needle complex. The flagellar type-III secretion apparatus utilizes both the energy of the proton motive force and ATP hydrolysis to energize substrate unfolding and translocation. We report formation of functional flagella in the absence of type-III ATPase activity by mutations that increased the proton motive force and flagellar substrate levels. We additionally show that increased proton motive force bypassed the requirement of the Salmonella pathogenicity island 1 virulence-associated type-III ATPase for secretion. Our data support a role for type-III ATPases in enhancing secretion efficiency under limited secretion substrate concentrations and reveal the dispensability of ATPase activity in the type-III protein export process. [ABSTRACT FROM AUTHOR]

Specification of cell identity and the proper functioning of a mature cell depend on precise regulation of gene expression. Both binary ON/OFF regulation of transcription, as well as more fine-tuned control of transcription levels in the ON state, are required to define cell types. The Drosophila melanogaster Hox gene, Ultrabithorax (Ubx), exhibits both of these modes of control during development. While ON/OFF regulation is needed to specify the fate of the developing wing (Ubx OFF) and haltere (Ubx ON), the levels of Ubx within the haltere differ between compartments along the proximal-distal axis. Here, we identify and molecularly dissect the novel contribution of a previously identified Ubx cis-regulatory module (CRM), anterobithorax (abx), to a negative auto-regulatory loop that decreases Ubx expression in the proximal compartment of the haltere as compared to the distal compartment. We find that Ubx, in complex with the known Hox cofactors, Homothorax (Hth) and Extradenticle (Exd), acts through low-affinity Ubx-Exd binding sites to reduce the levels of Ubx transcription in the proximal compartment. Importantly, we also reveal that Ubx-Exd-binding site mutations sufficient to result in de-repression of abx activity in a transgenic context are not sufficient to de-repress Ubx expression when mutated at the endogenous locus, suggesting the presence of multiple mechanisms through which Ubx-mediated repression occurs. Our results underscore the complementary nature of CRM analysis through transgenic reporter assays and genome modification of the endogenous locus; but, they also highlight the increasing need to understand gene regulation within the native context to capture the potential input of multiple genomic elements on gene control. [ABSTRACT FROM AUTHOR]

Phosphohexomutase superfamily enzymes catalyze the reversible intramolecular transfer of a phosphoryl moiety on hexose sugars. Bacillus subtilis phosphoglucomutase PgcA catalyzes the reversible interconversion of glucose 6-phosphate (Glc-6-P) and glucose 1-phosphate (Glc-1-P), a precursor of UDP-glucose (UDP-Glc). B. subtilis phosphoglucosamine mutase (GlmM) is a member of the same enzyme superfamily that converts glucosamine 6-phosphate (GlcN-6-P) to glucosamine 1-phosphate (GlcN-1-P), a precursor of the amino sugar moiety of peptidoglycan. Here, we present evidence that B. subtilis PgcA possesses activity as a phosphoglucosamine mutase that contributes to peptidoglycan biosynthesis. This activity was made genetically apparent by the synthetic lethality of pgcA with glmR, a positive regulator of amino sugar biosynthesis, which can be specifically suppressed by overproduction of GlmM. A gain-of-function mutation in a substrate binding loop (PgcA G47S) increases this secondary activity and suppresses a glmR mutant. Our results demonstrate that bacterial phosphoglucomutases may possess secondary phosphoglucosamine mutase activity, and that this dual activity may provide some level of functional redundancy for the essential peptidoglycan biosynthesis pathway. [ABSTRACT FROM AUTHOR]

Mitochondria have been increasingly recognized as a central regulatory nexus for multiple metabolic pathways, in addition to ATP production via oxidative phosphorylation (OXPHOS). Here we show that inducing mitochondrial DNA (mtDNA) stress in Drosophila using a mitochondrially-targeted Type I restriction endonuclease (mtEcoBI) results in unexpected metabolic reprogramming in adult flies, distinct from effects on OXPHOS. Carbohydrate utilization was repressed, with catabolism shifted towards lipid oxidation, accompanied by elevated serine synthesis. Cleavage and translocation, the two modes of mtEcoBI action, repressed carbohydrate rmetabolism via two different mechanisms. DNA cleavage activity induced a type II diabetes-like phenotype involving deactivation of Akt kinase and inhibition of pyruvate dehydrogenase, whilst translocation decreased post-translational protein acetylation by cytonuclear depletion of acetyl-CoA (AcCoA). The associated decease in the concentrations of ketogenic amino acids also produced downstream effects on physiology and behavior, attributable to decreased neurotransmitter levels. We thus provide evidence for novel signaling pathways connecting mtDNA to metabolism, distinct from its role in supporting OXPHOS. [ABSTRACT FROM AUTHOR]

Chromosome replication in Saccharomyces cerevisiae is initiated from ~300 origins that are regulated by DNA sequence and by the limited abundance of six trans-acting initiation proteins (Sld2, Sld3, Dpb11, Dbf4, Sld7 and Cdc45). We set out to determine how the levels of individual factors contribute to time of origin activation and/or origin efficiency using induced depletion of single factors and overexpression of sets of multiple factors. Depletion of Sld2 or Sld3 slows growth and S phase progression, decreases origin efficiency across the genome and impairs viability as a result of incomplete replication of the rDNA. We find that the most efficient early origins are relatively unaffected by depletion of either Sld2 or Sld3. However, Sld3 levels, and to a lesser extent Sld2 levels, are critical for firing of the less efficient early origins. Overexpression of Sld3 simultaneously with Sld2, Dpb11 and Dbf4 preserves the relative efficiency of origins. Only when Cdc45 and Sld7 are also overexpressed is origin efficiency equalized between early- and late-firing origins. Our data support a model in which Sld3 together with Cdc45 (and/or Sld7) is responsible for the differential efficiencies of origins across the yeast genome. [ABSTRACT FROM AUTHOR]

Plant trichomes originate from epidermal cell, forming protective structure from abiotic and biotic stresses. Different from the unicellular trichome in Arabidopsis, tomato trichomes are multicellular structure and can be classified into seven different types based on cell number, shape and the presence of glandular cells. Despite the importance of tomato trichomes in insect resistance, our understanding of the tomato trichome morphogenesis remains elusive. In this study, we quantitatively analyzed morphological traits of trichomes in tomato and further performed live imaging of cytoskeletons in stably transformed lines with actin and microtubule markers. At different developmental stages, two types of cytoskeletons exhibited distinct patterns in different trichome cells, ranging from transverse, spiral to longitudinal. This gradual transition of actin filament angle from basal to top cells could correlate with the spatial expansion mode in different cells. Further genetic screen for aberrant trichome morphology led to the discovery of a number of independent mutations in SCAR/WAVE and ARP2/3 complex, which resulted in actin bundling and distorted trichomes. Disruption of microtubules caused isotropic expansion while abolished actin filaments entirely inhibited axial extension of trichomes, indicating that microtubules and actin filaments may control distinct aspects of trichome cell expansion. Our results shed light on the roles of cytoskeletons in the formation of multicellular structure of tomato trichomes. [ABSTRACT FROM AUTHOR]

Variation in steroid hormone levels has wide implications for health and disease. The genes encoding the proteins involved in steroid disposition represent key determinants of interindividual variation in steroid levels and ultimately, their effects. Beginning with metabolomic data from genome-wide association studies (GWAS), we observed that genetic variants in the orphan transporter, SLC22A24 were significantly associated with levels of androsterone glucuronide and etiocholanolone glucuronide (sentinel SNPs p-value <1x10-30). In cells over-expressing human or various mammalian orthologs of SLC22A24, we showed that steroid conjugates and bile acids were substrates of the transporter. Phylogenetic, genomic, and transcriptomic analyses suggested that SLC22A24 has a specialized role in the kidney and appears to function in the reabsorption of organic anions, and in particular, anionic steroids. Phenome-wide analysis showed that functional variants of SLC22A24 are associated with human disease such as cardiovascular diseases and acne, which have been linked to dysregulated steroid metabolism. Collectively, these functional genomic studies reveal a previously uncharacterized protein involved in steroid homeostasis, opening up new possibilities for SLC22A24 as a pharmacological target for regulating steroid levels. [ABSTRACT FROM AUTHOR]

Comprehensive information on the timing and location of gene expression is fundamental to our understanding of embryonic development and tissue formation. While high-throughput in situ hybridization projects provide invaluable information about developmental gene expression patterns for model organisms like Drosophila, the output of these experiments is primarily qualitative, and a high proportion of protein coding genes and most non-coding genes lack any annotation. Accurate data-centric predictions of spatio-temporal gene expression will therefore complement current in situ hybridization efforts. Here, we applied a machine learning approach by training models on all public gene expression and chromatin data, even from whole-organism experiments, to provide genome-wide, quantitative spatio-temporal predictions for all genes. We developed structured in silico nano-dissection, a computational approach that predicts gene expression in >200 tissue-developmental stages. The algorithm integrates expression signals from a compendium of 6,378 genome-wide expression and chromatin profiling experiments in a cell lineage-aware fashion. We systematically evaluated our performance via cross-validation and experimentally confirmed 22 new predictions for four different embryonic tissues. The model also predicts complex, multi-tissue expression and developmental regulation with high accuracy. We further show the potential of applying these genome-wide predictions to extract tissue specificity signals from non-tissue-dissected experiments, and to prioritize tissues and stages for disease modeling. This resource, together with the exploratory tools are freely available at our webserver , which provides a valuable tool for a range of applications, from predicting spatio-temporal expression patterns to recognizing tissue signatures from differential gene expression profiles. [ABSTRACT FROM AUTHOR]

European and African descendants settled the continental US during the 17th-19th centuries, coming into contact with established Native American populations. The resulting admixture among these groups yielded a significant reservoir of Native American ancestry in the modern US population. We analyzed the patterns of Native American admixture seen for the three largest genetic ancestry groups in the US population: African descendants, Western European descendants, and Spanish descendants. The three groups show distinct Native American ancestry profiles, which are indicative of their historical patterns of migration and settlement across the country. Native American ancestry in the modern African descendant population does not coincide with local geography, instead forming a single group with origins in the southeastern US, consistent with the Great Migration of the early 20th century. Western European descendants show Native American ancestry that tracks their geographic origins across the US, indicative of ongoing contact during westward expansion, and Native American ancestry can resolve Spanish descendant individuals into distinct local groups formed by more recent migration from Mexico and Puerto Rico. We found an anomalous pattern of Native American ancestry from the US southwest, which most likely corresponds to the Nuevomexicano descendants of early Spanish settlers to the region. We addressed a number of controversies surrounding this population, including the extent of Sephardic Jewish ancestry. Nuevomexicanos are less admixed than nearby Mexican-American individuals, with more European and less Native American and African ancestry, and while they do show demonstrable Sephardic Jewish ancestry, the fraction is no greater than seen for other New World Spanish descendant populations. [ABSTRACT FROM AUTHOR]

The capacity of organisms to tune their development in response to environmental cues is pervasive in nature. This phenotypic plasticity is particularly striking in plants, enabled by their modular and continuous development. A good example is the activation of lateral shoot branches in Arabidopsis, which develop from axillary meristems at the base of leaves. The activity and elongation of lateral shoots depends on the integration of many signals both external (e.g. light, nutrient supply) and internal (e.g. the phytohormones auxin, strigolactone and cytokinin). Here, we characterise natural variation in plasticity of shoot branching in response to nitrate supply using two diverse panels of Arabidopsis lines. We find extensive variation in nitrate sensitivity across these lines, suggesting a genetic basis for variation in branching plasticity. High plasticity is associated with extreme branching phenotypes such that lines with the most branches on high nitrate have the fewest under nitrate deficient conditions. Conversely, low plasticity is associated with a constitutively moderate level of branching. Furthermore, variation in plasticity is associated with alternative life histories with the low plasticity lines flowering significantly earlier than high plasticity lines. In Arabidopsis, branching is highly correlated with fruit yield, and thus low plasticity lines produce more fruit than high plasticity lines under nitrate deficient conditions, whereas highly plastic lines produce more fruit under high nitrate conditions. Low and high plasticity, associated with early and late flowering respectively, can therefore be interpreted alternative escape vs mitigate strategies to low N environments. The genetic architecture of these traits appears to be highly complex, with only a small proportion of the estimated genetic variance detected in association mapping. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is currently one of the most important challenges to the treatment of bacterial infections. A critical issue to combat AMR is to restrict its spread. In several instances, bacterial plasmids are involved in the global spread of AMR. Plasmids belonging to the incompatibility group (Inc)HI are widespread in Enterobacteriaceae and most of them express multiple antibiotic resistance determinants. They play a relevant role in the recent spread of colistin resistance. We present in this report novel findings regarding IncHI plasmid conjugation. Conjugative transfer in liquid medium of an IncHI plasmid requires expression of a plasmid-encoded, large-molecular-mass protein that contains an Ig-like domain. The protein, termed RSP, is encoded by a gene (ORF R0009) that maps in the Tra2 region of the IncHI1 R27 plasmid. The RSP protein is exported outside the cell by using the plasmid-encoded type IV secretion system that is also used for its transmission to new cells. Expression of the protein reduces cell motility and enables plasmid conjugation. Flagella are one of the cellular targets of the RSP protein. The RSP protein is required for a high rate of plasmid transfer in both flagellated and nonflagellated Salmonella cells. This effect suggests that RSP interacts with other cellular structures as well as with flagella. These unidentified interactions must facilitate mating pair formation and, hence, facilitate IncHI plasmid conjugation. Due to its location on the outer surfaces of the bacterial cell, targeting the RSP protein could be a means of controlling IncHI plasmid conjugation in natural environments or of combatting infections caused by AMR enterobacteria that harbor IncHI plasmids. [ABSTRACT FROM AUTHOR]

The Y chromosome harbors nine multi-copy ampliconic gene families expressed exclusively in testis. The gene copies within each family are >99% identical to each other, which poses a major challenge in evaluating their copy number. Recent studies demonstrated high variation in Y ampliconic gene copy number among humans. However, how this variation affects expression levels in human testis remains understudied. Here we developed a novel computational tool Ampliconic Copy Number Estimator (AmpliCoNE) that utilizes read sequencing depth information to estimate Y ampliconic gene copy number per family. We applied this tool to whole-genome sequencing data of 149 men with matched testis expression data whose samples are part of the Genotype-Tissue Expression (GTEx) project. We found that the Y ampliconic gene families with low copy number in humans were deleted or pseudogenized in non-human great apes, suggesting relaxation of functional constraints. Among the Y ampliconic gene families, higher copy number leads to higher expression. Within the Y ampliconic gene families, copy number does not influence gene expression, rather a high tolerance for variation in gene expression was observed in testis of presumably healthy men. No differences in gene expression levels were found among major Y haplogroups. Age positively correlated with expression levels of the HSFY and PRY gene families in the African subhaplogroup E1b, but not in the European subhaplogroups R1b and I1. We also found that expression of five out of six Y ampliconic gene families is coordinated with that of their non-Y (i.e. X or autosomal) homologs. Indeed, five ampliconic gene families had consistently lower expression levels when compared to their non-Y homologs suggesting dosage regulation, while the HSFY family had higher expression levels than its X homolog and thus lacked dosage regulation. [ABSTRACT FROM AUTHOR]

Telomere shortening is associated with aging and age-associated diseases. Additionally, telomere dysfunction resulting from telomerase gene mutation can lead to premature aging, such as apparent skin atrophy and hair loss. However, the molecular signaling linking telomere dysfunction to skin atrophy remains elusive. Here we show that dysfunctional telomere disrupts BMP/pSmad/P63 signaling, impairing epidermal stem cell specification and differentiation of skin and hair follicles. We find that telomere shortening mediated by Terc loss up-regulates Follistatin (Fst), inhibiting pSmad signaling and down-regulating P63 and epidermal keratins in an ESC differentiation model as well as in adult development of telomere-shortened mice. Mechanistically, short telomeres disrupt PRC2/H3K27me3-mediated repression of Fst. Our findings reveal that skin atrophy due to telomere dysfunction is caused by a previously unappreciated link with Fst and BMP signaling that could be explored in the development of therapies. [ABSTRACT FROM AUTHOR]

Most current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. Our method treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also infer the trajectory of a SNP (EDAR) in Han Chinese, finding evidence that this allele’s age is much older than previously claimed. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, including ASIP, KITLG, and TYR. However, selection on OCA2/HERC2 seems to be much older and, in contrast to previous claims, we find no evidence of selection on TYRP1. [ABSTRACT FROM AUTHOR]

There has been much effort to prioritize genomic variants with respect to their impact on “function”. However, function is often not precisely defined: sometimes it is the disease association of a variant; on other occasions, it reflects a molecular effect on transcription or epigenetics. Here, we coupled multiple genomic predictors to build GRAM, a GeneRAlized Model, to predict a well-defined experimental target: the expression-modulating effect of a non-coding variant on its associated gene, in a transferable, cell-specific manner. Firstly, we performed feature engineering: using LASSO, a regularized linear model, we found transcription factor (TF) binding most predictive, especially for TFs that are hubs in the regulatory network; in contrast, evolutionary conservation, a popular feature in many other variant-impact predictors, has almost no contribution. Moreover, TF binding inferred from in vitro SELEX is as effective as that from in vivo ChIP-Seq. Second, we implemented GRAM integrating only SELEX features and expression profiles; thus, the program combines a universal regulatory score with an easily obtainable modifier reflecting the particular cell type. We benchmarked GRAM on large-scale MPRA datasets, achieving AUROC scores of 0.72 in GM12878 and 0.66 in a multi-cell line dataset. We then evaluated the performance of GRAM on targeted regions using luciferase assays in the MCF7 and K562 cell lines. We noted that changing the insertion position of the construct relative to the reporter gene gave very different results, highlighting the importance of carefully defining the exact prediction target of the model. Finally, we illustrated the utility of GRAM in fine-mapping causal variants and developed a practical software pipeline to carry this out. In particular, we demonstrated in specific examples how the pipeline could pinpoint variants that directly modulate gene expression within a larger linkage-disequilibrium block associated with a phenotype of interest (e.g., for an eQTL). [ABSTRACT FROM AUTHOR]

Plant mitochondrial genomes are usually assembled and displayed as circular maps based on the widely-held view across the broad community of life scientists that circular genome-sized molecules are the primary form of plant mitochondrial DNA, despite the understanding by plant mitochondrial researchers that this is an inaccurate and outdated concept. Many plant mitochondrial genomes have one or more pairs of large repeats that can act as sites for inter- or intramolecular recombination, leading to multiple alternative arrangements (isoforms). Most mitochondrial genomes have been assembled using methods unable to capture the complete spectrum of isoforms within a species, leading to an incomplete inference of their structure and recombinational activity. To document and investigate underlying reasons for structural diversity in plant mitochondrial DNA, we used long-read (PacBio) and short-read (Illumina) sequencing data to assemble and compare mitochondrial genomes of domesticated (Lactuca sativa) and wild (L. saligna and L. serriola) lettuce species. We characterized a comprehensive, complex set of isoforms within each species and compared genome structures between species. Physical analysis of L. sativa mtDNA molecules by fluorescence microscopy revealed a variety of linear, branched, and circular structures. The mitochondrial genomes for L. sativa and L. serriola were identical in sequence and arrangement and differed substantially from L. saligna, indicating that the mitochondrial genome structure did not change during domestication. From the isoforms in our data, we infer that recombination occurs at repeats of all sizes at variable frequencies. The differences in genome structure between L. saligna and the two other Lactuca species can be largely explained by rare recombination events that rearranged the structure. Our data demonstrate that representations of plant mitochondrial genomes as simple, circular molecules are not accurate descriptions of their true nature and that in reality plant mitochondrial DNA is a complex, dynamic mixture of forms. [ABSTRACT FROM AUTHOR]

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for ~22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL for Turicibacter sp. and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter, Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences in Slc10a2 gene expression associated with the different strains influences levels of both traits and revealed novel interactions between Turicibacter and BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions. [ABSTRACT FROM AUTHOR]

Ribosome assembly cofactors are widely conserved across all domains of life. One such group, the ribosome-associated GTPases (RA-GTPase), act as molecular switches to coordinate ribosome assembly. We previously identified the Staphylococcus aureus RA-GTPase Era as a target for the stringent response alarmone (p)ppGpp, with binding leading to inhibition of GTPase activity. Era is highly conserved throughout the bacterial kingdom and is essential in many species, although the function of Era in ribosome assembly is unclear. Here we show that Era is not essential in S. aureus but is important for 30S ribosomal subunit assembly. Protein interaction studies reveal that Era interacts with the 16S rRNA endonuclease YbeY and the DEAD-box RNA helicase CshA. We determine that both Era and CshA are required for growth at suboptimal temperatures and rRNA processing. Era and CshA also form direct interactions with the (p)ppGpp synthetase RelSau, with RelSau positively impacting the GTPase activity of Era but negatively affecting the helicase activity of CshA. We propose that in its GTP-bound form, Era acts as a hub protein on the ribosome to direct enzymes involved in rRNA processing/degradation and ribosome subunit assembly to their site of action. This activity is impeded by multiple components of the stringent response, contributing to the slowed growth phenotype synonymous with this stress response pathway. [ABSTRACT FROM AUTHOR]

The NAD+-dependent histone deacetylase Sir2 was originally identified in Saccharomyces cerevisiae as a silencing factor for HML and HMR, the heterochromatic cassettes utilized as donor templates during mating-type switching. MATa cells preferentially switch to MATα using HML as the donor, which is driven by an adjacent cis-acting element called the recombination enhancer (RE). In this study we demonstrate that Sir2 and the condensin complex are recruited to the RE exclusively in MATa cells, specifically to the promoter of a small gene within the right half of the RE known as RDT1. We also provide evidence that the RDT1 promoter functions as a locus control region (LCR) that regulates both transcription and long-range chromatin interactions. Sir2 represses RDT1 transcription until it is removed from the promoter in response to a dsDNA break at the MAT locus induced by HO endonuclease during mating-type switching. Condensin is also recruited to the RDT1 promoter and is displaced upon HO induction, but does not significantly repress RDT1 transcription. Instead condensin appears to promote mating-type donor preference by maintaining proper chromosome III architecture, which is defined by the interaction of HML with the right arm of chromosome III, including MATa and HMR. Remarkably, eliminating Sir2 and condensin recruitment to the RDT1 promoter disrupts this structure and reveals an aberrant interaction between MATa and HMR, consistent with the partially defective donor preference for this mutant. Global condensin subunit depletion also impairs mating-type switching efficiency and donor preference, suggesting that modulation of chromosome architecture plays a significant role in controlling mating-type switching, thus providing a novel model for dissecting condensin function in vivo. [ABSTRACT FROM AUTHOR]

Allele age has long been a focus of population genetic research, primarily because it can be an important clue to the fitness effects of an allele. By virtue of their effects on fitness, alleles under directional selection are expected to be younger than neutral alleles of the same frequency. We developed a new coalescent-based estimator of a close proxy for allele age, the time when a copy of an allele first shares common ancestry with other chromosomes in a sample not carrying that allele. The estimator performs well, including for the very rarest of alleles that occur just once in a sample, with a bias that is typically negative. The estimator is mostly insensitive to population demography and to factors that can arise in population genomic pipelines, including the statistical phasing of chromosomes. Applications to 1000 Genomes Data and UK10K genome data confirm predictions that singleton alleles that alter proteins are significantly younger than those that do not, with a greater difference in the larger UK10K dataset, as expected. The 1000 Genomes populations varied markedly in their distributions for singleton allele ages, suggesting that these distributions can be used to inform models of demographic history, including recent events that are only revealed by their impacts on the ages of very rare alleles. [ABSTRACT FROM AUTHOR]

DNA methyltransferases are ubiquitous enzymes conserved in bacteria, plants and opisthokonta. These enzymes, which methylate cytosines, are involved in numerous biological processes, notably development. In mammals and higher plants, methylation patterns established and maintained by the cytosine DNA methyltransferases (DMTs) are essential to zygotic development. In fungi, some members of an extensively conserved fungal-specific DNA methyltransferase class are both mediators of the Repeat Induced Point mutation (RIP) genome defense system and key players of sexual reproduction. Yet, no DNA methyltransferase activity of these purified RID (RIP deficient) proteins could be detected in vitro. These observations led us to explore how RID-like DNA methyltransferase encoding genes would play a role during sexual development of fungi showing very little genomic DNA methylation, if any. To do so, we used the model ascomycete fungus Podospora anserina. We identified the PaRid gene, encoding a RID-like DNA methyltransferase and constructed knocked-out ΔPaRid defective mutants. Crosses involving P. anserina ΔPaRid mutants are sterile. Our results show that, although gametes are readily formed and fertilization occurs in a ΔPaRid background, sexual development is blocked just before the individualization of the dikaryotic cells leading to meiocytes. Complementation of ΔPaRid mutants with ectopic alleles of PaRid, including GFP-tagged, point-mutated and chimeric alleles, demonstrated that the catalytic motif of the putative PaRid methyltransferase is essential to ensure proper sexual development and that the expression of PaRid is spatially and temporally restricted. A transcriptomic analysis performed on mutant crosses revealed an overlap of the PaRid-controlled genetic network with the well-known mating-types gene developmental pathway common to an important group of fungi, the Pezizomycotina. [ABSTRACT FROM AUTHOR]

One of the most frequently mutated proteins in human B-lineage leukemia is the transcription factor PAX5. These mutations often result in partial rather than complete loss of function of the transcription factor. While the functional dose of PAX5 has a clear connection to human malignancy, there is limited evidence for that heterozygote loss of PAX5 have a dramatic effect on the development and function of B-cell progenitors. One possible explanation comes from the finding that PAX5 mutated B-ALL often display complex karyotypes and additional mutations. Thus, PAX5 might be one component of a larger transcription factor network targeted in B-ALL. To investigate the functional network associated with PAX5 we used BioID technology to isolate proteins associated with this transcription factor in the living cell. This identified 239 proteins out of which several could be found mutated in human B-ALL. Most prominently we identified the commonly mutated IKZF1 and RUNX1, involved in the formation of ETV6-AML1 fusion protein, among the interaction partners. ChIP- as well as PLAC-seq analysis supported the idea that these factors share a multitude of target genes in human B-ALL cells. Gene expression analysis of mouse models and primary human leukemia suggested that reduced function of PAX5 increased the ability of an oncogenic form of IKZF1 or ETV6-AML to modulate gene expression. Our data reveals that PAX5 belong to a regulatory network frequently targeted by multiple mutations in B-ALL shedding light on the molecular interplay in leukemia cells. [ABSTRACT FROM AUTHOR]

Circadian clocks control the timing of animal behavioral and physiological rhythms. Fruit flies anticipate daily environmental changes and exhibit two peaks of locomotor activity around dawn and dusk. microRNAs are small non-coding RNAs that play important roles in post-transcriptional regulation. Here we identify Drosophila miR-210 as a critical regulator of circadian rhythms. Under light-dark conditions, flies lacking miR-210 (miR-210KO) exhibit a dramatic 2 hrs phase advance of evening anticipatory behavior. However, circadian rhythms and molecular pacemaker function are intact in miR-210KO flies under constant darkness. Furthermore, we identify that miR-210 determines the evening phase of activity through repression of the cell adhesion molecule Fasciclin 2 (Fas2). Ablation of the miR-210 binding site within the 3’ UTR of Fas2 (Fas2ΔmiR-210) by CRISPR-Cas9 advances the evening phase as in miR-210KO. Indeed, miR-210 genetically interacts with Fas2. Moreover, Fas2 abundance is significantly increased in the optic lobe of miR-210KO. In addition, overexpression of Fas2 in the miR-210 expressing cells recapitulates the phase advance behavior phenotype of miR-210KO. Together, these results reveal a novel mechanism by which miR-210 regulates circadian locomotor behavior. [ABSTRACT FROM AUTHOR]