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Selfish genetic elements (historically also referred to as selfish genes, ultra-selfish genes, selfish DNA, parasitic DNA, genomic outlaws) are genetic segments that can enhance their own transmission at the expense of other genes in the genome, even if this has no or a negative effect on organismal fitness. [–] Genomes have traditionally been viewed as cohesive units, with genes acting together to improve the fitness of the organism. However, when genes have some control over their own transmission, the rules can change, and so just like all social groups, genomes are . Early observations of selfish genetic elements were made almost a century ago, but the topic did not get widespread attention until several decades later. Inspired by the popularized by [] and ,[] two papers were published back-to-back in Nature in 1980—by and [] and and Carmen Sapienza[] respectively—introducing the concept of selfish genetic elements (at the time called “selfish DNA”) to the wider scientific community. Both papers emphasized that genes can spread in a population regardless of their effect on organismal fitness as long as they have a transmission advantage. Selfish genetic elements have now been described in most groups of organisms, and they demonstrate a remarkable diversity in the ways by which they promote their own transmission.[] Though long dismissed as genetic curiosities, with little relevance for evolution, they are now recognized to affect a wide swath of biological processes, ranging from genome size and architecture to speciation.[] [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]

In recent years, genome and exome sequencing studies have implicated a plethora of new disease genes with rare causal variants. Here, I review 150 exome sequencing studies that claim to have discovered that a disease can be caused by different rare variants in the same gene, and I determine whether their methods followed the current best-practice guidelines in the interpretation of their data. Specifically, I assess whether studies appropriately assess controls for rare variants throughout the entire gene or implicated region as opposed to only investigating the specific rare variants identified in the cases, and I assess whether studies present sufficient co-segregation data for statistically significant linkage. I find that the proportion of studies performing gene-based analyses has increased with time, but that even in 2015 fewer than 40% of the reviewed studies used this method, and only 10% presented statistically significant co-segregation data. Furthermore, I find that the genes reported in these papers are explaining a decreasing proportion of cases as the field moves past most of the low-hanging fruit, with 50% of the genes from studies in 2014 and 2015 having variants in fewer than 5% of cases. As more studies focus on genes explaining relatively few cases, the importance of performing appropriate gene-based analyses is increasing. It is becoming increasingly important for journal editors and reviewers to require stringent gene-based evidence to avoid an avalanche of misleading disease gene discovery papers. [ABSTRACT FROM AUTHOR]

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]

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]

The article discusses papers published within the issue, including the paper by V. F. Lanza et al. on plasmid flux in Escherichia coli ST131 sublineages and another by M. de Been et al. on dissemination of cephalosporing resistance genes between Escherichia coli strains from farm animals and humans by plasmid lineages.

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]

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]

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]

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]

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]

The article discusses a research paper on the use of a transgenic mouse model to examine the molecular pathways responsible for the mediation of the transition of thymic precursors into pre-leukemic stem cells. It references the study "SCL, LMO1 and Notch1 Reprogram Thymocytes Into Self-Renewing Cells," by B. Gerby et al. in the same issue of "PLOS Genetics". It discusses the development of T cell acute lymphoblastic leukemia and the conclusion of the study.

The article discusses a research paper on the continuous generation of antigenic diversity during persistent malaria infections. It references the study "Generation of Antigenic Diversity in Plasmodium Falciparum by Structured Rearrangement of Var Genes During Mitosis," by A. Claessens et al. in the same issue of "PLOS Genetics." It discusses the link between antigenic variation, sequestration and pathology, and analysis of subclones of the 3D7 parent clone.

The article discusses a research paper on the use of a reverse genetic approach to examine reproductive aging. It references the study "Gene Pathways That Delay Caemorhabditis Elegans Reproductive Senescence," in the same issue of "PLOS Genetics". It discusses the important health consequences of reproductive aging, and two approaches in identifying genes that modulate reproductive aging in Caenorhabditis elegans.

The article discusses a research paper by Yanmei Huang and colleagues on the role of translation regulation in circadian clock mechanism of Drosophila. Topics discussed include the effect of daily oscillations of the transcription factor period protein (PER), stimulation of PER by RNA-binding protein, influence of knock down of rhythmic RNA-binding protein (LARK) in the brain and overexpression of LARK in the neurons on circadian period, and clock/cycle transcription factors.