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Repetitive DNA sequences shape genome evolution and instability. Here, the authors analyze repeat length distributions across over 300 mammals and show that long repeats arise and persist through a dynamic balance of mutation processes, without requiring natural selection.

John Stamatoyannopoulos, Shamil Sunyaev and colleagues report a correlation between mutation rate and replication timing in the human genome, observing an increased mutation rate in later-replicating regions.

Using well-calibrated statistical methods the authors jointly analyze Undiagnosed Diseases Network genomes, identifying known and novel disease genes. Software is publicly available to support future cross-cohort rare disease discovery efforts.

Shamil Sunyaev, Paul de Bakker and colleagues report an analysis of 11,020 de novo mutations from the whole-genome sequences of Dutch families sequenced as part of the Genome of the Netherlands project. They identify correlations related to paternal age and genic content and develop an empirical human mutation rate map.

Shamil Sunyaev and colleagues present exome sequencing methods and their applications in studies to identify the genetic basis of human complex traits. They include analyses of the whole-exome sequences of 438 individuals from across several studies.

David Reich, Shamil Sunyaev and colleagues report an analysis of the per-genome accumulation of nonsynonymous substitutions across diverse pairs of human populations. They find no evidence for a higher load of deleterious mutations in non-Africans than in West Africans and show that the observed patterns are not likely to reflect changes in natural selection.

An analysis of cell-type-specific epigenomic features reveals a relationship between epigenomic and mutational profiles; chromatin characteristics can explain a large proportion of mutational variance in cancer genomes and the mutational distribution can identify the probable cell type from which a given cancer originated from.

Shamil Sunyaev, Alexander Gimelbrant and colleagues report an analysis of the genetic variability in human monoallelically expressed genes. They find that genes with monoallelic expression show greater genetic diversity than biallelically expressed genes and that this diversity is associated with greater allelic age.

Shamil Sunyaev, Chris Cotsapas and colleagues present a joint likelihood framework for determining the statistical evidence of shared genetic effects of overlapping disease-associated loci and expression quantitative trait loci (eQTLs). They find evidence for shared genetic effects at 25% of eQTL–autoimmune disease locus pairs.

Shamil Sunyaev, David Beier and colleagues report an analysis of the fitness effects of heterozygous protein-truncating variants from the Exome Aggregation Consortium. They find that high heterozygous selection coefficients are enriched in Mendelian disease-associated genes and essential mouse genes, suggesting that this coefficient can be used to prioritize candidate disease-associated genes from clinical exome-sequencing data.

A systematic statistical genetics approach discovers CES drivers as hotspots of human de novo mutation and shows that clonal expansions in germline may both modulate the prevalence of disorders and lead to false-positive disease associations.

MutPanning is a new method to detect cancer driver genes that identifies genes with an excess of mutations in unusual nucleotide contexts. Applying this to whole-exome sequencing data from 11,873 tumor–normal pairs identifies 460 driver genes.

This study describes the integrative analysis of 111 reference human epigenomes, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression; the results annotate candidate regulatory elements in diverse tissues and cell types, their candidate regulators, and the set of human traits for which they show genetic variant enrichment, providing a resource for interpreting the molecular basis of human disease.

Roulette enables the estimation of germline mutation rates at basepair resolution from humans. Genes encoding small nuclear RNA showed significant deviations from the mutation rate predicted by Roulette, highlighting RNA polymerase III (Pol III)-dependent transcription as a potent source of mutations in the human genome.

STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components. STAAR accounts for population structure and relatedness and is scalable for analyzing large whole-genome sequencing studies.

Combining a number of large data sets has established that a sample of European Americans have more potentially damaging mutations lurking in their genomes than a comparable sample of African Americans, supporting the model of European Americans going through a more recent population bottleneck than African Americans.

Development of a constraint model specifically for mitochondrial DNA and applied to data from the Genome Aggregation Database provides insights into which sites in the mitochondrial genome are important for health and disease.

Trans-ethnic genetic correlation is significantly less than 1 for many diseases. Here, the authors stratify this correlation by genomic annotations, finding that loci whose causal disease effect sizes differ between ethnicities are likely impacted by selection, particularly positive selection.

Joint likelihood mapping across six autoimmune diseases identifies shared and distinct association signals and improves fine-mapping resolution at loci with shared effects, yielding insights into the underlying biological mechanisms.

An extensive map of human DNase I hypersensitive sites, markers of regulatory DNA, in 125 diverse cell and tissue types is described; integration of this information with other ENCODE-generated data sets identifies new relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns.

This study presents a probabilistic framework for inferring negative and positive selection in human cancers that addresses the problem of mutation rate variation. Applying the model to sequencing data from 17 cancer types identifies new significantly mutated genes and detects significant signals of negative selection in many cancer types.

Allele-specific expression in diploid organisms can be quantified by RNA-seq and it is common practice to rely on a single library. Here, the authors show that the standard approach has variable error rate and present Qllelic as a tool to improve reproducibility of allele-specific RNA-seq analysis.

A framework for metagenomic variation analysis to explore variation in the human microbiome is developed; the study describes SNPs, short indels and structural variants in 252 faecal metagenomes of 207 individuals from Europe and North America.

Bats account for 20 per cent of all mammals, these are the only mammals with powered flight, and are among the few animals that echolocate. Here, Seim et al. sequence the genome of the long-lived (>40 years) Brandt’s bat, Myotis brandtiiand provide clues to its evolution, longevity and other traits.

Resistance to antibiotics hampers the treatment of infectious diseases such as tuberculosis (TB). Here, Farhat et al. perform genome-wide association testing for minimum inhibitory concentration (MIC) of 12 anti-TB drugs in whole-genome sequenced clinical M. tuberculosis isolates and identify 13 genomic loci.

Patterns of amino acid conservation have been used to guide the interpretation of the disease-causing potential of genetic variants in patients; now, an appreciable fraction of pathogenic alleles are shown to be fixed in the genomes of other species, suggesting that the genomic context has an important role in allele pathogenicity.

Negative selection removes deleterious genetic variation, and can influence genetic architectures and evolution of complex traits. Here, the authors analyze data from 25 UK Biobank diseases and complex traits, and quantify frequency-dependent genetic architectures which suggests actions of negative selection.

Cancer driver mutations can occur within noncoding genomic sequences. Here, the authors develop a statistical approach to identify candidate noncoding driver mutations in DNase I hypersensitive sites in breast cancer and experimentally demonstrate they are regulatory elements of known cancer genes.

Analysis of mutational asymmetry with respect to the direction of replication and transcription suggests that error-prone damage bypass on the lagging strand has a major role in human germline and cancer mutations.

STAARpipeline is a comprehensive framework for flexible and scalable rare-variant association analysis using whole-genome sequencing data and annotation information.

Paul de Bakker, Cisca Wijmenga and colleagues report on The Genome of the Netherlands Project, including whole-genome sequencing of 769 individuals of Dutch ancestry from 250 parent-offspring families and construction of a phased haplotype map. Their intermediate-coverage population sequencing data set provides a complementary resource to other publicly available data sets, including the 1000 Genomes Project.

Bogdan Pasaniuc, David Reich, Alkes Price and colleagues report analyses considering the potential of genome-wide association studies (GWAS) based on extremely low-coverage sequence data sets combined with imputation using data sets from the 1000 Genomes Project. They show with simulations and real exome-sequencing data that low-coverage sequencing can increase power for GWAS relative to genotyping arrays.

Analysis of two independent cohorts of patients with Bardet–Biedl syndrome (BBS) with known recessive biallelic pathogenic mutations in one of 17 BBS genes shows an enrichment of rare nonsynonymous secondary variants in the same gene set, with significant over-representation of secondary alleles in chaperonin-encoding genes.

The authors extend stratified linkage disequilibrium score regression to partition the heritability of both low-frequency and common variants in 40 heritable traits from the UK Biobank, providing insights into low-frequency and rare variant functional architectures.

Frequencies of rare variants fluctuate over populations, hampering gene discovery. Here the authors use a population-specific reference panel, the Genome of the Netherlands, to discover four novel loci involved in lipid metabolism, including an exonic variant in ABCA6.

Exome sequence analysis of nearly 10,000 people was carried out to identify alleles associated with early-onset myocardial infarction; mutations in low-density lipoprotein receptor (LDLR) or apolipoprotein A-V (APOA5) were associated with disease risk, identifying the key roles of low-density lipoprotein cholesterol and metabolism of triglyceride-rich lipoproteins.

Exome sequencing of 175 autism spectrum disorder parent–child trios reveals that few de novo point mutations have a role in autism spectrum disorder and those that do are distributed across many genes and are incompletely penetrant, further supporting extreme genetic heterogeneity of this spectrum disorder.

A mutation in RAS oncogene family-like 3 (RABL3) is discovered in a family with multiple cases of pancreatic cancer. Zebrafish modeling and biochemical approaches suggest that truncated RABL3 elevates KRAS activity via accelerated prenylation.

Soumya Raychaudhuri, Paul de Bakker and colleagues test the non-additive disease contributions of classical HLA alleles to five common autoimmune diseases. In four of the five diseases, they observe highly significant non-additive dominance and interaction effects.

David Altshuler and colleagues explore the genetic architecture of type 2 diabetes (T2D) using an integrated population genetics–based simulation framework calibrated with empirical data. Whereas they are able to exclude more extreme models, for example, those in which either common or rare variants explain all of the disease heritability, they find that a broad range of architecture remains consistent with current empirical data and suggest that continued large-scale sequencing and genotyping studies will be needed to more precisely characterize the genetic architecture of complex traits such as T2D.

Polak et al. analyze somatic mutations and chromatin accessibility data to gain insight into mutational processes in cancer genomes.

As the sample size in cancer genome studies increases, the list of genes identified as significantly mutated is likely to include more false positives; here, this problem is identified as stemming largely from mutation heterogeneity, and a new analytical methodology designed to overcome this problem is described.

The next step after sequencing a genome is to figure out how the cell actually uses it as an instruction manual. A large international consortium has examined 1% of the genome for what part is transcribed, where proteins are bound, what the chromatin structure looks like, and how the sequence compares to that of other organisms.

Genome-scale sequencing data have revealed statistical properties of mutagenesis in humans. Statistical analyses that interpret these patterns and incorporate knowledge on DNA replication and repair pathways can provide mechanistic models that shed light on the origin of spontaneous human mutation in the germ line.