Germline copy number variants (CNVs) are known to affect a large portion of the human genome and have been implicated in many diseases. Although whole-genome sequencing can help identify CNVs, existing analytical methods suffer from limited sensitivity and specificity. Here we show that this is in large part due to the non-uniformity of read coverage, even after intra-sample normalization, and that this is exacerbated in regions of low-mappability. To improve on this, we propose PopSV, an analytical method that uses multiple samples to control for technical variation and enables the robust detection of CNVs. We show that PopSV is able to detect up to 2.7 times more variants compared to previous methods, with an accuracy of about 90%. Applying PopSV to 640 normal and cancer whole-genome datasets, we demonstrate that CNVs affect on average 7.4 million DNA bases in each individual, a 23% increase versus previous estimates. Notably, we find that regions of low-mappability, which were often concealed in previous analyses, harbor approximately 10 times more CNVs than the rest of the genome and that this contrasts with somatic CNVs (sCNVs) that are nearly uniformly distributed. We also observe that CNVs are found more than expected near centromeres and telomeres, in segmental duplications, in specific types of satellite repeats and in some of the most recent families of transposable elements. Although CNVs are found to be depleted in protein-coding genes, we identify 7206 genes with at least one exonic CNV, 324 of which harbored CNVs that would have been missed if low-mappability regions had been excluded. Similarly, 2253 trait- and disease-associated loci are observed to overlap at least one CNV. Our results provide the most comprehensive map of CNVs across the human genome to date and demonstrate the broad functional impact of this type of genetic variation including in regions of low-mappability.

Genetic assimilation results from selection on phenotypic plasticity, but quantitative genetics models of linear reaction norms considering intercept and slope as traits do not fully incorporate the process of genetic assimilation. We argue that intercept-slope reaction norm models are insufficient representations of genetic effects on linear reaction norms, and that defining the intercept as a trait is unfortunate. Instead we suggest a model with three traits representing genetic effects that respectively (1) are independent of the environment, (2) alter the sensitivity of the phenotype to the environment, and (3) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection, and eventually become equal to the mean environment. Hence, in this model, genetic assimilation in a new environment becomes complete without changes in genetic correlations, genetic drift or imposing any fitness costs on maintaining plasticity. The asymptotic evolutionary outcome of this three-trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two-trait model, and maximum expected fitness does not occur at the mean trait values in the population.

Plants of the Cannabis genus are the only producers of phytocannabinoids, terpenoid compounds that strongly interact with evolutionarily ancient endocannabinoid receptors shared by most bilaterian taxa. For millennia, the plant has been cultivated for these compounds, but also for food, rope, paper, and clothing. Today, specialized varieties yielding high-quality textile fibers, nutritional seed oil or high cannabinoid content are cultivated across the globe. However, the genetic identities and histories of these diverse populations remain largely obscured. We analyzed the nuclear genomic diversity among 339 Cannabis varieties, and demonstrate the existence of at least three major groups of diversity. As well as being genetically distinct, each group produces unique cannabinoid and terpenoid content profiles. This combined analysis of population genomic and trait variation informs our understanding of the potential uses of different genetic variants for medicine and agriculture, providing valuable insights and tools for a rapidly emerging, valuable legal industry.

Genome sequencing studies of de novo mutations in humans have revealed surprising incongruities with our understanding of human germline mutation. In particular, the mutation rate observed in modern humans is substantially lower than that estimated from calibration against the fossil record, and the paternal age effect in mutations transmitted to offspring is much weaker than expected from our longstanding model of spermatogenesis. I consider possible explanations for these differences, including evolutionary changes in life history parameters such as generation time and the age of puberty, a possible contribution from undetected post-zygotic mutations early in embryo development, and variation in cellular mutation rates at different stages of the germline. I suggest a revised model of stem cell state transitions during spermatogenesis, in which ‘dark’ gonial stem cells play a more active role than hitherto envisaged, with a long cycle time undetected in experimental observations. More generally, I argue that the mutation rate and its evolution depend intimately on the structure of the germline in humans and other primates.

Unlike the autosomes, recombination between the X chromosome and Y chromosome often thought to be constrained to two small pseudoautosomal regions (PARs) at the tips of each sex chromosome. The PAR1 spans the first 2.7 Mb of the proximal arm of the human sex chromosomes, while the much smaller PAR2 encompasses the distal 320 kb of the long arm of each sex chromosome. In addition to the PAR1 and PAR2, there is a human-specific X-transposed region that was duplicated from the X to the Y. The X-transposed region is often not excluded from X-specific analyses, unlike the PARs, because it is not thought to routinely recombine. Genetic diversity is expected to be higher in recombining regions than in non-recombining regions because recombination reduces the effect of linked selection. In this study, we investigate patterns of genetic diversity in noncoding regions across the entire X chromosome of a global sample of 26 unrelated genetic females. We observe that genetic diversity in the PAR1 is significantly greater than the non-recombining regions (nonPARs). However, rather than an abrupt drop in diversity at the pseudoautosomal boundary, there is a gradual reduction in diversity from the recombining through the non-recombining region, suggesting that recombination between the human sex chromosomes spans across the currently defined pseudoautosomal boundary. In contrast, diversity in the PAR2 is not significantly elevated compared to the nonPAR, suggesting that recombination is not obligatory in the PAR2. Finally, diversity in the X-transposed region is higher than the surrounding nonPAR regions, providing evidence that recombination may occur with some frequency between the X and Y in the XTR.

Human migration and human isolation serve as the driving forces of modern human civilization. Recent migrations of long isolated populations have resulted in genetically admixed populations. The history of population admixture is generally complex; however, understanding the admixture process is critical to both evolutionary and medical studies. Here, we utilized admixture induced linkage disequilibrium (LD) to infer occurrence of continuous admixture events, which is common for most existing admixed populations. Unlike previous studies, we expanded the typical continuous admixture model to a more general admixture scenario with isolation after a certain duration of continuous gene flow. Based on the extended models, we developed a method based on weighted LD to infer the admixture history considering continuous and complex demographic process of gene flow between populations. We evaluated the performance of the method by computer simulation and applied our method to real data analysis of a few well-known admixed populations.

A recent study conducted the first genome-wide scan for selection in Inuit from Greenland using SNP chip data. Here, we report that selection in the region with the second most extreme signal of positive selection in Greenlandic Inuit favored a deeply divergent haplotype introgressed from an archaic population most closely related to Denisovans. The region contains two genes, WARS2 and TBX15, and has previously been associated with body-fat distribution in humans. We show that the adaptively introgressed allele has been under selection in a much larger geographic region than just Greenland. Furthermore, it is associated with changes in expression of WARS2 and TBX15 in multiple tissues including the adrenal gland and subcutaneous adipose tissue, and is associated with BMI-adjusted waist circumference. We also find that in this region both the Denisovan and individuals homozygous for the introgressed allele display differential DNA methylation.

The effect of fluctuating environmental conditions (i.e. environmental stochasticity) on the evolution of virulence has been broadly overlooked, presumably due to a lack of connection between the fields of evolutionary epidemiology and insect ecology. Practitioners of the latter have known for a long time that stochastic environmental variations can impact the population dynamics of many insects, some of which are vectors of infectious diseases. Here we investigate whether environmental stochasticity affecting a vector’s life history can have an indirect impact on the evolutionarily expected virulence of the parasite, using Chagas disease as an example. We model the evolution of virulence using the adaptive dynamics framework, showing that parasite virulence should decrease when the vector’s dynamics randomly change in time. The decrease is even more pronounced when environmental variations are frequent and ample. This decrease in virulence can be viewed as a bet-hedging strategy: when a parasite is at a risk of not being transmitted (e.g. because vectors are scarce), its best option is to stay in the host longer – that is, to be less virulent. Lowering virulence is thus very similar to increasing iteroparity, a well-known risk-spreading strategy, and should be expected to evolve whenever parasite transmission varies randomly in time.

Understanding the causes of gene expression variation is of major importance for many areas of biology. While cis-regulatory changes have long been suggested to be particularly important for adaptation, our understanding of what determines cis-regulatory variation remains limited in most species. Here, we have investigated the prevalence, selective importance, and genomic correlates of cis-regulatory variation in the outcrossing crucifer species Capsella grandiflora. We identify genes with cis-regulatory variation through analyses of allele-specific expression (ASE) in deep transcriptome sequencing data from flower buds and leaves, and use population genomic analyses of high-coverage whole genome resequencing data from both a range-wide sample and a natural population to quantify the impact of positive and purifying selection on these genes. Our results show that in C. grandiflora, cis-regulatory variation is pervasive, affecting an average of 35% of genes within individual plants. Genes harboring cis-regulatory variation are (1) under weaker purifying selection, (2) significantly more likely to harbor nearby transposable element (TE) insertions, and (3) undergo lower rates of adaptive substitutions in comparison to other genes. Using a linear model, we identified ASE as the strongest factor contributing to purifying selection when considered alongside several other commonly used contributing factors. In turn, the main genomic correlates of cis-regulatory variation are presence of nearby TE insertions and gene expression level; notably, the signal of relaxed positive and purifying selection on genes with ASE remains after controlling for expression level. Our results suggest that variation in the intensity of selection across the genome is a major determinant of the presence of intraspecific cis-regulatory variation in this outcrossing plant species.