Predicting Functional Consequences of Recent Natural Selection in Britain.

Ancient DNA can directly reveal the contribution of natural selection to human genomic variation. However, while the analysis of ancient DNA has been successful at identifying genomic signals of selection, inferring the phenotypic consequences of that selection has been more difficult. Most trait-associated variants are noncoding, so we expect that a large proportion of the phenotypic effects of selection will also act through noncoding variation.

Interpreting generative adversarial networks to infer natural selection from genetic data.

Understanding natural selection and other forms of non-neutrality is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent simulations for demographic inference, realistic simulations of selection typically require slow forward simulations.

Socio-cultural practices may have affected sex differences in stature in Early Neolithic Europe.

The rules and structure of human culture impact health as much as genetics or environment. To study these relationships, we combine ancient DNA (n = 230), skeletal metrics (n = 391), palaeopathology (n = 606) and dietary stable isotopes (n = 873) to analyse stature variation in Early Neolithic Europeans from North Central, South Central, Balkan and Mediterranean regions. In North Central Europe, stable isotopes and linear enamel hypoplasias indicate high environmental stress across sexes, but female stature is low, despite polygenic scores identical to males, and suggests that cultural factors preferentially supported male recovery from stress.

Genetic Analysis of Mingrelians Reveals Long-Term Continuity of Populations in Western Georgia (Caucasus).

To elucidate the population history of the Caucasus, we conducted a survey of genetic diversity in Samegrelo (Mingrelia), western Georgia. We collected DNA samples and genealogical information from 485 individuals residing in 30 different locations, the vast majority of whom being Mingrelian speaking. From these DNA samples, we generated mitochondrial DNA (mtDNA) control region sequences for all 485 participants (female and male), Y-short tandem repeat haplotypes for the 372 male participants, and analyzed all samples at nearly 590,000 autosomal single nucleotide polymorphisms (SNPs) plus around 33,000 on the sex chromosomes, with 27,000 SNP removed for missingness, using the GenoChip 2.

Predicting functional consequences of recent natural selection in Britain.

Ancient DNA can directly reveal the contribution of natural selection to human genomic variation. However, while the analysis of ancient DNA has been successful at identifying genomic signals of selection, inferring the phenotypic consequences of that selection has been more difficult. Most trait-associated variants are non-coding, so we expect that a large proportion of the phenotypic effects of selection will also act through non-coding variation.

Human genetics: An extreme fitness landscape.

A new study aims to identify how genetic and physiological adaptations to altitude affect pregnancy, childbirth and neonatal health in one of the most extreme environments on Earth, the Tibetan Plateau.

Regularized sequence-context mutational trees capture variation in mutation rates across the human genome.

Germline mutation is the mechanism by which genetic variation in a population is created. Inferences derived from mutation rate models are fundamental to many population genetics methods. Previous models have demonstrated that nucleotides flanking polymorphic sites-the local sequence context-explain variation in the probability that a site is polymorphic.

The genetic and phenotypic correlates of mtDNA copy number in a multi-ancestry cohort.

Mitochondrial DNA copy number (mtCN) is often treated as a proxy for mitochondrial (dys-) function and disease risk. Pathological changes in mtCN are common symptoms of rare mitochondrial disorders, but reported associations between mtCN and common diseases vary across studies. To understand the biology of mtCN, we carried out genome- and phenome-wide association studies of mtCN in 30,666 individuals from the Penn Medicine BioBank (PMBB)-a diverse cohort of largely African and European ancestry.

A gene-level test for directional selection on gene expression.

Most variants identified in human genome-wide association studies and scans for selection are noncoding. Interpretation of their effects and the way in which they contribute to phenotypic variation and adaptation in human populations is therefore limited by our understanding of gene regulation and the difficulty of confidently linking noncoding variants to genes. To overcome this, we developed a gene-wise test for population-specific selection based on combinations of regulatory variants.

Insufficient evidence for natural selection associated with the Black Death.

Klunk et al. analyzed ancient DNA data from individuals in London and Denmark before, during and after the Black Death [1], and argued that allele frequency changes at immune genes were too large to be produced by random genetic drift and thus must reflect natural selection. They also identified four specific variants that they claimed show evidence of selection including at , for which they estimate a selection coefficient of 0.

Hunter-gatherer admixture facilitated natural selection in Neolithic European farmers.

Ancient DNA has revealed multiple episodes of admixture in human prehistory during geographic expansions associated with cultural innovations. One important example is the expansion of Neolithic agricultural groups out of the Near East into Europe and their consequent admixture with Mesolithic hunter-gatherers. Ancient genomes from this period provide an opportunity to study the role of admixture in providing new genetic variation for selection to act upon, and also to identify genomic regions that resisted hunter-gatherer introgression and may thus have contributed to agricultural adaptations.

INTERPRETING GENERATIVE ADVERSARIAL NETWORKS TO INFER NATURAL SELECTION FROM GENETIC DATA.

Understanding natural selection in humans and other species is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent simulations for demographic inference, realistic simulations of selection typically requires slow forward simulations.

Gene burden analysis identifies genes associated with increased risk and severity of adult-onset hearing loss in a diverse hospital-based cohort.

Loss or absence of hearing is common at both extremes of human lifespan, in the forms of congenital deafness and age-related hearing loss. While these are often studied separately, there is increasing evidence that their genetic basis is at least partially overlapping. In particular, both common and rare variants in genes associated with monogenic forms of hearing loss also contribute to the more polygenic basis of age-related hearing loss.

Direct detection of natural selection in Bronze Age Britain.

We developed a novel method for efficiently estimating time-varying selection coefficients from genome-wide ancient DNA data. In simulations, our method accurately recovers selective trajectories and is robust to misspecification of population size. We applied it to a large data set of ancient and present-day human genomes from Britain and identified seven loci with genome-wide significant evidence of selection in the past 4500 yr.

Tracing the Evolution of Human Gene Regulation and Its Association with Shifts in Environment.

As humans populated the world, they adapted to many varying environmental factors, including climate, diet, and pathogens. Because many of these adaptations were mediated by multiple noncoding variants with small effects on gene regulation, it has been difficult to link genomic signals of selection to specific genes, and to describe the regulatory response to selection. To overcome this challenge, we adapted PrediXcan, a machine learning method for imputing gene regulation from genotype data, to analyze low-coverage ancient human DNA (aDNA).

The omnigenic model and polygenic prediction of complex traits.

The omnigenic model was proposed as a framework to understand the highly polygenic architecture of complex traits revealed by genome-wide association studies (GWASs). I argue that this model also explains recent observations about cross-population genetic effects, specifically the low transferability of polygenic scores and the lack of clear evidence for polygenic selection. In particular, the omnigenic model explains why the effects of most GWAS variants vary between populations.

Long Runs of Homozygosity Are Correlated with Marriage Preferences across Global Population Samples.

Children of consanguineous unions carry long runs of homozygosity (ROH) in their genomes, due to their parents' recent shared ancestry. This increases the burden of recessive disease in populations with high levels of consanguinity and has been heavily studied in some groups. However, there has been little investigation of the broader effect of consanguinity on patterns of genetic variation on a global scale.

Automatic inference of demographic parameters using generative adversarial networks.

Population genetics relies heavily on simulated data for validation, inference and intuition. In particular, since the evolutionary 'ground truth' for real data is always limited, simulated data are crucial for training supervised machine learning methods. Simulation software can accurately model evolutionary processes but requires many hand-selected input parameters.

The evolution of skin pigmentation-associated variation in West Eurasia.

Skin pigmentation is a classic example of a polygenic trait that has experienced directional selection in humans. Genome-wide association studies have identified well over a hundred pigmentation-associated loci, and genomic scans in present-day and ancient populations have identified selective sweeps for a small number of light pigmentation-associated alleles in Europeans. It is unclear whether selection has operated on all of the genetic variation associated with skin pigmentation as opposed to just a small number of large-effect variants.

Demographic history mediates the effect of stratification on polygenic scores.

Population stratification continues to bias the results of genome-wide association studies (GWAS). When these results are used to construct polygenic scores, even subtle biases can cumulatively lead to large errors. To study the effect of residual stratification, we simulated GWAS under realistic models of demographic history.

A Selective Sweep Conceals a MicroRNA with Broad Metabolic Effects.

The need for discovering new genes driving metabolic disease susceptibility is clear; even clearer is the need for their subsequent functional characterization. A new paper reports a role for miR-128-1 in metabolic control through a series of elegant mouse studies, and an intriguing hypothesis about its "thrifty" role in metabolism.

Boricua Founder Variant in Causes Epileptic Encephalopathy With Hyperkinetic Movements.

Objective: To describe a founder mutation effect and the clinical phenotype of homozygous c.737_739delGAG (p.Gly246del) variant in 15 children of Puerto Rican (Boricua) ancestry presenting with early infantile epileptic encephalopathy (EIEE-37) with prominent movement disorder.

Polygenic Scores for Height in Admixed Populations.

Polygenic risk scores (PRS) use the results of genome-wide association studies (GWAS) to predict quantitative phenotypes or disease risk at an individual level, and provide a potential route to the use of genetic data in personalized medical care. However, a major barrier to the use of PRS is that the majority of GWAS come from cohorts of European ancestry. The predictive power of PRS constructed from these studies is substantially lower in non-European ancestry cohorts, although the reasons for this are unclear.