A mitochondrial genetic divergence proxy predicts the reproductive compatibility of mammalian hybrids.

Numerous pairs of evolutionarily divergent mammalian species have been shown to produce hybrid offspring. In some cases, F1 hybrids are able to produce F2s through matings with F1s. In other instances, the hybrids are only able to produce offspring themselves through backcrosses with a parent species owing to unisexual sterility (Haldane's Rule). Here, we explicitly tested whether genetic distance, computed from mitochondrial and nuclear genes, can be used as a proxy to predict the relative fertility of the hybrid offspring resulting from matings between species of terrestrial mammals. We assessed the proxy's predictive power using a well-characterized felid hybrid system, and applied it to modern and ancient hominins. Our results revealed a small overlap in mitochondrial genetic distance values that distinguish species pairs whose calculated distances fall within two categories: those whose hybrid offspring follow Haldane's Rule, and those whose hybrid F1 offspring can produce F2s. The strong correlation between genetic distance and hybrid fertility demonstrated here suggests that this proxy can be employed to predict whether the hybrid offspring of two mammalian species will follow Haldane's Rule.

Ancient DNA suggests modern wolves trace their origin to a Late Pleistocene expansion from Beringia.

Grey wolves (Canis lupus) are one of the few large terrestrial carnivores that have maintained a wide geographical distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the Late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single Late Pleistocene population. Both the geographical origin of this ancestral population and how it became widespread remain unknown. Here, we used a spatially and temporally explicit modelling framework to analyse a data set of 90 modern and 45 ancient mitochondrial wolf genomes from across the Northern Hemisphere, spanning the last 50,000 years. Our results suggest that contemporary wolf populations trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum, and that this process was most likely driven by Late Pleistocene ecological fluctuations that occurred across the Northern Hemisphere. This study provides direct ancient genetic evidence that long-range migration has played an important role in the population history of a large carnivore, and provides insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because Late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.

Estimating mobility using sparse data: Application to human genetic variation.

Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or formal quantification of the underlying mobility, are poorly suited to spatially and temporally sparsely sampled data, and permit only limited systematic comparison between different time periods or geographic regions. Here we present an estimator of past mobility that addresses these issues by explicitly linking trait differentiation in space and time. We demonstrate the efficacy of this estimator using spatiotemporally explicit simulations and apply it to a large set of ancient genomic data from Western Eurasia. We identify a sequence of changes in human mobility from the Late Pleistocene to the Iron Age. We find that mobility among European Holocene farmers was significantly higher than among European hunter-gatherers both pre- and postdating the Last Glacial Maximum. We also infer that this Holocene rise in mobility occurred in at least three distinct stages: the first centering on the well-known population expansion at the beginning of the Neolithic, and the second and third centering on the beginning of the Bronze Age and the late Iron Age, respectively. These findings suggest a strong link between technological change and human mobility in Holocene Western Eurasia and demonstrate the utility of this framework for exploring changes in mobility through space and time.

Inferring Allele Frequency Trajectories from Ancient DNA Indicates That Selection on a Chicken Gene Coincided with Changes in Medieval Husbandry Practices.

Ancient DNA provides an opportunity to infer the drivers of natural selection by linking allele frequency changes to temporal shifts in environment or cultural practices. However, analyses have often been hampered by uneven sampling and uncertainties in sample dating, as well as being confounded by demographic processes. Here, we present a Bayesian statistical framework for quantifying the timing and strength of selection using ancient DNA that explicitly addresses these challenges. We applied this method to time series data for two loci: TSHR and BCDO2, both hypothesised to have undergone strong and recent selection in domestic chickens. The derived variant in TSHR, associated with reduced aggression to conspecifics and faster onset of egg laying, shows strong selection beginning around 1,100 years ago, coincident with archaeological evidence for intensified chicken production and documented changes in egg and chicken consumption. To our knowledge, this is the first example of preindustrial domesticate trait selection in response to a historically attested cultural shift in food preference. For BCDO2, we find support for selection, but demonstrate that the recent rise in allele frequency could also have been driven by gene flow from imported Asian chickens during more recent breed formations. Our findings highlight that traits found ubiquitously in modern domestic species may not necessarily have originated during the early stages of domestication. In addition, our results demonstrate the importance of precise estimation of allele frequency trajectories through time for understanding the drivers of selection.

Induced Pluripotent Stem Cells as a Possible Approach for Exploring the Pathophysiology of Polycystic Ovary Syndrome (PCOS).

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine condition among women with pleiotropic sequelae possessing reproductive, metabolic, and psychological characteristics. Although the exact origin of PCOS is elusive, it is known to be a complex multigenic disorder with a genetic, epigenetic, and environmental background. However, the pathogenesis of PCOS, and the role of genetic variants in increasing the risk of the condition, are still unknown due to the lack of an appropriate study model. Since the debut of induced pluripotent stem cell (iPSC) technology, the ability of reprogrammed somatic cells to self-renew and their potential for multidirectional differentiation have made them excellent tools to study different disease mechanisms. Recently, researchers have succeeded in establishing human in vitro PCOS disease models utilizing iPSC lines from heterogeneous PCOS patient groups (iPSCPCOS). The current review sets out to summarize, for the first time, our current knowledge of the implications and challenges of iPSC technology in comprehending PCOS pathogenesis and tissue-specific disease mechanisms. Additionally, we suggest that the analysis of polygenic risk prediction based on genome-wide association studies (GWAS) could, theoretically, be utilized when creating iPSC lines as an additional research tool to identify women who are genetically susceptible to PCOS. Taken together, iPSCPCOS may provide a new paradigm for the exploration of PCOS tissue-specific disease mechanisms.

Ancestral genomic contributions to complex traits in contemporary Europeans.

The contemporary European genetic makeup formed in the last 8,000 years when local Western Hunter-Gatherers (WHGs) mixed with incoming Anatolian Neolithic farmers and Pontic Steppe pastoralists.1-3 This encounter combined genetic variants with distinct evolutionary histories and, together with new environmental challenges faced by the post-Neolithic Europeans, unlocked novel adaptations.4 Previous studies inferred phenotypes in these source populations, using either a few single loci5-7 or polygenic scores based on genome-wide association studies,8-10 and investigated the strength and timing of natural selection on lactase persistence or height, among others.6,11,12 However, how ancient populations contributed to present-day phenotypic variation is poorly understood. Here, we investigate how the unique tiling of genetic variants inherited from different ancestral components drives the complex traits landscape of contemporary Europeans and quantify selection patterns associated with these components. Using matching individual-level genotype and phenotype data for 27 traits in the Estonian biobank13 and genotype data directly from the ancient source populations, we quantify the contributions from each ancestry to present-day phenotypic variation in each complex trait. We find substantial differences in ancestry for eye and hair color, body mass index, waist/hip circumferences, and their ratio, height, cholesterol levels, caffeine intake, heart rate, and age at menarche. Furthermore, we find evidence for recent positive selection linked to four of these traits and, in addition, sleep patterns and blood pressure. Our results show that these ancient components were differentiated enough to contribute ancestry-specific signatures to the complex trait variability displayed by contemporary Europeans.

Sometimes hidden but always there: the assumptions underlying genetic inference of demographic histories.

Demographic processes directly affect patterns of genetic variation within contemporary populations as well as future generations, allowing for demographic inference from patterns of both present-day and past genetic variation. Advances in laboratory procedures, sequencing and genotyping technologies in the past decades have resulted in massive increases in high-quality genome-wide genetic data from present-day populations and allowed retrieval of genetic data from archaeological material, also known as ancient DNA. This has resulted in an explosion of work exploring past changes in population size, structure, continuity and movement. However, as genetic processes are highly stochastic, patterns of genetic variation only indirectly reflect demographic histories. As a result, past demographic processes need to be reconstructed using an inferential approach. This usually involves comparing observed patterns of variation with model expectations from theoretical population genetics. A large number of approaches have been developed based on different population genetic models that each come with assumptions about the data and underlying demography. In this article I review some of the key models and assumptions underlying the most commonly used approaches for past demographic inference and their consequences for our ability to link the inferred demographic processes to the archaeological and climate records. This article is part of the theme issue 'Cross-disciplinary approaches to prehistoric demography'.

Parallel adaptation of rabbit populations to myxoma virus.

In the 1950s the myxoma virus was released into European rabbit populations in Australia and Europe, decimating populations and resulting in the rapid evolution of resistance. We investigated the genetic basis of resistance by comparing the exomes of rabbits collected before and after the pandemic. We found a strong pattern of parallel evolution, with selection on standing genetic variation favoring the same alleles in Australia, France, and the United Kingdom. Many of these changes occurred in immunity-related genes, supporting a polygenic basis of resistance. We experimentally validated the role of several genes in viral replication and showed that selection acting on an interferon protein has increased the protein's antiviral effect.