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Abstract 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 2.0+ microarray. The resulting data were compared with those from populations from Anatolia, the Caucasus, the Near East, and Europe. Overall, Mingrelians exhibited considerable mtDNA haplogroup diversity, having high frequencies of common West Eurasian haplogroups (H, HV, I, J, K, N1, R1, R2, T, U, and W. X2) and low frequencies of East Eurasian haplogroups (A, C, D, F, and G). From a Y-chromosome standpoint, Mingrelians possessed a variety of haplogroups, including E1b1b, G2a, I2, J1, J2, L, Q, R1a, and R1b. Analysis of autosomal SNP data further revealed that Mingrelians are genetically homogeneous and cluster with other modern-day South Caucasus populations. When compared with ancient DNA samples from Bronze Age archaeological contexts in the broader region, these data indicate that the Mingrelian gene pool began taking its current form at least by this period, probably in conjunction with the formation of a distinct linguistic community. 

Meiotic recombination is both a fundamental biological process required for proper chromosomal segregation during meiosis and an important genomic parameter that shapes major features of the genomic landscape. However, despite the central importance of this phenotype, we lack a clear understanding of the selective pressures that shape its variation in natural populations, including humans. While there is strong evidence of fitness costs of low rates of recombination, the possible fitness costs of high rates of recombination are less defined. To determine whether a single lower fitness bound can explain the variation in recombination rates observed in human populations, we simulated the evolution of recombination rates as a sexually dimorphic quantitative trait. Under each scenario, we statistically compared the resulting trait distribution with the observed distribution of recombination rates from a published study of the Icelandic population. To capture the genetic architecture of recombination rates in humans, we modeled it as a moderately complex trait with modest heritability. For our fitness function, we implemented a hyperbolic tangent curve with several flexible parameters to capture a wide range of existing hypotheses. We found that costs of low rates of recombination alone are likely insufficient to explain the current variation in recombination rates in both males and females, supporting the existence of fitness costs of high rates of recombination in humans. With simulations using both upper and lower fitness boundaries, we describe a parameter space for the costs of high recombination rates that produces results consistent with empirical observations. 

Abstract The levels and distribution of standing genetic variation in a genome can provide a wealth of insights about the adaptive potential, demographic history, and genome structure of a population or species. As structural variants are increasingly associated with traits important for adaptation and speciation, investigating both sequence and structural variation is essential for wholly tapping this potential. Using a combination of shotgun sequencing, 10x Genomics linked reads and proximity-ligation data (Chicago and Hi-C), we produced and annotated a chromosome-level genome assembly for the Atlantic silverside (Menidia menidia)—an established ecological model for studying the phenotypic effects of natural and artificial selection—and examined patterns of genomic variation across two individuals sampled from different populations with divergent local adaptations. Levels of diversity varied substantially across each chromosome, consistently being highly elevated near the ends (presumably near telomeric regions) and dipping to near zero around putative centromeres. Overall, our estimate of the genome-wide average heterozygosity in the Atlantic silverside is among the highest reported for a fish, or any vertebrate (1.32–1.76% depending on inference method and sample). Furthermore, we also found extreme levels of structural variation, affecting ∼23% of the total genome sequence, including multiple large inversions (> 1 Mb and up to 12.6 Mb) associated with previously identified haploblocks showing strong differentiation between locally adapted populations. These extreme levels of standing genetic variation are likely associated with large effective population sizes and may help explain the remarkable adaptive divergence among populations of the Atlantic silverside.