Biology subjects

Korunes, K. L.

Publications and source records attributed to Korunes, K. L..

4 recordsLinked to original sources

bioRxiv2022

Localizing post-admixture adaptive variants with object detection on ancestry-painted chromosomes

Gene flow between previously isolated populations during the founding of an admixed or hybrid population has the potential to introduce adaptive alleles into the new population. If the adaptive allele is common in one source population, but not the other, then as the adaptive allele rises in frequency in the admixed population, genetic ancestry from the source containing the adaptive allele will increase nearby as well. Patterns of genetic ancestry have therefore been used to identify post-admixture positive selection in humans and other animals, including examples in immunity, metabolism, and animal coloration. A common method identifies regions of the genome that have local ancestry outliers compared to the distribution across the rest of the genome, considering each locus independently. However, we lack theoretical models for expected distributions of ancestry under various demographic scenarios, resulting in potential false positives and false negatives. Further, ancestry patterns between distant sites are often not independent. As a result, current methods tend to infer wide genomic regions containing many genes as under selection, limiting biological interpretation. Instead, we develop a deep learning object detection method applied to images generated from local ancestry-painted genomes. This approach preserves information from the surrounding genomic context and avoids potential pitfalls of user-defined summary statistics. We find the-method is robust to a variety of demographic misspecifications using simulated data. Applied to human genotype data from Cabo Verde, we localize a known adaptive locus to a single narrow region compared to multiple or long windows obtained using two other ancestry-based methods.

genomics↗

bioRxiv2020

Sex-biased admixture and assortative mating shape genetic variation and influence demographic inference in admixed Cabo Verdeans

Genetic data can provide insights into population history, but first we must understand the patterns that complex histories leave in genomes. Here, we consider the admixed human population of Cabo Verde to understand the patterns of genetic variation left by social and demographic processes. First settled in the late 1400s, Cabo Verdeans are admixed descendants of Portuguese colonizers and enslaved West African people. We consider Cabo Verdes well-studied historical record alongside genome-wide SNP data from 563 individuals from 4 regions within the archipelago. We use genetic ancestry to test for patterns of nonrandom mating and sex-specific gene flow, and we examine the consequences of these processes for common demographic inference methods and for genetic patterns. Notably, multiple population genetic tools that assume random mating underestimate the timing of admixture, but incorporating non-random mating produces estimates more consistent with historical records. We consider how admixture interrupts common summaries of genomic variation such as runs-of-homozygosity (ROH). While summaries of ROH may be difficult to interpret in admixed populations, differentiating ROH by length class shows that ROH reflect historical differences between the islands in their contributions from the source populations and post-admixture population dynamics. Finally, we find higher African ancestry on the X chromosome than on the autosomes, consistent with an excess of European males and African females contributing to the gene pool. Considering these genomic insights into population history in the context of Cabo Verdes historical record, we can identify how assumptions in genetic models impact inference of population history more broadly.

evolutionary biology↗

bioRxiv2020

pixy: Unbiased estimation of nucleotide diversity and divergence in the presence of missing data

Population genetic analyses often use summary statistics to describe patterns of genetic variation and provide insight into evolutionary processes. Among the most fundamental of these summary statistics are{pi} and dXY, which are used to describe genetic diversity within and between populations, respectively. Here, we address a widespread issue in{pi} and dXY calculation: systematic bias generated by missing data of various types. Many popular methods for calculating{pi} and dXY operate on data encoded in the Variant Call Format (VCF), which condenses genetic data by omitting invariant sites. When calculating{pi} and dXY using a VCF, it is often implicitly assumed that missing genotypes (including those at sites not represented in the VCF) are homozygous for the reference allele. Here, we show how this assumption can result in substantial downward bias in estimates of{pi} and dXY that is directly proportional to the amount of missing data. We discuss the pervasive nature and importance of this problem in population genetics, and introduce a user-friendly UNIX command line utility, pixy, that solves this problem via an algorithm that generates unbiased estimates of{pi} and dXY in the face of missing data. We compare pixy to existing methods using both simulated and empirical data, and show that pixy alone produces unbiased estimates of{pi} and dXY regardless of the form or amount of missing data. In sum, our software solves a long-standing problem in applied population genetics and highlights the importance of properly accounting for missing data in population genetic analyses.

genetics↗

bioRxiv2019

Inversions shape the divergence of Drosophila pseudoobscura and D. persimilis on multiple timescales

By shaping meiotic recombination, chromosomal inversions can influence genetic exchange between hybridizing species. Despite the recognized importance of inversions in evolutionary processes such as divergence and speciation, teasing apart the effects of inversions over time remains challenging. For example, are their effects on sequence divergence primarily generated through creating blocks of linkage-disequilibrium pre-speciation or through preventing gene flux after speciation? We provide a comprehensive look into the influence of chromosomal inversions on gene flow throughout the evolutionary history of a classic system: Drosophila pseudoobscura and D. persimilis. We use extensive whole-genome sequence data to report patterns of introgression and divergence with respect to chromosomal arrangements. Overall, we find evidence that inversions have contributed to divergence patterns between Drosophila pseudoobscura and D. persimilis over three distinct timescales: 1) pre-speciation segregation of ancestral polymorphism, 2) post-speciation ancient gene flow, and 3) recent gene flow. We discuss these results in terms of our understanding of evolution in this classic system and provide cautions for interpreting divergence measures in similar datasets in other systems.

evolutionary biology↗