Biology subjects

Teterina, A. A.

Publications and source records attributed to Teterina, A. A..

4 recordsLinked to original sources

bioRxiv2026

GPU accelerated population genetics statistics using pg_gpu

Population genetics summary statistics--diversity, divergence, linkage disequilibrium, selection scans, and dimensionality reduction--are fundamental across human, agricultural, and ecological genomics. As whole-genome sequencing datasets have grown to hundreds of thousands of individuals, the cost of computing these statistics on conventional CPU implementations has become a major bottleneck: windowed scans of a single chromosome arm can take hours to days, and computation of pairwise linkage-disequilibrium statistics useful for demographic inference scales as O(n2) in sample size, often exceeding wall-clock budgets entirely. We present pg_gpu, a Python library implementing a comprehensive catalog of population-genetics summary statistics as fused CUDA kernels on NVIDIA GPUs. pg_gpu covers eleven categories spanning diversity and neutrality tests, divergence, admixture, the site-frequency spectrum, linkage disequilibrium, haplotype-based selection scans, dimensionality reduction (PCA, randomized PCA, local PCA / lostruct), distance distributions, relatedness, resampling, and a generalized weighted-SFS framework for custom{omega} estimators. On the full Ag1000G Phase 3 chromosome 3R arm (2,940 haplotypes, 10.9 million variants) pg_gpu agrees with scikit-allel and PLINK2 to machine precision while delivering a median 139x and maximum 1,096x speedup. For the multi-population LD statistics used by moments for demographic inference, pg_gpu is a drop-in replacement that yields a ~1,750-fold speedup over the native implementation. Whole chromosome arm scans, lostruct screens, and calculation of LD statistics complete on a single NVIDIA A100 in seconds to a few minutes.

evolutionary biology↗

bioRxiv2022

Genetic diversity landscapes in outcrossing and selfing Caenorhabditis nematodes

Caenorhabditis nematodes form an excellent model for studying how the mode of reproduction affects genetic diversity, as some species reproduce via outcrossing whereas others can self-fertilize. Currently, chromosome-level patterns of diversity and recombination are only available for self-reproducing Caenorhabditis, making the generality of genomic patterns across the genus unclear given the profound potential influence of reproductive mode. Here we present a whole-genome diversity landscape, coupled with a new genetic map, for the outcrossing nematode C. remanei. We demonstrate that the genomic distribution of recombination in C. remanei, like the model nematode C. elegans, shows high recombination rates on chromosome arms and low rates toward the central regions. Patterns of genetic variation across the genome are also similar between these species, but differ dramatically in scale, being 10-fold greater for C. remanei. Historical reconstructions of variation in effective population size over the past million generations echo this difference in polymorphism. Evolutionary simulations demonstrate how selection, recombination, mutation, and selfing shape variation along the genome, and that multiple drivers can produce patterns similar to those observed in natural populations. Convolutional neural networks demonstrate the potential for classifying distinct evolutionary scenarios in simulated populations. Distinguishing these forces confidently with the empirical data, however, will benefit from larger population genomic samples from multiple populations and consideration of an even more extensive training set of simulations.

evolutionary biology↗

bioRxiv2020

Chromosome-level assembly of the Caenorhabditis remanei genome reveals conserved patterns of nematode genome organization

The nematode Caenorhabditis elegans is one of the key model systems in biology, including possessing the first fully assembled animal genome. Whereas C. elegans is a self-reproducing hermaphrodite with fairly limited within-population variation, its relative C. remanei is an outcrossing species with much more extensive genetic variation, making it an ideal parallel model system for evolutionary genetic investigations. Here, we greatly improve on previous assemblies by generating a chromosome-level assembly of the entire C. remanei genome (124.8 Mb of total size) using long-read sequencing and chromatin conformation capture data. Like other fully assembled genomes in the genus, we find that the C. remanei genome displays a high degree of synteny with C. elegans despite multiple within-chromosome rearrangements. Both genomes have high gene density in central regions of chromosomes relative to chromosome ends and the opposite pattern for the accumulation of repetitive elements. C. elegans and C. remanei also show similar patterns of inter-chromosome interactions, with the central regions of chromosomes appearing to interact with one another more than the distal ends. The new C. remanei genome presented here greatly augments the use of the Caenorhabditis as a platform for comparative genomics and serves as a basis for molecular population genetics within this highly diverse species.

genomics↗

bioRxiv2019

Degradation of the repetitive genomic landscape in a close relative of C. elegans

The abundance, diversity, and genomic distribution of repetitive elements is highly variable among species. These patterns are thought to be driven in part by reproductive mode and the interaction of selection and recombination, and recombination rates typically vary by chromosomal position. In the nematode C. elegans, repetitive elements are enriched at chromosome arms and depleted on centers, and this mirrors the chromosomal distributions of other genomic features such as recombination rate. How conserved is this genomic landscape of repeats, and what evolutionary forces maintain it? To address this, we compared the genomic organization of repetitive elements across five Caenorhabditis species with chromosome-level assemblies. As previously reported, repeat content is enriched on chromosome arms in most Caenorhabditis species, and no obvious patterns of repeat content associated with reproductive mode were observed. However, the fig-associated Caenorhabditis inopinata has experienced rampant repetitive element expansion and reveals no association of global repeat content with chromosome position. Patterns of transposable element superfamily-specific distributions reveal this global pattern is driven largely by a few transposable element superfamilies that in C. inopinata have expanded in number and have weak associations with chromosome position. Additionally, 15% of predicted protein-coding genes in C. inopinata align to transposon-related proteins. When these are excluded, C. inopinata has no enrichment of genes in chromosome centers, in contrast to its close relatives who all have such clusters. Forward evolutionary simulations reveal that chromosomal heterogeneity in recombination rate is insufficient for generating structured genomic repetitive landscapes. Instead, heterogeneity in the fitness effects of transposable element insertion is needed to promote heterogeneity in repetitive landscapes. Thus, patterns of gene density along chromosomes are likely drivers of global repetitive landscapes in this group, although other historical or genomic factors are needed to explain the idiosyncrasy of genomic organization of various transposable element taxa within C. inopinata. Taken together, these results highlight the power of comparative genomics and evolutionary simulations in testing hypotheses regarding the causes of genome organization.

evolutionary biology↗