Biology subjects

Lou, R. N.

Publications and source records attributed to Lou, R. N..

7 recordsLinked to original sources

bioRxiv2026

The evolution of structural variation across 500 million years of vertebrate evolution

Structural variants (SVs) contribute substantially to genetic variation and play vital roles in adaptation and disease1,2. Nonetheless, SVs are poorly captured by short reads and thus remain understudied, especially in non-model organisms3,4. Here, using haplotype-resolved genome assemblies from >600 vertebrate species, we comprehensively survey the landscape of SVs across >500 million years of evolution. We identify 35.3 million SVs and 3.12 billion single nucleotide variants (SNVs) segregating between two representative haplotypes across species, with SVs impacting [~]12-fold more base pairs. SV and SNV heterozygosity are correlated across species, with endangered and threatened species exhibiting reduced genetic diversity. However, the contribution of SVs relative to SNVs fundamentally differs across major vertebrate clades: given the same number of SNVs, fishes, amphibians, and reptiles have 4.3-to-9.1 times the number of SVs than birds, and 1.7-to-3.6 times more than mammals. This reduction in the relative contribution of SVs in mammals and birds is linked to fewer non-repeat-associated SVs as well as lower transposable element (TE) abundance and diversity. We identify features underlying genomic instability across vertebrates, finding that SVs frequently occur in repetitive and SNV-rich regions and are mediated by both homology and non-canonical DNA structures. Notably, G-quadruplex structures are enriched 11.5-fold around SV breakpoints in birds, while Z-DNA structures are enriched 2.2-fold in cartilaginous fishes. TEs uniquely contribute to SVs both directly through transposition and indirectly by mediating ectopic recombination, with the proportion of TE-mediated SVs influenced by both genomic TE density and diversity. We identify >10,000 instances of recent TE turnover including extinction of LINE-2 in therian mammals and slowing of CR1 activity in passerine birds. Finally, we show that SVs have an outsized role in functional genetic variation and are >70 times more likely to strongly impact protein-coding sequences than SNVs. While SVs are on average deleterious, we identify extensive recurrent structural variation across multiple taxa in genes involved in sensory, immune, and metabolic systems. Together, this study highlights extraordinary variation in the abundance, composition, mechanism, and functional impact of SVs across vertebrates.

evolutionary biology↗

bioRxiv2026

A Pan-pangenome illuminates complex structural variation and selection in humans, chimpanzees, and bonobos

Complete, haplotype-resolved genome assemblies have provided unprecedented insight into the evolution of structurally complex, rapidly evolving regions of human genomes1-6; however, population-scale pangenome resources of our closest relatives, chimpanzees and bonobos (genus, Pan), are necessary to ascertain the origins and evolutionary context of these loci. Here, we sequence and assemble 58 haplotypes from four distinct Pan clades to high contiguity (median contig NG50=54 Mb), including eight near-T2T genomes. These genomes reveal previously intractable genetic variation increasing estimates of genome-wide genetic diversity 6-37% across populations compared to short-read estimates7. We identify recurrent structural polymorphisms across species impacting genes associated with immune response and host-pathogen interaction and find that structural variants (SVs) are 170- to 260-fold more likely than single nucleotide variants (SNVs) to exhibit high-impact effects across species. Contrasting SV patterns across primates we find that transposable element mutation rates differ by as much as threefold between species. We show that human disease-associated short tandem repeat (TR) loci have uniquely expanded in humans sensitizing our species to these TR-expansion disorders. Physically phased haplotypes enable reconstruction of genome-wide genealogical histories, uncovering ancient, functional genetic variation maintained by balancing selection, as well as signatures of recent adaptation in chimpanzee subspecies. Several malaria-associated loci exhibit ancient structural polymorphism, including the African great ape-specific glycophorin (GYP) gene expansion. We characterize the sequence, structure, and composition of diverse glycophorin haplotypes in humans and chimpanzees. We identify independent malaria-protective GYPA-B fusion events in humans and novel chimpanzee glycophorin genes resulting from both ancient and recent fusion events demonstrating parallel adaptations to pathogen resistance across hominins. Together, our resource highlights the critical importance of nonhuman primate population-scale pangenomics for understanding the evolution of complex genome structures and the biodiversity of our endangered closest living relatives.

evolutionary biology↗

bioRxiv2025

Machine learning-based prediction of human structural variation and characterization of associated sequence determinants

Structural variants (SVs) represent a major source of genetic diversity and play key roles in human disease and evolution. Yet, the extent to which local sequence context shapes the likelihood of structural variant formation remains poorly quantified. Here, we develop machine learning models to predict the occurrence of SVs across the human genome and characterize genomic determinants associated with their formation. We developed both a sequence only-based convolutional neural network (CNN) model as well as a random forest approach integrating diverse genomic annotations. Both models achieve high predictive performance individually (>90% AUROC) which can be further improved in an ensemble. The predictive ability of these models demonstrates that SV-prone regions can be accurately inferred from sequence context. Model interpretability techniques reveal key genomic contributors to SVs, including effects of sequence motifs such as microhomology and non-canonical DNA structures, as well as the presence of SV hotspots. We find that different classes of SVs exhibit distinct sequence determinants, with transposable elements and inversions displaying particularly unique signatures. Moreover, predicted SV probability correlates with allele frequency and gene functional constraint, indicating the potential utility of the model for variant effect prediction. These findings demonstrate that machine learning models trained on local sequence features can identify unstable genomic regions and provide a framework for quantifying SV susceptibility and SV variant effects in personalized genomics.

genetics↗

bioRxiv2025

Phylogenetically diverse introgression drives subtle population structure in Pacific rockfishes

Genomic methods have shown that admixture and introgression is common across animal taxa. Pacific rockfishes, genus Sebastes, are group of commercially important species that primarily inhabit inshore, shelf, and slope habitats along the North American west coast. Among these, Copper and Quillback Rockfishes (abbreviated to Copper and Quillback) are closely related species known to hybridize, particularly within the Salish Sea in North Americas Pacific Northwest. Here, we investigate genetic population structure and introgression patterns in Copper and Quillback from Alaska to California. Using whole-genome resequencing (WGS) across a broad geographic range, we seek to (1) compare population structure between these species, and (2) assess how introgression affects population structure patterns. Our analyses reveal that Copper exhibit much higher levels of population differentiation compared to Quillback, especially separating Salish Sea samples from all other populations. In contrast, Quillback populations appear to be nearly panmictic, with lower overall differentiation. Surprisingly, we detected signatures of introgression from 13 other rockfish species in Copper and 16 species in Quillback. This introgression was highly regional suggesting hybridization depended on geographic context and congener ranges. Yelloweye Rockfish introgression drives the strongest signal of regional population structure in Quillback. These findings provide novel insights into the range-wide genetic structure of these species and highlight that hybridization in Sebastes is phylogenetically broader than previously appreciated.

evolutionary biology↗

bioRxiv2025

Rapid turnover and recurrent structural variation at the 17q21.31 locus in modern and ancient human genomes, and primates

The 17q21.31 locus in humans harbors several complex structural haplotypes including a [~]970kb inversion. Different inversion haplotypes have been associated with susceptibility to microdeletions causing Koolen-de Vries syndrome and variation in fecundity and recombination rates. Here, using 210 haplotype-resolved human genome assemblies and pangenome graph-based approaches we characterize 11 distinct structural haplotypes, several of which have not been previously described. Extending our analyses to a set of haplotype-resolved great-ape genomes, we characterize the structure of an independent inversion in chimpanzees which extends an additional 650kb, encompasses 5 additional genes, and is [~]2 million years younger than the human inversion. We further determine that gorillas exhibit an independent duplication of the KANSL1 gene which may predispose them to Koolen-de Vries syndrome causing microdeletions. Using short read sequencing data we characterize 17q21.31 haplotype diversity worldwide in [~]5174 individuals from 107 populations finding increased frequencies of KANSL1 duplication-containing haplotypes in both European and South Asian populations as well as 8 double recombination events between inverted and non-inverted haplotypes ranging in size from 20-180kb. Finally, using 626 ancient Eurasian human genomes we show the frequency of haplotypes containing KANSL1 duplications has increased [~]6-fold over the past 12 thousand years in Europe. Together, our results highlight the dynamics, complexity, and recurrent, independent evolution of a medically relevant locus across humans and great apes.

genomics↗

bioRxiv2024

Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans

The adoption of agriculture, first documented [~]12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from [~]5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with more amylase gene copies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.

evolutionary biology↗

bioRxiv2019

The Effects of Quantitative Trait Architecture on Detection Power in Artificial Selection Experiments

Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTLs) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTLs affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of the above parameters can affect allele frequency dynamics at the QTLs and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTLs often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account in designing studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.

evolutionary biology↗