Biology subjects

Akey, J. M.

Publications and source records attributed to Akey, J. M..

16 recordsLinked to original sources

bioRxiv2026

Gene flux shapes diversity and evolution of the ancient 17q21.31 inversion polymorphism

A hallmark of chromosomal inversions is that they suppress recombination between haplotypes, allowing inversion haplotypes to persist as single co-inherited units. To determine the extent to which inversions nevertheless permit genetic exchange, we investigated a common 979-kb inversion polymorphism at the human 17q21.31 locus. This locus exhibits deep divergence between the reference (H1) and inverted (H2) haplotypes, extensive segmental duplications (SDs) flanking the inversion, and association with neurodegenerative diseases, developmental disorders, and fertility-related phenotypes. Using single-cell sperm genome sequencing data, we directly measured recombination rates between H1 and H2 haplotypes and found near-complete suppression of single-crossover events between the haplotypes. The rare single crossovers that did occur were mediated by non-allelic homologous recombination between shared H1 and H2 SDs, generating novel duplication architectures. In contrast, two-switch events consistent with gene conversion or double crossovers, spanning 17-150 kb, occurred throughout the inversion at rates exceeding genome-wide estimates for events of comparable size. Consistent with recurring genetic exchange, we identified 99 distinct H1-H2 recombinant haplotypes segregating in All of Us genomes, including 26 with combinations of H1 and H2 SDs. These recombinant haplotypes facilitated dissection of the inversion's effects on fertility-related phenotypes; using a large parent-embryo dataset, we found that H2 additively increases female crossover rates across chromosomes and that KANSL1 duplications do not explain this effect. Finally, ancestral recombination graphs dated H1-H2 gene flux (the exchange of genetic material between alternative arrangements) to approximately 100-500 thousand years ago, revealing that H1 and H2 haplotypes have co-segregated for at least half a million years. Together, these results demonstrate that inversions can be permeable barriers to recombination, with ongoing gene flux influencing the diversity and evolution of inversion polymorphisms.

genomics↗

bioRxiv2026

A Principled Framework for Using Correlated Traits to Improve Risk Prediction

Although many complex phenotypes and diseases are influenced by shared genetic and environmental factors, risk prediction methods typically rely on genetic information from a single trait, leaving a rich source of predictive information largely unexploited. Phenotypic correlations can potentially be used to improve the accuracy of polygenic scores (PGS), but the conditions under which correlated traits meaningfully enhance prediction remain poorly understood. Here, we develop a general theoretical and simulation framework that quantifies the extent to which correlated "helper" traits improve predictive accuracy and identifies the factors that determine the magnitude of these gains. We show that helper traits can substantially improve predictive accuracy, with the magnitude of these gains governed by baseline model performance, genetic and environmental correlations, and the heritability of the target and helper traits, providing principled guidance for helper-trait selection. Paradoxically, when the target trait is itself weakly heritable, helper traits need not be highly heritable to substantially improve the accuracy of PGS, because low-heritability traits can still capture non-redundant environmental factors shared with the target trait. We empirically evaluated the use of helper traits by developing PGS models to predict type 2 diabetes using data from the UK Biobank. Helper traits substantially improved predictive accuracy relative to a single-trait PGS (AUC-ROC = 0.907 versus 0.677) and achieved performance comparable to models that use HbA1c (AUC-ROC = 0.889), the current clinical gold-standard biomarker. Our results establish a general theoretical and practical framework for exploiting correlated traits to improve polygenic prediction, provide principled guidance for selecting informative helper traits, and demonstrate how shared genetic and environmental architecture can be leveraged to substantially increase predictive accuracy. Furthermore, we developed an interactive web application to estimate the expected gain in accuracy from candidate helper traits using empirically measurable quantities.

genomics↗

bioRxiv2026

An interpretable machine learning framework for dog breed inference and ancestry decomposition

The over 300 currently recognized breeds of domesticated dogs are the culmination of centuries of intense artificial selection and recurrent population bottlenecks. While breed labels are widely used in genetic and veterinary studies, inferring breed identity from genomic data remains challenging due to the high dimensionality of genotype data, uneven sampling across breeds, and admixture resulting in mixed-breed individuals. Here, we present an interpretable machine learning framework to infer dog breed labels from genome-wide SNP data. Our approach combines dimensionality reduction with a multi-output random forest model that maps genetic variation to a continuous representation of breed membership, enabling both classification and mixed-breed inference. We apply this framework to the Dog Aging Project (DAP) dataset of 6,572 purebred and mixed-breed dogs across 100 breed classes, achieving 91.7% accuracy with an overlap-based metric, outperforming an ADMIXTURE-based benchmark that achieved 87.8% accuracy. Notably, we find that as few as 150 informative SNPs are sufficient to achieve near-maximal predictive performance, highlighting the highly structured nature of canine genetic variation. We also introduce a SNP importance score metric that links model predictions back to individual genetic variants. Analysis of top-ranked variants reveals loci previously associated with morphological, pigmentation, and behavioral traits, as well as candidate loci lacking prior phenotypic annotation, supporting both the biological relevance and discovery potential of the framework. Together, these results demonstrate that our framework provides an accurate, flexible, and interpretable approach to predict breed ancestry, with applications in veterinary genomics, canine population genetics, and the identification of loci underlying hallmark breed phenotypes.

bioinformatics↗

bioRxiv2026

A Denisovan-derived Alu insertion in OCA2 contributes to pigmentation diversity in present-day Melanesians

Modern humans inherited DNA from Neanderthals and Denisovans, but the contribution of introgressed structural variants (SVs) to present-day human phenotypes and adaptation remains poorly understood. Here, we used a graph-genome approach to genotype 96,277 SVs in 3,332 present-day humans and three high-coverage archaic hominin genomes, identifying 153 candidate introgressed SVs. These SVs are enriched for signatures of local adaptation compared to non-introgressed SVs (p-value = 3.04 x 10-7). Among these, we focused on a Denisovan-derived Alu insertion located in intron 18 of OCA2, a gene central to pigmentation. This introgressed Alu insertion is most frequently observed (> 60%) in Indigenous people from Bougainville Island of Melanesia, and is significantly associated with increased skin pigmentation in this region. To assess its functional impact, the Alu insertion was introduced into human induced pluripotent stem cells (iPSCs), which were subsequently differentiated into melanocytes. Melanocytes harboring the Alu insertion demonstrated elevated OCA2 expression, increased pigmentation, and higher levels of enhancer activity compared to controls. Collectively, these findings highlight introgressed SVs as a significant source of adaptive and phenotypic diversity in modern humans and implicate the Denisovan-derived Alu insertion in OCA2 in pigmentation variation among present-day Melanesian populations.

genomics↗

bioRxiv2026

Harnessing methylation signals inherent in long-read sequencing data for improved variant phasing

Haplotypes are linear sequences of co-inherited alleles along individual chromosomes and are central to genetic mapping, clinical variant interpretation, and inference of population history. However, accurate genome-wide haplotype reconstruction remains challenging. Long-read sequencing has the potential to dramatically improve haplotype inference, but existing methods do not directly leverage all the information embedded in these data. Here, we present LongHap, a read-based phasing method that integrates sequence and 5-methylcytosine (5mC) information in a unified probabilistic framework. By leveraging differentially methylated sites, LongHap resolves phase relationships between variants that are inaccessible to sequence-based approaches alone. Across multiple datasets and sequencing platforms, LongHap increases phase block lengths by up to 30% while substantially reducing switch error rates. LongHap rigorously embeds complex structural variants into the broader haplotype context using loopy belief propagation, enabling improved phasing of INDELs and other variant classes that are inherently difficult to resolve. Methylation-aware phasing also improves the accuracy and contiguity of haplotypes spanning rare variants and structurally complex, medically relevant genes across diverse ancestries, facilitating the interpretation of compound heterozygosity and haplotype-specific regulatory architectures. These results establish methylation-aware phasing as a general framework for improving genome-wide haplotype reconstruction, with broad applications across genetics and genomics.

bioinformatics↗

bioRxiv2026

Blood biomarkers and breed genetics of aging in pet dogs

Pet dogs share human-like environments while aging on a compressed timescale, making them a powerful translational model for aging research. Using genomic and phenotypic data from 7,627 dogs in the Dog Aging Project, including 976 profiled for 159 blood metabolites and clinical analytes, we generated the first GWAS catalog in dogs. Blood traits map to orthologous loci in dogs and humans, indicating deeply conserved pathways. Breed ancestry explains substantial variance in blood traits, and selection on visible characteristics such as fur type has pleiotropic metabolic effects. Leveraging mosaic ancestry in mixed-breed dogs and longitudinal mortality data, we identify blood traits elevated in short-lived breeds that predict individual mortality risk -- including globulin and potassium -- and protective traits enriched in long-lived breeds, such as ethanolamine. Although some aging-associated traits relate to growth hormone pathways, many do not, indicating that aging in dogs is multifactorial. These findings establish dogs as a translational system for identifying genetic determinants and biomarkers of aging relevant to extending healthy lifespans.

genetics↗

bioRxiv2026

Disordered but Different: The Unique Characteristics of Intrinsically Disordered Regions in Human Transcription Factors

Intrinsically disordered regions (IDRs) of proteins play key roles in multivalent interactions and the formation of biomolecular condensates. IDRs are widespread across the human proteome but are significantly enriched in transcription factor (TF) activation domains. However, it remains unclear why TF activation domains are enriched for IDRs and whether these regions are fundamentally distinct from IDRs in other proteins. Here, we comprehensively identify and analyze human IDRs and discover widespread functional, phenotypic, and evolutionary differences between TF and non-TF IDRs. Notably, in contrast to the broader proteome, TFs have evolved to become more disordered over time. Correspondingly, highly disordered TFs are more likely to regulate developmental processes, govern larger regulatory networks, and be subject to stronger regulatory constraints. TF IDRs are also enriched for pathogenic mutations relative to non-TF IDRs, and disorder content significantly predicts the mode of disease inheritance. Our results provide novel insights into how the evolution of gene regulation has uniquely shaped the molecular function and disease burden of TF IDRs.

genomics↗

bioRxiv2025

Pervasive context-dependent effects in the genetic architecture of complex and quantitative traits revealed by a powerful multiparent mapping population in yeast

The genetic dissection of complex traits remains a major challenge in basic and biomedical research, but is essential for understanding the molecular pathways that shape phenotypic variation and for developing predictive models of trait and disease susceptibility. Here, we leverage a novel multiparent mapping population of budding yeast, CYClones, comprising 9,344 haploid strains derived from eight genetically diverse founders, to identify quantitative trait loci (QTL) and systematically investigate the genetic architecture of growth rates across ten environmental conditions. In total, we identified 349 QTL (ranging from 19 to 49 QTL per growth condition) that explained between 61% and 100% of narrow sense heritability across traits. The high power and resolution of CYClones revealed that growth traits exhibited distinct, condition-specific genetic architectures with extensive allelic heterogeneity, where a QTL was the result of multiple tightly linked causal variants. We also observed pleiotropy among QTL with complex, trait-dependent allele effects that are also consistent with allelic heterogeneity. Genetic complexity varied widely, with some traits showing nearly Mendelian architectures, while others were highly polygenic. Introgressed loci played a prominent role in the landscape of growth rate QTL, including one that is localized to a 2.4 kb interval in the PCA1 cadmium transporter and explains 72% of variation in cadmium resistance and another large-effect QTL that alters growth on galactose via complex non-additive interactions with the transcriptional regulator GAL3. In both cadmium and galactose conditions, we show that allelic variation at a small number of loci stratifies the population into regulatory or physiological subgroups, each with distinct genetic architectures, a phenomenon we term allele-dependent stratification. Collectively, our results provide novel insights into the genetics of growth rates in budding yeast, the architectural features of genetic complexity, and demonstrate that CYClones is a powerful platform for revealing the molecular basis of complex trait variation.

genetics↗

bioRxiv2025

CYClones: A highly powered, fully genotyped, 8-parent yeast mapping population

The budding yeast Saccharomyces cerevisiae is a remarkably adaptable organism that thrives in diverse environments. Global sequencing of natural isolates has revealed extensive genetic diversity within the species. Here, we describe the construction and characterization of CYClones (Collaborative Yeast Cross clones), a library of 11,392 segregants generated from a multiparent funnel cross of eight genetically diverse parental strains. To enable the genetic dissection of complex traits, we imputed whole-genome sequences for all segregants and show that CYClones captures a substantial fraction of the global genetic diversity of S. cerevisiae. Haplotype representation is well maintained, with each parental haplotype present at >5% frequency across >95% of the genome. Simulations demonstrate that CYClones has [≥]95% power to detect variants with heritability as low as 0.36%, with mapping resolution often finer than the length of a single gene. In summary, CYClones is a powerful community resource for dissecting the genetic architecture of complex and quantitative traits, uncovering context-dependent mutational effects, and identifying causal variants underlying phenotypic diversity.

genetics↗

bioRxiv2025

MutagenesisForge: A Framework for Modeling Codon-Level Mutational Biases and Calculating dN/dS

The ratio of nonsynonymous (dN) to synonymous (dS) substitutions in protein-coding genes is a fundamental metric in molecular evolution to test hypotheses about the relative contributions of genetic drift and natural selection in shaping patterns of protein divergence (Williams et al., 2020). However, interpretation of dN/dS ratios may be confounded by sequence context and specific substitution models (Hughes, 2007; Kryazhimskiy & Plotkin, 2008). We present MutagenesisForge, a modular command-line tool and Python package for simulating codon-level mutagenesis and calculating dN/dS under user-specified conditions. At its core is the MutationModel interface which supports specific substitution matrices and ensures consistency across both Exhaustive and Contextual modes of simulation. These modes allow for users to test evolutionary hypotheses or to generate null distributions of dN/dS across a range of biologically relevant models. As large-scale DNA sequencing data sets continue to be generated both within and between species, MutagenesisForge offers a flexible platform for evolutionary analysis and hypothesis testing of mutational processes in protein-coding genes.

evolutionary biology↗

bioRxiv2025

Dogs and humans share biomarkers of mortality

There is growing interest in the use of molecular features as predictors of age, age-related disease risk and age-related mortality. A major shortcoming of this field, however, is the lack of suitable translational research models to identify and understand the underlying mechanisms of these predictive biomarkers in human populations. In particular, we lack a system which, like humans, is genetically variable, lives in diverse environments, and experiences aging-related chronic conditions treated in the context of a sophisticated health care system. Here, we present results from our analysis of data from the Dog Aging Project, a long-term longitudinal study of aging in more than 50,000 companion dogs. In particular, using longitudinal survival models, we present the striking finding of a strong, highly significant positive correlation between the effect of individual metabolites on all-cause mortality in humans, and the association of those same metabolites on all-cause mortality in dogs. We also find that across these independent human studies, the biomarkers identified are also highly correlated, strongly suggesting a general signature of mortality within the plasma metabolome across humans, and now in dogs as well. Given the many similarities between dogs and humans with respect to genetics, environment, disease, and disease treatment, and the fact that dogs are so much shorter lived than humans, we argue that dogs represent an extremely valuable translational model in our ongoing effort to understand the underlying molecular causes and consequences of age-related morbidity and mortality in humans.

systems biology↗

bioRxiv2025

Landscape of human protein-coding somatic mutations across tissues and individuals

Although somatic mutations are fundamentally important to human biology, disease, and aging, many outstanding questions remain about their rates, spectrum, and determinants in apparently healthy tissues. Here, we performed high-coverage exome sequencing on 265 samples from 14 GTEx donors sampled for a median of 17.5 tissues per donor (spanning 46 total tissues). Using a novel probabilistic method tailored to the unique structure of our data, we identified 8,470 somatic variants. We leverage our compendium of somatic mutations to quantify the burden of deleterious somatic variants among tissues and individuals, identify molecular features such as chromatin accessibility that exhibit significantly elevated somatic mutation rates, provide novel biological insights into mutational mechanisms, and infer developmental trajectories based on patterns of multi-tissue somatic mosaicism. Our data provides a high-resolution portrait of somatic mutations across genes, tissues, and individuals.

genomics↗

bioRxiv2024

A Refined Analysis of Neanderthal-Introgressed Sequences in Modern Humans with a Complete Reference Genome

BackgroundLeveraging long-read sequencing technologies, the first complete human reference genome, T2T-CHM13, corrects the assembly errors in prior references and addresses the remaining 8% of the genome. While the studies on archaic admixture in modern humans so far have been relying on the GRCh37 reference due to the archaic genome data, the impact of T2T-CHM13 in this field remains unknown. ResultsWe remapped the sequencing reads of the high-quality Altai Neanderthal and Denisovan genomes onto GRCh38 and T2T-CHM13 respectively. Compared with GRCh37, we found T2T-CHM13 has a significant improvement of read mapping quality in archaic samples. We then applied IBDmix to identify Neanderthal introgressed sequences in 2,504 individuals from 26 geographically diverse populations in different references. We observed different pre-phasing filtering strategies prevalently used in public data can largely impact determination of archaic ancestry, calling for consideration on the choice of filters. We discovered ~51Mb T2T-CHM13 unique Neanderthal sequences, which are predominantly located in regions where the variants distinct between the GRCh38 and T2T-CHM13 assemblies emerge. Besides, we unfolded new instances of population-specific archaic introgression in diverse populations, covering genes involved in metabolism, olfactory-related, and icon-channel. Finally, we integrated the introgressed sequences and adaptive signals with all references into a visualization database website, called ASH (www.arcseqhub.com), to facilitate the utilization of archaic alleles and adaptive signals in human genomics and evolutionary research. ConclusionsOur study refines the detection of archaic variations in modern humans, highlights the importance of T2T-CHM13 reference utility, and provides novel insights into functional consequences of archaic hominin admixture.

evolutionary biology↗

bioRxiv2022

The genomic landscape of Saccharomyces paradoxus introgression in geographically diverse Saccharomyces cerevisiae strains

Natural hybrids between many pairs of the Saccharomyces species have been observed. Hybridization can allow for rapid adaptation to new environments, and when followed by repeated backcrossing can lead to small pieces of introgressed sequence from an individual of one species remaining in the genome of an individual of another species. Introgressed sequences that persist over time are interesting both because they provide evidence of past hybridization events and because they may contribute to functional and phenotypic diversity. Previous studies have identified some examples of introgressed sequences in S. cerevisiae, but we sought to gain a more comprehensive understanding of the landscape of introgression in this species. We developed a simple, flexible approach based on a hidden Markov model to identify introgression in yeast genomes. We used our method to look for introgression in 93 diverse S. cerevisiae genomes from its closest relative, S. paradoxus. We found evidence of introgression in all strains we considered, but the amount and location of introgression varied widely. We show that introgression contributes substantially to the total genetic diversity within these strains, and has the potential to confound inferences of their evolutionary relationships. Further characterizing introgression across diverse Saccharomyces species may help us better understand their evolution and the role that hybridization has played in adaptation to new environments.

evolutionary biology↗

bioRxiv2021

Evolution of Human-specific Alleles Protecting Cognitive Function of Grandmothers

Late-onset Alzheimers Disease (LOAD) pathology is rare in our closest living evolutionary relatives (chimpanzees), which also express much lower microglial levels of CD33(Siglec-3)-a myelomonocytic receptor inhibiting innate immune reactivity by extracellular V-set domain recognition of sialic acid(Sia)-containing "self-associated molecular patterns" (SAMPs). We earlier showed that V-set domain-deficient CD33-variant allele, protective against LOAD, is derived and specific to hominin-lineage. We now report that CD33 also harbors multiple hominin-specific V-set domain mutations and explore selection forces that may have favored such genomic changes. N-glycolylneuraminic acid (Neu5Gc), the preferred Sia-ligand of ancestral CD33 is absent in humans, due to hominin-specific, fixed loss-of-function mutation in CMAH, which generates CMP-Neu5Gc from its precursor, CMP-N-acetylneuraminic acid (Neu5Ac). Extensive mutational analysis and MD-simulations indicate that fixed change in amino acid 21 of hominin V-set domain and conformational changes related to His45 corrected for Neu5Gc-loss by switching to Neu5Ac-recognition. Considering immune-evasive "molecular mimicry" of SAMPs by pathogens, we found that human-specific pathogens Neisseria gonorrhoeae and Group B Streptococcus (affecting fertility and fetuses/neonates respectively) selectively bind huCD33 and this binding is significantly impacted by amino acid 21 modification. Alongside LOAD-protective CD33 alleles, humans harbor additional, derived, population-universal, cognition-protective variants absent in "great ape" genomes. Interestingly, 11 of 13 SNPs in these human genes (including CD33), that protect the cognitive health of elderly populations, are not shared by genomes of archaic hominins: Neanderthals and Denisovans. Finally, we present a plausible evolutionary scenario to compile, correlate and comprehend existing knowledge about huCD33 evolution and suggest that grandmothering emerged in humans.

evolutionary biology↗

bioRxiv2017

Short tandem repeats with massive variation and functional consequences across strains of Arabidopsis thaliana

Short tandem repeat (STR) mutations may be responsible for more than half of the mutations in eukaryotic coding DNA, yet STR variation is rarely examined as a contributor to complex traits. We assess the scope of this contribution across a collection of 96 strains of Arabidopsis thaliana by massively parallel STR genotyping. We found that 95% of examined STRs are polymorphic, with a median of six alleles per STR in these strains. Modest STR expansions are found in most strains, some of which have evident functional effects. For instance, three of six intronic STR expansions are associated with intron retention. Coding STRs are depleted of variation relative to non-coding STRs, consistent with the action of purifying selection, and some STRs show hypervariable patterns consistent with diversifying selection. Finally, we detect dozens of novel STR-phenotype associations that could not be detected with SNPs alone, validating several with follow-up experiments. Our results demonstrate that STRs comprise a large, unascertained reservoir of functionally relevant genomic variation.

genomics↗