Biology subjects

Lachance, J.

Publications and source records attributed to Lachance, J..

9 recordsLinked to original sources

bioRxiv2025

Nuclear-encoded tRNA genes harbor substantial allelic diversity in three nematode species

Cytosolic transfer RNAs, which are encoded as hundreds of genes in nuclear genomes, experience exceptionally high mutation rates and have been hypothesized to confer substantial mutational load in natural populations. Although this phenomenon appears universal across multicellular eukaryotes, a comprehensive characterization of standing variation in tRNA repertoires is still lacking in any system. Here, we resolve within-species allelic variation in nuclear-encoded tRNAs in three nematode species: Caenorhabditis elegans, C. briggsae, and C. tropicalis. We show that these genes carry signatures of high rates of historical transcription-associated mutagenesis and of purifying selection, resulting in allelic variation that includes pervasive instances of within-gene mismatches between the amino acid recognized by the tRNA backbone and that indicated by the anticodon. Furthermore, patterns of tRNA genomic organization and variation differ markedly from those of protein-coding regions. Individual genomes harbor distinct complements of tRNA genes with predicted functional differences, an observation that coincides with recent evidence that variation in tRNA expression and regulation contributes to human disease. Our findings offer an entry point for identifying the micro-evolutionary processes that act on tRNA repertoires, and in turn connecting those processes to the macro-evolutionary patterns that have more frequently been the focus of study. Significance statementTransfer RNAs (tRNAs) are ancient and essential molecules that deliver amino acids to the growing polypeptide chain during protein synthesis. Despite their importance, little is known about how the genes encoding tRNAs vary among individuals, even though they accumulate large numbers of mutations due to their high rates of expression. Here, we report that three nematode species, including the model organism C. elegans, show within-species variation in their tRNA gene repertoires, which may cause differences in protein synthesis across individuals. Our findings may represent patterns common across multicellular species and they set the stage for future investigation into how this diversity influences cellular function and organismal fitness.

genetics↗

bioRxiv2024

The evolutionary fate of Neanderthal DNA in 30,780 admixed genomes with recent African-like ancestry

Following introgression, Neanderthal DNA was initially purged from non-African genomes, but the evolutionary fate of remaining introgressed DNA has not been explored yet. To fill this gap, we analyzed 30,780 admixed genomes with African-like ancestry from the All of Us research program, in which Neanderthal alleles encountered novel genetic backgrounds during the last 15 generations. Observed amounts of Neanderthal DNA approximately match expectations based on ancestry proportions, suggesting neutral evolution. Nevertheless, we identified genomic regions that have significantly less or more Neanderthal ancestry than expected and are associated with spermatogenesis, innate immunity, and other biological processes. We also identified three novel introgression desert-like regions in recently admixed genomes, whose genetic features are compatible with hybrid incompatibilities and intrinsic negative selection. Overall, we find that much of the remaining Neanderthal DNA in human genomes is not under strong selection, and complex evolutionary dynamics have shaped introgression landscapes in our species.

evolutionary biology↗

bioRxiv2024

Uncovering the genetic architecture and evolutionary roots of androgenetic alopecia in African men

Androgenetic alopecia is a highly heritable trait. However, much of our understanding about the genetics of male pattern baldness comes from individuals of European descent. Here, we examined a novel dataset comprising 2,136 men from Ghana, Nigeria, Senegal, and South Africa that were genotyped using a custom array. We first tested how genetic predictions of baldness generalize from Europe to Africa, finding that polygenic scores from European GWAS yielded AUC statistics that ranged from 0.513 to 0.546, indicating that genetic predictions of baldness in African populations performed notably worse than in European populations. Subsequently, we conducted the first African GWAS of androgenetic alopecia, focusing on self-reported baldness patterns at age 45. After correcting for present age, population structure, and study site, we identified 266 moderately significant associations, 51 of which were independent (p-value < 10-5, r2 < 0.2). Most baldness associations were autosomal, and the X chromosomes does not appear to have a large impact on baldness in African men. Finally, we examined the evolutionary causes of continental differences in genetic architecture. Although Neanderthal alleles have previously been associated with skin and hair phenotypes, we did not find evidence that European-ascertained baldness hits were enriched for signatures of ancient introgression. Most loci that are associated with androgenetic alopecia are evolving neutrally. However, multiple baldness-associated SNPs near the EDA2R and AR genes have large allele frequency differences between continents. Collectively, our findings illustrate how evolutionary history contributes to the limited portability of genetic predictions across ancestries.

genomics↗

bioRxiv2022

Different genetic architectures of complex traits and their relevance to polygenic score performance

BackgroundDespite the many insights gleaned from GWAS, polygenic predictions of complex traits have had limited success, particularly when these predictions are applied to individuals of non-European descent. A deeper understanding of the genetic architecture of complex traits may inform why some traits are easier to predict than others. MethodsExamining 163 complex traits from the UK Biobank, we compared and contrasted three aspects of genetic architecture (SNP heritability, LD variability, and genomic inequality) with three aspects of polygenic score performance (prediction accuracy in the source population, portability across populations, and trait divergence across populations). Here, genomic inequality refers to how unequally the genetic variance of each trait is distributed across the top trait-associated SNPs, as quantified via a novel application of Gini coefficients. ResultsConsistent with reduced statistical power, polygenic predictions of binary traits performed worse than predictions of quantitative traits. Traits with low Gini coefficients (i.e., highly polygenic architectures) include hip circumference as well as systolic and diastolic blood pressure. Traits with large population-level differences in polygenic scores include skin pigmentation and hair color. Focusing on 96 quantitative traits, we found that highly heritable traits were easier to predict and had predictions that were more portable to other ancestries. Traits with highly divergent polygenic score distributions across populations were less likely to have portable predictions. Intriguingly, LD variability was largely uninformative regarding the portability of polygenic predictions. This suggests that factors other than the differential tagging of causal SNPs drive the reduction in polygenic score accuracy across populations. Subsequent analyses identified suites of traits with similar genetic architecture and polygenic score performance profiles. Importantly, lifestyle and psychological traits tended to have low heritability, as well as poor predictability and portability. ConclusionsNovel metrics capture different aspects of trait-specific genetic architectures and polygenic score performance. Our findings also caution against the application of polygenic scores to traits like general happiness, alcohol frequency, and average income, especially when polygenic scores are applied to individuals who have an ancestry that differs from the original source population.

genomics↗

bioRxiv2021

Ancient DNA reveals that few GWAS loci have been strongly selected during recent human history

Genetic data from ancient humans has provided new evidence in the study of loci thought to be under historic selection, and thus is a powerful tool for identifying instances of selection that might be missed by methods that use present-day samples alone. Using a curated set of disease-associated variants from the NHGRI-EBI GWAS Catalog, we provide an analysis to identify disease-associated variants that bear signatures of selection over time. After accounting for the fact that not every ancient individual contributed equally to modern genomes, a Bayesian inference method was used to infer allele frequency trajectories over time and determine which disease-associated loci exhibit signatures of natural selection. Of the 2,709 variants analyzed in this study, 895 show at least a weak signature of selection (|s| > 0.001), including multiple variants that are introgressed from Neanderthals. However, only nine disease-associated variants show a signature of strong selection (|s| > 0.01). Additionally, we find that many risk-associated alleles have increased in frequency during the past 10,000 years. Overall, we find that disease-associated variants from GWAS are governed by nearly neutral evolution. Exceptions to this broad pattern include GWAS loci that protect against asthma and variants in MHC genes. Ancient samples allow us an unprecedented look at how our species has changed over time, and our results represent an important early step in using this new source of data to better understand the evolution of hereditary disease risks.

evolutionary biology↗

bioRxiv2019

A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa

Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. We find that samples from Ghana and Nigeria cluster together, while samples from Senegal and South Africa yield distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores were also generated for each genome in the MADCaP pilot dataset, and we found that predicted risks of CaP are lower in Senegal and higher in Nigeria.\n\nSignificanceWe have developed an Africa-specific genotyping array which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.

genomics↗

bioRxiv2018

Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity, while contributing to health and disease in human populations

Regulatory DNA has the potential to be adaptive, and large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans. For the first time, a comprehensive study of adaptive eQTLs is possible. Many eQTLs have large allele frequency differences between populations, and these differences can be due to natural selection. Here, we combined population branch statistics with tissue-specific eQTL data to identify positively selected loci in human populations. Adaptive eQTLs tend to affect fewer tissues than non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results suggest that pleiotropy can inhibit adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we find that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for adaptive outliers. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. These results reveal tissues that have been the targets of adaptation during the last 100,000 years of human evolution. The strongest adaptive signal in many regions of the human genome is an eQTL, including an eQTL associated with the Duffy blood group and malaria resistance. Scans of selection also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that adaptive eQTLs have played an important role in human evolution.

genomics↗

bioRxiv2017

Ascertainment bias can create the illusion of genetic health disparities

BackgroundAccurate assessment of health disparities requires unbiased knowledge of genetic risks in different populations. Unfortunately, most genome-wide association studies use genotyping arrays and European samples. Here, we integrate whole genome sequence data from global populations, results from thousands of GWAS, and extensive computer simulations to identify how genetic disease risks can be misestimated.\n\nResultsIn contrast to null expectations, we find that risk allele frequencies at known disease loci are significantly different for African populations compared to other continents. Strikingly, ancestral risk alleles are found at 9.51% higher frequency in Africa and derived risk alleles are found at 5.40% lower frequency in Africa. By simulating GWAS with different study populations, we find that non-African cohorts yield disease associations that have biased allele frequencies and that African cohorts yield disease associations that are relatively free of bias. We also find empirical evidence that genotyping arrays and SNP ascertainment bias contribute to continental differences in risk allele frequencies. Because of these causes, polygenic risk scores can be grossly misestimated for individuals of African descent. Importantly, continental differences in risk allele frequencies are only moderately reduced if GWAS use whole genome sequences and hundreds of thousands of cases and controls. Finally, comparisons between uncorrected and corrected genetic risk scores reveal the benefits of considering whether risk alleles are ancestral or derived.\n\nConclusionsOur results imply that caution must be taken when extrapolating GWAS results from one population to predict disease risks in another population.

genomics↗

bioRxiv2017

The Genomic Health Of Ancient Hominins

The genomes of ancient humans, Neandertals, and Denisovans contain many alleles that influence disease risks. Using genotypes at 3180 disease-associated loci, we estimated the disease burden of 147 ancient genomes. After correcting for missing data, genetic risk scores were generated for nine disease categories and the set of all combined diseases. These genetic risk scores were used to examine the effects of different types of subsistence, geography, and sample age on the number of risk alleles in each ancient genome. On a broad scale, hereditary disease risks are similar for ancient hominins and modern-day humans, and the GRS percentiles of ancient individuals span the full range of what is observed in present day individuals. In addition, there is evidence that ancient pastoralists may have had healthier genomes than hunter-gatherers and agriculturalists. We also observed a temporal trend whereby genomes from the recent past are more likely to be healthier than genomes from the deep past. This calls into question the idea that modern lifestyles have caused genetic load to increase over time. Focusing on individual genomes, we find that the overall genomic health of the Altai Neandertal is worse than 97% of present day humans and that Otzi the Tyrolean Iceman had a genetic predisposition to gastrointestinal and cardiovascular diseases. As demonstrated by this work, ancient genomes afford us new opportunities to diagnose past human health, which has previously been limited by the quality and completeness of remains.

genomics↗