Biology subjects

de Vries, D.

Publications and source records attributed to de Vries, D..

6 recordsLinked to original sources

bioRxiv2023

Comparison of dental topography of marmosets and tamarins (Callitrichidae) to other platyrrhine primates using a novel freeware pipeline

Dental topographic metrics (DTMs), which quantify different aspects of the shape of teeth, are powerful tools for studying dietary adaptation and evolution in mammals. However, comparative samples of scanned mammal teeth suitable for analysis with DTMs remain limited in size and scope, with little or no representation of some major lineages, even within well-studied clades such as primates. In addition, current DTM protocols usually rely on proprietary software, which may be unavailable to many researchers for reasons of cost. We address these issues in the context of a DTM analysis of the primate clade Platyrrhini ("New World monkeys") by: 1) presenting a large comparative sample of scanned second lower molars (m2s) of callitrichids (marmosets and tamarins), which were previously underrepresented in publicly available platyrrhine datasets; and 2) giving full details of an entirely freeware pipeline for DTM analysis. We also present an updated discrete dietary classification scheme for extant platyrrhines, based on cluster analysis of dietary data extracted from 98 primary studies. Our freeware pipeline performs equally well in dietary classification accuracy of an existing sample of platyrrhine m2s (excluding callitrichids) as a published protocol that uses proprietary software, at least when multiple DTMs are combined. Individual DTMs however, sometimes showed very different results in classification accuracies between that of our freeware pipeline and that of the proprietary protocol, most likely due to the differences in the smoothing functions used. The addition of callitrichids still resulted in high classification accuracy in predicting diet with combined DTMs, although accuracy was considerably higher when molar size was included (90%) than excluded (73%). We conclude that our new freeware DTM pipeline is capable of accurately predicting diet in platyrrhines based on tooth shape and size, and so is suitable for inferring probable diet of taxa for which direct dietary information is unavailable, such as fossil species.

evolutionary biology↗

bioRxiv2023

Large-scale phylogenomics uncovers a complex evolutionary history and extensive ancestral gene flow in an African primate radiation

Understanding the drivers of speciation is fundamental in evolutionary biology, and recent studies highlight hybridization as a potential facilitator of adaptive radiations. Using whole-genome sequencing data from 22 species of guenons (tribe Cercopithecini), one of the worlds largest primate radiations, we show that rampant gene flow characterizes their evolutionary history, and identify ancient hybridization across deeply divergent lineages differing in ecology, morphology and karyotypes. Lineages experiencing gene flow tend to be more species-rich than non-admixed lineages. Mitochondrial transfers between distant lineages were likely facilitated by co-introgression of co-adapted nuclear variants. Although the genomic landscapes of introgression were largely lineage specific, we found that genes with immune functions were overrepresented in introgressing regions, in line with adaptive introgression, whereas genes involved in pigmentation and morphology may contribute to reproductive isolation. This study provides important insights into the prevalence, role and outcomes of ancestral hybridization in a large mammalian radiation.

evolutionary biology↗

bioRxiv2023

The landscape of tolerated genetic variation in humans and primates

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole genome sequencing data for 809 individuals from 233 primate species, and identified 4.3 million common protein-altering variants with orthologs in human. We show that these variants can be inferred to have non-deleterious effects in human based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases. One Sentence SummaryDeep learning classifier trained on 4.3 million common primate missense variants predicts variant pathogenicity in humans.

genomics↗

bioRxiv2023

A global catalog of whole-genome diversity from 233 primate species

The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology, and is urgent given severe threats these species are facing. Here, we present high coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human-specific. This study will open a wide range of research avenues for future primate genomic research. One-Sentence SummaryThe whole genome sequences of 233 primate species provide insight into the determinants of genetic diversity, phylogenomics, and human uniqueness.

genomics↗

bioRxiv2022

Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data

BackgroundExpression quantitative trait loci (eQTL) studies have shown how genetic variants affect downstream gene expression. To identify the upstream regulatory processes, single-cell data can be used. Single-cell data also offers the unique opportunity to reconstruct personalized co-expression networks--by exploiting the large number of cells per individual, we can identify SNPs that alter co-expression patterns (co-expression QTLs, co-eQTLs) using a limited number of individuals. ResultsTo tackle the large multiple testing burden associated with a genome-wide analysis (i.e. the need to assess all combinations of SNPs and gene pairs), we conducted a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets from three studies (reflecting 173 unique participants and 1 million cells) using a novel filtering strategy followed by a permutation-based approach. Before analysis, we evaluated the co-expression patterns to be used for co-eQTL identification using different external resources. The subsequent analysis identified a robust set of cell-type-specific co-eQTLs for 72 independent SNPs that affect 946 gene pairs, which we then replicated in a large bulk cohort. These co-eQTLs provide novel insights into how disease-associated variants alter regulatory networks. For instance, one co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell-activation and autoimmune disease. Among these genes, we identified enrichment for targets of five T-cell-activation-related transcriptional factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases. ConclusionOur co-eQTL results highlight the importance of studying gene regulation at the context-specific level to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy--combined with our technical guidelines--will soon identify many more co-eQTLs, further helping to elucidate unknown disease mechanisms.

genetics↗

bioRxiv2021

Total evidence tip-dating phylogeny of platyrrhine primates and 27 well-justified fossil calibrations for primate divergences

Phylogenies with estimates of divergence times are essential for investigating many evolutionary questions. In principle, "tip-dating" is arguably the most appropriate approach, with fossil and extant taxa analyzed together in a single analysis, and topology and divergence times estimated simultaneously. However, "node-dating" (as used in many molecular clock analyses), in which fossil evidence is used to calibrate the age of particular nodes a priori, will probably remain the dominant approach, due to various issues with analyzing morphological and molecular data together. Tip-dating may nevertheless play a key role in robustly identifying fossil taxa that can be used to inform node-dating calibrations. Here, we present tip-dating analyses of platyrrhine primates (so-called "New World monkeys") based on a total evidence dataset of 418 morphological characters and 10.2 kb of DNA sequence data from 17 nuclear genes, combined from previous studies. The resultant analyses support a late Oligocene or early Miocene age for crown Platyrrhini (composite age estimate: 20.7-28.2 Ma). Other key findings include placement of the early Miocene putative cebid Panamacebus outside crown Platyrrhini, equivocal support for Proteropithecia being a pitheciine, and support for a clade comprising three subfossil platyrrhines from the Caribbean (Xenothrix, Antillothrix and Paralouatta), related to Callicebinae. Based on these results and the available literature, we provide a list of 27 well-justified node calibrations for primate divergences, following best practices: 17 within Haplorhini, five within Strepsirrhini, one for crown Primates, and four for deeper divergences within Euarchontoglires. In each case, we provide a hard minimum bound, and for 23 of these we also provide a soft maximum bound and a suggested prior distribution. For each calibrated node, we provide the age of the oldest fossil of each daughter lineage that descends from it, which allows use of the "CladeAge" method for specifying priors on node ages.

evolutionary biology↗