Biology subjects

Meyer, W. K.

Publications and source records attributed to Meyer, W. K..

7 recordsLinked to original sources

bioRxiv2026

RERconverge Update: Runtime Reduction and Analysis Function Overhaul

MotivationConvergent evolution, or the independent acquisition of similar phenotypes in distinct lineages, provides a powerful framework for investigating genomic changes associated with a phenotype. This paper details an update to RERconverge, a powerful R package that tests for associations between gene relative evolutionary rates (RERs) and convergent phenotypes to infer genomic regions associated with traits or selective pressures. We introduce new customizable analysis choices and scalable and efficient algorithms that can process larger genomic datasets, a critical improvement as genomic data become available for more species. ResultsModifications to core functions in the RERconverge pipeline resulted in an immense speedup (by a factor of up to 28.6). The function that tests for associations between phenotypes and RERs has been expanded to include two new analytical methods for outlier control; we also provide here a summary of the statistical tests users can perform, along with their use cases. Availability and implementationThe code and walkthrough vignettes for the package are available at https://github.com/nclark-lab/RERconverge. ContactNathan L. Clark nclark@pitt.edu; Maria Chikina mchikina@pitt.edu

genomics↗

bioRxiv2023

RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution

Comparative genomics approaches seek to associate evolutionary genetic changes with the evolution of phenotypes across a phylogeny. Many of these methods, including our evolutionary rates based method, RERconverge, lack the capability of analyzing non-ordinal, multicategorical traits. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of multi-categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogenetic permulations on multi-categorical traits. In addition to demonstrating our new method on a three-category diet phenotype, we compare its performance to naive pairwise binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We also present a diagnostic analysis of the new permulations approach demonstrating how the method scales with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotype and that the new ancestral reconstruction drives an improvement in our ability to capture diet-related enriched pathways. Our categorical permulations were able to account for non-uniform null distributions and correct for non-independence in gene rank during pathway enrichment analysis. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution.

bioinformatics↗

bioRxiv2023

Convergent molecular constraint in mammalian carnivores: Selection on liver and kidney functions during the evolution of more carnivorous diets

Mammalia comprises a great diversity of diet types and associated adaptations. An understanding of the genomic mechanisms underlying these adaptations may offer insights for improving human health. Comparative genomic studies of diet that employ taxonomically restricted analyses or simplified diet classifications may suffer reduced power to detect molecular convergence associated with diet evolution. Here, we used a quantitative carnivory score--indicative of the amount of animal protein in the diet--for 80 mammalian species to detect significant correlations between the relative evolutionary rates of genes and changes in diet. We identified six genes--ACADSB, CLDN16, CPB1, PNLIP, SLC13A2, and SLC14A2--that experienced significant changes in evolutionary constraint alongside changes in carnivory score, becoming less constrained in lineages evolving more herbivorous diets. We further considered the biological functions associated with diet evolution and observed that pathways related to amino acid and lipid metabolism, biological oxidation, and small molecule transport experienced reduced purifying selection as lineages became more herbivorous. Liver and kidney functions showed similar patterns of constraint with dietary change. Our results indicate that, in highly carnivorous lineages, selection acts on the liver and kidneys to maintain sufficient metabolism and excretion of substances found in excess in carnivorous diets. These biological functions become less important with the evolution of increasing herbivory, so experience a relaxation of constraint in more herbivorous lineages.

genomics↗

bioRxiv2022

Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements

Vocal learning, the ability to modify vocal behavior based on experience, is a convergently evolved trait in birds and mammals. To identify genomic elements associated with vocal learning, we integrated new experiments conducted in the brain of the Egyptian fruit bat with analyses of the genomes of 222 placental mammals. We first identified an anatomically specialized region of the bat motor cortex containing direct monosynaptic projections to laryngeal motoneurons. Using wireless neural recordings of this brain region in freely vocalizing bats, we verified that single neuron activity in this region relates to vocal production. We profiled the open chromatin of this vocal-motor region, which we used to train machine learning models to identify enhancers associated with vocal learning across mammals. We found 201 proteins and 45 candidate enhancers that display convergent evolution associated with vocal learning, many of which overlapped loci associated with human speech disability. One such locus contains the neurodevelopmental transcription factors TSHZ3 and ZNF536 and multiple candidate vocal learning-associated enhancers, suggesting the co-evolution of protein and regulatory sequences underlying vocal learning. One-Sentence SummaryAnalyses of bat neural activity and epigenomic data in a brain region involved in vocal behavior were used to identify proteins and regulatory elements associated with vocal learning in mammals.

neuroscience↗

bioRxiv2022

Rapid reduction of Paraoxonase expression followed by inactivation across semiaquatic mammals suggests adaptive benefit of gene loss

Convergent adaptation to the same environment by multiple lineages frequently involves rapid evolutionary change at the same genes, implicating these genes as important for environmental adaptation. Such adaptive molecular changes may yield either change or loss of protein function; loss of function can eliminate newly deleterious proteins or reduce energy necessary for protein production. We previously found a striking case of recurrent pseudogenization of the Paraoxonase 1 (Pon1) gene among aquatic mammal lineages - Pon1 became a pseudogene with genetic lesions, such as stop codons and frameshifts, at least four times independently in aquatic and semiaquatic mammals. Here, we assess the landscape and pace of pseudogenization by studying Pon1 sequences, expression levels, and enzymatic activity across four aquatic and semiaquatic mammal lineages: pinnipeds, cetaceans, otters, and beavers. We observe in beavers and pinnipeds an unexpected reduction in expression of Pon3, a paralog with similar expression patterns but different substrate preferences. Ultimately, in all lineages with aquatic/semiaquatic members, we find that preceding any coding level pseudogenization events in Pon1, there is a drastic decrease in expression, followed by relaxed selection, thus allowing accumulation of disrupting mutations. The recurrent loss of Pon1 function in aquatic/semiaquatic lineages is consistent with a benefit to Pon1 functional loss in aquatic environments. Accordingly, we examine diving and dietary traits across pinniped species as potential driving forces of Pon1 functional loss. We find that loss is best correlated with diving activity and likely results from changes in selective pressures associated with hypoxia and hypoxia-induced inflammation.

evolutionary biology↗

bioRxiv2022

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Protein-coding differences between mammals often fail to explain phenotypic diversity, suggesting involvement of enhancers, often rapidly evolving regions that regulate gene expression. Identifying associations between enhancers and phenotypes is challenging because enhancer activity is context-dependent and may be conserved without much sequence conservation. We developed TACIT (Tissue-Aware Conservation Inference Toolkit) to associate open chromatin regions (OCRs) with phenotypes using predictions in hundreds of mammalian genomes from machine learning models trained to learn tissue-specific regulatory codes. Applying TACIT for motor cortex and parvalbumin-positive interneurons to neurological phenotypes revealed dozens of new OCR-phenotype associations. Many associated OCRs were near relevant genes, including brain size-associated OCRs near genes mutated in microcephaly or macrocephaly. Our work creates a forward genomics foundation for identifying candidate enhancers associated with phenotype evolution. One Sentence SummaryA new machine learning-based approach associates enhancers with the evolution of brain size and behavior across mammals.

genomics↗

bioRxiv2018

RERconverge: an R package for associating evolutionary rates with convergent traits

Motivation: When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits.\n\nResults: Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results.\n\nAvailability: RERconverge source code, documentation, and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila, and yeast are available at https://bit.ly/2J2QBnj.\n\nContact: mchikina@pitt.edu\n\nSupplementary information: Supplementary information, containing detailed vignettes for usage of RERconverge, are available at Bioinformatics online.

evolutionary biology↗