On the Decoupling of Evolutionary Changes in mRNA and Protein Levels

Molecular Biology and Evolution, Год журнала: 2023, Номер 40(8)

Опубликована: Июль 27, 2023

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein closer target natural selection but typically measured as amount mRNA. broad assumption that mRNA levels are good proxies for has been undermined by a number studies reporting moderate or weak correlations between two measures species. One biological explanation this discrepancy there compensatory evolution level regulation translation. However, we do not understand evolutionary conditions necessary occur nor expected strength correlation levels. Here, develop theoretical model coevolution investigate dynamics over time. We find widespread when stabilizing on level; observation held true variety regulatory pathways. When under directional selection, translation rate same were negatively correlated positively genes. These findings help results from comparative potentially enable researchers disentangle statistical hypotheses mismatch transcriptomic proteomic data.

Язык: Английский

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Macroevolutionary divergence of gene expression driven by selection on protein abundance

Science, Год журнала: 2025, Номер 387(6738), С. 1063 - 1068

Опубликована: Март 6, 2025

The regulation of messenger RNA (mRNA) and protein abundances is well-studied, but less known about the evolutionary processes shaping their relationship. To address this, we derived a new phylogenetic model applied it to multispecies mammalian data. Our analyses reveal (i) strong stabilizing selection on over macroevolutionary time, (ii) mutations affecting mRNA minimally impact abundances, (iii) evolve under align with (iv) adapt faster than owing greater mutational opportunity. These conclusions are supported by comparisons parameters independent functional genomic By decomposing selective influences mRNA-protein dynamics, our approach provides framework for discovering rules that drive divergence in gene expression.

Язык: Английский

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Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

PLoS Biology, Год журнала: 2024, Номер 22(10), С. e3002847 - e3002847

Опубликована: Окт. 9, 2024

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype environment focal trait. these 2 fields, there are sophisticated but disparate traditions aimed at tasks. The disconnect their respective approaches becoming untenable as questions in medicine, conservation biology, evolutionary biology increasingly rely on integrating data from within among species, once-clear conceptual divisions blurred. To help bridge this divide, we lay out general model describing covariance contributions quantitative phenotypes different individuals. Taking approach shows that standard models (e.g., genome-wide association studies; GWAS) phylogenetic comparative regression) can be interpreted special cases more quantitative-genetic model. fact share same core architecture means build unified understanding strengths limitations methods for controlling structure when testing associations. We develop intuition why spurious may occur analytically conduct population-genetic simulations traits. structural similarity problems phylogenetics enables us take methodological advances one field apply them other. demonstrate by showing how GWAS technique-including relatedness matrix (GRM) well its leading eigenvectors, corresponding principal components genotype matrix, regression model-can mitigate analyses. As case study, re-examine an analysis coevolution expression levels genes across fungal phylogeny show including eigenvectors covariates decreases false positive rate while simultaneously increasing true rate. More generally, work provides foundation integrative processes shape it.

Язык: Английский

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Constraints on the optimization of gene product diversity

Molecular Systems Biology, Год журнала: 2025, Номер unknown

Опубликована: Апрель 10, 2025

Abstract RNA and proteins can have diverse isoforms due to post-transcriptional post-translational modifications. A fundamental question is whether these are mostly beneficial or the result of noisy molecular processes. To assess plausibility explanations, we developed mathematical models depicting different regulatory architectures investigated isoform evolution under multiple population genetic regimes. We found that factors beyond selection, such as effective size number cis -acting loci, significantly influence evolutionary outcomes. sub-optimal phenotypes more likely evolve when populations small and/or -loci large. also discovered opposing selection on - trans loci constrain adaptation, leading a non-monotonic relationship between optimization. More generally, our provide quantitative framework for developing statistical tests analyze empirical data; demonstration this, analyzed A-to-I editing levels in coleoids be largely consistent with non-adaptive explanations.

Язык: Английский

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Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Фев. 12, 2024

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype environment focal trait. these two fields, there are sophisticated but disparate traditions aimed at tasks. The disconnect their respective approaches becoming untenable as questions in medicine, conservation biology, evolutionary biology increasingly rely on integrating data from within among species, once-clear conceptual divisions blurred. To help bridge this divide, we derive general model describing covariance contributions quantitative phenotypes different individuals. Taking approach shows that standard models (e.g., Genome-Wide Association Studies; GWAS) phylogenetic comparative regression) can be interpreted special cases more quantitative-genetic model. fact share same core architecture means build unified understanding strengths limitations methods for controlling structure when testing associations. We develop intuition why spurious may occur using analytical theory conduct population-genetic simulations traits. structural similarity problems phylogenetics enables us take methodological advances one field apply them other. demonstrate by showing how GWAS technique-including relatedness matrix (GRM) well its leading eigenvectors, corresponding principal components genotype matrix, regression model-can mitigate analyses. As case study this, re-examine an analysis co-evolution expression levels genes across fungal phylogeny, show including eigenvectors covariates decreases false positive rate while simultaneously increasing true rate. More generally, work provides foundation integrative processes shape it.

Язык: Английский

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Phylogenetic analysis reveals how selection and mutation shape the coevolution of mRNA and protein abundances

Опубликована: Июль 11, 2024

Abstract The regulatory mechanisms that shape mRNA and protein abundances are intensely studied. Much less is known about the evolutionary processes relationship between these two levels of gene expression. To disentangle contributions mutational selective processes, we derive a novel phylogenetic model fit it to multi-species data from mammalian skin tissue. We find over macroevolutionary time: 1) there has been strong stabilizing selection on abundances; 2) mutations impacting have minimal influence 3) under track abundances, 4) adapt more quickly than due increased opportunity. additional support for findings by comparing gene-specific parameter estimates our human functional genomic data. More broadly, new approach provides foundation testing hypotheses led divergence in

Язык: Английский

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Filtering for highly variable genes and high quality spots improves phylogenetic analysis of cancer spatial transcriptomics Visium data

Опубликована: Июль 16, 2024

Abstract Phylogenetic relationship of cells within tumours can help us to understand how cancer develops in space and time, iden-tify driver mutations other evolutionary events that enable can-cer growth spread. Numerous studies have reconstructed phylo-genies from single-cell DNA-seq data. Here we are looking into the problem phylogenetic analysis spatially resolved near RNA-seq data, which is a cost-efficient alternative (or complemen-tary) data source integrates multiple sources information including point mutations, copy-number changes, epimutations. Recent attempts use such although promis-ing, raised many methodological challenges. Here, explored data-preprocessing modelling approaches for analyses Visium spatial transcriptomics We conclude using only highly variable genes accounting heterogeneous RNA capture across tissue-covered spots improves topological relationships influences estimated branch lengths.

Язык: Английский

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Genetic and selective constraints on the optimization of gene product diversity

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июль 22, 2024

RNA and protein expressed from the same gene can have diverse isoforms due to various post-transcriptional post-translational modifications. For vast majority of alternative isoforms, It is unknown whether they are adaptive or simply biological noise. As we cannot experimentally probe function each isoform, ask distribution across genes species consistent with expectations different evolutionary processes. However, there currently no theoretical framework that generate such predictions. To address this, developed a mathematical model where isoform abundances determined collectively by

Язык: Английский

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Relevance of the regulation of the brain-placental axis to the nocturnal bottleneck of mammals

Placenta, Год журнала: 2024, Номер 155, С. 11 - 21

Опубликована: Авг. 6, 2024

Язык: Английский

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Quantifying transcriptome turnover on phylogenies by modeling gene expression as a binary trait

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Окт. 4, 2024

Abstract Changes in gene expression are a key driver of phenotypic evolution, leading to persistent interest the evolution transcriptomes. Traditionally, is modeled as continuous trait, leaving qualitative transitions largely unexplored. In this paper, we detail development new Bayesian inference techniques study evolutionary turnover organ-specific transcriptomes, which define instances where orthologous genes gain or lose particular organ. To test these techniques, analyze transcriptomes two male reproductive organs, testes and accessory glands, across 11 species Drosophila melanogaster group. We first discretize states by estimating probability that each expressed organ species. then phylogenetic model correlated transcriptome more organs fit it state data. Inferences under show many have gained lost organ, experienced accelerated on different branches phylogeny.

Язык: Английский

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