Biology subjects

Guez, J.

Publications and source records attributed to Guez, J..

4 recordsLinked to original sources

bioRxiv2024

Variant scoring performance across selection regimes depends on variant-to-gene and gene-to-disease components

Variant scoring methods (VSMs) aid in the interpretation of coding mutations and their potential impact on health, but their evaluation in the context of human genetics applications remains inconsistent. Here, we describe GeneticsGym, a systematic approach to evaluating the real-world impact of VSMs on human genetic analysis. We show that the relative performance of VSMs varies across regimes of natural selection, and that both variant-to-gene and gene-to-disease components contribute.

bioinformatics↗

bioRxiv2024

Widespread naturally variable human exons aid genetic interpretation

Most mammalian genes undergo alternative splicing. The splicing of some exons has been acquired or lost in specific mammalian lineages, but differences in splicing within the human population are poorly characterized. Using GTEx tissue transcriptomes from 838 individuals, we identified 56,415 exons which are included in mRNAs in some individuals but entirely excluded from others, which we term "naturally variable exons" (NVEs). NVEs impact three quarters of protein-coding genes, occur at all population frequencies, and are often absent from reference annotations. NVEs are more abundant in genes depleted of genetic loss-of-function mutations and aid in the interpretation of causal genetic variants. Genetic variants modulate the splicing of many NVEs, and 5UTR and coding-region NVEs are often associated with increased and decreased gene expression, respectively. Together, our findings characterize abundant splicing variation in the human population, with implications for a range of human genetic analyses.

genetics↗

bioRxiv2022

Correlated stabilizing selection shapes the topology of gene regulatory networks

The evolution of gene expression is constrained by the topology of gene regulatory networks, as co-expressed genes are likely to have their expressions affected together by mutations. Conversely, co-expression can also be an advantage when genes are under joint selection. Here, we assessed theoretically whether correlated selection (selection for a combination of traits) was able to affect the pattern of correlated gene expressions and the underlying gene regulatory networks. We ran individual-based simulations, applying a stabilizing correlated fitness function to three genetic architectures: a quantitative genetics (multilinear) model featuring epistasis and pleiotropy, a quantitative genetics model where each genes has an independent mutational structure, and a gene regulatory model, mimicking the mechanisms of gene expression regulation. Simulations showed that correlated mutational effects evolved in the three genetic architectures as a response to correlated selection, but the response in gene networks was specific. The intensity of gene co-expression was mostly explained by the regulatory distance between genes (largest correlations being associated to genes directly interacting with each other), and the sign of co-expression was associated with the nature of the regulation (transcription activation or inhibition). These results concur to the idea that gene network topologies could partly reflects past correlated selection patterns on gene expression.

evolutionary biology↗

bioRxiv2022

Cultural transmission of reproductive success impacts genomic diversity, coalescent tree topologies and demographic inferences

Cultural Transmission of Reproductive Success (CTRS) has been observed in many human populations as well as other animals. It consists in a positive correlation of non-genetic origin between the progeny size of parents and children. This correlation can result from various factors, such as the social influence of parents on their children, the increase of childrens survival through allocare from uncle and aunts, or the transmission of resources. Here, we study the evolution of genomic diversity through time under CTRS. We show that CTRS has a double impact on population genetics: (1) effective population size decreases when CTRS starts, mimicking a population contraction, and increases back to its original value when CTRS stops; (2) coalescent trees topologies are distorted under CTRS, with higher imbalance and higher number of polytomies. Under long-lasting CTRS, effective population size stabilises but the distortion of tree topology remains, which yields U-shaped Site Frequency Spectra (SFS) under constant population size. We show that this CTRS impact yields a bias in SFS-based demographic inference. Considering that CTRS was detected in numerous human and animal populations worldwide, one should be cautious that inferring population past histories from genomic data can be biased by this cultural process.

genetics↗