Biology subjects

Lopez-Cortegano, E.

Publications and source records attributed to Lopez-Cortegano, E..

3 recordsLinked to original sources

bioRxiv2026

The effect of a reduction in population size on mean fitness and inbreeding depression

A sudden reduction in population size increases the rate of genetic drift, reducing variability and increasing the mean level of homozygosity. The resulting increase in exposure of strongly deleterious, recessive or partially recessive alleles to selection against homozygotes may lead to their being purged from the population, potentially allowing mean fitness to increase after an initial decline, and accelerating the decline in inbreeding depression associated with reduced variability. However, detailed population genetic theory on the effects of population bottlenecks on mean fitness and inbreeding depression remains limited. We develop a theoretical framework for small, randomly mating populations founded from a large population at mutation-selection-drift equilibrium, using both simulations and approximate analytical results. These provide quantitative predictions for the dynamics of the population's mean fitness and level of inbreeding depression following a bottleneck. In particular, we derive an approximate expression for the time needed for mean fitness to recover after an initial decline; such a recovery requires selection to be sufficiently strong relative to drift, and mutations to be sufficiently recessive. In contrast, weakly deleterious mutations cause reductions in mean fitness and inbreeding depression that are similar in size to those predicted from increases in homozygosity for neutral alleles, over the relatively short timescales considered here.

genetics↗

bioRxiv2022

Rates and spectra of de novo structural mutation in Chlamydomonas reinhardtii

Genetic variation originates from several types of spontaneous mutation, including single nucleotide substitutions, short insertions and deletions (INDELs), and larger structural changes. Structural mutations (SMs) drive genome evolution and are thought to play major roles in evolutionary adaptation, speciation and genetic disease, including cancers. Sequencing of mutation accumulation (MA) lines has provided estimates of rates and spectra of single nucleotide and INDEL mutations in many species, yet the rate of new SMs is largely unknown. Here, we use long-read sequencing to determine the full mutation spectrum in MA lines derived from two strains (CC-1952 and CC-2931) of the green alga Chlamydomonas reinhardtii. The SM rate is highly variable between strains and MA lines, and SMs represent a substantial proportion of all mutations in both strains (CC-1952 6%; CC-2931 12%). The SM spectra also differs considerably between the two strains, with almost all inversions and translocations occurring in CC-2931 MA lines. This variation is associated with heterogeneity in the number and type of active transposable elements (TEs), which comprise major proportions of SMs in both strains (CC-1952 22% and CC-2931 38% of SMs). In CC-2931, a Crypton and a previously undescribed type of DNA element caused 71% of chromosomal rearrangements, while in CC-1952 a Dualen LINE was associated with 87% of duplications. Other SMs, notably many large duplications in CC-2931, were likely products of various double-strand break repair pathways. Our results demonstrate that diverse types of SMs occur at substantial rates and support prominent roles for SMs and TEs in evolution.

evolutionary biology↗

bioRxiv2018

Inferring the nature of missing heritability in human traits

Thousands of genes responsible for many diseases and other common traits in humans have been detected by Genome Wide Association Studies (GWAS) in the last decade. However, candidate causal variants found so far usually explain only a small fraction of the heritability estimated by family data, the rest remaining missing. The most common explanation for this observation is that the missing heritability corresponds to variants, either rare or common, with very small effect, which pass undetected due to a lack of statistical power. We carried out a meta-analysis using data from the NHGRI-EBI GWAS Catalog in order to explore the distribution of gene effects for a set of 59 complex traits, to investigate the factors related to new gene discovery and to quantify their contributions to heritability. With the data obtained we were able to predict the expected distribution of gene effects for 16 traits and diseases including cancer and immune disorders, the missing number of genes yet to be discovered, and the additive contribution of common variants to heritability. Our results indicate that, for most traits, the additive contribution of hundreds or thousands of genes is able to explain the familiar heritability. However, for some traits, the predicted heritability is lower than the familiar one, so that part of the missing heritability cannot be explained by the contribution of common variants with additive effects, and other phenomena (e.g. dominance or epistasis) should be invoked.\n\nAUTHOR SUMMARYThe heritability of biological traits refers to the fraction of the phenotypic (i.e. visible or diagnosable) variability that is explained by the underlying genetic variability. Despite the efforts made to find the genes responsible for complex traits and diseases, most of the heritability explained by the variants found explains only a small fraction of that measured by population and family studies. The remaining missing heritability is usually assumed to be due to the additive effect of undetected variants. Here we carried out a meta-analysis using records from a publicly available database of genome-wide studies on humans. With these data, we were able to investigate and make inferences on the nature of heritability and the factors associated to new gene discovery. Our results indicate that increasing population sample size, as well as its diversity, enhances the discovery of new genes, but these have lower and lower effects, contributing little to heritability. We were also able to predict the distribution of gene effects for many traits and the number of variants needed to fully explain the heritability. For some traits, the additive effects of single variants yet to be discovered cannot explain the heritability, suggesting that other sources of variation are involved.

genetics↗