Biology subjects

Lavanchy, E.

Publications and source records attributed to Lavanchy, E..

3 recordsLinked to original sources

bioRxiv2023

Detecting inbreeding depression in structured populations

Measuring inbreeding as well as its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the most appropriate method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. In this project, we simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structure (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients (F) to quantify the strength of inbreeding depression: allele sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model including a genetic relatedness matrix (GRM) as random effect to account for the non-independence of observations. We find linear mixed models give better results in scenarios with population or family structure. Within the mixed models, we compare three different GRM matrices and show that in homogeneous populations, there is little difference among the different F and GRM for inbreeding depression quantification. However, as soon as strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if (i) the phenotypes are regressed on inbreeding coefficient based on a weighted version of the correlation of uniting gametes, which gives more weight to common alleles and (ii) with the GRM obtained from an allele sharing relatedness estimator.

genomics↗

bioRxiv2022

Effect of reduced genomic representation on using runs of homozygosity for inbreeding characterization

Runs of homozygosity (ROHs) are proxy for genomic Identical-by-Descent segments and are increasingly used to measure individual inbreeding. ROHs analyses are mostly carried out on SNPs-arrays and whole-genome-sequencing data. Softwares recurrently used for their detection usually assume that genomic positions which have not been genotyped are non-variant. This might be true for whole-genome-sequencing data, but not for reduced genomic representations and can lead to spurious ROHs detection. We simulated the outputs of whole-genome-sequencing, two SNP-arrays and RAD-sequencing for three populations with different sizes. We compare the results of ROHs calling with two softwares: PLINK and RZooRoH. We demonstrate that to obtain meaningful estimates of inbreeding coefficients, RZooRoH requires fraction of genome seven times smaller compared to PLINK. When the SNP density is above 20 SNPs/Mb for PLINK and 3 SNPs/Mb for RZooRoH, ranks of ROHs-based inbreeding coefficients are conserved among individuals. With reduced genomic representations, ROHs distributions are consistently biased towards an underestimation of the total numbers of small and an overestimation of the total numbers of large ROHs, except for RZooRoH and high-density SNPs-arrays. We conclude that both ROHs-based inbreeding coefficients and ROHs distributions exact quantification are highly dependent on the fraction of genome sequenced and should thus be treated with caution. However, relative inbreeding estimates, such as comparison between individuals or populations, are reliable with reduced genomic representations providing that the fraction of genome sequenced is large enough. Consequently, we advise researchers working with reduced genomic data to use SNPs-independent measures or model-based ROHs calling methods for inbreeding estimations.

genomics↗

bioRxiv2021

Genomic consequences of colonisation, migration and genetic drift in barn owl insular populations of the eastern Mediterranean

The study of insular populations was key in the development of evolutionary theory. The successful colonisation of an island depends on the geographic context, and specific characteristics of the organism and the island, but also on stochastic processes. As a result, apparently identical islands may harbour populations with contrasting histories. Here, we use whole genome sequences of 65 barn owls to investigate the patterns of inbreeding and genetic diversity of insular populations in the eastern Mediterranean Sea. We focus on Crete and Cyprus, islands with similar size, climate and distance to mainland, that provide natural replicates for a comparative analysis of the impacts of microevolutionary processes on isolated populations. We show that barn owl populations from each island have a separate origin, Crete being genetically more similar to other Greek islands and mainland Greece, and Cyprus more similar to the Levant. Further, our data show that their respective demographic histories following colonisation were also distinct. On the one hand, Crete harbours a small population and maintains very low levels of gene flow with neighbouring populations. This has resulted in low genetic diversity, strong genetic drift, increased relatedness in the population and remote inbreeding. Cyprus, on the other hand, appears to maintain enough gene flow with the mainland to avoid such an outcome. Our work provides a comparative population genomic analysis of the effects of neutral processes on a classical island-mainland model system. It provides empirical evidence for the role of stochastic processes in determining the fate of diverging isolated populations.

evolutionary biology↗