Calling Structural Variants with Confidence from Short-Read Data in Wild Bird Populations

作者：Gabriel David, Alicia Bertolotti, Ryan M. Layer, Douglas G. Scofield, Alexander Hayward, Tobias Baril, Hamish A. Burnett, Erik Gudmunds, Henrik Jensen, Arild Husby · 发表于：Genome Biology and Evolution · 年份：2024 · DOI：10.1093/gbe/evae049 · 被引用次数：11 · 研究领域：Genetic diversity and population structure、Genetic and phenotypic traits in livestock、Genomics and Phylogenetic Studies

Comprehensive characterization of structural variation in natural populations has only become feasible in the last decade. To investigate the population genomic nature of structural variation, reproducible and high-confidence structural variation callsets are first required. We created a population-scale reference of the genome-wide landscape of structural variation across 33 Nordic house sparrows (Passer domesticus). To produce a consensus callset across all samples using short-read data, we compare heuristic-based quality filtering and visual curation (Samplot/PlotCritic and Samplot-ML) approaches. We demonstrate that curation of structural variants is important for reducing putative false positives and that the time invested in this step outweighs the potential costs of analyzing short-read-discovered structural variation data sets that include many potential false positives. We find that even a lenient manual curation strategy (e.g. applied by a single curator) can reduce the proportion of putative false positives by up to 80%, thus enriching the proportion of high-confidence variants. Crucially, in applying a lenient manual curation strategy with a single curator, nearly all (>99%) variants rejected as putative false positives were also classified as such by a more stringent curation strategy using three additional curators. Furthermore, variants rejected by manual curation failed to reflect the expected population structure from SNPs, whereas variants passing curation d...