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Biology subjects

Schmidt, R. H.

Publications and source records attributed to Schmidt, R. H..

2 recordsLinked to original sources

Powerful one-dimensional scan to detect heterotic QTL

To meet the growing global demand for food, increasing yields through heterosis in agriculture is crucial. A deep understanding of the genetic basis of heterosis has led to the development of a quantitative genetic framework that incorporates both dominance and epistatic effects. However, incorporating all pairwise epistatic interactions is computationally challenging due to the large sequencing depth and population sizes needed to uncover the genes behind complex traits. In this study, we developed hQTL-ODS, a one-dimensional scanning method that directly assesses the net contribution of each locus to heterosis. Simulations show that hQTL-ODS reduces computational time while offering higher power and lower false-positive rate. We applied this method to a population of 5,234 wheat hybrids with whole-genome sequenced profile, revealing key epistatic hubs that play a critical role in determining heterosis. Our findings offered valuable insights for improving breeding strategies to enhance crop yields.

genetics↗

A comprehensive overview and benchmarking analysis of fast algorithms for genome-wide association studies

Genome-wide association studies (GWAS) are a ubiquitous tool for identifying genetic variants associated with complex traits in structured populations. During the past 15 years, many fast GWAS algorithms based on a state-of-the-art model, namely the linear mixed model, have been published to cope with the rapidly growing data size. In this study, we provide a comprehensive overview and benchmarking analysis of 33 commonly used GWAS algorithms. Key mathematical techniques implemented in different algorithms were summarized. Empirical data analysis with 12 selected algorithms showed differences regarding the identification of quantitative trait loci (QTL) in several plant species. The performance of these algorithms evaluated in 10,800 simulated data sets with distinct population size, heritability and genetic architecture revealed the impact of these parameters on the power of QTL identification and false positive rate. Based on these results, a general guide on the choice of algorithms for the research community is proposed.

genetics↗