BionomeeX, Montpellier, France.
IMAG, Univ. Montpellier, CNRS, Montpellier, France.
Genome Biol. 2024 Mar 25;25(1):76. doi: 10.1186/s13059-024-03202-0.
The problem of missing heritability requires the consideration of genetic interactions among different loci, called epistasis. Current GWAS statistical models require years to assess the entire combinatorial epistatic space for a single phenotype. We propose Next-Gen GWAS (NGG) that evaluates over 60 billion single nucleotide polymorphism combinatorial first-order interactions within hours. We apply NGG to Arabidopsis thaliana providing two-dimensional epistatic maps at gene resolution. We demonstrate on several phenotypes that a large proportion of the missing heritability can be retrieved, that it indeed lies in epistatic interactions, and that it can be used to improve phenotype prediction.
遗传力缺失问题需要考虑不同基因座之间的遗传相互作用，称为上位性。目前的 GWAS 统计模型需要数年时间来评估单个表型的整个组合上位性空间。我们提出了 Next-Gen GWAS（NGG），它可以在数小时内评估超过 600 亿个单核苷酸多态性组合一阶相互作用。我们将 NGG 应用于拟南芥，提供了基因分辨率的二维上位性图谱。我们在几个表型上证明了很大一部分遗传力缺失可以被找回，它确实存在于上位性相互作用中，并且可以用于改善表型预测。
