Facilitating Complex Trait Analysis via Reduced Complexity Crosses. Issue 8 (August 2020) - Bryant, Camron D.; Smith, Desmond J.; Kantak, Kathleen M.; Nowak, Thaddeus S.; Williams, Robert W.; Damaj, M. Imad; Redei, Eva E.; Chen, Hao; Mulligan, Megan K.
Abstract : Genetically diverse inbred strains are frequently used in quantitative trait mapping to identify sequence variants underlying trait variation. Poor locus resolution and high genetic complexity impede variant discovery. As a solution, we explore reduced complexity crosses (RCCs) between phenotypically divergent, yet genetically similar, rodent substrains. RCCs accelerate functional variant discovery via decreasing the number of segregating variants by orders of magnitude. The simplified genetic architecture of RCCs often permit immediate identification of causal variants or rapid fine-mapping of broad loci to smaller intervals. Whole-genome sequences of substrains make RCCs possible by supporting the development of array- and targeted sequencing-based genotyping platforms, coupled with rapid genome editing for variant validation. In summary, RCCs enhance discovery-based genetics of complex traits. Highlights: Discovery of causal genes and variants underlying complex trait variation using traditional rodent crosses is limited by the combination of high genetic complexity and modest locus resolution. Whole-genome sequencing of nearly isogenic rodent substrains now enables a new type of cross, RCC, which can be highly efficient for variant discovery. Residual heterozygosity and spontaneous mutations between rodent breeding colonies make RCCs an efficient approach for identifying quantitative trait genes and variants. Compared with traditional crosses, RCCs segregate orders of magnitude fewer variants and accelerate causal quantitative trait gene and variant identification. Gene editing strengthens causal gene discovery by providing an efficient means to demonstrate both the necessity and sufficiency of variants on substrain backgrounds.