Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

• DOI: 10.1007/s00122-017-2911-7
• Publication Date: 2017-04-28T09:23:24Z
• Authors: Ziliang Luo; Meng Wang; Yan Long; Yongju Huang; Lei Shi; Chunyu Zhang; Xiang Liu; Bruce D. L. Fitt; Jinxia Xiang; Annaliese S. Mason; Rod J. Snowdon; Peifa Liu; Jinling Meng; Jun Zou
• Keywords: Family-based QTL mapping; Trait; Genetic architecture

A comprehensive linkage atlas for seed yield in rapeseed. Most agronomic traits of interest crop improvement (including yield) are highly complex quantitative controlled by numerous genetic loci, which brings challenges comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie such as yield, and considering these component their can dissect individual loci (QTL) effects more effectively improve predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed large set data generated 19 independent experiments to investigate correlations between other traits, further identified QTL this population with SNP-based bin map. total 1904 consensus accounting 22 including 80 directly affecting were anchored the B. napus reference sequence. Through association analysis meta-analysis, 525 indivisible either or indirectly contributed 295 detected across environments. majority (81.5%) pleiotropic. By associations 25 yield-related previously ignored due contrasting effects, well 31 minor complementary effects. Implementation genomic prediction models improved accuracy. Dissecting phenotypic interrelationships underlying using method will provide valuable insights genomics-based improvement.