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Wang, Qian; Yan, Tao; Long, Zhengbiao; Huang, Luna Yue; Zhu, Yang; Xu, Ying; Chen, Xiaoyang; Pak, Haksong; Li, Jiqiang; Wu, Dezhi; Xu, Yang; Hua, Shuijin; Jiang, Lixi
PLoS genetics, 11/2021, Letnik: 17, Številka: 11Journal Article
The utilization of heterosis is a successful strategy in increasing yield for many crops. However, it consumes tremendous manpower to test the combining ability of the parents in fields. Here, we applied the genomic-selection (GS) strategy and developed models that significantly increase the predictability of heterosis by introducing the concept of a regional parental genetic-similarity index (PGSI) and reducing dimension in the calculation matrix in a machine-learning approach. Overall, PGSI negatively affected grain yield and several other traits but positively influenced the thousand-seed weight of the hybrids. It was found that the C subgenome of rapeseed had a greater impact on heterosis than the A subgenome. We drew maps with overviews of quantitative-trait loci that were responsible for the heterosis (h-QTLs) of various agronomic traits. Identifications and annotations of genes underlying high impacting h-QTLs were provided. Using models that we elaborated, combining abilities between an Ogu-CMS-pool member and a potential restorer can be simulated in silico, sidestepping laborious work, such as testing crosses in fields. The achievements here provide a case of heterosis prediction in polyploid genomes with relatively large genome sizes.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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