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Combined linkage and association mapping reveal candidate loci for kernel size and weight in maize.


ABSTRACT: Yield improvement is a top priority for maize breeding. Kernel size and weight are important determinants of maize grain yield. In this study, a recombinant inbred line (RIL) population and an association panel were used to identify quantitative trait loci (QTLs) for four maize kernel-related traits: kernel length, width, thickness and 100-kernel weight. Twenty-seven QTLs were identified for kernel-related traits across three environments and the best linear unbiased predictions (BLUPs) of each trait by linkage analysis, and four QTLs were stably detected in more than two environments. Additionally, 29 single nucleotide polymorphisms (SNPs) were identified as significantly associated with the four kernel-related traits and BLUPs by genome-wide association study, and two loci could be stably detected in both environments. In total, four QTLs/SNPs were co-associated with various traits in both populations. Using combined-linkage analysis and association mapping, PZE-101066560 on chromosome 1, associated with kernel width and with 100-kernel weight in the association panel, was co-localized within the QTL interval of qKW1-3 for kernel width in the RILs. Two annotated genes in the candidate region were considered as potential candidate genes. The QTLs and candidate genes identified here will facilitate molecular breeding for grain yield improvement in maize.

SUBMITTER: Hao D 

PROVIDER: S-EPMC6776153 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Combined linkage and association mapping reveal candidate loci for kernel size and weight in maize.

Hao Derong D   Xue Lin L   Zhang Zhenliang Z   Cheng Yujing Y   Chen Guoqing G   Zhou Guangfei G   Li Pengcheng P   Yang Zefeng Z   Xu Chenwu C  

Breeding science 20190627 3


Yield improvement is a top priority for maize breeding. Kernel size and weight are important determinants of maize grain yield. In this study, a recombinant inbred line (RIL) population and an association panel were used to identify quantitative trait loci (QTLs) for four maize kernel-related traits: kernel length, width, thickness and 100-kernel weight. Twenty-seven QTLs were identified for kernel-related traits across three environments and the best linear unbiased predictions (BLUPs) of each  ...[more]

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