Literature DB >> 31807910

Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize.

Xiaoxiang Zhang1, Zhongrong Guan2, Lei Wang1, Jun Fu1, Yinchao Zhang1, Zhaoling Li1, Langlang Ma1, Peng Liu1, Yanling Zhang1, Min Liu1, Peng Li1, Chaoying Zou1, Yongcong He1, Haijian Lin1, Guangsheng Yuan1, Shibin Gao1,3, Guangtang Pan1, Yaou Shen4,5.   

Abstract

Kernel weight in a unit volume is referred to as kernel test weight (KTW) that directly reflects maize (Zea mays L.) grain quality. In this study, an inter-mated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population and an association panel were used to identify loci responsible for KTW of maize across multiple environments. A total of 18 significant KTW-related single-nucleotide polymorphisms (SNPs) were identified using genome-wide association study (GWAS); they were closely linked to 12 candidate genes. In the IBM Syn10 DH population, linkage analysis detected 19 common quantitative trait loci (QTL), five of which were repeatedly detected among multiple environments. Several verified genes that regulate maize seed development were found in the confidence intervals of the mapped QTL and the LD regions of GWAS, such as ZmYUC1, BAP2, ZmTCRR-1, dek36 and ZmSWEET4c. Combined QTL mapping and GWAS identified one significant SNP that was co-identified in the both populations. Based on the co-localized SNP across the both populations, 17 candidate genes were identified. Of them, Zm00001d044075, Zm00001d044086, and Zm00001d044081 were further identified by candidate gene association study for KTW. Zm00001d044081 encodes homeobox-leucine zipper protein ATHB-4, which has been demonstrated to control apical embryo development in Arabidopsis. Our findings provided insights into the mechanism underlying maize KTW and contributed to the application of molecular-assisted selection of high KTW breeding in maize.

Entities:  

Keywords:  Candidate gene association study; GWAS; Kernel test weight; Maize; QTL mapping

Mesh:

Substances:

Year:  2019        PMID: 31807910     DOI: 10.1007/s00438-019-01631-2

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


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