Integrating Genome-Wide Association Study with Transcriptomic Analysis to Predict Candidate Genes Controlling Storage Root Flesh Color in Sweet Potato
文献类型： 外文期刊
第一作者： Liu, Yi
作者： Liu, Yi;Lei, Jian;Wang, Lianjun;Chai, Shasha;Jin, Xiaojie;Jiao, Chunhai;Yang, Xinsun;Pan, Rui;Zhang, Wenying
作者机构：
关键词： sweet potato; genome-wide association studies; storage root flesh color; transcriptomic analysis
期刊名称：AGRONOMY-BASEL （ 影响因子：3.949； 五年影响因子：4.117 ）
ISSN：
年卷期： 2022 年 12 卷 5 期
页码：
收录情况： SCI
摘要： Sweet potato is a hexaploid heterozygote with a complex genetic background, self-pollination infertility, and cross incompatibility, which makes genetic linkage analysis quite difficult. Genome-wide association studies (GWAS) provide a new strategy for gene mapping and cloning in sweet potato. Storage root flesh color (SRFC) is an important sensory evaluation, which correlates with storage root flesh composition, such as starch, anthocyanin, and carotenoid. We performed GWAS using SRFC data of 300 accessions and 567,828 single nucleotide polymorphism (SNP) markers. Furthermore, we analyzed transcriptome data of different SRFC varieties, and conducted real-time quantitative PCR (qRT-PCR) to measure the expression level of the candidate gene in purple and non-purple fleshed sweet potato genotypes. The results showed that five unique SNPs were significantly (-log(10)P > 7) associated with SRFC. Based on these trait-associated SNPs, four candidate genes, g55964 (IbF3'H), g17506 (IbBAG2-like), g25206 (IbUGT-73D1-like), and g58377 (IbVQ25-isoform X2) were identified. Expression profiles derived from transcriptome data and qRT-PCR analyses showed that the expression of g55964 in purple-fleshed sweet potato was significantly (p < 0.01) higher than that of non-purple fleshed sweet potato. By combining the GWAS, transcriptomic analysis and qRT-PCR, we inferred that g55964 is the key gene related to purple formation of storage root in sweet potato. Our results lay the foundation for accelerating sweet potato genetic improvement of anthocyanin through marker-assisted selection.
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