生物
基因组
遗传学
全基因组关联研究
计算生物学
遗传关联
进化生物学
基因
单核苷酸多态性
基因型
作者
Junwei Yang,Bin Liang,Yuemei Zhang,Yun Liu,Shengyuan Wang,Qinqin Yang,Xiaolin Geng,Simiao Liu,Yaoyao Wu,Yingfang Zhu,Tao Lin
出处
期刊:BMC Biology
[BioMed Central]
日期:2022-05-24
卷期号:20 (1): 120-120
被引量:13
标识
DOI:10.1186/s12915-022-01327-x
摘要
BACKGROUND: Long-term domestication and intensive breeding of crop plants aim to establish traits desirable for human needs, and characteristics related to yield, disease resistance, and postharvest storage have traditionally received considerable attention. These processes have led also to negative consequences, as is the case of loss of variants controlling fruit quality, for instance in tomato. Tomato fruit quality is directly associated to metabolite content profiles; however, a full understanding of the genetics affecting metabolite content during tomato domestication and improvement has not been reached due to limitations of the single detection methods previously employed. Here, we aim to reach a broad understanding of changes in metabolite content using a genome-wide association study (GWAS) with eigenvector decomposition (EigenGWAS) on tomato accessions. RESULTS: An EigenGWAS was performed on 331 tomato accessions using the first eigenvector generated from the genomic data as a "phenotype" to understand the changes in fruit metabolite content during breeding. Two independent gene sets were identified that affected fruit metabolites during domestication and improvement in consumer-preferred tomatoes. Furthermore, 57 candidate genes related to polyphenol and polyamine biosynthesis were discovered, and a major candidate gene chlorogenate: glucarate caffeoyltransferase (SlCGT) was identified, which affected the quality and diseases resistance of tomato fruit, revealing the domestication mechanism of polyphenols. CONCLUSIONS: We identified gene sets that contributed to consumer liking during domestication and improvement of tomato. Our study reports novel evidence of selective sweeps and key metabolites controlled by multiple genes, increasing our understanding of the mechanisms of metabolites variation during those processes. It also supports a polygenic selection model for the application of tomato breeding.
科研通智能强力驱动
Strongly Powered by AbleSci AI