QTL analysis of important agronomic traits and metabolites in foxtail millet ( Setaria italica ) by RIL population and widely targeted metabolome

• Published in: Frontiers in plant science 2023-01, Vol.13, p.1035906-1035906
• Main Authors: Wei, Wei, Li, Shuangdong, Li, Peiyu, Yu, Kuohai, Fan, Guangyu, Wang, Yixiang, Zhao, Fang, Zhang, Xiaolei, Feng, Xiaolei, Shi, Gaolei, Zhang, Weiqin, Song, Guoliang, Dan, Wenhan, Wang, Feng, Zhang, Yali, Li, Xinru, Wang, Dequan, Zhang, Wenying, Pei, Jingjing, Wang, Xiaoming, Zhao, Zhihai
• Format: Article
• Language: English
• Subjects: foxtail millet; metabolic QTL; phenotypic QTL; Plant Science; RIL population; widely targeted metabolomics
• ISSN: 1664-462X; 1664-462X
• DOI: 10.3389/fpls.2022.1035906

As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet ( ) is insufficient. Here, based on the linkage analysis of 3,452 metabolites with high-quality genetic linkage maps, we detected a total of 1,049 metabolic quantitative trait loci (mQTLs) distributed in 11 hotspots, and 28 metabolite-related candidate genes were mined from 14 mQTLs. In addition, 136 single-environment phenotypic QTL (pQTLs) related to 63 phenotypes were identified by linkage analysis, and there were 12 hotspots on these pQTLs. We futher dissected 39 candidate genes related to agronomic traits through metabolite-phenotype correlation and gene function analysis, including semidwarf gene, which can affect plant height by regulating GA synthesis. Combined correlation network and QTL analysis, we found that flavonoid-lignin pathway maybe closely related to plant architecture and yield in foxtail millet. For example, the correlation coefficient between apigenin 7-rutinoside and stem diameter reached 0.98, and they were co-located at 41.33-44.15 Mb of chromosome 5, further gene function analysis revealed that 5 flavonoid pathway genes, as well as , were located in this interval . Therefore, the correlation and co-localization between flavonoid-lignins and plant architecture may be due to the close linkage of their regulatory genes in millet. Besides, we also found that a combination of genomic and metabolomic for BLUP analysis can better predict plant agronomic traits than genomic or metabolomic data, independently. In conclusion, the combined analysis of mQTL and pQTL in millet have linked genetic, metabolic and agronomic traits, and is of great significance for metabolite-related molecular assisted breeding.