Jing Wang , Haitao Guan , Xiaolei Zhang , Changjun Dai , Cuiling Wang , Guofeng Chen , Kun Li , Zhenhua Xu , Ruiying Zhang , Baohai Liu , Hongtao Wen
{"title":"Metabonomic and transcriptomic profiling reveals amino acid metabolism affects the quality of premium japonica rice varieties in Northeast China","authors":"Jing Wang , Haitao Guan , Xiaolei Zhang , Changjun Dai , Cuiling Wang , Guofeng Chen , Kun Li , Zhenhua Xu , Ruiying Zhang , Baohai Liu , Hongtao Wen","doi":"10.1016/j.fochms.2024.100230","DOIUrl":null,"url":null,"abstract":"<div><div>Rice consumption and demand for premium rice are increasing worldwide. However, the characterizations and how to identify the premium rice are still unclear. Small molecular metabolites have a great advantage in distinguishing subtle differences among similar agricultural products. So, we hypothesized that the metabolites would be the key to identifying the tiny differences in premium rice among similar varieties. In this study, we performed metabolomic and transcriptomic profiles to comprehensively elucidate key metabolites, genes, and formation mechanisms of premium rice. As a result, eight compounds belong to four categories, and 49 different expressional genes were identified in premium rice varieties after comparing with the second-best varieties. Moreover, the integrated analysis confirmed that the amino acid pathway, including 42 expression genes and 11 metabolites, was critical for the premium rice formation. Six genes and two metabolites had significant regulatory effects on the pathways. Furthermore, amino acid quantification confirmed the content of 12 kinds of hydrolytic amino acids, such as aspartic acid and arginine were different between premium and other varieties. These amino acids may serve as potential biomarkers for differentiating premium rice in Northeast China. Our results strongly support the possibility of differentiating premium rice and would provide essential data for premium rice identification and metabolomics-assisted breeding.</div></div>","PeriodicalId":34477,"journal":{"name":"Food Chemistry Molecular Sciences","volume":"9 ","pages":"Article 100230"},"PeriodicalIF":4.1000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Chemistry Molecular Sciences","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666566224000376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Rice consumption and demand for premium rice are increasing worldwide. However, the characterizations and how to identify the premium rice are still unclear. Small molecular metabolites have a great advantage in distinguishing subtle differences among similar agricultural products. So, we hypothesized that the metabolites would be the key to identifying the tiny differences in premium rice among similar varieties. In this study, we performed metabolomic and transcriptomic profiles to comprehensively elucidate key metabolites, genes, and formation mechanisms of premium rice. As a result, eight compounds belong to four categories, and 49 different expressional genes were identified in premium rice varieties after comparing with the second-best varieties. Moreover, the integrated analysis confirmed that the amino acid pathway, including 42 expression genes and 11 metabolites, was critical for the premium rice formation. Six genes and two metabolites had significant regulatory effects on the pathways. Furthermore, amino acid quantification confirmed the content of 12 kinds of hydrolytic amino acids, such as aspartic acid and arginine were different between premium and other varieties. These amino acids may serve as potential biomarkers for differentiating premium rice in Northeast China. Our results strongly support the possibility of differentiating premium rice and would provide essential data for premium rice identification and metabolomics-assisted breeding.