Using Interactome Big Data to Crack Genetic Mysteries and Enhance Future Crop Breeding
作者机构：National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan 430070China lnstitute of Crop ScienceChinese Academy of Agricultural SciencesBeijing 100081China
出 版 物：《Molecular Plant》 (分子植物（英文版）)
年 卷 期：2021年第14卷第1期
页 面：77-94页
核心收录：
学科分类：0710[理学-生物学] 07[理学] 08[工学] 09[农学] 071007[理学-遗传学] 0901[农学-作物学] 0902[农学-园艺学] 0836[工学-生物工程] 090102[农学-作物遗传育种]
基 金：This research was supported by the National Natural Science Foundation of China(92035302,31922068) the Fundamental Research Funds for the Central Universities(ZK201908) the Fundamental Research Funds for the Central Universities(2662020ZKPY017) the Huazhong Agricultural University Scientific&Technological Self-innovation Foundation(2015R016) the China Postdoctoral Science Foundation(2019M662666)
主 题：genetic mystery interactome big data machine learning crop breeding
摘 要：The functional genes underlying phenotypic variation and their interactions represent“genetic mysteries.Understanding and utilizing these genetic mysteries are key solutions for mitigating the current threats to agriculture posed by population growth and individual food *** to advances in highthroughput multi-omics technologies,we are stepping into an Interactome Big Data era that is certain to revolutionize genetic *** this article,we provide a brief overview of current strategies to explore genetic *** then introduce the methods for constructing and analyzing the Interactome Big Data and summarize currently available interactome ***,we discuss how Interactome Big Data can be used as a versatile tool to dissect genetic *** propose an integrated strategy that could revolutionize genetic research by combining Interactome Big Data with machine learning,which involves mining information hidden in Big Data to identify the genetic models or networks that control various traits,and also provide a detailed procedure for systematic dissection of genetic mysteries,Finally,we discuss three promising future breeding strategies utilizing the Interactome Big Data to improve crop yields and quality.
维普期刊数据库