An inferred functional impact map of genetic variants in rice  

作　　者：Hu Zhao Jiacheng Li Ling Yang Gang Qin Chunjiao Xia Xingbing Xu Yangmeng Su Yinmeng Liu Luchang Ming Ling-Ung Chen Lizhong Xiong Weibo Xie 

机构地区：[1]National Key Laboratory of Crop Genetic Improvement,Hubei Hongshan Laboratory,Huazhong Agricultural University,Wuhan,China [2]Hubei Key Laboratory of Agricultural Bioinformatics,College of Informatics,Huazhong Agricultural University,Wuhan,China [3]State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources,College of Life Science and Technology,Guangxi University,Nanning,China

出　　处：《Molecular Plant》2021年第9期1584-1599,共16页分子植物（英文版）

基　　金：This work was supported by grants from the National Key Research and Development Program of China(2016YFD0100803);the National Natural Science Foundation of China(31821005,31922065,31771755);the State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources(SKLCUSA-b202002).

摘　　要：Interpreting the functional impacts of genetic variants(GVs)is an important challenge for functional genomic studies in crops and next-generation breeding.Previous studies in rice(Oryza sativa)have focused mainly on the identification of GVs,whereas systematic functional annotation of GVs has not yet been performed.Here,we present a functional impact map of GVs in rice.We curated haplotype information for 17397026 GVs from sequencing data of 4726 rice accessions.We quantitatively evaluated the effects of missense mutations in coding regions in each haplotype based on the conservation of amino acid residues and obtained the effects of 918848 non-redundant missense GVs.Furthermore,we generated high-quality chromatin accessibility(CA)data from six representative rice tissues and used these data to train deep convolutional neural network models to predict the impacts of 5067405 GVs for CA in regulatory regions.We characterized the functional properties and tissue specificity of the GV effects and found that large-effect GVs in coding and regulatory regions may be subject to selection in different directions.Finally,we demonstrated how the functional impact map could be used to prioritize causal variants in mapping populations.This impact map will be a useful resource for accelerating gene cloning and functional studies in rice,and can be freely queried in RiceVarMap V2.0(http://ricevarmap.ncpgr.cn).

关 键 词：ricegenetic variantschromatin accessibilityfunctional impact mapdeep learning 

分 类 号：S511[农业科学—作物学]