Literature DB >> 28039028

Genome-wide Association Studies in Maize: Praise and Stargaze.

Yingjie Xiao1, Haijun Liu1, Liuji Wu2, Marilyn Warburton3, Jianbing Yan4.   

Abstract

Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.
Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  GWAS; Zea mays; functional genomics; mixed model; omics; population design

Mesh:

Year:  2016        PMID: 28039028     DOI: 10.1016/j.molp.2016.12.008

Source DB:  PubMed          Journal:  Mol Plant        ISSN: 1674-2052            Impact factor:   13.164


  90 in total

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9.  Identification of a candidate gene underlying qKRN5b for kernel row number in Zea mays L.

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10.  Genome-wide association study dissects yield components associated with low-phosphorus stress tolerance in maize.

Authors:  Cheng Xu; Hongwei Zhang; Jianhao Sun; Zifeng Guo; Cheng Zou; Wen-Xue Li; Chuanxiao Xie; Changling Huang; Ruineng Xu; Hong Liao; Jinxiang Wang; Xiaojie Xu; Shanhong Wang; Yunbi Xu
Journal:  Theor Appl Genet       Date:  2018-05-12       Impact factor: 5.699

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