Literature DB >> 33469070

Detection of QTNs for kernel moisture concentration and kernel dehydration rate before physiological maturity in maize using multi-locus GWAS.

Shufang Li1, Chunxiao Zhang1, Deguang Yang2, Ming Lu3, Yiliang Qian4, Fengxue Jin1, Xueyan Liu1, Yu Wang5, Wenguo Liu6, Xiaohui Li7.   

Abstract

Maize is China's largest grain crop. Mechanical grain harvesting is the key technology in maize production, and the kernel moisture concentration (KMC) is the main controlling factor in mechanical maize harvesting in China. The kernel dehydration rate (KDR) is closely related to the KMC. Thus, it is important to conduct genome-wide association studies (GWAS) of the KMC and KDR in maize, detect relevant quantitative trait nucleotides (QTNs), and mine relevant candidate genes. Here, 132 maize inbred lines were used to measure the KMC every 5 days from 10 to 40 days after pollination (DAP) in order to calculate the KDR. These lines were genotyped using a maize 55K single-nucleotide polymorphism array. QTNs for the KMC and KDR were detected based on five methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, and ISIS EM-BLASSO) in the package mrMLM. A total of 334 significant QTNs were found for both the KMC and KDR, including 175 QTNs unique to the KMC and 178 QTNs unique to the KDR; 116 and 58 QTNs were detected among the 334 QTNs by two and more than two methods, respectively; and 9 and 5 QTNs among 58 QTNs were detected in 2 and 3 years, respectively. A significant enrichment in cellular component was revealed by Gene Ontology enrichment analysis of candidate genes in the intervals adjacent to the 14 QTNs and this category contained five genes. The information provided in this study may be useful for further mining of genes associated with the KMC and KDR in maize.

Entities:  

Year:  2021        PMID: 33469070      PMCID: PMC7815807          DOI: 10.1038/s41598-020-80391-1

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  29 in total

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Journal:  Am J Hum Genet       Date:  2000-05-26       Impact factor: 11.025

2.  Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

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Journal:  Mol Ecol       Date:  2005-07       Impact factor: 6.185

3.  Mapping quantitative trait loci using naturally occurring genetic variance among commercial inbred lines of maize (Zea mays L.).

Authors:  Yuan-Ming Zhang; Yongcai Mao; Chongqing Xie; Howie Smith; Lang Luo; Shizhong Xu
Journal:  Genetics       Date:  2005-02-16       Impact factor: 4.562

4.  Ribosomal DNA spacer-length polymorphisms in barley: mendelian inheritance, chromosomal location, and population dynamics.

Authors:  M A Saghai-Maroof; K M Soliman; R A Jorgensen; R W Allard
Journal:  Proc Natl Acad Sci U S A       Date:  1984-12       Impact factor: 11.205

5.  Enrichment of statistical power for genome-wide association studies.

Authors:  Meng Li; Xiaolei Liu; Peter Bradbury; Jianming Yu; Yuan-Ming Zhang; Rory J Todhunter; Edward S Buckler; Zhiwu Zhang
Journal:  BMC Biol       Date:  2014-10-17       Impact factor: 7.431

6.  Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology.

Authors:  Shi-Bo Wang; Jian-Ying Feng; Wen-Long Ren; Bo Huang; Ling Zhou; Yang-Jun Wen; Jin Zhang; Jim M Dunwell; Shizhong Xu; Yuan-Ming Zhang
Journal:  Sci Rep       Date:  2016-01-20       Impact factor: 4.379

7.  Genome-Wide Association Studies Reveal Genetic Variation and Candidate Genes of Drought Stress Related Traits in Cotton (Gossypium hirsutum L.).

Authors:  Sen Hou; Guozhong Zhu; Yuan Li; Weixi Li; Jie Fu; Erli Niu; Lechen Li; Dayong Zhang; Wangzhen Guo
Journal:  Front Plant Sci       Date:  2018-09-03       Impact factor: 5.753

8.  QTLs and candidate genes for desiccation and abscisic acid content in maize kernels.

Authors:  Valérie Capelle; Carine Remoué; Laurence Moreau; Agnès Reyss; Aline Mahé; Agnès Massonneau; Matthieu Falque; Alain Charcosset; Claudine Thévenot; Peter Rogowsky; Sylvie Coursol; Jean-Louis Prioul
Journal:  BMC Plant Biol       Date:  2010-01-04       Impact factor: 4.215

9.  Genetic Dissection of Maize Embryonic Callus Regenerative Capacity Using Multi-Locus Genome-Wide Association Studies.

Authors:  Langlang Ma; Min Liu; Yuanyuan Yan; Chunyan Qing; Xiaoling Zhang; Yanling Zhang; Yun Long; Lei Wang; Lang Pan; Chaoying Zou; Zhaoling Li; Yanli Wang; Huanwei Peng; Guangtang Pan; Zhou Jiang; Yaou Shen
Journal:  Front Plant Sci       Date:  2018-04-26       Impact factor: 5.753

10.  Genome-Wide Association Studies for Five Forage Quality-Related Traits in Sorghum (Sorghum bicolor L.).

Authors:  Jieqin Li; Weijie Tang; Ya-Wen Zhang; Kai-Ning Chen; Chenchen Wang; Yanlong Liu; Qiuwen Zhan; Chunming Wang; Shi-Bo Wang; Shang-Qian Xie; Lihua Wang
Journal:  Front Plant Sci       Date:  2018-08-21       Impact factor: 5.753

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  2 in total

1.  High-Density Genetic Variation Map Reveals Key Candidate Loci and Genes Associated With Important Agronomic Traits in Peanut.

Authors:  Huiling Zhao; Ruizheng Tian; Han Xia; Changsheng Li; Guanghui Li; Aiqin Li; Xianying Zhang; Ximeng Zhou; Jing Ma; Huailing Huang; Kun Zhang; Mahendar Thudi; Changle Ma; Xingjun Wang; Chuanzhi Zhao
Journal:  Front Genet       Date:  2022-03-25       Impact factor: 4.599

2.  Genome-Wide Association Study Reveals the Genetic Basis of Kernel and Cob Moisture Changes in Maize at Physiological Maturity Stage.

Authors:  Minyan Zhang; Chaoyang Xiangchen; Jiaquan Yan; Yujuan Chengxu; Hao Liu; Chaoying Zou; Guangtang Pan; Yaou Shen; Langlang Ma
Journal:  Plants (Basel)       Date:  2022-07-30
  2 in total

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