Genome-wide dissection of the maize ear genetic architecture using multiple populations

Genome-wide dissection of the maize ear genetic architecture using multiple populations

© 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Bibliographische Detailangaben
Veröffentlicht in:The New phytologist. - 1979. - 210(2016), 3 vom: 20. Mai, Seite 1095-106
1. Verfasser: Xiao, Yingjie (VerfasserIn)
Weitere Verfasser: Tong, Hao, Yang, Xiaohong, Xu, Shizhong, Pan, Qingchun, Qiao, Feng, Raihan, Mohammad Sharif, Luo, Yun, Liu, Haijun, Zhang, Xuehai, Yang, Ning, Wang, Xiaqing, Deng, Min, Jin, Minliang, Zhao, Lijun, Luo, Xin, Zhou, Yang, Li, Xiang, Liu, Jie, Zhan, Wei, Liu, Nannan, Wang, Hong, Chen, Gengshen, Cai, Ye, Xu, Gen, Wang, Weidong, Zheng, Debo, Yan, Jianbing
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:The New phytologist
Schlagworte:Journal Article Research Support, Non-U.S. Gov't genome-wide association study (GWAS) joint linkage mapping maize (Zea mays) multi-parent population quantitative trait loci (QTLs) yield traits
Beschreibung
Zusammenfassung:© 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
Improvement of grain yield is an essential long-term goal of maize (Zea mays) breeding to meet continual and increasing food demands worldwide, but the genetic basis remains unclear. We used 10 different recombination inbred line (RIL) populations genotyped with high-density markers and phenotyped in multiple environments to dissect the genetic architecture of maize ear traits. Three methods were used to map the quantitative trait loci (QTLs) affecting ear traits. We found 17-34 minor- or moderate-effect loci that influence ear traits, with little epistasis and environmental interactions, totally accounting for 55.4-82% of the phenotypic variation. Four novel QTLs were validated and fine mapped using candidate gene association analysis, expression QTL analysis and heterogeneous inbred family validation. The combination of multiple different populations is a flexible and manageable way to collaboratively integrate widely available genetic resources, thereby boosting the statistical power of QTL discovery for important traits in agricultural crops, ultimately facilitating breeding programs
Beschreibung:Date Completed 26.12.2016
Date Revised 31.03.2022
published: Print-Electronic
Citation Status MEDLINE
ISSN:1469-8137
DOI:10.1111/nph.13814