Genome-wide association study (GWAS) reveals genetic basis of ear-related traits in maize

生物 全基因组关联研究 最佳线性无偏预测 近交系 遗传学 数量性状位点 遗传关联 单核苷酸多态性 等位基因 关联映射 候选基因 基因 选择(遗传算法) 基因型 人工智能 计算机科学
作者
Lin Yang,Ting Li,Xiaokang Tian,Bingpeng Yang,Yonghui Lao,Yahui Wang,Xinghua Zhang,Jiquan Xue,Shutu Xu
出处
期刊:Euphytica [Springer Science+Business Media]
卷期号:216 (11) 被引量:11
标识
DOI:10.1007/s10681-020-02707-6
摘要

Maize ear-related traits are important components of grain yield that directly influence maize production. The genetic basis of ear-related traits is still not completely understood, which would be helpful in the improvement of grain yield. In this study, to dissect the genetic basis of ear diameter (ED), ear row number (ERN), and kernel number per row (KNR), a genome-wide association study of maize inbred lines was conducted using the phenotype of the three traits in two environments and the best linear unbiased prediction (BLUP) value. We detected 116 significant loci, i.e., 37, 42, and 37 related to ED, ERN, and KNR, respectively. Among these significant loci, 19 were co-localized when using the traits in two environments and BLUP value. The increase of superior allele number for the 19 co-localized loci was positively correlated with maize grain yield. Further, from the candidate regions of 116 significant loci, 558 genes expressed in maize cob and silk and participated in 71 biological pathways, such as RNA transport, protein export, biosynthesis of amino acids, and starch and sucrose metabolism. Of these candidate genes, some putative functional genes from the co-localized regions were predicted including ts6, pin4, Zm00001d038022, and Zm00001d041584, of which ts6 located in a known major QTL for ERN (named krn1). These results promote the understanding of the genetic basis for these three traits, which contributes to maize grain yield improvement by breeding.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
孑与应助王赟赟采纳,获得10
1秒前
Owen应助xue采纳,获得10
1秒前
1秒前
Dolphin发布了新的文献求助10
2秒前
2秒前
underway发布了新的文献求助10
3秒前
迷人的数据线完成签到,获得积分10
3秒前
乐lll完成签到,获得积分10
3秒前
cyy完成签到,获得积分10
3秒前
3秒前
4秒前
4秒前
嗯哼发布了新的文献求助10
4秒前
洁净的从凝完成签到,获得积分10
4秒前
5秒前
赘婿应助里奥采纳,获得10
5秒前
迷迷发布了新的文献求助10
5秒前
5秒前
zak发布了新的文献求助10
6秒前
6秒前
7秒前
陈陈陈完成签到,获得积分10
7秒前
一只耳完成签到,获得积分10
7秒前
孑与应助YIDAN采纳,获得10
7秒前
大力的远望完成签到 ,获得积分10
8秒前
8秒前
丫头完成签到,获得积分20
8秒前
QQ发布了新的文献求助10
9秒前
李健应助夕沫采纳,获得10
9秒前
积极的诗桃完成签到 ,获得积分10
9秒前
火焰鼠发布了新的文献求助10
10秒前
10秒前
10秒前
科研通AI6.2应助如常采纳,获得10
10秒前
小马甲应助xh采纳,获得10
10秒前
10秒前
xue完成签到,获得积分10
11秒前
无花果应助zhen采纳,获得10
11秒前
11秒前
迷迷完成签到,获得积分10
11秒前
高分求助中
Clinical Epidemiology: The Essentials, 6e 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Graphene Handbook (2019 Edition) 800
Adhesion Science: Principles & Practice 800
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
The Immune System (Fifth Edition) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6557441
求助须知:如何正确求助?哪些是违规求助? 8341199
关于积分的说明 17871382
捐赠科研通 5676611
什么是DOI,文献DOI怎么找? 2940950
邀请新用户注册赠送积分活动 1916772
关于科研通互助平台的介绍 1787785