Genome-wide association study (GWAS) reveals genetic basis of ear-related traits in maize
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Genome-wide association study (GWAS) reveals genetic basis of ear-related traits in maize Lin Yang . Ting Li . Xiaokang Tian . Bingpeng Yang . Yonghui Lao . Yahui Wang . Xinghua Zhang . Jiquan Xue . Shutu Xu
Received: 26 April 2020 / Accepted: 26 September 2020 Ó Springer Nature B.V. 2020
Abstract 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 colocalized 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. Keywords Zea mays Ear-related traits GWAS Significant loci Candidate genes
Lin Yang and Ting Li contributed equally to this work.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10681-020-02707-6) contains supplementary material, which is available to authorized users. L. Yang T. Li X. Tian B. Yang Y. Lao Y. Wang X. Zhang J. Xue (&) S. Xu (&) Laboratory of Biology and Genetic Improvement of Maize in the Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, Shaanxi, China e-mail: [email protected] S. Xu e-mail: [email protected]
Introduction Maize (Zea mays L.) is one of the most important staple foods worldwide and plays a crucial role in sustaining food security and satisfying energy requirements (Zhu et al. 2018). Improving maize grain yield is a main long-term breeding goal in response to population growth, limited farmland, and the consequent food crisis (Li et al. 2011a). Dissecting the genetic architecture of grain yield can contribute to accomplish breeding goals and is a permanent research hotspot for agricultural science. However,
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grain yield is a complex quantita
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