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QTL mapping and transcriptome analysis identify candidate genes influencing water-nitrogen interaction in maize.

Authors :
Kunhui He
Yakun Zhang
Wei Ren
Pengyun Chen
Jianchao Liu
Guohua Mi
Fanjun Chen
Qingchun Pan
Source :
Crop Journal (2095-5421); Dec2023, Vol. 11 Issue 6, p1872-1883, 12p
Publication Year :
2023

Abstract

Water and nitrogen fertilization are the key factors limiting maize productivity. The genetic basis of interactions between maize genotype, water, and nitrogen is unclear. A recombinant inbred line (RIL) maize population was evaluated for seven yield and five agronomic traits under four water and nitrogen conditions: water stress and low nitrogen, water stress and high nitrogen, well-watered and low nitrogen, and well-watered and high nitrogen. Respectively eight, six, and six traits varied in response to genotype-water interactions, genotype-nitrogen interactions, and genotype-water-nitrogen interactions. Using a linkage map consisting of 896 single-nucleotide polymorphism markers and multiple-environmental quantitative-trait locus (QTL) mapping, we identified 31 QTL, including 12 for genotype-water-nitrogen interaction, across the four treatments. A set of 8060 genes were differentially expressed among treatments. Integrating genetic analysis, gene co-expression, and functional annotation revealed two candidate genes controlling genotype-water-nitrogen interactions, affecting both leaf width and grain yield. Genes involved in abscisic acid biosynthesis and bZIP, NAC, and WRKY transcription factors participated in maize response to water and nitrogen conditions. These results represent a step toward understanding the genetic regulatory network of maize that responds to water and nitrogen stress and provide a theoretical basis for the genetic improvement of both water- and nitrogen-use efficiency. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20955421
Volume :
11
Issue :
6
Database :
Complementary Index
Journal :
Crop Journal (2095-5421)
Publication Type :
Academic Journal
Accession number :
174806958
Full Text :
https://doi.org/10.1016/j.cj.2023.09.001