Integrating a genome-wide association study with transcriptomic analysis to detect genes controlling grain drying rate in maize (Zea may, L.)

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2019-12-03
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Jia, Tengjiao
Wang, Lifeng
Li, Jingjing
Ma, Juan
Cao, Yanyong
Lubberstedt, Thomas
Li, Huiyong
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Key message Candidate genes on GDR were identified and drying molecular mechanism of grain was explored by integrating genome-wide association with transcriptomic analysis in maize.

Abstract Grain drying rate (GDR) is a key determinant of grain moisture (GM) at harvest. Here, a genome-wide association study (GWAS) of 309 inbred maize lines was used to identify single nucleotide polymorphisms (SNPs) associated with drying rates of grain, cobs, and bracts. Out of 217,933 SNPs, seven significant SNPs were repeatedly identified in four environments (P< 10-4). Based on genomic position of significant SNPs, six candidate genes were identified, and one of which (Zm00001d047468) was verified by transcriptomic data between inbred lines with high and low GDR, indicating stable and reliable correlation with GDR. To further detect more genes correlated with GDR and explore drying molecular mechanism of grain, expression profile of all GWAS-identified genes (4,941) detected from different environments, tissues and developmental stage were evaluated by transcriptomic data of six inbred lines with high or low GDR. Results revealed 162 genes exhibit up-regulated expression and another 123 down-regulated in three higher GDR inbred lines. Based on GO enrichment, 162 up-regulated genes were significantly enriched into grain primary metabolic process, nitrogen compound metabolic process and marcromolecule metabolic process (P< 0.05), which indicated grain filling impose notably influence on GDR before and after physiological maturity. Our results lay foundation in accelerating development of higher GDR maize gerplasm through marker-assisted selection and clarifying genetic mechanism of GDR in maize.

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This is a manuscript of an article published as Jia, Tengjiao, Lifeng Wang, Jingjing Li, Juan Ma, Yanyong Cao, Thomas Lübberstedt, and Huiyong Li. "Integrating a genome-wide association study with transcriptomic analysis to detect genes controlling grain drying rate in maize (Zea may, L.)." Theoretical and Applied Genetics (2019). doi: 10.1007/s00122-019-03492-0. Posted with permission.

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Tue Jan 01 00:00:00 UTC 2019
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