Genome wide association study for protein expression under normal and water deficit conditions in maize leaves
Résumé
Maize is one of the main crops worldwide, but its yield can be severely affected by drought. Drought tolerance in maize is genotype-dependent, indicating that this trait can be genetically improved. This study aimed to identify genetic determinants of drought tolerance by using genome wide association study (GWAS) to identify pQTLs for protein abundance that colocalize with QTL for ecophysiological traits. A panel of 251 maize genotypes was grown in the high-throughput phenotyping platform PhenoArch (Montpellier) under water deficit (WW) and well-watered (WD) conditions and in two replicates. Several ecophysiological parameters were measured during plant growth and analyzed elsewhere (Alvarez Prado et al., submitted). At the pre-flowering stage, 1004 samples were taken on the last ligulated leaf and analyzed by shotgun proteomics. Protein identification and inference were performed using X!TandemPipeline (Langella et al., 2017, J. Proteome Res., 16:494-503). A total of 1950 proteins were quantified either by extracted ion current using MassChroq (Valot et al., 2011, Proteomics 11:3572-77) or by peak counting. GWAS was performed for 3900 molecular phenotypes (=1950 proteins x 2 conditions) using FaST-LMM (Lippert et al., 2011, Nature Methods, 8:833-835). Most proteins showed significant abundance variations in response to water deficit and to genotype. Drought responsive proteins, like dehydrins, were highly induced under WD, while proteins of energy metabolism were down-regulated. pQTLs were detected for most proteins, confirming the high genetic variability of their abundances. The most strongly associated pQTLs were located close to the protein encoding genes. Forty seven pQTL/QTL colocalizations, involving 5 ecophysiological traits and 58 proteins, were identified, mostly in WD. These results show the potential of high-throughput quantitative proteomics to decipher the determinisms of protein abundance regulation and to discover candidate genes and proteins potentially involved in the variation of plant phenotypic traits.
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Licence : CC BY NC - Paternité - Pas d'utilisation commerciale
Licence : CC BY NC - Paternité - Pas d'utilisation commerciale