Meta-Quantitative Trait Loci Analysis and Candidate Gene Mining for Drought Tolerance-Associated Traits in Maize (
candidate genes
drought tolerance
maize
meta-QTL
Journal
International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791
Informations de publication
Date de publication:
12 Apr 2024
12 Apr 2024
Historique:
received:
07
03
2024
revised:
10
04
2024
accepted:
11
04
2024
medline:
27
4
2024
pubmed:
27
4
2024
entrez:
27
4
2024
Statut:
epublish
Résumé
Drought is one of the major abiotic stresses with a severe negative impact on maize production globally. Understanding the genetic architecture of drought tolerance in maize is a crucial step towards the breeding of drought-tolerant varieties and a targeted exploitation of genetic resources. In this study, 511 quantitative trait loci (QTL) related to grain yield components, flowering time, and plant morphology under drought conditions, as well as drought tolerance index were collected from 27 published studies and then projected on the IBM2 2008 Neighbors reference map for meta-analysis. In total, 83 meta-QTL (MQTL) associated with drought tolerance in maize were identified, of which 20 were determined as core MQTL. The average confidence interval of MQTL was strongly reduced compared to that of the previously published QTL. Nearly half of the MQTL were confirmed by co-localized marker-trait associations from genome-wide association studies. Based on the alignment of rice proteins related to drought tolerance, 63 orthologous genes were identified near the maize MQTL. Furthermore, 583 candidate genes were identified within the 20 core MQTL regions and maize-rice homologous genes. Based on KEGG analysis of candidate genes, plant hormone signaling pathways were found to be significantly enriched. The signaling pathways can have direct or indirect effects on drought tolerance and also interact with other pathways. In conclusion, this study provides novel insights into the genetic and molecular mechanisms of drought tolerance in maize towards a more targeted improvement of this important trait in breeding.
Identifiants
pubmed: 38673880
pii: ijms25084295
doi: 10.3390/ijms25084295
pii:
doi:
Types de publication
Journal Article
Meta-Analysis
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Hainan Provincial Natural Science Foundation of China
ID : 321MS067
Organisme : the PhD Scientific Research and Innovation Foundation of Sanya Yazhou Bay Science and Technology City
ID : HSPHDSRF-2023-05-007
Organisme : the Science and Technology Innovation Team of Maize Modern Seed Industry in Hebei
ID : 21326319D
Organisme : the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
ID : 328017493/GRK 2366