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Genome-Wide Association Analysis Identified Quantitative Trait Loci (QTLs) Underlying Drought-Related Traits in Cultivated Peanut ( L.)

Overview
Journal Genes (Basel)
Publisher MDPI
Date 2024 Jul 27
PMID 39062647
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Abstract

Drought is a destructive abiotic stress that affects all critical stages of peanut growth such as emergence, flowering, pegging, and pod filling. The development of a drought-tolerant variety is a sustainable strategy for long-term peanut production. The U.S. mini-core peanut germplasm collection was evaluated for drought tolerance to the middle-season drought treatment phenotyping for pod weight, pod count, relative water content (RWC), specific leaf area (SLA), leaf dry matter content (LDMC), and drought rating. A genome-wide association study (GWAS) was performed to identify minor and major QTLs. A total of 144 QTLs were identified, including 18 significant QTLs in proximity to 317 candidate genes. Ten significant QTLs on linkage groups (LGs) A03, A05, A06, A07, A08, B04, B05, B06, B09, and B10 were associated with pod weight and pod count. RWC stages 1 and 2 were correlated with pod weight, pod count, and drought rating. Six significant QTLs on LGs A04, A07, B03, and B04 were associated with RWC stages 1 and 2. Drought rating was negatively correlated with pod yield and pod count and was associated with a significant QTL on LG A06. Many QTLs identified in this research are novel for the evaluated traits, with verification that the pod weight shared a significant QTL on chromosome B06 identified in other research. Identified SNP markers and the associated candidate genes provide a resource for molecular marker development. Verification of candidate genes surrounding significant QTLs will facilitate the application of marker-assisted peanut breeding for drought tolerance.

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References
1.
Vadez V, Kholova J, Medina S, Kakkera A, Anderberg H . Transpiration efficiency: new insights into an old story. J Exp Bot. 2014; 65(21):6141-53. DOI: 10.1093/jxb/eru040. View

2.
Wang J, Zhang Z . GAPIT Version 3: Boosting Power and Accuracy for Genomic Association and Prediction. Genomics Proteomics Bioinformatics. 2021; 19(4):629-640. PMC: 9121400. DOI: 10.1016/j.gpb.2021.08.005. View

3.
Lubkowitz M . The oligopeptide transporters: a small gene family with a diverse group of substrates and functions?. Mol Plant. 2011; 4(3):407-15. DOI: 10.1093/mp/ssr004. View

4.
Liang S, Xu S, Qu D, Yang L, Wang J, Liu H . Identification and Functional Analysis of the Caffeic Acid O-Methyltransferase (COMT) Gene Family in Rice ( L.). Int J Mol Sci. 2022; 23(15). PMC: 9369235. DOI: 10.3390/ijms23158491. View

5.
Atif R, Shahid L, Waqas M, Ali B, Rehman Rashid M, Azeem F . Insights on Calcium-Dependent Protein Kinases (CPKs) Signaling for Abiotic Stress Tolerance in Plants. Int J Mol Sci. 2019; 20(21). PMC: 6862689. DOI: 10.3390/ijms20215298. View