Literature DB >> 29876718

Identification of charcoal rot resistance QTLs in sorghum using association and in silico analyses.

Amer F Mahmoud1, Salah Fatouh Abou-Elwafa2, Tariq Shehzad3.   

Abstract

Charcoal rot disease, a root and stem disease caused by the soil-borne fungus Macrophomina phaseolina (Tassi) Goid., is a major biotic stress that limits sorghum productivity worldwide. Charcoal rot resistance-related parameters, e.g., pre-emergence damping-off%, post-emergence damping-off%, charcoal rot disease severity, and plant survival rates, were measured in a structured sorghum population consisting of 107 landraces. Analysis of variance of charcoal rot resistance-related parameters revealed significant variations in the response to M. phaseolina infection within evaluated accessions. Continuous phenotypic variations for resistance-related parameters were observed indicating a quantitative inheritance of resistance. The population was genotyped using 181 simple sequence repeat (SSR) markers. Association analysis identified 13 markers significantly associated with quantitative trait genes (QTLs) conferring resistance to charcoal rot disease with an R2 value ranging between 9.47 to 18.87%, nine of which are environment-specific loci. Several QTL-linked markers are significantly associated with more than one resistance-related parameter, suggesting that those QTLs might contain genes involved in the plant defense response. In silico analysis of four novel major QTLs identified 11 putative gene homologs that could be considered as candidate genes for resistance against charcoal rot disease. Cluster analysis using the genotypic data of 181 SSR markers from 107 sorghum accessions identified 12 main clusters. The results provide a basis for further functional characterization of charcoal rot disease resistance or defense genes in sorghum and for further dissection of their molecular mechanisms.

Entities:  

Keywords:  Association mapping; Charcoal rot; GWAS; Macrophomina phaseolina; Quantitative trait genes; Sorghum bicolor

Mesh:

Substances:

Year:  2018        PMID: 29876718     DOI: 10.1007/s13353-018-0446-5

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   3.240


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