Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize.
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| Title: | Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize. |
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| Authors: | Song, Junqiao1,2,3 (AUTHOR), Liu, Yubo2,4 (AUTHOR), Guo, Rui2,5 (AUTHOR), Pacheco, Angela2 (AUTHOR), Muñoz-Zavala, Carlos2 (AUTHOR), Song, Wei2,5 (AUTHOR), Wang, Hui2,4 (AUTHOR), Cao, Shiliang2,6 (AUTHOR), Hu, Guanghui2,6 (AUTHOR), Zheng, Hongjian4 (AUTHOR), Dhliwayo, Thanda2 (AUTHOR), San Vicente, Felix2 (AUTHOR), Prasanna, Boddupalli M.7 (AUTHOR), Wang, Chunping1 (AUTHOR) chunpingw@haust.edu.cn, Zhang, Xuecai2,8,9 (AUTHOR) xc.zhang@cgiar.org |
| Source: | Theoretical & Applied Genetics. May2024, Vol. 137 Issue 5, p1-20. 20p. |
| Abstract: | Key message: A stable genomic region conferring FSR resistance at ~250 Mb on chromosome 1 was identified by GWAS. Genomic prediction has the potential to improve FSR resistance. Fusarium stalk rot (FSR) is a global destructive disease in maize; the efficiency of phenotypic selection for improving FSR resistance was low. Novel genomic tools of genome-wide association study (GWAS) and genomic prediction (GP) provide an opportunity for genetic dissection and improving FSR resistance. In this study, GWAS and GP analyses were performed on 562 tropical maize inbred lines consisting of two populations. In total, 15 SNPs significantly associated with FSR resistance were identified across two populations and the combinedPOP consisting of all 562 inbred lines, with the P-values ranging from 1.99 × 10–7 to 8.27 × 10–13, and the phenotypic variance explained (PVE) values ranging from 0.94 to 8.30%. The genetic effects of the 15 favorable alleles ranged from −4.29 to −14.21% of the FSR severity. One stable genomic region at ~ 250 Mb on chromosome 1 was detected across all populations, and the PVE values of the SNPs detected in this region ranged from 2.16 to 5.18%. Prediction accuracies of FSR severity estimated with the genome-wide SNPs were moderate and ranged from 0.29 to 0.51. By incorporating genotype-by-environment interaction, prediction accuracies were improved between 0.36 and 0.55 in different breeding scenarios. Considering both the genome coverage and the threshold of the P-value of SNPs to select a subset of molecular markers further improved the prediction accuracies. These findings extend the knowledge of exploiting genomic tools for genetic dissection and improving FSR resistance in tropical maize. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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