Experimental evaluation of effectiveness of genomic selection for resistance to northern corn leaf blight in maize.

Autor: Lohithaswa HC; Department of Genetics and Plant Breeding, University of Agricultural Sciences, GKVK, Bangalore, 560 065, Karnataka, India. lohithaswa.chandappa@gmail.com., Balasundara DC; Department of Genetics and Plant Breeding, University of Agricultural Sciences, GKVK, Bangalore, 560 065, Karnataka, India.; Corteva Agriscience Pvt. Ltd, Kallinayakanahalli, 561 213, Gauribidanur, Chikkaballapur, Karnataka, India., Mallikarjuna MG; Division of Genetics, ICAR-Indian Agricultural Research Institute (ICAR, PUSA Campus, New Delhi, 110 012, India., Sowmya MS; Department of Genetics and Plant Breeding, University of Agricultural Sciences, GKVK, Bangalore, 560 065, Karnataka, India., Mallikarjuna N; Zonal Agriculture Research Station, V.C. Farm, Mandya, 571 405, India., Kulkarni RS; Department of Genetics and Plant Breeding, University of Agricultural Sciences, GKVK, Bangalore, 560 065, Karnataka, India., Pandravada AS; Corteva Agriscience Pvt. Ltd, Kallinayakanahalli, 561 213, Gauribidanur, Chikkaballapur, Karnataka, India., Bhatia BS; Corteva Agriscience Pvt. Ltd, Kallinayakanahalli, 561 213, Gauribidanur, Chikkaballapur, Karnataka, India.
Jazyk: angličtina
Zdroj: Journal of applied genetics [J Appl Genet] 2024 Oct 24. Date of Electronic Publication: 2024 Oct 24.
DOI: 10.1007/s13353-024-00911-x
Abstrakt: Northern corn leaf blight (NLB) caused by Setosphaeria turcica (Luttrell) Leonard & Suggs is a severe foliar disease in maize. Resistance to NLB is complexly inherited and controlled by several quantitative trait loci (QTL) distributed across the genome. Phenotype and DNA marker-based selection for resistance to NLB is expected to be effective. Hence, an investigation was carried out to predict the genetic value of selection candidates for resistance to NLB and compare the accuracies of genomic prediction in two F 2:3 populations of two crosses (CM212 × MAI172; CM202 × SKV50) derived from contrasting parents. Linkage analysis using 297 polymorphic SNPs in population-1 and 290 polymorphic SNPs in population-2 revealed ten linkage groups spanning 3623.88 cM and 4261.92 cM with an average distance of 12.40 cM and 14.9 cM in population-1 and population-2, respectively. Location-wise and pooled data across locations identified common QTLs on linkage groups 1 and 6 in population-1 and 3 and 8 in population-2. The prediction accuracy of the QTL mapping (9.92 and 9.10 for population-1 and population-2, respectively) was based on only a few markers, which explained higher percent phenotypic variation. The prediction accuracies of the genomic estimated breeding values in the present investigation were relatively low in population-1 (0.24 to 0.26) and population-2 (0.29-0.32) compared to the expected accuracies. This could be due to fewer polymorphic markers and a small training/population size. Though the GS prediction accuracies were relatively low, they were significantly higher than QTL mapping, which promises better genetic gain per cycle. The resistant progenies from both populations were advanced to derive inbred lines and crossed with four different testers in line × tester mating design to test for their combining ability and effectiveness of genomic selection. High overall general combining ability was exhibited by 21 inbred lines. Among F 1 s, 48% were assigned high overall specific combining ability status. Out of the 136 single crosses, seven recorded significant positive standard heterosis over the best check for grain yield. Twenty-five inbreds with high GEBVs were crossed with four testers to obtain 100 F 1 s and evaluated for their response to NLB. The majority of hybrids displayed moderate to resistant reaction to NLB either in combination with susceptible or resistant testers indicating the effectiveness of selection based on high GEBVs.
(© 2024. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.)
Databáze: MEDLINE
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