Genomic prediction of hybrid performance for agronomic traits in sorghum

Abstract

Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time consuming, genomic prediction of parental lines and hybrids based on genetic data would reduce breeding cycle length and increase probability of recovering exceptional product genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency > 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76 to 0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12% to 90%, with plant height showing the greatest decline. Mean accuracies for predicting general combining ability (GCA) of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.

Evaluating and Predicting the Performance of Sorghum Lines in an Elite by Exotic Backcross-Nested Association Mapping Population

“…The prediction accuracies for days to mid-anthesis and grain yield ( Figure 4 ) are like those reported in other studies in sorghum [ 5 , 15 , 16 , 20 , 21 , 22 , 23 ]. However, the prediction accuracies for plant height are lower than in previous studies, much like what was observed by Winans et al [ 5 ] and Sapkota et al [ 22 ]. From observation, there is a large amount of variation in plant height, and it is likely that a few of the families are segregating for major dwarfing genes.…”

“…From observation, there is a large amount of variation in plant height, and it is likely that a few of the families are segregating for major dwarfing genes. Studies reporting high prediction accuracy for plant height had lines subject to more intense selection pressure, and it is likely that large-effect genes that control height were fixed [ 16 , 21 , 23 ], whereas studies with large variation in height, exotic germplasms, and minimal selection reported lower prediction accuracies [ 5 , 22 ]. Within this study, the GBLUP approach is limited in its ability to capture large single gene effects due to the distributed weight of effects across the genome [ 11 , 24 ].…”

Production and cultivation dynamics of millets in India

“…Heterotic grouping of hybrid parental lines and heterosis prediction in hybrids are the priority focus for increased heterosis to realize a significant jump in the productivity of pearl millet and sorghum. Some attempts have been made to define heterotic groups both in pearl millet and sorghum (Maulana et al, 2023;Pucher et al, 2018;Ramya et al, 2018;Sapkota et al, 2023). A study involving 320R and 260B Indian pearl millet parents identified two distinct heterotic groups from each group based on the heterotic performance and combining ability (S. K. Gupta et al, 2020).…”

“…This study also indicated that distinct parental groups could be formed based on molecular markers, which can help in assigning hybrid parental lines into appropriate heterotic groups to develop high-yielding hybrids. In sorghum, Sapkota et al (2023) phenotyped 602 hybrids for agronomic performance and genotyped their two female and 301 restorer male parents using 2.69 million single nucleotide polymorphisms for genomic prediction. Genomic best linear unbiased prediction showed that the agronomic performance of hybrids can be predicted with high accuracy, while the prediction of general combining ability of male parents varied from 0.33 to 0.62 for Crop Science different traits.…”