ArticleInternational journal of molecular sciences2025
Genomic Prediction for Germplasm Improvement Through Inter-Heterotic-Group Line Crossing in Maize.
Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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7 authors.
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Abstract
Germplasm improvement is essential for maize breeding. Currently, intra-heterotic-group crossing is the major method for germplasm improvement, while inter-heterotic-group crossing is also used in breeding but not in a systematic way. In this study, five inbred lines from four heterotic groups were used to develop a connected segregating population through inter-heterotic-group line crossing (CSPIC), which comprised 5 subpopulations with 535 doubled haploid (DH) lines and 15 related test-cross populations including 1568 hybrids. Significant genetic variation was observed in most subpopulations, with several DH populations exhibiting superior phenotypes regarding traits such as plant height (PH), ear height (EH), days to anthesis (DTA), and days to silking (DTS). Notably, 10.8% of hybrids in the population POP5/C229 surpassed the high-yielding hybrid ND678 (CK). To reduce field planting costs and quickly screen for the best inter-heterotic-group DH lines and test-cross hybrids, we assessed the accuracy of genomic selection (GS) for within- and between-population predictions in the DH populations and the test-cross populations. Within the DH or the hybrid population, the prediction accuracy varied across populations and traits, with an average hybrid yield prediction accuracy of 0.41, reaching 0.54 in POP5/Z58. In the cross DH population predictions, the prediction accuracy of the half-sib population exceeded that of the non-sib cross population prediction, with the highest accuracy observed when the non-shared parents were from the same heterotic group, and the average phenotypic prediction accuracies of POP3 predicting POP2 and POP2 predicting POP3 were 0.54 and 0.45, respectively. In the cross hybrid population predictions, the accuracy was highest when both the training and the test sets came from the same DH populations, with an average accuracy of 0.43. The proportion of shared polymorphisms with respect to SNPs between the training and the test sets (PSP) exhibited a significant and strong correlation with the prediction accuracy of cross population prediction. This study demonstrates the feasibility of creating new heterotic groups through inter-heterotic-group crossing in germplasm improvement, and some cross population prediction patterns exhibited excellent prediction accuracy.
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