Hybrid breeding technology is one of the most feasible options to meet the future food challenges and sustainable agriculture. Development of hybrids through the exploitation of heterosis involves evaluation of hundreds of test crosses in the field, making it input and resource intensive3. Therefore, plant breeders are interested in methods that can forecast the potential parental combinations so that only limited test crosses can be evaluated. In this regard, pedigree data of parental lines and molecular data have been effectively employed to predict field performance of hybrids3.

Genetic distance (GD) estimated using molecular marker heterozygosity between parents has been used as a useful criterion to predict single cross with good amount of heterosis. In a related study, heterosis prediction was made based on expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers and correlation between coefficient of marker polymorphism (CMP) and standard heterosis was positive and significant (r= 0.58**) indicating grouping of parental lines based on molecular characterization is helpful in identifying heterotic patterns in rice2. But efficiency of this method depends on many factors and did not give consistent results. Hence, a combination of parental genetic and metabolic markers, can significantly improve the prediction accuracy1. Recently, best linear unbiased prediction (BLUP), GBLUP, RR-BLUP, Genomic selection (GS) and Trait- marker best linear unbiased predictions (TM-BLUP) are being employed for predicting performance of hybrids. Genomic prediction of hybrid performance for agronomic traits in sorghum using Genomic best linear unbiased prediction (GBLUP) yielded an average prediction accuracy of 0.76–0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets4.

Increasing crop yields has been the most important objective and in this regard prediction of heterosis using phenotypic as well as molecular data is expected to aid in the identification of superior hybrids in an efficient way and with limited resources and inputs through the evaluation of limited experimental hybrids developed from predicted parental combinations.

References: 

1. GARTNER, T., STEINFATH, M., ANDORF, S., LISEC, J., MEYER, R. C., ALTMANN, T., WILLMITZER, L. AND SELBIG, J., 2009, Improved heterosis prediction by combining information on DNA-and metabolic markers. PloS one, 4(4):5220.

2. PAVANI, M., SUNDARAM, R. M., RAMESHA, M. S., KAVI KISHOR, P. B. AND KEMPARAJU, K. B., 2018, Prediction of heterosis in rice based on divergence of morphological and molecular markers. J. Genet., 97:1263-1279.

3. RAJENDRAKUMAR, P., 2015, Heterosis prediction using DNA markers. Sorghum molecular breeding, 101-114.

4. SAPKOTA, S., BOATWRIGHT, J. L., KUMAR, N., MYERS, M., COX, A., ACKERMAN, A. AND KRESOVICH, S., 2023, Genomic prediction of hybrid performance for agronomic traits in sorghum. G3-Genes Genom Genet, 13(4):311.