Evaluating introgression sorghum germplasm selected at the population level while exploring genomic resources as a screening method

Authors: WINANS, NOAH - Texas A&M University; Klein, Robert - Bob; FONSECA, JALES - Texas A&M University; KLEIN, PATRICIA - Texas A&M University; ROONEY, WILLIAMS - Texas A&M University

Submitted to: Plants
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/13/2023
Publication Date: 1/13/2023
Citation: Winans, N.D., Klein, R.R., Fonseca, J.M., Klein, P.E., Rooney, W.L. 2023. Evaluating introgression sorghum germplasm selected at the population level while exploring genomic resources as a screening method. Plants. Article e12030444. https://doi.org/10.3390/plants12030444.
DOI: https://doi.org/10.3390/plants12030444

Interpretive Summary: The yield potential in grain sorghum hybrids has increased at a slower rate than other cereal crops including its close relative maize. While there are many reasons for this lag, increasing hybrid performance through genomic selection has the potential to accelerate the rate of genetic gain in sorghum to levels that parallel gains in hybrid maize. To address this issue, we implemented a pilot program to predict hybrid grain yield performance in genetically diverse populations of sorghum using genome prediction models. This study will provide the necessary knowledge to breeders who work to exploit genomic technologies in improving grain yield of hybrid cereal crops including sorghum.

Technical Abstract: To exploit the novel genetic diversity residing in tropical sorghum germplasm, an expansive backcross nested-association mapping (BC-NAM) resource was developed in which novel genetic diversity was introgressed into elite inbreds. A major limitation to exploiting this type of genetic resource in hybrid improvement programs is the required evaluation in hybrid combination of the vast number of populations and lines. To address this, the utility of genomic information was evaluated to predict the hybrid performance of BC-NAM populations. Two agronomically-elite BC-NAM populations were chosen for evaluation in which elite inbred RTx436 was the recurrent parent. Each BC-NAM line was evaluated in hybrid combination with an elite tester in two locations with phenotypes of grain yield, plant height, and days to anthesis collected on all test cross hybrids. Lines from both populations were found to outperform their recurrent parent. Efforts to utilize genetic distance based on genotyping-by-sequence as a predictive tool for hybrid performance was ineffective. However, utilizing genomic prediction models using additive and dominance GBLUP kernels to screen germplasm appeared to be an effective method to eliminate inferior-performing lines that will not be useful in a hybrid breeding program.