Genomics and phenomics enabled prebreeding improved early-season chilling tolerance in Sorghum

Abstract

In temperate climates, earlier planting of tropical-origin crops can provide longer growing seasons, reduce water loss, suppress weeds, and escape post-flowering drought stress. However, chilling sensitivity of sorghum, a tropical-origin cereal crop, limits early planting, and over 50 years of conventional breeding has been stymied by coinheritance of chilling tolerance (CT) loci with undesirable tannin and dwarfing alleles. In this study, phenomics and genomics-enabled approaches were used for prebreeding of sorghum early-season CT. Uncrewed aircraft systems (UAS) high-throughput phenotyping platform tested for improving scalability showed moderate correlation between manual and UAS phenotyping. UAS normalized difference vegetation index values from the chilling nested association mapping population detected CT quantitative trait locus (QTL) that colocalized with manual phenotyping CT QTL. Two of the 4 first-generation Kompetitive Allele Specific PCR (KASP) molecular markers, generated using the peak QTL single nucleotide polymorphisms (SNPs), failed to function in an independent breeding program as the CT allele was common in diverse breeding lines. Population genomic fixation index analysis identified SNP CT alleles that were globally rare but common to the CT donors. Second-generation markers, generated using population genomics, were successful in tracking the donor CT allele in diverse breeding lines from 2 independent sorghum breeding programs. Marker-assisted breeding, effective in introgressing CT allele from Chinese sorghums into chilling-sensitive US elite sorghums, improved early-planted seedling performance ratings in lines with CT alleles by up to 13–24% compared to the negative control under natural chilling stress. These findings directly demonstrate the effectiveness of high-throughput phenotyping and population genomics in molecular breeding of complex adaptive traits.

Introgression of Stay Green Quantitative Trait Locus (QTLS) into Elite Sorghum Variety by MABC

“…To ensure the quality of the data, a subset of samples was genotyped in duplicate, and the genotyping results were compared to ensure consistency. In addition, a set of positive and negative control samples were included in each genotyping run to monitor the performance of the reaction and to assess the accuracy of the genotyping results [5].…”

The role of phenomics and genomics in delineating the genetic basis of complex traits in millets

“…QTL mapping has been used in sorghum to study genomics and phenomics. For example, a study utilized a chilling nested association mapping population with 43 K GBS SNPs and uncrewed aircraft system (UAS) high-throughput phenotyping to provide high-resolution chilling tolerance (CT) mapping, addressing weak trait-to-QTL association from previous sorghum CT studies (Marla et al 2023) Similarly, a genome-wide association study (GWAS) identified causal polymorphisms for traits like drought tolerance and biomass yield based on historical recombination events in sorghum by employing a drone (Spindel et al 2018). The drone was a modified multirotor vehicle with Blue River's proprietary imaging payload (Spindel et al 2018).…”