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Common genetic control for grain filling duration and kernel weight in grain sorghum
Daniel Otwani1,2, Colleen Hunt3,4,5, Alan Cruickshank4
1Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Hermitage Research Facility, Warwick, QLD, Australia. d.otwani@uq.edu.au.
Key Message:
The genetic control of GFD in sorghum closely overlaps with that of grain size, is influenced by both pre- and post-anthesis processes, offering new opportunities for yield improvement through targeted breeding and inter-racial trait introgression. The duration of the grain filling period has been associated with yield increases in cereals including maize and sorghum. The genetic control of grain filling duration (GFD) is however not known in sorghum. This study explored the genetic variation and extent of genetic control for GFD in a diverse panel of sorghum genotypes (n=904), in three environments across two years. A genome wide association analysis revealed 86 QTLs, 46 of which collocated with 54 previously reported grain size candidate genes in sorghum, indicating a significant enrichment. Single marker analysis revealed that genomic regions associated with GFD were similarly associated with grain size. Interestingly, in silico expression analysis of candidate genes associated with GFD revealed that GFD could be associated with processes that happen both before and after anthesis contrary to the understanding that GFD was primarily associated with processes that happen post anthesis. Haplotype analysis of SbGS3 resolved 8 haplotypes associated with grain filling duration, 2 of which were exclusive to the Guinea and Asian durra racial groups revealing opportunities for trait introgression across sorghum racial groups. These results indicate considerable opportunity to increase grain yield in sorghum, by selecting for longer GFD and diverse inter racial crosses to improve the genetic diversity for GFD in sorghum. Sorghum breeders will find application of these results in diversifying trait selection to optimise yields in changing environments.