Genetic control of leaf angle in sorghum and its effect on light interception.

Zhi X, Tao Y, Jordan D, Borrell A, Hunt C, Cruickshank A, Potgieter A, Wu A, Hammer G, George-Jaeggli B, Mace E

Published: 27 October 2021 in Journal of experimental botany
Keywords: Auxin, brassinosteroids, candidate genes, genome-wide association study, leaf angle, light interception, photosynthesis, sorghum
Pubmed ID: 34698817
DOI: 10.1093/jxb/erab467

Developing sorghum genotypes adapted to different light environments requires understanding of a plant's ability to capture light, determined through leaf angle specifically. This study dissected the genetic basis of leaf angle in 3 year field trials at two sites, using a sorghum diversity panel (729 accessions). A wide range of variation in leaf angle with medium heritability was observed. Leaf angle explained 36% variation in canopy light extinction coefficient, highlighting the extent to which variation in leaf angle influences light interception at the whole-canopy level. This study also found that the sorghum races of Guinea and Durra consistently having the largest and smallest leaf angle, respectively, highlighting the potential role of leaf angle in adaptation to distinct environments. The genome-wide association study detected 33 quantitative trait loci (QTLs) associated with leaf angle. Strong synteny was observed with previously detected leaf angle QTLs in maize (70%) and rice (40%) within 10 cM, among which the overlap was significantly enriched according to χ2 tests, suggesting a highly consistent genetic control in grasses. A priori leaf angle candidate genes identified in maize and rice were found to be enriched within a 1-cM window around the sorghum leaf angle QTLs. Additionally, protein domain analysis identified the WD40 protein domain as being enriched within a 1-cM window around the QTLs. These outcomes show that there is sufficient heritability and natural variation in the angle of upper leaves in sorghum which may be exploited to change light interception and optimize crop canopies for different contexts.