QTL Identified for Source-Sink Relationships in a Bi-Parental Recombinant Inbred Line Population
Sorghum grown under favorable conditions has high production potential. Photoassimilate production at the source (leaf) and transport to the sink (grain) are primary determinants of the yield. Mapping Quantitative Trait Loci (QTL) for source-sink relationships is of interest to biologists and breeders alike and will give breeders tools for sorghum improvement.
To identify QTLs related to source- sink relationships, researchers at Kansas State University, Texas A&M University, Mississippi State University, Agriculture and Agri-Food Canada, and USDA-ARS measured traits in a bi-parental Recombinant Inbred Line (RIL) population derived from SC35 and RTx430 inbreds. They hypothesized that the population would exhibit a wide range in grain yield, therefore making it possible to map QTL for source, sink and panicle neck diameter-related traits during different growth stages and environmental conditions. These traits were positively associated with grain yield per panicle at mid-grain filling and at maturity. The QTL hotspots identified in this study could lead to sorghum yield improvement via marker-assisted selection and breeding by targeting multiple traits.
There were no previous studies in sorghum which attempted to map source and sink related QTL under different environmental conditions. Hence to fill the knowledge gap, we set up this experiment under wide environment and moisture conditions including full irrigation throughout the crop duration. – Anuj Chiluwal
We anticipate that the identified QTL from this study would be helpful in pyramiding favorable alleles for improving source and sink dynamics to optimize sorghum yield under diverse environments. – Krishna Jagadish
SorghumBase example
Reference
Chiluwal A, Perumal R, Poudel HP, Muleta K, Ostmeyer T, Fedenia L, Pokharel M, Bean SR, Sebela D, Bheemanahalli R, Oumarou H, Klein P, Rooney WL, Jagadish SVK. Genetic control of source-sink relationships in grain sorghum. Planta. 2022 Jan 17;255(2):40. doi: 10.1007/s00425-022-03822-5. PMID: 35038036. Read More
Related Project Websites:
Kansas State University https://www.agronomy.k-state.edu/people/faculty/jagadish-sv-krishna/
