Association mapping for grain quality in a diverse sorghum collection - Sukumaran, Sivakumar; Xiang, Wenwen; Bean, Scott R.; Pedersen, Jeffrey F.; Kresovich, Stephen; Tuinstra, Mitchell R.; Tesso, Tesfaye T.; Hamblin, Martha T.; Yu, Jianming (My University, 2013)
Knowledge of the genetic bases of grain quality traits will complement plant breeding efforts to improve the end-use value of sorghum [Sorghum bicolor (L.) Moench]. Candidate gene association mapping was used on a diverse panel of 300 sorghum accessions to assess marker–trait associations for 10 grain quality traits measured using the single kernel characterization system (SKCS) and near-infrared reflectance spectroscopy (NIRS). The analysis of the accessions through 1290 genomewide single nucleotide polymorphisms (SNPs) separated the panel into five subpopulations that corresponded to three major sorghum races (durra, kafir, and caudatum), one intermediate race (guinea-caudatum), and one working group (zerazera-caudatum). These subpopulations differed in kernel hardness, acid detergent fiber, and total digestible nutrients. After model testing, association analysis between 333 SNPs in candidate genes and/or loci and grain quality traits resulted in eight significant marker–trait associations. A SNP in starch synthase IIa (SSIIa) gene was associated with kernel hardness (KH) with a likelihood ratio-based R[superscript 2] (R[subscript LR][superscript 2]) value of 0.08, a SNP in starch synthase (SSIIb) gene was associated with starch content with an R[subscript LR][superscript 2] value of 0.10, and a SNP in loci pSB1120 was associated with starch content with an R[subscript LR][superscript 2] value of 0.09.
Citation: Sukumaran, Sivakumar, Wenwen Xiang, Scott R. Bean, Jeffrey F. Pedersen, Stephen Kresovich, Mitchell R. Tuinstra, Tesfaye T. Tesso, Martha T. Hamblin, and Jianming Yu. “Association Mapping for Grain Quality in a Diverse Sorghum Collection.” The Plant Genome 5, no. 3 (2012): 126–35. https://doi.org/10.3835/plantgenome2012.07.0016.
Keywords: Sorghum; Gene association mapping; Single kernel characterization system