|KULKARNI, KRISHNANAND - Kyungpook National University|
|ASEKOVA, SOVETGUL - Kyungpook National University|
|LEE, DONG-HO - Kyungpook National University|
|SONG, JONG TAE - Kyungpook National University|
|LEE, JEONG-DONG - Kyungpook National University|
Submitted to: Crop and Pasture Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/31/2017
Publication Date: 2/28/2017
Publication URL: http://handle.nal.usda.gov/10113/5688590
Citation: Kulkarni, K.P., Asekova, S., Lee, D., Bilyeu, K.D., Song, J., Lee, J. 2017. Mapping QTLs for 100-seed weight in an interspecific soybean cross of Williams 82 (Glycine max) x PI 366121 (Glycine soja). Crop and Pasture Science. 68(2):148-155. doi: 10.1071/CP16246.
Interpretive Summary: Soybean yield is controlled by many genetic and environmental factors. Understanding the genetic basis of soybean yield and the interaction of the genes with each other and the environment will aid yield improvement efforts. The weight of individual seeds is one yield component with both genetic and environmental impacts. The objective of this research was to identify regions of the genome that contain genes that influence soybean seed weight in different environments from a popualation derived from a cross between a cultivated and a wild soybean line. Several regions were identified that matched previously identified regions, and additional novel regions were identified. The impact of this work is confirmation and identification of regions that become candidates for selection and isolation of an important yield-controlling trait.
Technical Abstract: 100-seed weight is a critical component for soybean quality and yield. The objective of the present study was to identify quantitative trait loci (QTLs) for 100-seed weight using 169 recombinant inbred lines (RILs) derived from the cross of Williams 82 x PI 366121. The parental lines and RILs were grown for four consecutive years (2012 – 2015) in the field. The seeds were harvested after maturity, dried and used to measure the 100-seed weight. Analysis of variance for 100-seed weight indicated significant environment, genotype, and genotype x environment interactions. QTL analysis employing inclusive composite interval mapping of additive QTLs implemented in QTL IciMapping (Version 4.0 identified a total of 9 QTLs (LOD > 3) on chromosomes 1, 2, 6, 8, 13, 14, 17 and 20. The individual QTLs explained phenotypic variation in the range 6 – 12 %. The QTLs were detected in a minimum of one to a maximum of two environments, indicating major influence of the growing environment on seed weight expression. A total of four QTLs, Qsw2-1, Qsw6-1, Qsw13-1 and Qsw14-1, identified in this study were found to be novel QTLs. The findings in this study may be helpful to reveal the molecular genetic basis of the seed weight trait in soybean.