Location: Crop Genetics ResearchTitle: Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations
|HWANG, SADAL - University Of Arkansas|
|KING, C - University Of Arkansas|
|Ray, Jeffery - Jeff|
|CHEN, PENGYIN - University Of Arkansas|
|Carter Jr, Thomas|
|LI, ZENGLU - University Of Georgia|
|MATSON, KEVIN - Monsanto Corporation|
|SCHAPAUGH JR., WILLIAM - Kansas State University|
|PURCELL, LARRY - University Of Arkansas|
Submitted to: Journal of Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/16/2015
Publication Date: 7/12/2015
Citation: Hwang, S., King, C.A., Ray, J.D., Cregan, P.B., Chen, P., Carter Jr, T.E., Li, Z., Abdel-Haleem, H.A., Matson, K.W., Schapaugh Jr., W., Purcell, L.C. 2015. Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations. Journal of Theoretical and Applied Genetics. 128:2047-2065.
Interpretive Summary: Delayed canopy wilting has been identified as a potential drought tolerance trait. Understanding the genetics of this trait would be useful in developing soybean lines with increased drought tolerance. In this study, specific locations in the soybean genome associated with delayed canopy wilting were identified across five soybean populations segregating for canopy wilting. The genomic locations are identified by molecular markers. Overall, the results indicated that there were likely eight separate genomic locations associated with delayed canopy wilting identified in more than one population. Molecular markers near these genomic locations may be useful in marker-assisted selection in soybean breeding programs.
Technical Abstract: Quantitative trait loci (QTLs) for canopy wilting were identified in five recombinant inbred line populations, 93705 KS4895 x Jackson, 08705 KS4895 x Jackson, KS4895 x PI 424140, A5959 x PI 416937, and Benning x PI 416937 in a total of 15 site-years. For most environments, heritability of canopy wilting ranged from 0.65 to 0.85 but was somewhat lower when averaged over environments. Putative QTLs were identified with composite interval mapping and/or multiple interval mapping methods in each population and positioned on the consensus map along with their 95% confidence intervals (CIs). We initially found nine QTL clusters with overlapping CIs on chromosomes 2, 5, 11, 14, 17, and 19 identified from at least two different populations, but a simulation study indicated that the QTLs on Gm14 could be false positives. A QTL on Gm8 in the 93705 KS4895 x Jackson population co-segregated with a QTL for wilting published previously in a Kefung1 x Nannong 1138-2 population, indicating that this may be an additional QTL cluster. Excluding the QTL cluster on Gm14, results of the simulation study indicated that the eight remaining QTL clusters and the QTL on Gm8 appeared to be authentic QTLs. QTL x year interactions indicated that QTLs were stable over years except for major QTLs on Gm11 and Gm19. The stability of QTLs located on seven clusters indicates that they are possible candidates for use in marker-assisted selection.