AbstractsBiology & Animal Science

QTL mapping and GWAS identify sources of iron deficiency chlorosis and canopy Wilt Tolerance in the Fiskeby III X Mandarin (Ottawa) soybean population

by Karl Joseph Butenhoff




Institution: University of Minnesota
Department:
Year: 2015
Keywords: GWAS; IDC; QTL; Soybean; Wilt; Applied plant sciences
Record ID: 2058690
Full text PDF: http://hdl.handle.net/11299/170730


Abstract

Abiotic stresses are a major yield limiting component in soybean production that producers cannot directly control. Therefore, an increase in the understanding of how different abiotic stresses affect soybean, and the identification of sources of tolerance to these stresses will be critical for the continued increase of soybean productivity well into the future. Here I present three separate, but related, studies analyzing iron deficiency chlorosis and drought tolerance in several soybean populations. For the first and second studies, the objectives were to (i) characterize the Fiskeby III X Mandarin (Ottawa) recombinant inbred line (RIL) population for its tolerance to iron deficiency chlorosis (IDC) and drought; (ii) identify quantitative trait loci (QTL) via composite interval mapping for iron deficiency chlorosis and canopy wilt in the RIL population; and (iii) identify co-localization of abiotic stress QTL and putative candidate genes for iron deficiency chlorosis tolerance and delayed canopy wilt. Iron chlorosis and canopy wilt scores were significantly different across the three years tested between the RILs as well as the parents of the population. Fiskeby III consistently scored better than Mandarin (Ottawa) for tolerance to iron chlorosis and canopy wilt in all three years. Two QTL were discovered, one on chromosome five and one on chromosome six, that together accounted for approximately 25 percent of the phenotypic variation for IDC. Two QTL were also identified for canopy wilt, one on chromosome six and one on chromosome 12, that together accounted for approximately 13 percent of the phenotypic variation. The two QTL identified on chromosome six co-localized to the same confidence interval. Several previously identified QTL co-localized with the identified IDC and canopy wilt QTL in this study. In addition, a potential candidate gene was identified on chromosome five that may play a role in the soybean IDC response. The third study was undertaken to potentially validate the QTL identified for IDC in the first study in two independent soybean populations. The objectives of this study were to (i) utilize association mapping to detect markers significantly associated with IDC in two independent populations, (ii) compare significant identified markers with the QTL regions identified in the bi-parental RIL population, and (iii) validate the major QTL identified on chromosome five in the RIL population. Association mapping identified 12 significant markers that accounted for 27.2 percent and 8.9 percent of the phenotypic variation for IDC in the two populations, respectively. These markers co-localized with several known iron related QTL and genes. A significant cluster of 11 markers on chromosome five co-localized with the major IDC QTL identified in the bi-parental Fiskeby III X Mandarin (Ottawa) population. A second potential candidate gene was identified in this QTL region that may be related to IDC in soybean.