Identification of QTLs Underlying Water-Logging Tolerance in Soybean

Cornelious, B.; Chen, P.; Chen, Y.; León, Natalia de; Shannon, J. Grover; Wang, D.

doi:10.1007/s11032-005-5911-2

Cited by 92 publications

(75 citation statements)

References 27 publications

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“…Leaf chlorosis is a direct symptom of flooding that has been successfully applied in wheat (Boru et al 2001), soybean (Cornelious et al 2005) and barley (Li et al 2008). In our study, a MFVW that integrates a wilting index, a chlorosis score and the dead leaf proportion of waterlogged plants was deployed to measure WT.…”

Section: Discussionmentioning

confidence: 99%

Combining ability, heterosis, genetic distance and their intercorrelations for waterlogging tolerance traits in chrysanthemum

Zhang

Yang

et al. 2017

Euphytica

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Waterlogging tolerance (WT) is a major objective in chrysanthemum breeding programs, and although certain genotypes with different tolerance levels have been identified, their value as parents for WT breeding is unknown. Here, twelve F 1 crosses derived from an incomplete diallel mating scheme were conducted to investigate combining ability and heterosis for WT and their relationships with parental genetic distance. The results showed that the membership function value of waterlogging (MFVW) was controlled by additive and non-additive gene effects, whereas other growth and biomass traits were mainly controlled by non-additive gene effects. The estimated broad and narrow sense heritabilities of the MFVW were 97.5 and 51.5%, respectively. Combining ability analyses indicated that 'Nannong Xuefeng' showing the largest general combining ability (GCA) effect for the MFVW was the best combiner, and identified several best cross combinations with high positive specific combining ability (SCA) effects for most WT-related traits. Mid-and high-parent heterosis occurred widely. The three distance measures, based on phenotypic traits (PD), molecular markers (GD) and markers linked with quantitative trait loci (QTL-GD), presented a nonsignificant correlation with combining ability except for the GD with GCA for the relative root fresh weight. The correlations between the QTL-GD and heterosis were significant for certain traits and generally higher than that of the PD or GD and heterosis. The SCA effects were positively correlated with heterosis for most of the WT traits (0.51 B r B 0.80). The findings benefit understanding the inheritance mode and then achieving desirable improvement for WT in chrysanthemum.

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Section: Discussionmentioning

confidence: 99%

Combining ability, heterosis, genetic distance and their intercorrelations for waterlogging tolerance traits in chrysanthemum

Zhang

Yang

et al. 2017

Euphytica

View full text Add to dashboard Cite

show abstract

“…In practice, the sample sizes varied considerably, from 60 to 380 (Melchinger et al 2000). If the results can be repeatedly verified in multiple environments, a small population with appropriate variation should be considered effective (Cornelious et al 2005;Yesudas et al 2013). In this study, the population was small, consisting of 87 F 5 -derived RILs, and might be less effective in detecting minoreffect QTLs than a larger population.…”

Section: Comparison Of Qtls Detected In Different Studiesmentioning

confidence: 98%

“…QTL analysis was conducted in WinQTLCart version 2.5 (Wang et al 2005) for each environment and the average data over seven environments. Single marker analysis (SMA), interval mapping (IM), and composite interval mapping (CIM) were performed.…”

Section: Qtl Mapping and Statistical Analysismentioning

confidence: 99%

“…According to the permutation tests (performed 1,000 times at a = 0.05 for experiment-wise Type I error) and referring to the empirical threshold values widely used for QTL mapping (Bachlava et al 2009;Jiang et al 2007;Panthee et al 2006;Tucker et al 2010;Winter et al 2007;Yue et al 2001), a LOD value of 2.5 was set as the threshold for significance of a QTL. In few cases, the QTLs with a LOD value above 2.0 (equivalently P = 0.002 and significant at P \ 0.01 for ANOVA) that were detected in at least two environments and by at least two methods were also declared significant (Concibido et al 1997;Cornelious et al 2005;Li et al 2002;Winter et al 2007;Yesudas et al 2013). However, the QTLs that could be detected in only one environment were not declared significant.…”

Section: Qtl Mapping and Statistical Analysismentioning

confidence: 99%

“…Therefore, only the QTLs which were detected by CIM and/or IM as well as SMA in at least two individual environments and also confirmed by ANOVA are presented in this paper. To confirm or validate the results of QTL Cartographer (Wang et al 2005), QTL analysis was also performed by inclusive interval mapping (IIM) and inclusive composite interval mapping (ICIM) in the software QTL IciMapping version 3.1 (Wang et al 2011).…”

Section: Qtl Mapping and Statistical Analysismentioning

confidence: 99%

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