Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean

Hwang, Sadal; King, C. Andy; Chen, Pengyin; Ray, Jeffery D.; Cregan, Perry B.; Carter, Thomas E.; Li, Zenglu; Abdel‐Haleem, Hussein; Matson, Kevin W.; Schapaugh, William T.; Purcell, Larry C.

doi:10.1007/s11032-016-0516-5

Cited by 42 publications

(37 citation statements)

References 75 publications

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“…Soya bean genotypes differ in the beginning and severity of wilting in response to drought stress (King et al., ; Sloane et al., ). Canopy wilting has a broad‐sense heritability of around 0.60 and has been mapped in multiple populations (Abdel‐Haleem et al., ; Charlson et al., ; Hwang et al., , ). The slow‐wilting trait in soya bean has been found in several genotypes including PI 416937 (King et al., ; Sadok & Sinclair, ), PI 471938 (Fletcher, Sinclair, & Allen, ; King et al., ), PI 567690 (Pathan et al., ) and PI 567731 (Pathan et al., ).…”

Section: Introductionmentioning

confidence: 99%

Aerial canopy temperature differences between fast‐ and slow‐wilting soya bean genotypes

Bai

Purcell

2018

J Agronomy Crop Science

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Drought stress limits crop growth and yield in soya bean (Glycine max [L.] Merr.), but there are relatively few tools available to assess the ability of different genotypes to tolerate drought. Aerial infrared image analysis was evaluated as a potential tool for identifying drought tolerance in soya bean. Drought effects were evaluated from late vegetative to mid‐reproductive stages of soya bean development in an experiment with ten genotypes including five slow‐ and five fast‐wilting genotypes that were from a population derived from Benning×PI416937. There were two deficit irrigation levels for 2 years and one deficit irrigation level for the third year along with a fully irrigated control level. When the canopy was completely closed, relative canopy temperature was determined using an infrared camera taken from an aerial platform 50–75 m above the experiment. As water availability decreased, the relative canopy temperature generally increased. Moreover, slow‐wilting soya bean genotypes generally had lower canopy temperature compared to fast‐wilting genotypes, and grain yield was generally positively associated with cool canopy temperatures. The results indicate that the determination of canopy temperature is a promising tool for rapid characterization of drought‐related traits in soya bean.

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Section: Introductionmentioning

confidence: 99%

Aerial canopy temperature differences between fast‐ and slow‐wilting soya bean genotypes

Bai

Purcell

2018

J Agronomy Crop Science

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“…The first application of meta‐analysis in soybean was the integration of original QTLs relating to soybean cyst nematode (SCN) resistance (Guo et al., ). Since then, several meta‐QTL analyses have been carried out in soybean on traits such as leaf traits (Shi et al., ), plant height (Sun, Luan, et al., ), 100‐seed weight (Sun, Pan, et al., ), sulphur‐containing amino acids (Qiu et al., ), delayed‐canopy‐wilting (Hwang et al., ), protein and oil content and composition (Van & McHale, ), and other related traits. These results offer a basis for gene mining and molecular breeding in soybean.…”

Section: Introductionmentioning

confidence: 99%

Meta‐analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining

et al. 2018

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As soybean seed fatty acid content is valued in food, animal feed and some industrial applications, plant breeders continually aim to improve seed fatty acid constituent value. This study analysed 163 original quantitative trait loci (QTLs) related to soybean fatty acid content from databases and references and revealed 43 consensus QTLs. Meta‐analysis using BioMercator ver.2.1 indicated that these were located across 16 linkage groups (LGs) excluding LG D1a, LG C1, LG M and LG H. Moreover, the overview method was used to optimize these QTLs based on statistical analysis. Some valid QTL regions were narrowed down to 0.5 Mb and mapped on the same LGs as the meta‐analysis result. Furthermore, the functions of all genes located in these consensus QTL intervals were predicted and eight candidate genes were identified. KEGG pathway analysis indicated that Glyma.13G127900 and Glyma.18G232000 were involved in the fatty acid synthesis metabolic (pathway ID ko00071, ko00062, ko01040). These results lay a foundation for fine mapping of QTLs related to fatty acid content and marker‐assisted breeding in soybean.

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“…Several meta-QTL analyses have been carried out in soybean and have included traits such as resistance to soybean cyst nematode [20], plant height [21], 100-seed weight [22] and delayed-canopy-wilting [23]. Contents of soybean seed protein [24] and oil [25] have also been previously studied by meta-analysis with 107 and 121 QTLs, respectively.…”

Section: Introductionmentioning

confidence: 99%

Meta-Analyses of QTLs Associated with Protein and Oil Contents and Compositions in Soybean [Glycine max (L.) Merr.] Seed

Van

McHale

2017

IJMS

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Soybean [Glycine max (L.) Merr.] is a valuable and nutritious crop in part due to the high protein meal and vegetable oil produced from its seed. Soybean producers desire cultivars with both elevated seed protein and oil concentrations as well as specific amino acid and fatty acid profiles. Numerous studies have identified quantitative trait loci (QTLs) associated with seed composition traits, but validation of these QTLs has rarely been carried out. In this study, we have collected information, including genetic location and additive effects, on each QTL for seed contents of protein and oil, as well as amino acid and fatty acid compositions from over 80 studies. Using BioMercator V. 4.2, a meta-QTL analysis was performed with genetic information comprised of 175 QTLs for protein, 205 QTLs for oil, 156 QTLs for amino acids, and 113 QTLs for fatty acids. A total of 55 meta-QTL for seed composition were detected on 6 out of 20 chromosomes. Meta-QTL possessed narrower confidence intervals than the original QTL and candidate genes were identified within each meta-QTL. These candidate genes elucidate potential natural genetic variation in genes contributing to protein and oil biosynthesis and accumulation, providing meaningful information to further soybean breeding programs.

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Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean

Cited by 42 publications

References 75 publications

Aerial canopy temperature differences between fast‐ and slow‐wilting soya bean genotypes

Aerial canopy temperature differences between fast‐ and slow‐wilting soya bean genotypes

Meta‐analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining

Meta-Analyses of QTLs Associated with Protein and Oil Contents and Compositions in Soybean [Glycine max (L.) Merr.] Seed

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