Literature DB >> 26163767

Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations.

Sadal Hwang1, C Andy King1, Jeffery D Ray2, Perry B Cregan3, Pengyin Chen1, Thomas E Carter4, Zenglu Li5, Hussein Abdel-Haleem6, Kevin W Matson7, William Schapaugh8, Larry C Purcell9.   

Abstract

KEY MESSAGE: QTLs for delayed canopy wilting from five soybean populations were projected onto the consensus map to identify eight QTL clusters that had QTLs from at least two independent populations. Quantitative trait loci (QTLs) for canopy wilting were identified in five recombinant inbred line (RIL) populations, 93705 KS4895 × Jackson, 08705 KS4895 × Jackson, KS4895 × PI 424140, A5959 × PI 416937, and Benning × 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 Gm02, Gm05, Gm11, Gm14, Gm17, and Gm19 identified from at least two different populations, but a simulation study indicated that the QTLs on Gm14 could be false positives. A QTL on Gm08 in the 93705 KS4895 × Jackson population co-segregated with a QTL for wilting published previously in a Kefeng1 × 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 Gm08 appeared to be authentic QTLs. QTL × 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.

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Year:  2015        PMID: 26163767     DOI: 10.1007/s00122-015-2566-1

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  26 in total

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Journal:  DNA Res       Date:  2001-04-27       Impact factor: 4.458

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Authors:  Hussein Abdel-Haleem; Geung-Joo Lee; Roger H Boerma
Journal:  Theor Appl Genet       Date:  2010-12-17       Impact factor: 5.699

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Journal:  Mamm Genome       Date:  2007-03-08       Impact factor: 2.957

5.  QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations.

Authors:  Jian Yang; Chengcheng Hu; Han Hu; Rongdong Yu; Zhen Xia; Xiuzi Ye; Jun Zhu
Journal:  Bioinformatics       Date:  2008-01-17       Impact factor: 6.937

6.  QTL analysis: a simple 'marker-regression' approach.

Authors:  M J Kearsey; V Hyne
Journal:  Theor Appl Genet       Date:  1994-11       Impact factor: 5.699

7.  Maximum likelihood techniques for the mapping and analysis of quantitative trait loci with the aid of genetic markers.

Authors:  J I Weller
Journal:  Biometrics       Date:  1986-09       Impact factor: 2.571

8.  Simple sequence repeat (SSR) markers linked to E1, E3, E4, and E7 maturity genes in soybean.

Authors:  Stephen J Molnar; Satish Rai; Martin Charette; Elroy R Cober
Journal:  Genome       Date:  2003-12       Impact factor: 2.166

9.  QTL mapping of ten agronomic traits on the soybean ( Glycine max L. Merr.) genetic map and their association with EST markers.

Authors:  W-K Zhang; Y-J Wang; G-Z Luo; J-S Zhang; C-Y He; X-L Wu; J-Y Gai; S-Y Chen
Journal:  Theor Appl Genet       Date:  2004-01-22       Impact factor: 5.699

10.  An R package for SNP marker-based parent-offspring tests.

Authors:  Hussein Abdel-Haleem; Pengsheng Ji; H Roger Boerma; Zenglu Li
Journal:  Plant Methods       Date:  2013-11-19       Impact factor: 4.993

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  9 in total

1.  A Nuclear Factor Y-B Transcription Factor, GmNFYB17, Regulates Resistance to Drought Stress in Soybean.

Authors:  Maolin Sun; Yue Li; Jiqiang Zheng; Depeng Wu; Chunxia Li; Zeyang Li; Ziwei Zang; Yanzheng Zhang; Qingwei Fang; Wenbin Li; Yingpeng Han; Xue Zhao; Yongguang Li
Journal:  Int J Mol Sci       Date:  2022-06-29       Impact factor: 6.208

2.  Genome-wide association mapping of canopy wilting in diverse soybean genotypes.

Authors:  Avjinder S Kaler; Jeffery D Ray; William T Schapaugh; C Andy King; Larry C Purcell
Journal:  Theor Appl Genet       Date:  2017-07-20       Impact factor: 5.699

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4.  The importance of slow canopy wilting in drought tolerance in soybean.

Authors:  Heng Ye; Li Song; William T Schapaugh; Md Liakat Ali; Thomas R Sinclair; Mandeep K Riar; Raymond N Raymond; Yang Li; Tri Vuong; Babu Valliyodan; Antonio Pizolato Neto; Mariola Klepadlo; Qijian Song; J Grover Shannon; Pengyin Chen; Henry T Nguyen
Journal:  J Exp Bot       Date:  2020-01-07       Impact factor: 6.992

5.  Identification of quantitative trait loci associated with canopy temperature in soybean.

Authors:  Sumandeep K Bazzer; Larry C Purcell
Journal:  Sci Rep       Date:  2020-10-19       Impact factor: 4.379

6.  Phenotyping and Quantitative Trait Locus Analysis for the Limited Transpiration Trait in an Upper-Mid South Soybean Recombinant Inbred Line Population ("Jackson" × "KS4895"): High Throughput Aquaporin Inhibitor Screening.

Authors:  Sayantan Sarkar; Avat Shekoofa; Angela McClure; Jason D Gillman
Journal:  Front Plant Sci       Date:  2022-01-20       Impact factor: 5.753

7.  Genome-Wide Association Analyses Reveal Genomic Regions Controlling Canopy Wilting in Soybean.

Authors:  Clinton J Steketee; William T Schapaugh; Thomas E Carter; Zenglu Li
Journal:  G3 (Bethesda)       Date:  2020-04-09       Impact factor: 3.154

8.  In search for drought-tolerant soybean: is the slow-wilting phenotype more than just a curiosity?

Authors:  Karl Kunert; Barend J Vorster
Journal:  J Exp Bot       Date:  2020-01-07       Impact factor: 6.992

9.  Identification and Confirmation of Loci Associated With Canopy Wilting in Soybean Using Genome-Wide Association Mapping.

Authors:  Siva K Chamarthi; Avjinder S Kaler; Hussein Abdel-Haleem; Felix B Fritschi; Jason D Gillman; Jeffery D Ray; James R Smith; Arun P Dhanapal; Charles A King; Larry C Purcell
Journal:  Front Plant Sci       Date:  2021-07-14       Impact factor: 5.753

  9 in total

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