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Joint linkage QTL analyses for partial resistance to Phytophthora sojae in soybean using six nested inbred populations with heterogeneous conditions

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Abstract

Partial resistance to Phytophthora sojae in soybean is controlled by multiple quantitative trait loci (QTL). With traditional QTL mapping approaches, power to detect such QTL, frequently of small effect, can be limited by population size. Joint linkage QTL analysis of nested recombinant inbred line (RIL) populations provides improved power to detect QTL through increased population size, recombination, and allelic diversity. However, uniform development and phenotyping of multiple RIL populations can prove difficult. In this study, the effectiveness of joint linkage QTL analysis was evaluated on combinations of two to six nested RIL populations differing in inbreeding generation, phenotypic assay method, and/or marker set used in genotyping. In comparison to linkage analysis in a single population, identification of QTL by joint linkage analysis was only minimally affected by different phenotypic methods used among populations once phenotypic data were standardized. In contrast, genotyping of populations with only partially overlapping sets of markers had a marked negative effect on QTL detection by joint linkage analysis. In total, 16 genetic regions with QTL for partial resistance against P. sojae were identified, including four novel QTL on chromosomes 4, 9, 12, and 16, as well as significant genotype-by-isolate interactions. Resistance alleles from PI 427106 or PI 427105B contributed to a major QTL on chromosome 18, explaining 10–45 % of the phenotypic variance. This case study provides guidance on the application of joint linkage QTL analysis of data collected from populations with heterogeneous assay conditions and a genetic framework for partial resistance to P. sojae.

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Acknowledgments

This study was funded in part by United Soybean Board and Ohio Soybean Council through soybean producer’s check-off dollars. We would like to acknowledge Dr. Perry Cregan’s laboratory (USDA-ARS, Beltsville, MA) for the preliminary SNP genotyping of parental genotypes with 1,536 SNPs. We thank Dr. Steve St. Martin for advice on statistical analysis, and Dr. Huihui Li (Chinese Academy of Agricultural Science, Beijing, China) for helpful discussion of JICIM and provision of scripts for permutation analysis. We also thank T. Mendiola, L. Wallace, A. Bhupendra, A. Gunadi, A. Stasko, C. Phelan, C. Balk, C. Smith, D. Plewa, D. Veney, D. Wickramasinghe, and R. Schneider for technical assistance, and J. Whittier for conducting Illumina’s GoldenGate® SNP genotyping at the MCIC/OARDC.

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The authors declare that they have no conflict of interests.

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  1. Hehe Wang

    Present address: U.S. Horticultural Research Laboratory, University of Florida, 2001 South Rock Road, Fort Pierce, FL, 34945, USA

Authors and Affiliations

  1. Department of Horticulture and Crop Science, The Ohio State University, 1680 Madison Avenue, Wooster, OH, 44691, USA

    Sungwoo Lee, M. A. Rouf Mian & Clay H. Sneller

  2. Corn, Soybean and Wheat Quality Research Unit, USDA-ARS, Wooster, OH, 44691, USA

    M. A. Rouf Mian

  3. Department of Plant Pathology, The Ohio State University, 1680 Madison Avenue, Wooster, OH, 44691, USA

    Hehe Wang & Anne E. Dorrance

  4. Department of Horticulture and Crop Science, The Ohio State University, 2021 Coffey Road, Columbus, OH, 43210, USA

    Leah K. McHale

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  1. Sungwoo Lee
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Correspondence to Leah K. McHale.

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Communicated by A. E. Melchinger.

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Lee, S., Mian, M.A.R., Sneller, C.H. et al. Joint linkage QTL analyses for partial resistance to Phytophthora sojae in soybean using six nested inbred populations with heterogeneous conditions. Theor Appl Genet 127, 429–444 (2014). https://doi.org/10.1007/s00122-013-2229-z

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