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Analyzing complex traits with congenic strains

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Abstract

Congenic strains continue to be a fundamental resource for dissecting the genetic basis of complex traits. Traditionally, genetic variants (QTLs) that account for phenotypic variation in a panel of congenic strains are sought first by comparing phenotypes for each strain to the host (reference) strain, and then by examining the results to identify a common chromosome segment that provides the best match between genotype and phenotype across the panel. However, this “common-segment” method has significant limitations, including the subjective nature of the genetic model and an inability to deal formally with strain phenotypes that do not fit the model. We propose an alternative that we call “sequential” analysis and that is based on a unique principle of QTL analysis where each strain, corresponding to a single genotype, is tested individually for QTL effects rather than testing the congenic panel collectively for common effects across heterogeneous backgrounds. A minimum spanning tree, based on principles of graph theory, is used to determine the optimal sequence of strain comparisons. For two traits in two panels of congenic strains in mice, we compared results for the sequential method with the common-segment method as well as with two standard methods of QTL analysis, namely, interval mapping and multiple linear regression. The general utility of the sequential method was demonstrated with analysis of five additional traits in congenic panels from mice and rats. Sequential analysis rigorously resolved phenotypic heterogeneity among strains in the congenic panels and found QTLs that other methods failed to detect.

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Acknowledgments

The authors thank Richard J. Roman, Andrew S. Greene, Mary L. Kaldunski, and Jozef Lazar for their contributions to the rat studies. This work was supported in part by NIH grants CA75056, CA116867, and RR12305 to JHN, grants HL54998 and HL82798 to AJC and HJJ, and grant HD048960 to MRP. DSS was supported by a fellowship from the Canadian Diabetes Association.

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Author notes

  1. David S. Sinasac

    Present address: Biochemical Genetics Laboratory, Alberta Children’s Hospital, Calgary, AB, T3B 6A8, Canada

  2. Mark R. Palmert

    Present address: Division of Endocrinology, The Hospital for Sick Children and the University of Toronto, Toronto, ON, M5G 1X8, Canada

Authors and Affiliations

  1. Department of Genetics, Case Western Reserve University School of Medicine, 10900 Euclid Avenue, Cleveland, OH, 44106, USA

    Haifeng Shao, David S. Sinasac, Lindsay C. Burrage & Joseph H. Nadeau

  2. Department of Pediatrics, Rainbow Babies and Children’s Hospital and Case Western Reserve University School of Medicine, Cleveland, OH, USA

    Craig A. Hodges, Pamela J. Supelak & Mark R. Palmert

  3. Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA

    Carol Moreno, Allen W. Cowley Jr. & Howard J. Jacob

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  1. Haifeng Shao
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Correspondence to Haifeng Shao or Joseph H. Nadeau.

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Shao, H., Sinasac, D.S., Burrage, L.C. et al. Analyzing complex traits with congenic strains. Mamm Genome 21, 276–286 (2010). https://doi.org/10.1007/s00335-010-9267-5

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