Genetic analysis of complex traits in the emerging Collaborative Cross

David L. Aylor, William Valdar, Wendy Foulds-Mathes, Ryan J. Buus, Ricardo A. Verdugo, Ralph S. Baric, Martin T. Ferris, Jeff A. Frelinger, Mark Heise, Matt B. Frieman, Lisa E. Gralinski, Timothy A. Bell, John D. Didion, Kunjie Hua, Derrick L. Nehrenberg, Christine L. Powell, Jill Steigerwalt, Yuying Xie, Samir N.P. Kelada, Francis S. CollinsIvana V. Yang, David A. Schwartz, Lisa A. Branstetter, Elissa J. Chesler, Darla R. Miller, Jason Spence, Eric Yi Liu, Leonard McMillan, Abhishek Sarkar, Jeremy Wang, Wei Wang, Qi Zhang, Karl W. Broman, Ron Korstanje, Caroline Durrant, Richard Mott, Fuad A. Iraqi, Daniel Pomp*, David Threadgill, Fernando Pardo Manuel De Villena, Gary A. Churchill

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The Collaborative Cross (CC) is a mouse recombinant inbred strain panel that is being developed as a resource for mammalian systems genetics. Here we describe an experiment that uses partially inbred CC lines to evaluate the genetic properties and utility of this emerging resource. Genome-wide analysis of the incipient strains reveals high genetic diversity, balanced allele frequencies, and dense, evenly distributed recombination sites - all ideal qualities for a systems genetics resource. We map discrete, complex, and biomolecular traits and contrast two quantitative trait locus (QTL) mapping approaches. Analysis based on inferred haplotypes improves power, reduces false discovery, and provides information to identify and prioritize candidate genes that is unique to multifounder crosses like the CC. The number of expression QTLs discovered here exceeds all previous efforts at eQTL mapping in mice, and we map local eQTL at 1-Mb resolution. We demonstrate that the genetic diversity of the CC, which derives from random mixing of eight founder strains, results in high phenotypic diversity and enhances our ability to map causative loci underlying complex disease-related traits.

Original languageEnglish
Pages (from-to)1213-1222
Number of pages10
JournalGenome Research
Issue number8
StatePublished - Aug 2011


FundersFunder number
National Institute of General Medical SciencesR01GM070683


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