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The genetic structure of recombinant inbred mice: High-resolution consensus maps for complex trait analysis

Robert W Williams12*, Jing Gu1, Shuhua Qi1 and Lu Lu12

Author Affiliations

1 Center of Genomics and Bioinformatics, Center for Neuroscience

2 Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, College of Medicine, Memphis, TN 38163, USA

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Genome Biology 2001, 2:preprint0007-preprint0007.44  doi:10.1186/gb-2001-2-8-preprint0007

This was the first version of this article to be made available publicly. A peer-reviewed and modified version is now available in full at

Published: 18 July 2001



Recombinant inbred (RI) strains of mice are an important resource used to map and analyze complex traits. They have proved particularly effective in multidisciplinary genetic studies. Widespread use of RI strains has been hampered by their modest numbers and by the difficulty of combining results derived from different RI sets.


We have increased the density of typed microsatellite markers 2- to 5-fold in each of several major RI sets that share C57BL/6 as a parental strain (AXB, BXA, BXD, BXH, and CXB). A common set of 490 markers was genotyped in just over 100 RI strains. Genotypes of another ~1100 microsatellites were generated, collected, and error checked in one or more RI sets. Consensus RI maps that integrate genotypes of ~1600 microsatellite loci were assembled. The genomes of individual strains typically incorporate 45-55 recombination breakpoints. The collected RI set - termed the BXN set - contains approximately 5000 breakpoints. The distribution of recombinations approximates a Poisson distribution and distances between breakpoints average about 0.5 cM. Locations of most breakpoints have been defined with a precision of < 2 cM. Genotypes deviate from Hardy-Weinberg equilibrium in only a small number of intervals.


Consensus maps derived from RI strains conform almost precisely with theoretical expectation and are close to the length predicted by the Haldane-Waddington equation (X3.6 for a 2-3 cM interval between markers). Non-syntenic associations among different chromosomes introduce predictable distortions in QTL data sets that can be partly corrected using two-locus correlation matrices.