In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genomewide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.16S rDNA | pyrosequencing | quantitative trait loci mapping | microbiome phenotyping | population

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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.

The Collaborative Cross Consortium reports here on the development of a unique genetic resource population. The Collaborative Cross (CC) is a multiparental recombinant inbred panel derived from eight laboratory mouse inbred strains. Breeding of the CC lines was initiated at multiple international sites using mice from The Jackson Laboratory. Currently, this innovative project is breeding independent CC lines at the University of North Carolina (UNC), at Tel Aviv University (TAU), and at Geniad in Western Australia (GND). These institutions aim to make publicly available the completed CC lines and their genotypes and sequence information. We genotyped, and report here, results from 458 extant lines from UNC, TAU, and GND using a custom genotyping array with 7500 SNPs designed to be maximally informative in the CC and used a novel algorithm to infer inherited haplotypes directly from hybridization intensity patterns. We identified lines with breeding errors and cousin lines generated by splitting incipient lines into two or more cousin lines at early generations of inbreeding. We then characterized the genome architecture of 350 genetically independent CC lines. Results showed that founder haplotypes are inherited at the expected frequency, although we also consistently observed highly significant transmission ratio distortion at specific loci across all three populations. On chromosome 2, there is significant overrepresentation of WSB/EiJ alleles, and on chromosome X, there is a large deficit of CC lines with CAST/EiJ alleles. Linkage disequilibrium decays as expected and we saw no evidence of gametic disequilibrium in the CC population as a whole or in random subsets of the population. Gametic equilibrium in the CC population is in marked contrast to the gametic disequilibrium present in a large panel of classical inbred strains. Finally, we discuss access to the CC population and to the associated raw data describing the genetic structure of individual lines. Integration of rich phenotypic and genomic data over time and across a wide variety of fields will be vital to delivering on one of the key attributes of the CC, a common genetic reference platform for identifying causative variants and genetic networks determining traits in mammals.

Genetic mapping studies in the mouse and other model organisms are used to search for genes underlying complex phenotypes. Traditional genetic mapping studies that employ single-generation crosses have poor mapping resolution and limit discovery to loci that are polymorphic between the two parental strains. Multiparent outbreeding populations address these shortcomings by increasing the density of recombination events and introducing allelic variants from multiple founder strains. However, multiparent crosses present new analytical challenges and require specialized software to take full advantage of these benefits. Each animal in an outbreeding population is genetically unique and must be genotyped using a high-density marker set; regression models for mapping must accommodate multiple founder alleles, and complex breeding designs give rise to polygenic covariance among related animals that must be accounted for in mapping analysis. The Diversity Outbred (DO) mice combine the genetic diversity of eight founder strains in a multigenerational breeding design that has been maintained for >16 generations. The large population size and randomized mating ensure the long-term genetic stability of this population. We present a complete analytical pipeline for genetic mapping in DO mice, including algorithms for probabilistic reconstruction of founder haplotypes from genotyping array intensity data, and mapping methods that accommodate multiple founder haplotypes and account for relatedness among animals. Power analysis suggests that studies with as few as 200 DO mice can detect loci with large effects, but loci that account for <5% of trait variance may require a sample size of up to 1000 animals. The methods described here are implemented in the freely available R package DOQTL.

Substantial variability exists in collateral density and ischemia-induced collateral growth among species. To begin to probe the underlying mechanisms, which are unknown, we characterized two mouse strains with marked differences in both parameters. Immediately after femoral artery ligation, collateral and foot perfusion were lower in BALB/c than C57BL/6 ( P < 0.05 here and below), suggesting fewer pre-existing collaterals. This was confirmed with angiography and immunohistochemistry (∼35% fewer collaterals in the BALB/c's thigh). Recovery of hindlimb perfusion was attenuated in BALB/c, in association with 54% less collateral remodeling, reduced angiogenesis, greater ischemia, and more impaired hindlimb use. Densities of CD45+ and CD4+ leukocytes around collaterals increased similarly, but TNF-α expression was 50% lower in BALB/c, which may contribute to reduced collateral remodeling. In normal tissues, compared with C57BL/6, BALB/c exhibit an altered arterial branching pattern and, like skeletal muscle above, have 30% fewer collaterals in intestine and, remarkably, almost none in pial circulation, resulting in greatly impaired perfusion after cerebral artery occlusion. Ischemic induction of VEGF-A was attenuated in BALB/c. Analysis of a C57BL/6 × BALB/c recombinant inbred strain dataset identified a quantitative trait locus for VEGF-A mRNA abundance at or near the Vegfa locus that associates with lower expression in BALB/c. This suggests a cis-acting polymorphism in the Vegfa gene in BALB/c could contribute to reduced VEGF-A expression and, in turn, the above deficiencies in this strain. These findings suggest these strains offer a model to investigate genetic determinants of collateral formation and growth in ischemia.

The problem of identifying complex epistatic quantitative trait loci (QTL) across the entire genome continues to be a formidable challenge for geneticists. The complexity of genome-wide epistatic analysis results mainly from the number of QTL being unknown and the number of possible epistatic effects being huge. In this article, we use a composite model space approach to develop a Bayesian model selection framework for identifying epistatic QTL for complex traits in experimental crosses from two inbred lines. By placing a liberal constraint on the upper bound of the number of detectable QTL we restrict attention to models of fixed dimension, greatly simplifying calculations. Indicators specify which main and epistatic effects of putative QTL are included. We detail how to use prior knowledge to bound the number of detectable QTL and to specify prior distributions for indicators of genetic effects. We develop a computationally efficient Markov chain Monte Carlo (MCMC) algorithm using the Gibbs sampler and MetropolisHastings algorithm to explore the posterior distribution. We illustrate the proposed method by detecting new epistatic QTL for obesity in a backcross of CAST/Ei mice onto M16i. M ANY complex human diseases and traits of biotive corrections for multiple testing. Non-Bayesian model logical and/or economic importance are deterselection methods combine simultaneous search with a mined by multiple genetic and environmental influsequential procedure such as forward or stepwise selecences (Lynch and Walsh 1998). Mounting evidence tion and apply criteria such as P-values or modified Bayesuggests that interactions among genes (epistasis) play sian information criterion (BIC) to identify well-fitting an important role in the genetic control and evolumultiple-QTL models (Kao et al. 1999; Carlborg et al. tion of complex traits (Cheverud 2000; Carlborg and 2000;Reifsnyder et al. 2000; Bogdan et al. 2004). These Haley 2004). Mapping quantitative trait loci (QTL) is methods, although appealing in their simplicity and popa process of inferring the number of QTL, their genoularity, have several drawbacks, including: (1) the uncermic positions, and genetic effects given observed phenotainty about the model itself is ignored in the final intype and marker genotype data. From a statistical perference, (2) they involve a complex sequential testing spective, two key problems in QTL mapping are model strategy that includes a dynamically changing null hysearch and selection (e.g., Broman and ful and conceptually simple approach to mapping multiExtensions of this approach can allow for main and epiple QTL (Satagopan et al. 1996; Hoeschele 2001; Sen static effects at two or perhaps a few QTL at a time and and Churchill 2001). The Bayesian approach proemploy a multidimensional scan to detect QTL. Howceeds by setting up a likelihood function for the phenoever, such an approach neglects potential confoundtype and assigning prior distributions to all unknowns ing effects from additional QTL and requires prohibiin the prob...

A cattle genetic linkage map was constructed which covers more than 95 percent of the bovine genome at medium density. Seven hundred and forty six DNA polymorphisms were genotyped in cattle families which comprise 347 individuals in full sibling pedigrees. Seven hundred and three of the loci are linked to at least one other locus. All linkage groups are assigned to chromosomes, and all are orientated with regards to the centromere. There is little overall difference in the lengths of the bull and cow linkage maps although there are individual differences between maps of chromosomes. One hundred and sixty polymorphisms are in or near genes, and the resultant genome-wide comparative analyses indicate that while there is greater conservation of synteny between cattle and humans compared with mice, the conservation of gene order between cattle and humans is much less than would be expected from the conservation of synteny. This map provides a basis for high-resolution mapping of the bovine genome with physical resources such as Yeast and Bacterial Artificial Chromosomes as well as providing the underpinning for the interpolation of information from the Human Genome Project.