Jeremy L. Peirce

A new set of BXD recombinant inbred lines from advanced intercross populations in mice

BackgroundRecombinant inbred (RI) strains are an important resource for mapping complex traits in many species. While large RI panels are available for Arabidopsis, maize, C. elegans, and Drosophila, mouse RI panels typically consist of fewer than 30 lines. This is a severe constraint on the power and precision of mapping efforts and greatly hampers analysis of epistatic interactions.ResultsIn order to address these limitations and to provide the community with a more effective collaborative RI mapping panel we generated new BXD RI strains from two independent advanced intercrosses (AI) between C57BL/6J (B6) and DBA/2J (D2) progenitor strains. Progeny were intercrossed for 9 to 14 generations before initiating inbreeding, which is still ongoing for some strains. Since this AI base population is highly recombinant, the 46 advanced recombinant inbred (ARI) strains incorporate approximately twice as many recombinations as standard RI strains, a fraction of which are inevitably shared by descent. When combined with the existing BXD RI strains, the merged BXD strain set triples the number of previously available unique recombinations and quadruples the total number of recombinations in the BXD background.ConclusionThe combined BXD strain set is the largest mouse RI mapping panel. It is a powerful tool for collaborative analysis of quantitative traits and gene function that will be especially useful to study variation in transcriptome and proteome data sets under multiple environments. Additional strains also extend the value of the extensive phenotypic characterization of the previously available strains. A final advantage of expanding the BXD strain set is that both progenitors have been sequenced, and approximately 1.8 million SNPs have been characterized. This provides unprecedented power in screening candidate genes and can reduce the effective length of QTL intervals. It also makes it possible to reverse standard mapping strategies and to explore downstream effects of known sequence variants.

The nature and identification of quantitative trait loci: a community’s view

This white paper by eighty members of the Complex Trait Consortium presents a communitys view on the approaches and statistical analyses that are needed for the identification of genetic loci that determine quantitative traits. Quantitative trait loci (QTLs) can be identified in several ways, but is there a definitive test of whether a candidate locus actually corresponds to a specific QTL?

Genetics of the Hippocampal Transcriptome in Mouse: A Systematic Survey and Online Neurogenomics Resource

Differences in gene expression in the CNS influence behavior and disease susceptibility. To systematically explore the role of normal variation in expression on hippocampal structure and function, we generated an online microarray database for a diverse panel of strains of mice, including most common inbred strains and numerous recombinant inbred lines (www.genenetwork.org). Using this resource, coexpression networks for families of genes can be generated rapidly to test causal models related to function. The data set is optimized for quantitative trait locus (QTL) mapping and was used to identify over 5500 QTLs that modulate mRNA levels. We describe a wide variety of analyses and novel synthetic approaches that take advantage of this resource, and demonstrate how both the data and associated tools can be applied to the study of gene regulation in the hippocampus and relations to structure and function.

Genetic architecture of the mouse hippocampus: identification of gene loci with selective regional effects

We recently mapped two quantitative trait loci that have widespread effects on hippocampal architecture in mouse: Hipp1a and Hipp5a. We also noted remarkable strain differences in the relative sizes of different hippocampal regions. Estimated heritable variation for these differences was 42% in hippocampus proper, 40% in dentate gyrus, 31% in granule cell layer and 18% in pyramidal cell layer. Region size varied at least 50% from largest to smallest measurement. Here we have utilized these differences to identify loci with effects on the dentate gyrus, granule cell layer, hippocampus proper and pyramidal cell layer. Our sample consists of C57BL/6J and DBA/2J and 32 BXD recombinant inbred strains. Volumetric data were corrected for shrinkage and for differences in brain weight. We identified significant loci on chromosomes (Chr) 6, 13 and 15, and a significant interaction locus on proximal Chr 11. A suggestive distal Chr 1 locus overlaps with Hipp1a. HipV13a (Chr 13, 42–78 Mb) has an additive effect of 0.56 mm3 (12.1%) on dentate gyrus volume, while GrV6a (Chr 6, 29–65 Mb) has additive effects of 0.14 mm3 (16.0%) on the volume of the granule cell layer. HipV13a also interacts with DGVi11a, a locus on proximal Chr 11 that operates exclusively through its epistatic effect on HipV13a and has no independent main effect. HipV15a (Chr 15, 0–51 Mb) has an additive effect of 1.76 mm3 (9.0%) on the volume of the hippocampus proper. We used WebQTL, a recently described web‐based tool, to examine genetic correlation of gene expression with hippocampal volume. We identified a number of genes that map within the QTL intervals and have highly correlated expression patterns. Using WebQTLs extensive database of published BXD phenotypes, we also detected a strong and potentially biologically meaningful correlation between hippocampal volume and the acoustic startle response.

A MAJOR INFLUENCE OF SEX-SPECIFIC LOCI ON ALCOHOL PREFERENCE IN C57BL/6 AND DBA/2 INBRED MICE

Abstract. C57Bl/6 mice reproducibly prefer to ingest more 10% ethanol in a two-bottle choice paradigm than do DBA/2J mice. In this paper we report the identification of two new sex-specific alcohol preference (Alcp) loci. Melo and associates (1996) identified two loci: Alcp1, a male-specific locus on Chromosome (Chr) 2, and Alcp2, a female- and cross-specific locus on Chr 11. We have additionally identified Alcp3, a male-specific locus on Chr 3, and Alcp4, a female-specific locus on Chr 1. We have also performed a statistical analysis to exclude the possibility of undiscovered major alcohol preference loci that are not sex-specific in our backcross paradigm. Our results indicate that alcohol preference in C57BL/6 mice, as measured in our backcross, is largely controlled in a sex-specific manner.

How replicable are mRNA expression QTL

Applying quantitative trait analysis methods to genome-wide microarray-derived mRNA expression phenotypes in segregating populations is a valuable tool in the attempt to link high-level traits to their molecular causes. The massive multiple-testing issues involved in analyzing these data make the correct level of confidence to place in mRNA abundance quantitative trait loci (QTL) a difficult problem. We use a unique resource to directly test mRNA abundance QTL replicability in mice: paired recombinant inbred (RI) and F2 data sets derived from C57BL/6J (B6) and DBA/2J (D2) inbred strains and phenotyped using the same Affymetrix arrays. We have one forebrain and one striatum data set pair. We describe QTL replication at varying stringencies in these data. For instance, 78% of mRNA expression QTL (eQTL) with genome-wide adjusted p ≤ 0.0001 in RI data replicate at a genome-wide adjusted p < 0.05 or better. Replicated QTL are disproportionately putatively cis-acting, and approximately 75% have higher apparent expression levels associated with B6 genotypes, which may be partly due to probe set generation using B6 sequence. Finally, we note that while trans-acting QTL do not replicate well between data sets in general, at least one cluster of trans-acting QTL on distal Chr 1 is notably preserved between data sets.

Genome Reshuffling for Advanced Intercross Permutation (GRAIP): simulation and permutation for advanced intercross population analysis.

Background Advanced intercross lines (AIL) are segregating populations created using a multi-generation breeding protocol for fine mapping complex trait loci (QTL) in mice and other organisms. Applying QTL mapping methods for intercross and backcross populations, often followed by naïve permutation of individuals and phenotypes, does not account for the effect of AIL family structure in which final generations have been expanded and leads to inappropriately low significance thresholds. The critical problem with naïve mapping approaches in AIL populations is that the individual is not an exchangeable unit. Methodology/Principal Findings The effect of family structure has immediate implications for the optimal AIL creation (many crosses, few animals per cross, and population expansion before the final generation) and we discuss these and the utility of AIL populations for QTL fine mapping. We also describe Genome Reshuffling for Advanced Intercross Permutation, (GRAIP) a method for analyzing AIL data that accounts for family structure. GRAIP permutes a more interchangeable unit in the final generation crosses – the parental genome – and simulating regeneration of a permuted AIL population based on exchanged parental identities. GRAIP determines appropriate genome-wide significance thresholds and locus-specific P-values for AILs and other populations with similar family structures. We contrast GRAIP with naïve permutation using a large densely genotyped mouse AIL population (1333 individuals from 32 crosses). A naïve permutation using coat color as a model phenotype demonstrates high false-positive locus identification and uncertain significance levels, which are corrected using GRAIP. GRAIP also detects an established hippocampus weight locus and a new locus, Hipp9a. Conclusions and Significance GRAIP determines appropriate genome-wide significance thresholds and locus-specific P-values for AILs and other populations with similar family structures. The effect of family structure has immediate implications for the optimal AIL creation and we discuss these and the utility of AIL populations.

Using gene expression databases for classical trait QTL candidate gene discovery in the BXD recombinant inbred genetic reference population: Mouse forebrain weight

BackgroundSuccessful strategies for QTL gene identification benefit from combined experimental and bioinformatic approaches. Unique design aspects of the BXD recombinant inbred line mapping panel allow use of archived gene microarray expression data to filter likely from unlikely candidates. This prompted us to propose a simple five-filter protocol for candidate nomination. To filter more likely from less likely candidates, we required candidate genes near to the QTL to have mRNA abundance that correlated with the phenotype among the BXD lines as well as differed between the parental lines C57BL/6J and DBA/2J. We also required verification of mRNA abundance by an independent method, and finally we required either differences in protein levels or confirmed DNA sequence differences.ResultsQTL mapping of mouse forebrain weight in 34 BXD RI lines found significant association on chromosomes 1 and 11, with each C57BL/6J allele increasing weight by more than half a standard deviation. The intersection of gene lists that were within ± 10 Mb of the strongest associated location, that had forebrain mRNA abundance correlated with forebrain weight among the BXD, and that had forebrain mRNA abundance differing between C57BL/6J and DBA/2J, produced two candidates, Tnni1 (troponin 1) and Asb3 (ankyrin repeat and SOCS box-containing protein 3). Quantitative RT-PCR confirmed the direction of an increased expression in C57BL/6J genotype over the DBA/2J genotype for both genes, a difference that translated to a 2-fold difference in Asb3 protein. Although Tnni1 protein differences could not be confirmed, a 273 bp indel polymorphism was discovered 1 Kb upstream of the transcription start site.ConclusionDelivery of well supported candidate genes following a single quantitative trait locus mapping experiment is difficult. However, by combining available gene expression data with QTL mapping, we illustrated a five-filter protocol that nominated Asb3 and Tnni1 as candidates affecting increased mouse forebrain weight. We recommend our approach when (1) investigators are working with phenotypic differences between C57BL/6J and DBA/2J, and (2) gene expression data are available on http://www.genenetwork.org that relate to the phenotype of interest. Under these circumstances, measurement of the phenotype in the BXD lines will likely also deliver excellent candidate genes.

A Simple Method for Combining Genetic Mapping Data from Multiple Crosses and Experimental Designs

Background Over the past decade many linkage studies have defined chromosomal intervals containing polymorphisms that modulate a variety of traits. Many phenotypes are now associated with enough mapping data that meta-analysis could help refine locations of known QTLs and detect many novel QTLs. Methodology/Principal Findings We describe a simple approach to combining QTL mapping results for multiple studies and demonstrate its utility using two hippocampus weight loci. Using data taken from two populations, a recombinant inbred strain set and an advanced intercross population we demonstrate considerable improvements in significance and resolution for both loci. 1-LOD support intervals were improved 51% for Hipp1a and 37% for Hipp9a. We first generate locus-wise permuted P-values for association with the phenotype from multiple maps, which can be done using a permutation method appropriate to each population. These results are then assigned to defined physical positions by interpolation between markers with known physical and genetic positions. We then use Fishers combination test to combine position-by-position probabilities among experiments. Finally, we calculate genome-wide combined P-values by generating locus-specific P-values for each permuted map for each experiment. These permuted maps are then sampled with replacement and combined. The distribution of best locus-specific P-values for each combined map is the null distribution of genome-wide adjusted P-values. Conclusions/Significance Our approach is applicable to a wide variety of segregating and non-segregating mapping populations, facilitates rapid refinement of physical QTL position, is complementary to other QTL fine mapping methods, and provides an appropriate genome-wide criterion of significance for combined mapping results.

Combining gene expression QTL mapping and phenotypic spectrum analysis to uncover gene regulatory relationships

Gene expression QTL (eQTL) mapping can suggest candidate regulatory relationships between genes. Recent advances in mammalian phenotype annotation such as mammalian phenotype ontology (MPO) enable systematic analysis of the phenotypic spectrum subserved by many genes. In this study we combined eQTL mapping and phenotypic spectrum analysis to predict gene regulatory relationships. Five pairs of genes with similar phenotypic effects and potential regulatory relationships suggested by eQTL mapping were identified. Lines of evidence supporting some of the predicted regulatory relationships were obtained from biological literature. A particularly notable example is that promoter sequence analysis and real-time PCR assays support the predicted regulation of protein kinase C epsilon (Prkce) by cAMP responsive element binding protein 1 (Creb1). Our results show that the combination of gene eQTL mapping and phenotypic spectrum analysis may provide a valuable approach to uncovering gene regulatory relations underlying mammalian phenotypes.