Biology subjects

Gatti, D. M.

Publications and source records attributed to Gatti, D. M..

At least 19 recordsLinked to original sources

bioRxiv2026

A panel of Diversity Outbred mouse embryonic stem cells: enabling the functional characterization of natural genetic variation in vitro

Phenotypic variation in pluripotent stem cells arises largely from genetic variants that impact stability of the pluripotent state, response to differentiation cues, and cell fate diversification. Panels derived from genetic reference populations leverage genetic diversity to map the loci influencing these molecular and cellular traits. Here we describe the first publicly available resource for in vitro systems genetics in Mus musculus: 299 genetically diverse, highly heterozygous embryonic stem cell lines derived from Diversity Outbred mice, with minimal kinship across the panel. We characterize genomic integrity and allelic variation across the panel and describe differences in pluripotency and differentiation networks in embryoid bodies. Mapping the genetic determinants of gene expression differences in response to cadmium exposure in embryoid bodies identified 13 regulatory hotspots, the largest acting on ribosome biogenesis genes. This panel enables mapping of loci and gene-by-environment interactions that influence molecular identity in pluripotent cells and their derived cell types.

systems biology↗

bioRxiv2026

Simplifying Systems Genetics with QTLretrievR: An R Package for Molecular QTL Identification

MotivationOver the past two decades, integrating "-omics" scale molecular profiling with genetic mapping in diverse populations--termed "systems genetics"--has proven powerful for linking complex disease phenotypes to genetic variants and their regulatory effects. However, these combined genomic and genetic analyses remain computationally intensive and often inaccessible to researchers without a strong computational background, a problem compounded in studies with multiple tissues or thousands of molecular -omics phenotypes. ResultsWe developed QTLretrievR, an R package designed to simplify and streamline the identification and downstream analysis of molecular quantitative trait loci in genetically diverse populations. QTLretrievR builds on widely used R packages such as r/qtl2 for quantitative trait locus mapping and r/intermediate for mediation analysis, and incorporates substantial parallelization features to improve computational efficiency. Benchmarking demonstrates that QTLretrievR can reproduce results from previous quantitative trait locus studies while significantly reducing the time required for quantitative trait locus peak detection and downstream analyses. Additionally, QTL-retrievR includes plotting functions to visualize results of the included downstream analyses. AvailabilitySource code is available at https://github.com/deweyhannah/QTLretrievR. ContactSteven Munger, steven.munger@jax.org

genetics↗

bioRxiv2025

Dynamic fates of dietary antigen-specific T helper cells in a model of early life oral tolerance

Dietary antigens are first encountered in the gut during early life, when the immune system and microbiota are still maturing. In healthy individuals, oral tolerance develops towards dietary antigens: an active process which results in local and systemic immune unresponsiveness to antigens first encountered in the gut. Despite a wealth of research describing mechanisms contributing to oral tolerance in adult rodent models, questions remain about how the early life environment impacts oral tolerance development. We set out to characterize the fate(s) of CD4+ T cells during oral tolerance development using a robust early life mouse model, where controlled oral doses of dietary antigen are given directly to pups during the pre-weaning period. Orally administering 2mg of ovalbumin (OVA) daily during the third week of life was sufficient to confer oral tolerance to OVA in female and male C57BL/6 and BALB/c mice. Following early life oral OVA exposure, a large proportion of OVA-specific CD4+ T cells acquired a Th2 phenotype, alongside some OVA-specific Tregs. Following systemic challenges of OVA with an adjuvant, both OVA-specific Tregs and Th lineage-negative cells expressing anergy markers were detectable in pups given early life oral OVA, while OVA-specific Th2 cells were suppressed in comparison to pups who never received early life oral OVA. These data highlight the diverse fates of CD4+ T cells during early life oral tolerance development and maintenance, and we present a model to study oral tolerance during the early life period when dietary antigens are first encountered.

immunology↗

bioRxiv2025

Low-coverage whole-genome sequencing facilitates accurate and cost-effective haplotype reconstruction in complex mouse crosses

The search for the underlying genetic contributions to complex traits and diseases relies on accurate genetic data from populations of interest. Outbred populations, like the Diversity Outbred (DO), are commonly genotyped using commercial SNP arrays, such as the Giga Mouse Universal Genotyping Array (GigaMUGA). However, array genotypes are expensive to collect, subject to significant ascertainment bias, and too sparse to capture the genetic structure of highly recombined mouse crosses. We investigated the efficacy of sequencing-based genotyping by comparing genotyping results between the GigaMUGA, double-digest restriction-site associated DNA sequencing (ddRADseq), and low-coverage whole-genome sequencing (lcWGS). We aligned reads at [~]1X coverage and imputed segregating SNPs from the eight DO founder strains onto 48 DO genomes and reconstructed their haplotypes using R/qtl2. Haplotype reconstructions derived from all three methods were highly concordant. However, lcWGS more faithfully recapitulated crossover counts and identified more small (< 1 Mb) haplotype blocks at as low as 0.1X coverage. Over 90% of local expression quantitative trait loci identified in a set of 183 DO-derived embryoid bodies using the GigaMUGA were recalled by lcWGS at coverages as low as 0.1X. We recommend that lcWGS be adopted as the primary method of genotyping complex crosses, and cell-based resources derived from them because they are as accurate as array-based reconstructions, robust to ultra-low sequencing depths, may more accurately model haplotypes of the mouse genome that are difficult to resolve with dense reference data, and cost-effective.

genetics↗

bioRxiv2025

Prevalent cross-cell type QTL trans-regulatory genetic effects impacting innate lymphoid cells in the small intestine

Tissue function in homeostasis and disease arise from coordinated interactions between different cell types and can vary between individuals in a population, in part due to the impact of genetic variants. In barrier tissues such as the gut, innate lymphoid cells (ILCs) play critical roles in maintaining tissue homeostasis and immunity, but the genetic basis and associated regulatory circuitry affecting tissue ILCs remain largely unknown. Here, we systematically mapped the regulatory functions of genetic variants across 273,370 gut ILCs profiled by single cell RNA-seq from 274 diversity outbred (DO) mice. Computational analysis identified quantitative trait loci (QTL) impacting ILCs at three levels: cell subtype-specific mRNA expression (local and distal), cell subset proportions, and ILC gene expression programs (in trans), of which we experimentally validated a pivotal role for the transcription factor Rbpj in regulating ILC3s. All three classes of ILC QTL display polygenic inheritance signatures and broadly overlap with QTL affecting peripheral cytokine levels that we measured in another 261 DO mice. Strikingly, nearly half of trans-QTL affecting ILC traits did not overlap (within a 50-kb window) genes expressed in ILCs, and such loci were enriched for genes expressed by non-ILCs especially enteric neurons and intestinal glia. This suggests that such loci may act instead across cell type boundaries and allowed us to recover causal trans-cell type regulatory circuits in the tissue, including loci encoding multiple neuron-expressed peptides, epithelial-cell expressed Sox9, and phagocyte-expressed Ccl17. Finally, human orthologs of genes in QTL impacting gene expression and cell proportions are enriched for autoimmune disease risk heritability, suggesting their relevance to human disease. Our findings highlight how the impact of genetic variants may propagate to maintain tissue homeostasis and show a path to understand causality in tissue biology using quantitative genetics.

genetics↗

bioRxiv2024

Analysis of lifespan across Diversity Outbred mouse studies identifies multiple longevity-associated loci

Lifespan is an integrative phenotype whose genetic architecture is likely to highlight multiple processes with high impact on health and aging. Here, we conduct a genetic meta-analysis of longevity in Diversity Outbred (DO) mice that includes 2,444 animals from three independently conducted lifespan studies. We identify six loci that contribute significantly to lifespan independently of diet and drug treatment, one of which also influences lifespan in a sex-dependent manner, as well as an additional locus with a diet-specific effect on lifespan. Collectively, these loci explain over half of the estimated heritable variation in lifespan across these studies and provide insight into the genetic architecture of lifespan in DO mice.

genetics↗

bioRxiv2023

Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice.

Mycobacterium tuberculosis, the bacillus that causes tuberculosis (TB), infects 2 billion people across the globe, and results in 8-9 million new TB cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. We investigated the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using clinical indicators of disease, granuloma histopathological features, and immune response traits identified five new loci on mouse chromosomes 1, 2, 4, 16 and three previously identified loci on chromosomes 3 and 17. Quantitative trait loci (QTLs) on chromosomes 1, 16, and 17, associated with multiple correlated traits and had similar patterns of allele effects, suggesting these QTLs contain important genetic regulators of responses to M. tuberculosis. To narrow the list of candidate genes in QTLs, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks, generating functional scores. The scores were then used to rank candidates for each mapped trait in each locus, resulting in 11 candidates: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Importantly, all 11 candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling. Further, all candidates contain single nucleotide polymorphisms (SNPs), and some but not all SNPs were predicted to have deleterious consequences on protein functions. Multiple methods were used for validation including (i) a statistical method that showed Diversity Outbred mice carrying PWH/PhJ alleles on chromosome 17 QTL have shorter survival; (ii) quantification of S100A8 protein levels, confirming predicted allele effects; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and new functionally relevant gene candidates that may be major regulators of granuloma necrosis and acute inflammation in pulmonary TB.

genetics↗

bioRxiv2023

Into the Wild: A novel wild-derived inbred strain resource expands the genomic and phenotypic diversity of laboratory mouse models

The laboratory mouse has served as the premier animal model system for both basic and preclinical investigations for a century. However, laboratory mice capture a narrow subset of the genetic variation found in wild mouse populations. This consideration inherently restricts the scope of potential discovery in laboratory models and narrows the pool of potentially identified phenotype-associated variants and pathways. Wild mouse populations are reservoirs of predicted functional and disease-associated alleles, but the sparsity of commercially available, well-characterized wild mouse strains limits their broader adoption in biomedical research. To overcome this barrier, we have recently imported, sequenced, and phenotyped a set of 11 wild-derived inbred strains developed from wild-caught Mus musculus domesticus. Each of these "Nachman strains" immortalizes a unique wild haplotype sampled from five environmentally diverse locations across North and South America: Saratoga Springs, New York, USA; Gainesville, Florida, USA; Manaus, Brazil; Tucson, Arizona, USA; and Edmonton, Alberta, Canada. Whole genome sequence analysis reveals that each strain carries between 4.73-6.54 million single nucleotide differences relative to the mouse reference assembly, with 42.5% of variants in the Nachman strain genomes absent from classical inbred mouse strains. We phenotyped the Nachman strains on a customized pipeline to assess the scope of disease-relevant neurobehavioral, biochemical, physiological, metabolic, and morphological trait variation. The Nachman strains exhibit significant inter-strain variation in >90% of 1119 surveyed traits and expand the range of phenotypic diversity captured in classical inbred strain panels alone. Taken together, our work introduces a novel wild-derived inbred mouse strain resource that will enable new discoveries in basic and preclinical research. These strains are currently available through The Jackson Laboratory Repository under laboratory code NachJ.

genetics↗

bioRxiv2023

Perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell gene expression pathways identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice{-}{-}{-}

Humans are highly genetically diverse, and most are resistant to Mycobacterium tuberculosis. However, lung tissue from genetically resistant humans is not readily available to identify potential mechanisms of resistance. To address this, we model M. tuberculosis infection in Diversity Outbred mice. Like humans, Diversity Outbred mice also exhibit genetically determined susceptibility to M. tuberculosis infection: Progressors who succumb within 60 days of a low dose aerosol infection due to acute necrotizing granulomas, and Controllers who maintain asymptomatic infection for at least 60 days, and then develop chronic pulmonary TB with occasional necrosis and cavitation, over months to greater than 1 year. Here, we identified specific regions of granuloma-associated lymphoid tissue (GrALT) and B-cell gene expression pathways as key features of asymptomatic lung infection using cytokine, antibody, granuloma image, and gene expression datasets. Cytokines and anti-M. tuberculosis cell wall antibodies discriminated acute vs chronic pulmonary TB but not asymptomatic lung infection. To find unique features of asymptomatic lung infection, we trained a weakly supervised, deep-learning neural network on lung histology images. The neural network accurately produced an interpretable imaging biomarker: perivascular and bronchiolar lymphocytic cuffs, a type of GrALT. We expected CD4 T cell genes would be highly expressed in asymptomatic lung infection. However, the significantly different, highly expressed genes in lungs of asymptomatically infected Diversity Outbred mice corresponded to B-cell activation, proliferation, and antigen-receptor signaling, including Fcrl1, Cd79, Pax5, Cr2, and Ms4a1. Overall, our results suggest that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection.

pathology↗

bioRxiv2021

Systems genetics uncovers microbe-lipid-host connections in the murine gut

The molecular bases of how host genetic variation impact gut microbiome remain largely unknown. Here, we used a genetically diverse mouse population and systems genetics strategies to identify interactions between molecular phenotypes, including microbial functions, intestinal transcripts and cecal lipids that influence microbe-host dynamics. Quantitative trait loci (QTL) analysis identified genomic regions associated with variations in bacterial taxa, bacterial functions, including motility, sporulation and lipopolysaccharide production, and levels of bacterial- and host-derived lipids. We found overlapping QTL for the abundance of Akkermansia muciniphila and cecal levels of ornithine lipids (OL). Follow-up studies revealed that A. muciniphila is a major source of these lipids in the gut, provided evidence that OL have immunomodulatory effects and identified intestinal transcripts co-regulated with these traits. Collectively, these results suggest that OL are key players in A. muciniphila-host interactions and support the role of host genetics as a determinant of responses to gut microbes.

genetics↗

bioRxiv2021

Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population

BackgroundA strong predictor for the development of alcohol use disorders (AUDs) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool for elucidating the genetic basis of behavioral and physiological traits relevant to AUDs; but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations allow for the opportunity to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification. MethodsWe have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high density MEGAMuga and GIGAMuga arrays to obtain genotypes ranging from 77,808 - 143,259 SNPs. In addition, we performed RNA sequencing in striatum to map expression QTLs and to identify gene expression-trait correlations. ResultsWe then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exist between DNA sequence, gene expression values and ethanol-related phenotypes to prioritize our list of positional candidate genes. ConclusionsOur results can be used to identify alleles that contribute to AUDs in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions.

genetics↗

bioRxiv2020

Genotype-free individual genome reconstruction of Multiparental Population Models by RNA sequencing data

AbstractMulti-parent populations (MPPs), model organisms derived from two or more inbred founder strains, are widely used in biomedical and agricultural research. Gene expression profiling by direct RNA sequencing (RNA-Seq) is commonly applied to MPPs to investigate gene expression regulation and to identify candidate genes. In genetically diverse populations, including MPPs, quantification of gene expression is improved when the RNA-Seq reads are aligned to individualized transcriptomes that incorporate known polymorphic loci. However, the process of constructing and analyzing individual genomes can be computationally demanding and error prone. We propose a new approach, genome reconstruction by RNA-Seq (GBRS), that relies on simultaneous alignment of RNA-Seq reads to founder strain transcriptomes to reconstruct the diploid genome and quantify total and allele-specific gene expression in MPPs. We demonstrate that GBRS performs as well as methods that rely on high-density genotyping arrays. When used in conjunction with other genotyping methods, GBRS provides quality control for detecting sample mix-ups or contamination. GBRS software is freely available at https://github.com/churchill-lab/gbrs.

bioinformatics↗

bioRxiv2019

Genetic determinants of gut microbiota composition and bile acid profiles in mice

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for [~]22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL for Turicibacter sp. and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter, Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences in Slc10a2 gene expression associated with the different strains influences levels of both traits and revealed novel interactions between Turicibacter and BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions.\n\nAuthor summaryInter-individual variation in the composition of the intestinal microbiota can in part be attributed to host genetics. However, the specific genes and genetic variants underlying differences in the microbiota remain largely unknown. To address this, we profiled the fecal microbiota composition of 400 genetically distinct mice, for which genotypic data is available. We identified many loci of the mouse genome associated with changes in abundance of bacterial taxa. One of these loci is also associated with changes in the abundance of plasma bile acids--metabolites generated by the host that influence both microbiota composition and host physiology. Follow up validation experiments provide mechanistic insights linking host genetic differences, with changes in ileum gene expression, bile acid-bacteria interactions and bile acid homeostasis. Together, this work demonstrates how genetic approaches can be used to generate testable hypothesis to yield novel insight into how host genetics shape gut microbiota composition.

systems biology↗

bioRxiv2019

Genetic variation influences pluripotent ground state stability in mouse embryonic stem cells through a hierarchy of molecular phenotypes

Mouse embryonic stem cells (mESCs) cultured under controlled conditions occupy a stable ground state where pluripotency-associated transcriptional and epigenetic circuitry are highly active. However, mESCs from some genetic backgrounds exhibit metastability, where ground state pluripotency is lost in the absence of ERK1/2 and GSK3 inhibition. We dissected the genetic basis of metastability by profiling gene expression and chromatin accessibility in 185 genetically heterogeneous mESCs. We mapped thousands of loci affecting chromatin accessibility and/or transcript abundance, including eleven instances where distant QTL co-localized in clusters. For one cluster we identified Lifr transcript abundance as the causal intermediate regulating 122 distant genes enriched for roles in maintenance of pluripotency. Joint mediation analysis implicated a single enhancer variant ~10kb upstream of Lifr that alters chromatin accessibility and precipitates a cascade of molecular events affecting maintenance of pluripotency. We validated this hypothesis using reciprocal allele swaps, revealing mechanistic details underlying variability in ground state metastability in mESCs.

genomics↗

bioRxiv2019

Cleaning genotype data from Diversity Outbred mice

Data cleaning is an important first step in most statistical analyses, including efforts to map the genetic loci that contribute to variation in complex quantitative traits. Data cleaning is more difficult in multiparent populations (experimental crosses derived from more than two founder strains), as individual SNP markers have incomplete information. We describe our process for cleaning SNP microarray genotype data from Diversity Outbred (DO) mice, illustrated with genotype data from the MegaMUGA array on a set of 291 DO mice. We first consider the proportion of missing genotypes in each mouse, as an indicator of sample quality. We use microarray probe intensities for SNPs on the X and Y chromosomes to check mouse sex. We use the proportion of matching SNP genotypes in pairs of mice to detect sample duplicates. We use a hidden Markov model to calculate genotype probabilities across the genome for each mouse, which we use to estimate the number of crossovers in each mouse, and to identify potential genotyping errors. The estimated genotyping error rate, by mouse sample and by SNP marker, is a useful diagnostic. We also consider the SNP genotype frequencies by mouse and by marker, with markers grouped according to the minor allele frequency in the founder strains. For markers with high apparent error rates, a scatterplot of the allele intensities from the microarray, colored by both observed and predicted genotypes, can be revealing about the underlying cause. But the detection of low-quality samples is more important than the detection of low-quality markers.

genetics↗

bioRxiv2018

Mouse Genome-Wide Association and Systems Genetics Identifies Lhfp as a Regulator of Bone Mass

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P=3.1 x 10-12) BMD locus on Chromosome 3@52.5 Mbp that replicated in two seperate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts and its expression was regulated by local expression QTL (eQTL) in multiple tissues. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp-/- displayed increased osteogenic differentiation. Lfhp-/- mice also had elevated BMD due to increased cortical bone mass. In conclusion, we used GWAS and systems genetics in mice to identify Lhfp as a regulator of osteoblast activity and bone mass.

genetics↗

bioRxiv2018

R/qtl2: software for mapping quantitative trait loci with high dimensional data and multi-parent populations

R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely-used R/qtl software package to include multi-parent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2 comes with a test framework and is free and open source software written in the R and C++ programming languages.

genetics↗

bioRxiv2018

Genetic mapping in Diversity Outbred mice identifies a Trpa1 variant influencing late phase formalin response

Identification of genetic variants that influence susceptibility to chronic pain is key to identifying molecular mechanisms and targets for effective and safe therapeutic alternatives to opioids. To identify genes and variants associated with chronic pain, we measured late phase response to formalin injection in 275 male and female Diversity Outbred (DO) mice genotyped for over 70 thousand SNPs. One quantitative trait locus (QTL) reached genome-wide significance on chromosome 1 with a support interval of 3.1 Mb. This locus, Nociq4 (nociceptive sensitivity inflammatory QTL 4; MGI:5661503), harbors the well-known pain gene Trpa1 (transient receptor potential cation channel, subfamily A, member 1). Trpa1 is a cation channel known to play an important role in acute and chronic pain in both humans and mice. Analysis of DO founder strain allele effects revealed a significant effect of the CAST/EiJ allele at Trpa1, with CAST/EiJ carrier mice showing an early, but not late, response to formalin relative to carriers of the seven other inbred founder alleles (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ). We characterized possible functional consequences of sequence variants in Trpa1 by assessing channel conductance, Trpa1/Trpv1 interactions, and isoform expression. The phenotypic differences observed in CAST/EiJ relative to C57BL/6J carriers were best explained by Trpa1 isoform expression differences, implicating a splice junction variant as the causal functional variant. This study demonstrates the utility of advanced, high-precision genetic mapping populations in resolving specific molecular mechanisms of variation in pain sensitivity.

bioinformatics↗