Biology subjects

Reinholdt, L. G.

Publications and source records attributed to Reinholdt, L. G..

At least 19 recordsLinked to original sources

bioRxiv2026

The Flame Retardant Triphenyl Phosphate Induces Varying Responses in Genetically Diverse Mouse Induced Pluripotent Stem Cells

Genetic variation impacts biological response to chemical and environmental exposures, contributing to differences in resistance or susceptibility. Forward genetic screens of genetically diverse cell populations can be used to identify the precise genetic variants that drive response variation. Cell lines from laboratory mouse genetic reference populations like the Diversity Outbred (DO) population are well powered for genetic mapping. Diverse stem cell panels are especially beneficial for studying early developmental effects of chemical exposures like triphenyl phosphate (TPHP), an organophosphate flame retardant linked to adverse developmental effects, including altered cell cycle in stem cells. Self-renewal and pluripotency are defining properties of stem cells during development; therefore, it is important to understand how chemicals like TPHP may alter these critical characteristics. To better understand the influence of genetic variation on TPHP exposure response, we utilized a genetically diverse panel of DO induced pluripotent stem cells (DO iPSCs). Our analyses characterize interline variation in gene expression through differential gene expression analysis and expression quantitative trait locus (eQTL) mapping. We identified genomic loci that contribute to variation in gene expression following TPHP exposure, including a regulatory hotspot on chromosome 15. Gene set enrichment highlighted several pathways affected by TPHP including lipid metabolism, steroid hormone signaling, and cell cycle. Our study shows that genetic variation modulates the effects of TPHP on gene expression and cell cycle in stem cells. Additionally, our work demonstrates that genetically diverse cell panels like the DO iPSC resource offer a tractable and scalable approach for identifying the genetic determinants of chemical toxicity.

genomics↗

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

Molecular and genetic heterogeneity in iPSCs derived from an outbred laboratory mouse population

Genetically diverse panels of human pluripotent stem cells enable genetic dissection of cellular phenotypes, but comparable induced pluripotent stem cell (iPSC) resources in model organisms remain limited. We generated a panel of iPSCs from the Diversity Outbred (DO) mouse population and established 288 genetically unique lines that retain the allele frequency distribution, heterozygosity, and low population structure of the source population. The lines exhibit consistent growth, pluripotent gene expression profiles, and capacity to form embryoid bodies. Transcriptomic profiling of the lines revealed significant variation in gene expression driven in part by genetic background. We used expression quantitative trait locus (eQTL) mapping to identify over 10,000 regulatory loci that influence gene expression variation, including multiple distal eQTL hotspots that are key gene regulatory hubs and are shared with DO embryonic stem cells (ESCs). The largest hotspot, mediated by Lifr, showed a shift in founder allele effects relative to ESCs, consistent with differences in cellular state and culture conditions. These results establish the DO iPSC panel as a genetically diverse, publicly accessible platform derived from a laboratory mouse genetic reference population, enabling integration of in vitro cellular phenotypes with in vivo traits within a closed, outbred population.

genetics↗

bioRxiv2025

A shared genetic regulator of metabolism and addiction-related behavior in mice and humans

Substance use disorders and other mental health conditions often co-occur with metabolic disorders, suggesting shared biological underpinnings1. These heightened behavioral and physiological responses may have evolved to promote survival during resource scarcity but can become maladaptive in modern environments2. The genetic mechanisms linking these traits have remained elusive. Here, we show that a variable gene enhancer in mice jointly regulates genes encoding an epigenetic factor (Eed) and a mitochondrial enzyme (Me3) thereby influencing propensity to addiction-related behaviors and mitochondrial function. We further identify variation in a corresponding enhancer in humans regulating EED and ME3 associated with substance use, psychiatric and metabolic disorders. These findings reveal a convergent genetic regulatory network linking mitochondrial biology to behavioral and metabolic risk, offering insight into how genetic variation in beneficial regulatory pathways can predispose individuals to substance use disorders and related conditions.

genetics↗

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

Cross cell-type systems genetics reveals the influence of eQTL at multiple points in the developmental trajectory of mouse neural progenitor cells

Genetic variation leads to phenotypic variability in pluripotent stem cells that presents challenges for regenerative medicine. Although recent studies have investigated the impact of genetic variation on pluripotency maintenance and differentiation capacity, less is known about how genetic variants affecting the pluripotent state influence gene regulation in later stages of development. Here, we characterized expression of more than 12,000 genes in 127 donor-matched Diversity Outbred (DO) mouse embryonic stem cell (mESC) and neural progenitor cell (mNPC) lines. Quantitative trait locus (QTL) mapping identified 2,947 expression QTL (eQTL) unique to DO mNPCs and 1,113 eQTL observed in both mNPCs and mESCs with highly concordant allele effects. We mapped three eQTL hotspots on Chromosomes (Chrs) 1, 10, and 11 that were unique to mNPCs. Target genes of the Chr 1 hotspot were overrepresented for those involved in mRNA processing, DNA repair, chromatin organization, protein degradation, and cell cycle. Mediation analysis of the Chr 1 hotspot identified Rnf152 as the best candidate mediator expressed in mNPCs, while cross-cell type mediation using mESC gene expression along with partial correlation analysis strongly implicated genetic variant(s) affecting Pign expression in the mESC state as regulating the mNPC Chr 1 eQTL hotspot. Together these findings highlight that many local eQTL confer similar effects on gene expression in multiple cell states; distant eQTL in DO mNPCs are numerous and largely unique to that cell state, with many co-localizing to mNPC-specific hotspots; and mediation analysis across cell types suggests that expression of Pign early in development (mESCs) shapes the transcriptome of the more specialized mNPC state.

genetics↗

bioRxiv2024

Anapc5 and Anapc7 as genetic modifiers of KIF18A function in fertility and mitotic progression

The kinesin family member 18A (KIF18A) is an essential regulator of microtubule dynamics and chromosome alignment during mitosis. Functional dependency on KIF18A varies by cell type and genetic context but the heritable factors that influence this dependency remain unknown. To address this, we took advantage of the variable penetrance observed in different mouse strain backgrounds to screen for loci that modulate germ cell depletion in the absence of KIF18A. We found a significant association at a Chr5 locus where anaphase promoting complex subunits 5 (Anapc5) and 7 (Anapc7) were the top candidate genes. We found that both genes were differentially expressed in a sensitive strain background when compared to resistant strain background at key timepoints in gonadal development. We also identified a novel retroviral insertion in Anapc7 that may in part explain the observed expression differences. In cell line models, we found that depletion of KIF18A induced mitotic arrest, which was partially rescued by co-depletion of ANAPC7 (APC7) and exacerbated by co-depletion of ANAPC5 (APC5). These findings suggest that differential expression and activity of Anapc5 and Anapc7 may influence sensitivity to KIF18A depletion in germ cells and CIN cells, with potential implications for optimizing antineoplastic therapies.

cell biology↗

bioRxiv2024

Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.

cancer biology↗

bioRxiv2024

Chromosome X Dosage Modulates Development of Aneuploidy in Genetically Diverse Mouse Embryonic Stem Cells

The genetic integrity of pluripotent stem cells (PSC) is critical to their applications in research and therapy, but it is compromised by frequent development of structural chromosome variants associated with malignancy. Many cell lines exhibit remarkable genetic stability, but little is known about the basis of the known variation in genomic integrity amongst different PSC isolates. Here we identify aneuploidies using RNA-seq and proteomics data from a panel of mouse embryonic stem cell (mESC) lines derived from 170 Diversity Outbred mice. We found 62 lines with detectable aneuploid subpopulations and a subset of originally XX lines that lost one Chromosome X (XO). Strikingly, a much lower proportion of XX lines were aneuploid, compared to XY or XO lines. Two single-cell RNA-seq data sets demonstrated that aneuploid XY DO mESC also show lower Chromosome X gene expression, and a prospective study confirmed that XY mESC accumulate higher aneuploid proportions in culture than isogenic XX lines. We identify potential mechanisms for this protective effect of X chromosome dosage, including our findings that the lines with two active X Chromosomes have a higher proportion of 2-cell-like cells, a state associated with maintenance of genetic integrity of mESC, and that they show differential expression of X-linked tumor suppressor genes associated with the DNA damage response. HighlightsO_LIFirst genetic analysis of predisposition to aneuploidy in pluripotent stem cell cultures C_LIO_LIChromosomal regions duplicated in aneuploid mouse embryonic stem cells are syntenic with regions overrepresented in human pluripotent stem cell lines bearing recurrent genetic abnormalities C_LIO_LIX-Chromosome dosage strongly influences susceptibility to aneuploidy in mouse embryonic stem cells and to a lesser degree in human pluripotent stem cells C_LIO_LIXX mouse embryonic stem cell lines show a higher proportion of cells in 2 cell-like state and higher expression of tumor suppressor genes associated with DNA damage response C_LI

genetics↗

bioRxiv2024

The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states

Postnatal genomic regulation significantly influences tissue and organ maturation but is under-studied relative to existing genomic catalogs of adult tissues or prenatal development in mouse. The ENCODE4 consortium generated the first comprehensive single-nucleus resource of postnatal regulatory events across a diverse set of mouse tissues. The collection spans seven postnatal time points, mirroring human development from childhood to adulthood, and encompasses five core tissues. We identified 30 cell types, further subdivided into 69 subtypes and cell states across adrenal gland, left cerebral cortex, hippocampus, heart, and gastrocnemius muscle. Our annotations cover both known and novel cell differentiation dynamics ranging from early hippocampal neurogenesis to a new sex-specific adrenal gland population during puberty. We used an ensemble Latent Dirichlet Allocation strategy with a curated vocabulary of 2,701 regulatory genes to identify regulatory "topics," each of which is a gene vector, linked to cell type differentiation, subtype specialization, and transitions between cell states. We find recurrent regulatory topics in tissue-resident macrophages, neural cell types, endothelial cells across multiple tissues, and cycling cells of the adrenal gland and heart. Cell-type-specific topics are enriched in transcription factors and microRNA host genes, while chromatin regulators dominate mitosis topics. Corresponding chromatin accessibility data reveal dynamic and sex-specific regulatory elements, with enriched motifs matching transcription factors in regulatory topics. Together, these analyses identify both tissue-specific and common regulatory programs in postnatal development across multiple tissues through the lens of the factors regulating transcription.

genomics↗

bioRxiv2024

A pluripotent stem cell platform for in vitro systems genetics studies of mouse development

The directed differentiation of pluripotent stem cells (PSCs) from panels of genetically diverse individuals is emerging as a powerful experimental system for characterizing the impact of natural genetic variation on developing cell types and tissues. Here, we establish new PSC lines and experimental approaches for modeling embryonic development in a genetically diverse, outbred mouse stock (Diversity Outbred mice). We show that a range of inbred and outbred PSC lines can be stably maintained in the primed pluripotent state (epiblast stem cells -- EpiSCs) and establish the contribution of genetic variation to phenotypic differences in gene regulation and directed differentiation. Using pooled in vitro fertilization, we generate and characterize a genetic reference panel of Diversity Outbred PSCs (n = 230). Finally, we demonstrate the feasibility of pooled culture of Diversity Outbred EpiSCs as "cell villages", which can facilitate the differentiation of large numbers of EpiSC lines for forward genetic screens. These data can complement and inform similar efforts within the stem cell biology and human genetics communities to model the impact of natural genetic variation on phenotypic variation and disease-risk.

developmental biology↗

bioRxiv2024

Identification of robust cellular programs using reproducible LDA that impact sex-specific disease progression in different genotypes of a mouse model of AD

The gene expression profiles of distinct cell types reflect complex genomic interactions among multiple simultaneous biological processes within each cell that can be altered by disease progression as well as genetic background. The identification of these active cellular programs is an open challenge in the analysis of single-cell RNA-seq data. Latent Dirichlet Allocation (LDA) is a generative method used to identify recurring patterns in counts data, commonly referred to as topics that can be used to interpret the state of each cell. However, LDAs interpretability is hindered by several key factors including the hyperparameter selection of the number of topics as well as the variability in topic definitions due to random initialization. We developed Topyfic, a Reproducible LDA (rLDA) package, to accurately infer the identity and activity of cellular programs in single-cell data, providing insights into the relative contributions of each program in individual cells. We apply Topyfic to brain single-cell and single-nucleus datasets of two 5xFAD mouse models of Alzheimers disease crossed with C57BL6/J or CAST/EiJ mice to identify distinct cell types and states in different cell types such as microglia. We find that 8-month 5xFAD/Cast F1 males show higher level of microglial activation than matching 5xFAD/BL6 F1 males, whereas female mice show similar levels of microglial activation. We show that regulatory genes such as TFs, microRNA host genes, and chromatin regulatory genes alone capture cell types and cell states. Our study highlights how topic modeling with a limited vocabulary of regulatory genes can identify gene expression programs in singlecell data in order to quantify similar and divergent cell states in distinct genotypes.

genomics↗

bioRxiv2023

Cell morphology QTL reveal gene by environment interactions in a genetically diverse cell population

Genetically heterogenous cell lines from laboratory mice are promising tools for population-based screening as they offer power for genetic mapping, and potentially, predictive value for in vivo experimentation in genetically matched individuals. To explore this further, we derived a panel of fibroblast lines from a genetic reference population of laboratory mice (the Diversity Outbred, DO). We then used high-content imaging to capture hundreds of cell morphology traits in cells exposed to the oxidative stress-inducing arsenic metabolite monomethylarsonous acid (MMAIII). We employed dose-response modeling to capture latent parameters of response and we then used these parameters to identify several hundred cell morphology quantitative trait loci (cmQTL). Response cmQTL encompass genes with established associations with cellular responses to arsenic exposure, including Abcc4 and Txnrd1, as well as novel gene candidates like Xrcc2. Moreover, baseline trait cmQTL highlight the influence of natural variation on fundamental aspects of nuclear morphology. We show that the natural variants influencing response include both coding and non-coding variation, and that cmQTL haplotypes can be used to predict response in orthogonal cell lines. Our study sheds light on the major molecular initiating events of oxidative stress that are under genetic regulation, including the NRF2-mediated antioxidant response, cellular detoxification pathways, DNA damage repair response, and cell death trajectories.

genetics↗

bioRxiv2022

Resolution of structural variation in diverse mouse genomes reveals chromatin remodeling due to transposable elements

Diverse inbred mouse strains are among the foremost models for biomedical research, yet genome characterization of many strains has been fundamentally lacking in comparison to human genomics research. In particular, the discovery and cataloging of structural variants is incomplete, limiting the discovery of potentially causative alleles for phenotypic variation across individuals. Here, we utilized long-read sequencing to resolve genome-wide structural variants (SVs, variants [≥] 50 bp) in 20 genetically distinct inbred mice. We report 413,758 site-specific SVs that affect 13% (356 Mbp) of the current mouse reference assembly, including 510 previously unannotated variants which alter coding sequences. We find that 39% of SVs are attributed to transposable element (TE) variation accounting for 75% of bases altered by SV. We then utilized this callset to investigate the impact of TE heterogeneity on mouse embryonic stem cells (mESCs), and find multiple TE classes that influence chromatin accessibility across loci. We also identify strain-specific transcription start sites originating in polymorphic TEs that modify gene expression. Our work provides the first long-read based analysis of mouse SVs and illustrates that previously unresolved TEs underlie epigenetic and transcriptome differences in mESCs.

genomics↗

bioRxiv2022

PROTEIN CODING VARIATION IN OUTBRED LABORATORY MOUSE STOCKS PROVIDES A MOLECULAR BASIS FOR DISTINCT RESEARCH APPLICATIONS

Outbred laboratory mice (Mus musculus) are readily available and have high fecundity, making them a popular choice for biomedical research, especially toxicological and pharmacological applications. Direct high throughput genome sequencing (HTS) of these widely used research animals is an important genetic quality control measure that ensures research reproducibility. HTS data have been used to confirm the common origin of outbred stocks and to molecularly define distinct outbred populations. But these data have also revealed unexpected population structure and homozygosity in some populations; genetic features that emerge when outbred stocks are not properly maintained. We used exome sequencing to discover and interrogate protein coding variation in a newly established population of Swiss-derived outbred stock (J:ARC) that is closely related to other, commonly used CD-1 outbred populations. We used these data to describe the genetic architecture of the J:ARC population including heterozygosity, minor allele frequency, LD decay, and we defined the novel, protein-coding sequence variation. These data reveal the expected genetic architecture for a properly maintained outbred stock and provide a basis for on-going genetic quality control. We also compared these data to protein coding variation found in a multiparent outbred stock, the Diversity Outbred (J:DO). We found that the more recently derived, multiparent outbred stock has significantly higher interindividual variability, greater overall genetic variation, higher heterozygosity, and fewer novel variants than the Swiss derived J:ARC stock. However, among the novel variants found in the J:DO stock, significantly more are predicted to be protein-damaging. That individuals from this population can tolerate a higher load of potentially damaging variants highlights the buffering effects of allelic diversity and the differing selective pressures in these stocks. While both outbred stocks offer significant individual heterozygosity, our data provide a molecular basis for their intended applications, where the J:DO are best suited for studies requiring maximum, population-level genetic diversity and power for mapping, while the J:ARC are best suited as a general-purpose outbred stock with robust fecundity, relatively low allelic diversity, and less potential for extreme phenotypic variability.

genetics↗

bioRxiv2022

Genetic dissection of the pluripotent proteome through multi-omics data integration

Genetic background is a major driver of phenotypic variability in pluripotent stem cells (PSCs). Most studies of variation in PSCs have relied on transcript abundance as the primary molecular readout of cell state. However, little is known about how proteins, the primary functional units in the cell, vary across genetically diverse PSCs, how protein abundance relates to variation in other cell characteristics, and how genetic background confers these effects. Here we present a comprehensive genetic study characterizing the pluripotent proteome of 190 unique mouse embryonic stem cell lines (mESCs) derived from genetically heterogeneous Diversity Outbred (DO) mice. The quantitative proteome is highly variable across DO mESCs, and we identified differentially activated pluripotency-associated pathways in the proteomics data that were not evident in transcriptome data from the same cell lines. Comparisons of protein abundance to transcript levels and chromatin accessibility show broad co-variation across molecular layers and variable correlation across samples, with some lines showing high and others low correlation between these multi-omics datasets. Integration of these three molecular data types using multi-omics factor analysis revealed shared and unique drivers of quantitative variation in pluripotency-associated pathways. QTL mapping localized the genetic drivers of this quantitative variation to a number of genomic hotspots, and demonstrated that multi-omics data integration consolidates the influence of genetic signals shared across molecular traits to increase QTL detection power and overcome the limitations inherent in mapping individual molecular features. This study reveals transcriptional and post-transcriptional mechanisms and genetic interactions that underlie quantitative variability in the pluripotent proteome, and in so doing provides a regulatory map for mouse ESCs that can provide a rational basis for future mechanistic studies, including studies of human PSCs.

genetics↗

bioRxiv2022

Imputation of 3D genome structure by genetic-epigenetic interaction modeling in mice

Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions has previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic-epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic-epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of three- dimensional chromatin structure. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/479436v3_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@14d4221org.highwire.dtl.DTLVardef@130a812org.highwire.dtl.DTLVardef@16a6069org.highwire.dtl.DTLVardef@df9d9c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2022

Reversal Learning Phenotypes are Linked with Novel Genetic Loci in Diversity Outbred Mice

Impulsive behavior and impulsivity are heritable phenotypes that are strongly associated with risk for substance use disorders in human subjects. Consequently, identifying the neurogenetic mechanisms that influence impulsivity may also reveal novel biological insights into addiction vulnerability. Past studies from our laboratory using the BXD and Collaborative Cross (CC) recombinant inbred mouse panels have revealed that behavioral indicators of impulsivity measured in a reversal learning task are heritable and are genetically correlated with aspects of intravenous cocaine self-administration. Genome wide linkage studies in the BXD panel revealed a quantitative trait locus (QTL) on chromosome 10, but the specific genes affecting this trait remain elusive. To achieve greater precision in our mapping efforts, we have turned to Diversity Outbred (DO) mice. A total of 392 DO mice (230 males, 295 females) were successfully phenotyped using the same reversal learning test utilized in our earlier studies. Our primary indicator of impulsive responding, a measure that isolates the relative difficulty mice have with reaching performance criteria under reversal conditions, revealed a genome wide significant QTL on chromosome 7 (max LOD score = 8.73, p<0.05). A measure of premature responding akin to that implemented in the 5-choice serial reaction time task yielded a suggestive QTL on chromosome 17 (max LOD score = 9.14, p<0.1). Positional candidate genes were prioritized (2900076A07Rik, Wdr73 and Zscan2) based upon expression QTL data we collected in DO and CC mice and analyses using publicly available gene expression and phenotype databases. These findings may advance understanding of the genetics that drive impulsive behavior and enhance risk for substance use disorders.

genetics↗