Biology subjects

Philip, V.

Publications and source records attributed to Philip, V..

14 recordsLinked to original sources

bioRxiv2026

Identification of Genomic Loci Associated with Cellular Rhythms in Diversity Outbred Mice

Inter-individual variation in human molecular and behavioral circadian rhythms motivates genetic dissection in model systems with human-like diversity. We quantified cellular clock phenotypes from primary skin fibroblasts of several hundred Diversity Outbred (DO) mice-each carrying a unique mosaic of eight founder genomes-by longitudinal bioluminescence recordings of a Bmal1-luciferase reporter (LumiCycle). Canonical rhythm parameters (period, phase, amplitude, damping) were extracted and exhibited broad variability (heritability {approx}13-35%), exceeding the ranges of founder strains. We performed genome-wide QTL mapping with R/qtl2 (linear mixed models with sex and experimental group covariates, kinship control, permutation-based significance, 1.5-LOD support intervals). A suggestive QTL for amplitude localized to chromosome 12 (LOD 6.9; [~]7.5-12.0 Mb), with founder effects indicating higher amplitude for C57BL/6J and lower for PWK/PhJ. Among 21 protein-coding genes in this interval, Apob (apolipoprotein B), a clock-regulated determinant of lipoprotein assembly, emerged as a strong candidate for amplitude control. A phase QTL mapped to chromosome 1 (support interval [~]1.36 Mb) with divergent founder effects (C57BL/6J, NOD/ShiLtJ, WSB/EiJ: delayed; PWK/PhJ, CAST/EiJ: advanced) and prioritized candidates including Epha4 (an Eph receptor tyrosine kinase implicated in photic entrainment) and Acsl3. Integrative analysis in GeneWeaver connected QTL gene sets to prior loci for voluntary alcohol consumption and circadian period on proximal chromosome 12, and highlighted overlaps with GWAS signals for adolescent idiopathic scoliosis and schizophrenia, suggesting shared pathways between circadian regulation, metabolism, and neurobehavioral traits. Together, these findings define reproducible genomic loci for cellular clock phenotypes in a highly recombinant population, nominate tractable candidate genes (Apob, Epha4/Acsl3) for mechanistic follow-up, and illustrate how high-diversity mouse genetics bridges cellular circadian variation with complex disease biology.

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

Innate immune system signaling and CD11b+CD11c+CD103+ cell migration to the brain underlie changes in mouse behavior after microbial colonization.

Background and AimsAccumulating evidence suggests the microbiota is a key factor in disorders of gut-brain interaction (DGBI), by affecting host immune and neural systems. However, the underlying mechanisms remain elusive due to their complexity and clinical heterogeneity of patients with DGBIs. We aimed to identify neuroimmune pathways that are critical in microbiota-gut-brain communication during de novo gut colonization. MethodsWe employed a combination of gnotobiotic and state-of-the-art microbial tools, behavioral analysis, immune and pharmacological approaches. Germ-free wild type, MyD88-/- Ticam1-/- and SCID mice were studied before and after colonization with specific pathogen-free microbiota, Altered Schaedler Flora, E. coli or S. typhimurium (permanent or transient colonizers). TLR agonists and antagonists, CCR7 antagonist or immunomodulators were used to study immune pathways. We assessed brain c-Fos, brain-derived neurotrophic factor, and dendritic and glial cells by immunofluorescence, expression of neuroimmune genes by NanoString and performed brain proteomics. ResultsBacterial monocolonization, conventionalization or administration of microbial products to germ-free mice altered mouse behavior similarly, acting through Toll-like receptor or nucleotide-binding oligomerization domain signaling. The process required CD11b+CD11c+CD103+ cell activation and migration into the brain. The change in behavior did not require the continued presence of bacteria and was associated with activation of multiple neuro-immune networks in the gut and the brain. ConclusionsChanges in neural plasticity occur rapidly upon initial gut microbial colonization and involve innate immune signaling to the brain, mediated by CD11b+CD11c+CD103+ cell migration. The results identify a new target with therapeutic potential for DGBIs developing in context of increased gut and blood-brain barrier permeability. HighlightsO_LIMicrobiota impairment is a key factor in disorders of gut-brain interaction (DGBI) C_LIO_LIMicrobial colonization induces changes in brain and behavior via innate immunity C_LIO_LIMicrobial colonization activates multiple neuro-immune networks in gut and brain C_LIO_LIBehavioral change is mediated by CD11b+CD11c+CD103+ cells migration to the brain C_LI

animal behavior and cognition↗

bioRxiv2023

mzrtsim: Raw Data Simulation for Reproducible Gas/Liquid Chromatography Mass Spectrometry Based Non-targeted Metabolomics Data Analysis

Reproducibility of data analysis is pivotal in the context of non-targeted metabolomics based on mass spectrometry coupled with chromatography. While various algorithms have been proposed for feature or peak extraction, their validation often revolves around a limited set of known compounds or standards. While data simulation is widely used in other omics studies, simulation are focused on the feature level, neglecting uncertainties inherent in the feature or peak extraction process for metabolomics mass spectrometry data. In this technique note, we introduce a R package called mzrtsim to simulate gas/liquid chromatography full scan raw data in the mzML format. Unlike simulations solely based on virtual features, our approach leverages experimental spectral data from the MassBank of North America (MoNA) and the human metabolome database (HMDB). We developed algorithms to simulate chromatographic peaks, accounting for the tailing factor. The results of our study demonstrate the potential of this tool for comparing established metabolomics software (e.g., XCMS, mzMine, and OpenMS) against a ground truth. We found that the investigated software introduced false positive peaks and/or loss compounds with less peaks. They also showed different sensitivity to tailing and leading peaks and we also found setting appropriate intensity cutoffs will not lose information for the following statistical analysis. This R package is free and available online (https://github.com/yufree/mzrtsim). TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/567024v3_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@2861forg.highwire.dtl.DTLVardef@1b36989org.highwire.dtl.DTLVardef@1d5c939org.highwire.dtl.DTLVardef@8ddce6_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Identification of Genetic and Genomic Influences on Progressive Ethanol Consumption in Diversity Outbred Mice

Genetic factors play a significant role in the risk for development of alcohol use disorder (AUD). Using 3-bottle choice intermittent access ethanol (IEA), we have employed the Diversity Outbred (DO) mouse panel as a model of alcohol use disorder in a genetically diverse population. Through use of gene expression network analysis techniques, in combination with expression quantitative trait loci (eQTL) mapping, we have completed an extensive analysis of the influence of genetic background on gene expression changes in the prefrontal cortex (PFC). This approach revealed that, in DO mice, genes whose expression was significantly disrupted by intermittent ethanol in the PFC also tended to be those whose expression correlated to intake. This finding is in contrast to previous studies of both mice and nonhuman primates. Importantly, these analyses identified genes involved in myelination in the PFC as significantly disrupted by IEA, correlated to ethanol intake, and having significant eQTLs. Genes that code for canonical components of the myelin sheath, such as Mbp, also emerged as key drivers of the gene expression response to intermittent ethanol drinking. Several regulators of myelination were also key drivers of gene expression, and had significant QTLs, indicating that genetic background may play an important role in regulation of brain myelination. These findings underscore the importance of disruption of normal myelination in the PFC in response to prolonged ethanol exposure, that genetic variation plays an important role in this response, and that this interaction between genetics and myelin disruption in the presence of ethanol may underlie previously observed behavioral changes under intermittent access ethanol drinking such as escalation of consumption.

genomics↗

bioRxiv2023

DISCOVERY AND VALIDATION OF GENES DRIVING DRUG-INTAKE AND RELATED BEHAVIORAL TRAITS IN MICE

Substance use disorders (SUDs) are heritable disorders characterized by compulsive drug use, but the biological mechanisms driving addiction remain largely unknown. Genetic correlations reveal that predisposing drug-naive phenotypes, including anxiety, depression, novelty preference, and sensation seeking, are predictive of drug-use phenotypes, implicating shared genetic mechanisms. Because of this relationship, high-throughput behavioral screening of predictive phenotypes in knockout (KO) mice allows efficient discovery of genes likely to be involved in drug use. We used this strategy in two rounds of screening in which we identified 33 drug-use candidate genes and ultimately validated the perturbation of 22 of these genes as causal drivers of substance intake. In our initial round of screening, we employed the two-bottle-choice paradigms to assess alcohol, methamphetamine, and nicotine intake. We identified 19 KO strains that were extreme responders on at least one predictive phenotype. Thirteen of the 19 gene deletions (68%) significantly affected alcohol use three methamphetamine use, and two both. In the second round of screening, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15 KO strains that were extreme responders across the predisposing drug-naive phenotypes. Eight of the 15 gene deletions (53%) significantly affected intake or preference for three alcohol, eight methamphetamine or three both (3). We observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.

genetics↗

bioRxiv2023

Gene expression genetics of the striatum of Diversity Outbred mice

Brain transcriptional variation is a heritable trait that mediates complex behaviors, including addiction. Expression quantitative trait locus (eQTL) mapping reveals genomic regions harboring genetic variants that influence transcript abundance. In this study, we profiled transcript abundance in the striatum of 386 Diversity Outbred (J:DO) mice of both sexes using RNA-Seq. All mice were characterized using a behavioral battery of widely-used exploratory and risk-taking assays prior to transcriptional profiling. We performed eQTL mapping, incorporated the results into a browser-based eQTL viewer, and deposited co-expression network members in GeneWeaver. The eQTL viewer allows researchers to query specific genes to obtain allelic effect plots, analyze SNP associations, assess gene expression correlations, and apply mediation analysis to evaluate whether the regulatory variant is acting through the expression of another gene. GeneWeaver allows multi-species comparison of gene sets using statistical and combinatorial tools. This data resource allows users to find genetic variants that regulate differentially expressed transcripts and place them in the context of other studies of striatal gene expression and function in addiction-related behavior.

genetics↗

bioRxiv2022

Collaborative partnership model to transform bioinformatics core into a highly effective research partner and multiply the impact

Many bioinformatics cores face a multitude of challenges. We recognized that the primary source of these challenges was the service-centric approach. So, we initiated the transformation of our bioinformatics core, Computational Sciences (CS), at the Jackson Laboratory (Jax) to be a science-centric collaborative research partner for our faculty and project stakeholders. We call our model as collaborative partnership model. With the effective replacement of the service model with the collaborative partnership model, CS now acts as both an effective collaborator and a co-driver of scientific research and innovation at Jax. In this paper, we describe the principles and practices we adopted to realize this transformation and present the resulting growth in the impact of CS in the research enterprise at Jax.

scientific communication and education↗

bioRxiv2022

Cell-free Tumor Methylome Analysis of Small Cell Lung Cancer Patients Identifies Subgroups with Prognostic Associations

IntroductionSmall cell lung cancer (SCLC) is a highly aggressive type of cancer with a high risk of recurrence. The SCLC methylome may yield biologic insight but is understudied due to difficulty in acquiring primary patient tissue. Here, we comprehensively profile the SCLC methylome using cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq). MethodscfDNA was extracted from plasma samples collected from 74 SCLC patients prior to initiation of first-line treatment and from 20 non-cancer smoker participants. Genomic DNA (gDNA) was also extracted from paired peripheral blood leukocytes from the 74 SCLC patients and 7 accompanying circulating-tumour-cell patient-derived xenografts (CDX). cfDNA and gDNA were used as input for cfMeDIP-seq. We developed PeRIpheral blood leukocyte MEthylation (PRIME) subtraction as an algorithm to improve tumour specificity of cell-free methylome. ResultsSCLC total plasma cfDNA methylation profiles obtained using cfMeDIP-seq are representative of CDX tumour methylation. SCLC cfDNA methylation is distinct from non-cancer plasma. Using PRIME and k-means consensus clustering, we identified two SCLC methylome clusters with prognostic associations. These clusters had methylated biological pathways related to axon guidance, neuroactive ligand-receptor interaction, pluripotency of stem cells, and were differentially methylated at long noncoding RNA, LINEs, SINEs, retrotransposons, and other repeats features. ConclusionsWe have comprehensively profiled the SCLC methylome using cfMeDIP-seq in a large patient cohort and identified methylome clusters with prognostic associations. Our work demonstrates the potential of liquid biopsies in examining SCLC biology encoded in the methylome.

cancer biology↗

bioRxiv2022

Conserved cell-type specific signature of resilience to Alzheimer's disease nominates role for excitatory cortical neurons

Alzheimers disease (AD), the leading cause of dementia, affects millions of people worldwide. With no disease-modifying medication currently available, the human toll and economic costs are rising rapidly. Under current standards, a patient is diagnosed with AD when both cognitive decline and pathology (amyloid plaques and neurofibrillary tangles) are present. Remarkably, some individuals who have AD pathology remain cognitively normal. Uncovering factors that lead to "cognitive resilience" to AD is a promising path to create new targets for therapies. However, technical challenges discovering novel human resilience factors limit testing, validation, and nomination of novel drugs for AD. In this study, we use single-nucleus transcriptional profiles of postmortem cortex from human individuals with high AD pathology who were either cognitively normal (resilient) or cognitively impaired (susceptible) at time of death, as well as mouse strains that parallel these differences in cognition with high amyloid load. Our cross-species discovery approach highlights a novel role for excitatory layer 4/5 cortical neurons in promoting cognitive resilience to AD, and nominates several resilience genes that include ATP1A1, GRIA3, KCNMA1, and STXBP1. This putative cell type has been implicated in resilience in previous studies on bulk RNA-seq tissue, but our single-nucleus and cross-species approach identifies particular resilience-associated gene signatures in these cells. These novel resilience candidate genes were tested for replication in orthogonal data sets and confirmed to be correlated with cognitive resilience. Based on these gene signatures, we identified several potential mechanisms of resilience, including regulation of synaptic plasticity, axonal and dendritic development, and neurite vesicle transport along microtubules that are potentially targetable by available therapeutics. Because our discovery of resilience-associated genes in layer 4/5 cortical neurons originates from an integrated human and mouse transcriptomic space from susceptible and resilient individuals, we are positioned to test causality and perform mechanistic, validation, and pre-clinical studies in our human-relevant AD-BXD mouse panel.

neuroscience↗

bioRxiv2022

Hypothalamic gene network dysfunction is associated with cognitive decline and body weight loss in Alzheimer's disease mice

Recent studies, both clinical and experimental, indicate that many neurodegenerative disorders including Alzheimers disease (AD) often display coexisting metabolic dysfunctions, which may exacerbate neurological symptoms. The hypothalamus is a brain region highly involved in maintaining metabolic and other homeostatic processes and is known to be involved in the etiology of AD, although the role of hypothalamic dysfunction in the onset, progression, and severity of AD is poorly understood. In this study, we demonstrate that our new model of genetic diversity in AD, the AD-BXDs, exhibits non-cognitive symptoms consistent with hypothalamic dysfunction and examined hypothalamic bulk RNA sequencing data in the AD-BXD panel to investigate how the AD transgene impacts gene expression profiles in the hypothalamus. Mostly notably, we identified strong neuroinflammatory signatures from the hypothalamus in the AD-BXDs as early as six months of age. A functionally unknown WGCNA module showed correlation to female body weight and contextual fear acquisition. Eigengene expression of microglial/macrophagic modules and their hub gene expressions were correlated to cognitive phenotypes. From these analyses, we nominated Plek and Laptm5 as new targets to attenuate neuroinflammation in AD.

neuroscience↗

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↗

bioRxiv2021

Heritable Variation in Locomotion, Reward Sensitivity, and Impulsive Action, Choice, and Waiting in a Genetically Diverse Inbred Mouse Panel

Drugs of abuse, including alcohol and stimulants like cocaine, produce effects that are subject to individual variability, and genetic variation accounts for at least a portion of those differences. Notably, research in both animal models and human subjects point towards reward sensitivity and impulsivity as being trait characteristics that predict relatively greater positive subjective responses to stimulant drugs. Here we describe use of the eight Collaborative Cross (CC) founder strains and multiple CC strains to examine the heritability of reward sensitivity and impulsivity traits, as well as genetic correlations between these measures and existing addiction-related phenotypes. Methods. Strains were all tested for activity in an open field and reward sensitivity (intake of chocolate BOOST(R)). Mice were then divided into two counterbalanced groups and underwent reversal learning (impulsive action and waiting impulsivity) or delay discounting (impulsive choice). Results. CC and founder mice demonstrate significant heritability for impulsive action, impulsive choice, waiting impulsivity, locomotor activity, and reward sensitivity, with each impulsive phenotype determined to be non-correlating, independent traits. This research was conducted within the broader, inter-laboratory effort of the Center for Systems Neurogenetics of Addiction (CSNA) to characterize CC and DO mice for multiple, cocaine abuse related traits. These data will facilitate the discovery of genetic correlations between predictive traits, which will then guide discovery of genes and genetic variants that contribute to addictive behaviors.

neuroscience↗

bioRxiv2018

Systems genetic discovery of host-microbiome interactions reveals mechanisms of microbial involvement in disease

The role of the microbiome in health and disease involves complex networks of host genetics, genomics, microbes and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in the laboratory mouse enables data-driven discovery of network components and mechanisms of host-microbial interactions underlying multiple disease phenotypes. To examine the interplay among the whole host genome, transcriptome and microbiome, we mapped quantitative trait loci and correlated the abundance of cecal mRNA, luminal microflora, physiology and behavior in incipient strains of the highly diverse Collaborative Cross mouse population. The relationships that are extracted can be tested experimentally to ascribe causality among host and microbe in behavior and physiology, providing insight into disease. Application of this strategy in the Collaborative Cross population revealed experimentally validated mechanisms of microbial involvement in models of autism, inflammatory bowel disease and sleep disorder.\n\neTOC BlurbHost genetic diversity provides a variable selection environment and physiological context for microbiota and their interaction with host physiology. Using a highly diverse mouse population Bubier et al. identified a variety of host, microbe and potentially disease interactions.\n\nHighlights* 18 significant species-specific QTL regulating microbial abundance were identified\n* Cis and trans eQTL for 1,600 cecal transcripts were mapped in the Collaborative Cross\n* Sleep phenotypes were highly correlated with the abundance of B.P. Odoribacter\n* Elimination of sleep-associated microbes restored normal sleep patterns in mice.

genetics↗