Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantitative trait locus analysis identifies Gabra3 as a regulator of behavioral despair in mice.

ABSTRACT: The Tail Suspension Test (TST), which measures behavioral despair, is widely used as an animal model of human depressive disorders and antidepressant efficacy. In order to identify novel genes involved in the regulation of TST performance, we crossed an inbred strain exhibiting low immobility in the TST (RIIIS/J) with two high-immobility strains (C57BL/6J and NZB/BlNJ) to create two distinct F2 hybrid populations. All F2 offspring (n = 655) were genotyped at high density with a panel of SNP markers. Whole-genome interval mapping of the F2 populations identified statistically significant quantitative trait loci (QTLs) on mouse chromosomes (MMU) 4, 6, and X. Microarray analysis of hippocampal gene expression in the three parental strains was used to identify potential candidate genes within the MMUX QTLs identified in the NZB/BlNJ x RIIIS/J cross. Expression of Gabra3, which encodes the GABA(A) receptor alpha3 subunit, was robust in the hippocampus of B6 and RIIIS mice but absent from NZB hippocampal tissue. To verify the role of Gabra3 in regulating TST behavior in vivo, mice were treated with SB-205384, a positive modulator of the alpha3 subunit. SB-205384 significantly reduced TST immobility in B6 mice without affecting general activity, but it had no effect on behavior in NZB mice. This work suggests that GABRA3 regulates a behavioral endophenotype of depression and establishes this gene as a viable new target for the study and treatment of human depression.

SUBMITTER: Miller BH

PROVIDER: S-EPMC2890984 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator.

Project description:Thousands of genetic variants have been associated with complex traits through genome-wide association studies. However, the functional variants or mechanistic consequences remain elusive. Intermediate traits such as gene expression or protein levels are good proxies of the metabolic state of an organism. Proteome analysis especially can provide new insights into the molecular mechanisms of complex traits like obesity. The role of genetic variation in determining protein level variation has not been assessed in obesity. To address this, we design a large-scale protein quantitative trait locus (pQTL) analysis based on a set of 1129 proteins from 494 obese subjects before and after a weight loss intervention. This reveals 55 BMI-associated cis-pQTLs and trans-pQTLs at baseline and 3 trans-pQTLs after the intervention. We provide evidence for distinct genetic mechanisms regulating BMI-associated proteins before and after weight loss. Finally, by functional analysis, we identify and validate FAM46A as a trans regulator for leptin.

| S-EPMC5727191 | biostudies-literature

Quantitative trait locus mapping methods for diversity outbred mice.

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

| S-EPMC4169154 | biostudies-literature

Expression quantitative trait locus analysis of chicken liver

Project description:This data originates from an expression quantitative trait locus analysis of liver in an advanced intercross of Red Jungefowl and White Leghorn chickens. The aim of the study was to map the genetic basis of growth traits and transcript abundance traits in the liver, and use the latter to search for candidate causative genes for chicken growth.

2018-01-25 | E-MTAB-5572 | biostudies-arrayexpress

Expression quantitative trait locus analysis of chicken cerebrum

Project description:This data originates from an expression quantitative trait locus analysis of cerebrum in an advanced intercross of Red Jungefowl and White Leghorn chickens. The aim of the study was to map the genetic basis of cerebrum and body mass, and idenifiy transcriptional differences within the intercross to assess any candidate genes for cerebrum and body mass.

2020-07-07 | E-MTAB-9313 | biostudies-arrayexpress

Expression quantitative trait locus analysis for translational medicine.

Project description:Expression quantitative trait locus analysis has emerged as an important component of efforts to understand how genetic polymorphisms influence disease risk and is poised to make contributions to translational medicine. Here we review how expression quantitative trait locus analysis is aiding the identification of which gene(s) within regions of association are causal for a disease or phenotypic trait; the narrowing down of the cell types or regulators involved in the etiology of disease; the characterization of drivers and modifiers of cancer; and our understanding of how different environments and cellular contexts can modify gene expression. We also introduce the concept of transcriptional risk scores as a means of refining estimates of individual liability to disease based on targeted profiling of the transcripts that are regulated by polymorphisms jointly associated with disease and gene expression.

| S-EPMC4479075 | biostudies-literature

Quantitative trait locus analysis for hemostasis and thrombosis.

Project description:Susceptibility to thrombosis varies in human populations as well as many in inbred mouse strains. The objective of this study was to characterize the genetic control of thrombotic risk on three chromosomes. Previously, utilizing a tail-bleeding/rebleeding assay as a surrogate of hemostasis and thrombosis function, three mouse chromosome substitution strains (CSS) (B6-Chr5(A/J), Chr11(A/J), Chr17(A/J)) were identified (Hmtb1, Hmtb2, Hmtb3). The tail-bleeding/rebleeding assay is widely used and distinguishes mice with genetic defects in blood clot formation or dissolution. In the present study, quantitative trait locus (QTL) analysis revealed a significant locus for rebleeding (clot stability) time (time between cessation of initial bleeding and start of the second bleeding) on chromosome 5, suggestive loci for bleeding time (time between start of bleeding and cessation of bleeding) also on chromosomes 5, and two suggestive loci for clot stability on chromosome 17 and one on chromosome 11. The three CSS and the parent A/J had elevated clot stability time. There was no interaction of genes on chromosome 11 with genes on chromosome 5 or chromosome 17. On chromosome 17, twenty-three candidate genes were identified in synteny with previously identified loci for thrombotic risk on human chromosome 18. Thus, we have identified new QTLs and candidate genes not previously known to influence thrombotic risk.

| S-EPMC3375051 | biostudies-literature

Multiethnic Meta-Analysis Identifies RAI1 as a Possible Obstructive Sleep Apnea-related Quantitative Trait Locus in Men.

Project description:Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N?=?6,737; P?=?1.7?×?10-8) but not in women (P?=?0.77). The association with NREM AHI was replicated in a physiological research study (N?=?67; P?=?0.047). This locus overlapping the RAI1 gene and encompassing genes PEMT1, SREBF1, and RASD1 was previously reported to be associated with coronary artery disease, lipid metabolism, and implicated in Potocki-Lupski syndrome and Smith-Magenis syndrome, which are characterized by abnormal sleep phenotypes. We also identified gene-by-sex interactions in suggestive association regions, suggesting that genetic variants for AHI appear to vary by sex, consistent with the clinical observations of strong sexual dimorphism.

| S-EPMC5854957 | biostudies-literature

Quantitative trait locus linkage analysis in a large Amish pedigree identifies novel candidate loci for erythrocyte traits.

Project description:We characterized a large Amish pedigree and, in 384 pedigree members, analyzed the genetic variance components with covariate screen as well as genome-wide quantitative trait locus (QTL) linkage analysis of red blood cell count (RBC), hemoglobin (HB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), platelet count (PLT), and white blood cell count (WBC) using SOLAR. Age and gender were found to be significant covariates in many CBC traits. We obtained significant heritability estimates for RBC, MCV, MCH, MCHC, RDW, PLT, and WBC. We report four candidate loci with LOD scores above 2.0: 6q25 (MCH), 9q33 (WBC), 10p12 (RDW), and 20q13 (MCV). We also report eleven candidate loci with LOD scores between 1.5 and < 2.0. Bivariate linkage analysis of MCV and MCH on chromosome 20 resulted in a higher maximum LOD score of 3.14. Linkage signals on chromosomes 4q28, 6p22, 6q25, and 20q13 are concomitant with previously reported QTL. All other linkage signals reported herein represent novel evidence of candidate QTL. Interestingly rs1800562, the most common causal variant of hereditary hemochromatosis in HFE (6p22) was associated with MCH and MCHC in this family. Linkage studies like the one presented here will allow investigators to focus the search for rare variants amidst the noise encountered in the large amounts of data generated by whole genome sequencing.

| S-EPMC3775389 | biostudies-literature

Model selection for quantitative trait locus analysis in polyploids.

Project description:Over the years, substantial gains have been made in locating regions of agricultural genomes associated with characteristics, diseases, and agroeconomic traits. These gains have relied heavily on the ability to statistically estimate the association between DNA markers and regions of a genome (quantitative trait loci or QTL) related to a particular trait. The majority of these advances have focused on diploid species, even though many important agricultural crops are, in fact, polyploid. The purpose of our work is to initiate an algorithmic approach for model selection and QTL detection in polyploid species. This approach involves the construction of all possible chromosomal configurations (models) that may result in a gamete, model reduction based on estimation of marker dosage from progeny data, and lastly model selection. While simplified for initial explanation, our approach has demonstrated itself to be extendible to many breeding schemes and less restricted settings.

| S-EPMC16651 | biostudies-literature

Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate.

Project description:Elevated serum urate levels lead to gout and are associated with hypertension, metabolic syndrome, type 2 diabetes and cardiovascular diseases. The purpose of this study was to identify evidence for genetic linkage with serum urate and to determine whether variation within positional candidate genes is associated with serum urate levels in a non-European population. Genetic linkage analysis and single nucleotide polymorphism (SNP) genotyping was performed in a large family pedigree cohort from Mauritius. We assessed associations between serum urate levels and 97 SNPs in a positional candidate gene, SLC2A9. A genome-wide scan identified a new region with evidence for linkage for serum urate at 4p15.3. SNP genotyping identified significant association between six SNP variants in SLC2A9 and serum urate levels. Allelic and gender-based effects were noted for several SNPs. Significant correlations were also observed between serum urate levels and individual components of metabolic syndrome. Our study results implicate genetic variation in SLC2A9 in influencing levels of serum urate over a broad range of values in a large Mauritian family cohort.

| S-EPMC2987471 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data