ABHD3
- Known as:
- ABHD3
- Catalog number:
- 000940A
- Product Quantity:
- 250ul
- Category:
- -
- Supplier:
- ABM
- Gene target:
- ABHD3
Related genes to: ABHD3
- Gene:
- ABHD3 NIH gene
- Name:
- abhydrolase domain containing 3
- Previous symbol:
- -
- Synonyms:
- LABH3
- Chromosome:
- 18q11.2
- Locus Type:
- gene with protein product
- Date approved:
- 2002-06-20
- Date modifiied:
- 2019-03-21
Related products to: ABHD3
Related articles to: ABHD3
- Genome-wide association studies (GWAS) have identified many quantitative trait loci (QTL) associated with complex traits, predominantly in non-coding regions, posing challenges in pinpointing the causal variants and their target genes. Three types of evidence can help identify the gene through which QTL acts: (1) proximity to the most significant GWAS variant, (2) correlation of gene expression with the trait, and (3) the gene's physiological role in the trait. However, there is still uncertainty about the success of these methods in identifying the correct genes. Here, we test the ability of these methods in a comparatively simple series of traits associated with the concentration of polar lipids in milk. We conducted single-trait GWAS for ~14 million imputed variants and 56 individual milk polar lipid (PL) phenotypes in 336 cows. A multi-trait meta-analysis of GWAS identified 10,063 significant SNPs at FDR ≤ 10% (P ≤ 7.15E-5). Transcriptome data from blood (~12.5K genes, 143 cows) and mammary tissue (~12.2K genes, 169 cows) were analyzed using the genetic score omics regression (GSOR) method. This method links observed gene expression to genetically predicted phenotypes and was used to find associations between gene expression and 56 PL phenotypes. GSOR identified 2,186 genes in blood and 1,404 in mammary tissue associated with at least one PL phenotype (FDR ≤ 1%). We partitioned the genome into non-overlapping windows of 100 Kb to test for overlap between GSOR-identified genes and GWAS signals. We found a significant overlap between these two datasets, indicating that GSOR-significant genes were more likely to be located within 100 Kb windows that include GWAS signals than those that do not (P = 0.01; odds ratio = 1.47). These windows included 70 significant genes expressed in mammary tissue and 95 in blood. Compared to all expressed genes in each tissue, these genes were enriched for lipid metabolism gene ontology (GO). That is, seven of the 70 significant mammary transcriptome genes (P < 0.01; odds ratio = 3.98) and five of the 95 significant blood genes (P < 0.10; odds ratio = 2.24) were involved in lipid metabolism GO. The candidate causal genes include DGAT1, ACSM5, SERINC5, ABHD3, CYP2U1, PIGL, ARV1, SMPD5, and NPC2, with some overlap between the two tissues. The overlap between GWAS, GSOR, and GO analyses suggests that together, these methods are more likely to identify genes mediating QTL, though their power remains limited, as reflected by modest odds ratios. Larger sample sizes would enhance the power of these analyses, but issues like linkage disequilibrium would remain. - Source: PubMed
Publication date: 2025/05/30
Ghoreishifar MohammadMacleod Iona MChamberlain Amanda JLiu ZhiqianLopdell Thomas JLittlejohn Mathew DXiang RuidongPryce Jennie EGoddard Michael E - Hepatic fibrosis may progress to liver cirrhosis and eventually cause death. Epithelial-mesenchymal transition (EMT) of hepatocytes plays critical roles in hepatic fibrosis. Exploring the mechanisms underlying EMT is crucial for a better understanding of hepatic fibrosis pathogenesis. - Source: PubMed
Publication date: 2025/03/18
Chen LiminYang HuiWang JuanZhang HaoyeFu KangkangYan YuLiu Zhenguo - Climate change has significantly increased the frequency of our exposure to heat, adversely affecting human health and industries. Heat stress is an environmental stress defined as the exposure of organisms and cells to abnormally high temperatures. To comprehensively explain the mechanisms underlying an organism's response to heat stress, it is essential to investigate and analyze genes that have been under-represented or less well-known in previous studies. In this study, we analyzed heat stress-responsive genes using a meta-analysis of numerous gene expression datasets from the public database. We obtained 322 human and 242 mouse pairs as the heat exposure and control data. The meta-analysis of these data identified 76 upregulated and 37 downregulated genes common to both humans and mice. We performed enrichment, protein-protein interaction network, and transcription factor target gene analyses for these genes. Furthermore, we conducted an integrated analysis of these genes using publicly available chromatin immunoprecipitation sequencing (ChIP-seq) data for HSF1, HSF2, and PPARGC1A (PGC-1α) as well as gene2pubmed data from the existing literature. The results identified previously overlooked genes, such as , , and , as commonly upregulated genes. Further functional analysis of these genes can contribute to coping with climate change and potentially lead to technological advancements. - Source: PubMed
Publication date: 2023/08/30
Yonezawa SoraBono Hidemasa - Inhalation of ambient PM2.5, shown to be able to cross the placenta, has been linked to adverse obstetric and postnatal metabolic health outcomes. The placenta regulates fetal growth and influences postnatal development via fetal programming. Placental gene expression may be influenced by intrauterine exposures to PM2.5. Herein, we explore whether maternal PM2.5 exposure during pregnancy alters placental gene expression related to lipid and glucose metabolism in a U.S. birth cohort, the Rhode Island Child Health Study (RICHS). Average PM2.5 exposure level was estimated linking residential addresses and satellite data across the three trimesters using spatio-temporal models. Based on Gene Ontology annotations, we curated a list of 657 lipid and glucose metabolism genes. We conducted a two-staged analysis by leveraging placental RNA-Seq data from 148 subjects to identify top dysregulated metabolic genes associated with PM2.5 (Phase I) and then validated the results in placental samples from 415 participants of the cohort using RT-qPCR (Phase II). Associations between PM2.5 and placental gene expression were explored using multivariable linear regression models in the overall population and in sex-stratified analyses. The average level of PM2.5 exposure across pregnancy was 8.0μg/m, which is below the national standard of 12μg/m. Phase I revealed that expression levels of 32 out of the curated list of 657 genes were significantly associated with PM2.5 exposure (FDR P<0.01), 28 genes showed differential expression modified by sex of the infant. Five of these genes (ABHD3, ATP11A, CLTCL1, ST6GALNAC4 and PSCA) were validated using RT-qPCR. Associations were stronger in placentas from male births compared to females, indicating a sex-dependent effect. These genes are involved in inflammation, lipid transport, cell-cell communication or cell invasion. Our results suggest that gestational PM2.5 exposure may alter placental metabolic function. However, whether it confers long-term programming effects postnatally, especially in a sex-specific matter, warrants further studies. - Source: PubMed
Publication date: 2022/03/03
Kaur KirtanLesseur CorinaDeyssenroth Maya AKloog ItaiSchwartz Joel DMarsit Carmen JChen Jia - Despite the crucial roles of lipids in metabolism, we are still at the early stages of comprehensively annotating lipid species and their genetic basis. Mass spectrometry-based discovery lipidomics offers the potential to globally survey lipids and their relative abundances in various biological samples. To discover the genetics of lipid features obtained through high-resolution liquid chromatography-tandem mass spectrometry, we analysed liver and plasma from 384 diversity outbred mice, and quantified 3,283 molecular features. These features were mapped to 5,622 lipid quantitative trait loci and compiled into a public web resource termed LipidGenie. The data are cross-referenced to the human genome and offer a bridge between genetic associations in humans and mice. Harnessing this resource, we used genome-lipid association data as an additional aid to identify a number of lipids, for example gangliosides through their association with B4galnt1, and found evidence for a group of sex-specific phosphatidylcholines through their shared locus. Finally, LipidGenie's ability to query either mass or gene-centric terms suggests acyl-chain-specific functions for proteins of the ABHD family. - Source: PubMed
Publication date: 2020/09/21
Linke VanessaOvermyer Katherine AMiller Ian JBrademan Dain RHutchins Paul DTrujillo Edna AReddy Thiru RRussell Jason DCushing Emily MSchueler Kathryn LStapleton Donald SRabaglia Mary EKeller Mark PGatti Daniel MKeele Gregory RPham DuyBroman Karl WChurchill Gary AAttie Alan DCoon Joshua J