Ask about this productRelated genes to: TMEM161A Blocking Peptide
- Gene:
- TMEM161A NIH gene
- Name:
- transmembrane protein 161A
- Previous symbol:
- -
- Synonyms:
- FLJ39645, FLJ20422
- Chromosome:
- 19p13.11
- Locus Type:
- gene with protein product
- Date approved:
- 2006-06-21
- Date modifiied:
- 2014-11-19
Related products to: TMEM161A Blocking Peptide
Related articles to: TMEM161A Blocking Peptide
- Bone remodeling is an extraordinarily complex process involving a variety of factors, such as genetic, metabolic, and environmental components. Although genetic factors play a particularly important role, many have not been identified. In this study, we investigated the role of transmembrane 161a (Tmem161a) in bone structure and function using wild-type (WT) and Tmem161a-depleted (Tmem161a) mice. Mice femurs were examined by histological, morphological, and bone strength analyses. Osteoblast differentiation and mineral deposition were examined in Tmem161a-overexpressed, -knockdown and -knockout MC3T3-e1 cells. In WT mice, Tmem161a was expressed in osteoblasts of femurs; however, it was depleted in Tmem161a mice. Cortical bone mineral density, thickness, and bone strength were significantly increased in Tmem161a mice femurs. In MC3T3-e1 cells, decreased expression of alkaline phosphatase (ALP) and Osterix were found in Tmem161a overexpression, and these findings were reversed in Tmem161a-knockdown or -knockout cells. Microarray and western blot analyses revealed upregulation of the P38 MAPK pathway in Tmem161a-knockout cells, which referred as stress-activated protein kinases. ALP and flow cytometry analyses revealed that Tmem161a-knockout cells were resistant to oxidative stress. In summary, Tmem161a is an important regulator of P38 MAPK signaling, and depletion of Tmem161a induces thicker and stronger bones in mice. - Source: PubMed
Publication date: 2023/09/05
Nagai TakuyaSekimoto TomohisaKurogi SyujiOhta TomomiMiyazaki ShihokoYamaguchi YoichiroTajima TakuyaChosa EtsuoImasaka MaiYoshinobu KumikoAraki KimiAraki MasatakeChoijookhuu NarantsogSato KatsuakiHishikawa YoshitakaFunamoto Taro - Osteonecrosis of the femoral head (ONFH) is a kind of disabling disease, given that the molecular mechanism of ONFH has not been elucidated, it is of significance to use bioinformatics analysis to understand the disease mechanism of ONFH and discover biomarkers. Gene set for ONFH GSE74089 was downloaded in the Gene Expression Omnibus, and "limma" package in R software was used to identify differentially expressed genes related to oxidative stress. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyze were performed for functional analysis. We constructed a protein interaction network and identified potential transcription factors and therapeutic drugs for the hub genes, and delineated the TF-hub genes network. Least absolute shrinkage and selection operator regression, support vector machine and cytoHubba were used to screen feature genes and key genes, which were validated by Receiver operating characteristic. CIBERSORT was used to explored the immune microenvironment. Subsequently, we identified the function of key genes using Gene set variation analysis and their relationship with each type of immune cell. Finally, molecular docking validated the binding association between molecules and validated genes. We detected 144 differentially expressed oxidative stress-related genes, and enrichment analysis showed that they were enriched in reactive oxygen species and AGE-RAGE signaling pathway. Protein-protein interaction and TF-hub genes network were conducted. Further exploration suggested that APOD and TMEM161A were feature genes, while TNF, NOS3 and CASP3 were key genes. Receiver operating characteristic analysis showed that APOD, CASP3, NOS3, and TNF have strong diagnostic ability. The key genes were enriched in oxidative phosphorylation. CIBERSORT analysis showed that 17 types immune cells were differentially relocated, and most of which were also closely related to key genes. In addition, genistein maybe potential therapeutic compound. In all, we identified that TNF, NOS3, and CASP3 played key roles on ONFH, and APOD, CASP3, NOS3, and TNF could serve as diagnostic biomarkers. - Source: PubMed
Chen ZhengJiang YuankangWu SuwenDang Meng - Geese are one of the most economically important waterfowl. However, the low reproductive performance and egg quality of geese hinder the development of the goose industry. The identification and application of genetic markers may improve the accuracy of beneficial trait selection. To identify the genetic markers associated with goose reproductive performance and egg quality traits, we performed a genome-wide association study (GWAS) for body weight at birth (BBW), the number of eggs at 48 weeks of age (EN48), the number of eggs at 60 weeks of age (EN60) and egg yolk color (EYC). The GWAS acquired 2.896 Tb of raw sequencing data with an average depth of 12.44× and identified 9,279,339 SNPs. The results of GWAS showed that 26 SNPs were significantly associated with BBW, EN48, EN60, and EYC. Moreover, five of these SNPs significantly associated with EN48 and EN60 were in a haplotype block on chromosome 35 from 4,512,855 to 4,541,709 bp, oriented to and another five SNPs significantly correlated to EYC were constructed in haplotype block on chromosome 5 from 21,069,009 to 21,363,580, which annotated by , , , and . Those genes were enriched in epidermal growth factor-activated receptor activity, regulation of epidermal growth factor receptor signaling pathway. The SNPs, haplotype markers, and candidate genes identified in this study can be used to improve the accuracy of marker-assisted selection for the reproductive performance and egg quality traits of geese. In addition, the candidate genes significantly associated with these traits may provide a foundation for better understanding the mechanisms underlying reproduction and egg quality in geese. - Source: PubMed
Publication date: 2021/03/12
Gao GuangliangGao DengfengZhao XianzhiXu SongsongZhang KeshanWu RuiYin ChunhuiLi JingXie YouhuiHu SiluWang Qigui - To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRβ chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli. Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer. - Source: PubMed
Chiou Shin-HengTseng DianeReuben AlexandreMallajosyula VamseeMolina Irene SConley StephanieWilhelmy JulieMcSween Alana MYang XinboNishimiya DaisukeSinha RahulNabet Barzin YWang ChunlinShrager Joseph BBerry Mark FBackhus LeahLui Natalie SWakelee Heather ANeal Joel WPadda Sukhmani KBerry Gerald JDelaidelli AlbertoSorensen Poul HSotillo ElenaTran PatrickBenson Jalen ARichards RebeccaLabanieh LouaiKlysz Dorota DLouis David MFeldman Steven ADiehn MaximilianWeissman Irving LZhang JianjunWistuba Ignacio IFutreal P AndrewHeymach John VGarcia K ChristopherMackall Crystal LDavis Mark M - Metabolic syndrome is a highly prevalent human disease with substantial genomic and environmental components. Previous studies indicate the presence of significant genetic determinants of several features of metabolic syndrome on rat chromosome 16 (RNO16) and the syntenic regions of human genome. We derived the SHR.BN16 congenic strain by introgression of a limited RNO16 region from the Brown Norway congenic strain (BN-Lx) into the genomic background of the spontaneously hypertensive rat (SHR) strain. We compared the morphometric, metabolic, and hemodynamic profiles of adult male SHR and SHR.BN16 rats. We also compared in silico the DNA sequences for the differential segment in the BN-Lx and SHR parental strains. SHR.BN16 congenic rats had significantly lower weight, decreased concentrations of total triglycerides and cholesterol, and improved glucose tolerance compared with SHR rats. The concentrations of insulin, free fatty acids, and adiponectin were comparable between the two strains. SHR.BN16 rats had significantly lower systolic (18-28 mmHg difference) and diastolic (10-15 mmHg difference) blood pressure throughout the experiment (repeated-measures ANOVA, P < 0.001). The differential segment spans approximately 22 Mb of the telomeric part of the short arm of RNO16. The in silico analyses revealed over 1200 DNA variants between the BN-Lx and SHR genomes in the SHR.BN16 differential segment, 44 of which lead to missense mutations, and only eight of which (in Asb14, Il17rd, Itih1, Syt15, Ercc6, RGD1564958, Tmem161a, and Gatad2a genes) are predicted to be damaging to the protein product. Furthermore, a number of genes within the RNO16 differential segment associated with metabolic syndrome components in human studies showed polymorphisms between SHR and BN-Lx (including Lpl, Nrg3, Pbx4, Cilp2, and Stab1). Our novel congenic rat model demonstrates that a limited genomic region on RNO16 in the SHR significantly affects many of the features of metabolic syndrome. - Source: PubMed
Publication date: 2016/03/31
Šedová LuciePravenec MichalKřenová DrahomíraKazdová LudmilaZídek VáclavKrupková MichaelaLiška FrantišekKřen VladimírŠeda Ondřej