Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identification of a recombinogenic major histocompatibility complex Q gene with diverse alleles.

ABSTRACT: Structural diversity enables class Ia molecules to present a diverse repertoire of peptides to the T cell receptor. This diversity is thought to be generated by recombinations between class I genes. We have found that two class Ib Q2 alleles exhibit extremely high sequence diversity, even higher than class Ia alleles. Clustered nucleotide differences between Q2b and Q2k suggest that this sequence diversity was generated by microrecombinations between Q2 genes and other class I genes. The relatively high expression of Q2b in the thymus may be significant and perhaps suggests a novel role for a Q2b product in the education and selection of the T cell repertoire.

SUBMITTER: Cullen MK

PROVIDER: S-EPMC2191030 | biostudies-other | 1993 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Publications

Identification of a recombinogenic major histocompatibility complex Q gene with diverse alleles.

Cullen M K MK Lapierre L A LA Kesari K V KV Geliebter J J

The Journal of experimental medicine 19930601 6

Structural diversity enables class Ia molecules to present a diverse repertoire of peptides to the T cell receptor. This diversity is thought to be generated by recombinations between class I genes. We have found that two class Ib Q2 alleles exhibit extremely high sequence diversity, even higher than class Ia alleles. Clustered nucleotide differences between Q2b and Q2k suggest that this sequence diversity was generated by microrecombinations between Q2 genes and other class I genes. The relativ ...[more]

PMID: 8496692

Similar Datasets

Major histocompatibility complex alleles associated with parasite susceptibility in wild giant pandas.

Project description:Major histocompatibility complex (MHC) polymorphism is thought to be driven by antagonistic coevolution between pathogens and hosts, mediated through either overdominance or frequency-dependent selection. However, investigations under natural conditions are still rare for endangered mammals which often exhibit depleted variation, and the mechanism of selection underlying the maintenance of characteristics remains a considerable debate. In this study, 87 wild giant pandas were used to investigate MHC variation associated with parasite load. With the knowledge of the MHC profile provided by the genomic data of the giant panda, seven DRB1, seven DQA1 and eight DQA2 alleles were identified at each single locus. Positive selection evidenced by a significantly higher number of non-synonymous substitutions per non-synonymous codon site relative to synonymous substitutions per synonymous codon site could only be detected at the DRB1 locus, which leads to the speculation that DRB1 may have a more important role in dealing with parasite infection for pandas. Coprological analyses revealed that 55.17% of individuals exhibited infection with 1-2 helminthes and 95.3% of infected pandas carried Baylisascaris shroederi. Using a generalized linear model, we found that Aime-DRB1*10 was significantly associated with parasite infection, but no resistant alleles could be detected. MHC heterozygosity of the pandas was found to be uncorrelated with the infection status or the infection intensity. These results suggested that the possible selection mechanisms in extant wild pandas may be frequency dependent rather than being determined by overdominance selection. Our findings could guide the candidate selection for the ongoing reintroduction or translocation of pandas.

| S-EPMC4815596 | biostudies-literature

Using a novel structure/function approach to select diverse swine major histocompatibility complex 1 alleles to predict epitopes for vaccine development.

Project description:MotivationSwine leukocyte antigens (SLAs) (i.e. swine major histocompatibility complex proteins) conduct a fundamental role in swine immunity. To generate a protective vaccine across an outbred species, such as pigs, it is critical that epitopes that bind to diverse SLA alleles are used in the vaccine development process. We introduced a new strategy for epitope prediction.ResultsWe employed molecular dynamics simulation to identify key amino acids for interactions with epitopes. We developed an algorithm wherein each SLA-1 is compared to a crystalized reference allele with unique weighting for non-conserved amino acids based on R group and position. We then performed homology modeling and electrostatic contact mapping to visualize how relatively small changes in sequences impacted the charge distribution in the binding site. We selected eight diverse SLA-1 alleles and performed homology modeling followed, by protein-peptide docking and binding affinity analyses, to identify porcine reproductive and respiratory syndrome virus matrix protein epitopes that bind with high affinity to these alleles. We also performed docking analysis on the epitopes identified as strong binders using NetMHCpan 4.1. Epitopes predicted to bind to our eight SLA-1 alleles had equivalent or higher energetic interactions than those predicted to bind to the NetMHCpan 4.1 allele repertoire. This approach of selecting diverse SLA-1 alleles, followed by homology modeling, and docking simulations, can be used as a novel strategy for epitope prediction that complements other available tools and is especially useful when available tools do not offer a prediction for SLAs/major histocompatibility complex.Availability and implementationThe data underlying this article are available in the online Supplementary Material.

| S-EPMC10551226 | biostudies-literature

Correlation in chicken between the marker LEI0258 alleles and Major Histocompatibility Complex sequences.

Project description:BACKGROUND:The LEI0258 marker is located within the B region of the chicken Major Histocompatibility Complex (MHC), and is surprisingly well associated with serology. Therefore, the correlation between the LEI0258 alleles and the MHC class I and the class II alleles at the level of sequences is worth investigating in chickens. Here we describe to which extent the LEI0258 alleles are associated with alleles of classical class I genes and non-classical class II genes, in reference animals as well as local breeds with unknown MHC haplotypes. METHODS:For the class I region, in an exploratory project, we studied 10 animals from 3 breeds: Rhode Island Red, White Leghorn and Fayoumi chickens, by cloning and sequencing B-F1 and B-F2 cDNA from exon 1 to 3'UTR. For the class II region, we reconstructed haplotypes of the 8.8 kb genomic region encompassing three non-classical class II genes: B-DMA, B-DMB1 and B-DMB2, for 146 animals from more than 50 breeds including wild species of jungle fowls. RESULTS:Overall we found that the LEI0258 marker genotypes gave good indications of the MHC haplotypes, and a very good predictions (>0.95) of the heterozygosity of an animal at the MHC locus. CONCLUSIONS:Our results show that the LEI0258 alleles are strongly associated with haplotypes of classical class I genes and non-classical class II genes, unravelling the reasons why this marker is becoming the reference marker for MHC genotyping in chickens.

| S-EPMC3108224 | biostudies-literature

Evolution of major histocompatibility complex gene copy number.

Project description:MHC genes, which code for proteins responsible for presenting pathogen-derived antigens to the host immune system, show remarkable copy-number variation both between and within species. However, the evolutionary forces driving this variation are poorly understood. Here, we use computer simulations to investigate whether evolution of the number of MHC variants in the genome can be shaped by the number of pathogen species the host population encounters (pathogen richness). Our model assumed that while increasing a range of pathogens recognised, expressing additional MHC variants also incurs costs such as an increased risk of autoimmunity. We found that pathogen richness selected for high MHC copy number only when the costs were low. Furthermore, the shape of the association was modified by the rate of pathogen evolution, with faster pathogen mutation rates selecting for increased host MHC copy number, but only when pathogen richness was low to moderate. Thus, taking into account factors other than pathogen richness may help explain wide variation between vertebrate species in the number of MHC genes. Within population, variation in the number of unique MHC variants carried by individuals (INV) was observed under most parameter combinations, except at low pathogen richness. This variance gave rise to positive correlations between INV and host immunocompetence (proportion of pathogens recognised). However, within-population variation in host immunocompetence declined with pathogen richness. Thus, counterintuitively, pathogens can contribute more to genetic variance for host fitness in species exposed to fewer pathogen species, with consequences to predictions from "Hamilton-Zuk" theory of sexual selection.

| S-EPMC6541284 | biostudies-literature

Identification of equine major histocompatibility complex haplotypes using polymorphic microsatellites.

Project description:A system for identifying equine major histocompatibility complex (MHC) haplotypes was developed based on five polymorphic microsatellites located within the MHC region on ECA 20. Molecular signatures for 50 microsatellite haplotypes were recognized from typing 353 horses. Of these, 23 microsatellite haplotypes were associated with 12 established equine leucocyte antigen (ELA) haplotypes in Thoroughbreds and Standardbreds. Five ELA serotypes were associated with multiple microsatellite subhaplotypes, expanding the estimates of diversity in the equine MHC. The strong correlations between serological and microsatellite typing demonstrated a linkage to known MHC class I protein polymorphisms and validated this assay as a useful supplement to ELA serotyping, and in some applications, a feasible alternative method for MHC genotyping in horse families and in population studies.

| S-EPMC3289534 | biostudies-literature

Major histocompatibility complex complement (MHC) Bf alleles show trans species evolution between man and chimpanzee.

Project description:HLA and disease studies by using single allele statistics have been fruitless during the last 40 years for explaining association pathogenesis of the associated diseases.Other approaches are necessary to untangle this puzzle. We aim to revisit complement alleleism in humans and primates for both studying MHC and disease association to complotypes and extended MHC haplotypes in order to also explain the positive directional selection of maintaining immune response genes (complement, MHC adaptive and MHC non-specific genes) that keeps these three type of genes together in a short chromosome stretch (MHC) for million years. These genes may be linked to conjointly avoid microbes attack and autoimmunity. In the present paper, it is obtained a new Bf chimpanzee allele, provisionaly named Patr-Bf*A:01,that differs from other Bf alleles by having CTG at eleventh codon of exon 2 in order to start the newly suggested methodology and explain functional and evolutionary MHC obscure aspects. Exons 1 to 6 of Ba fragment of Bf gene were obtained from chimpanzee. This new chimpanzee Factor B allele (Patr-Bf*A:01) is to be identical to a infrequent human Bf allele (SNP rs641153); it stresses the strong evolutive pressure upon certain alleles that are trans specific. It also may apply to MHC extended haplotipes which may conjointly act to start an adequate immune response. It is the first time that a complement MHC class III allele is described to undergo trans species evolution,in contrast to class I and class II alleles which had already been reported . Allelism of complement factors are again proposed for studying MHC complement genes, complotypes, and extended MHC haplotypes which may be more informative that single MHC marker studies.

| S-EPMC10550962 | biostudies-literature

major histocompatibility complex class II

Project description:amphibian MHC IIB1 Raw sequence reads

| PRJNA862637 | ENA

Major Histocompatibility Complex Class I-Related Chain A Alleles and Histology of Nonalcoholic Fatty Liver Disease.

Project description:Major histocompatibility complex class I-related chain A (MICA) is a highly polymorphic gene that modulates immune surveillance by binding to its receptor on natural killer cells, and its genetic polymorphisms have been associated with chronic immune-mediated diseases. The progressive form of nonalcoholic fatty liver disease (NAFLD), nonalcoholic steatohepatitis (NASH), is characterized by accumulation of fat and inflammatory cells in the hepatic parenchyma, potentially leading to liver cell injury and fibrosis. To date, there are no data describing the potential role of MICA in the pathogenesis of NAFLD. Therefore, our aim was to assess the association between MICA polymorphism and NASH and its histologic features. A total of 134 subjects were included. DNA from patients with biopsy-proven NAFLD were genotyped using polymerase chain reaction-sequence-specific oligonucleotide for MICA alleles. Liver biopsies were assessed for histologic diagnosis of NASH and specific pathologic features, including stage of fibrosis and grade of inflammation. Multivariate analysis was performed to draw associations between MICA alleles and the different variables; P ≤ 0.05 was considered significant. Univariate analysis showed that MICA*011 (odds ratio [OR], 7.14; 95% confidence interval [CI], 1.24-41.0; P = 0.04) was associated with a higher risk for histologic NASH. Multivariate analysis showed that MICA*002 was independently associated with a lower risk for focal hepatocyte necrosis (OR, 0.24; 95% CI, 0.08-0.74; P = 0.013) and advanced fibrosis (OR, 0.11; 95% CI, 0.02-0.70; P = 0.019). MICA*017 was independently associated with a higher risk for lymphocyte-mediated inflammation (OR, 5.12; 95% CI, 1.12-23.5; P = 0.035). Conclusion: MICA alleles may be associated with NASH and its histologic features of inflammation and fibrosis. Additional research is required to investigate the potential role of MICA in increased risk or protection against NAFLD.

| S-EPMC7789833 | biostudies-literature

Association between variant alleles of major histocompatibility complex class II regulatory genes and nasopharyngeal carcinoma susceptibility.

Project description:Major histocompatibility complex (MHC) class II regulatory genes play a paramount role in immune response that can exert a predominant influence on clinical outcome of Epstein-Barr virus infection consistently assumed as the main pathogenetic factor for nasopharyngeal carcinoma. To elucidate the relationship between allelic variants of MHC class II regulatory genes and susceptibility to nasopharyngeal carcinoma, a total of 28 polymorphic loci at MHC class II regulatory genes, involving CIITA, CREB1, RFX family genes (RFX5, RFXAP, and RFXANK), and NFY family genes (NFYA, NFYB, and NFYC), were genotyped by multiplex SNaPshot minisequencing in 137 patients with nasopharyngeal carcinoma and 107 healthy controls from the southern Chinese population. Allelic analysis disclosed that rs7404873, rs6498121, rs6498126, and rs56074043 shared correlations with nasopharyngeal carcinoma (Ptrend < 0.05). Further, rs6498126 on CIITA was independently associated with the risk of developing nasopharyngeal carcinoma (CC vs. GG, odds ratio: 7.386, 95% confidence interval: 1.934-28.207, Ptrend < 0.01). Conversely, rs7404873 on CIITA and rs56074043 on NFYB manifested epistatic interaction to decreased susceptibility of nasopharyngeal carcinoma (rs7404873, TT vs. GG, odds ratio: 0.256, 95% confidence interval: 0.088-0.740, Ptrend < 0.05; rs56074043, AA vs. AG, odds ratio: 0.341, 95% confidence interval: 0.129-0.900, Ptrend < 0.05). Additionally, bioinformatics analysis revealed that the three variants were transcriptional regulatory in function and might impact the expression of nearby genes. The findings suggested genetic variants on MHC class II regulatory genes contributed to nasopharyngeal carcinoma susceptibility and might provide new insights for screening high-risk population.

| S-EPMC7531501 | biostudies-literature

Gorilla class I major histocompatibility complex alleles: comparison to human and chimpanzee class I.

Project description:14 gorilla class I major histocompatibility complex (MHC) alleles have been isolated, sequenced, and compared to their counterparts in humans and chimpanzees. Gorilla homologues of HLA-A, -B, and -C were readily identified, and four Gogo-A, four Gogo-B, and five Gogo-C alleles were defined. In addition, an unusual Gogo class I gene with features in common with HLA-A and its related pseudogene, HLA-H, is described. None of the gorilla alleles is identical or even closely related to known class I alleles and each encodes a unique antigen recognition site. However, the majority of polymorphic substitutions and sequence motifs of gorilla class I alleles are shared with the human or chimpanzee systems. In particular, elements shared with HLA-A2 and HLA-B27 are found in Gogo-A and -B alleles. Diversity at the Gogo-B locus is less than at the Gogo-A locus, a trend the opposite of that seen for HLA-A and -B. The Gogo-C locus also appears to have limited polymorphism compared to Gogo-A. Two basic Gogo-C motifs were found and they segregate with distinctive sets of HLA-C alleles. HLA-A allels are divided into five families derived from two ancient lineages. All chimpanzee A alleles derived from one of these lineages and all gorilla alleles derive from the other. Unlike chimpanzee Patr-A alleles, the Gogo-A alleles do not clearly partition with one of the HLA-A families but have similarities with two. Overall, gorilla class I diversity appears from this sampling to show more distinctions from class I HLA than found for chimpanzee class I.

| S-EPMC2119018 | biostudies-other

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