Introduction to Major Histocompatibility Complex (MHC)
The major histocompatibility complex (MHC) is undoubtedly the nerve center of the immune system, with genes associated with both innate and adaptive immune reactions such as those involved in antigen processing and presentation. The MHC area has now been identified in several mammalian species, including eutherians, marsupials, and monotremes18,19,20. The MHC area is categorized into three classes Class I, Class II, and Class III, which are arranged in a Class I-III-II pattern along the chromosome.
The purpose of MHC molecules is to connect pathogen-derived peptide fragments and exhibit them on the cell surface for identification by T cells. Virus-infected cells die, macrophages are triggered to destroy bacteria living in their intracellular vesicles, and B cells are triggered to generate antibodies that kill or neutralize extracellular pathogens. As a result, any pathogen that has mutated in such a way that it avoids being presented by an MHC molecule faces strong selective pressure. As a result, any pathogen that has mutated in such a way that it avoids being presented by an MHC molecule faces strong selective pressure.
Pathogens find it difficult to evade immune responses in this way due to two distinct properties of the MHC. First, the MHC is polygenic: it includes two different MHC class I and MHC class II genes, resulting in a set of MHC molecules with varying peptide-binding particularities in each individual. Second, the MHC is highly polymorphic, meaning that each gene has numerous variants within the population. The MHC genes are the most polymorphic genes ever discovered. In this segment, we'll go over how the genes in the MHC are organized and how variance in MHC molecules emerges.
MHC Captured Sequencing Data
The MHC captured sequencing information is captured by designing the probe using the target region MHC region sequence, enriching this area using the capture method, and sequencing the DNA sequence in this area using the high-throughput sequencing technique. Different probes can be designed to capture different areas of the MHC. Through the bioinformatics analysis of the captured sequencing data, the genes in this region can be divided into different genotyped, and the SNP and InDel associated with diseases can also be found.
Applications
The findings of MHC capture and sequencing data bioinformatics analysis can be applied to the following research areas.
- Research into autoimmune diseases linked to HLA mutations, as well as a wide range of complex diseases and cancers.
- Identification of organ transplantation matching based on HLA typing accuracy.
- Vaccine and drug screening for a specific population.
- Forensic medicine and paternity tests
- Ethnic development
MHC Capture Sequencing Data Standard Analysis Content
- Remove joint contamination and low-quality data.
- The data is compared with the database through BWA.
- Statistical assessment of data output, depth evaluation of sequencing, and
uniformity assessment of coverage.
- SNP mutation information identification.
- SNP's RefGene annotation.
- SNP database assessment (database annotation assessment with dbSNP and hundreds of genomic info).
- Single specimen SNP conservative prediction, pathogenicity assessment.
- Distribution statistics of SNP on each gene functional component.
- InDel mutation information identification.
- InDel's RefGene annotation.
- InDel database assessment (database annotation assessment with dbSNP, hundreds of genomic data, ESP exome database);
- Distribution statistics of InDel on each gene functional component.
- HLA typing.
About CD Genomics Bioinformatics Analysis
The bioinformatics analysis department of CD Genomics provides novel solutions for data-driven innovation aimed at discovering the hidden potential in biological data, tapping new insights related to life science research, and predicting new prospects.
References
- Dapprich J, Ferriola D, Mackiewicz K, et al. The next generation of target capture technologies-large DNA fragment enrichment and sequencing determines regional genomic variation of high complexity. BMC genomics. 2016, 17(1).
- Ng JH, Tachedjian M, Deakin J, et al. Evolution and comparative analysis of the bat MHC-I region. Scientific reports. 2016, 6(1):1-8.
- Pröll JO, Danzer MA, Stabentheiner ST, et al. Sequence capture and next generation resequencing of the MHC region highlights potential transplantation determinants in HLA identical haematopoietic stem cell transplantation. DNA research. 2011, 18(4).
