【6.7.1】体细胞超突变--shm
Antibody repertoires are generated by complex processes:
- V(D)J recombination
- intergenic insertions
- somatic hypermutations
Somatic hypermutation (SHM) is a process that diversifies BCRs by introducing point mutations into Ig genes at a high rate :
- SHM is initiated when activation-induced cytidine deaminase (AID) is recruited to the Ig locus and converts cytosine (C) to uracil (U).
- Error-prone DNA repair pathways are then activated, resulting in somatic mutations either at the AID-targeted C/G base pair (phase I) or at neighboring base pairs
体细胞超突变（Somatic hypermutation，SHM）是一种细胞机制，免疫系统通过该机制适应与其相对的新外来元件（例如微生物），如类别转换期间所见。 亲和力成熟（ affinity maturation）过程的一个主要组成部分，SHM使用于识别外来元素（抗原）的B细胞受体多样化，并允许免疫系统在生物体的有效期内适应其对新威胁的反应。[1] 体细胞超突变涉及影响免疫球蛋白基因可变区的程序化突变过程。与种系突变不同，SHM仅影响生物体的个体免疫细胞，并且突变不会传播给生物体的后代。[2] Mistargeted体细胞超突变是B细胞淋巴瘤[3]和许多其他癌症发展的可能机制。[4] [5]
Igblast
https://www.ncbi.nlm.nih.gov/igblast/
主流的三个shm工具
- IgSimulator
- shazaM
- AbSim
现有的突变模型
- Random ( Eg: Absim-Position)
- WRC (W equals A ; T and R equals A or G, Eg: Absim-wrc)
- Data ( specific mutations targeting nucleotides in complementary determining regions (CDRs), where each nucleotide has a user-defined probability for mutation, defined by m. Additionally, this method allows the use of different mutation rates for transitions and transversions, Eg: Absim )
- RGYW and TAA Motif ( 1992, Eg: Igsimulator)
- S5F (2013, Eg: SHazaM-S5F and Absim-Motif)
- S5F L and RS5NF L (2016)
一、Igsimulator
官网： http://yana-safonova.github.io/ig_simulator/ （github: https://github.com/yana-safonova/ig_simulator）
软件说明：
http://yana-safonova.github.io/ig_simulator/ig_simulator_manual.html
二、AbSim
官网：
https://cran.r-project.org/web/packages/AbSim/vignettes/vignette.html
采用的是IMGT的数据库构建的模型
三、shazaM
官网：
https://shazam.readthedocs.io/en/version-0.1.9---baseline-fixes/
软件说明文档：
https://shazam.readthedocs.io/en/version-0.1.9---baseline-fixes/vignettes/Shmulate-Vignette/
采用的是S5F模型（Models of SHM Targeting and Substitution），数据集的位置：
http://clip.med.yale.edu/shm/download.php
突变至少受周边两个碱基的影响：
Hot spot 有更高的突变频率：
优点：
1.数据量大，基于大量的数据构建的模型更能反映真实的突变频率。
缺点：
- 因为数据集来自重链，所以该模型不适用于轻链的预测
- 因为K-mer的多态性（适用的5kmer的比例为 717/1024）
- 数据集来自同义突变，对非同义突变的处理能力不强
参考资料
- https://en.wikipedia.org/wiki/Somatic_hypermutation
- Ang Cui et al. .A Model of Somatic Hypermutation Targeting in Mice Based on High-Throughput Ig Sequencing Data . The Journal of Immunology ,2016.
- A model of somatic hypermutation targeting and substitution based on synonymous mutations from high-throughput Immunoglobulin sequencing data” Gur Yaari, Jason Vander Heiden,, Mohamed Uduman, Daniel Gadala-Maria, Namita Gupta, Joel N.H. Stern, Kevin C. O’Connor, David A. Hafler, Uri Laserson, Francois Vigneault and Steven H. Kleinstein. 2013. (Frontiers in Immunology, Submitted)
- Yaari et al. Models of somatic hypermutation targeting and substitution based on synonymous mutations from high-throughput immunoglobulin sequencing data, Frontiers in Immunology, 2013
