【5.3】体细胞超突变--shm

Antibody repertoires are generated by complex processes:

  1. V(D)J recombination
  2. intergenic insertions
  3. somatic hypermutations

Somatic hypermutation (SHM) is a process that diversifies BCRs by introducing point mutations into Ig genes at a high rate :

  1. SHM is initiated when activation-induced cytidine deaminase (AID) is recruited to the Ig locus and converts cytosine © to uracil (U).
  2. 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

  1. IgSimulator
  2. shazaM
  3. 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

http://www.imgt.org/

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:

  1. 因为数据集来自重链,所以该模型不适用于轻链的预测
  2. 因为K-mer的多态性(适用的5kmer的比例为 717/1024)
  3. 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
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