Volpe Joseph M, Cowell Lindsay G, Kepler Thomas B
Computational Biology and Bioinformatics Program, Duke University Medical Center Box 90090 Duke University, Durham, NC 27708-0090, USA.
Bioinformatics. 2006 Feb 15;22(4):438-44. doi: 10.1093/bioinformatics/btk004. Epub 2005 Dec 15.
The antigen receptors of adaptive immunity-T-cell receptors and immunoglobulins-are encoded by genes assembled stochastically from combinatorial libraries of gene segments. Immunoglobulin genes then experience further diversification through hypermutation. Analysis of the somatic genetics of the immune response depends explicitly on inference of the details of the recombinatorial process giving rise to each of the participating antigen receptor genes. We have developed a dynamic programming algorithm to perform this reconstruction and have implemented it as web-accessible software called SoDA (Somatic Diversification Analysis).
We tested SoDA against a set of 120 artificial immunoglobulin sequences generated by simulation of recombination and compared the results with two other widely used programs. SoDA inferred the correct gene segments more frequently than the other two programs. We further tested these programs using 30 human immunoglobulin genes from Genbank and here highlight instances where the recombinations inferred by the three programs differ. SoDA appears generally to find more likely recombinations.
适应性免疫的抗原受体——T细胞受体和免疫球蛋白——由从基因片段组合文库中随机组装的基因编码。免疫球蛋白基因随后通过超突变经历进一步的多样化。免疫反应的体细胞遗传学分析明确依赖于对产生每个参与的抗原受体基因的重组过程细节的推断。我们开发了一种动态规划算法来执行这种重建,并将其实现为一个名为SoDA(体细胞多样化分析)的可通过网络访问的软件。
我们用一组通过重组模拟生成的120个人工免疫球蛋白序列测试了SoDA,并将结果与其他两个广泛使用的程序进行了比较。SoDA比其他两个程序更频繁地推断出正确的基因片段。我们使用来自Genbank的30个人类免疫球蛋白基因进一步测试了这些程序,并在此突出显示了三个程序推断的重组不同的实例。SoDA似乎总体上能找到更可能的重组。