Barak Michal, Zuckerman Neta S, Edelman Hanna, Unger Ron, Mehr Ramit
The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel.
J Immunol Methods. 2008 Sep 30;338(1-2):67-74. doi: 10.1016/j.jim.2008.06.006. Epub 2008 Aug 14.
Lineage trees describe the microevolution of cells within an organism. They have been useful in the study of B cell affinity maturation, which is based on somatic hypermutation of immunoglobulin genes in germinal centers and selection of the resulting mutants. Our aim was to create and implement an algorithm that can generate lineage trees from immunoglobulin variable region gene sequences. The IgTree program implements the algorithm we developed, and generates lineage trees. Original sequences found in experiments are assigned to either leaves or internal nodes of the tree. Each tree node represents a single mutation separating the sequences. The mutations that separate the sequences from each other can be point mutations, deletions or insertions. The program can deal with gaps and find potential reversion mutations. The program also enumerates mutation frequencies and sequence motifs around each mutation, on a per-tree basis. The algorithm has proven useful in several studies of immunoglobulin variable region gene mutations.
谱系树描述了生物体内细胞的微观进化。它们在B细胞亲和力成熟的研究中很有用，B细胞亲和力成熟基于生发中心免疫球蛋白基因的体细胞超突变以及对所得突变体的选择。我们的目标是创建并实施一种算法，该算法可以从免疫球蛋白可变区基因序列生成谱系树。IgTree程序实现了我们开发的算法，并生成谱系树。实验中发现的原始序列被分配到树的叶节点或内部节点。每个树节点代表一个分隔序列的单一突变。将序列彼此分隔开的突变可以是点突变、缺失或插入。该程序可以处理缺口并找到潜在的回复突变。该程序还会在每棵树的基础上枚举每个突变周围的突变频率和序列基序。该算法在几项免疫球蛋白可变区基因突变研究中已证明很有用。
