Abstract
BackgroundB cell affinity maturation enables B cells to generate high-affinity antibodies. This process involves somatic hypermutation of B cell immunoglobulin receptor (BCR) genes and selection by their ability to bind antigens. Lineage trees are used to describe this microevolution of B cell immunoglobulin genes. In a lineage tree, each node is one BCR sequence that mutated from the germinal center and each directed edge represents a single base mutation, insertion or deletion. In BCR sequencing data, the observed data only contains a subset of BCR sequences in this microevolution process. Therefore, reconstructing the lineage tree from experimental data requires algorithms to build the tree based on partially observed tree nodes.ResultsWe developed a new algorithm named Grow Lineages along Minimum Spanning Tree (GLaMST), which efficiently reconstruct the lineage tree given observed BCR sequences that correspond to a subset of the tree nodes. Through comparison using simulated and real data, GLaMST outperforms existing algorithms in simulations with high rates of mutation, insertion and deletion, and generates lineage trees with smaller size and closer to ground truth according to tree features that highly correlated with selection pressure.ConclusionsGLaMST outperforms state-of-art in reconstruction of the BCR lineage tree in both efficiency and accuracy. Integrating it into existing BCR sequencing analysis frameworks can significant improve lineage tree reconstruction aspect of the analysis.
Highlights
B cell affinity maturation enables B cells to generate high-affinity antibodies
In a B cell immunoglobulin receptor (BCR) lineage tree, each tree node corresponds to one unique sequence, and each directed edge indicates the relationship between one sequence and its immediate ancestor, which are separated by one-base muta
This process is similar to building the phylogenetic tree among species, except that only leaf nodes are observed in phylogenetic problem, whereas some internal nodes and the root nodes are observed in this BCR lineage tree reconstruction problem
Summary
B cell affinity maturation enables B cells to generate high-affinity antibodies. This process involves somatic hypermutation of B cell immunoglobulin receptor (BCR) genes and selection by their ability to bind antigens. Given high throughput BCR sequencing data of a repertoire, the observed sequences correspond to some of the internal nodes and the leaf nodes of the BCR lineage tree, while many intermediate nodes are not observed due to the diversification and selection process the repertoire went through, as well as subsampling inherent to the assay. With these observed sequences, we can identify the root sequence of this tree by sequence alignment against known germline BCR segments in the genome [6]. We decided to pursue the maximum parsimony idea to reconstruct the BCR lineage tree, which intends to reconstruct a tree as small as possible, which connects all the observed sequences with minimum number of mutation, insertion and deletion events
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