Bibliographic Details
| Title: |
Reconstructing B cell lineage trees with minimum spanning tree and genotype abundances. |
| Authors: |
Abdollahi, Nika1,2 (AUTHOR), Jeusset, Lucile1,3 (AUTHOR), de Septenville, Anne3 (AUTHOR), Davi, Frederic3 (AUTHOR), Bernardes, Juliana Silva1 (AUTHOR) juliana.silva_bernardes@sorbonne-universite.fr |
| Superior Title: |
BMC Bioinformatics. 2/27/2023, Vol. 24 Issue 1, p1-19. 19p. |
| Subject Terms: |
*B cells, *SPANNING trees, *B cell receptors, *GENOTYPES |
| Abstract: |
B cell receptor (BCR) genes exposed to an antigen undergo somatic hypermutations and Darwinian antigen selection, generating a large BCR-antibody diversity. This process, known as B cell affinity maturation, increases antibody affinity, forming a specific B cell lineage that includes the unmutated ancestor and mutated variants. In a B cell lineage, cells with a higher antigen affinity will undergo clonal expansion, while those with a lower affinity will not proliferate and probably be eliminated. Therefore, cellular (genotype) abundance provides a valuable perspective on the ongoing evolutionary process. Phylogenetic tree inference is often used to reconstruct B cell lineage trees and represents the evolutionary dynamic of BCR affinity maturation. However, such methods should process B-cell population data derived from experimental sampling that might contain different cellular abundances. There are a few phylogenetic methods for tracing the evolutionary events occurring in B cell lineages; best-performing solutions are time-demanding and restricted to analysing a reduced number of sequences, while time-efficient methods do not consider cellular abundances. We propose ClonalTree, a low-complexity and accurate approach to construct B-cell lineage trees that incorporates genotype abundances into minimum spanning tree (MST) algorithms. Using both simulated and experimental data, we demonstrate that ClonalTree outperforms MST-based algorithms and achieves a comparable performance to a method that explores tree-generating space exhaustively. Furthermore, ClonalTree has a lower running time, being more convenient for building B-cell lineage trees from high-throughput BCR sequencing data, mainly in biomedical applications, where a lower computational time is appreciable. It is hundreds to thousands of times faster than exhaustive approaches, enabling the analysis of a large set of sequences within minutes or seconds and without loss of accuracy. The source code is freely available at github.com/julibinho/ClonalTree. [ABSTRACT FROM AUTHOR] |
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