Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.

Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell rece...

Full description

Bibliographic Details
Main Authors: Nima Nouri, Steven H Kleinstein
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-06-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1007977
id doaj-c4ef81cdadb142b5a64361c52aa46f93
record_format Article
spelling doaj-c4ef81cdadb142b5a64361c52aa46f932021-04-21T15:18:12ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-06-01166e100797710.1371/journal.pcbi.1007977Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.Nima NouriSteven H KleinsteinAdaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptor (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones. Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or newer) in the Immcantation framework: www.immcantation.org under the AGPLv3 license.https://doi.org/10.1371/journal.pcbi.1007977
collection DOAJ
language English
format Article
sources DOAJ
author Nima Nouri
Steven H Kleinstein
spellingShingle Nima Nouri
Steven H Kleinstein
Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.
PLoS Computational Biology
author_facet Nima Nouri
Steven H Kleinstein
author_sort Nima Nouri
title Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.
title_short Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.
title_full Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.
title_fullStr Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.
title_full_unstemmed Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.
title_sort somatic hypermutation analysis for improved identification of b cell clonal families from next-generation sequencing data.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2020-06-01
description Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptor (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones. Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or newer) in the Immcantation framework: www.immcantation.org under the AGPLv3 license.
url https://doi.org/10.1371/journal.pcbi.1007977
work_keys_str_mv AT nimanouri somatichypermutationanalysisforimprovedidentificationofbcellclonalfamiliesfromnextgenerationsequencingdata
AT stevenhkleinstein somatichypermutationanalysisforimprovedidentificationofbcellclonalfamiliesfromnextgenerationsequencingdata
_version_ 1714667565069893632