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Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations.

ABSTRACT: The adaptive immune response selectively expands B- and T-cell clones following antigen recognition by B- and T-cell receptors (BCR and TCR), respectively. Next-generation sequencing is a powerful tool for dissecting the BCR and TCR populations at high resolution, but robust computational analyses are required to interpret such sequencing. Here, we develop a novel computational approach for BCR repertoire analysis using established next-generation sequencing methods coupled with network construction and population analysis. BCR sequences organize into networks based on sequence diversity, with differences in network connectivity clearly distinguishing between diverse repertoires of healthy individuals and clonally expanded repertoires from individuals with chronic lymphocytic leukemia (CLL) and other clonal blood disorders. Network population measures defined by the Gini Index and cluster sizes quantify the BCR clonality status and are robust to sampling and sequencing depths. BCR network analysis therefore allows the direct and quantifiable comparison of BCR repertoires between samples and intra-individual population changes between temporal or spatially separated samples and over the course of therapy.

SUBMITTER: Bashford-Rogers RJ

PROVIDER: S-EPMC3814887 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations.

Bashford-Rogers Rachael J M RJ Palser Anne L AL Huntly Brian J BJ Rance Richard R Vassiliou George S GS Follows George A GA Kellam Paul P

Genome research 20130606 11

The adaptive immune response selectively expands B- and T-cell clones following antigen recognition by B- and T-cell receptors (BCR and TCR), respectively. Next-generation sequencing is a powerful tool for dissecting the BCR and TCR populations at high resolution, but robust computational analyses are required to interpret such sequencing. Here, we develop a novel computational approach for BCR repertoire analysis using established next-generation sequencing methods coupled with network construc ...[more]

PMID: 23742949

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Project description:BackgroundMyositis, or idiopathic inflammatory myopathy (IIM), is a group disorders of unknown etiology characterized by the inflammation of skeletal muscle. The role of T cells and their antigenic targets in IIM initiation and progression is poorly understood. T cell receptor (TCR) repertoire sequencing is a powerful approach for characterizing complex T cell responses. However, current TCR sequencing methodologies are complex, expensive, or both, greatly limiting the scale of feasible studies.MethodsHere we present Framework Region 3 AmplifiKation sequencing ("FR3AK-seq"), a simplified multiplex PCR-based approach for the ultra-efficient and quantitative analysis of TCR complementarity determining region 3 (CDR3) repertoires. By using minimal primer sets targeting a conserved region immediately upstream of CDR3, undistorted amplicons are analyzed via short read, single-end sequencing. We also introduce the novel algorithm Inferring Sequences via Efficiency Projection and Primer Incorporation ("ISEPPI") for linking CDR3s to their associated variable genes.FindingsWe find that FR3AK-seq is sensitive and quantitative, performing comparably to two different industry standards. FR3AK-seq and ISEPPI were used to efficiently and inexpensively characterize the T cell infiltrates of surgical muscle biopsies obtained from 145 patients with IIM and controls. A cluster of closely related TCRs was identified in samples from patients with sporadic inclusion body myositis (IBM).InterpretationThe ease and minimal cost of FR3AK-seq removes critical barriers to routine, large-scale TCR CDR3 repertoire analyses, thereby democratizing the quantitative assessment of human TCR repertoires in disease-relevant target tissues. Importantly, discovery of closely related TCRs in muscle from patients with IBM provides evidence for a shared antigen-driven T cell response in this disease of unknown pathogenesis.FundingThis work was supported by NIH grant U24AI118633 and a Prostate Cancer Foundation Young Investigator Award.

Dataset Information

Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations.

Publications

Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations.

Similar Datasets

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