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Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

Antibody repertoire sequencing analysis.

Senxin Zhang¹, Tiange Yang², Xiaojing Liu²

¹Department of Mathematics, Shanghai Normal University, Shanghai 200234, China.

Acta Biochimica Et Biophysica Sinica

|June 17, 2022

Summary

This summary is machine-generated.

High-throughput sequencing of B cell receptor (BCR) repertoires offers insights into adaptive immunity. This review details BCR-seq methods, focusing on V(D)J annotation, phylogenetic inference, and repertoire profiling for data analysis.

Keywords:

BCR repertoire analysis high-throughput sequencing profiling and data mining statistical method

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Last Updated: Sep 7, 2025

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

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Published on: August 22, 2019

Area of Science:

Immunology
Bioinformatics
Genomics

Background:

B cell receptor (BCR) repertoire sequencing is crucial for understanding adaptive immunity.
Advancements in BCR-seq technology generate vast amounts of data requiring sophisticated analysis.
Existing reviews often lack detailed explanations of underlying principles.

Purpose of the Study:

To provide a comprehensive overview of BCR repertoire library preparation protocols.
To summarize and explain the key steps in BCR-seq data analysis: V(D)J annotation, phylogenetic inference, and repertoire profiling.
To elucidate the statistical principles and intuitive background of BCR-seq analysis methods for biologists.

Main Methods:

Review of various BCR repertoire library preparation protocols.
Systematic summary of BCR-seq data analysis workflows.
Explanation of statistical underpinnings for V(D)J annotation, clonal inference, and repertoire profiling.

Main Results:

Detailed outline of BCR repertoire library preparation techniques.
Comprehensive summary of the three core BCR-seq data analysis stages.
Emphasis on the statistical and intuitive aspects of BCR-seq methodologies.
Discussion of current data mining challenges and emerging multi-sample analysis techniques.

Conclusions:

This review offers a foundational understanding of BCR-seq protocols and analysis.
It empowers biologists with the knowledge of statistical principles for interpreting BCR repertoire data.
Highlights future directions in BCR-seq data mining, particularly for multiple-sample studies.