#Immune repertoire sequencing how to#
#Immune repertoire sequencing software#

Individual B cells gain this specificity during their development in the bone marrow, where they undergo a somatic rearrangement process that combines multiple germline-encoded gene segments to produce the BCR (Fig. For example, some B cells will bind to epitopes expressed by influenza A viruses, and others to smallpox viruses. Each B cell expresses a different BCR that allows it to recognize a particular set of molecular patterns. These cells are critical components of adaptive immunity, and directly bind to pathogens through BCRs expressed on the cell surface. There are approximately 10 10–10 11 B cells in a human adult. Thus, it is timely to provide an introduction to the major steps involved in B-cell Rep-seq analysis. Although Rep-seq produces important basic science and clinical insights, the computational analysis pipelines required to analyze these data have not yet been standardized, and generally remain inaccessible to non-specialists. Rep-seq may also shed new light on antibody discovery. In addition to probing the fundamental processes underlying the immune system in healthy individuals, Rep-seq has the potential to reveal the mechanisms underlying autoimmune diseases, allergy, cancer and aging. These BCR repertoire sequencing (Rep-seq) studies have important basic science and clinical relevance. More recently, HTS has been applied to study the diversity of B cells, each of which expresses a practically unique B-cell immunoglobulin receptor (BCR). Each new technique has required the development of specialized computational methods to analyze these complex datasets and produce biologically interpretable results.

Applications of HTS to genomes (DNA sequencing (DNA-seq)), transcriptomes (RNA sequencing (RNA-seq)) and epigenomes (chromatin immunoprecipitation sequencing (ChIP-seq)) are becoming standard components of immune profiling. Rapid improvements in high-throughput sequencing (HTS) technologies are revolutionizing our ability to carry out large-scale genetic profiling studies.

#Immune repertoire sequencing how to#

The guidelines presented here highlight the major steps involved in the analysis of B-cell repertoire sequencing data, along with recommendations on how to avoid common pitfalls. These include methods for unique molecular identifiers and sequencing error correction, V(D)J assignment and detection of novel alleles, clonal assignment, lineage tree construction, somatic hypermutation modeling, selection analysis, and analysis of stereotyped or convergent responses. Here we provide a set of practical guidelines for B-cell receptor repertoire sequencing analysis, starting from raw sequencing reads and proceeding through pre-processing, determination of population structure, and analysis of repertoire properties. Common file formats for data sharing are also lacking. However, the field has yet to converge on a standard pipeline for data processing and analysis.

#Immune repertoire sequencing software#

Numerous methods and tools have been developed to handle different steps of the analysis, and integrated software suites have recently been made available. These data require specialized bioinformatics pipelines to be analyzed effectively. As sequencing technologies continue to improve, these repertoire sequencing experiments are producing ever larger datasets, with tens- to hundreds-of-millions of sequences. Recent applications include the study of autoimmunity, infection, allergy, cancer and aging. High-throughput sequencing of B-cell immunoglobulin repertoires is increasingly being applied to gain insights into the adaptive immune response in healthy individuals and in those with a wide range of diseases.