High-Throughput DNA Sequencing Analysis of Antibody Repertoires

B cell receptor repertoire abnormalities in autoimmune disease

B cells play a crucial role in the immune response and contribute to various autoimmune diseases. Recent studies have revealed abnormalities in the B cell receptor (BCR) repertoire of patients with autoimmune diseases, with distinct features observed among different diseases and B cell subsets. Classically, BCR repertoire was used as an identifier of distinct antigen-specific clonotypes, but the recent advancement of analyzing large-scale repertoire has enabled us to use it as a tool for characterizing cellular biology. In this review, we provide an overview of the BCR repertoire in autoimmune diseases incorporating insights from our latest research findings. In systemic lupus erythematosus (SLE), we observed a significant skew in the usage of VDJ genes, particularly in CD27+IgD+ unswitched memory B cells and plasmablasts. Notably, autoreactive clones within unswitched memory B cells were found to be increased and strongly associated with disease activity, underscoring the clinical significance of this subset. Similarly, various abnormalities in the BCR repertoire have been reported in other autoimmune diseases such as rheumatoid arthritis. Thus, BCR repertoire analysis holds potential for enhancing our understanding of the underlying mechanisms involved in autoimmune diseases. Moreover, it has the potential to predict treatment effects and identify therapeutic targets in autoimmune diseases.

nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets. nf-core/airrflow is available free of charge, under the MIT license on GitHub (https://github.com/nf-core/airrflow). Detailed documentation and example results are available on the nf-core website at (https://nf-co.re/airrflow).

Role of the mechanisms for antibody repertoire diversification in monoclonal light chain deposition disorders: when a friend becomes foe

The adaptive immune system of jawed vertebrates generates a highly diverse repertoire of antibodies to meet the antigenic challenges of a constantly evolving biological ecosystem. Most of the diversity is generated by two mechanisms: V(D)J gene recombination and somatic hypermutation (SHM). SHM introduces changes in the variable domain of antibodies, mostly in the regions that form the paratope, yielding antibodies with higher antigen binding affinity. However, antigen recognition is only possible if the antibody folds into a stable functional conformation. Therefore, a key force determining the survival of B cell clones undergoing somatic hypermutation is the ability of the mutated heavy and light chains to efficiently fold and assemble into a functional antibody. The antibody is the structural context where the selection of the somatic mutations occurs, and where both the heavy and light chains benefit from protective mechanisms that counteract the potentially deleterious impact of the changes. However, in patients with monoclonal gammopathies, the proliferating plasma cell clone may overproduce the light chain, which is then secreted into the bloodstream. This places the light chain out of the protective context provided by the quaternary structure of the antibody, increasing the risk of misfolding and aggregation due to destabilizing somatic mutations. Light chain-derived (AL) amyloidosis, light chain deposition disease (LCDD), Fanconi syndrome, and myeloma (cast) nephropathy are a diverse group of diseases derived from the pathologic aggregation of light chains, in which somatic mutations are recognized to play a role. In this review, we address the mechanisms by which somatic mutations promote the misfolding and pathological aggregation of the light chains, with an emphasis on AL amyloidosis. We also analyze the contribution of the variable domain (V_L) gene segments and somatic mutations on light chain cytotoxicity, organ tropism, and structure of the AL fibrils. Finally, we analyze the most recent advances in the development of computational algorithms to predict the role of somatic mutations in the cardiotoxicity of amyloidogenic light chains and discuss the challenges and perspectives that this approach faces.

Antigen presentation dynamics shape the antibody response to variants like SARS-CoV-2 Omicron after multiple vaccinations with the original strain

The Omicron variant of SARS-CoV-2 is not effectively neutralized by most antibodies elicited by two doses of mRNA vaccines, but a third dose increases anti-Omicron neutralizing antibodies. We reveal mechanisms underlying this observation by combining computational modeling with data from vaccinated humans. After the first dose, limited antigen availability in germinal centers (GCs) results in a response dominated by B cells that target immunodominant epitopes that are mutated in an Omicron-like variant. After the second dose, these memory cells expand and differentiate into plasma cells that secrete antibodies that are thus ineffective for such variants. However, these pre-existing antigen-specific antibodies transport antigen efficiently to secondary GCs. They also partially mask immunodominant epitopes. Enhanced antigen availability and epitope masking in secondary GCs together result in generation of memory B cells that target subdominant epitopes that are less mutated in Omicron. The third dose expands these cells and boosts anti-variant neutralizing antibodies.

Different classes of genomic inserts contribute to human antibody diversity

The enormous diversity of antibodies is a key element to combat infections. Antibodies containing pathogen receptors were a surprising discovery that contrasted antibody diversification through classic recombination events. However, such insert-containing antibodies were thus far exclusively detected in African individuals exposed to malaria parasites and were identified as screening byproducts or through hypothesis-driven search. The prevalence and complexity of insertion events remained elusive. In this study, we devise an unbiased, systematic approach to identify inserts in the human antibody repertoire. We show that inserts from distant genomic regions occur in the majority of donors and are independent of Plasmodium falciparum preexposure. Our findings suggest that four distinct classes of insertion events contribute diversity to the human antibody repertoire.

Recombination of antibody genes in B cells can involve distant genomic loci and contribute a foreign antigen-binding element to form hybrid antibodies with broad reactivity for Plasmodium falciparum. So far, antibodies containing the extracellular domain of the LAIR1 and LILRB1 receptors represent unique examples of cross-chromosomal antibody diversification. Here, we devise a technique to profile non-VDJ elements from distant genes in antibody transcripts. Independent of the preexposure of donors to malaria parasites, non-VDJ inserts were detected in 80% of individuals at frequencies of 1 in 10⁴ to 10⁵ B cells. We detected insertions in heavy, but not in light chain or T cell receptor transcripts. We classify the insertions into four types depending on the insert origin and destination: 1) mitochondrial and 2) nuclear DNA inserts integrated at VDJ junctions; 3) inserts originating from telomere proximal genes; and 4) fragile sites incorporated between J-to-constant junctions. The latter class of inserts was exclusively found in memory and in in vitro activated B cells, while all other classes were already detected in naïve B cells. More than 10% of inserts preserved the reading frame, including transcripts with signs of antigen-driven affinity maturation. Collectively, our study unravels a mechanism of antibody diversification that is layered on the classical V(D)J and switch recombination.

Antibody repertoire sequencing analysis

High-throughput sequencing for B cell receptor (BCR) repertoire provides useful insights for the adaptive immune system. With the continuous development of the BCR-seq technology, many efforts have been made to develop methods for analyzing the ever-increasing BCR repertoire data. In this review, we comprehensively outline different BCR repertoire library preparation protocols and summarize three major steps of BCR-seq data analysis, i. e., V(D)J sequence annotation, clonal phylogenetic inference, and BCR repertoire profiling and mining. Different from other reviews in this field, we emphasize background intuition and the statistical principle of each method to help biologists better understand it. Finally, we discuss data mining problems for BCR-seq data and with a highlight on recently emerging multiple-sample analysis.

Exploring the Diversity of the B-Cell Receptor Repertoire Through High-Throughput Sequencing

Repertoire sequencing of B cells is the high-throughput profiling of B cell receptors (BCR) expressed on the surface of B cells and of immunoglobulins (Ig) expressed by antibody secreting cells. Each BCR/Ig transcript has a unique complementarity-determining region 3 (CDR3) sequence that can be used to identify and track individual B cell lymphocytes over time and throughout different compartments of the human body. B cell differentiation can be further tracked by assessing the point mutations acquired during affinity maturation via somatic hypermutation (SHM). Here we describe a method for high-throughput sequencing of the variable region of Ig heavy-chain transcripts for repertoire analysis of human B cells on the Illumina Miseq platform.

Next Generation Sequencing of Cerebrospinal Fluid B Cell Repertoires in Multiple Sclerosis and Other Neuro-Inflammatory Diseases-A Comprehensive Review

During the last few decades, the role of B cells has been well established and redefined in neuro-inflammatory diseases, including multiple sclerosis and autoantibody-associated diseases. In particular, B cell maturation and trafficking across the blood–brain barrier (BBB) has recently been deciphered with the development of next-generation sequencing (NGS) approaches, which allow the assessment of representative cerebrospinal fluid (CSF) and peripheral blood B cell repertoires. In this review, we perform literature research focusing on NGS studies that allow further insights into B cell pathophysiology during neuro-inflammation. Besides the analysis of CSF B cells, the paralleled assessment of peripheral blood B cell repertoire provides deep insights into not only the CSF compartment, but also in B cell trafficking patterns across the BBB. In multiple sclerosis, CSF-specific B cell maturation, in combination with a bidirectional exchange of B cells across the BBB, is consistently detectable. These data suggest that B cells most likely encounter antigen(s) within the CSF and migrate across the BBB, with further maturation also taking place in the periphery. Autoantibody-mediated diseases, such as neuromyelitis optica spectrum disorder and LGI1 / NMDAR encephalitis, also show features of a CSF-specific B cell maturation and clonal connectivity with peripheral blood. In conclusion, these data suggest an intense exchange of B cells across the BBB, possibly feeding autoimmune circuits. Further developments in sequencing technologies will help to dissect the exact pathophysiologic mechanisms of B cells during neuro-inflammation.

Profiling of T Cell Receptor β-Chain Complimentary Determining Regions 3 Repertoire in Subarachnoid Hemorrhage Patients Using High-Throughput Sequencing

Objective

The adaptive immune response following subarachnoid hemorrhage (SAH) is not well understood. We evaluated and compared the T cell receptor (TCR) immune repertoire of good-grade and poor-grade SAH patients to elucidate the T cell immunology after ictus.

Methods

Peripheral blood from six SAH patients was collected at two different times, admission and at the 7-day follow-up. Composition and variation of the TCR β-chain (TCRB) complimentary determining regions (CDR) 3 repertoire was examined using high-throughput sequencing; the analysis was based on sampling time and disease severity (good vs. poor-grade SAH).

Results

Clonality at admission and follow-up were 0.059 (0.037–0.038) and 0.027 (0.014–0.082) (median, 25th–75th percentile). Poor-grade SAH (0.025 [0.011–0.038]) was associated with significantly lower clonality than good-grade SAH (0.095 [0.079–0.101]). Poor-grade SAH patients had higher diversity scores than good-grade SAH patients. CDR length was shorter in good-grade SAH vs. poor-grade SAH. Differences in clonotype distribution were more prominent in TCRBV gene segments than TCRBJ segments. TCRBV19-01/TCRBJ02-04 and TCRBV28-01/TCRBJ02-04 were the most increased and the most decreased V-J pairs in the 7-day follow-up compared to admission in good-grade SAH. The most increased and decreased V-J pairs in poor-grade SAH patients were TCRBV28-01/TCRBJ02-06 and TCRBV30-01/TCRBJ02-04, respectively.

Conclusion

The TCRB repertoire is dynamic in nature following SAH. TCRB repertoire may facilitate our understanding of adaptive immune response according to SAH severity.

Network Organization of Antibody Interactions in Sequence and Structure Space: the RADARS Model

Adaptive immunity in vertebrates is a complex self-organizing network of molecular interactions. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper, a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RAdial ADjustment of System Resolution (RADARS), is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction corresponding to particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power law distribution of antibody-free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees, and B1 cells function as nodes with minimal degree. Overall, the RADARS model implies that a finite number of antibody structures can interact with an infinite number of antigens by immunologically controlled adjustment of interaction energy distribution. Understanding quantitative network properties of the system should help the organization of sequence-derived predicted structural data.

V(D)J recombination, somatic hypermutation and class switch recombination of immunoglobulins: mechanism and regulation

Immunoglobulins emerging from B lymphocytes and capable of recognizing almost all kinds of antigens owing to the extreme diversity of their antigen-binding portions, known as variable (V) regions, play an important role in immune responses. The exons encoding the V regions are known as V (variable), D (diversity), or J (joining) genes. V, D, J segments exist as multiple copy arrays on the chromosome. The recombination of the V(D)J gene is the key mechanism to produce antibody diversity. The recombinational process, including randomly choosing a pair of V, D, J segments, introducing double-strand breaks adjacent to each segment, deleting (or inverting in some cases) the intervening DNA and ligating the segments together, is defined as V(D)J recombination, which contributes to surprising immunoglobulin diversity in vertebrate immune systems. To enhance both the ability of immunoglobulins to recognize and bind to foreign antigens and the effector capacities of the expressed antibodies, naive B cells will undergo class switching recombination (CSR) and somatic hypermutation (SHM). However, the genetics mechanisms of V(D)J recombination, CSR and SHM are not clear. In this review, we summarize the major progress in mechanism studies of immunoglobulin V(D)J gene recombination and CSR as well as SHM, and their regulatory mechanisms.

Longitudinal analysis of the antibody repertoire of a Zika virus-infected patient revealed dynamic changes in antibody response

The Zika virus (ZIKV) is a mosquito-borne flavivirus that causes neonatal abnormalities and other disorders. Antibodies to the ZIKV envelope (E) protein can block infection. In this study, next-generation sequencing (NGS) of immunoglobulin heavy chain (IgH) mRNA transcripts was combined with single-cell PCR cloning of E-binding monoclonal antibodies for analysing antibody response in a patient from the early stages of infection to more than one year after the clearance of the virus. The patient's IgH repertoire 14 and 64 days after symptom onset showed dramatic dominant clonal expansion but low clonal diversity. IgH repertoire 6 months after disease-free status had few dominant clones but increased diversity. E-binding antibodies appeared abundantly in the repertoire during the early stages of infection but quickly declined after clearance of the virus. Certain VH genes such as VH5-10-1 and VH4-39 appeared to be preferentially enlisted for a rapid antibody response to ZIKV infection. Most of these antibodies require relatively few somatic hypermutations to acquire the ability to bind to the E protein, pointing to a possible mechanism for rapid defence against ZIKV infection. This study provides a unique and holistic view of the dynamic changes and characteristics of the antibody response to ZIKV infection.

Understanding the human antibody repertoire

The origins of the various elements in the human antibody repertoire have been and still are subject to considerable uncertainty. Uncertainty in respect of whether the various elements have always served a specific defense function or whether they were co-opted from other organismal roles to form a crude naïve repertoire that then became more complex as combinatorial mechanisms were added. Estimates of the current size of the human antibody naïve repertoire are also widely debated with numbers anywhere from 10 million members, based on experimentally derived numbers, to in excess of one thousand trillion members or more, based on the different sequences derived from theoretical combinatorial calculations. There are questions that are relevant at both ends of this number spectrum. At the lower bound it could be questioned whether this is an insufficient repertoire size to counter all the potential antigen-bearing pathogens. At the upper bound the question is rather simpler: How can any individual interrogate such an astronomical number of antibody-bearing B cells in a timeframe that is meaningful? This review evaluates the evolutionary aspects of the adaptive immune system, the calculations that lead to the large repertoire estimates, some of the experimental evidence pointing to a more restricted repertoire whose variation appears to derive from convergent 'structure and specificity features', and includes a theoretical model that seems to support it. Finally, a solution that may reconcile the size difference anomaly, which is still a hot subject of debate, is suggested.

iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories

Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org.

Next-generation sequencing reveals new insights about gene usage and CDR-H3 composition in the horse antibody repertoire

Horse serum antibodies have been used for greater than a century for the treatment and prophylaxis of infectious diseases and envenomations. Little is known, however, about the immunogenetic diversity that produces horse serum antibodies. Here, we employed next-generation sequencing for a first-in-kind comprehensive analysis of the equine B-cell repertoire. Nearly 45,000 and 30,000 clonotypes were obtained for the heavy-chain (IGH) and lambda light-chain (IGL) loci, respectively. We observed skewed use of the common subgroups IGHV2 (92.49%) and IGLV8 (82.50%), consistent with previous reports, but also novel use of the rare genes IGHV6S1 and IGLV4S2. CDR-H3 amino acid composition revealed different amino acid patterns at positions 106 and 116 compared to human, rabbit, and mouse, suggesting that an extended conformation predominates among horse CDR-H3 loops. Our analysis provides new insights regarding the mechanisms employed to generate antibody diversity in the horse, and could be applicable to the optimized design of synthetic antibodies intended for future therapeutic use.

A comparison of unamplified and massively multiplexed PCR amplification for murine antibody repertoire sequencing

Sequencing antibody repertoires has steadily become cheaper and easier. Sequencing methods usually rely on some form of amplification, often a massively multiplexed PCR prior to sequencing. To eliminate potential biases and create a data set that could be used for other studies, our laboratory compared unamplified sequencing results from the splenic heavy‐chain repertoire in the mouse to those processed through two commercial applications. We also compared the use of mRNA vs total RNA, reverse transcriptase, and primer usage for cDNA synthesis and submission. The use of mRNA for cDNA synthesis resulted in higher read counts but reverse transcriptase and primer usage had no statistical effects on read count. Although most of the amplified data sets contained more antibody reads than the unamplified data set, we detected more unique variable (V)‐gene segments in the unamplified data set. Although unique CDR3 detection was much lower in the unamplified data set, RNASeq detected 98% of the high‐frequency CDR3s. We have shown that unamplified profiling of the antibody repertoire is possible, detects more V‐gene segments, and detects high‐frequency clones in the repertoire.

Next generation sequencing reveals changes of the γδ T cell receptor repertoires in patients with pulmonary tuberculosis

Tuberculosis (TB) is a severe global threat to human health. The immune protection initiated by γδ T cells play an important role in mycobacterial infection. Vaccines for Mycobacterium tuberculosis (Mtb) based on γδ T cells provide a novel approach for TB control. In our previous studies, we found a preponderant complementarity-determining region 3 (CDR3) sequence of the γδ T cell receptor (TCR) in TB patients, and successfully identified a tuberculosis antigen that can effectively activate γδ T cells with a reverse genetic strategy. However, due to the throughput limitation of the method we used, the information we obtained about the γδ TCR repertoire and preponderant CDR3 sequences was limited. In this study, we introduced next generation sequencing (NGS) to study the γδ TCR CDR3 repertoires in TB patients. We found that the CDR3δ tended to be more polyclonal and CDR3γ tended to be longer in TB patients; the γδ T cells expressing CDR3 sequences using a Vγ9-JγP rearrangement expanded significantly during Mtb infection. We also identified new preponderant CDR3 sequences during Mtb infection. This study comprehensively characterized the γδ T cell receptor repertoire changes, and provides useful information for the development of new vaccines and adjuvants against TB.

The Individual and Population Genetics of Antibody Immunity

Antibodies (Abs) produced by immunoglobulin (IG) genes are the most diverse proteins expressed in humans. While part of this diversity is generated by recombination during B-cell development and mutations during affinity maturation, the germ-line IG loci are also diverse across human populations and ethnicities. Recently, proof-of-concept studies have demonstrated genotype–phenotype correlations between specific IG germ-line variants and the quality of Ab responses during vaccination and disease. However, the functional consequences of IG genetic variation in Ab function and immunological outcomes remain underexplored. In this opinion article, we outline interconnections between IG genomic diversity and Ab-expressed repertoires and structure. We further propose a strategy for integrating IG genotyping with functional Ab profiling data as a means to better predict and optimize humoral responses in genetically diverse human populations, with immediate implications for personalized medicine.

Genetic variation in human populations affects how individuals are able to mount functional antibody responses.

Different alleles can encode convergent binding motifs that result in successful Ab responses against specific infections and vaccinations.

Given the complexity of the IG loci and the diversity of the antibody repertoire, links between IG polymorphism and antibody repertoire variability have not been thoroughly explored.

We present a strategy to mine genotype–repertoire–disease associations.

Hierarchical Clustering Can Identify B Cell Clones with High Confidence in Ig Repertoire Sequencing Data

Adaptive immunity is driven by the expansion, somatic hypermutation, and selection of B cell clones. Each clone is the progeny of a single B cell responding to Ag, with diversified Ig receptors. These receptors can now be profiled on a large scale by next-generation sequencing. Such data provide a window into the microevolutionary dynamics that drive successful immune responses and the dysregulation that occurs with aging or disease. Clonal relationships are not directly measured, but they must be computationally inferred from these sequencing data. Although several hierarchical clustering-based methods have been proposed, they vary in distance and linkage methods and have not yet been rigorously compared. In this study, we use a combination of human experimental and simulated data to characterize the performance of hierarchical clustering-based methods for partitioning sequences into clones. We find that single linkage clustering has high performance, with specificity, sensitivity, and positive predictive value all >99%, whereas other linkages result in a significant loss of sensitivity. Surprisingly, distance metrics that incorporate the biases of somatic hypermutation do not outperform simple Hamming distance. Although errors were more likely in sequences with short junctions, using the entire dataset to choose a single distance threshold for clustering is near optimal. Our results suggest that hierarchical clustering using single linkage with Hamming distance identifies clones with high confidence and provides a fully automated method for clonal grouping. The performance estimates we develop provide important context to interpret clonal analysis of repertoire sequencing data and allow for rigorous testing of other clonal grouping algorithms.

Practical guidelines for B-cell receptor repertoire sequencing analysis

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. Recent applications include the study of autoimmunity, infection, allergy, cancer and aging. As sequencing technologies continue to improve, these repertoire sequencing experiments are producing ever larger datasets, with tens- to hundreds-of-millions of sequences. These data require specialized bioinformatics pipelines to be analyzed effectively. Numerous methods and tools have been developed to handle different steps of the analysis, and integrated software suites have recently been made available. However, the field has yet to converge on a standard pipeline for data processing and analysis. Common file formats for data sharing are also lacking. 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. 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. 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.