scholarly journals Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data: Table 1.

2015 ◽  
Vol 31 (20) ◽  
pp. 3356-3358 ◽  
Author(s):  
Namita T. Gupta ◽  
Jason A. Vander Heiden ◽  
Mohamed Uduman ◽  
Daniel Gadala-Maria ◽  
Gur Yaari ◽  
...  
Keyword(s):  
B Cell ◽  
Large Scale ◽  
Sequencing Data ◽  
Data Table ◽  
Repertoire Sequencing ◽  
Immunoglobulin Repertoire

scholarly journals Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles

2015 ◽  
Vol 112 (8) ◽  
pp. E862-E870 ◽  
Author(s):  
Daniel Gadala-Maria ◽  
Gur Yaari ◽  
Mohamed Uduman ◽  
Steven H. Kleinstein
Keyword(s):  
B Cell ◽  
Large Scale ◽  
Gene Segment ◽  
Automated Analysis ◽  
Sequencing Data ◽  
Cell Repertoire ◽  
Accurate Analysis ◽  
V Genes ◽  
Repertoire Sequencing ◽  
Novel Alleles

Individual variation in germline and expressed B-cell immunoglobulin (Ig) repertoires has been associated with aging, disease susceptibility, and differential response to infection and vaccination. Repertoire properties can now be studied at large-scale through next-generation sequencing of rearranged Ig genes. Accurate analysis of these repertoire-sequencing (Rep-Seq) data requires identifying the germline variable (V), diversity (D), and joining (J) gene segments used by each Ig sequence. Current V(D)J assignment methods work by aligning sequences to a database of known germline V(D)J segment alleles. However, existing databases are likely to be incomplete and novel polymorphisms are hard to differentiate from the frequent occurrence of somatic hypermutations in Ig sequences. Here we develop a Tool for Ig Genotype Elucidation via Rep-Seq (TIgGER). TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.

scholarly journals Polymorphisms in immunoglobulin heavy chain variable genes and their upstream regions

2020 ◽  
Author(s):  
Ivana Mikocziova ◽  
Moriah Gidoni ◽  
Ida Lindeman ◽  
Ayelet Peres ◽  
Omri Snir ◽  
...  
Keyword(s):  
B Cell ◽  
Disease Susceptibility ◽  
Genomic Variation ◽  
B Cell Receptors ◽  
Sequencing Data ◽  
Repertoire Sequencing ◽  
V Region ◽  
Immunoglobulin Repertoire ◽  
Novel Alleles ◽  
High Degree

ABSTRACTGermline variations in immunoglobulin genes influence the repertoire of B cell receptors and antibodies, and such polymorphisms may impact disease susceptibility. However, the knowledge of the genomic variation of the immunoglobulin loci is scarce. Here, we report 25 novel germline IGHV alleles as inferred from rearranged naïve B cell cDNA repertoires of 98 individuals. Thirteen novel alleles were selected for validation, out of which ten were successfully confirmed by targeted amplification and Sanger sequencing of non-B cell DNA. Moreover, we detected a high degree of variability upstream of the V-region in the 5’UTR, leader 1, and leader 2 sequences, and found that identical V-region alleles can differ in upstream sequences. Thus, we have identified a large genetic variation not only in the V-region but also in the upstream sequences of IGHV genes. Our findings challenge current approaches used for annotating immunoglobulin repertoire sequencing data.

scholarly journals Polymorphisms in human immunoglobulin heavy chain variable genes and their upstream regions

2020 ◽  
Vol 48 (10) ◽  
pp. 5499-5510 ◽  
Author(s):  
Ivana Mikocziova ◽  
Moriah Gidoni ◽  
Ida Lindeman ◽  
Ayelet Peres ◽  
Omri Snir ◽  
...  
Keyword(s):  
B Cell ◽  
Disease Susceptibility ◽  
Genomic Variation ◽  
Sequencing Data ◽  
Repertoire Sequencing ◽  
V Region ◽  
Immunoglobulin Repertoire ◽  
New Perspective ◽  
Novel Alleles ◽  
High Degree

Abstract Germline variations in immunoglobulin genes influence the repertoire of B cell receptors and antibodies, and such polymorphisms may impact disease susceptibility. However, the knowledge of the genomic variation of the immunoglobulin loci is scarce. Here, we report 25 potential novel germline IGHV alleles as inferred from rearranged naïve B cell cDNA repertoires of 98 individuals. Thirteen novel alleles were selected for validation, out of which ten were successfully confirmed by targeted amplification and Sanger sequencing of non-B cell DNA. Moreover, we detected a high degree of variability upstream of the V-REGION in the 5′UTR, L-PART1 and L-PART2 sequences, and found that identical V-REGION alleles can differ in upstream sequences. Thus, we have identified a large genetic variation not only in the V-REGION but also in the upstream sequences of IGHV genes. Our findings provide a new perspective for annotating immunoglobulin repertoire sequencing data.

scholarly journals SCIGA: Software for large-scale, single-cell immunoglobulin repertoire analysis

GigaScience ◽  
2021 ◽  
Vol 10 (9) ◽  
Author(s):  
Haocheng Ye ◽  
Lin Cheng ◽  
Bin Ju ◽  
Gang Xu ◽  
Yang Liu ◽  
...  
Keyword(s):  
B Cell ◽  
Single Cell ◽  
Light Chain ◽  
Neutralizing Antibodies ◽  
Large Scale ◽  
Specialized Software ◽  
Repertoire Analysis ◽  
Multiple Sample ◽  
Immunoglobulin Repertoire ◽  
Diverse Data

Abstract Background B-cell immunoglobulin repertoires with paired heavy and light chain can be determined by means of 10X single-cell V(D)J sequencing. Precise and quick analysis of 10X single-cell immunoglobulin repertoires remains a challenge owing to the high diversity of immunoglobulin repertoires and a lack of specialized software that can analyze such diverse data. Findings In this study, specialized software for 10X single-cell immunoglobulin repertoire analysis was developed. SCIGA (Single-Cell Immunoglobulin Repertoire Analysis) is an easy-to-use pipeline that performs read trimming, immunoglobulin sequence assembly and annotation, heavy and light chain pairing, statistical analysis, visualization, and multiple sample integration analysis, which is all achieved by using a 1-line command. Then SCIGA was used to profile the single-cell immunoglobulin repertoires of 9 patients with coronavirus disease 2019 (COVID-19). Four neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified from these repertoires. Conclusions SCIGA provides a complete and quick analysis for 10X single-cell V(D)J sequencing datasets. It can help researchers to interpret B-cell immunoglobulin repertoires with paired heavy and light chain.

scholarly journals A framework for annotation of antigen specificities in high-throughput T-cell repertoire sequencing studies

2019 ◽  
Author(s):  
Mikhail V Pogorelyy ◽  
Mikhail Shugay
Keyword(s):  
T Cell ◽  
Large Scale ◽  
Cell Receptor ◽  
Specific Response ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Antigen Specificity ◽  
Cell Repertoire ◽  
Sequencing Studies ◽  
Repertoire Sequencing

AbstractRecently developed molecular methods allow large-scale profiling of T-cell receptor (TCR) sequences that encode for antigen specificity and immunological memory of these cells. However, it is well known, that the even unperturbed TCR repertoire structure is extremely complex due to the high diversity of TCR rearrangements and multiple biases imprinted by VDJ rearrangement process. The latter gives rise to the phenomenon of “public” TCR clonotypes that can be shared across multiple individuals and non-trivial structure of the TCR similarity network. Here we outline a framework for TCR sequencing data analysis that can control for these biases in order to infer TCRs that are involved in response to antigens of interest. Using an example dataset of donors with known HLA haplotype and CMV status we demonstrate that by applying HLA restriction rules and matching against a database of TCRs with known antigen specificity it is possible to robustly detect motifs of an epitope-specific responses in individual repertoires. We also highlight potential shortcomings of TCR clustering methods and demonstrate that highly expanded TCRs should be individually assessed to get the full picture of antigen-specific response.

scholarly journals Exploring Human Antimicrobial Antibody Responses on a Single B Cell Level

2017 ◽  
Vol 24 (5) ◽  
Author(s):  
Daniel Hofmann ◽  
Jonathan R. Lai
Keyword(s):  
B Cell ◽  
Vaccine Design ◽  
Antibody Responses ◽  
Cell Cloning ◽  
Protective Antibody ◽  
Functional Activities ◽  
Variable Domains ◽  
Repertoire Sequencing ◽  
Immunoglobulin Repertoire

ABSTRACT Analysis of monoclonal antibodies (MAbs) derived from single B cell cloning has been highly beneficial for antimicrobial immunotherapy, vaccine design, and advancing our understanding of pathogen-triggered effects on the human immunoglobulin repertoire. Sequencing of variable domains of single B cells, and characterization of binding and functional activities of MAbs derived from those sequences, provides in-depth insight not only into sites of susceptibility for antibody-mediated neutralization or opsonization of the pathogen but also into the dynamics of protective antibody evolution during infection. This information can be utilized to rapidly develop novel immunotherapies of completely human origin and provides a roadmap for structure-based vaccine design that aims to elicit similar protective antibody responses. Here, we summarize recent aspects of the single B cell cloning approach.

scholarly journals The influence of the phylogenetic inference pipeline on murine antibody repertoire sequencing data following viral infection

2020 ◽  
Author(s):  
Alexander Yermanos ◽  
Victor Greiff ◽  
Tanja Stadler ◽  
Annette Oxenius ◽  
Sai T. Reddy
Keyword(s):  
B Cell ◽  
Neutralizing Antibodies ◽  
Clonal Selection ◽  
Phylogenetic Inference ◽  
Antibody Repertoire ◽  
Sequencing Data ◽  
Cell Evolution ◽  
Wide Range ◽  
Repertoire Sequencing ◽  
Inference Methods

AbstractUnderstanding B cell evolution following vaccination or infection is crucial for instructing targeted immunotherapies when searching for potential therapeutic or virus-neutralizing antibodies. Antibody phylogenetics holds the potential to quantify both clonal selection and somatic hypermutation, two key players shaping B cell evolution. A wide range of bioinformatic pipelines and phylogenetic inference methods have been utilized on antibody repertoire sequencing datasets to delineate B cell evolution. Although the majority of B cell repertoire studies incorporate some aspect of antibody evolution, how the chosen computational methods affect the results is largely ignored. Therefore, we performed an extensive computational analysis on time-resolved antibody repertoire sequencing data to better characterize how commonly employed bioinformatic practices influence conclusions regarding antibody selection and evolution. Our findings reveal that different combinations of clonal lineage assignment strategies, phylogenetic inference methods, and biological sampling affect the inferred size, mutation rates, and topologies of B cell lineages in response to virus infection.

scholarly journals The fundamental principles of antibody repertoire architecture revealed by large-scale network analysis

2017 ◽  
Author(s):  
Enkelejda Miho ◽  
Victor Greifft ◽  
Rok Roškar ◽  
Sai T. Reddy
Keyword(s):  
Network Analysis ◽  
B Cell ◽  
High Performance ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Antibody Repertoire ◽  
Sequencing Data ◽  
Cell Receptors ◽  
Computing Platform ◽  
Antibody Repertoires

ABSTRACTThe antibody repertoire is a vast and diverse collection of B-cell receptors and antibodies that confer protection against a plethora of pathogens. The architecture of the antibody repertoire, defined by the network similarity landscape of its sequences, is unknown. Here, we established a novel high-performance computing platform to construct large-scale networks from high-throughput sequencing data (>100’000 unique antibodies), in order to uncover the architecture of antibody repertoires. We identified three fundamental principles of antibody repertoire architecture across B-cell development: reproducibility, robustness and redundancy. Reproducibility of network structure explains clonal expansion and selection. Robustness ensures a functional immune response even under extensive loss of clones (50%). Redundancy in mutational pathways suggests that there is a pre-programmed evolvability in antibody repertoires. Our analysis provides guidelines for a quantitative network analysis of antibody repertoires, which can be applied to other facets of adaptive immunity (e.g., T cell receptors), and may direct the construction of synthetic repertoires for biomedical applications.

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