IgE-associated IGHV genes from venom and peanut allergic individuals lack mutational evidence of antigen selection.

Antigen selection of B cells within the germinal center reaction generally leads to the accumulation of replacement mutations in the complementarity-determining regions (CDRs) of immunoglobulin genes. Studies of mutations in IgE-associated VDJ gene sequences have cast doubt on the role of antigen selection in the evolution of the human IgE response, and it may be that selection for high affinity antibodies is a feature of some but not all allergic diseases. The severity of IgE-mediated anaphylaxis is such that it could result from higher affinity IgE antibodies.

The inference of phased haplotypes for the immunoglobulin H chain V region gene loci by analysis of VDJ gene rearrangements.

The existence of many highly similar genes in the lymphocyte receptor gene loci makes them difficult to investigate, and the determination of phased "haplotypes" has been particularly problematic. However, V(D)J gene rearrangements provide an opportunity to infer the association of Ig genes along the chromosomes. The chromosomal distribution of H chain genes in an Ig genotype can be inferred through analysis of VDJ rearrangements in individuals who are heterozygous at points within the IGH locus.

Divergent human populations show extensive shared IGK rearrangements in peripheral blood B cells.

We have analysed the transcribed immunoglobulin kappa (IGK) repertoire of peripheral blood B cells from four individuals from two genetically distinct populations, Papua New Guinean and Australian, using high-throughput DNA sequencing. The depth of sequencing data for each individual averaged 5,548 high-quality IGK reads, and permitted genotyping of the inferred IGKV and IGKJ germline gene segments for each individual. All individuals were homozygous at each IGKJ locus and had highly similar inferred IGKV genotypes.

Benchmarking the performance of human antibody gene alignment utilities using a 454 sequence dataset.

Motivation: Immunoglobulin heavy chain genes are formed by recombination of genes randomly selected from sets of IGHV, IGHD and IGHJ genes. Utilities have been developed to identify genes that contribute to observed VDJ rearrangements, but in the absence of datasets of known rearrangements, the evaluation of these utilities is problematic. We have analyzed thousands of VDJ rearrangements from an individual (S22) whose IGHV, IGHD and IGHJ genotype can be inferred from the dataset.

Clustering-based identification of clonally-related immunoglobulin gene sequence sets.

Background: Clonal expansion of B lymphocytes coupled with somatic mutation and antigen selection allow the mammalian humoral immune system to generate highly specific immunoglobulins (IG) or antibodies against invading bacteria, viruses and toxins. The availability of high-throughput DNA sequencing methods is providing new avenues for studying this clonal expansion and identifying the factors guiding the generation of antibodies. The identification of groups of rearranged immunoglobulin gene sequences descended from the same rearrangement (clonally-related sets) in very large sets of sequences is facilitated by the availability of immunoglobulin gene sequence alignment and partitioning software that can accurately predict component germline gene, but has required painstaking visual inspection and analysis of sequences.

Individual variation in the germline Ig gene repertoire inferred from variable region gene rearrangements.

Individual variation in the Ig germline gene repertoire leads to individual differences in the combinatorial diversity of the Ab repertoire, but the study of such variation has been problematic. The application of high-throughput DNA sequencing to the study of rearranged Ig genes now makes this possible. The sequencing of thousands of VDJ rearrangements from an individual, either from genomic DNA or expressed mRNA, should allow their germline IGHV, IGHD, and IGHJ repertoires to be inferred.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data.

Background: The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies.

Results: We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations.

Identifying highly mutated IGHD genes in the junctions of rearranged human immunoglobulin heavy chain genes.

The reliable identification of IGHD genes within human immunoglobulin heavy chains is challenging with up to one third of rearrangements having no identifiable IGHD gene. The short, mutated IGHD genes are generally assumed to be indistinguishable from the N-REGIONS of non-template encoded nucleotides that surround them. In this study we have characterised N-REGIONS, demonstrating the importance of nucleotide composition biases in the addition process, including the formation of homopolymer tracts.

iHMMune-align: hidden Markov model-based alignment and identification of germline genes in rearranged immunoglobulin gene sequences.

Motivation: Immunoglobulin heavy chain (IGH) genes in mature B lymphocytes are the result of recombination of IGHV, IGHD and IGHJ germline genes, followed by somatic mutation. The correct identification of the germline genes that make up a variable VH domain is essential to our understanding of the process of antibody diversity generation as well as to clinical investigations of some leukaemias and lymphomas.

Results: We have developed iHMMune-align, an alignment program that uses a hidden Markov model (HMM) to model the processes involved in human IGH gene rearrangement and maturation.