Biology subjects

Yaari, G.

Publications and source records attributed to Yaari, G..

27 records · Page 2Linked to original sources

bioRxiv2021

Alternative splice variants and germline polymorphisms in human immunoglobulin light chain genes

Immunoglobulin loci are rich in germline polymorphisms and identification of novel polymorphic variants can be facilitated by germline inference of B cell receptor repertoires. Germline gene inference is complicated by somatic hypermutations, errors arising from PCR amplification, and DNA sequencing as well as from the varying length of reference alleles. Inference of light chain genes is even more challenging than inference of heavy chain genes due to large gene duplication events on the kappa locus as well as absence of D genes in the rearranged light chain transcripts. Here, we analyzed the light chain cDNA sequences from naive BCR repertoires of a Norwegian cohort of 100 individuals. We optimized light chain allele inference by tweaking parameters within TIgGER functions, extending the germline reference sequences, and establishing mismatch frequency patterns at polymorphic positions to filter out false positive candidates. As a result, we identified 48 previously unreported variants of light chain variable genes. Altogether, we selected 14 candidates for novel light chain polymorphisms for validation and successfully validated 11 by Sanger sequencing. Additional clustering of light chain 5UTR, L-PART1 and L-PART2 revealed partial intron retention in alternative splice variants in 11 kappa and 9 lambda V alleles. The alternatively spliced transcripts were only observed in genes with low expression levels, suggesting a possible role in expression regulation. Our results provide novel insight into germline variation in human light chain immunoglobulin loci.

genetics↗

bioRxiv2020

Machine learning analysis of naïve B-cell receptor repertoires stratifies celiac disease patients and controls

Celiac disease (CeD) is a common autoimmune disorder caused by an abnormal immune response to dietary gluten proteins. The disease has high heritability. HLA is the major susceptibility factor, and the HLA effect is mediated via presentation of deamidated gluten peptides by disease-associated HLA-DQ variants to CD4+ T cells. In addition to gluten-specific CD4+ T cells the patients have antibodies to transglutaminase 2 (autoantigen) and deamidated gluten peptides. These disease-specific antibodies recognize defined epitopes and they display common usage of specific heavy and light chains across patients. Interactions between T cells and B cells are likely central in the pathogenesis, but how the repertoires of naive T and B cells relate to the pathogenic effector cells is unexplored. To this end, we applied machine learning classification models to naive B cell receptor (BCR) repertoires from CeD patients and healthy controls. Strikingly, we obtained a promising classification performance with an F1 score of 85%. Clusters of heavy and light chain sequences were inferred and used as features for the model, and signatures associated with the disease were then characterized. These signatures included amino acid (AA) 3-mers with distinct bio-physiochemical characteristics and enriched V and J genes. We found that CeD-associated clusters can be identified and that common motifs can be characterized from naive BCR repertoires. The results may indicate a genetic influence by BCR encoding genes in CeD. Analysis of naive BCRs as presented here may become an important part of assessing the risk of individuals to develop CeD. Our model demonstrates the potential of using BCR repertoires and in particular, naive BCR repertoires, as disease susceptibility markers.

immunology↗

bioRxiv2020

Multi-Clonal Live SARS-CoV-2 In Vitro Neutralization by Antibodies Isolated from Severe COVID-19 Convalescent Donors

The interactions between antibodies, SARS-CoV-2 and immune cells contribute to the pathogenesis of COVID-19 and protective immunity. To understand the differences between antibody responses in mild versus severe cases of COVID-19, we analyzed the B cell responses in patients 1.5 months post SARS-CoV-2 infection. Severe and not mild infection correlated with high titers of IgG against Spike receptor binding domain (RBD) that were capable of viral inhibition. B cell receptor (BCR) sequencing revealed two VH genes, VH3-38 and VH3-53, that were enriched during severe infection. Of the 22 antibodies cloned from two severe donors, six exhibited potent neutralization against live SARS-CoV-2, and inhibited syncytia formation. Using peptide libraries, competition ELISA and RBD mutagenesis, we mapped the epitopes of the neutralizing antibodies (nAbs) to three different sites on the Spike. Finally, we used combinations of nAbs targeting different immune-sites to efficiently block SARS-CoV-2 infection. Analysis of 49 healthy BCR repertoires revealed that the nAbs germline VHJH precursors comprise up to 2.7% of all VHJHs. We demonstrate that severe COVID-19 is associated with unique BCR signatures and multi-clonal neutralizing responses that are relatively frequent in the population. Moreover, our data support the use of combination antibody therapy to prevent and treat COVID-19.

immunology↗

bioRxiv2020

Polymorphisms in immunoglobulin heavy chain variable genes and their upstream regions

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 novel germline IGHV alleles as inferred from rearranged naive 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 5UTR, 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.

immunology↗

bioRxiv2019

Applications of community detection algorithms to large biological datasets

Recent advances in data acquiring technologies in biology have led to major challenges in mining relevant information from large datasets. For example, single-cell RNA sequencing technologies are producing expression and sequence information from tens of thousands of cells in every single experiment. A common task in analyzing biological data is to cluster samples or features (e.g. genes) into groups sharing common characteristics. This is an NP-hard problem for which numerous heuristic algorithms have been developed. However, in many cases, the clusters created by these algorithms do not reflect biological reality. To overcome this, a Networks Based Clustering (NBC) approach was recently proposed, by which the samples or genes in the dataset are first mapped to a network and then community detection (CD) algorithms are used to identify clusters of nodes. Here, we created an open and flexible python-based toolkit for NBC that enables easy and accessible network construction and community detection. We then tested the applicability of NBC for identifying clusters of cells or genes from previously published large-scale single-cell and bulk RNA-seq datasets. We show that NBC can be used to accurately and efficiently analyze large-scale datasets of RNA sequencing experiments.

bioinformatics↗

bioRxiv2018

Axonal tree morphology and signal propagation dynamics improve neuronal classification

Classification of neurons into specific subtypes is essential for better understanding of brain function and information transmission. Despite continuous progress, there is still no consensus regarding categorizing neuron taxonomy into proper subtypes. Current morphology-based classification approaches largely rely on the dendritic tree structure or on the general axonal projection layout. In this study, we support the use of a morphology-based classification approach, focusing on the axonal tree. We demonstrate that utilizing the geometrical parameters of axonal tree structures significantly improves neuronal classification compared to the dendritic tree classification. Furthermore, we used neuronal activity patterns to classify interneurons into subtypes as well. Simulations of the activity along ramified axonal trees indicate that the axonal branching geometry may yield diverse responses in different subtrees. The classification schemes introduced here can be utilized to robustly classify neuronal subtypes in a functionally relevant manner. Our results open the door for deducing functionality from anatomical data.

neuroscience↗

bioRxiv2018

Identification of subject-specific immunoglobulin alleles from expressed repertoire sequencing data

The adaptive immune receptor repertoire (AIRR) contains information on an individuals immune past, present and potential in the form of the evolving sequences that encode the B cell receptor (BCR) repertoire. AIRR sequencing (AIRR-seq) studies rely on databases of known BCR germline variable (V), diversity (D) and joining (J) genes to detect somatic mutations in AIRR-seq data via comparison to the best-aligning database alleles. However, it has been shown that these databases are far from complete, leading to systematic misidentification of mutated positions in subsets of sample sequences. We previously presented TIgGER, a computational method to identify subject-specific V gene genotypes, including the presence of novel V gene alleles, directly from AIRR-seq data. However, the original algorithm was unable to detect alleles that differed by more than 5 single nucleotide polymorphisms (SNPs) from a database allele. Here we present and apply an improved version of the TIgGER algorithm which can detect alleles that differ by any number of SNPs from the nearest database allele, and can construct subject-specific genotypes with minimal prior information. TIgGER predictions are validated both computationally (using a leave-one-out strategy) and experimentally (using genomic sequencing), resulting in the addition of three new immunoglobulin heavy chain V (IGHV) gene alleles to the IMGT repertoire. Finally, we develop a Bayesian strategy to provide a confidence estimate associated with genotype calls. All together, these methods allow for much higher accuracy in germline allele assignment, an essential step in AIRR-seq studies.

bioinformatics↗

bioRxiv2018

Mice developing mammary tumors evolve T cell sequences shared with human breast cancer patients

Cancer immunotherapy by checkpoint blockade proves that an effective immune response to a tumor can be induced clinically. However, little is known about the evolution of tumor-associated T-cell receptor (TCR) repertoires without intervention. Here we studied TCR repertoire evolution in mice spontaneously developing mammary tumors; we sequenced peripheral blood alpha and beta TCRs of CD4+CD62L+CD44- T cells monthly for 8 months in 10 FVB/NJ mice transgenic at the Erbb2 locus, all developing tumors; 5 FVB/NJ mice without the transgene were age-matched controls. Sequences were either private (restricted to one mouse) or public (shared among mice); public sequences were either exclusive to the tumor group or inclusive among different groups. We now report that 1), public AA sequences were each encoded by many different nucleotide sequences (NT) recombinations (convergent recombination; CR); 2) mice developing tumors evolved tumor-exclusive public sequences, derived initially from private or from inclusive public sequences; and 3) tumor-exclusive public sequences in mice were also present among published public TCR sequences from human breast cancer patients. These cross-species tumor-exclusive TCR sequences manifested high CR; but the AA sequences shared by mice and humans did not share NT sequences. Thus, tumor-exclusive TCR AA sequences across species are selected from different NT recombination events. The roles of tumor-exclusive TCR repertoires in advancing or inhibiting tumor development and the effects of tumor immunotherapy on these T cells remain to be seen.

cancer biology↗

bioRxiv2018

Mosaic deletion patterns of the human antibody heavy chain gene locus

Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding antibody genes is incomplete, mostly due to technical difficulties in aligning short reads to these highly repetitive loci. The partial knowledge results in conflicting V-D-J gene assignments between different algorithms, and biased genotype and haplotype inference. Previous studies have shown that haplotypes can be inferred by taking advantage of IGHJ6 heterozygosity, observed in approximately one third of the population. Here, we propose a robust novel method for determining V-D-J haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, thereby enabling inference of complex genetic events like deletions and copy number variations in the entire population. We generated the largest multi individual data set, to date, of naive B-cell repertoires, and tested our method on it. We present evidence for allele usage bias, as well as a mosaic, tiled pattern of deleted and present IGHD and IGHV nearby genes, across the population. The inferred haplotypes and deletion patterns may have clinical implications for genetic predispositions to diseases. Our findings greatly expand the knowledge that can be extracted from antibody repertoire sequencing data.

genomics↗