Biology subjects

Stubbington, M. J. T.

Publications and source records attributed to Stubbington, M. J. T..

5 recordsLinked to original sources

bioRxiv2020

IL-7R signalling activates widespread VH and DH gene usage to drive antibody diversity in bone marrow B cells

Generation of the primary antibody repertoire requires V(D)J recombination of hundreds of gene segments in the immunoglobulin heavy chain (Igh) locus. It has been proposed that interleukin-7 receptor (IL-7R) signalling is necessary for Igh recombination, but this has been challenging to partition from the receptors role in B cell survival and proliferation. By generating the first detailed description of the Igh repertoire of murine IL-7R-/- bone marrow B cells, we demonstrate that IL-7R signalling profoundly influences VH gene selection during VH-to-DJH recombination. We find skewing towards usage of 3 VH genes during de novo VH-to-DJH recombination that is more severe than the fetal liver (FL) B cell repertoire, and we now show a role for IL-7R signalling in DH-to-JH recombination. Transcriptome and accessibility analyses suggests reduced expression of B lineage-specific transcription factors (TFs) and their targets, and loss of DH and VH antisense transcription in IL-7R-/- B cells. These results refute models suggesting that IL-7R signalling is only required for survival and proliferation, and demonstrate a pivotal role in shaping the Igh repertoire by activating underpinning epigenetic mechanisms.

immunology↗

bioRxiv2020

Linking T cell receptor sequence to transcriptional profiles with clonotype neighbor graph analysis (CoNGA)

Multi-modal single-cell technologies capable of simultaneously assaying gene expression and surface phenotype across large numbers of immune cells have described extensive heterogeneity within these complex populations, in healthy and diseased states. In the case of T cells, these technologies have made it possible to profile clonotype, defined by T cell receptor (TCR) sequence, and phenotype, as reflected in gene expression (GEX) profile, surface protein expression, and peptide:MHC (pMHC) binding, across large and diverse cell populations. These rich, high-dimensional datasets have the potential to reveal new relationships between TCR sequence and T cell phenotype that go beyond identification of features shared by clonally related cells. In order to uncover these connections in an unbiased way, we developed a graph-theoretic approach---clonotype neighbor-graph analysis or "CoNGA"---that identifies correlations between GEX profile and TCR sequence through statistical analysis of a pair of T cell similarity graphs, one in which cells are linked based on gene expression similarity and another in which cells are linked by similarity of TCR sequence. Applying CoNGA across diverse human and mouse T cell datasets uncovered known and novel associations between TCR sequence features and cellular phenotype including the classical invariant T cell subsets; a novel defined population of human blood CD8+ T cells expressing the transcription factors HOBIT and HELIOS, NK-associated receptors, and a biased TCR repertoire, representing a potential previously undescribed lineage of "natural lymphocytes"; a striking association between usage of a specific V-beta gene segment and expression of the EPHB6 gene that is conserved between mouse and human; and TCR sequence determinants of differentiation in developing thymocytes. As the size and scale of single-cell datasets continue to grow, we expect that CoNGA will prove to be a useful tool for deconvolving complex relationships between TCR sequence and cellular state in single-cell applications.

immunology↗

bioRxiv2019

scHLAcount: Allele-specific HLA expression from single-cell gene expression data

Studies in bulk RNA sequencing data suggest cell-type and allele-specific expression of the human leukocyte antigen (HLA) genes. These loci are extremely diverse and they function as part of the major histocompatibility complex (MHC) which is responsible for antigen presentation. Mutation and or misregulation of expression of HLA genes has implications in diseases, especially cancer. Immune responses to tumor cells can be evaded through HLA loss of function. However, bulk RNA-seq does not fully disentangle cell type specificity and allelic expression. Here we present scHLAcount, a workflow for computing allele-specific molecule counts of the HLA genes in single cells an individualized reference. We demonstrate that scHLAcount can be used to find cell-type specific allelic expression of HLA genes in blood cells, and detect different allelic expression patterns between tumor and normal cells in patient biopsies. scHLAcount is available at https://github.com/10XGenomics/scHLAcount.

bioinformatics↗

bioRxiv2019

Decoding the development of the blood and immune systems during human fetal liver haematopoiesis

Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells/multipotent progenitors (HSC/MPPs), yet remains poorly defined in humans. Using single cell transcriptome profiling of ~133,000 fetal liver and ~65,000 fetal skin and kidney cells, we identify the repertoire of blood and immune cells in first and early second trimesters of development. From this data, we infer differentiation trajectories from HSC/MPPs, and evaluate the impact of tissue microenvironment on blood and immune cell development. We predict coupling of mast cell differentiation with erythro-megakaryopoiesis and identify physiological erythropoiesis in fetal skin. We demonstrate a shift in fetal liver haematopoietic composition during gestation away from being erythroid-predominant, accompanied by a parallel change in HSC/MPP differentiation potential, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a valuable reference for understanding and harnessing the therapeutic potential of HSC/MPPs.

developmental biology↗

bioRxiv2017

BraCeR: Reconstruction of B-cell receptor sequences and clonality inference from single-cell RNA-sequencing

Reconstruction of antigen receptor sequences from single-cell RNA-sequencing (scRNA-seq) data allows the linking of antigen receptor usage to the full transcriptomic identity of individual B lymphocytes, without having to perform additional targeted repertoire sequencing (Rep-seq). Here we report BraCeR (freely available at https://github.com/teichlab/bracer/), an extension of TraCeR [1], for reconstruction of paired full-length B-cell receptor sequences and inference of clonality from scRNA-seq data (Supplementary Note 1).

bioinformatics↗