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Young, M. D.

Publications and source records attributed to Young, M. D..

3 recordsLinked to original sources

A novel innate lymphoid cell delineates childhood autoimmune arthritis

Inflammation in autoimmune disease is mediated by a complex network of interacting cells. Their identity and cross-talk are encoded in messenger RNA (mRNA). Juvenile idiopathic arthritis (JIA), a chronic autoimmune arthritis of childhood, is characterised by synovial inflammation with infiltration of both innate and adaptive immune cells1. Activated T cells play a role in disease2 but the cell types that drive the recruitment and activation of immune cells within the synovium are not known. Here, we utilised droplet-based and full length single cell mRNA sequencing to obtain a quantitative map of the cellular landscape of JIA. We studied 45,715 cells from the synovial fluid of inflamed knee joints and peripheral blood. We identified a population of synovial innate lymphoid cells (ILCs), shared across patients, that exhibited a unique transcriptional profile in comparison to canonical ILC subtypes. Validation at protein-level across a spectrum of autoimmune arthritides revealed that these ILCs are pathologically expanded in a particular type of JIA. Using statistical tools to assess cellular interactions in synovial fluid, ILCs emerged as a central node of communication, expressing the full repertoire of genes required to orchestrate and maintain the inflammatory milieu. Several ILC-mediated signalling pathways may lend themselves as novel therapeutic targets. Together our findings demonstrate a distinct ILC subtype associated with a tissue-specific childhood autoimmune disease.

immunology

SoupX removes ambient RNA contamination from droplet based single cell RNA sequencing data

BackgroundDroplet based single-cell RNA sequence analyses assume all acquired RNAs are endogenous to cells. However, any cell free RNAs contained within the input solution are also captured by these assays. This sequencing of cell free RNA constitutes a background contamination that confounds the biological interpretation of single-cell transcriptomic data. ResultsWe demonstrate that contamination from this soup of cell free RNAs is ubiquitous, with experiment-specific variations in composition and magnitude. We present a method, SoupX, for quantifying the extent of the contamination and estimating background corrected cell expression profiles that seamlessly integrate with existing downstream analysis tools. Applying this method to several datasets using multiple droplet sequencing technologies, we demonstrate that its application improves biological interpretation of otherwise misleading data, as well as improving quality control metrics. ConclusionsWe present SoupX, a tool for removing ambient RNA contamination from droplet based single cell RNA sequencing experiments. This tool has broad applicability and its application can improve the biological utility of existing and future data sets. Key PointsO_LIThe signal from droplet based single cell RNA sequencing is ubiquitously contaminated by capture of ambient mRNA. C_LIO_LISoupX is a method to quantify the abundance of these ambient mRNAs and remove them. C_LIO_LICorrecting for ambient mRNA contamination improves biological interpretation. C_LI

bioinformatics

An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures

Anaplastic meningioma is a rare and aggressive brain tumor characterised by intractable recurrences and dismal outcomes. Here, we present an integrated analysis of the whole genome, transcriptome and methylation profiles of primary and recurrent anaplastic meningioma. A key finding was the delineation of two distinct molecular subgroups that were associated with diametrically opposed survival outcomes. Relative to lower grade meningiomas, anaplastic tumors harbored frequent driver mutations in SWI/SNF complex genes, which were confined to the poor prognosis subgroup. Our analyses discern two biologically distinct variants of anaplastic meningioma with potential prognostic and therapeutic significance.

genomics