Inflammatory pathways are central to posterior cerebrovascular artery remodelling prior to the onset of congenital hypertension

Cerebral artery hypoperfusion may provide the basis for linking ischemic stroke with hypertension. Brain hypoperfusion may induce hypertension that may serve as an auto-protective mechanism to prevent ischemic stroke. We hypothesised that hypertension is caused by remodelling of the cerebral arteries, which is triggered by inflammation. We used a congenital rat model of hypertension and examined age-related changes in gene expression of the cerebral arteries using RNA sequencing. Prior to hypertension, we found changes in signalling pathways associated with the immune system and fibrosis. Validation studies using second harmonics generation microscopy revealed upregulation of collagen type I and IV in both tunica externa and media. These changes in the extracellular matrix of cerebral arteries pre-empted hypertension accounting for their increased stiffness and resistance, both potentially conducive to stroke. These data indicate that inflammatory driven cerebral artery remodelling occurs prior to the onset of hypertension and may be a trigger elevating systemic blood pressure in genetically programmed hypertension. </jats:p

Supporting code for "Molecular phenotyping reveals the identity of Barrett's esophagus and its malignant transition"

Supporting code for "Molecular phenotyping reveals the identity of Barrett's esophagus and its malignant transition" manuscript This repository contains all steps required for analysis and production of figures as presented in the "Molecular phenotyping reveals the identity of Barrett's esophagus and its malignant transition" manuscript. Scripts are split into the following folders: Preprocessing This folder contains low level steps using in the analysis of data. The analysis follows a stepwise process: 1.4_Quality_control.Rmd Contains script used for the reading of raw count data output from Cell Ranger v3.0.1 count function. The reads were aligned to GRCh38.92 gencode annotation. Quality control includes assessment of proportion of reads mapping to mitochondrial genes, removal of cells with low read and feature count and high proportion of reads mapped to mitochondrial RNA. The selection criteria are described in Table S1 of the manuscript. 2.4_Normalization_filtered.Rmd Read count normalisation within individual samples 3.4_Further_processing_filtered.Rmd Clustering of cells within individual samples. 4.4_Tissue_correction_filtered.Rmd Batch correction and clustering of individual cells with individual tissue types 5.4_Reclustering.Rmd In the case of NSCJ we identified novel cell type. This cell type seem to be comprised of four additional cell types. Code associated with this reclustering is here. Further, in the BSCJ NOUROG3 and Goblet cells were not separated into two clusters in step 4.4. Additional reclustering is performed here. 6.4_Full_data_batch_correction_filtered.Rmd This code includes full data integration across all tissue types and samples. 7.4_Cluster_annotation.Rmd This code introduces manually annoted cell types into SingleCellExperiment containing all high quality filtered cell types. Figures All code used for generation of figures within the manuscript are located within that folder. The name of hte files corresponds to individual figures. Please note that in additional to the images used within the manuscripts, code also contains information for generation of diagnostic figures within each analysis. Analysis/Functions Functions associated with the analysis are located in the auxiliary.R file. Analysis/Battenberg Contains steps used in the low level analysis of WGS samples using Battenberg and DPClus

EINCR1 is an EGF inducible lincRNA overexpressed in lung adenocarcinomas

Long non-coding RNAs are being increasingly recognised as important molecules involved in regulating a diverse array of biological functions. For example, many long non-coding RNAs have been associated with tumourigenesis and in this context their molecular functions often involves impacting on chromatin and transcriptional control processes. One important cellular control system that is often deregulated in cancer cells is the ERK MAP kinase pathway. Here we have investigated whether ERK pathway signaling in response to EGF stimulation, leads to changes in the production of long non-coding RNAs. We identify several different classes of EGF pathway-regulated lncRNAs. We focus on one of the inducible lincRNAs, EGF inducible long intergenic non-coding RNA 1 (EINCR1). EINCR1 is predominantly nuclear and shows delayed activation kinetics compared to other immediate-early EGF-inducible genes. In humans it is expressed in a tissue-specific manner and is mainly confined to the heart but it exhibits little evolutionary conservation. Importantly, in several cancers EINCR1 shows elevated expression levels which correlate with poor survival in lung adenocarcinoma patients. In the context of lung adenocarcinomas, EINCR1 expression is anti-correlated with the expression of several protein coding EGF-regulated genes. A potential functional connection is demonstrated as EINCR1 overexpression is shown to reduce the expression of EGF-regulated protein coding genes including FOS and FOSB

The mutREAD method detects mutational signatures from low quantities of cancer DNA

Funder: We thank the Human Research Tissue Bank, which is supported by the UK National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, from Addenbrooke’s Hospital. Additional infrastructure support was provided from the Cancer Research UK–funded Experimental Cancer Medicine CentreAbstract: Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings

The mutREAD method detects mutational signatures from low quantities of cancer DNA

Funder: We thank the Human Research Tissue Bank, which is supported by the UK National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, from Addenbrooke’s Hospital. Additional infrastructure support was provided from the Cancer Research UK–funded Experimental Cancer Medicine CentreAbstract: Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings

The mutREAD method detects mutational signatures from low quantities of cancer DNA

Sequencing tumour genomes can reveal information about the processes that drive the formation of cancer. Here, the authors describe a method that can detect these mutational signatures from small amounts of DNA and degraded samples

Complexities in the role of acetylation dynamics in modifying inducible gene activation parameters.

High levels of histone acetylation are associated with the regulatory elements of active genes, suggesting a link between acetylation and gene activation. We revisited this model, in the context of EGF-inducible gene expression and found that rather than a simple unifying model, there are two broad classes of genes; one in which high lysine acetylation activity is required for efficient gene activation, and a second group where the opposite occurs and high acetylation activity is inhibitory. We examined the latter class in more detail using EGR2 as a model gene and found that lysine acetylation levels are critical for several activation parameters, including the timing of expression onset, and overall amplitudes of the transcriptional response. In contrast, DUSP1 responds in the canonical manner and its transcriptional activity is promoted by acetylation. Single cell approaches demonstrate heterogenous activation kinetics of a given gene in response to EGF stimulation. Acetylation levels modify these heterogenous patterns and influence both allele activation frequencies and overall expression profile parameters. Our data therefore point to a complex interplay between acetylation equilibria and target gene induction where acetylation level thresholds are an important determinant of transcriptional induction dynamics that are sensed in a gene-specific manner