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8 Generating a genomic-wide transcriptomic atlas of the mammalian cardiovascular system
  1. Hiu-Gwen Tsang1,
  2. Emily L Clark1,
  3. Stephen J Bush1,
  4. David A Hume1,
  5. Brendan M Corcoran2,
  6. Vicky E MacRae1,
  7. Kim M Summers1
  1. 1The Roslin Institute, The University of Edinburgh, Easter Bush, UK
  2. 2The University of Edinburgh, Hospital for Small Animals, Easter Bush, UK

Abstract

The various highly specialised tissues and structures that form the cardiovascular system enable the transport of blood, oxygen and other important molecules throughout the body. Perturbations in this system increase the risk of developing cardiovascular-related disease.

A sheep cardiovascular transcriptomic atlas was generated using RNA-seq to explore gene expression patterns in the mammalian cardiovascular system. Tissues included the cardiac valves, as well as left and right auricles and ventricles. Detailed functional clustering of the sheep transcriptome was performed, where transcripts were grouped according to their expression pattern. This analysis, using the innovative Miru (Kajeka) bioinformatics tool, was based on a gene-to-gene comparison of the expression patterns across analysed samples, using a Pearson correlation matrix (correlation value R≥0.99). Expressed genes in clusters were grouped together according to region-specific roles and specialised cellular functions. Notably, one cluster contained genes with high expression in the auricles in this dataset. The cluster genes were involved in cation channel activity (GO term enrichment analysis returned a Benjamini corrected p-value of 3.4 × 10–2). Genes in this cluster included potassium channel subfamily K member 3 (KCNK3; also known as TWIK-related acid-sensitive K+ channel, TASK1), potassium voltage-gated channel subfamily J member 3 (KCNJ3), and myosin light chain 4 (MYL4). Additionally, a number of genes within this cluster have been implicated in atrial fibrillation, and further genes in this cluster may also be important in atrial function.

This dataset provides a highly valuable resource for understanding gene expression in the mammalian cardiovascular system.

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