Cross-species high-resolution transcriptome profiling suggests biomarkers and therapeutic targets for ulcerative colitis

Background: Ulcerative colitis (UC) is a disorder with unknown etiology, and animal models play an essential role in studying its molecular pathophysiology. Here, we aim to identify common conserved pathological UC-related gene expression signatures between humans and mice that can be used as treatment targets and/or biomarker candidates.Methods: To identify differentially regulated protein-coding genes and non-coding RNAs, we sequenced total RNA from the colon and blood of the most widely used dextran sodium sulfate Ulcerative colitis mouse. By combining this with public human Ulcerative colitis data, we investigated conserved gene expression signatures and pathways/biological processes through which these genes may contribute to disease development/progression.Results: Cross-species integration of human and mouse Ulcerative colitis data resulted in the identification of 1442 genes that were significantly differentially regulated in the same direction in the colon and 157 in blood. Of these, 51 genes showed consistent differential regulation in the colon and blood. Less known genes with importance in disease pathogenesis, including SPI1, FPR2, TYROBP, CKAP4, MCEMP1, ADGRG3, SLC11A1, and SELPLG, were identified through network centrality ranking and validated in independent human and mouse cohorts.Conclusion: The identified Ulcerative colitis conserved transcriptional signatures aid in the disease phenotyping and future treatment decisions, drug discovery, and clinical trial design

Broadening the miRNA Catalogue in Livestock Species

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Mapping of tissue names to Brenda Tissue Ontology terms

These files contain the mapping from tissue names to Brenda Tissue Ontology terms for the tissue expression datasets used in the publication TISSUES 2.0: An integrative web resource on mammalian tissue expression, Oana Palasca, Alberto Santos, Christian Stolte, Jan Gorodkin, Lars Juhl Jense

TISSUES datasets

Tissue expression datasets available in the TISSUES 2.0. database (including non-confident gene-tissue associations

Datasets

Tissue expression datasets available in the TISSUES 2.0. database including non-confident gene-tissue associations

Quality Assessment of Domesticated Animal Genome Assemblies

The era of high-throughput sequencing has made it relatively simple to sequence genomes and transcriptomes of individuals from many species. In order to analyze the resulting sequencing data, high-quality reference genome assemblies are required. However, this is still a major challenge, and many domesticated animal genomes still need to be sequenced deeper in order to produce high-quality assemblies. In the meanwhile, ironically, the extent to which RNA seq and other next-generation data is produced frequently far exceeds that of the genomic sequence. Furthermore, basic comparative analysis is often affected by the lack of genomic sequence. Herein, we quantify the quality of the genome assemblies of 20 domesticated animals and related species by assessing a range of measurable parameters, and we show that there is a positive correlation between the fraction of mappable reads from RNAseq data and genome assembly quality. We rank the genomes by their assembly quality and discuss the implications for genotype analyses

Proteomics data and Brefeldin A treatment.

a) Protein coverage of the proteomics data sets used in the study (after isoform removal and accessions homogenization—see material and methods). These are identified by the first author’s name (left). The data set “Frejno” contained two independent MS searches of different cell line panels, we kept them separated. The total number of protein groups detected in the data sets are indicated in the bar plot on the right-hand side (color-coded by the cell line panel). The protein groups identified in multiple data sets are indicated by the bar plot on the bottom: number of protein groups detected in the data sets indicated by a dot on the dot plot. b) Volcano plots for each cell line treated with Brefeldin A. Genes constituting the proliferation signature are highlighted in orange. The dashed line corresponds to a q-value of 0.05. (TIFF)</p

Genes/proteins used for calculating pseudo-proliferation index.

List of genes and protein accessions selected for calculating the pseudo-proliferation index. (XLSX)</p