Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Identification of microRNAs association with Rheumatoid Arthritis Synovial Fibroblasts using the Human TNF Transgenic Mouse Model

ABSTRACT: OBJECTIVE: MicroRNAs (miRNAs, miRs), a class of small non-coding RNA molecules, are posttranscriptional regulators involved in a plethora of cellular functions and have been proposed as potential therapeutic targets in various diseases, including rheumatoid arthritis (RA). In this study, we sought to discover novel miR associations in synovial fibroblasts (SFs), a key cell type mediating RA pathogenesis, by performing miR expression profiling on cells isolated from the human TNF transgenic mouse model (TghuTNF or Tg197). METHODS: miR expression in SFs isolated from 8-week-old, fully diseased TghuTNF and WT littermate control mice were determined by deep sequencing of small RNAs and the arthritic profile was established by pairwise comparisons of the two groups. qRT-PCR analysis was utilised for profile validation purposes and miR quantitation in patient SFs. Dysregulated miR target genes and pathways were predicted via bioinformatic algorithms. Synovial Fibroblasts isolated from TghuTNF mice (2 x biological replicates) and control WT littermate mice (2 x biological replicates)

ORGANISM(S): Mus musculus

SUBMITTER: Martin Reczko

PROVIDER: E-GEOD-31667 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Identification of microRNA-221/222 and microRNA-323-3p association with rheumatoid arthritis via predictions using the human tumour necrosis factor transgenic mouse model.

Pandis Ioannis I Ospelt Caroline C Karagianni Niki N Denis Maria C MC Reczko Martin M Camps Carme C Hatzigeorgiou Artemis G AG Ragoussis Jiannis J Gay Steffen S Kollias George G

Annals of the rheumatic diseases 20120505 10

<h4>Objective</h4>To identify novel microRNA (miR) associations in synovial fibroblasts (SF), by performing miR expression profiling on cells isolated from the human tumour necrosis factor (TNF) transgenic mouse model (TghuTNF, Tg197) and patients biopsies.<h4>Methods</h4>miR expression in SF from TghuTNF and wild-type (WT) control mice were determined by miR deep sequencing (miR-seq) and the arthritic profile was established by pairwise comparisons. Quantitative PCR analysis was utilised for pr ...[more]

PMID: 22562984

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Project description:MicroRNAs (miRNAs) are a class of non-coding RNA molecules which have significant gene regulation roles in organisms. The advent of new high throughput sequencing technologies has enabled the revelation of novel miRNAs. Although there are two recent reports on high throughput sequencing analysis of small RNA libraries from different organs of two grapevine wine varieties, there were significant divergence in the number and kinds of miRNAs sequenced in these studies. More sequencing of small RNA libraries is still important for the discovery of novel miRNAs in grapevine. Here, we initially constructed a small RNA library of flower and fruit tissues of a table grapevine cultivar M-bM-^@M-^XSummer BlackM-bM-^@M-^Y and performed sequencing and analysis of sRNAs using the Illumina Solexa platform, expecting to discover more miRNAs related to the development of grapevine flowers and berries and the formation of dessert quality in grapevine berries. Totally, 130 conserved grapevine miRNA (Vv-miRNA) belonging to 28 Vv-miRNA families were validated, and 92 novel potential grapevine-specific ones representing 80 unique ones were first discovered. Forty-two (48.84%) of the novel miRNAs possessed differential semi-quantitative PCR expression profiles in various grapevine tissues that could further confirm their existence in the grapevine, among which twenty were expressed only in grapevine berries, indicating some fruit-specificity. 130 target genes for 46 novel miRNAs could be predicted. The locations of these potential target genes on grapevine chromosomes and their complementary levels with the corresponding miRNAs were also analyzed. Size fractionated small RNAs (16-30 bp) from total RNA extracts was ligated to 5' and 3' adapters, and reverse transcribed. After PCR amplification the sample was subjected to Solexa sequencing. The resultant 35nt sequence data were filtered according to base quality value. The remained sequences were used to trim 5' and 3' adaptors. The clean tags were used for further analysis.

Dataset Information

Identification of microRNAs association with Rheumatoid Arthritis Synovial Fibroblasts using the Human TNF Transgenic Mouse Model

Publications

Identification of microRNA-221/222 and microRNA-323-3p association with rheumatoid arthritis via predictions using the human tumour necrosis factor transgenic mouse model.

Similar Datasets

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