ausblenden:
Schlagwörter:
PULMONARY ARTERIAL-HYPERTENSION; SICKLE-CELL-DISEASE; LUNG-CANCER
DIAGNOSIS; SMALL RNAS; PROTEOMIC ANALYSIS; SERUM MICRORNAS; GENE;
REGENERATION; FIBROSIS; EVOLUTIONBiochemistry & Molecular Biology; Biotechnology & Applied Microbiology;
Mathematical & Computational Biology; MiRNA target interactions; miRNA target linkage; Transcriptome;
Proteome; miRNAome; Niche model organisms;
Zusammenfassung:
Background: MicroRNAs (miRNAs) impact various biological processes within animals and plants. They complementarily bind target mRNAs, effecting a post-transcriptional negative regulation on mRNA level. The investigation of miRNA target interactions (MTIs) by high throughput screenings is challenging, as frequently used in silico target prediction tools are prone to emit false positives. This issue is aggravated for niche model organisms, where validated miRNAs and MTIs both have to be transferred from well described model organisms. Even though DBs exist that contain experimentally validated MTIs, they are limited in their search options and they utilize different miRNA and target identifiers.
Results: The implemented pipeline LimiTT integrates four existing DBs containing experimentally validated MTIs. In contrast to other cumulative databases (DBs), LimiTT includes MTI data of 26 species. Additionally, the pipeline enables the identification and enrichment analysis of MTIs with and without species specificity based on dynamic quality criteria. Multiple tabular and graphical outputs are generated to permit the detailed assessment of results.
Conclusion: Our freely available web-based pipeline LimiTT (https://bioinformatics.mpi-bn.mpg.de/) is optimized to determine MTIs with and without species specification. It links miRNAs and/or putative targets with high granularity. The integrated mapping to homologous target identifiers enables the identification of MTIs not only for standard models, but for niche model organisms as well.
