The DIANA resource of computationally predicted miRNA-mRNA interactions

DIANA-microT 2023 webserver is a reference resource catering computationally predicted miRNA interactions with protein coding genes. Its current version hosts more than 86 million miRNA-gene interactions, coupled with their exact genomic locations of miRNA Recognition Elements (MREs) and extensive supplemental support.

DIANA-microT 2023 is based on the reference miRNA target prediction algorithm DIANA-microT-CDS. Its current version was executed using miRNA sequences derived from miRBase 22.1 and MirGeneDB 2.1 on Ensembl 102 transcript annotations regarding 6 metazoan species (H. sapiens, M. musculus, R. norvegicus, G. gallus, D. melanogaster, C. elegans). 

For the first time, ~2.5 million miRNA target predictions regarding experimentally verified miRNA sequences from Herpesviruses, Polyomaviruses and Retroviruses are also offered (miRBase 22.1 annotation). They pertain to host transcripts of human (viruses EBV, KSHV, HSV1-2, HCMV, SFV, HBV, HIV1, HHV6B, MCPV, JCV, BKV, SV40, TTV), mouse (viruses MGHV, MCMV) and chicken (viruses MDV1-2, HVT, ILTV).

Users can provide miRNA and/or gene names and identifiers and filter interactions by species, miRNA annotation confidence, and MRE genomic localization (UTR/CDS). They may also combine microT predictions with experimental support (DIANA-TarBase v8.0, http://microrna.gr/tarbase/) or additional prediction support (TargetScan, https://www.targetscan.org/).

DIANA-microT 2023 has incorporated summarized abundance estimates for miRNAs in 60 tissues and 210 cell-lines from DIANA-miTED resource (https://dianalab.e-ce.uth.gr/mited/#/). Also, summarized gene expression estimates from healthy human (GTEx, https://gtexportal.org/home/) and mouse (Sollner et al., 2017), as well as cancerous tissues (TCGA, https://portal.gdc.cancer.gov/) are also included, enabling simultaneous browsing of miRNA-gene interactions and their relative abundance in tissues, cell types and conditions of interest. 

Additional external resources included to enrich the webserver content and expand its array of potential uses include SNPs (from dbSNP v151 and ClinVar) that overlap MREs, causal miRNA-disease links derived from HMDD 3.2 resource (https://www.cuilab.cn/hmdd) and circulating biomarker miRNA-disease associations derived from plasmiR (https://dianalab.e-ce.uth.gr/plasmir/#/).

DIANA-microT 2023 content is available freely to all, without any login and/or license requirements.

Please cite:

Spyros Tastsoglou, Athanasios Alexiou, Dimitra Karagkouni, Giorgos Skoufos, Elissavet Zacharopoulou & Artemis G Hatzigeorgiou. DIANA-microT 2023: including predicted targets of virally encoded miRNAs (Nucleic Acids Research, DOI:10.1093/nar/gkad283)

The “ELIXIR-GR: Managing and Analysing Life Sciences Data (MIS: 5002780)” Project is co-financed by Greece and the European Union - European Regional Development Fund