isoMiRmap1, available for download below, is an open source tool for the fast, deterministic, and exhaustive mining of isomiRs from microRNA (miRNA) precursors. Also included on this page are downloadable isomiR/miRNA profiles, generated using isoMiRmap, for 11,085 datasets from the 1000 Genomes and TCGA projects consisting of 5 population groups and 33 cancer types respectively. View the full publication.
Download the isoMiRmap tool
Version: Initial Release
Significance of isomiR and miRNA profiles
While the data from our isoMiRmap mining tool can be used to generate standard miRNA expression profiles, the option to include isomiRs provides more granular isoform level quantification. As mentioned in our publication, for nearly 20 years, only the reference miRNA served as the basis for designing synthetic RNAs and quantification assays used in experimental work. However, it is now known that a ‘cloud of isoforms’ emerge from miRNA precursors which are known as isomiRs. IsomiR’s from the same locus differ from each other and can even target/regulate different genes. By providing information at the isomiR level, in addition to the miRNA level, our mining tool provides greater visibility into the specific molecules that are active within cells which can differ by sex, race/ethnicity, tissue type/state, disease type/subtype, and population of origin. These enhanced miRNA profiles can facilitate the hunt for more accurate biomarker diagnostics, therapeutics, and enriched biological understanding.
Reporting of non-templated isomiRs
Our tool is able to profile miRNA in which there are differences when compared to the reference genome assembly. Not all cells contain exactly the same DNA – thus, isoMIRmap uses information from popular databases for the mining and reporting of miRNA and isomiRs that have both SNPs (single nucleotide polymorphisms) and/or somatic mutations. All individuals are unique, and as we demonstrate in our publication, having this information helps us better understand the differences across population groups. By providing this level of resolution, we hope to facilitate research into the genetic drivers of health disparities and molecular underpinnings that make us unique. IsomiR’s with other 3′ non-templated additions (e.g. uridylation) are also reported. While the functions of these frequent additions are still being sought, early indications suggest they could act to control miRNA and arm production, modulate miRNA target effectiveness, and contribute to miRNA stabilization.
License, program output, requirements and help
Our open source tool produces output in HTML, miRGFF32, and in tab-delimited formats. IsoMiRmap runs quickly (i.e. profiling 50 million reads in only a few minutes) on a standard laptop or computer system. For detailed license information, program help and requirements, please see the readme file included in the downloadable bundle at the top of this page. Please contact us with any questions!
Quick Glance: key features of the isoMiRmap mining tool for miRNA and isomiRs
- Marks isomiRs as ambiguous that could be transcribed both within and outside of known miRNA precursors. These molecules may belong to other classes of RNA.
- Comprehensively and exhaustively reports all precursor origin(s) of isomiRs. This is especially important when profiling miRNA with highly similar isomiRs such as in the let-7 family which many mappers underreport.
- Reports an isomiR’s intersections with repeat elements (e.g. LINE, SINE, ALU, rRNA, tRNA, etc.). These regions may have an increased chance in producing other classes of RNA such as small interfering RNAs, tRFs, etc.
- Profiles isomiRs/miRNA with known single-nucleotide polymorphisms and somatic mutations. This helps capture attributes that make individuals and cells unique.
- Profiles isomiRs/miRNA with 3′ non-templated (e.g. uridylation) additions
- Supports multiple mapping bundles (e.g. miRBase, miRCarta) and is extendible to other species and assemblies.
- Does not double-count molecules that have multiple genomic instances.
- Runs very quickly on an average laptop with minimal setup. A high-performance compute environment or specialized compute-node is not required to map miRNA.
- Various output formats for easy integration with Web browsers, Microsoft Excel, Bioinformatics pipelines, etc.
- Free and open source.
Download isomiR expression profiles
In this section you can find 11,085 downloadable isomiR expression profiles (generated using isoMiRmap) from:
- LCL (lymphoblastoid cell lines) transcriptomes (n=482) from the 1000 Genomes Project consisting of five population groups
- TCGA (The Cancer Genome Atlas Program) transcriptomes (n=10,603) across 33 different cancer types
Note: these downloadable isomiR profiles below are bundled using popular Tar and Gzip tools. While most new operating systems can open these natively, some versions of Windows may require tools such as 7-Zip or WinZip to open.
IsomiR profiles from the 1000 Genomes Project (n=482 total samples)
| Population Group | isoMiRmap profiles (miRBase v22 reference) |
isoMiRmap profiles (miRCarta v1.1 reference) |
|---|---|---|
| CEU (Utah residents, CEPH, with Northern and Western European ancestry) | ||
| FIN (Finnish in Finland) | ||
| GBR (British in England and Scotland) | ||
| TSI (Toscani in Italy) | ||
| YRI (Yoruba in Ibadan, Nigeria) |
IsomiR profiles from TCGA (n=10,603 total samples)
| TCGA Study | isoMiRmap profiles (miRBase v22 reference) |
isoMiRmap profiles (miRCarta v1.1 reference) |
|---|---|---|
| ACC (Adrenocortical carcinoma) | ||
| BLCA (Bladder Urothelial Carcinoma) | ||
| BRCA (Breast invasive carcinoma) | ||
| CESC (Cervical squamous cell carcinoma and endocervical adenocarcinoma) | ||
| CHOL (Cholangiocarcinoma) | ||
| COAD (Colon adenocarcinoma) | ||
| DLBC (Lymphoid Neoplasm Diffuse Large B-cell Lymphoma) | ||
| ESCA (Esophageal carcinoma) | ||
| GBM (Glioblastoma multiforme) | ||
| HNSC (Head and Neck squamous cell carcinoma) | ||
| KICH (Kidney Chromophobe) | ||
| KIRC (Kidney renal clear cell carcinoma) | ||
| KIRP (Kidney renal papillary cell carcinoma) | ||
| LAML (Acute Myeloid Leukemia) | ||
| LGG (Brain Lower Grade Glioma) | ||
| LIHC (Liver hepatocellular carcinoma) | ||
| LUAD (Lung adenocarcinoma) | ||
| LUSC (Lung squamous cell carcinoma) | ||
| MESO (Mesothelioma) | ||
| OV (Ovarian serous cystadenocarcinoma) | ||
| PAAD (Pancreatic adenocarcinoma) | ||
| PCPG (Pheochromocytoma and Paraganglioma) | ||
| PRAD (Prostate adenocarcinoma) | ||
| READ (Rectum adenocarcinoma) | ||
| SARC (Sarcoma) | ||
| SKCM (Skin Cutaneous Melanoma) | ||
| STAD (Stomach adenocarcinoma) | ||
| TGCT (Testicular Germ Cell Tumors) | ||
| THCA (Thyroid carcinoma) | ||
| THYM (Thymoma) | ||
| UCEC (Uterine Corpus Endometrial Carcinoma) | ||
| UCS (Uterine Carcinosarcoma) | ||
| UVM (Uveal Melanoma) |
References
- Loher P, Karathanasis N, Londin E, Bray P, Pliatsika V, Telonis AG, Rigoutsos I. IsoMiRmap-fast, deterministic, and exhaustive mining of isomiRs from short RNA-seq datasets. Bioinformatics. 2021 Jan 20:btab016. doi: 10.1093/bioinformatics/btab016. Epub ahead of print. PubMed PMID:33471076.
- Desvignes, T, Loher, P, Eilbeck, K, Ma, J, Urgese, G, Fromm, B, Sydes, J, Aparicio-Puerta, E, Barrera, V, Espín, R, Thibord, F, Bofill-De Ros, X, Londin, E, Telonis, AG, Ficarra, E, Friedländer, MR, Postlethwait, JH, Rigoutsos, I, Hackenberg, M, Vlachos, IS, Halushka, MK, Pantano, L. Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API. Bioinformatics 36(3):698-703 (2020). doi: 10.1093/bioinformatics/btz675. PubMed PMID:31504201.