| URL: | https://www.ccb.uni-saarland.de/tissueatlas2025 |
| Full name: | the human and mouse small noncoding RNA tissue atlas |
| Description: | miRNATissueAtlas 2025, which contains expressions from 9 classes of ncRNA from 799 billion reads across 61 593 samples for H. sapiens and M. musculus. The number of organs and tissues has increased from 28 and 54 to 74 and 373, respectively. |
| Year founded: | 2016 |
| Last update: | 2025-01-06 |
| Version: | v3 |
| Accessibility: |
Accessible
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| Country/Region: | Germany |
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| University/Institution: | Saarland University |
| Address: | |
| City: | Saarbrucken |
| Province/State: | |
| Country/Region: | Germany |
| Contact name (PI/Team): | Andreas Keller |
| Contact email (PI/Helpdesk): | andreas.keller@ccb.uni-saarland.de |
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miRNATissueAtlas 2025: an update to the uniformly processed and annotated human and mouse non-coding RNA tissue atlas. [PMID: 39540421]
MiRNAs represent a non-coding RNA class that regulate gene expression and pathways. While miRNAs are evolutionary conserved most data stems from Homo sapiens and Mus musculus. As miRNA expression is highly tissue specific, we developed miRNATissueAtlas to comprehensively explore this landscape in H. sapiens. We expanded the H. sapiens tissue repertoire and included M. musculus. In past years, the number of public miRNA expression datasets has grown substantially. Our previous releases of the miRNATissueAtlas represent a great framework for a uniformly pre-processed and label-harmonized resource containing information on these datasets. We incorporate the respective data in the newest release, miRNATissueAtlas 2025, which contains expressions from 9 classes of ncRNA from 799 billion reads across 61 593 samples for H. sapiens and M. musculus. The number of organs and tissues has increased from 28 and 54 to 74 and 373, respectively. This number includes physiological tissues, cell lines and extracellular vesicles. New tissue specificity index calculations build atop the knowledge of previous iterations. Calculations from cell lines enable comparison with physiological tissues, providing a valuable resource for translational research. Finally, between H. sapiens and M. musculus, 35 organs overlap, allowing cross-species comparisons. The updated miRNATissueAtlas 2025 is available at https://www.ccb.uni-saarland.de/tissueatlas2025. |
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miRNATissueAtlas2: an update to the human miRNA tissue atlas. [PMID: 34570238]
Small non-coding RNAs (sncRNAs) are pervasive regulators of physiological and pathological processes. We previously developed the human miRNA Tissue Atlas, detailing the expression of miRNAs across organs in the human body. Here, we present an updated resource containing sequencing data of 188 tissue samples comprising 21 organ types retrieved from six humans. Sampling the organs from the same bodies minimizes intra-individual variability and facilitates the making of a precise high-resolution body map of the non-coding transcriptome. The data allow shedding light on the organ- and organ system-specificity of piwi-interacting RNAs (piRNAs), transfer RNAs (tRNAs), microRNAs (miRNAs) and other non-coding RNAs. As use case of our resource, we describe the identification of highly specific ncRNAs in different organs. The update also contains 58 samples from six tissues of the Tabula Muris collection, allowing to check if the tissue specificity is evolutionary conserved between Homo sapiens and Mus musculus. The updated resource of 87 252 non-coding RNAs from nine non-coding RNA classes for all organs and organ systems is available online without any restrictions (https://www.ccb.uni-saarland.de/tissueatlas2). |
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Distribution of miRNA expression across human tissues. [PMID: 26921406]
We present a human miRNA tissue atlas by determining the abundance of 1997 miRNAs in 61 tissue biopsies of different organs from two individuals collected post-mortem. One thousand three hundred sixty-four miRNAs were discovered in at least one tissue, 143 were present in each tissue. To define the distribution of miRNAs, we utilized a tissue specificity index (TSI). The majority of miRNAs (82.9%) fell in a middle TSI range i.e. were neither specific for single tissues (TSI > 0.85) nor housekeeping miRNAs (TSI < 0.5). Nonetheless, we observed many different miRNAs and miRNA families that were predominantly expressed in certain tissues. Clustering of miRNA abundances revealed that tissues like several areas of the brain clustered together. Considering -3p and -5p mature forms we observed miR-150 with different tissue specificity. Analysis of additional lung and prostate biopsies indicated that inter-organism variability was significantly lower than inter-organ variability. Tissue-specific differences between the miRNA patterns appeared not to be significantly altered by storage as shown for heart and lung tissue. MiRNAs TSI values of human tissues were significantly (P = 10(-8)) correlated with those of rats; miRNAs that were highly abundant in certain human tissues were likewise abundant in according rat tissues. We implemented a web-based repository enabling scientists to access and browse the data (https://ccb-web.cs.uni-saarland.de/tissueatlas). |