We and others (e.g. Saetrom 2007) have shown that microRNA (miRNA) binding sites are more often located in a defined cooperativity range of about 15 to 26 nucleotides between two consecutive miRNA 5’ ends than expected by chance. Additionally, our study shows that functionally related miRNAs show an enrichment of cooperative binding sites. Still, the biological relevance of cooperativity in miRNA function has to be shown experimentally. MiRco is a web application meant to aid experimental research into the cooperative action of miRNAs. It predicts potentially cooperatively targeted mRNAs based on binding site distances and thus might help to identify key regulatory miRNA-mRNA networks. In serving as a starting point for wet lab scientists, miRco allows to input miRNAs and search for cooperative targets. In addition the user can specify a set of genes and find all miRNAs that target these genes in a cooperative fashion. This dual approach helps to narrow down lists of candidate genes and miRNAs and makes it more feasible to test cooperativity in a complex biological context.

How to use it

1. Choose organism

First, the user is asked to choose the species for which the search is to be carried out. Choose between “Human”, “Mouse” and “Rat”. This specifies the target data set for the indicated organism obtained from the current release of TargetScan (version 6.0).

2. Set limit for cooperativity range

Second, to predict mRNAs that are cooperatively regulated, miRco searches by default for target sites within a distance of 15 to 26 nucleotides from the 5’-end of one miRNA to the 5’-end of the next one. This setting was chosen based on our findings and on reported experimental data (Doench 2004, Grimson 2007, Saetrom 2007, Broderick 2011). Alternatively, the user may define a custom lower and upper limit of the distance.

3. Input genes and/or microRNAs

Third, a list of miRNAs, or genes, or both may be submitted. If either miRNAs or genes are left blank, the complete data set is used for analysis. Our tool is connected to the PhenomiR (Ruepp 2010) database. The user can select a disease annotated in PhenomiR and input a set of disease-associated miRNAs.

4. Check input

Fourth, the user is asked to confirm if the selected input is contained in our database and if the nomenclature is in accordance with our entries.

5. Start analysis

Fifth, press “run analysis!” to start the query. Output The output of miRco is presented as a list of target genes with corresponding binding sites in the aforementioned cooperativity range. Data is initially sorted based on the context+ score calculated by TargetScan and can subsequently be listed by target gene symbol and average distance between the binding sites. Furthermore, the result table can be filtered for the occurrence of one or multiple miRNAs within the list of candidate mRNAs.


Rinck A, Preusse MM, Laggerbauer B, Lickert H, Engelhardt S, Theis FJ. Distance makes a difference: the transcriptome is enriched for proximal microRNA binding sites. RNA Biology. 2013


Doench JG, Sharp P. Specificity of microRNA target selection in translational repression. Genes & development. 2004;18(5):504–11

Grimson A, Farh KK-H, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Molecular cell. 2007;27(1):91–105

Saetrom P, Heale BSE, Snøve O, Aagaard L, Alluin J, Rossi JJ. Distance constraints between microRNA target sites dictate efficacy and cooperativity. Nucleic acids research. 2007;35(7):2333–42

Ruepp A, Kowarsch A, Schmidl D, Buggenthin F, Brauner B, Dunger I, et al. PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes. Genome biology. 2010;11(1):R6.

Broderick J a., Salomon WE, Ryder SP, Aronin N, Zamore PD. Argonaute protein identity and pairing geometry determine cooperativity in mammalian RNA silencing. RNA. 2011:1858–1869