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. 2011 May 15;27(10):1346-50.
doi: 10.1093/bioinformatics/btr149. Epub 2011 Mar 26.

The sufficient minimal set of miRNA seed types

Daniel C Ellwanger  1 , Florian A Büttner, Hans-Werner Mewes, Volker Stümpflen
Affiliations

The sufficient minimal set of miRNA seed types

Daniel C Ellwanger et al. Bioinformatics. .

Abstract

Motivation: Pairing between the target sequence and the 6-8 nt long seed sequence of the miRNA presents the most important feature for miRNA target site prediction. Novel high-throughput technologies such as Argonaute HITS-CLIP afford meanwhile a detailed study of miRNA:mRNA duplices. These interaction maps enable a first discrimination between functional and non-functional target sites in a bulky fashion. Prediction algorithms apply different seed paradigms to identify miRNA target sites. Therefore, a quantitative assessment of miRNA target site prediction is of major interest.

Results: We identified a set of canonical seed types based on a transcriptome wide analysis of experimentally verified functional target sites. We confirmed the specificity of long seeds but we found that the majority of functional target sites are formed by less specific seeds of only 6 nt indicating a crucial role of this type. A substantial fraction of genuine target sites arenon-conserved. Moreover, the majority of functional sites remain uncovered by common prediction methods.

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Figures

Fig. 1.
Fig. 1.
Definition of seed types. The seed types were termed by the start position relative to the 5′-end of the miRNA and the length of the consecutive seed match. The defined set of canonical seed types can be surjectively projected to the seed type set of (Bartel, 2009). Equivalent definitions could be found for 6merγ, 6merβ and 7merβ. In the case of miRNAs having a seed sequence beginning with an uracile, 7merα complies with 7mer-A1 and 8merα is equal to 8mer. Otherwise 6merβ equates 7mer-A1 and 7mer β complies with 8mer. If the first position within the target sequence is not an adenine, 8merα equates 7mer-m8 and 7merα is equal to 6mer. Additionally, our set considered 6mer matches that are complementary to the first position of a miRNA seed (6merα). Common target site prediction tools focus on seeds of length seven and eight to increase precision.
Fig. 2.
Fig. 2.
Accuracy evaluation. (A and C) The impact of each seed type on miRNA target site prediction was determined by means of recall and specificity. The effect of the (default) seed type selection is shown for several prediction algorithms. These values present respectively the minimum specificity and the maximum recall of the tools. The dashed line shows an average random prediction. (B and D) Removing non-conserved target sites increases the precision, but lowers the recall. Note that panels (C and D) do not reflect the ranking of predictions based on the algorithms' scoring schemes.
Fig. 3.
Fig. 3.
Heatmap showing the seed type distribution for each miRNA. The colors affected by the row z-score indicate the bias of miRNAs to prefer targets holding a specific seed type. A red/blue coloration implies a higher/lower usage of a seed type compared to other miRNAs.
Fig. 4.
Fig. 4.
Observed and expected fraction of conserved seed matches for each seed type illustrated for functional target sites.
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References

    1. Alexiou P., et al. Lost in translation: an assessment and perspective for computational microrna target identification. Bioinformatics. 2009;25:3049–3055. - PubMed
    1. Baek D., et al. The impact of micrornas on protein output. Nature. 2008;455:64–71. - PMC - PubMed
    1. Bagga S., et al. Regulation by let-7 and lin-4 mirnas results in target mRNA degradation. Cell. 2005;122:553–563. - PubMed
    1. Bartel D.P. Micrornas: target recognition and regulatory functions. Cell. 2009;136:215–233. - PMC - PubMed
    1. Betel D., et al. The microrna.org resource: targets and expression. Nucleic Acids Res. 2008;36:D149–D153. - PMC - PubMed

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