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. 2014 May 15;30(10):1377-83.
doi: 10.1093/bioinformatics/btu045. Epub 2014 Jan 26.

Composition of seed sequence is a major determinant of microRNA targeting patterns

Xiaowei Wang  1
Affiliations

Composition of seed sequence is a major determinant of microRNA targeting patterns

Xiaowei Wang. Bioinformatics. .

Abstract

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in gene expression regulation. One major roadblock in functional miRNA studies is the reliable prediction of genes targeted by miRNAs, as rules defining miRNA target recognition have not been well-established to date. Availability of high-throughput experimental data from a recent CLASH (cross linking, ligation and sequencing of hybrids) study has presented an unprecedented opportunity to characterize miRNA target recognition patterns, which may provide guidance for improved miRNA target prediction.

Results: The CLASH data were analysed to identify distinctive sequence features that characterize canonical and non-canonical miRNA target types. Most miRNA targets were of non-canonical type, i.e. without involving perfect pairing to canonical miRNA seed region. Different miRNAs have distinct targeting patterns, and this miRNA-to-miRNA variability was associated with seed sequence composition. Specifically, seed-based canonical target recognition was dependent on the GC content of the miRNA seed. For miRNAs with low GC content of the seed region, non-canonical targeting was the dominant mechanism for target recognition. In contrast to canonical targeting, non-canonical targeting did not lead to significant target downregulation at either the RNA or protein level.

Contact: xwang@radonc.wustl.edu.

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Figures

Fig. 1.
Fig. 1.
Occurrence of target sites matching to miRNA 6-mer words. For each miRNA-target pair, the 6-mer word from each position of the miRNA sequence was compared with the target sequence to identify any perfect base pairing. The numbers of miRNA-target pairs with 6-mer match at the same miRNA positions were summarized and presented in the graph. As negative control, the cognate target sequence in each miRNA-target pair was replaced with a randomly assigned non-target transcript sequence for 6-mer word analysis (shuffled control). The negative control simulation run was repeated 10 times and the average number of matched 6-mers at each position was presented (±SD)
Fig. 2.
Fig. 2.
GC content and thermostability of canonical seeds that were paired to the target sites. (A and B) Correlation between GC content of canonical seeds (positions 2–7 or 3–8) and percentage of seed-pairing target sites. (C and D) Correlation between thermostability of seed binding, as measured by free energy (ΔG) and percentage of seed-pairing target sites
Fig. 3.
Fig. 3.
GC content and thermostability of non-canonical seeds that were paired to the target sites. (A) Correlation between GC content of non-canonical extended seeds (any 6-mer within positions 4–10) and percentage of perfect seed-pairing target sites. (B) Correlation between thermostability of extended seed binding, as measured by free energy (ΔG) and percentage of seed-pairing target sites. (C) Correlation between any 6-mer seed and percentage of imperfect seed-pairing target sites containing a G-U mismatch. (D) Correlation between non-seed 6-mers in miRNA sequence and percentage of targets with 6-mer matching sites
Fig. 4.
Fig. 4.
Thermostability of miRNA-target duplex for individual targeting patterns. A cumulative distribution of targets in relation to ΔG was presented for each target type. The following target groups were considered: targets matching to at least one canonical 6-mer seed, but not to any extended seed; targets not matching to any canonical seed, but to at least one 6-mer extended seed; target not matching to any type of seed, but to at least one 6-mer in the non-seed region; targets with no 6-mer match anywhere in the miRNA sequence. As negative control, the cognate target sequence was replaced by a randomly assigned transcript sequence for miRNA pairing analysis (shuffled control)
Fig. 5.
Fig. 5.
Impact on target gene expression was dependent on miRNA targeting patterns. The following target groups were considered: targets matching to at least one canonical 6-mer seed, but not to any extended seed; targets not matching to any canonical seed, but to at least one 6-mer extended seed; target not matching to any type of seed, but to at least one 6-mer in the non-seed region; targets with no 6-mer match anywhere in the miRNA sequence. A cumulative distribution of targets in relation to gene expression changes was presented for each target type. (A) Target mRNA expression changes resulting from simultaneous depletion of 25 miRNAs (Hafner et al., 2010). As negative control, the cognate target sequence was replaced by a randomly assigned transcript sequence for miRNA pairing analysis (shuffled control). (B) Target protein expression changes resulting from individually overexpressing five miRNAs (Selbach et al., 2008). All 330 miRNA-target pairs present in both the proteomic and CLASH datasets were included in the analysis of different miRNA targeting patterns. As negative control, the cognate target protein was replaced by a randomly assigned protein from the proteomic dataset (shuffled control)
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