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Comprehensive discovery of endogenous Argonaute binding sites in Caenorhabditis elegans - PubMed

Comprehensive discovery of endogenous Argonaute binding sites in Caenorhabditis elegans

Dimitrios G Zisoulis et al. Nat Struct Mol Biol. 2010 Feb.

Abstract

MicroRNAs (miRNAs) regulate gene expression by guiding Argonaute proteins to specific target mRNA sequences. Identification of bona fide miRNA target sites in animals is challenging because of uncertainties regarding the base-pairing requirements between miRNA and target as well as the location of functional binding sites within mRNAs. Here we present the results of a comprehensive strategy aimed at isolating endogenous mRNA target sequences bound by the Argonaute protein ALG-1 in C. elegans. Using cross-linking and ALG-1 immunoprecipitation coupled with high-throughput sequencing (CLIP-seq), we identified extensive ALG-1 interactions with specific 3' untranslated region (UTR) and coding exon sequences and discovered features that distinguish miRNA complex binding sites in 3' UTRs from those in other genic regions. Furthermore, our analyses revealed a striking enrichment of Argonaute binding sites in genes important for miRNA function, suggesting an autoregulatory role that may confer robustness to the miRNA pathway.

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Figures

Figure 1
Figure 1

MicroRNA targets identified by ALG-1 CLIP-seq in L4-stage worms. Graphical depictions of the number and location of reads from alg-1(−) (red upper tracks) and WT (blue lower tracks) from three biological replicates, CLIP-derived clusters (solid rectangular boxes over the reads) and putative miRNA binding sites in the 3′ UTR of mRNA transcripts (LCS, let-7 complementary sequence; LCE, lin-4 complementary element). (a) lin-41 3′ UTR. Of the six predicted LCSs, LCS1 and LCS2 (open boxes) have experimentally validated let-7 sites–. (b) lin-14 3′ UTR. Deletion of all the predicted LCE sites or of LCEs 1–5 results in misregulation of lin-14 expression,. (c) hbl-1 3′ UTR,,. The sites for let-7 miRNA (LCSs 1–8) binding have been predicted but not experimentally tested. (d) daf-12 3′ UTR. Deletion of the predicted LCSs 1–4 or 5–8 in reporter constructs leads to misregulation of reporter gene expression.

Figure 2
Figure 2

Relative position of ALG-1 binding sites across protein-coding genes. (a) Distribution of WT (blue) and alg-1(−) (red) clusters across a composite mRNA length. Cluster position is depicted as a percentage of the gene region, from the beginning to the end of spliced transcripts. (b) Distribution of WT (blue) and alg-1(−) (red) clusters across the 3′ UTR region. Cluster position is depicted as a percentage of the region from the annotated translational stop codon to the end of transcripts, as defined by our reannotation of C. elegans genes.

Figure 3
Figure 3

Attributes enriched in ALG-1 binding sites within 3′ UTRs. (a) Box plots of the conservation levels measured as the fraction of perfectly conserved nucleotides between genome-wide alignments of C. elegans and HG004659 and GM084317 brenneri in CLIP-derived clusters (CDCs) and randomly derived clusters (RDCs). CDCs are significantly more conserved than RDCs as assessed by the Kolgomorov-Smirnov two-sample test (P < 10−36). (b) Box plots of RNA accessibility, measured as the average probability of being unpaired, of CDC and RDC and their corresponding flanking sequences (100 nt upstream or downstream). CDCs and flanking sequences are significantly more accessible than RDCs in the same locations as assessed by the Kolgomorov-Smirnov two-sample test (P < 10−10). (c) The ten most enriched k-mers (k = 5, 6, 7) within or 100 nt upstream or downstream of CDCs, compared to RDCs, are shown along with the range of Z-scores for the specific categories. (d–g). The number of conserved hexamers within CDCs (solid line) and RDCs (dashed line) that base-pair to miRNA or scrambled miRNA regions (dotted line), allowing for zero (orange) or only one G•U base pair (black). Error bars in dashed and dotted lines represent the s.d. among ten independent sets of RDCs and scrambled miRNAs, respectively. Hexamers within 3′-UTR CDCs and RDCs (d) or coding-exon CDCs and RDCs (e) that base-pair to cloned miRNAs or shuffled versions of cloned miRNAs. Hexamers within 3′-UTR CDCs and RDCs that base-pair to the let-7 or shuffled let-7 miRNA (f) and lin-4 or shuffled lin-4 miRNA (g). Regions of the miRNA(s) that have statistically enriched numbers of complementary hexamers within CDCs when compared to RDCs or shuffled miRNAs are denoted by * (P < 0.01) and ** (P < 10−6) as measured by a Z-test.

Figure 4
Figure 4

Relationship between ALG-1 binding and mRNA expression levels. (a) Effects of ALG-1 binding on mRNA levels. Box plots representing the differential expression (as a t-statistic) of genes from biological replicate microarray experiments comparing alg-1(−) to WT L4-stage worms. Genes are divided into those that contained no CDCs and those that contained CDCs only within 3′ UTRs or coding exons. Compared to genes with no CDCs or coding-exon CDCs, genes with 3′-UTR CDCs are significantly more upregulated in alg-1(−) relative to WT as assayed by the Wilcoxon rank-sum test (P < 10−4). (b) Functional enrichment of genes that have CDCs only within 3′ UTR or coding exons that are up- or downregulated in alg-1(−) worms using significantly enriched (P < 0.05 in at least one row; Holm-Bonferroni corrected) functional categories defined by the C. elegans Topomap algorithm. The intensity on the heat-map denotes −log10(p value). Genes represented by these functional categories can be divided in a matrix (right) depending on the location of the CDCs (3′ UTRs or coding exons), and whether the genes are up- or downregulated in the alg-1(−) mutants relative to WT worms. Several categories occupy multiple cells in the matrix, for example “Cell structure,” “Collagen,” “Cell adhesion,” “Protein expression,” “RNA binding” and “Germ line–enriched.” (c) UCSC Genome Browser view depicting clusters in the 3′ UTR of the alg-1 gene (blue, WT clusters; red, alg-1(−) clusters, none present) and the predicted miRNA binding sites by the various algorithms.

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