Abstract
Simple SummarymiRNAs are omnipresent short non-coding RNA molecules, which post-transcriptionally fine-tune the expression of most protein-coding genes in health and disease. In cancer, miRNAs have been described to directly regulate the amounts of targeted tumor suppressors and oncogenes. Although their canonical mechanism of action is well understood, the correct prediction of miRNA target genes is still a challenge. We describe here the unbiased investigation of the miRNA targetome in cancer (melanoma) cells using a technique, which allows to physically link the miRNA to its target gene. The herein identified miRNA-target interactions reveal further layers of complexity of post-transcriptional gene regulation in cancer cells and shed new light on miRNA-target gene interactions.MicroRNAs are key post-transcriptional gene regulators often displaying aberrant expression patterns in cancer. As microRNAs are promising disease-associated biomarkers and modulators of responsiveness to anti-cancer therapies, a solid understanding of their targetome is crucial. Despite enormous research efforts, the success rates of available tools to reliably predict microRNAs (miRNA)-target interactions remains limited. To investigate the disease-associated miRNA targetome, we have applied modified cross-linking ligation and sequencing of hybrids (qCLASH) to BRAF-mutant melanoma cells. The resulting RNA-RNA hybrid molecules provide a comprehensive and unbiased snapshot of direct miRNA-target interactions. The regulatory effects on selected miRNA target genes in predicted vs. non-predicted binding regions was validated by miRNA mimic experiments. Most miRNA–target interactions deviate from the central dogma of miRNA targeting up to 60% interactions occur via non-canonical seed pairing with a strong contribution of the 3′ miRNA sequence, and over 50% display a clear bias towards the coding sequence of mRNAs. miRNAs targeting the coding sequence can directly reduce gene expression (miR-34a/CD68), while the majority of non-canonical miRNA interactions appear to have roles beyond target gene suppression (miR-100/AXL). Additionally, non-mRNA targets of miRNAs (lncRNAs) whose interactions mainly occur via non-canonical binding were identified in melanoma. This first application of CLASH sequencing to cancer cells identified over 8 K distinct miRNA–target interactions in melanoma cells. Our data highlight the importance non-canonical interactions, revealing further layers of complexity of post-transcriptional gene regulation in melanoma, thus expanding the pool of miRNA–target interactions, which have so far been omitted in the cancer field.
Highlights
MicroRNAs are short non-coding RNA molecules and important regulators of post-transcriptional gene expression and as such they balance gene levels, which is vital for many physiological responses to stimuli in healthy and diseased cells [1,2]
The most common approach to date begins with screening of miRNA targets predicted by using in silico tools [14], which employ algorithms that are based on the “central dogma” of miRNA targeting: miRNAs bind via their seed sequence, which is defined as the region between nucleotides 2–7 at the 5 end of the miRNA, to a complementary sequence in the 3 untranslated region (3 UTR) of the mRNA
We have investigated miRNome and transcriptome changes in melanoma cells resistant to targeted BRAF inhibition therapy, followed by a miRNA-mRNA co-expression analysis with the aim to identify miRNA–target interactions potentially involved in the emergence and maintenance of drug resistance [8]
Summary
MicroRNAs (miRNAs) are short non-coding RNA molecules and important regulators of post-transcriptional gene expression and as such they balance gene levels, which is vital for many physiological responses to stimuli in healthy and diseased cells [1,2]. While the biogenesis pathway and its overall regulation as well as canonical targeting rules of miRNAs are well understood [1,6,7], we still lack insights into disease- and cell-specific miRNA– target interactions and how these regulatory networks could be exploited in therapies against complex diseases such as cancer. While many methods exist that study RNA–protein interactions [15,16], techniques that allow for investigation of direct RNA–RNA interactions have only recently been developed [17,18,19] These approaches have revealed that miRNAs can modulate the expression of target mRNAs by following non-predicted and non-canonical interaction patterns, for instance by binding via nucleotides beyond the seed sequence [17,18,20]. To further exploit miRNAs as therapeutic targets or as biomarkers, a more detailed understanding of their gene regulatory networks in physiological conditions is required and how these are re-wired in malignancies [9,24]
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