Identifying transcriptional start sites of human microRNAs based on high-throughput sequencing data

Abstract

MicroRNAs (miRNAs) are critical small non-coding RNAs that regulate gene expression by hybridizing to the 3′-untranslated regions (3′-UTR) of target mRNAs, subsequently controlling diverse biological processes at post-transcriptional level. How miRNA genes are regulated receives considerable attention because it directly affects miRNA-mediated gene regulatory networks. Although numerous prediction models were developed for identifying miRNA promoters or transcriptional start sites (TSSs), most of them lack experimental validation and are inadequate to elucidate relationships between miRNA genes and transcription factors (TFs). Here, we integrate three experimental datasets, including cap analysis of gene expression (CAGE) tags, TSS Seq libraries and H3K4me3 chromatin signature derived from high-throughput sequencing analysis of gene initiation, to provide direct evidence of miRNA TSSs, thus establishing an experimental-based resource of human miRNA TSSs, named miRStart. Moreover, a machine-learning-based Support Vector Machine (SVM) model is developed to systematically identify representative TSSs for each miRNA gene. Finally, to demonstrate the effectiveness of the proposed resource, an important human intergenic miRNA, hsa-miR-122, is selected to experimentally validate putative TSS owing to its high expression in a normal liver. In conclusion, this work successfully identified 847 human miRNA TSSs (292 of them are clustered to 70 TSSs of miRNA clusters) based on the utilization of high-throughput sequencing data from TSS-relevant experiments, and establish a valuable resource for biologists in advanced research in miRNA-mediated regulatory networks.

Epidrug mediated re-expression of miRNA targeting the HMGA transcripts in pituitary cells

“…[14] MiRNA sequences, their specific transcription start sites and, where present, their associated CpG islands, were determined using the, miRBase, miRStart and miRT databases. [21][22][23] Expression Analysis:…”

“…[28] Bisulphite conversions were performed using EZ DNA Methylation-Gold Kit and the converted DNA eluted from the column and stored at -20°C as previously described. [29] The methylation status of selected miRNA associated CpG islands were determined using primers within bona fide CpG islands associated with the individual miRNA and as determined by miRStart and miRT analysis [22,23,21]. Sequences for analysis were imported into PyroMark Assay Design 2.0 software for primer design of sodium bisulphite-converted DNA (Qiagen, Crawley, UK) and in the majority of cases encompassed 5-8 CpG dinucleotides (Table 1, Supplemental data).…”

“…In these cases primers were designed to regions associated with transcription start sites and identified employing the on line databases previously described. [23,22] Percentage enrichment were determined relative to input DNA and was calculated as 100 X 2 -(CT adjusted input-CT immune-precipitated) . Input DNA CT was adjusted from 10% to 100% by subtracting 3.322 CT or Log 2 .…”

MicroRNA-144 Is Regulated by Activator Protein-1 (AP-1) and Decreases Expression of Alzheimer Disease-related A Disintegrin and Metalloprotease 10 (ADAM10)

“…Using the publicly accessible algorithm MiRStart (36), which integrates three datasets including cap analysis of gene expression (CAGE) Tags (37,38), TSS Seq libraries, and H3K4me3 chromatin signatures, the site at Ϫ371 bp upstream of the miR-144 precursor was predicted as the TSS of the primary miR-144. To experimentally verify this putative TSS, we generated a luciferase reporter construct containing the 2.8-kb region upstream of the precursor miR-144, named pGL3-promoter-2808.…”

A Database for TSSs of Human MicroRNAs

“…3. It includes nine loci (three from three different cell lines in [19] and one from each of the others [4,5,6,11,17,21]) of the same miRNA that are very close with respect to the large span of the genome, even though they differ much (σ ∼ 17225.6 for start TSS and σ ∼ 19656.4 for end TSS). …”