Beta Cell 5′-Shifted isomiRs Are Candidate Regulatory Hubs in Type 2 Diabetes

Baran-Gale, Jeanette; Fannin, Emily E.; Kurtz, C. Lisa; Sethupathy, Praveen

doi:10.1371/journal.pone.0073240

Cited by 81 publications

(105 citation statements)

References 49 publications

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“…Consequently, the canonical miRNA “seed” sequence is altered, potentially conferring recognition of different mRNA targets [24–26]. Therefore, it is important that miRNA analysis includes quantification of isomiRs.…”

Section: Resultsmentioning

confidence: 99%

Bioinformatic analysis of endogenous and exogenous small RNAs on lipoproteins

Allen

Zhao

Solano

et al. 2018

J of Extracellular Vesicle

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To comprehensively study extracellular small RNAs (sRNA) by sequencing (sRNA-seq), we developed a novel pipeline to overcome current limitations in analysis entitled, “Tools for Integrative Genome analysis of Extracellular sRNAs (TIGER)”. To demonstrate the power of this tool, sRNA-seq was performed on mouse lipoproteins, bile, urine and livers. A key advance for the TIGER pipeline is the ability to analyse both host and non-host sRNAs at genomic, parent RNA and individual fragment levels. TIGER was able to identify approximately 60% of sRNAs on lipoproteins and >85% of sRNAs in liver, bile and urine, a significant advance compared to existing software. Moreover, TIGER facilitated the comparison of lipoprotein sRNA signatures to disparate sample types at each level using hierarchical clustering, correlations, beta-dispersions, principal coordinate analysis and permutational multivariate analysis of variance. TIGER analysis was also used to quantify distinct features of exRNAs, including 5ʹ miRNA variants, 3ʹ miRNA non-templated additions and parent RNA positional coverage. Results suggest that the majority of sRNAs on lipoproteins are non-host sRNAs derived from bacterial sources in the microbiome and environment, specifically rRNA-derived sRNAs from Proteobacteria. Collectively, TIGER facilitated novel discoveries of lipoprotein and biofluid sRNAs and has tremendous applicability for the field of extracellular RNA.

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Section: Resultsmentioning

confidence: 99%

Bioinformatic analysis of endogenous and exogenous small RNAs on lipoproteins

Allen

Zhao

Solano

et al. 2018

J of Extracellular Vesicle

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“…Small RNAseq data were processed as previously described (Baran-Gale et al 2013) to identify robustly expressed miRNAs and their isoforms (isomiRs). Resulting miRNA counts were normalized using a reads-per-million-mapped (RPMM) transformation.…”

Section: Dynamics Of Estrogen-regulated Mirnasmentioning

confidence: 99%

“…We next explored the potential regulatory interactions between miRNAs and mRNAs in the temporal response to estrogen using our previously published miRNA target site enrichment algorithm, miRhub (Baran-Gale et al 2013). miRhub identifies candidate master miRNA regulators by identifying those miRNAs that are predicted to target and regulate a gene set of interest significantly more than expected by chance.…”

Section: Computational Prediction Of Mirna-mrna Regulatory Interactionsmentioning

confidence: 99%

“…Small RNA-seq reads were trimmed using cutAdapt (−O 10 -e 0.1) (Martin 2011) to remove remnants of the 3 ′ -adapter sequence, then the first four and last four nucleotides of small RNA-seq reads were trimmed to remove the degenerate nucleotides in the adapters. Subsequent mapping of trimmed reads to the human genome and miRNA/isomiR quantification were performed exactly as previously described (Baran-Gale et al 2013). The threshold used to classify miRNAs as robustly expressed was set at a mean of 50 RPMM across the time series.…”

Section: Sequencing and Differential Expression Analysismentioning

confidence: 99%

“…A selection of the most significant categories is depicted in Figure 2E-G. miRNA target site enrichment was conducted by (i) identifying the list of miRNA families whose members have a mean expression of 50 RPMM, (ii) identifying lists of "characteristic genes" whose change in expression best describes the difference between consecutive time points (Clark et al 2014), and (iii) using our miRNA target site enrichment algorithm (miRhub) (Baran-Gale et al 2013) to identify miRNA families that act as "master regulators" of the "characteristic gene sets." miRNA target site predictions used in the miRhub enrichment algorithm are derived from TargetScan5.2 (Grimson et al 2007).…”

Section: Clusteringmentioning

confidence: 99%

See 2 more Smart Citations

An integrative transcriptomics approach identifies miR-503 as a candidate master regulator of the estrogen response in MCF-7 breast cancer cells

Baran-Gale

Purvis

Sethupathy

2016

RNA

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Estrogen receptor α (ERα) is an important biomarker of breast cancer severity and a common therapeutic target. In response to estrogen, ERα stimulates a dynamic transcriptional program including both coding and noncoding RNAs. We generate a fine-scale map of expression dynamics by performing a temporal profiling of both messenger RNAs (mRNAs) and microRNAs (miRNAs) in MCF-7 cells (an ER+ model cell line for breast cancer) in response to estrogen stimulation. We identified three primary expression trends-transient, induced, and repressed-that were each enriched for genes with distinct cellular functions. Integrative analysis of mRNA and miRNA temporal expression profiles identified miR-503 as the strongest candidate master regulator of the estrogen response, in part through suppression of ZNF217-an oncogene that is frequently amplified in cancer. We confirmed experimentally that miR-503 directly targets ZNF217 and that overexpression of miR-503 suppresses MCF-7 cell proliferation. Moreover, the levels of ZNF217 and miR-503 are associated with opposite outcomes in breast cancer patient cohorts, with high expression of ZNF217 associated with poor survival and high expression of miR-503 associated with improved survival. Overall, these data indicate that miR-503 acts as a potent estrogen-induced candidate tumor suppressor miRNA that opposes cellular proliferation and has promise as a novel therapeutic for breast cancer. More generally, our work provides a systemslevel framework for identifying functional interactions that shape the temporal dynamics of gene expression.

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MicroRNAs as regulators of beta‐cell function and dysfunction

Osmai

Bang-Berthelsen

et al. 2015

Diabetes Metabolism Res

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SummaryIn the last decade, there has been an explosion in both the number of and knowledge about miRNAs associated with both type 1 and type 2 diabetes. Even though we are presently in the initial stages of understanding how this novel class of posttranscriptional regulators are involved in diabetes, recent studies have demonstrated that miRNAs are important regulators of the islet transcriptome, controlling apoptosis, differentiation and proliferation, as well as regulating unique islet and beta-cell functions and pathways such as insulin expression, processing and secretion. Furthermore, a large number of miRNAs have been linked to diabetogenic processes induced by elevated levels of glucose, free fatty acids and inflammatory cytokines. Thus, miRNAs are novel therapeutic targets with the potential of protecting the beta-cell, and there is proof of principle that miRNA antagonists, so-called antagomirs, are effective in vivo for other disorders. miRNAs are exported out of cells in exosomes, raising the intriguing possibility of cell-to-cell communication between distant tissues via miRNAs and that miRNAs can be used as biomarkers of beta-cell function, mass and survival. The purpose of this review is to provide a status on how miRNAs control beta-cell function and viability in health and disease. Copyright © 2015 John Wiley & Sons, Ltd. Keywords miRNA; diabetes; apoptosis; islets; insulin; beta-cells Non-coding RNAs -an introductionA central dogma in molecular biology states that DNA is converted to messenger RNAs (mRNA) that carry the genetic information to ribosomes where the mRNAs are translated to polypeptides. This dogma has been moderated by the realization that large amounts of genomic regions harbour non-coding RNA (ncRNA), as well as the discovery of new classes of short and long ncRNAs with different regulatory roles in the cell. The involvement of ncRNAs in many regulatory systems in the cell and their diversity of functions have led to an increased focus on their role in cell development and differentiation, physiology and the pathophysiology of diseases such as diabetes [1][2][3].The provision of novel high-throughput, low-cost technologies to sequence millions of RNA reads has revolutionized the discovery of novel classes of RNA species, and RNA molecules with important regulatory functions have been identified, such as microRNA (miRNA), circular RNA, endogenous small-interfering RNA, Piwi interacting RNA, small nucleolar RNA, vault RNA, small nuclear RNA and several classes of long ncRNA [4][5][6] (Figure 1), many of which are emerging as interesting subjects in diabetes research [2,7].

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Beta Cell 5′-Shifted isomiRs Are Candidate Regulatory Hubs in Type 2 Diabetes

Cited by 81 publications

References 49 publications

Bioinformatic analysis of endogenous and exogenous small RNAs on lipoproteins

Bioinformatic analysis of endogenous and exogenous small RNAs on lipoproteins

An integrative transcriptomics approach identifies miR-503 as a candidate master regulator of the estrogen response in MCF-7 breast cancer cells

MicroRNAs as regulators of beta‐cell function and dysfunction

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