miRSeq: A User-Friendly Standalone Toolkit for Sequencing Quality Evaluation and miRNA Profiling

MicroRNAs (miRNAs) present diverse regulatory functions in a wide range of biological activities. Studies on miRNA functions generally depend on determining miRNA expression profiles between libraries by using a next-generation sequencing (NGS) platform. Currently, several online web services are developed to provide small RNA NGS data analysis. However, the submission of large amounts of NGS data, conversion of data format, and limited availability of species bring problems. In this study, we developed miRSeq to provide alternatives. To test the performance, we had small RNA NGS data from four species, including human, rat, fly, and nematode, analyzed with miRSeq. The alignments results indicate that miRSeq can precisely evaluate the sequencing quality of samples regarding percentage of self-ligation read, read length distribution, and read category. miRSeq is a user-friendly standalone toolkit featuring a graphical user interface (GUI). After a simple installation, users can easily operate miRSeq on a PC or laptop by using a mouse. Within minutes, miRSeq yields useful miRNA data, including miRNA expression profiles, 3′ end modification patterns, and isomiR forms. Moreover, miRSeq supports the analysis of up to 105 animal species, providing higher flexibility.

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miRNA expression profiles in Smad4-positive and Smad4-negative SW620 human colon cancer cells detected by next-generation small RNA sequencing

Cancer Management and Research ◽

10.2147/cmar.s178261 ◽

2018 ◽

Vol Volume 10 ◽

pp. 5479-5490

Author(s):

Wei Yan ◽

Zhongcai Liu ◽

Wenchao Yang ◽

Guoyang Wu

Keyword(s):

Colon Cancer ◽

Small Rna ◽

Mirna Expression ◽

Expression Profiles ◽

Human Colon ◽

Small Rna Sequencing ◽

Colon Cancer Cells ◽

Human Colon Cancer ◽

Mirna Expression Profiles ◽

Human Colon Cancer Cells

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Evaluating gastroenteropancreatic neuroendocrine tumors through microRNA sequencing

Endocrine Related Cancer ◽

10.1530/erc-18-0244 ◽

2019 ◽

Vol 26 (1) ◽

pp. 47-57 ◽

Cited By ~ 10

Author(s):

Nicole Panarelli ◽

Kathrin Tyryshkin ◽

Justin Jong Mun Wong ◽

Adrianna Majewski ◽

Xiaojing Yang ◽

...

Keyword(s):

Neuroendocrine Tumors ◽

Small Rna ◽

Mirna Expression ◽

Expression Profiles ◽

Machine Learning Techniques ◽

Disease Stage ◽

Small Rna Sequencing ◽

Gastroenteropancreatic Neuroendocrine Tumors ◽

Mirna Expression Profiles ◽

Microrna Sequencing

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) can be challenging to evaluate histologically. MicroRNAs (miRNAs) are small RNA molecules that often are excellent biomarkers due to their abundance, cell-type and disease stage specificity and stability. To evaluate miRNAs as adjunct tissue markers for classifying and grading well-differentiated GEP-NETs, we generated and compared miRNA expression profiles from four pathological types of GEP-NETs. Using quantitative barcoded small RNA sequencing and state-of-the-art sequence annotation, we generated comprehensive miRNA expression profiles from archived pancreatic, ileal, appendiceal and rectal NETs. Following data preprocessing, we randomly assigned sample profiles to discovery (80%) and validation (20%) sets prior to data mining using machine-learning techniques. High expression analyses indicated that miR-375 was the most abundant individual miRNA and miRNA cistron in all samples. Leveraging prior knowledge that GEP-NET behavior is influenced by embryonic derivation, we developed a dual-layer hierarchical classifier for differentiating GEP-NET types. In the first layer, our classifier discriminated midgut (ileum, appendix) from non-midgut (rectum, pancreas) NETs based on miR-615 and -92b expression. In the second layer, our classifier discriminated ileal from appendiceal NETs based on miR-125b, -192 and -149 expression, and rectal from pancreatic NETs based on miR-429 and -487b expression. Our classifier achieved overall accuracies of 98.5% and 94.4% in discovery and validation sets, respectively. We also found provisional evidence that low- and intermediate-grade pancreatic NETs can be discriminated based on miR-328 expression. GEP-NETs can be reliably classified and potentially graded using a limited panel of miRNA markers, complementing morphological and immunohistochemistry-based approaches to histologic evaluation.

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Differential miRNA Expression Profiles in Cumulus and Mural Granulosa Cells from Human Pre-ovulatory Follicles

MicroRNA ◽

10.2174/2211536607666180912152618 ◽

2018 ◽

Vol 8 (1) ◽

pp. 61-67 ◽

Cited By ~ 4

Author(s):

Daniela Andrei ◽

Roland A. Nagy ◽

Aafke van Montfoort ◽

Uwe Tietge ◽

Martijn Terpstra ◽

...

Keyword(s):

Rna Sequencing ◽

Granulosa Cells ◽

Small Rna ◽

Mirna Expression ◽

Target Gene ◽

Expression Profiles ◽

Cell Types ◽

Small Rna Sequencing ◽

Gene Sets ◽

Mirna Expression Profiles

Background: Mural Granulosa Cells (MGCs) and Cumulus Cells (CCs) are two specialized cell types that differentiate from a common progenitor during folliculogenesis. Although these two cell types have specialized functions and gene expression profiles, little is known about their microRNA (miRNA) expression patterns. Objective: To describe the miRNA profile of mural and cumulus granulosa cells from human preovulatory follicles. </P><P> Methods: Using small RNA sequencing, we defined the miRNA expression profiles of human primary MGCs and CCs, isolated from healthy women undergoing ovum pick-up for in vitro Fertilization (IVF). Results: Small RNA sequencing revealed the expression of several hundreds of miRNAs in MGCs and CCs with 53 miRNAs being significantly differentially expressed between MGCs and CCs. We validated the differential expression of miR-146a-5p, miR-149-5p, miR-509-3p and miR-182-5p by RT-qPCR. Analysis of proven targets revealed 37 targets for miR-146a-5p, 43 for miR-182-5p, 2 for miR-509-3p and 9 for miR-149-5p. Gene Ontology (GO) analysis for these 4 target gene sets revealed enrichment of 12 GO terms for miR-146a-5p and 10 for miR-182-5p. The GO term ubiquitin-like protein conjugation was enriched within both miRNA target gene sets. We generated miRNA expression profiles for MGCs and CCs and identified several differentially expressed miRNAs.

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Faculty Opinions recommendation of Altered miRNA expression profiles and miR-1a associated with urethane-induced pulmonary carcinogenesis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718117616.793484333 ◽

2013 ◽

Author(s):

James Klaunig ◽

Zemin Wang

Keyword(s):

Mirna Expression ◽

Expression Profiles ◽

Mirna Expression Profiles ◽

Pulmonary Carcinogenesis

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The Predominant microRNAs in β-cell Clusters for Insulin Regulation and Diabetic Control

Current Drug Targets ◽

10.2174/1389450121666191230145848 ◽

2020 ◽

Vol 21 (7) ◽

pp. 722-734

Author(s):

Adele Soltani ◽

Arefeh Jafarian ◽

Abdolamir Allameh

Keyword(s):

Mirna Expression ◽

Expression Profiles ◽

Expression Patterns ◽

Diabetic Control ◽

In Vitro Proliferation ◽

Cell Functions ◽

Mirna Expression Profiles ◽

Multiple Processes ◽

The Impact

micro (mi)-RNAs are vital regulators of multiple processes including insulin signaling pathways and glucose metabolism. Pancreatic β-cells function is dependent on some miRNAs and their target mRNA, which together form a complex regulative network. Several miRNAs are known to be directly involved in β-cells functions such as insulin expression and secretion. These small RNAs may also play significant roles in the fate of β-cells such as proliferation, differentiation, survival and apoptosis. Among the miRNAs, miR-7, miR-9, miR-375, miR-130 and miR-124 are of particular interest due to being highly expressed in these cells. Under diabetic conditions, although no specific miRNA profile has been noticed, the expression of some miRNAs and their target mRNAs are altered by posttranscriptional mechanisms, exerting diverse signs in the pathobiology of various diabetic complications. The aim of this review article is to discuss miRNAs involved in the process of stem cells differentiation into β-cells, resulting in enhanced β-cell functions with respect to diabetic disorders. This paper will also look into the impact of miRNA expression patterns on in vitro proliferation and differentiation of β-cells. The efficacy of the computational genomics and biochemical analysis to link the changes in miRNA expression profiles of stem cell-derived β-cells to therapeutically relevant outputs will be discussed as well.

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