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Non-Coding RNA, Volume 3, Issue 2 (June 2017) – 6 articles

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190 KiB  
Editorial
The Non-Coding RNA Journal Club: Highlights on Recent Papers—5
by Cyrinne Achour, Baptiste Bogard, Florent Hubé, Sendurai A. Mani, Gaetano Santulli and Joseph H. Taube
Non-Coding RNA 2017, 3(2), 21; https://doi.org/10.3390/ncrna3020021 - 14 Jun 2017
Cited by 1 | Viewed by 3680
Abstract
We are delighted to share with you our fifth Journal Club and highlight some of the most interesting papers published recently.[...] Full article
(This article belongs to the Collection The Non-Coding RNA Journal Club: Highlights on Recent Papers)
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Article
Detecting Disease Specific Pathway Substructures through an Integrated Systems Biology Approach
by Salvatore Alaimo, Gioacchino Paolo Marceca, Alfredo Ferro and Alfredo Pulvirenti
Non-Coding RNA 2017, 3(2), 20; https://doi.org/10.3390/ncrna3020020 - 19 Apr 2017
Cited by 21 | Viewed by 5494
Abstract
In the era of network medicine, pathway analysis methods play a central role in the prediction of phenotype from high throughput experiments. In this paper, we present a network-based systems biology approach capable of extracting disease-perturbed subpathways within pathway networks in connection with [...] Read more.
In the era of network medicine, pathway analysis methods play a central role in the prediction of phenotype from high throughput experiments. In this paper, we present a network-based systems biology approach capable of extracting disease-perturbed subpathways within pathway networks in connection with expression data taken from The Cancer Genome Atlas (TCGA). Our system extends pathways with missing regulatory elements, such as microRNAs, and their interactions with genes. The framework enables the extraction, visualization, and analysis of statistically significant disease-specific subpathways through an easy to use web interface. Our analysis shows that the methodology is able to fill the gap in current techniques, allowing a more comprehensive analysis of the phenomena underlying disease states. Full article
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-Coding RNA Research)
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Article
Deciphering microRNAs and Their Associated Hairpin Precursors in a Non-Model Plant, Abelmoschus esculentus
by Kavitha Velayudha Vimala Kumar, Nagesh Srikakulam, Priyavathi Padbhanabhan and Gopal Pandi
Non-Coding RNA 2017, 3(2), 19; https://doi.org/10.3390/ncrna3020019 - 31 Mar 2017
Cited by 10 | Viewed by 5185
Abstract
MicroRNAs (miRNAs) are crucial regulatory RNAs, originated from hairpin precursors. For the past decade, researchers have been focusing extensively on miRNA profiles in various plants. However, there have been few studies on the global profiling of precursor miRNAs (pre-miRNAs), even in model plants. [...] Read more.
MicroRNAs (miRNAs) are crucial regulatory RNAs, originated from hairpin precursors. For the past decade, researchers have been focusing extensively on miRNA profiles in various plants. However, there have been few studies on the global profiling of precursor miRNAs (pre-miRNAs), even in model plants. Here, for the first time in a non-model plant—Abelmoschus esculentus with negligible genome information—we are reporting the global profiling to characterize the miRNAs and their associated pre-miRNAs by applying a next generation sequencing approach. Preliminarily, we performed small RNA (sRNA) sequencing with five biological replicates of leaf samples to attain 207,285,863 reads; data analysis using miRPlant revealed 128 known and 845 novel miRNA candidates. With the objective of seizing their associated hairpin precursors, we accomplished pre-miRNA sequencing to attain 83,269,844 reads. The paired end reads are merged and adaptor trimmed, and the resulting 40–241 nt (nucleotide) sequences were picked out for analysis by using perl scripts from the miRGrep tool and an in-house built shell script for Minimum Fold Energy Index (MFEI) calculation. Applying the stringent criteria of the Dicer cleavage pattern and the perfect stem loop structure, precursors for 57 known miRNAs of 15 families and 18 novel miRNAs were revealed. Quantitative Real Time (qRT) PCR was performed to determine the expression of selected miRNAs. Full article
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Article
Assessment of isomiR Discrimination Using Commercial qPCR Methods
by Rogan Magee, Aristeidis G. Telonis, Tess Cherlin, Isidore Rigoutsos and Eric Londin
Non-Coding RNA 2017, 3(2), 18; https://doi.org/10.3390/ncrna3020018 - 24 Mar 2017
Cited by 42 | Viewed by 5049
Abstract
We sought to determine whether commercial quantitative polymerase chain reaction (qPCR) methods are capable of distinguishing isomiRs: variants of mature microRNAs (miRNAs) with sequence endpoint differences. We used two commercially available miRNA qPCR methods to quantify miR-21-5p in both synthetic and real cell [...] Read more.
We sought to determine whether commercial quantitative polymerase chain reaction (qPCR) methods are capable of distinguishing isomiRs: variants of mature microRNAs (miRNAs) with sequence endpoint differences. We used two commercially available miRNA qPCR methods to quantify miR-21-5p in both synthetic and real cell contexts. We find that although these miRNA qPCR methods possess high sensitivity for specific sequences, they also pick up background signals from closely related isomiRs, which influences the reliable quantification of individual isomiRs. We conclude that these methods do not possess the requisite specificity for reliable isomiR quantification. Full article
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Article
Computational Characterization of ncRNA Fragments in Various Tissues of the Brassica rapa Plant
by Boseon Byeon, Andriy Bilichak and Igor Kovalchuk
Non-Coding RNA 2017, 3(2), 17; https://doi.org/10.3390/ncrna3020017 - 24 Mar 2017
Cited by 9 | Viewed by 4789
Abstract
Recently, a novel type of non-coding RNA (ncRNA), known as ncRNA fragments or ncRFs, has been characterised in various organisms, including plants. The biogenesis mechanism, function and abundance of ncRFs stemming from various ncRNAs are poorly understood, especially in plants. In this work, [...] Read more.
Recently, a novel type of non-coding RNA (ncRNA), known as ncRNA fragments or ncRFs, has been characterised in various organisms, including plants. The biogenesis mechanism, function and abundance of ncRFs stemming from various ncRNAs are poorly understood, especially in plants. In this work, we have computationally analysed the composition of ncRNAs and the fragments that derive from them in various tissues of Brassica rapa plants, including leaves, meristem tissue, pollen, unfertilized and fertilized ova, embryo and endosperm. Detailed analysis of transfer RNA (tRNA) fragments (tRFs), ribosomal RNA (rRNA) fragments (rRFs), small nucleolar RNA (snoRNA) fragments (snoRFs) and small nuclear RNA (snRNA) fragments (snRFs) showed a predominance of tRFs, with the 26 nucleotides (nt) fraction being the largest. Mapping ncRF reads to full-length mature ncRNAs showed a strong bias for one or both termini. tRFs mapped predominantly to the 5′ end, whereas snRFs mapped to the 3′ end, suggesting that there may be specific biogenesis and retention mechanisms. In the case of tRFs, specific isoacceptors were enriched, including tRNAGly(UCC) and tRFAsp(GUC). The analysis showed that the processing of 26-nt tRF5′ occurred by cleavage at the last unpaired nucleotide of the loop between the D arm and the anticodon arm. Further support for the functionality of ncRFs comes from the analysis of binding between ncRFs and their potential targets. A higher average percentage of binding at the first half of fragments was observed, with the highest percentage being at 2–6 nt. To summarise, our analysis showed that ncRFs in B. rapa are abundantly produced in a tissue-specific manner, with bias toward a terminus, the bias toward the size of generated fragments and the bias toward the targeting of specific biological processes. Full article
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-Coding RNA Research)
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Article
Present Scenario of Long Non-Coding RNAs in Plants
by Garima Bhatia, Neetu Goyal, Shailesh Sharma, Santosh Kumar Upadhyay and Kashmir Singh
Non-Coding RNA 2017, 3(2), 16; https://doi.org/10.3390/ncrna3020016 - 24 Mar 2017
Cited by 52 | Viewed by 9381
Abstract
Small non-coding RNAs have been extensively studied in plants over the last decade. In contrast, genome-wide identification of plant long non-coding RNAs (lncRNAs) has recently gained momentum. LncRNAs are now being recognized as important players in gene regulation, and their potent regulatory roles [...] Read more.
Small non-coding RNAs have been extensively studied in plants over the last decade. In contrast, genome-wide identification of plant long non-coding RNAs (lncRNAs) has recently gained momentum. LncRNAs are now being recognized as important players in gene regulation, and their potent regulatory roles are being studied comprehensively in eukaryotes. LncRNAs were first reported in humans in 1992. Since then, research in animals, particularly in humans, has rapidly progressed, and a vast amount of data has been generated, collected, and organized using computational approaches. Additionally, numerous studies have been conducted to understand the roles of these long RNA species in several diseases. However, the status of lncRNA investigation in plants lags behind that in animals (especially humans). Efforts are being made in this direction using computational tools and high-throughput sequencing technologies, such as the lncRNA microarray technique, RNA-sequencing (RNA-seq), RNA capture sequencing, (RNA CaptureSeq), etc. Given the current scenario, significant amounts of data have been produced regarding plant lncRNAs, and this amount is likely to increase in the subsequent years. In this review we have documented brief information about lncRNAs and their status of research in plants, along with the plant-specific resources/databases for information retrieval on lncRNAs. Full article
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-Coding RNA Research)
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