DOCSLIB.ORG

RNA Sequencing Services

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
RNA Sequencing Services RNA Sequencing Services microRNA / Small RNA Digital Gene Expression (mRNA) Sequencing Service Sequencing Service Next-gen sequencing is a new method and powerful tool The DGE service offered by LC Sciences makes use of used to identify and quantitatively decode the entire RNA Sequencing technology to “count” each individual population of small RNAs in your total RNA sample. LC transcript, offering distinct advantages over semi- Sciences provides a comprehensive sequencing service quantitative array-based gene-expression analysis utilizing Illumina’s high-throughput sequencing systems which rely on signal intensities. As an technology which enables comprehensive, highly alternative to expression arrays, DGE provides a cost sensitive and specific discovery and profiling of all forms effective basic differential expression analysis of known of small RNAs in your sample. genes via the latest next-gen sequencing technology. Single-Cell RNA-Seq Service Poly(A) RNA-Seq / Total RNA-Seq Sequencing Services Single-cell RNA-Seq can be used to examine the expression of individual cells and provides a higher In addition to expression quantification, RNA-Seq resolution of cellular differences as compared to technology can be used to determine the structure of traditional RNA-Seq. Single-cell RNA-Seq enables us to genes, their splicing patterns or other post understand the function of an individual cell in the transcriptional modifications, and to detect rare and context of its microenvironment. Start with as little as novel transcripts. Total RNA-Seq enables the sequencing 10 pg-10 ng of total RNA. of both poly(A) and non-poly(A) RNAs, such as long non -coding RNA (lncRNA), via a ribosomal depletion library preparation strategy. LC Sciences provides a turnkey solution for transcriptome sequencing featuring the latest in RNA-Seq technology. www.lcsciences.com 1-888-528-8818 LC Sciences Comprehensive Services Turnkey Solution These comprehensive services are designed to be one-stop and produce the results needed to quickly advance your biological and biomedical research. For all types of RNA sequencing, our “Total RNA to Data” services include: sample prep/QC, library preparation, RNA sequencing, bioinformatics analysis, and high-level customer support. Expert Services LC Sciences has been providing RNA discovery, profiling and related bioinformatics services since 2005 and our experts have examined thousands of varied RNA datasets, giving us unique insight into RNA research. We don’t merely deliver data; we will handle all the advanced bioinformatics analysis and help you find answers to the questions you’re asking. Library Deep Advanced Preparation Sequencing Data Analysis Key Advantages of RNA Sequencing RNA Sequencing provides a more comprehensive view of the transcriptome. RNA Sequencing enables us to sequence and profile all species of transcripts in your total RNA samples - from mRNA to non-coding RNAs to small RNAs. RNA Sequencing is not necessarily dependent on any prior sequence knowledge. There is no need for the design of probes that must be based on prior sequence or secondary structure information. Therefore, transcriptome profiling in any species is possible, making this method particularly attractive for non-model species. Additionally, RNA Sequencing data can be used to build de novo gene models. RNA Sequencing has increased dynamic range and sensitivity. RNA Sequencing enables you to achieve “digital” transcript expression analysis meaning that expression level data are based on each individual transcript that is sequenced and counted. By increasing the sequencing depth, a potentially unlimited dynamic range can be reached making RNA Sequencing an ideal tool for detection rare transcripts. RNA Sequencing provides information of sequence variation in transcripts. RNA-Seq yields a rich data set that includes information about post transcriptional mutations and their genomic context. Because RNA-Seq data yields information about how exons are connected, it can reveal sequence variations in the transcripts due to alternative splicing events and provide allele-specific or isoform-specific gene expression information. Additionally, RNA-Seq data is useful for gene mapping functions such as describing the length of UTRs and exon boundaries. 60-03F-02 microRNA Sequencing Service RNA Sequencing provides an excellent tool for discovery of novel microRNAs (miRNAs) as well as genome-wide profiling of small RNA and miRNA expression in various samples. LC Sciences provides a discovery sequencing service utilizing the Illumina high-throughput sequencing technology which enables comprehensive coverage, highly sensitive and specific discovery and profiling of all forms of small RNAs in your sample. Profile miRNA in any species - there is no need for probes based on prior sequence or secondary structure information. Profiling is transcriptome-wide - investigate all miRNAs and small RNAs, of any size, known and unknown, in your sample. Discover novel small RNAs and detect rare transcripts and transcript variants, such as sequence isoforms and SNPs. Bioinformatics Package Includes: Raw sequencing data – up to 100M 50bp single-end reads per Alignment, classification, & functional annotation of all mapped lane – either FASTA-A or FASTA-Q files with base-calling quality reads scores Biostatistical analysis – expression analysis, multi-parameter data LC Sciences analysis and quality filtering - processed data is analysis, length distribution, transcript copy number reduced to mappable reads comparisons, etc Custom construction of reference database(s) - miRBase, miRNA target prediction genome, etc and mapping of all quality reads miRNA target GO and KEGG enrichment analysis microRNA Sequencing Data Flow Example - pig sample generated ~20M reads. Sequencing reads are mapped to pig mirs in miRBase, mirs of related species and mapped to pig genome. Group 1 Others Known Pig miRNAs Group 2 Group 3 Group 4 No Hit Known miRNAs Candidate pig miRNAs Potentially Candidate pig miRNAs genome inconsistent novel miRNAs (713) 664-7087 with miRBase 1-888-528-8818 Fax (713) 664-8181 [email protected] 60-03F-03 www.lcsciences.com Digital Gene Expression (mRNA) Sequencing Service The incredible power of RNA-Seq was initially applied primarily for complex whole transcriptome applications such as discovery of rare genes, splice junctions and gene fusions or for the study of novel and less well-characterized organisms. However, as the technology is improving and costs are decreasing, RNA sequencing is now suitable to be used for simple expression profiling of known genes as well. An Alternative to Expression Arrays Achieve digital transcript expression analysis – RNA sequencing technology digitally “counts” each individual transcript, offering distinct advantages over semi-quantitative array-based gene-expression analysis systems which rely on relative signal intensities. Expression profiling is truly genome-wide – there is no need for probes based on prior sequence information. Accurate quantitation of expression levels over 5 orders of magnitude of transcript abundance. Profile gene expression in any species – quantitate differential expression across groups of different biological samples. Provides a cost effective basic differential expression analysis of known genes via the latest next-gen sequencing technology. Bioinformatics Package Includes: Raw sequencing data – up to 100M 50bp single-end reads per lane – either FASTA- A or FASTA-Q files with base-calling quality scores Data reduced to mappable reads, a list of unique sequences and their copy numbers Genomic mapping of quality sequencing reads Gene expression profiling Test for differential expression at gene and transcript level GO and KEGG annotation and enrichment analysis Simple report of analysis showing statistical significance of differential expression Log FPKM FPKM Test_id Gene Locus (fold Test_stat P_value Significant Sample1 Sample2 change) XLOC_041924 BCLAF1 1:29312111-29312566 7.23 0.30 -3.18 -3.12 0.0018 Yes XLOC_145478 MOSPD1 X:108883967-108884284 13.84 4.76 -1.07 -3.10 .0019 Yes XLOC_150271 IRF7 2:294234-294407 11.27 28.54 .93 3.09 .0020 Yes XLOC_180169 SORBS2 15:44062921-44063290 8.59 0.37 -3.14 -3.08 .0021 Yes 60-03F-05 Digital Gene Expression (mRNA) Sequencing Service Poly(A) RNA-Seq Sequencing Service LC Sciences provides a turnkey solution for transcriptome sequencing featuring the latest in RNA-Seq technology. Next-gen sequencing is a powerful tool used for transcriptome analysis that can determine the structure of genes, their splicing patterns and other post transcriptional modifications, detect rare and novel transcripts, and quantify their changing expression levels during development and under different disease conditions. Profile expression in any species - there is no need for probes based on prior sequence information. Compare genome-wide expression in different species or otherwise different biological samples. Detect mutation events such as: novel splicing events, gene fusions, isoforms, SNPs, or other specific coding mutations. Detect rare, or novel transcripts. Bioinformatics Package Includes: RNA-Seq Reads Raw sequencing data – up to 125M x 2 100bp paired-end reads – either FASTA-A or FASTA-Q files with base-calling quality scores Processed data is reduced to mappable reads De Novo assembly (if applicable) Align reads to Alignment of RNA-Seq reads to customer specified reference genome genome Identification and construction of splice-junctions
Load more

Recommended publications
  • Next Generation DNA Sequencing
    Genes 2010, 1, 385-387; doi:10.3390/genes1030385 OPEN ACCESS genes ISSN 2073-4425 www.mdpi.com/journal/genes Editorial Special Issue: Next Generation DNA Sequencing Paul Richardson PRC LLC, 25 Amber Lane, Lafayette, CA 94549, USA; E-Mail: [email protected]; Tel.: +1 925 301-5460 Received: 21 October 2010 / Accepted: 26 October 2010 / Published: 27 October 2010 Next Generation Sequencing (NGS) refers to technologies that do not rely on traditional dideoxy-nucleotide (Sanger) sequencing where labeled DNA fragments are physically resolved by electrophoresis. These new technologies rely on different strategies, but essentially all of them make use of real-time data collection of a base level incorporation event across a massive number of reactions (on the order of millions versus 96 for capillary electrophoresis for instance). The major commercial NGS platforms available to researchers are the 454 Genome Sequencer (Roche), Illumina (formerly Solexa) Genome analyzer, the SOLiD system (Applied Biosystems/Life Technologies) and the Heliscope (Helicos Corporation). The techniques and different strategies utilized by these platforms are reviewed in a number of the papers in this special issue. These technologies are enabling new applications that take advantage of the massive data produced by this next generation of sequencing instruments. In this special issue, nine papers review and demonstrate the utility and potential of next generation sequencing. One of the biggest consequences with NGS technologies is how to deal with all of the data produced by these platforms. Magi et al. [1] review the software tools available for the multiple functions needed to process and interpret the huge amounts of data produced by these instruments.
    [Show full text]
  • Evaluation of Normalization Methods in Mammalian Microrna-Seq Data
    Downloaded from rnajournal.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press METHOD Evaluation of normalization methods in mammalian microRNA-Seq data LANA XIA GARMIRE1 and SHANKAR SUBRAMANIAM1 Department of Bioengineering, Jacobs School of Engineering, University of California at San Diego, La Jolla, California 92093-0412, USA ABSTRACT Simple total tag count normalization is inadequate for microRNA sequencing data generated from the next generation sequencing technology. However, so far systematic evaluation of normalization methods on microRNA sequencing data is lacking. We comprehensively evaluate seven commonly used normalization methods including global normalization, Lowess normalization, Trimmed Mean Method (TMM), quantile normalization, scaling normalization, variance stabilization, and invariant method. We assess these methods on two individual experimental data sets with the empirical statistical metrics of mean square error (MSE) and Kolmogorov-Smirnov (K-S) statistic. Additionally, we evaluate the methods with results from quantitative PCR validation. Our results consistently show that Lowess normalization and quantile normalization perform the best, whereas TMM, a method applied to the RNA-Sequencing normalization, performs the worst. The poor performance of TMM normalization is further evidenced by abnormal results from the test of differential expression (DE) of microRNA-Seq data. Comparing with the models used for DE, the choice of normalization method is the primary factor that affects the results of DE. In summary, Lowess normalization and quantile normalization are recommended for normalizing microRNA-Seq data, whereas the TMM method should be used with caution. Keywords: microRNA-Seq; next generation sequencing; statistical normalization; high-throughput data analysis INTRODUCTION much smaller than mRNAs. For example, so far there are <1000 annotated microRNAs in human that are expected to The next generation sequencing (NGS) technology has regulate z30% of genes.
    [Show full text]
  • Ancient Microrna Profiles of a 14,300-Year-Old Canid Samples Confirm
    Downloaded from rnajournal.cshlp.org on October 7, 2021 - Published by Cold Spring Harbor Laboratory Press Fromm et al 1 2 Title: Ancient microRNA profiles of a 14,300-year-old canid samples confirm 3 taxonomic origin and give glimpses into tissue-specific gene regulation from 4 the Pleistocene 5 6 Running title: Sequencing of ancient microRNAs. 7 8 Authors: Bastian Fromm1*, Marcel Tarbier1, Oliver Smith2,3, Emilio Mármol- 9 Sánchez1,4, Love Dalén4,5, M. Tom P. Gilbert2,6, Marc R. Friedländer1* 10 11 Affiliations: 12 1 Science for Life Laboratory, Department of Molecular Biosciences, The Wenner-Gren 13 Institute, Stockholm University, Stockholm, Sweden 14 2 Section for Evolutionary Genomics, The Globe Institute, Faculty of Health and Medical 15 Sciences, University of Copenhagen, Copenhagen, Denmark 16 3 Micropathology Ltd, Venture Centre, University of Warwick Science Park, Coventry, UK 17 4 Centre for Palaeogenetics, Stockholm, Sweden 18 5 Department of Bioinformatics and Genetics, Swedish Museum of Natural History, 19 SE-10405 Stockholm, Sweden 20 6 Norwegian University of Science and Technology, University Museum, Trondheim, 21 Norway 22 23 24 * corresponding authors: [email protected] and [email protected] 25 26 Keywords: microRNAs, paleotranscriptomics, Pleistocene, canid, gene regulation Downloaded from rnajournal.cshlp.org on October 7, 2021 - Published by Cold Spring Harbor Laboratory Press Fromm et al. 27 Abstract 28 DNA sequencing is the current key technology for historic or ancient biological samples and has 29 led to many exciting discoveries in the field of paleogenomics. However, functional insights into 30 tissue identity, cellular composition or gene regulation cannot be gained from DNA.
    [Show full text]
  • Downregulation of Hsa-Microrna-204-5P and Identification of Its Potential Regulatory Network in Non-Small Cell Lung Cancer: RT-Q
    Liang et al. Respiratory Research (2020) 21:60 https://doi.org/10.1186/s12931-020-1274-9 RESEARCH Open Access Downregulation of hsa-microRNA-204-5p and identification of its potential regulatory network in non-small cell lung cancer: RT- qPCR, bioinformatic- and meta-analyses Chang-Yu Liang1†, Zu-Yun Li1†, Ting-Qing Gan2†, Ye-Ying Fang3†, Bin-Liang Gan1†, Wen-Jie Chen1†, Yi-Wu Dang1†, Ke Shi1†, Zhen-Bo Feng1* and Gang Chen1* Abstract Background: Pulmonary malignant neoplasms have a high worldwide morbidity and mortality, so the study of these malignancies using microRNAs (miRNAs) has attracted great interest and enthusiasm. The aim of this study was to determine the clinical effect of hsa-microRNA-204-5p (miR-204-5p) and its underlying molecular mechanisms in non-small cell lung cancer (NSCLC). Methods: Expression of miR-204-5p was investigated by real-time quantitative PCR (RT-qPCR). After data mining from public online repositories, several integrative assessment methods, including receiver operating characteristic (ROC) curves, hazard ratios (HR) with 95% confidence intervals (95% CI), and comprehensive meta-analyses, were conducted to explore the expression and clinical utility of miR-204-5p. The potential objects regulated and controlled by miR-204-5p in the course of NSCLC were identified by estimated target prediction and analysis. The regulatory network of miR-204-5p, with its target genes and transcription factors (TFs), was structured from database evidence and literature references. Results: The expression of miR-204-5p was downregulated in NSCLC, and the downtrend was related to gender, histological type, vascular invasion, tumor size, clinicopathologic grade and lymph node metastasis (P<0.05).
    [Show full text]
  • Analyzing Mirna from Raw NGS Data to Quantification
    G C A T T A C G G C A T genes Article DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification Athanasios Alexiou 1,2, Dimitrios Zisis 2, Ioannis Kavakiotis 1, Marios Miliotis 1,2, Antonis Koussounadis 3 , Dimitra Karagkouni 1,2 and Artemis G. Hatzigeorgiou 1,2,3,* 1 DIANA Lab, Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece; [email protected] (A.A.); [email protected] (I.K.); [email protected] (M.M.); [email protected] (D.K.) 2 Hellenic Pasteur Institute, 11521 Athens, Greece; [email protected] 3 Department of Electrical & Computer Engineering, University of Thessaly, 38221 Volos, Greece; [email protected] * Correspondence: [email protected]; Tel.: +30-24210-74758; Fax: +30-24210-74997 Abstract: microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological con- ditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated compu- tational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the anal- ysis for the robustness of the final results and conclusions.
    [Show full text]
  • Addressing Bias in Small RNA Library Preparation for Sequencing: a New Protocol Recovers Micrornas That Evade Capture by Current Methods
    ORIGINAL RESEARCH published: 22 December 2015 doi: 10.3389/fgene.2015.00352 Addressing Bias in Small RNA Library Preparation for Sequencing: A New Protocol Recovers MicroRNAs that Evade Capture by Current Methods Jeanette Baran-Gale1,2*,C.LisaKurtz2, Michael R. Erdos3, Christina Sison4, Alice Young4, Emily E. Fannin2, Peter S. Chines3 and Praveen Sethupathy1,2* 1 Bioinformatics and Computational Biology Curriculum, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 2 Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 3 National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA, 4 NIH Intramural Sequencing Center, National Institutes of Health, Rockville, MD, USA Edited by: Ghanshyam Upadhyay, Recent advances in sequencing technology have helped unveil the unexpected City College of New York-CUNY, USA Reviewed by: complexity and diversity of small RNAs. A critical step in small RNA library preparation Sandeep Kumar, for sequencing is the ligation of adapter sequences to both the 5 and 3 ends of small State University of New York College RNAs. Studies have shown that adapter ligation introduces a significant but widely of Optometry, USA Ravi C. Kalathur, unappreciated bias in the results of high-throughput small RNA sequencing. We show New York Structural Biology Center, that due to this bias the two widely used Illumina library preparation protocols produce USA strikingly different microRNA (miRNA) expression profiles in the same batch of cells. Manish Mishra, All Saints University College There are 102 highly expressed miRNAs that are >5-fold differentially detected and of Medicine, Saint Vincent some miRNAs, such as miR-24-3p, are over 30-fold differentially detected.
    [Show full text]
  • Microrna and Circrna Expression Analysis in a Zbtb1 Gene Knockout Monoclonal EL4 Cell Line
    ORIGINAL RESEARCH published: 05 July 2021 doi: 10.3389/fcimb.2021.706919 MicroRNA and circRNA Expression Analysis in a Zbtb1 Gene Knockout Monoclonal EL4 Cell Line † † Jun-Hong Wang 1,2,3 , Chun-Wei Shi 1,2,3 , Yi-Yuan Lu 1,2,3, Yan Zeng 1,2,3, Ming-Yang Cheng 1,2,3, Ru-Yu Wang 1,2,3,YuSun 1,2,3, Yan-Long Jiang 1,2,3, Wen-Tao Yang 1,2,3, Dan-Dan Zhao 1,2,3, Hai-Bin Huang 1,2,3, Li-Ping Ye 1,2,3, Xin Cao 1,2,3*, Gui-Lian Yang 1,2,3* and Chun-Feng Wang 1,2,3* 1 College of Veterinary Medicine, Jilin Agricultural University, Changchun, China, 2 Jilin Provincial Engineering Research Center of Animal Probiotics, Jilin Agricultural University, Changchun, China, 3 Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, China Edited by: Yongsheng Liu, Chinese Academy of Agricultural Zinc finger and BTB domain containing 1(Zbtb1) is a transcriptional suppressor protein, Sciences, China and a member of the mammalian Zbtb gene family. Previous studies have shown that Reviewed by: Zbtb1 is essential for T-cell development. However, the role of Zbtb1 in T-cell lymphoma is Peng Tan, Broad Institute, United States undetermined. In this study, an EL4 cell line with Zbtb1 deletion was constructed using the Dongqin Yang, CRISPR-Cas9 technique. The expression profiles of microRNA and circRNA produced by Fudan University, China the control and gene deletion groups were determined by RNA-seq.
    [Show full text]
  • Single-Cell Microrna Sequencing Method Comparison and Application to Cell Lines and Circulating Lung Tumor Cells
    ARTICLE https://doi.org/10.1038/s41467-021-24611-w OPEN Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells Sarah M. Hücker 1,8, Tobias Fehlmann 2,8, Christian Werno1, Kathrin Weidele1, Florian Lüke1,3, ✉ Anke Schlenska-Lange4, Christoph A. Klein 1,5, Andreas Keller 2,6,7,9 & Stefan Kirsch 1,9 1234567890():,; Molecular single cell analyses provide insights into physiological and pathological processes. Here, in a stepwise approach, we first evaluate 19 protocols for single cell small RNA sequencing on MCF7 cells spiked with 1 pg of 1,006 miRNAs. Second, we analyze MCF7 single cell equivalents of the eight best protocols. Third, we sequence single cells from eight different cell lines and 67 circulating tumor cells (CTCs) from seven SCLC patients. Altogether, we analyze 244 different samples. We observe high reproducibility within pro- tocols and reads covered a broad spectrum of RNAs. For the 67 CTCs, we detect a median of 68 miRNAs, with 10 miRNAs being expressed in 90% of tested cells. Enrichment analysis suggested the lung as the most likely organ of origin and enrichment of cancer-related categories. Even the identification of non-annotated candidate miRNAs was feasible, underlining the potential of single cell small RNA sequencing. 1 Division of Personalized Tumor Therapy, Fraunhofer-Institute for Toxicology and Experimental Medicine, Regensburg, Germany. 2 Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany. 3 Department of Internal Medicine III Hematology & Oncology, University Medical Center Regensburg, Regensburg, Germany. 4 Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany.
    [Show full text]
  • Erythrocyte Microrna Sequencing Reveals Differential Expression in Relapsing-Remitting Multiple Sclerosis Kira Groen1,2, Vicki E
    Groen et al. BMC Medical Genomics (2018) 11:48 https://doi.org/10.1186/s12920-018-0365-7 RESEARCH ARTICLE Open Access Erythrocyte microRNA sequencing reveals differential expression in relapsing-remitting multiple sclerosis Kira Groen1,2, Vicki E. Maltby1,2, Rodney A. Lea2,3, Katherine A. Sanders4, J. Lynn Fink5, Rodney J. Scott2,6,7, Lotti Tajouri8 and Jeannette Lechner-Scott1,2,9* Abstract Background: There is a paucity of knowledge concerning erythrocytes in the aetiology of Multiple Sclerosis (MS) despite their potential to contribute to disease through impaired antioxidant capacity and altered haemorheological features. Several studies have identified an abundance of erythrocyte miRNAs and variable profiles associated with disease states, such as sickle cell disease and malaria. The aim of this study was to compare the erythrocyte miRNA profile of relapsing-remitting MS (RRMS) patients to healthy sex- and age-matched controls. Methods: Erythrocytes were purified by density-gradient centrifugation and RNA was extracted. Following library preparation, samples were run on a HiSeq4000 Illumina instrument (paired-end 100 bp sequencing). Sequenced erythrocyte miRNA profiles (9 patients and 9 controls) were analysed by DESeq2. Differentially expressed miRNAs were validated by RT-qPCR using miR-152-3p as an endogenous control and replicated in a larger cohort (20 patients and 18 controls). After logarithmic transformation, differential expression was determined by two-tailed unpaired t-tests. Logistic regression analysis was carried out and receiver operating characteristic (ROC) curves were generated to determine biomarker potential. Results: A total of 236 erythrocyte miRNAs were identified. Of twelve differentially expressed miRNAs in RRMS two showed increased expression (adj.
    [Show full text]
  • Computational Analysis of Microrna Function
    microRNA and smallRNA profiling Anton Enright Group Leader EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK http://www.ebi.ac.uk/enright/ [email protected] High Throughput Sequencing Analysis 2013 Thursday, 24 October 13 microRNA Regulation Adapted from He L. and Hannon G.J; Nature reviews genetics 5:552 (2004) EMBL-EBI 2 High throughput RNA Seq Thursday, 24 October 13 microRNA Regulation Adapted from He L. and Hannon G.J; Nature reviews genetics 5:552 (2004) EMBL-EBI 2 High throughput RNA Seq Thursday, 24 October 13 MicroRNA Processing EMBL-EBI 3 High throughput RNA Seq Thursday, 24 October 13 MicroRNA Processing EMBL-EBI 3 High throughput RNA Seq Thursday, 24 October 13 MicroRNA Processing EMBL-EBI 3 High throughput RNA Seq Thursday, 24 October 13 microRNA Profiling EMBL-EBI 4 High throughput RNA Seq Thursday, 24 October 13 microRNA Profiling • MicroRNA microarray • Statistical issues with number of probes • Cross-hybridisation and biases • Cheap and straightforward • Small RNA Sequencing • Quantitation can be difficult due to biases • Ability to detect novel microRNAs, edits and variation • Reproducible • qRT-PCR Based Approaches • quite accurate • lower throughput • Single Molecule profiling • e.g. Nanostring • New technology EMBL-EBI 5 High throughput RNA Seq Thursday, 24 October 13 Nanostring EMBL-EBI 6 High throughput RNA Seq Thursday, 24 October 13 Nanostring EMBL-EBI 6 High throughput RNA Seq Thursday, 24 October 13 microRNA microarrays • MicroRNA array manufacturers love to talk about how many probes they have on their chips. • In reality there are < 1000 microRNAs for your species and likely <30 expressed in your sample.
    [Show full text]
  • Deep-Sequencing of Endothelial Cells Exposed to Hypoxia Reveals the Complexity of Known and Novel Micrornas
    Downloaded from rnajournal.cshlp.org on October 8, 2021 - Published by Cold Spring Harbor Laboratory Press Deep-sequencing of endothelial cells exposed to hypoxia reveals the complexity of known and novel microRNAs CHRISTINE VOELLENKLE,1,6 JEROEN VAN ROOIJ,1,6 ALESSANDRO GUFFANTI,2,6 ELENA BRINI,2 PASQUALE FASANARO,3 ELEONORA ISAIA,1 LARRY CROFT,4 MATEI DAVID,5 MAURIZIO C. CAPOGROSSI,3 ANNA MOLES,2 ARMANDO FELSANI,2 and FABIO MARTELLI3,7 1Laboratorio di Cardiologia Molecolare, IRCCS-Policlinico San Donato, San Donato Milanese, 20097 Milan, Italy 2Genomnia srl, Lainate, 20020 Milan, Italy 3Laboratorio di Patologia Vascolare, Istituto Dermopatico dell’Immacolata-IRCCS, 00167 Rome, Italy 4Institute for Molecular Bioscience, University of Queensland, 4072 Brisbane, Australia 5Computational Biology Laboratory, University of Toronto, M5S 3G4 Toronto, Canada ABSTRACT In order to understand the role of microRNAs (miRNAs) in vascular physiopathology, we took advantage of deep-sequencing techniques to accurately and comprehensively profile the entire miRNA population expressed by endothelial cells exposed to hypoxia. SOLiD sequencing of small RNAs derived from human umbilical vein endothelial cells (HUVECs) exposed to 1%% O2 or normoxia for 24 h yielded more than 22 million reads per library. A customized bioinformatic pipeline identified more than 400 annotated microRNA/microRNA* species with a broad abundance range: miR-21 and miR-126 totaled almost 40%% of all miRNAs. A complex repertoire of isomiRs was found, displaying also 59 variations, potentially affecting target recognition. High- stringency bioinformatic analysis identified microRNA candidates, whose predicted pre-miRNAs folded into a stable hairpin. Validation of a subset by qPCR identified 18 high-confidence novel miRNAs as detectable in independent HUVEC cultures and associated to the RISC complex.
    [Show full text]
  • Mirge 2.0 for Comprehensive Analysis of Microrna Sequencing Data Yin Lu, Alexander S
    Lu et al. BMC Bioinformatics (2018) 19:275 https://doi.org/10.1186/s12859-018-2287-y SOFTWARE Open Access miRge 2.0 for comprehensive analysis of microRNA sequencing data Yin Lu, Alexander S. Baras and Marc K. Halushka* Abstract Background: miRNAs play important roles in the regulation of gene expression. The rapidly developing field of microRNA sequencing (miRNA-seq; small RNA-seq) needs comprehensive, robust, user-friendly and standardized bioinformatics tools to analyze these large datasets. We present miRge 2.0, in which multiple enhancements were made towards these goals. Results: miRge 2.0 has become more comprehensive with increased functionality including a novel miRNA detection method, A-to-I editing analysis, integrated standardized GFF3 isomiR reporting, and improved alignment to miRNAs. The novel miRNA detection method uniquely uses both miRNA hairpin sequence structure and composition of isomiRs resulting in higher specificity for potential miRNA identification. Using known miRNA data, our support vector machine (SVM) model predicted miRNAs with an average Matthews correlation coefficient (MCC) of 0.939 over 32 human cell datasets and outperformed miRDeep2 and miRAnalyzer regarding phylogenetic conservation. The A-to-I editing detection strongly correlated with a reference dataset with adjusted R2 = 0.96. miRge 2.0 is the most up-to-date aligner with custom libraries to both miRBase v22 and MirGeneDB v2.0 for 6 species: human, mouse, rat, fruit fly, nematode and zebrafish; and has a tool to create custom libraries. For user-friendliness, miRge 2.0 is incorporated into bcbio- nextgen and implementable through Bioconda. Conclusions: miRge 2.0 is a redesigned, leading miRNA RNA-seq aligner with several improvements and novel utilities.
    [Show full text]