RNA-Seq Blog

Happening This Week: RNA-Seq Summit 2013

RNA-Seq Blog Administrator — Wed, 19 Jun 2013 17:19:25 +0000

The much anticipated RNA-Seq Summit will be held this week in Boston, MA.

RNA-Seq 2013 brings together RNA-Seq leaders and innovators from pharma, biotech, genome institutes and universities. Leave the meeting with…

An understanding of when and how to transition to RNA-Seq from microarray technology for maximum accuracy of gene expression measurement
A toolbox of bioinformatics solutions and the most appropriate and unified integrated approach to managing, analyzing and interpreting huge volumes of data
Knowledge of how an exceptional experimental design can help to enhance drug discovery to maximize the results
An overview of the benefits of outsourcing to boost the time and cost efficiency of your NGS program for more streamlined applications
An expert’s guide to the latest and best software frameworks for de novo transcriptome assembly and analysis
The answers to optimizing biomarker discovery and target validation through streamlined techniques data application and integration techniques

Just a short list of the attending organizations…

Pfizer

Fluidigm

Beckman Coulter

Complete Genomics

Merck

GlaxoSmtihKline

Bristol-Myers Squibb

Genzyme Biosurgery

Agilent Technologies

Boehringer Ingelheim

AstraZeneca

UCSF

NuGEN Technologies

AVEO Pharmaceuticals

H3 Biomedicine

Synthetic Genomics

Broad Institute

Complete Genomics

University of North Carolina

Sanofi

Enzymatics

Stanford University

Genentech

Asuragen

Maverix Biomics

Biogen Idec

QIAGEN

Expression Analysis

Baylor College of Medicine

Illumina

Yale University

Arizona State University

Vertex Pharmaceuticals

Affymetrix

Lexogen

Dendreon Corporation

Happening This Week: RNA-Seq Summit 2013 is a post from: RNA-Seq Blog

A Review of Computational Tools in microRNA Discovery

RNA-Seq Blog Administrator — Thu, 13 Jun 2013 19:39:04 +0000

Since microRNAs (miRNAs) were discovered, their impact on regulating various biological activities has been a surprising and exciting field. Knowing the entire repertoire of these small molecules is the first step to gain a better understanding of their function. High throughput discovery tools such as RNA-Seq significantly increased the number of known miRNAs in different organisms in recent years. However, the process of being able to accurately identify miRNAs is still a complex and difficult task, requiring the integration of experimental approaches with computational methods. A number of prediction algorithms based on characteristics of miRNA molecules have been developed to identify new miRNA species. Different approaches have certain strengths and weaknesses and in this review, the authors aim to summarize several commonly used tools in metazoan miRNA discovery.

Selected computational tools for miRNA prediction and their main characteristics.

Tool	Website	Year
miRscan	genes.mit.edu/mirscan	2003
miRSeeker	–	2003
miRAlign	bioinfo.au.tsinghua.edu.cn/miralign	2005
Phylogenetic shadowing	–	2005
ProMiR	bi.snu.ac.kr/ProMiR	2005
Triplet-SVM	bioinfo.au.tsinghua.edu.cn/software/mirnasvm	2005
miR-abela	www.mirz.unibas.ch/cgi/pred_miRNA_genes.cgi	2005
RNAmicro	www.bioinf.uni-leipzig.de/~jana/index.php/jana-hertel-software/65-jana-hertel-rnamicro	2006
miRFinder	www.bioinformatics.org/mirfinder	2007
miPred	www.bioinf.seu.edu.cn/miRNA	2007
MiRRim	www.ncrna.org/software/miRRim	2007
miRDeep	www.mdc-berlin.de/en/research/research_teams/systems_biology_of_gene_regulatory_elements/projects/miRDeep	2008
miRanalyzer	web.bioinformatics.cicbiogune.es/microRNA/miRanalyser.php	2009
SSCprofiler	mirna.imbb.forth.gr/SSCprofiler.html	2009
HHMMiR	http://www.benoslab.pitt.edu/kadriAPBC2009.html	2009

Gomes CP, Cho JH, Hood L, Franco OL, Pereira RW, Wang K. (2013) A Review of Computational Tools in microRNA Discovery. Front Genet 4, 81. [article]

A Review of Computational Tools in microRNA Discovery is a post from: RNA-Seq Blog

Incoming search terms:

Sequence Comparative Analysis Using Networks source code
tcga rna-seq depth
best methods to rna-seq mirna
mirna for non model genomes rnaseq
mirnaseq normalization

MicroRNA Transcriptome Reveals Novel and Conserved Targets in Hot Pepper (Capsicum annuum)

RNA-Seq Blog Administrator — Wed, 12 Jun 2013 19:32:03 +0000

MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 21 nt in length which play important roles in regulating gene expression in plants. Although many miRNA studies have focused on a few model plants, miRNAs and their target genes remain largely unknown in hot pepper (Capsicum annuum), one of the most important crops cultivated worldwide.

Here, researchers at the Seoul National University, Korea employed high-throughput sequencing technology to identify miRNAs in pepper extensively from 10 different libraries, including leaf, stem, root, flower, and six developmental stage fruits. Based on a bioinformatics pipeline, they successfully identified 29 and 35 families of conserved and novel miRNAs, respectively. Northern blot analysis was used to validate further the expression of representative miRNAs and to analyze their tissue-specific or developmental stage-specific expression patterns. Moreover, they computationally predicted miRNA targets, many of which were experimentally confirmed using 5′ rapid amplification of cDNA ends analysis. One of the validated novel targets of miR-396 was a domain rearranged methyltransferase, the major de novo methylation enzyme, involved in RNA-directed DNA methylation in plants. This work provides the first reliable draft of the pepper miRNA transcriptome. It offers an expanded picture of pepper miRNAs in relation to other plants, providing a basis for understanding the functional roles of miRNAs in pepper.

Hwang DG, Park JH, Lim JY, Kim D, Choi Y, Kim S, Reeves G, Yeom SI, Lee JS, Park M, Kim S, Choi IY, Choi D, Shin C. (2013) The Hot Pepper (Capsicum annuum) MicroRNA Transcriptome Reveals Novel and Conserved Targets: A Foundation for Understanding MicroRNA Functional Roles in Hot Pepper. PLoS One 8(5)e64238. [article]

MicroRNA Transcriptome Reveals Novel and Conserved Targets in Hot Pepper (Capsicum annuum) is a post from: RNA-Seq Blog

Incoming search terms:

eco PCR check the RNAseq library quantity
transcriptomic analysis ppt

A Hierarchical Bayesian Model for Estimating and Inferring Differential Isoform Expression for Multi-Sample RNA-Seq Data

RNA-Seq Blog Administrator — Tue, 11 Jun 2013 19:22:36 +0000

RNA-Seq has drastically changed our ways of studying transcriptomes in providing more precise estimates of gene expression, including isoform-specific expression. Most of the available methods for RNA-Seq data focus on one sample at a time. Researchers at the University of Pennsylvania School of Medicine present a Poisson-Gamma hierarchical model for multi-sample RNA-Seq data analysis in order to simultaneously estimate isoform-specific expression and to identify differentially expressed iso-forms. This model has the advantage of borrowing information across all samples in estimating expression levels, which can improve the estimates drastically, particularly for low abundance isoforms. Furthermore, their hierarchical model has the ability to account for overdispersion in the data and also can incorporate sample-specific covariates in the underlying model, which facilitates the isoform-specific differential expression analysis. Simulation studies demonstrated that this Bayesian multi-sample approach can lead to more precise estimates of isoform-specific expression and higher power to detect differential expression by borrowing information across all samples than single sample analysis, especially for isoforms of low abundance. They further illustrated our methods using the RNA-Seq data of 10 Yoruban and 10 Caucasian individuals.

Vardhanabhuti S, Li M, Li H. (2013) A Hierarchical Bayesian Model for Estimating and Inferring Differential Isoform Expression for Multi-Sample RNA-Seq Data. Stat Biosci 5(1), 119-137. [abstract]

A Hierarchical Bayesian Model for Estimating and Inferring Differential Isoform Expression for Multi-Sample RNA-Seq Data is a post from: RNA-Seq Blog

Incoming search terms:

a hierarchical bayesian model for estimating and inferring differential isoform expression for multi-sample rna-seq data
isoform expression compare database

RNA-Seq analysis of the effects of metal nanoparticle exposure on the transcriptome of Chlamydomonas reinhardtii

RNA-Seq Blog Administrator — Tue, 11 Jun 2013 19:11:27 +0000

The wide spread use of anoparticles (NPs) raises concern of their potential toxicological effects in humans and ecosystems. Here researchers at the Université de Montréal used RNA-Seq to evaluate the effects of exposure to four different metal-based NPs, nAg, nTiO2, and nZnO and CdTe/CdS quantum dots (QD), in the eukaryotic green alga Chlamydomonas reinhardtii. The transcriptome was characterized before and after exposure to each NP type. Specific toxicological effects were inferred from the functions of genes whose transcripts either increased or decreased. Data analysis resulted in important differences and also similarities among the NPs. Elevated levels of transcripts of several marker genes for stress were observed, suggesting that only nZnO caused non-specific global stress to the cells under environmentally relevant conditions. Genes with photosynthesis-related functions were decreased drastically during exposure to nTiO2 and slightly during exposures to the other NP types. This pattern suggests either toxicological effects in the chloroplast or effects that mimic a transition from low to high light. nAg exposure dramatically elevated the levels of transcripts encoding known or predicted components of the cell wall and the flagella, suggesting it damages structures exposed to the external milieu. Exposures to nTiO2, nZnO, and QD elevated transcripts encoding subunits of the proteasome, suggesting proteasome inhibition, a phenomenon believed to underlie the development and progression of several major diseases, including Alzheimer’s disease, and used in chemotherapy against multiple myeloma.

Simon DF, Domingos RF, Hauser C, Hutchins CM, Zerges W, Wilkinson KJ. (2013) RNA-Seq analysis of the effects of metal nanoparticle exposure on the transcriptome of Chlamydomonas reinhardtii. Appl Environ Microbiol [Epub ahead of print]. [abstract]

RNA-Seq analysis of the effects of metal nanoparticle exposure on the transcriptome of Chlamydomonas reinhardtii is a post from: RNA-Seq Blog

Transcriptome Characterization by RNA-Seq Reveals the Involvement of the Complement Components in Noise-Traumatized Rat Cochleae

RNA-Seq Blog Administrator — Mon, 10 Jun 2013 19:04:23 +0000

Acoustic trauma, a leading cause of sensorineural hearing loss in adults, induces a complex degenerative process in the cochlea. Although previous investigations have identified multiple stress pathways, a comprehensive analysis of cochlear responses to acoustic injury is still lacking. In the current study, researchers from the Center for Hearing and Deafness University at Buffalo used the next-generation RNA-sequencing (RNA-seq) technique to sequence the whole transcriptome of the normal and noise-traumatized cochlear sensory epithelia (CSE). CSE tissues were collected from rat inner ears 1 d after the rats were exposed to a 120-dB (sound pressure level) noise for 2 h. The RNA-seq generated over 176 million sequence reads for the normal CSE and over 164 million reads for the noise-traumatized CSE. Alignment of these sequences with the rat Rn4 genome revealed the expression of over 17000 gene transcripts in the CSE, over 2000 of which were exclusively expressed in either the normal or noise-traumatized CSE. Seventy-eight gene transcripts were differentially expressed (70 upregulated and 8 downregulated) after acoustic trauma. Many of the differentially expressed genes are related to the innate immune system. Further expression analyses using qRT-PCR confirmed the constitutive expression of multiple complement genes in the normal organ of Corti and the changes in the expression levels of the complement factor I (Cfi) and complement component 1, s subcomponent (C1s) after acoustic trauma. Moreover, protein expression analysis revealed strong expression of Cfi and C1s proteins in the organ of Corti. Importantly, these proteins exhibited expression changes following acoustic trauma. Collectively, the results of the current investigation suggest the involvement of the complement components in cochlear responses to acoustic trauma.

Patel M, Hu Z, Bard J, Jamison J, Cai Q, Hu BH. (2013) Transcriptome Characterization by RNA-Seq Reveals the Involvement of the Complement Components in Noise-Traumatized Rat Cochleae. Neuroscience [Epub ahead of print]. [article]

Transcriptome Characterization by RNA-Seq Reveals the Involvement of the Complement Components in Noise-Traumatized Rat Cochleae is a post from: RNA-Seq Blog

Incoming search terms:

htseq-count transposable element
Transcriptome characterization by RNA-Seq reveals the involvement of the complement components in noise-traumatized rat cochleae

VirusFinder: Software for Efficient and Accurate Detection of Viruses and Their Integration Sites in Host Genomes through Next Generation Sequencing Data

RNA-Seq Blog Administrator — Fri, 07 Jun 2013 18:57:36 +0000

Next generation sequencing (NGS) technologies allow us to explore virus interactions with host genomes that lead to carcinogenesis or other diseases; however, this effort is largely hindered by the dearth of efficient computational tools.

Now, researchers at Vanderbilt University School of Medicine have developed a new tool, VirusFinder, for the identification of viruses and their integration sites in host genomes using NGS data, including whole transcriptome sequencing (RNA-Seq), whole genome sequencing (WGS), and targeted sequencing data. VirusFinder’s unique features include the characterization of insertion loci of virus of arbitrary type in the host genome and high accuracy and computational efficiency as a result of its well-designed pipeline.

Availability: The source code as well as additional data of VirusFinder is publicly available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.

Wang Q, Jia P, Zhao Z. (2013) VirusFinder: Software for Efficient and Accurate Detection of Viruses and Their Integration Sites in Host Genomes through Next Generation Sequencing Data. PLoS One 2013 May 24;8(5), e64465. [article]

VirusFinder: Software for Efficient and Accurate Detection of Viruses and Their Integration Sites in Host Genomes through Next Generation Sequencing Data is a post from: RNA-Seq Blog

Incoming search terms:

ddl ebook RNAs in Prokaryotes
NGS sequencing bin ?
Optimizing de novo assembly of short-read RNA-seq data for phylogenomics ppt
P-body RNASeq
r based pipelines for ngs sequence analysis
software trinity rna-seq parametros

Featured Job – Bioinformatician – VBI

RNA-Seq Blog Administrator — Thu, 06 Jun 2013 13:04:37 +0000

Established in July 2000 at Virginia Tech, the Virginia Bioinformatics Institute (VBI) is a world-class research institute dedicated to the study of the biological sciences. The Institute’s mission is to solve some of society’s most important problems in life science through transdisciplinary research and education.

By using bioinformatics and combining transdisciplinary approaches to information technology and biology, researchers at VBI interpret and apply vast amounts of biological data generated from basic research to some of today’s key challenges in the biomedical, environmental and agricultural sciences. Work at VBI involves collaboration in diverse disciplines such as mathematics, computer science, biology, plant pathology, medical informatics, biochemistry, systems biology, statistics, economics and synthetic biology. Transdisciplinary research at the institute encompasses scientific program areas that include bioinformatics, cellular networks, complex systems and genomes. The institute develops genomic and bioinformatic tools that can be applied to the study of infectious diseases as well as the discovery of new vaccine, drug and diagnostic targets.

The Bioinformatician will serve as a member in VBI’s Data Analysis Core (DAC). In achieving the Institute’s mission, the DAC focuses its multidisciplinary research on working with PI’s to apply computational biology and informatics tools to PI focused projects where the infrastructure or expertise are beyond what is feasible or logistically appropriate to duplicate in individual PI labs. The Bioinformatician will be expected to contribute to collaborative research involving human disease and biotechnology, and genetics, genomics and proteomics research.

The Bioinformatician will work with a team of scientists and programmers on various projects involving basic clinical research and clinical operations, especially Next Gen Sequencing data and microarray data. The Bioinformatician will be expected to work collaboratively and participate in the development of publications for peer-reviewed journals as well as on grants proposals to funding agencies and other entities.

In accordance the university hiring procedures for non-student positions, this position will require a conviction check prior to beginning an employment engagement.

Dependent on the qualifications of the successful candidate, the research faculty rank may be either Research Associate or Senior Research Associate. For information regarding the university’s faculty ranks, please review the Faculty Handbook at http://www.provost.vt.edu/faculty_handbook/faculty_handbook.html

The successful candidate will possess a MS in Biological Sciences or equivalent field. Experience in programming in R, Perl, Java and Python on Linux clusters is a must as well as demonstrated proficiency working with bioinformatics tools. Proven organizational, time management, and multi-tasking skills and creativity, independence, high motivation and good communication skills are required. The successful candidate will also demonstrate ability to work collaboratively and effectively with researchers and scientists from a wide range of disciplines and capable of working a team environment and a strong inclination for trans-disciplinary science.

Preference will be given those candidates possessing a PhD in Biological Sciences or related field (required for the rank of Senior Research Associate). Knowledge or experience with CLIA/CAP regulations (required for the rank of Senior Research Associate). Experience in developing publications based on individual research with demonstrated record of publication in peer-reviewed journals (required for the rank of Senior Research Associate) coupled with a demonstrated publication record in disease biology.

Interested candidates should submit a current CV, letter of interest, and listing of professional references upon applying through www.jobs.vt.edu posting number SR0130061. To be considered, applications must be received through the website link provided and not through alternative channels. Review of applications will begin on June 3, 2013.

Compensation commensurate with experience

To learn more about VBI, please visit us at www.vbi.vt.edu

Equal Opportunity/Affirmative Action Employer

Featured Job – Bioinformatician – VBI is a post from: RNA-Seq Blog

Incoming search terms:

www rna-seqblog com featured-job-bioinformatician-vbi

RNA Sequencing Sources Sought – Notice RFP HHS-NIH-NIDA-NIA-AM2975853

RNA-Seq Blog Administrator — Thu, 06 Jun 2013 12:43:37 +0000

RNA Sequencing

Solicitation Number: RFPHHSNIHNIDANIAAM2975853

Agency: Department of Health and Human Services
Office: National Institutes of Health
Location: National Institute on Drug Abuse

Solicitation Number:

RFPHHSNIHNIDANIAAM2975853

Notice Type:

Sources Sought

Synopsis:

Added: Jun 03, 2013 12:50 pm

RNA Sequencing
Sources Sought Notice
RFP HHS-NIH-NIDA-NIA-AM2975853
Contracting Office Address
Department of Health and Human Services, National Institutes of Health, National Institute on Drug Abuse, Station Support Simplified Acquisitions, 9000 Rockville Pike, Bldg. 31, Rm. 1B59 Bethesda, MD, 20892, UNITED STATES

Introduction
This is a Small Business Sources Sought notice. This is NOT a solicitation for proposals, proposal abstracts, or quotations. The purpose of this notice is to obtain information regarding: (1) the availability and capability of qualified small business sources; (2) whether they are small businesses; HUBZone small businesses; service-disabled, veteran-owned small businesses; 8(a) small businesses; veteran-owned small businesses; woman-owned small businesses; or small disadvantaged businesses; and (3) their size classification relative to the North American Industry Classification System (NAICS) code for the proposed acquisition. Your responses to the information requested will assist the Government in determining the appropriate acquisition method, including whether a set-aside is possible.

Background Information
The Laboratory of Molecular Medicine and Neuroscience (LMMN) focuses on the disease Progressive Multifocal Leukoencephalopathy, which is caused by JC Virus. JC Virus causes lytic infection of cells of the central nervous system, particularly oligodendrocytes. In order to facilitate research on JC Virus, the LMMN has developed a system of human fetal neural multipotential cells, which can be differentiated into Oligodendrocytes. The differentiation process in humans is poorly understood, so we will perform RNA-seq at numerous time points during the differentiation process to understand gene expression in developing human oligodendrocytes. Our lab does not have the equipment to perform RNA-seq, so we need an outside group to provide this service.

Purpose and Objectives for the Procurement
The service provider will provide RNA Sequencing (RNA-Seq) for LMMN supplied RNA
templates. The RNA-Seq service includes: cDNA synthesis and library preparation, detection of
sequencing fragments using the Illumina platform, and an alignment of reads against a reference
genome. The primary objective of the study is to determine changes in gene expression and RNA splicing that occur during oligodendrocyte differentiation.

Capability Statement
Businesses that believe they possess the capabilities necessary to undertake this work should submit complete documentation of their capabilities to the Contract Specialist. The capabilities statement must specifically address each project requirement separately. Additionally, the capability statement should include 1) the total number of employees, 2) the professional qualifications of scientists, medical experts, and technical personnel as it relates to the above outlined requirements, 3) a description of general and specific facilities and equipment available, including computer equipment and software, 4) an outline of previous research projects that are similar to the project requirements in which the organization and proposed personnel have participated, and 5) any other information considered relevant to this program. The capability statement must not exceed 15 single sided or 7.5 double sided pages in length and using a 12-point font size minimum.

Interested organizations are required to identify their size standards in accordance with the Small Business Administration. The government requests that no proprietary or confidential business data be submitted in a response to this notice. However, responses that indicate the information therein is proprietary will be properly safeguarded for Government use only. Capability statements must include the name and telephone numbers of a point of contact having authority and knowledge to discuss responses with Government representatives. Capability statements in response to this market survey that do not provide sufficient information for evaluation will be considered non-responsive. When submitting this information, please reference the solicitation notice number.

All capability statements sent in response to this Sources Sought Notice must be submitted electronically (via email) to Andrea McGee, Contract Specialist – andrea.mcgee@nih.gov in MS Word within 15 calendar days of the date of this announcement. All responses must be received by the specified due date and time in order to be considered.

This notice does not obligate the Government to award a contract or otherwise pay for the information provided in the response. No proprietary, classified, confidential, or sensitive information should be included in your response. The Government reserves the right to use information provided by respondents for any purpose deemed necessary and legally appropriate. Any organization responding to this notice should ensure that its response is complete and sufficiently detailed to allow the Government to determine the organization’s qualifications to perform the work. Respondents are advised that the Government is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted. After review of the responses received, pre-solicitation and solicitation notices may be published in Federal Business Opportunities. However, responses to this notice will not be considered adequate responses to a solicitation. The solicitation release date is pending. The Government intends to negotiate a fixed-price contract.
Due Date: June 11, 2013 – 3:00 P. M. Eastern Standard Time.

Contracting Office Address:

6001 Executive Boulevard
Room 4211 – MSC 9559
Bethesda, Maryland 20892
United States

Place of Performance:

9000 Rockville Pike
Bldg. 10
Bethesda, Maryland 20892
United States

Primary Point of Contact.:

Andrea McGee

andrea.mcgee@nih.gov

Phone: 3014358781

Incoming search terms:

www rna-seqblog com rna-sequencing-sources-sought-notice-rfp-hhs-nih-nida-nia-am2975853
dario\s research about makabuhay plant
hhs-nih-nida-nia-am2975853
media rfp
sources sought notice

Computational approaches to the analysis of RNA-seq data

RNA-Seq Blog Administrator — Wed, 05 Jun 2013 12:10:25 +0000

From – I519: Introduction to Bioinformatics (3CR) – Indiana University – Bloomington

Instructor: Haixu Tang

Computational approaches to the analysis of RNA-seq data is a post from: RNA-Seq Blog

Incoming search terms:

Bias in Single-cell mRNA-Seq
paired end mapping rna seq seqmonk
Presentations|RNA-SeqBlog
r/bioconductor rna-seq
rna seq experiment ppt
www rna-seqblog com computational-approaches-to-the-analysis-of-rna-seq-data