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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

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.

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]

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]

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]

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]

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]

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. Read more

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

Instructor: Haixu Tang

Epidermal Growth Factor (EGF) plays an important function in the regulation of cell growth, proliferation, and differentiation by binding to its receptor (EGFR) and providing cancer cells with increased survival responsiveness. Signal transduction carried out by EGF has been extensively studied at both transcriptional and post-transcriptional levels. Little is known about the involvement of microRNAs (miRNAs) in the EGF signaling pathway. miRNAs have emerged as major players in the complex networks of gene regulation, and cancer miRNA expression studies have evidenced a direct involvement of miRNAs in cancer progression.

In this study, a team led by researchers at the Centre for Genomic Regulation (CRG), Barcelona, Spain have used an integrative high content analysis approach to identify the specific miRNAs implicated in EGF signaling in HeLa cells as potential mediators of cancer mediated functions. They used microarray and deep-sequencing technologies in order to obtain a global view of the EGF miRNA transcriptome with a robust experimental cross-validation. By applying a procedure based on Rankprod tests, they delimited a solid set of EGF-regulated miRNAs. After validating regulated miRNAs by reverse transcription quantitative PCR, they derived protein networks and biological functions from the predicted targets of the regulated miRNAs to gain insight into the potential role of miRNAs in EGF-treated cells. In addition, they analyzed sequence heterogeneity due to editing relative to the reference sequence (isomiRs) among regulated miRNAs.

The researchers propose that the use of global genomic miRNA cross-validation derived from high throughput technologies can be used to generate more reliable datasets inferring more robust networks of co-regulated predicted miRNA target genes.

• Llorens F, Hummel M, Pantano L, Pastor X, Vivancos A, Castillo E, Matllin H, Ferrer A, Ingham M, Noguera M, Kofler R, Dohm JC, Pluvinet R, Bayés M, Himmelbauer H, Del Rio JA, Martí E, Sumoy L. (2013) Microarray and deep sequencing cross-platform analysis of the mirRNome and isomiR variation in response to epidermal growth factor. BMC Genomics 14(1), 371. [Epub ahead of print]. [abstract]

Ganesh Sathe speaks to Izzy Scott-Moncrieff in the run up to the upcoming RNA-Seq 2013 summit,18^th -20^th June 2013, Boston, MA

Dr. Ganesh Sathe was instrumental in forming various technology groups including DNA synthesis, mouse-genotyping, DNA/ protein sequencing, microarray, gene synthesis etc at GlaxoSmithKline (GSK). Ganesh continues to work as a manger of DNA sequencing and Transcriptomics technologies at GSK and contributes to drug discovery and development.

What initially attracted you to RNA-Seq?

RNA-Seq gives us the complete gene expression profile per given sample, and therefore the ability to capture data from the entire transcriptome.

RNA-seq provides researchers several  advantages over microarray assays: firstly, measuring expression by RNA-seq is a quantitative process because actual cDNA fragments are counted. Microarrays rely on an analog to digital signal conversion of a hybridization signal to measure expression.

The second reason is due to recent developments in platforms like that from Illumina, which give researchers the ability to perform RNA-Seq on hundreds of samples in parallel, thereby decreasing the cost-per-sample of RNA-seq significantly. In fact, with current technology and chemistries, RNA-seq already costs less per sample than a microarray.

Download a PDF of the entire interview at – http://rna-seqsummit.com/library

Conifers have dominated forests for more than 200 million years and are of huge ecological and economic importance. Here a team led by researchers at the Stockholm University, Sweden present the draft assembly of the 20-gigabase genome of Norway spruce (Picea abies), the first available for any gymnosperm. The number of well-supported genes (28,354) is similar to the >100 times smaller genome of Arabidopsis thaliana, and there is no evidence of a recent whole-genome duplication in the gymnosperm lineage. Instead, the large genome size seems to result from the slow and steady accumulation of a diverse set of long-terminal repeat transposable elements, possibly owing to the lack of an efficient elimination mechanism. Comparative sequencing of Pinus sylvestris, Abies sibirica, Juniperus communis, Taxus baccata and Gnetum gnemon reveals that the transposable element diversity is shared among extant conifers. Expression of 24-nucleotide small RNAs, previously implicated in transposable element silencing, is tissue-specific and much lower than in other plants. The researchers further identify numerous long (>10,000 base pairs) introns, gene-like fragments, uncharacterized long non-coding RNAs and short RNAs. This opens up new genomic avenues for conifer forestry and breeding.

• Nystedt B,  et al. (2013) The Norway spruce genome sequence and conifer genome evolution. Nature 497(7451), 579-84. [article]

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