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“RNA-Seq is perhaps the most complex NGS application “

In recent years, the introduction of massively parallel sequencing platforms for Next Generation Sequencing (NGS) protocols, able to simultaneously sequence hundred thousand DNA fragments, dramatically changed the landscape of the genetics studies. RNA-Seq for transcriptome studies, Chip-Seq for DNA-proteins interaction, CNV-Seq for large genome nucleotide variations are only some of the intriguing new applications supported by these innovative platforms. Among them RNA-Seq is perhaps the most complex NGS application. Expression levels of specific genes, differential splicing, allele-specific expression of transcripts can be accurately determined by RNA-Seq experiments to address many biological-related issues. All these attributes are not readily achievable from previously widespread hybridization-based or tag sequence-based approaches. However, the unprecedented level of sensitivity and the large amount of available data produced by NGS platforms provide clear advantages as well as new challenges and issues. This technology brings the great power to make several new biological observations and discoveries, it also requires a considerable effort in the development of new bioinformatics tools to deal with these massive data files. The paper aims to give a survey of the RNA-Seq methodology, particularly focusing on the challenges that this application presents both from a biological and a bioinformatics point of view.

J Biomed Biotechnol – 2010 – Costa V, Angelini C, De Feis I, Ciccodicola A

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Mar 15, 2011, 06:00 ET

Ingenuity Announces RNA-Sequencing Workflow Support and First-of-Its-Kind microRNA Filtering Capability With Latest Release of IPA

PR Newswire – Processed RNA-Seq datasets can now be uploaded directly into IPA and analyzed in the context of pathways and diseases for a rich biological interpretation of the data. This helps researchers quickly and accurately focus on the most important information within their large RNA – Seq datasets quickening…

March 14, 2011 08:30 ET

Partek Expands Global Operations – Software Manufacturer Increases Staff in Europe and Asia

Business Wire – Partek Incorporated, a global leader in bioinformatics software, today announced the expansion of its business development and support staff to keep pace with continued demand for its core product offering, Partek Genomics Suite. The company now has personnel throughout Europe — United Kingdom, France, Germany, Spain and Croatia — and a wholly owned subsidiary in Singapore servicing Asia, Australia and New Zealand.

Feb 23, 2011, 07:30 ET

Life Technologies to Launch Ion 318 Chip in Second Half of 2011 with 1Gb of Data Output

PR Newswire – Life Technologies Corporation (Nasdaq: LIFE) today announced that the Ion 318 semiconductor sequencing chip will be available for early access in September of this year, complete with RNA – Seq kits and analysis software, providing up to 1Gb of data output – 100…

Transcriptome characterization of the South African abalone Haliotis midae using sequencing-by-synthesis

Worldwide, the genus Haliotis is represented by 56 extant species and several of these are commercially cultured. Among the six abalone species found in South Africa, Haliotis midae is the only aquacultured species. Despite its economic importance, genomic sequence resources for H. midae, and for abalone in general, are still scarce. Next generation sequencing technologies provide a fast and efficient tool to generate large sequence collections that can be used to characterize the transcriptome and identify expressed genes associated with economically important traits like growth and disease resistance.¹

Novel and Conserved Micrornas in Dalian Purple Urchin (Strongylocentrotus Nudus) Identified by Next Generation Sequencing

The purple urchin, Strongylocentrotus nudus, is one of the most important marine economic animals that widely distributed in the cold seas along the coasts of eastern pacific area. To date, only 45 microRNAs have been identified in a related species, Strongylocentrotus purpurtus, and there is no report on S. nudus microRNAs. Herein, solexa sequencing technology was used to high throughput sequencing analysis of microRNAs in small RNA library isolated from five tissues of S. nudus.²

1. Franchini P, van der Merwe M, Roodt-Wilding R (2011) Transcriptome characterization of the South African abalone Haliotis midae using sequencing-by-synthesis. BMC Research Notes 4, 59. [article]
2. Wei Z, Liu X, Feng T, Chang Y. (2011) Novel and conserved micrornas in dalian purple urchin (strongylocentrotus nudus) identified by next generation sequencing. Int J Biol Sci 7(2):180-92. [article]

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GenomeView is a next-generation genome browser. This video shows some RNA-seq data from B. anthracis.

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SeqMonk is a program to enable the visualization and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It’s main features are:

• Import of mapped data from text files
• Creation of data groups for visualization and analysis
• Visualization of mapped regions against an annotated genome.
• Flexible quantitation of the mapped data to allow comparisons between data sets
• Statistical analysis of data to find regions of interest
• Creation of reports containing data and genome annotation

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ArrayExpressHTS is an R based pipeline for pre-processing, expression estimation and data quality assessment of high-throughput sequencing transcriptional profiling (RNA-seq) datasets. The pipeline starts from raw sequence files and produces standard Bioconductor R objects containing gene or transcript measurements for downstream analysis along with web reports for data quality assessment. It may be run locally on a user’s own computer or remotely on a distributed R-cloud farm at the European Bioinformatics Institute. It can be used to analyse user’s own datasets or public RNA-seq datasets from the ArrayExpress Archive. Read more

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GenePattern – is a powerful genomic analysis platform that provides access to more than 100 tools for gene expression analysis, proteomics, SNP analysis and common data processing tasks.

GenePattern offers a suite of tools to support a wide variety of RNA-seq analyses, including short-read mapping, identification of splice junctions, transcript and isoform detection, quantitation, and differential expression. The modules have been adapted from widely-used tools. GenePattern also provides pipelines that allow you to perform a number of multi-step RNA-seq analyses automatically. Read more

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We asked: In the Year 2015, what will it cost to perform RNA-Seq (whole transcriptome sequencing – human sample)?

You Answered:

$10	17	13%
$100	40	31%
$500	38	29%
$1,000	25	19%
$2,500	6	5%
$5,000	5	4%

The second wave of next generation sequencing technologies, referred to as single-molecule sequencing (SMS), carries the promise of profiling samples directly without employing polymerase chain reaction steps used by amplification-based sequencing (AS) methods. With the goal of uncovering the merits of both technologies, researchers at the University of Michigan examined mRNA sequencing results from single-molecule and amplification-based sequencing in a set of human cancer cell lines and tissues.

They observed a characteristic coverage bias towards high abundance transcripts in amplification-based sequencing. A larger fraction of AS reads cover highly expressed genes, such as those associated with translational processes and housekeeping genes, resulting in relatively lower coverage of genes at low and mid-level abundance. In contrast, the coverage of high abundance transcripts plateaus off using SMS. Consequently, SMS is able to sequence lower- abundance transcripts more thoroughly, including some that are undetected by AS methods; however, these include many more mapping artifacts.

A better understanding of the technical and analytical factors introducing platform specific biases in high throughput transcriptome sequencing applications will be critical in cross platform meta-analytic studies.

Sam LT, Lipson D, Raz T, Cao X, Thompson J, et al. (2011) A Comparison of Single Molecule and Amplification Based Sequencing of Cancer Transcriptomes. PLoS ONE 6(3), e17305. [article]

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By Vicki Glaser – Genetic Engineering News

Advanced Technological Approach Generates Genomic Data Better, Faster, and Cheaper

In the next-gen sequencing (NGS) arena, the focus over the past several years has been on technological advances, moving from second-generation to third-generation sequencing strategies and producing research instruments capable of delivering whole-genome sequences in parallel at increasing speed. More recently, as read lengths and coverage continue to increase, throughputs rise, and costs decline, the expanding range of applications of NGS has taken center stage.

…Genomic Health announced results from its next-gen sequencing-driven biomarker discovery program in breast cancer at the recent “Advances in Genome Biology and Technology” (AGBT) meeting. Based on sequencing of the whole human transcriptome in formalin-fixed paraffin-embedded (FFPE) tumor and normal breast tissue samples, the company found hundreds of differences in both coding and noncoding transcripts between the two sample populations. Genomic Health reported an association between specific genes and some non-coding RNAs and risk of breast cancer recurrence.

(read the entire article… )

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Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using high-throughput Illumina RNA-seq, the transcriptome from C. sinensis was analyzed at an unprecedented depth.

(read more… )

Shi C et al. (2011) Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds. BMC Genomics [Epub ahead of print]. [article]

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SeqMap is a tool for identifying viral integration sites from LAM-PCR and LM-PCR analysis. The tool will extract vector sequence data then search existing genome databases for matches to the unique sequences generated by the LAM or LM-PCR reaction. SeqMap displays the vector insertion site graphically, showing the chromosome location and distance to surrounding genes. The tool also allows you to organize your data and make notations. Read more

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• SEQanswers – RNA Sequencing

  • DESeq; can I omit timepoints during dispersal estimation? May 24, 2013
    I have a bacterial timecourse with 2 biological replicates per timepoint. There is a fair bit of variance between my replicates. I have spent the... […]
    amcloon
  • HT Seq Count stranded options May 24, 2013
    I am very new to bioinformatics, so I would be really grateful for some help! I have been using *HTSeq Count v0.5.3* and I am bit confused about... […]
    qwrissie
  • Tophat 2.0.8b installation error May 24, 2013
    I install tophat-2.0.8b to rerun the mapping. but when i make it, the error appears like this. make[1]: Entering directory... […]
    canhu
  • reason for low mapping rate?? May 23, 2013
    we did RNASeq using HiSeq 2000 100PE. When the data were back, I mapping them to the reference sequence, but got very low mapping rate (30-40%). I... […]
    miaom
  • cross-species data - questions about normalization May 23, 2013
    Hi, I have some data form various samples (cell types) in different species. I want to compare and analyze gene expression variability across the... […]
    trelek2
  • CuffDiff strange output May 23, 2013
    Hi, I hope that someone can be so gentle to help me. I'm analizing some data from RNA-Seq with TopHat and Cufflinks and I focus my attention on... […]
    Pruexel

• Biostar – RNA-Seq

  • Why am I getting so many unmapped reads in STAR, classified as "too short"?
    I am currently using STAR to map several Hi-SEQ mRNA runs. I'm having trouble getting a decent amount of reads to map, but I don't really understand why. I'm hoping you can shed some light :) In the final log, only about 50% (or less) of the reads map to the reference. I'm using a GTF in addition to the genome. The unmapped bin that most […]
  • What are the best practices for SNP identification in RNA seq transcriptome data
    I have 20 RICE RNA seq tranascriptome data hiseq 2000 platform paired end reads. I aligned fasta reads with BWA and remove PCR duplicates with PICARD. Later I call SNP with samtools using various parameters. I would like to clarify what parameters should I used while alinging to reference rice genome for looking SNP location 100 bp upstream and 250 bp downst […]
  • How do TopHat options -g , --supress-hits, and Bowtie options interplay?
    Hi, I am currently using TopHat2 to map RNA-seq runs. I think there have been some changes pertaining the -g option. Does anyone know how it works now? I used to think that setting -g would look for n alignments for a given read, report them [if top-scoring] and discard those reads that had more than g [top scoring] alignments. Now, the description sounds mo […]
  • What happened to -k in TopHat for multiple-mapping reads?
    Selecting -g n in tophat does not discard reads mapping more than n, but instead only reports n alignments for those out all all their TOP scoring alignments. I think there used to be an option -k that would allow one to discard reads that topped x alignments -- whatever happened to that? I only see -g in the tophat 2 manual, no reporting options like before […]
  • Does tophat use the library-type information for mapping, or just for the XS flag?
    When I specify library-type to TopHat, i.e., first-strand, second-strand, unstranded, TopHat appends a value + or - to the XS:A flag, which is useful for subsequent analyses, such as annotation. However, does this information actually influence the "mappability" of reads, or is this unaffected? My thinking is that the information would be considere […]
  • Purpose of Y-shaped adapters in Illumina Sequencing?
    Hi all, Y adapters different sequences to be annealed to the 5' and 3' ends of each molecule in a library. The arms of the Y are unique, and the middle part, connected to the DNA fragment, is complementary. What are the advantages of this? My take of this over having fully-complementary adapters (ADAPTER1 - - - - - ADAPTER1) is that: -Upon primer a […]