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Alternative mRNA splicing (AS) is a major mechanism for increasing regulatory complexity. A key concept in AS is the distinction between alternatively and constitutively spliced exons (ASEs and CSEs, respectively). ASEs and CSEs have been reported to be differentially regulated, and to have distinct biological properties. However, the recent flood of RNA-sequencing data has obscured the boundary between ASEs and CSEs. Researchers are beginning to question whether ‘authentic CSEs’ do exist, and whether the ASE/CSE distinction is biologically invalid.

Here, Feng-Chi Chen with the National Health Research Institutes of Taiwan examines the influences of increasing transcriptome data on the human ASE/CSE classification and our past understanding of the properties of these two types of exons. Interestingly, although the percentage of human ASEs has increased dramatically in recent years, the overall distinction between ASEs and CSEs remains valid. For example, CSEs are longer, evolve more slowly, and less frequently correspond to intrinsically disordered protein regions than ASEs. In addition, only a relatively small number of human genes have their transcripts composed entirely of ASEs despite the large amount of high-throughput transcriptome information. Therefore, the ‘backbone’ concept of AS, in which CSEs constitute the invariant part and ASEs the flexible part of the transcript, appears to be generally true despite the increasing percentage of ASEs in the human exome.

 

• Chen FC. (2013) Are all of the human exons alternatively spliced? Brief Bioinform [Epub ahead of print]. [abstract]

Incoming search terms:

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Breast cancer transcriptome acquires a myriad of regulation changes, and splicing is critical for the cell to “tailor-make” specific functional transcripts. Researchers at The George Washington University systematically revealed splicing signatures of the three most common types of breast tumors using RNA sequencing: TNBC, non-TNBC and HER2-positive breast cancer.

1. Discovered subtype specific differentially spliced genes and splice isoforms not previously recognized in human transcriptome.
2. Demonstrated that exon skip and intron retention are predominant splice events in breast cancer.
3. Found that differential expression of primary transcripts and promoter switching are significantly deregulated in breast cancer compared to normal breast.
4. Validated the presence of novel hybrid isoforms of critical molecules like CDK4, LARP1, ADD3, and PHLPP2.

This study provides the first comprehensive portrait of transcriptional and splicing signatures specific to breast cancer sub-types, as well as previously unknown transcripts that prompt the need for complete annotation of tissue and disease specific transcriptome.

• Eswaran J, Horvath A, Godbole S, Reddy SD, Mudvari P, Ohshiro K, Cyanam D, Nair S, Fuqua SA, Polyak K, Florea LD, Kumar R. (2013) RNA sequencing of cancer reveals novel splicing alterations. Sci Rep 3, 1689. [article]

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Integromics partners with CITRE and CEIT to develop new algorithms and statistical tools to identify alternative splicing events significantly related with disease associated biomarkers or therapeutic targets using RNA sequencing (RNA-seq).

Venture attracts EUR 2 million grant for ‘new frontier’ of data interpretation for drug development

Granada and Madrid, Spain and Madison, WI, U.S., April 18, 2013 – Integromics®, a market leader in IT solutions for life sciences in the field of genomics and proteomics, today announces that it has entered into a partnership with the Celgene Institute for Translational Research Europe (CITRE) and the Centre of Studies and Technical Research (CEIT), for the execution of SANSCRIPT, a project that aims at the development of new data analysis methods applied in clinical genomics studies.

Based on the strength of its R&D work, the new partnership has been awarded a EUR two million grant from the Spanish Government for the development of algorithms and statistical tools to identify alternative splicing events significantly related with disease associated biomarkers or therapeutic targets using RNA sequencing (RNA-seq). Read more

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from figshare – by Eduardo Eyras, Gael P. Alamancos & Eneritz Agirre

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Many RNA sequencing studies set out to predict mutations, splice junctions or fusion RNAs. Now a team of researchers in France has developed a method, CRAC, that integrates genomic locations and local coverage to enable such predictions to be made directly from RNA-Seq read analysis. A k-mer profiling approach detects candidate mutations, indels and splice or chimeric junctions in each single read. CRAC increases precision compared with existing tools, reaching 99:5% for splice junctions, without losing sensitivity. Importantly, CRAC predictions improve with read length. In cancer libraries, CRAC recovered 74% of validated fusion RNAs and predicted novel recurrent chimeric junctions.

Availability – CRAC is available at http://crac.gforge.inria.fr.

• Philippe N, Salson M, Commes T, Rivals E. (2013) CRAC: an integrated approach to the analysis of RNA-seq reads. Genome Biology 14, R30. [abstract]

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• identifying splice variants tool rnaseq

Supervisors

Dr Qiongyi Zhao qiongyi.zhao@uq.edu.au

Dr Kostya Shakhbazov k.shakhbazov@uq.edu.au

A/Prof Naomi Wray naomi.wray@uq.edu.au

Project Description

Alternative splicing (AS) is a regulated process during gene expression that results in a single gene locus transcribing to multiple isoforms. It is well known that alternative splicing occurs as a normal phenomenon in eukaryotes, and alternative pre-mRNA splicing affects the majority of human genes and plays important roles in development and disease. However, the methodology for accurate identification of AS events based on high throughput sequencing data is not yet well developed. Current publically available tools/packages like “DEXSeq” and “cufflinks” only focus on differential usage of exons in known isoforms or just provide partial results for AS events. Thus, it is essential to develop new analytical methods or tools to accurately identify AS events and facilitate the RNA-Seq community to study AS events.

The PhD project will involve developing a user-friendly tool to identify AS events based on RNA-Seq data sets and analysing AS events in human transcriptome sequencing data. Analyses may focus on AS events in disease vs control (for example Motor Neurone Disease or Schizophrenia) or in male vs. female. Development of a user-friendly tool is essential and important for the RNA-Seq community.

The PhD student will be based within the QBI bioinformatics core that supports all sequencing projects undertaken on the in-house Illumina HiSeq. The student will be exposed to a range of ongoing projects and will learn skills in computational approaches/pipelines to integrate and analyze large-scale NGS data sets including genomics, expression, transcriptomics, epigenomics and proteomics data sets for scientific discovery and validation. A small sequencing project designed by the student could also be part of the project.

Read more at : http://www.complextraitgenomics.com/phd_positions/

 

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Alternative splicing is central for cellular processes and substantially increases transcriptome and proteome diversity. Aberrant splicing events often have pathological consequences and are associated with various diseases and cancer types. The emergence of next generation RNA sequencing (RNA-seq) provides an exciting new technology to analyse alternative splicing on a large scale. However, algorithms that enable the analysis of alternative splicing from short-read sequencing are not fully established yet and there are still no standard solutions available for a variety of data analysis tasks.

Now a team led by researchers at German Cancer Research Center (DKFZ) have developed a new method and software to predict genes that are differentially spliced between two different conditions using RNA-seq data. Their method employs geometric angles between the high dimensional vectors of exon read counts. With this, differential splicing can be detected even if the splicing events comprise of higher complexity and involve previously unknown splicing patterns. They applied the approach to two case studies including neuroblastoma tumour data with favourable and unfavourable clinical courses. They show the validity of our predictions as well as the applicability of our method in the context of patient clustering.

AVAILABILITY: SplicingCompass is licensed under the GNU GPL and freely available as a package in the statistical language R at http://www.ichip.de/software/SplicingCompass.html

CONTACT: m.aschoff@dkfz.de; r.koenig@dkfz.de.

• Aschoff M, Hotz-Wagenblatt A, Glatting KH, Fischer M, Eils R, König R. SplicingCompass: differential splicing detection using RNA-Seq data. Bioinformatics.  [Epub ahead of print]. [abstract]

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The biogenesis, development and metastases of cancer are associated with many variations in the transcriptome. Alternative splicing of genes is a major post-transcriptional regulation mechanism that is involved in many types of cancer. The next-generation sequencing applied on RNAs (RNA-Seq) provides a new technology for studying transcriptomes. It provides an unprecedented opportunity for quantitatively studying alternative splicing in a systematic way. This mini-review summarizes the current RNA-Seq studies on cancer transcriptomes especially studies on cancer-related alternative splicing, and discusses the strategy for quantitative study of alternative splicing in cancers with RNA-Seq, the bioinformatics methods available and existing questions.

•  Feng H, Qin Z, Zhang X. (2012) Opportunities and Methods for Studying Alternative Splicing in Cancer with RNA-Seq. Cancer Lett [Epub ahead of print]. [abstract]

Incoming search terms:

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Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, Ψ) metric estimates the incidence of single-exon skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the vast majority of human splicing events are more complex than single-exon skipping.

A team led by scientists at the Centre de Regulació Genòmica, Spain has now developed a framework that generalizes the Ψ metric to arbitrary classes of splicing events. They change the view from exon-centric to intron-centric and split the value of Ψ into two indices, ψ(5) and ψ(3), measuring the rate of splicing at the 5′- and 3′-end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index (COSI) is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data since no such standard procedure currently exists.

AVAILABILITY: The C(++) code of bam2ssj is open-source and is available at https://github.com/pervouchine/bam2ssj CONTACT: dp@crg.eu.

Pervouchine DD, Knowles DG, Guigó R. (2012) Intron-Centric Estimation of Alternative Splicing from RNA-seq data. Bioinformatics [Epub ahead of print]. [article]

Incoming search terms:

• ASprofile
• Opportunities and Methods for Studying Alternative Splicing in Cancer with RNA-Seq
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ASprofile consists of several programs for extracting (extract-as), quantifying (extract-as-fpkm) and comparing (collect-fpkm) AS events from transcripts assembled from RNA-seq data in multiple conditions, e.g. tissues.

The first program, extract-as, takes as input a GTF transcript file, such as that created by Cufflinks, and compares all pairs of transcripts within a gene to determine exon-intron structure differences that indicate an AS event. To determine AS events among multiple samples, the input file should be the concatenation of the transcript files of individual samples, with the gene names reconciled across the samples to allow comparison. The same event may be discovered and reported multiple times, from different transcripts. For this reason, we recommend that you run the script summarize_as to create a non-redundant listing (catalog) of all events. This format is also required for the rest of the programs in the ASprofile suite.

Download ASprofile here. The catalog of exon skipping events, and other types of events inferred from the Illumina Human Body Map data are here.

(more info…)

Incoming search terms:

• quantify splicing events from sequencing
• asprofile is a suite of programs for extracting quantifying and comparing alternative splicing (as) events from rna-seq data
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Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. A team led by researchers at  Genentech has performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs.

Overall, the data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators, including KDM6A, ASH1L, SMARCA4 and ATAD2, are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified 106 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. RAC1b, an isoform of the RAC1 GTPase that includes one additional exon, was found to be preferentially up-regulated in lung cancer. The team further showed that its expression is significantly associated with sensitivity to a MAP2K (MEK) inhibitor PD-0325901.

Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer-specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers. The detailed characterizations of the lung cancer cell lines also provide genomic context to the vast amount of experimental data gathered for these lines over the decades, and represent highly valuable resources for cancer biology.

• Liu J et al. (2012) Genome and transcriptome sequencing of lung cancers reveal diverse mutational and splicing events. Genome Res [Epub ahead of print]. [article]

Incoming search terms:

• Genome and 8 transcriptome sequencing of lung cancers reveal diverse mutational and splicing 9 events
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FusionFinder is Perl-based software designed to automate the discovery of candidate gene fusion partners from single-end (SE) or paired-end (PE) RNA-Seq read data. FusionFinder was applied to data from a previously published analysis of the K562 chronic myeloid leukaemia (CML) cell line. FusionFinder successfully replicated the findings of this study and detected additional previously unreported fusion genes in their dataset, which were confirmed experimentally. These included two isoforms of a fusion involving the genes BRK1 and VHL, whose co-deletion has previously been associated with the prevalence and severity of renal-cell carcinoma.

FusionFinder is made freely available for non-commercial use and can be downloaded from the project website (http://bioinformatics.childhealthresearc​h.org.au/software/fusionfinder/).

• Francis RW, Thompson-Wicking K, Carter KW, Anderson D, Kees UR, Beesley AH. (2012) FusionFinder: A Software Tool to Identify Expressed Gene Fusion Candidates from RNA-Seq Data. PLoS One 7(6):e39987. [article]

Incoming search terms:

• how to find the fusion gene in rna-seq bam file
• gene fusion bam file
• RNA-seq Xenome
• rna sequencing to identify candidate gene

Bellerophontes is a new framework for the detection of fusion transcripts through short paired-end reads which integrates splicing-driven alignment and abundance estimation analysis, producing a more accurate set of reads supporting the junction discovery and taking into account also not annotated transcripts. Bellerophontes performs a selection of putative junctions on the basis of a match to an accurate gene fusion model. Bellerophontes runs on top of TopHat and Cufflinks tools (developed by Trapnell et al.). The analysis is based on the results of TopHat alignment and Cufflinks transcript isoform detection.

AVAILABILITY:  Bellerophontes JAVA/Perl/Bash software implementation is free and available at http://eda.polito.it/bellerophontes/

• Abate F, Acquaviva A, Paciello G, Ficarra E, Ferrarini A, Delledonne M, Soverini S, Martinelli G, Macii E. (2102) Bellerophontes: A RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model. Bioinformatics [Epub ahead of print]. [abstract]

Incoming search terms:

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• SEQanswers – RNA Sequencing

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• Biostar – RNA-Seq

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    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 […]
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