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Rnaseq forgenefinding

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  • Cap analysis of gene expression, Massively parallel signature sequencing , Serial analysis of gene expression
  • An overview of the MapSplice pipeline. The algorithm contains two phases: tag alignment (Step 1–Step 4) and splice inference (Step 5–Step 6). In the ‘tag alignment' phase, candidate alignments of the mRNA tags to the reference genome are determined. In the ‘splice inference' phase, splice junctions that appear in one or more tag alignments are analyzed to determine a splice significance score based on the quality and diversity of alignments that include the splice. Ambiguous candidate alignments are resolved by selecting the alignment with the overall highest quality match and highest confidence splice junctions.
  • Transcript

    • 1. Transcript discovery and gene model correction using next generation sequencing data
      SuchetaTripathy, VBI, 11th Nov 2010
    • 2. Brief History of Sequencing
      Sanger Dideoxy Sequencing methods(1977).
      Maxam Gilberts Chemical degradation methods(1977).
      Two Labs that owned automated sequencers:
      1. Leroy Hood at Caltech, 1986(commercialized by AB)
      2. Wilhelm Ansorge at EMBL, 1986(commercialized by Pharmacia-Amersham and GE healthcare)
    • 3. Brief History Of sequencing
      Hypoxanthine-guanine phosphoribosyltransferase (HGPRT)
      Alu sequences
    • 4. Hitachi Laboratory developed High throughput capillary array sequencer, 1996.
      1991, A patent filed by EMBL on media less, solid support based sequencing.
      Brief History Of sequencing
    • 5. NextGen Sequencing Methods
      454 sequencing methods(2006)
      Principles of pyrophosphate detection(1985, 1988)
      Illumina(Solexa) Genome sequencing methods(2007)
      Applied Biosystems ABI SOLiD System(2007)
      Helicos single molecule sequencing(Helioscope, 2007)
      Pacific Biosciences single-molecule real-time(SMRT) technology, 2010
      Sequenom for Nanotechnology based sequencing.
      BioNanomatrixnanofluidiscs.
      RNAP technology.
    • 6. Figure 1. (A) Outline of the GS 454 DNA sequencer workflow. Library construction (I) ligates 454-specific adapters to DNA fragments (indicated as A and B) and couples amplification beads with DNA in an emulsion PCR to amplify fragments before sequencing (II). The beads are loaded into the picotiter plate (III). (B) Schematic illustration of the pyrosequencing reaction which occurs on nucleotide incorporation to report sequencing-by-synthesis. (Adapted from http://www.454.com.)
    • 7. Outline of the Illumina Genome Analyzer workflow. Similar fragmentation and adapter ligation steps take place (I), before applying the library onto the solid surface of a flow cell. Attached DNA fragments form ‘bridge’ molecules which are subsequently amplified via an isothermal amplification process, leading to a cluster of identical fragments that are subsequently denatured for sequencing primer annealing (II). Amplified DNA fragments are subjected to sequencing-by-synthesis using 3′ blocked labelled nucleotides (III). (Adapted from the Genome Analyzer brochure, http://www.solexa.com.)
    • 8. (A) Primers hybridise to the P1 adapter within the library template. A set of four fluorescence-labelleddi-base probes competes for ligation to the sequencing primer. These probes have partly degenerated DNA sequence (indicated by n and z). Specificity of the di-base probe is achieved by interrogating the first and second base in each ligation reaction (CA in this case for the complementary strand). (B) Sequence determination by the SOLiD DNA sequencing platform is performed in multiple ligation cycles, using different primers, each one shorter from the previous one by a single base. The number of ligation cycles determines the eventual read length, whilst for each sequence tag, six rounds of primer reset occur [from primer (n) to primer (n − 4)]. (Adapted and modified from http://www.appliedbiosystems.com.)
    • 9. Cost
      Adapted from Eric Lander, 2010
    • 10. Throughput
      Standard ABI “Sanger” sequencing
      96 samples/day
      Read length ~650 bp
      Total = 450,000 bases of sequence data
      454 was the game changer!
      ~400,000 different templates (reads)/day
      Read length ~250 bp
      Total = 100,000,000 bases of sequence data!!!
    • 11. Throughput
      454 Life Sciences/Roche
      Genome Sequencer FLX: currently produces 400-600 million bases per day per machine
      Published 1 million bases of Neanderthal DNA in 2006
      May 2007 published complete genome of James Watson (3.2 billion bases ~20x coverage)
      Solexa/Illumina
      10 GB per machine/week
      May 2008 published complete genomes for 3 hapmap subjects (14x coverage)
      ABI SOLID
      20 GB per machine/week
    • 12. RNASeq
      Catalogue all species of transcripts.
      mRNA
      Non-coding RNA
      Small RNA
      Splicing patterns or other post-transcriptional modifications.
      Quantify the expression levels.
    • 13. Zhong Wang et al; Nat. Rev. Genetics, 2009
    • 14. Other Applications
      SNP detection
      Splice Variant Discovery
      Identification of miRNA targets
      TF binding sites
      Genome Methylation pattern
      RNA editing
      Metagenomic projects
      Gene Expression Analysis
    • 15. Difference with other expression sequencing
      EST: Low throughput, expansive, NOT quantitative.
      SAGA, CAGE, MPSS: Highthroughput, digital gene expression levels
      Expansive
      Sanger sequencing methods
      A portion of transcript is analyzed
      Isoforms are indistinguishable
    • 16. Advantages:
      Zero or very less background noise.
      Sensitive to isoform discovery.
      Both low and highly expressed genes can be quantified.
      Highly reproducible.
    • 17. Data Analysis
      Mapping Reads to the reference assembly
      Filtering output:
      Reads mapping > x number of times
      Downstream data analysis
    • 18. Mapping
      One or two mis-matches < 35 bases
      One insertion/deletion.
      K-mer based seeding.
      • Identification of Novel Transcripts.
      • 19. Transcript abundance.
    • Available tools for Nextgen sequence alignment
      BFAST: Blat like Fast Alignment Tool.
      Bowtie: Burrows-Wheeler-Transformed (BWT) index.
      BWA:Gapped global alignment wrt query sequences.
      ELAND: Is part of Illumina distr. And runs on single processor, Local Alignment.
      SOAP: Short Oligonucleotide Alignment Program.
      SSAHA: SSAHA (Sequence Search and Alignment by Hashing Algorithm)
      SOCS: Rabin-Karp string search algorithm, which uses hashing
      Vmatch: A Large string matching toolbox.
      .
    • 20. Integrated Pipeline
      • SOLiD™ System Analysis Pipeline Tool (Corona Lite)
      • 21. CLCBio Genomic workbench.
      • 22. Galaxy Server.
      • 23. ERANGE:Is a full package for RNASeq and chipSeq data analysis
      • 24. DESEQ(used by edgeR package)
    • Trapnell et. al 2009
    • 25.
    • 26. An overview of the MapSplice pipeline.
      © The Author(s) 2010. Published by Oxford University Press.
      Wang K et al. Nucl. Acids Res. 2010;38:e178-e178
    • 27. Larsen et al 2010
    • 28. Denoeud et al, 2008
    • 29. Transcripts discovered/Corrected
      10,000 new Transcription start site discovered in Rhesus macaque(Liu et al., NAR 2010)
      602 transcriptionally active regions and numerous introns in Candida albicans(Bruno et al., 2010, Genome Research)
      96% of the genes were corrected in Laccaria bicolor(Larsen et al., PLoS One 2010).
      16,923 regions in mouse (Martazavi et al., 2008).
      3,724 novel isoforms (Trapanell2010).
    • 30. Bioinformatics Challenges
      Store , retrieve and analyze large amounts of data
      Matching of reads to multiple locations
      Short reads with higher copy number and long reads representing less expressed genes.
    • 31. References:
      Wilhelm J. Ansorge, Next-generation DNA sequencing techniques, New Biotechnology, Volume 25, Issue 4, April 2009, Pages 195-203
      Zhong Wang, Mark Gerstein, and Michael Snyder. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009 January; 10(1): 57–63.
      Peter E. Larsen et al., Using Deep RNA Sequencing for the Structural Annotation of the Laccaria Bicolor MycorrhizalTranscriptomePLoS One. 2010; 5(7): e9780
      Wang et al. MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery, NAR, 2010
      Denoeud et al., Annotating genomes with massive-scale RNA sequencing, Genome Biology, 2008
      Trapnell C, Williams BA, Pertea G, Mortazavi AM, Kwan G, van Baren MJ, Salzberg SL, Wold B, Pachter L.Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Nature Biotechnology doi:10.1038/nbt.1621
      Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics doi:10.1093/bioinformatics/btp120
      Mortazavi et al. Nature Methods, May 2008

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