Metodologie di sequenziamemento

Transcription

1 Metodologie di sequenziamemento di DNA ed RNA Metzker et al Sequencing technologies the next generation. Nature Reviews Genetics, vol. 11, p. 31 Stranneheim and Lundeberg Stepping stones in DNA sequencing. Biotechnol. J., vol. 7, p Head et al Library construction for next-generation sequencing: Overviews and challenges. BioTechniques 56:61-77 Jenny Wu;Introduction To Next Generation Sequencing (NGS) Data Analysis; online pptx presentation

2 Stranneheim and Lundeberg 2012

3 Un po di storia 25 Aprile 1953 James D. Watson e Francis Crick pubblicano la struttura del DNA (Watson JD, Crick FHC "A Structure for Deoxyribose Nucleic Acid", Nature vol. 171, pp ; 1953) fondando il campo della genetica molecolare. Premio Nobel nel Metà degli anni 50: Arthur Kornberg inizia a studiare il meccanismo di replicazione del DNA. Nel 1957 identifica la prima DNA polimerasi. L enzima copia in una sola direzione e richiede degli inneschi preesistenti (primer) per iniziare a copiare il filamento. Premio Nobel nel All inizio degli anni 60 Gobind Khorana chiarisce molti aspetti del codice genetico. Successivamente inizia un progetto per la sintesi in vitro di un gene umano e in questi esperimenti getta le basi per l utilizzo di oligonucleotidi sintetici (usati sia come blocchi per la costruzione del gene, sia come inneschi per la DNA polimerasi) Premio Nobel per il suo lavoro sul codice genetico Thomas D. Brock isola un nuovo batterio dalle sorgenti calde dello Yellowstone National Park. Nel 1976 viene islata la DNA polimerasi di T. aquaticus (taq) in grado di mantenere la sua attività oltre i 75 C Frederick Sanger sviluppa un metodo per determinare la sequenza del DNA. (Sanger F, Nicklen S, Coulson AR "DNA sequencing with chain-terminating inhibitors" Proc Natl Acad Sci vol. 74(12) pp ; 1977). 1980: Premio Nobel. Nel 1980 tutti I componenti per fare un ampplificazione con PCR sono conosciuti dalla comunità scientifica

4 50-68 C

5 Elongation Strand Separation Primer Annealing Termination

6 Termination Standard Nucleotides Dye-labeled dideoxynucleotides ddntp incorporation leads to chain growth termination

7 Capillary Electrophoresis ABI 3730, 96-capillary Capillary Tube Laser Photo cell cromatogramma

8 NGS

9 Applications Espressione genica Caratterizzazione regioni di interazione DNA-proteine Epigenetica

10 Applications: genomes, exomes, transcriptomes

11 Applications: RNA seq (trascrittoma)

12 Applications:ChIP-Seq

13 Library preparation

14 library Frammentazione Legame adattatori Template preparation Serve a reggiungere una quantità di DNA stampo sufficiente per la lettura del sequenziamento sequencing Sequencing by synthesis Lettura del segnale

15 Preparazione del DNA o dell RNA in una forma utilizzabile dalla tecnologia di sequenziamento (lunghezza adeguata tipicamente poche centinaia di bp, dsdna, adattatori)

16 With the exception of Illumina s Nextera prep, library preparation generally entails: (i) Fragmentation, end-repair, phosphorylation of the 5 prime ends, A-tailing of the 3 ends to facilitate ligation to sequencing adapters (ii) ligation of adapters (iii) some number of PCR cycles to enrich for product that has adapters ligated to both ends The primary differences in an Ion Torrent workflow are the use of blunt-end ligation to different adapter sequences. (iv) To facilitate multiplexing, different barcoded adapters (index) can be used with each sample. Es. Illumina adaptors P5/ P7: binding sites to the flow cell Rd 1 SP: read1 sequencing primer Rd 2 SP: read2 sequencing primer

17 NGS Up to 250

18 Up to 250

19 Up to 250

20 MiSeq Sequencing Technology - one-lane flow cell Mill. reads - 150b/read => 4,6 Gb = 4600 Mb Genome sizes: human XX: 3194 Mbp E.coli: 4,7 Mbp HIV: 8000bp Amoeba proteos Mbp - library prep RNA: 320 DNA: sequencing MiSeq Run: 1020

21 Prima massive parallel sequencing technologies: 2003 Quasi in disuso a causa degli elevati costi di gestione, l emulsion PCR è stata ereditata da Ion Torrent (Life Technologies)

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23 Ma che cosa abbiamo realmente sequenziato? Single end seq Paired end seq

24 M: milioni Gb: gigabasi:

25 Read: singola sequenza di basi, prodotto del sequenziamento Coverage: numero di volte in cui una base viene letta in una corsa di sequenziamento

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27 Il numero di basi lette per read dipende dalla tecnologia e dalla chimica usate La lunghezza di questo inserto che non verrà sequenziato è molto importante per mappare le due estremità sulla sequenza di riferimento

28 Why Bioinformatics Informatics (wall.hms.harvard.edu)

29 Bioinformatics Challenges in NGS Data Analysis VERY large text files (thousands of millions of lines long) Can t do business as usual with familiar tools Impossible memory usage and execution time Manage, analyze, store, transfer and archive huge files Need for powerful computers and expertise Informatics groups must manage compute clusters New algorithms and software are required and often time they are open source Unix/Linux based. Collaboration of IT, bioinformaticians and biologists Jenny Wu

30 Terminology Coverage (depth): The number of nucleotides from reads that are mapped to a given position. Quality Score: Each called base comes with a quality score which measures the probability of base call error. Paired-End Sequencing: Both end of the DNA fragment is sequenced, allowing highly precise alignment. Multiplex Sequencing: "barcode" sequences are added to each sample so they can be distinguished in order to sequence large number of samples on one lane. Mapping: Align reads to reference to identify their origin. Assembly: Merging of fragments of DNA in order to reconstruct the original sequence. Duplicate reads: Reads that are identical. Multi-reads: Reads that can be mapped to multiple locations equally well. Jenny Wu

31 File Formats Reference sequences, reads: FASTQ FASTA Alignments: SAM BAM Features, annotation, scores: GFF/GTF BED/BigBed WIG/BigWig Jenny Wu

32 General Data Pipeline Jenny Wu

33 FASTA Format (Reference Seq) Jenny Wu

34 FASTQ Format (reads) Jenny Wu

35 FASTQ Format (Illumina Example) Read Record Header Flow Cell ID Lane Tile Tile Coordinates Barcode Separator (with optional repeated header) tile 1:N:0:AGTCAA CAGGAGTCTTCGTACTGCTTCTCGGCCTCAGCCTGATCAGTCACACCGTT + BCCFFFDFHHHHHIJJIJJJJJJJIJJJJJJJJJJIJJJJJJJJJIJJJJ Read 1:N:0:AG AAAACTCTTACTACATCAGTATGGCTTTTAAAACCTCTGTTTGGAGCCAG + Read 1:N:0:AG CCTCCTGCTTAAAACCCAAAAGGTCAGAAGGATCGTGAGGCCCCGCTTTC + 1:N:0:AG GAAGATTTATAGGTAGAGGCGACAAACCTACCGAGCCTGGTGATAGCTGG + CCCFFFFFHHHHHGGIJJJIJJJJJJIJJIJJJJJGIJJJHIIJJJIJJJ NOTE: for paired-end runs, there is a second file with one-to-one corresponding headers and reads. (Passarelli, 2012)

36 Data Analysis Pipeline Sequence quality control (QC) and preprocessing Obtaining and preparing reference Sequence mapping Downstream analysis workflow and software

37 The UCSC Genome Browser Homepage General information Get genome annotation here! Get reference sequences here! Specific information new features, current status, etc. Jenny Wu

38 Getting reference sequences Jenny Wu

39 Getting Reference Annotation Jenny Wu

40 Sequence Mapping Challenges Alignment (Mapping) is the first steps once analysis-read reads are obtained. The task: to align sequencing reads against a known reference. Difficulties: high volume of data, size of reference genome, computation time, read length constraints, ambiguity caused by repeats and sequencing errors. Jenny Wu

41 Short Read Alignment Olson et al. Jenny Wu

42 Short Read Alignment Software Jenny Wu

43 Short Reads Mapping Software Jenny Wu

44 How to choose an aligner? There are many aligners and they vary a lot in performance(accuracy, memory usage, speed and flexibility etc). Factors to consider : application, platform, read length, downstream analysis, etc. Constant trade off between speed and sensitivity (e.g. MAQ vs. Bowtie) Guaranteed high accuracy will take longer. Jenny Wu

45 NGS Applications and Analysis Strategy:downstream analysis Name Nucleic acid population Brief analysis strategy RNA-Seq RNA (may be poly-a mrna or total RNA) Alignment of reads to genes ; variations for detecting splice junctions and quantifying abundance Small RNA sequencing Small RNA (often mirna) Alignment of reads to small RNA references (e.g. mirbase), then to the genome; quantify abundance ChIP-Seq DNA bound to protein, captured via antibody (ChIP = Chromatin ImmunoPrecipitation) Align reads to reference genome, identify peaks & motifs RIP-Seq RNA bound to protein, captured via antibody (RIP = RNA ImmunoPrecipitation) Align reads to reference genome and/or genes, identify peaks and motifs Methylation Analysis SNP calling/ discovery Structural Variation Analysis de novo Sequencing Select methylated genomic DNA regions, or convert methylated nucleotides to alternate forms All or some genomic DNA or RNA Genomic DNA, with two reads (mate-pair reads) per DNA template Genomic DNA (possibly with external data e.g. cdna, genomes of closely related species, etc.) Align reads to reference and either identify peaks or regions of methylation Either align reads to reference and identify statistically significant SNPs, or compare multiple samples to each other to identify SNPs Align mate-pairs to reference sequence and interpret structural variants Piece-together reads to assemble contigs, scaffolds, and (ideally) whole-genome sequence Metagenomics Entire RNA or DNA from a (usually microbial) community Phylogenetic analysis of sequences (Hunicke-Smith et al, 2010)