Next Generation Sequencing 2018

next generation sequencing an application in forensic sciences and next generation sequencing data analysis online course
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Published Date:08-07-2017
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Overview of Next Generation Sequencing (NGS) Technologies Vivien G. Dugan Office of Genomics and Advanced Technologies NIAID/NIH Timothy Stockwell J. Craig Venter Institute th August 26 , 2013 NIAID Genomic Sequencing Centers for Infectious Diseases Bioinformatics High Throughput Genomics Sample Processing Metagenomics Tools Sequencing Bioinformatics Method Develop Transcriptomics Data Analysis Pipelines Training Pipelines What is‘NextGen’ sequencing? • Different chemistry from Sanger • Sequences everything in a sample • Host, pathogen, cells, etc. • Sequences clonally amplified molecule • Sequencing occurs in parallel • Millions of sequences produced concurrently • Gigabytes of sequences What is‘NextGen’ sequencing? • Less time than Sanger • Large capacity • Multiplexing, variation detection, gene expression, metagenomics • Address various biological questions Sanger vs Next-generation sequencing 100 of these…. = 1 of these…. GS-FLX Roche/454 ABI 3730x “Single Molecule Sequencing” Add adapters Shear DNA Select for fragments with Sequence A & B adapters & Assemble Attach to solid Data surface complementary to adapters Mapping sequence reads to reference Why use NextGen?  High rates of accuracy  Many reads per sequencing run  Faster time per sequencing run  Multiplexing capabilities  Decreased cost  Useful for many different applications Why use NextGen?  2004: 100 influenza genomes in NCBI  2013: 14,000+ influenza genomes in NCBI Genomics Analysis at the Population Level Diversity Molecular Epidemiology Deep sequencing R CLADE 2 Consensus sequencing Elodie Ghedin Center for Vaccine Research CLADE 7 Dept. Computational & Systems Biology NGS: Things to Consider  Each platform has advantages & disadvantages – Read length, accuracy, reads per run, time, sequencing error rates  Biology of the pathogen of interest  What is your goal in sequencing? – Complete genome – Specific region or gene True Diversity or Error? RNA polymerase Error: 0.001% 454 substitution Error: 0.03% Consensus of Clusters to Smooth out errors NGS: Things to Consider  Sample preparation is important – Sequencing everything in the sample Mammalian Virus Reads RNA Reads 0% Mammalian 3% Other Reads mtDNA Reads 12% 2% Mycoplasma Reads 83% Summary  Next Generation sequencing provides increasingly vital information not previously available  NGS technologies becoming more commonly used in the field of infectious disease research  Sequencing technologies, assembly and analyses tools rapidly improving NGS Criteria to Consider  Ultimate goal  Sequencing platform(s) – Coverage level/depth – Read length – Error rates  Sample preparation  Confirmatory sequencing Overview of Next Generation Sequencing (NGS) Technologies Timothy Stockwell (JCVI) Vivien Dugan (NIAID/NIH) Outline • Some history of DNA sequencing • Overview of NextGen Sequencing Technologies at JCVI • Roche/454 Pyrosequencing • LifeTechnologies/IonTorrent Semiconductor Sequencing • Illumina/Solexa Sequencing By Synthesis (SBS) • Other technologies Review - Sanger Sequencing • Randomly shear DNA, put it in a vector, and amplify with E. coli, or PCR amplify a region of a genome • The Sanger sequencing reaction is like PCR, except there is only one primer, and in addition to regular nucleotides, there are also a small amount of dye labelled dideoxy nucleotides, with a distinct dye for each base • As polymerase makes new ssDNA fragments, when a dye labelled dideoxy nucleotide is added, extension stops, and the fragment is labelled with a dye corresponding to the last base added. Review - Sanger Sequencing • Over many cycles, fragments of all the different lengths are formed, with each length fragment ending with the dye corresponding to the base at that position • Capillary electrophoresis in polyacrylamide gel is used to separate the fragments by length and pass them by a laser and reader to interrogate the base at each position • The result is a chromatogram, that is then “base called” using algorithms to output the most likely base at each position, usually with an indication of accuracy of the base call. A chromatogram