Sequencing Theory. Brett E. Pickett, Ph.D. J. Craig Venter Institute

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1 Sequencing Theory Brett E. Pickett, Ph.D. J. Craig Venter Institute Applications of Genomics and Bioinformatics to Infectious Diseases GABRIEL Network

2 Agenda Sequencing Instruments Sanger Illumina Ion Torrent Oxford Nanopore PacBio

3 Virus (or Pathogen) Sequencing Application of NGS to study of Virus Evolution and Molecular Epidemiology Track the evolution of viruses over time Better understand the selective pressures that drive virus evolution Identify the origins (reservoir) of outbreak strains Investigate transmission dynamics Identify molecular determinants of host range Identification of evolutionarily conserved regions for targeted vaccines

4 Some Trivia What year was the first whole genome sequence reported? a) 1969 b) 1977 c) 1981 d) 1985 For which organism? Bacteriophage ΦX174 (5,375 bp) What method was used? dideoxy chain termination with 32 P (aka Sanger sequencing) What year was the first whole genome sequence for a free living organism reported? a) 1979 b) 1984 c) 1989 d) 1995 For which organism? Haemophilus influenza (1.8 x 10 6 bp) What method was used?

5 Some Trivia What year was the first whole genome sequence reported? a) 1969 b) 1977 c) 1981 d) 1985 For which organism? Bacteriophage ΦX174 (5,375 bp) What method was used? dideoxy chain termination with 32 P (aka Sanger sequencing) What year was the first whole genome sequence for a free living organism reported? a) 1979 b) 1984 c) 1989 d) 1995 For which organism? Haemophilus influenza (1.8 x 10 6 bp) What method was used? Sanger sequencing with fluorescence

6 JCVI Joint Technology Core ABI 3730xl Capacity: 240,000 sequences/day or 80 million lanes/year at 24 runs per day

7 New JCVI Joint Technology Core Illumina NextSeq/MiSeq 800 million reads/runs Oxford Nanopore MinION

8 Sanger vs NGS

9 Change in Cost 1st Generation Next Generation Next Generation w/broad adoption Wetterstrand KA. DNA Sequencing Costs: Data from the NHGRI Genome Sequencing Program (GSP) Available at: Accessed 23AUG2017.

10 Sanger

11 Sanger 1 => Sanger 2

12 A chromatogram

13 Illumina

14 Illumina Instruments

15 Illumina Sequencing (Optics-Based)

16 ION Torrent

17 ION Torrent Sequencing (H+ Based) High-throughput

18 PacBio

19 Single molecule detection Sequencing by synthesis Single base incorporation Sequences same molecule multiple times Random error detection Easy to generate consensus

20 Oxford Nanopore

21 Oxford Nanopore sequencing DNA pushed through a nanopore in a lipid membrane Speed control provided by a Phi29 DNA polymerase Measure changes in the ionic current of an applied electric field Combined w/ other platform to improve quality of assembly

22 Read Lengt 2e+05 Oxford 5 produces high quality reads >50 Read kb; GC Content longest 1e+05 >800 Read GC Content kb 1e+05 C Read Read Lengt D 2e+05 Read 5 0e+00 0e+00 E e Read Length Read GC Content 1e+05 Oxford F Read Length 2e+05 1e Read GC Content PacBio 0e+00 0e Read GC Content Read GC Content Read Length 2e+05 1e+05 0e+00 E Read Length 2e+05 1e+05 Read Length F Read Length 2e+05 1e+05 2e+05 1e+05 0e+00 0e Read Quality Score Read Quality Score 0e Read Quality Score Read Quality Score 4k 8k 12k 4k 8k 12k 20k 40k 60k 20k 40k 60k Read Count Read Count Read Count Read Count

23 Long Read Technology Comparison Advantages Full length transcriptomes, including splice variants Resolution of long repeat regions in genomes Genomic structural variants Haplotype phasing Disadvantages High error rates Higher cost Lower throughput

24 Instrument Comparison Platform Advantages Disadvantages HiSeq PE run (2x75) MiSeq PE run (2x300) Ion Torrent (200bp, 318 chip) high throughput, lowest per base cost high throughput, low per base cost, fast turnaround? fast turn-around short reads, long run time data quality, homopolymers Oxford Nanopore PacBio Sanger run (96 wells) Fast turn-around, various use cases, long reads, low-cost instrument base-calling various use cases, long reads, high quality data, long read length intense library prep, instrument cost high cost, low throughput

FastQ Format @HWUSI-EAS582_157:6:1:1:1501/1 NCACAGACACACACGAACACACAAAGACATGCCCATATGAAGAT + %.

25 FastQ NCACAGACACACACGAACACACAAAGACATGCCCATATGAAGAT + NCTGGCACCTTGATTTTGGACTTCCCAGCCTCCAGAACTGTGAG + % NCTGCTTGCACCCCTGAAGTCACTGATCACATTTCAGGGTCACC + NGATTGACATTGGCAAAGAGGACAACTGATTGCAAACTTCACAC + NAGGCTCAGGCGCACGGCCTACATCGTCGCTGTCGGCCAAGGGG + Read (sequence) Quality scores (phred-33)

Assessing Quality: Phred scores Phred quality scores were originally produced by the Phred base calling program using a statistical analysis of Sanger chromatogram trace files

26 Assessing Quality: Phred scores Phred quality scores were originally produced by the Phred base calling program using a statistical analysis of Sanger chromatogram trace files in support of the Human Genome Project. Subsequently adapted to NGS technologies for judging qualities of sequences. Q = -10 log 10 P e P e = error probability of a given base call

27 Acknowledgements JCVI Vinita Puri William Nierman, Ph.D. Karen Nelson, Ph.D. Alan Durbin Torrey Williams Kari A. Dilley, Ph.D. Lauren Oldfield, Ph.D. Susmita Shrivastava Nadia Fedorova Mark Novotny U19AI Paolo Amedeo, Ph.D. Reed S. Shabman, Ph.D. Gene Tan, Ph.D.

28 Questions?

Aaron Liston, Oregon State University Botany 2012 Intro to Next Generation Sequencing Workshop

Output (bp) Aaron Liston, Oregon State University Growth in Next-Gen Sequencing Capacity 3.5E+11 2002 2004 2006 2008 2010 3.0E+11 2.5E+11 2.0E+11 1.5E+11 1.0E+11 Adapted from Mardis, 2011, Nature 5.0E+10