Goal: Learn some of the latest research in genomics Learn/practice basic programming and data mining skills

Transcription

1 Course outline Goal: Learn some of the latest research in genomics Learn/practice basic programming and data mining skills Structure: Lectures (4) Paper discussion (6) Workshops (5) Grading: Problem sets (2) 20 points Class participation (paper discussion) 35 points Paper reviews (2) 30 points Data analysis (1) 15 points

2 Introduction to genomics and genome sequencing: Approaches and Platforms Bio472- Spring 2016 Amanda Larracuente

3 Outline 1. History 2. Basic assembly approaches 3. First generation technology 4. Second generation technology 5. Third generation technology 6. Challenges

4 1. History History of genomics Darwin: The Origin of Species 1859

5 1. History History of genomics Mendel: laws of inheritance 1865 Avery: DNA as inherited material 1944 Watson, Crick & Franklin: DNA structure 1953

6 1. History History of genomics Arthur Kornberg: DNA polymerase 1956 Nirenberg: genetic code 1961 Gilbert and Sanger: sequencing 1977

7 Genomics 1. History

8 1. History Sanger sequenced genomes Bacteriophage lambda H. influenzae Yeast C. elegans Drosophila melanogaster Arabidopsis Human Comparative genomics!

9 Human Genome Project Discussed Projected to finish in 2005 Completed ahead of schedule in 2000 Published in 2001

10 1. History Progress in genome sequencing NHGRI at genome.gov

11 2. Basic Assembly Approaches Sequence reads Reads Sequence output from a DNA fragment Base qualities Paired-end reads Paired-end reads DNA fragment Reads from both ends of a DNA fragment Similar to or same as mate pairs (depending on platform)

12 2. Basic Assembly Approaches Genome assemblies 10 9 short sequencing reads 3Gb whole genome Human male karyotype

13 2. Basic Assembly Approaches Whole Genome Shotgun (WGS) approach Overlapping reads 1. Shear genome into 3-5kb fragments, clone into plasmids and sequence 2. Find overlapping reads contig 3. Assemble overlapping reads into contigs Mate pairs ( ( 4. Assemble contigs into scaffolds GATCGTGTCCCATTGTCAGATCGTG Finished assembly scaffold Chromosomes 5. Link scaffolds into finished sequence corresponding to chromosomes

14 2. Basic Assembly Approaches Hierarchical Approach BACs kb inserts 1. Shear genome into 150kb fragments and put in BACs 2. Create map of BACs to genome and create a tiling path Tiling path 3. Shotgun sequence individual BACs from tiling path Mate pairs 4. Assemble BAC sequences ( ( scaffold 5. Use sequenced tiling path to reconstruct genome GATCGTGTCCCATTGTCAGATCGTG Finished assembly Chromosomes

15 2. Basic Assembly Approaches Comparing assembly approaches Whole Genome Shotgun Faster Assembly is a huge computational effort Celera Genomics approach to human genome Hierarchical Slower Labor-intensive Higher quality assembly in difficult-to-assemble regions Publicly funded Human Genome Project Took >10 years and cost $3 billion

16 3. First generation technology First generation sequencing technology Shear genomic DNA Subclone into vectors Bacterial replication Isolate amplified clones Capillary sequencing

17 3. First generation technology Sanger sequencing primer% Chain termination Fluorescently labeled, modified nucleotides Capillary gel electrophoresis Fragment%size% Template%DNA% Capillary%Gel% DNA% polymerase% TCTAGAGCCTGCAATACGATC% TCTAGAGCCTGCAATACGAT% TCTAGAGCCTGCAATACGA% TCTAGAGCCTGCAATACG% TCTAGAGCCTGCAATAC% TCTAGAGCCTGCAATA% TCTAGAGCCTGCAAT% TCTAGAGCCTGCAA% TCTAGAGCCTGCA% TCTAGAGCCTGC% TCTAGAGCCTG% TCTAGAGCCT% TCTAGAGCC% TCTAGAGC% TCTAGAG% TCTAGA% TCTAG% TCTA% TCT% TC% T% TCTAGAGCCTGCAATACGATC% +" Sequence%

18 3. First generation technology Applications Sequencing PCR fragments Sequencing off plasmids Sequencing genomes Sequencing cdna libraries

19 4. Second generation technology Second generation sequencing technology Shear genomic DNA Solid support fixation Amplification Wash and Scan Base detection

20 4. Second generation technology 454 pyrosequencing a. Isolate gdna, fragment and ligate adapters b. Bind to beads and carry out emulsion PCR (empcr 1 fragment/bead) c. Break emulsion and add beads to fiber-optic slide d. Pyrosequencing reaction, 1 nt added at a time (peak height corresponds to # of nucl) a b c d Rothberg and Leamon 2008

21 4. Second generation technology Illumina Fragment gdna Ligate adapters Fix fragments on solid surface Bridge amplification to generate clusters Sequence one end (using reversible terminators) If paired-end, regenerate cluster and sequence the other end Figure from Mardis 2013

22 *more like 2.5-generation technology 4. Second generation technology Ion Torrent 1. Shear DNA, ligate adapters 2. Attach fragments to beads and amplify with empcr 4. Flow nucleotides over wells, one at a time 5. DNA polymerase incorporates bases and give off H+ 3. Place bead in wells on plate 6. Mini semi-conductor reads ph change

23 4. Second generation technology Applications Genome re-sequencing (reference based assembly) Genome sequencing (de novo assembly) Sequencing transcriptome (RNAseq) Sequencing DNA associated with proteins (CHiPseq)

24 5. Third generation technology Third generation sequencing technology Shear genomic DNA No amplification solid support fixation Base detection Single-molecule sequencing

25 5. Third generation technology Single molecule sequencing e.g. Pacific Biosciences (PacBio) Single-molecule real-time (SMRT) sequencing Real time fluorescent nucleotides Average reads >15 kb; some reads >50 kb High (~15%) error rate Eid et al. 2009

26 5. Third generation technology Applications Low-depth: Scaffolding contigs (de novo assembly) High-depth: Genome sequencing of repetitive regions or structural rearrangements

27 De novo assembly of self-corrected reads Raw reads Errorcorrected reads (~25X) Assembled Contig Overlap-layout-consensus (e.g. Celera assembler) Chin et al. 2013; Huddleston et al. 2014; Berlin et al. 2014

28 6. Challenges Comparison of NGS technologies (non-exhaustive) Method strategy Read length Error type Error rate Output per run 454 Synthesis/ pyrosequencing Up to 700bp indels 1% Mbp SOLID DNA ligase 75bp AT bias > % Gbp Illumina (HiSeq) Synthesis/DNA poly 150bp Subs. >0.1% 600 Gbp Ion Torrent H+ detection 90bp indels 1.5% 1 Gbp PacBio Single molecule/ synthesis >15kb (up to 50kb) insertions 15% Mbp (5-10 Mbp usable)

29 6. Challenges The $1000 genome Illumina! Reported January : The HiSeq X Ten, composed of 10 HiSeq X Systems, is the first sequencing platform that breaks the $1000 barrier for a 30x human genome. The HiSeq X Ten System is ideal for population-scale projects focused on the discovery of genotypic variation to understand and improve human health

30 6. Challenges Summary of technology Point: Sequencing is cheap Individual labs Current challenge Computational Data management NHGRI at genome.gov

31 6. Challenges Repetitive DNA Interspersed repeats? e.g. transposable elements Tandem repeats? e.g. satellites, CNVs

32 6. Challenges Challenges for repetitive DNA Repeat unit longer than read length (e.g. Transposable elements) Repeat unit longer than insert sizes (e.g. Transposable elements)

33 6. Challenges Challenges for repetitive DNA True Genomic sequence CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC

34 6. Challenges Challenges for repetitive DNA True Genomic sequence CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC Single end libraries Assembly CCTGCGATAATATGGAATATGGTGTACCC CCTGCGATAATATG CCTGCGATAATATG CGATAATATGGAA TAATATGGAATA AATATGGAATATGG AATATGGAATATGG AATATGGAATATGG AATATGGAATATGG AATATGGAATATGG AATATGGAATATGG AATATGGAATATGG GAATATGGTGTA AATATGGTGTACCC AATATGGTGTACCC

35 6. Challenges Challenges for repetitive DNA True Genomic sequence CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC Paired end libraries Assembly CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC CCTGCGATAATATG GGAATATGGA GCGATAATATGGAA ATATGGA TAATATGGAATATG GGAATATGG ATGGAATATGGAA AATATGGAATAT AATATGGAATA TATGGAATATG AATATGGAA AATATGGTGTA AATATGGAATAT TGGTGTACCC

36 6. Challenges Challenges for repetitive DNA True Genomic sequence CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC Paired end + Mate pair libraries Assembly CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC CCTGCGATAATATG GGAATATGGA GCGATAATATGGAA ATATGGA TAATATGGAATATG GGAATATGG AATATGGAATA TATGGAATATG GCGATAATATG GGAATATGGAATA AATATGGAA ATATGGAATATGG TATGGAATAT ATGGAATATG AATATGGAA AATATGGTGTA AATATGGAATAT TGGTGTACCC

37 6. Challenges Repeats cause Misassemblies Complex rearrangements Gaps

38 6. Challenges Next gen applications and repeats WGS with Sanger Repetitive DNA unstable in cloning vectors Paired end/mate pairs help with assembly 454 pyrosequencing Problems with homopolymers Paired end/mate pairs help with assembly Illumina Repetitive elements longer than read length Deep coverage and mate pairs help with assembly PacBio Problem is very high error rate: requires deep coverage PacBio or short reads Read length plows through repeats

39 Further reading: Metzker Sequencing technologies the next generation. Nature Reviews. 11: Mardis Next-Generation Sequencing Platforms. Ann. Rev. Anal. Chem 6: Treangen and Salzberg Repetitive DNA and nextgeneration sequencing: computational challenges and solutions. Nature Reviews Genetics 13:36-46.

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41 Getting on BlueHive Course scratch space: /scratch/bio472_2016 In terminal: ssh bluehive.circ.rochester.edu l username

42 Running graphical software on BlueHive Please go to: Getting_Started And Install X11 application if needed