Course outline - blogs.rochester.edublogs.rochester.edu/selfishDNA/wp-content/uploads/2014/01/Bio472... · • 1996- Yeast • 1998- C ... Whole Genome Shotgun (WGS) approach ( (

Course outline Goal: Learn basic programming and bioinformatic skills to complete a project using available NGS data Structure: Lectures (4) Journal club (4) Workshops (4) Grading: Problem sets (3) Class participation (journal club) Project report (oral and written)

Introduction to genome sequencing: Approaches and Platforms Bio472- Spring 2014 Amanda Larracuente

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

Progress in genome sequencing

NHGRI at genome.gov

1. History

History: Sanger sequencing •  Introduced in 1975 •  1982- Bacteriophage lambda •  1995- H. influenzae •  1996- Yeast •  1998- C. elegans •  2000- Drosophila melanogaster •  2000- Arabidopsis •  2001- Human

1. History

Sequence reads • Reads

•  Sequence output from a DNA fragment •  Base qualities

• Paired-end reads

•  Reads from both ends of a DNA fragment •  Similar to or same as mate pairs (depending on platform)

2. Basic Assembly Approaches

DNA fragment

Paired-end reads

Genome assemblies

Human male karyotype http://www.genome.gov

109 short sequencing reads 3Gb whole genome


Whole Genome Shotgun (WGS) approach

( (

Overlapping reads

contig

Mate pairs

scaffold

Chromosomes GATCGTGTCCCATTGTCAGATCGTG Finished assembly

1.  Shear genome into 3-5kb

fragments, clone into plasmids and sequence

2.  Find overlapping reads 3.  Assemble overlapping reads

into contigs

4.  Assemble contigs into scaffolds 5.  Link scaffolds into “finished”

sequence corresponding to chromosomes


Hierarchical Approach

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BACs

100-150 kb inserts

Mate pairs

scaffold

Chromosomes

1.  Shear genome into 150kb

fragments and put in BACs 2.  Create map of BACs to

genome and create a tiling path 3.  Shotgun sequence individual

BACs from tiling path

4.  Assemble BAC sequences 5.  Use sequenced tiling path to

reconstruct genome

GATCGTGTCCCATTGTCAGATCGTG Finished assembly

Tiling path


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

First generation sequencing technology

Shear genomic DNA

Subclone into vectors

Bacterial replication

Isolate amplified clones

Capillary sequencing

3. First generation technology

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(.2,-.%Sanger sequencing • Chain termination •  Fluorescently labeled,

modified nucleotides • Capillary gel

electrophoresis


Applications • Sequencing PCR fragments • Sequencing off plasmids

• Sequencing genomes

• Sequencing cDNA libraries


Second generation sequencing technology

Amplification

Base detection

Shear genomic DNA

Solid support fixation

4. Second generation technology

Wash and Scan

454 pyrosequencing

Rothberg and Leamon 2008

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


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


Ion Torrent 1. Shear DNA, ligate adapters

2. Attach fragments to beads and amplify with emPCR

3. Place bead in wells on plate

4. Flow nucleotides over wells, one at a time

5. DNA polymerase incorporates bases and give off H+

6. Mini semi-conductor reads pH change

http://www.lifetechnologies.com


*more like 2.5-generation technology

Applications • Genome re-sequencing (reference based assembly)

• Genome sequencing (de novo assembly)

• Sequencing transcriptome (RNAseq)

• Sequencing DNA associated with proteins (CHiPseq)


Third generation sequencing technology

No amplification

Base detection

solid support fixation

Shear genomic

DNA

5. Third generation technology

Single-molecule sequencing

Single molecule sequencing e.g. Pacific Biosciences (PacBio)

•  Single-molecule real-time (SMRT) sequencing •  Real time fluorescent nucleotides •  Some reads >10kb •  High error rate

Eid et al. 2009


Applications •  Low-depth: Scaffolding contigs (de novo assembly) • High-depth: Genome sequencing of repetitive regions or

structural rearrangements


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% 400-600 Mbp

SOLID DNA ligase 75bp AT bias >0.01-0.06% 20-30 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

>2.5kb (up to 10kb) insertions 15%

75-100 Mbp (5-10 Mbp

usable)

6. Challenges

The $1000 genome—Illumina!

“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”

http://investor.illumina.com/

Reported January 14 2014:

6. Challenges

Summary of technology • Point:

•  Sequencing is cheap and easy

•  Individual labs

• Current challenge •  Computational •  Data management

6. Challenges

NHGRI at genome.gov

Repetitive DNA

Interspersed repeats

e.g. transposable elements

Tandem repeats

e.g. satellites, CNVs

?

?

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)

6. Challenges

Challenges for repetitive DNA

6. Challenges

CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC

AATATGGAATATGG

AATATGGAATATGGAATATGGAATATGGAATATGGAATATGG


CCTGCGATAATATGCCTGCGATAATATG

CGATAATATGGAA

AATATGGTGTACCCAATATGGTGTACCC

GAATATGGTGTA

TAATATGGAATA

CCTGCGATAATATGGAATATGGTGTACCC

ATGGAATATGGAA

AATATGGAATAT

AATATGGAATA

GGAATATGGA

TATGGAATATGAATATGGAA

GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG

TGGTGTACCCAATATGGTGTA

CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC

ATATGGA GCGATAATATGGAA

AATATGGAATAT

True Genomic sequence


6. Challenges


AATATGGAATATGG




CGATAATATGGAA


GAATATGGTGTA

TAATATGGAATA


ATGGAATATGGAA

AATATGGAATAT

AATATGGAATA

GGAATATGGA


GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG




AATATGGAATAT


Assembly CCTGCGATAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGAATATGGTGTACCC

AATATGGAATATGG




CGATAATATGGAA


GAATATGGTGTA

TAATATGGAATA


ATGGAATATGGAA

AATATGGAATAT

AATATGGAATA

GGAATATGGA


GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG




AATATGGAATAT

Single end libraries


6. Challenges


AATATGGAATATGG




CGATAATATGGAA


GAATATGGTGTA

TAATATGGAATA


ATGGAATATGGAA

AATATGGAATAT

AATATGGAATA

GGAATATGGA


GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG




AATATGGAATAT


Assembly


AATATGGAATATGG




CGATAATATGGAA


GAATATGGTGTA

TAATATGGAATA


ATGGAATATGGAA

AATATGGAATAT

AATATGGAATA

GGAATATGGA


GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG




AATATGGAATAT

Paired end libraries


6. Challenges


AATATGGAATATGG




CGATAATATGGAA


GAATATGGTGTA

TAATATGGAATA


ATGGAATATGGAA

AATATGGAATAT

AATATGGAATA

GGAATATGGA


GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG




AATATGGAATAT


Assembly


AATATGGAATATGG




CGATAATATGGAA


GAATATGGTGTA

TAATATGGAATA


TATGGAATAT

AATATGGAATA

GGAATATGGA

TATGGAATATG

AATATGGAA

GGAATATGG

CCTGCGATAATATG

TAATATGGAATATG

ATGGAATATG ATATGGAATATGG


GCGATAATATG

TGGTGTACCCAATATGGAATAT


GGAATATGGAATA

AATATGGTGTA AATATGGAA

Paired end + Mate pair libraries

Repeats cause

6. Challenges

•  Misassemblies •  Complex rearrangements •  Gaps

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

6. Challenges

Further reading: • Metzker. 2010. Sequencing technologies—the next

generation. Nature Reviews. 11:31-46. • Mardis. 2013. Next-Generation Sequencing Platforms.

Ann. Rev. Anal. Chem 6:287-303. •  Treangen and Salzberg. 2012. Repetitive DNA and next-

generation sequencing: computational challenges and solutions. Nature Reviews Genetics 13:36-46.

Project background reading •  Brennecke, J, AA Aravin, A Stark, M Dus, M Kellis, R Sachidanandam, GJ

Hannon. 2007. Discrete small RNA-generating loci as master regulators of transposon activity in Drosophila. Cell 128:1089-1103.

•  Lemos, B, LO Araripe, DL Hartl. 2008. Polymorphic Y chromosomes harbor

cryptic variation with manifold functional consequences. Science 319:91-93. •  Nagao, A, T Mituyama, H Huang, D Chen, MC Siomi, H Siomi. 2010.

Biogenesis pathways of piRNAs loaded onto AGO3 in the Drosophila testis. RNA 16:2503-2515.

•  Filion, GJ, JG van Bemmel, U Braunschweig, et al. 2010. Systematic protein

location mapping reveals five principal chromatin types in Drosophila cells. Cell 143:212-224.

Papers •  Akbari, OS, I Antoshechkin, BA Hay, PM Ferree. 2013. Transcriptome

profiling of Nasonia vitripennis testis reveals novel transcripts expressed from the selfish B chromosome, paternal sex ratio. G3 (Bethesda) 3:1597-1605.

•  Blumenstiel, JP, X Chen, M He, CM Bergman. 2014. An Age-of-Allele Test of

Neutrality for Transposable Element Insertions. Genetics 196:523-538. •  Rogers, RL, JM Cridland, L Shao, TT Hu, P. Andolfatto, and KR Thornton.

2014. Landscape of standing variation for tandem duplications in Drosophila yakuba and Drosophila simulans. ArXiv preprint.

•  Kelleher, E.S., and Barbash D.A. (2013) Analysis of piRNA-mediated

silencing of active TEs in Drosophila melanogaster suggests limits on the evolution of host genome defense. Molecular Biology and Evolution. 30:1816-1819.

Getting setup to run graphical software on BlueHive • Please go to: https://www.circ.rochester.edu/wiki/index.php/Getting_Started And https://www.circ.rochester.edu/wiki/index.php/NX_Cluster •  Install X11 application if needed

Documents

Course outline - blogs.rochester.edublogs.rochester.edu/selfishDNA/wp-content/uploads/2014/01/Bio472... · • 1996- Yeast • 1998- C ... Whole Genome Shotgun (WGS) approach ( (