Introduction to Sequencing Technologies

August 22, 2014 Manpreet Katari

Why do we sequence?

•  Genome Annotation: A complete genome sequence provides us with the raw data to

construct a "parts list".

•  Comparative Genomics: Conserved regions in the genome are more likely to play an

important role in biology of the species.

•  Functional Genomics: Sequencing the RNA provides us with an insight into the

transcriptionally active regions of the genome.

•  Population Genetics and Genomics: Genetic structure and diversity reveals history and distribution of

phenotypic traits (e.g. disease susceptibility alleles)

•  Genetic Analysis:

Map and characterize molecular basis of allelic variants 2

Examples of Large Genome Projects

•  1000 Genomes Project (www.1000genomes.org). An effort to sequence the genome of 1000 people to identify genetic variants that occur in atleast 1% of the human population.

•  1001 Arabidopsis thaliana Genomes Project (www.1001genomes.org) . Study the genomes and phenotypes of 1001 accession that can explain difference in phenotype caused by adaptation to different conditions.

•  Metagenomics – Human Microbiome Project (http://commonfund.nih.gov/hmp/): Sequencing of DNA samples from environments, for example mouth, skin, and digestive system, to identify the different bacterial species present.

Evolution of Sequencing Technology

•  Method

•  Sanger sequencing (manual)

•  Automated Sanger sequencing Lee Hood (first semi-automated machine)

99.999% accuracy

$0.50/kilobase

•  Cyclic array sequencing •  sequencing by synthesis

•  sequencing by hybridization

•  Throughput

•  Tens of thousands of bp per person-year

~400-500bp/run

•  Thousands of bp per run (multiplexed) ~ millions of bp per year

~700-800bp/run

•  Millions of bp per run

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1977

1986

2000's

⇒ A 3’ hydroxyl group is essential for chain elongation

5’

3’

5

Sanger DNA Sequencing

CHAIN TERMINATOR

32P labeled audioradiogram 6

Sanger DNA Sequencing

Denaturing gel Labeled strands

Add dNTPs, Polymerase,

ddNTP

Template + Product

Primer Denatured Template Run samples on

denaturing polyacrylamide gel

+

−

5'

3'

Capillary Gel Electrophoresis

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3'- G A C T G A A G C T G T T

-5'

⇒ Fluorescent dye vs. radioactive label on dNTPs

⇒ Sequencing reaction is performed in a single tube with a mixture of fluorescently labeled ddNTPs

⇒ Reaction is electrophoresed in a single denaturing capillary gel (96 samples run at once using robotics)

⇒ Different wavelengths emitted by fluorescent dyes are automatically detected upon laser excitation

⇒ Computer software automatically reads sequence and assesses quality

Laser Detector

Trace file

ssDNA to be sequenced

5'- C G A A G T C A G -3'

Radioactive vs. Fluorescent Sequencing

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• 32P-labeled dNTPs • One lane per base • Autoradiogram

• 4 different fluorophores • Single capillary gel • Laser detector

Automated Sequencing

•  Perhaps the most important contribution to large-scale sequencing was the development of automated sequencers.

•  The industry is currently transitioning from Sanger sequencers to second-generation cycle sequencers for large-scale applications.

•  Automated Sanger sequencers still fill an important niche currently –

•  but mostly for small-scale applications, like checking that clones contain the expected sequence

•  Next-gen platforms are currently very expensive

•  but table-top models will probably be standard laboratory equipment in 5-10 years.

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MegaBACE •  Made by Amersham •  96 capillaries •  Robotic loading from 384–well

plate •  Two to four hours per run •  Up to 800 bases per read

Automated Sequencers

ABI 3700 •  Made by Applied Biosystems •  Most widely used :

•  96 capillaries •  robotic loading from 384-well

plates •  Two to three hours per run •  600–700 bases per read

ABI traces

Video Demos

Sanger Sequencing - http://youtu.be/nudG0r9zL2M

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Workflow of conventional vs. second-generation sequencing

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High-throughput shotgun Sanger sequencing

Cyclic array shotgun sequencing

96 or 384 long reads per run

Millions of short reads per run

Template immobilization Sanger cycle seq

(Template amplification)

Template amplification

Capillary electrophoresis

Seq by synthesis or hybridization

Workflow of conventional vs. second-generation sequencing

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High-throughput shotgun Sanger sequencing

Cyclic array shotgun sequencing

96 or 384 long reads per run

Millions of short reads per run

Template immobilization Sanger cycle seq

(Template amplification)

Template amplification

Capillary electrophoresis

Seq by synthesis or hybridization

Cost of Sequence per megabase

Template Immobilization Strategies

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Illumina

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Video Demos

Illumina - http://youtu.be/womKfikWlxM

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PacBio

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Video Demos

PacBio - http://youtu.be/NHCJ8PtYCFc

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J. Craig Venter Celera Genomics

Francis Collins Human Genome Project

Road to Human Genome

Map-­‐based  sequencing  I  

•  Human  Genome  Project  adopted  a  map-­‐based  strategy  – Start with well-defined physical map – Produce shortest tiling path for large-insert clones – Assemble the sequence for each clone – Then assemble the entire sequence, based on the

physical map

Map-­‐based  sequencing  II  

Construct  clone  map  and  select  mapped  clones  

Generate  several  thousand  sequence  reads  per  clone  

Assemble  

Physical  mapping  

•  Determina@on  of  physical  distance  between  two  points  on  chromosome  – Distance  in  base  pairs  

•  Example:  between  physical  marker  and  a  gene  •  Need  overlapping  fragments  of  DNA  

– Requires  vectors  that  accommodate  large  inserts  •  Examples:  cosmids,  YACs,  and  BACs      

BACs  and  PACs  •  BACs and PACs

–  Most commonly used vectors for large-scale sequencing

–  Good compromise between insert size and ease of use

–  Growth and isolation similar to that for plasmids

Con@gs •  Contigs are groups of overlapping pieces of chromosomal

DNA –  Make contiguous clones

•  For sequencing one wants to create “minimum tiling path” –  Contig of smallest number of inserts that covers a region of

the chromosome

genomic  DNA  

con@g  

minimum  @ling  path  

Con@gs  from  overlapping  restric@on  fragments

•  Cut inserts with restriction enzyme

•  Look for similar pattern of restriction fragments –  Known as

“fingerprinting” •  Line up overlapping

fragments •  Continue until a contig

is built

Gel  image  processing

FPC:  fingerprint  analysis  window

The C. elegans genome project

The  first  mul@cellular  organism  to  have  its  genome  fully  sequenced  (97  million  bases)  The  sequence  was  completed  in  1998  

⇒   The  minimum  @ling  path,  or  “The  Golden  Path”  

Mapless  sequencing  

•  Alterna@ve  solu@on:  fragment  en@re  genome  – Sequence  each  fragment  – Assemble  overlapping  sequences  to  form  con@guous  sequence  

•  Focus  on  principles  and  techniques  of  mapping  and  sequencing  

Whole-­‐genome  shotgun  sequencing  I  •  Developed  by  Celera  

–  Subsidiary  of  Applied  Biosystems,  maker  of  automated  sequencers  

•  No  mapping    •  Instead,  the whole

genome is sheared •  Randomly sequenced

Whole-­‐genome  shotgun  sequencing  II  

Generate  tens  of  millions  of  sequence  reads  

Assemble  

Whole-­‐genome  shotgun  sequencing  III  

•  Major  challenge:  assembly  – Repe@@ve  elements  are  the  biggest  problem  

•  Performed  on  very  high-­‐speed  computers,  using  novel  soYware  

•  Key  to  assembly  is  paired  reads  – Sequence  both  ends  of  each  clone  

Milestone:  26  June  2000  -­‐    White  House  press  conference  with  Bill  Clinton:    HGP:    Started  1990  ~22.1  billion  nucleo@des  of  sequence  data  7-­‐fold  coverage  Unfinished  (24%  completely  finished,  50%  near-­‐finished)    Celera:    Started  1998  ~14.5  billion  nucleo@des  of  sequence  data  4.6-­‐fold  coverage  Complete  assembled  genome  with  >99%  coverage        First  assembled  draY  of  human  genome  was  simultaneously  published  in  Nature  &  Science  15  &  16  February  2001  (Nature  published  1  day  earlier).      

© 2005 Prentice Hall Inc. / A Pearson Education Company / Upper Saddle River, New Jersey 07458

Hierarchical vs shotgun

Hybrid  approach  

•  Combines aspects of both map-based and whole-genome shotgun approaches – Map clones – Sequence some of the mapped clones – Do whole-genome sequencing – Combine information from both methods

•  Use sequence from mapped clones as scaffold to assemble whole-genome shotgun reads

•  Used for sequencing the mouse genome

Genome Assembly

Whole  Genome  Shotgun  Sequencing  

Comparison of overlap graph and ���de Brujin graph for assembly

Shatz et al. Genome Research 2010, Analysis of large genomes

Example of Tour Bus error correction.

Zerbino D R , and Birney E Genome Res. 2008;18:821-829

Copyright © 2008, Cold Spring Harbor Laboratory Press

End Reads (Mates)

Primer

Central  steps  of  the  assembly  

Finishing  I  •  Process  of  assembling  raw  

sequence  reads  into  accurate  con@guous  sequence  –  Required  to  achieve  

1/10,000  accuracy  •  Manual  process  

–  Look  at  sequence  reads  at  posi@ons  where  programs  can’t  tell  which  base  is  the  correct  one  

–  Fill  gaps  –  Ensure  adequate  coverage  

 Gap  

Single  stranded  

Finishing  II  •  To  fill  gaps  in  sequence,  

design  primers  and  sequence  from  primer  

•  To  ensure  adequate  coverage,  find  regions  where  there  is  not  sufficient  coverage  and  use  specific  primers  for  those  areas  

GAP  

Primer  

Primer  

Assembly  Progression  (Macro  View)  

Each  nucleo@de  sequenced  many  @mes  

Lander-­‐Waterman  Model  

Rough-draft and skimming sequence

•  Rough-draft sequence refers to an average of 5x coverage

•  Skimming is 1–3x coverage • Obtains 67%–97% of the sequence • On average, 99% accurate • Of greatest use when can compare the sequence

to a reference sequence • For example, chimpanzee genome compared

with human genome

DNA RNA

cDNA

phenotype protein

[1] Transcription [2] RNA processing (splicing) [3] RNA export [4] RNA surveillance

The Expressed Genome

•  Sequencing mRNA: •  gene discovery •  define gene structures •  define differences in mRNA processing

•  alternative transcription start sites •  alternative exons and splice junction usage •  alternative polyA site usage

•  mRNA profiling •  characterize functional differences between developmental stages and

tissues

•  Small RNA profiling: •  discover small RNAs, e.g. miRNA, siRNA, piRNA etc…

•  these often have regulatory functions

EST sequencing

•  Extract RNA from different developmental stages and tissues

•  Make cDNA library

•  Select clones at random

•  Sequence in from one or both ends

•  One-pass sequencing

•  The resulting sequence = expressed sequence tag (EST)

Muscle mRNA

cDNA libraries

LIMS

Robotic stations DNA sequencers

5’ 3’ cDNA

Partial sequence = EST

ESTs Mapped to Genome

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EST sequencing: pros and cons

•  Advantages

•  Relatively inexpensive

•  Certainty that sequence comes from transcribed gene

•  Information about tissue and developmental stage

•  Long contiguous sequence often spanning introns

•  Can provide clear boundary for ends of transcripts

•  Disadvantages

•  No regulatory information

•  Usually <60% of genes found in EST collections (random sampling of transcripts based on abundance)

•  Most ESTs are not full-length (higher representation of 3' ends)

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Questions that can be addressed with genome-wide expression analysis:

•  What genes have similar function? •  What regulatory pathways exist? •  Can we subdivide experiments or genes into meaningful classes? •  Can we correctly classify an unknown experiment or gene into a

known class? •  Can we make better treatment decisions for a cancer patient based

on his or her gene expression profile?

Microarrays vs Northern blots: from Gene to Genome Science

•  Northern blot: limited by number of lanes in gel

•  Microarray: A large number

of DNA fragments are attached in a systematic way to a solid substrate, can measure mRNA levels for thousands of genes (~ every gene in a genome) in parallel

Three types of array manufacture

•  On-chip oligonucleotide synthesis •  Photolithography

•  Affymetrix (~25-mers) •  Ink-jet printing

•  Agilent (~60-mers)

•  Spotted microarrays •  Long dsDNA (typically genomic PCR products)

Affymetrix gene chip

Probe pairs

•  Oligos are selected from a region of the gene that has low similarity to other genes.

Perfect match: ATGTTTGACGCTGCGTAGATCCGAG Mismatch: ATGTTTGACGCTACGTAGATCCGAG

MicroArray

Microarray hybridization

Spotted microarrays •  Competitive hybridization: two labeled

cDNA samples (experimental and control) hybridized to same slide

•  Cy3 and Cy5 dye labeling, fluoresce at different wavelengths

Affymetrix GeneChips

•  One labeled RNA population per chip •  Biotin labeling, binds to fluorescently

labeled avidin (Comparison made between hybridization intensities of same oligonucleotides on different chips).

mRNA

cDNA

DNA microarray

samples

Microarray Animation

Spotted glass microarray

Comparisons  of  Gene  Expression    across  samples  

whole  body   liver  

brain   kidney  liver   lung    

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3 54 0

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Gene A Gene B

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Gene A Gene B

Transcriptomics using RNA-seq

RNA-seq provides even more

Candidate new and revised exons

Reproducibility, linearity and sensitivity.

Reproducibility, linearity and sensitivity.

Reproducibility, linearity and sensitivity.

Reproducibility, linearity and sensitivity.

Illum

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Log

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Log (KNO3/KCl) Affymetrix  ATH1  chips  

N-­‐regula@on  of  mRNA:    Illumina  vs  ATH1      

R2 = 0.85

Comparison of platforms for detecting gene expression

AFFY Gene Chip Illumina

All protein coding genes are represented X

Can detect all the different types of RNA X

Cost (including analyzing data) X

Can determine gene regulation X X

Requires pre-existing knowledge of gene sequence X