1. Next-generation DNA sequencing
Boston College Biology Department
BI420 Introduction to Bioinformatics
Fall 2012

2. Traditional DNA sequencing

3. Genetics of living organisms
Chromosomes
DNA

4. Radioactive label gel sequencing

5. Four-color capillary sequencing
~1 Mb
~100 Mb
>100 Mb
~3,000 Mb
ABI 3700 four-color sequence trace

6. Individual human resequencing

7. Next-generation sequencing

8. … offer vast throughput … & many applications
Illumina, SOLiD
1 Tb
100 Gb
10 Gb
454
bases per machine run
1 Gb
100 Mb
10 Mb
ABI / capillary
1 Mb
10 bp
100 bp
1,000 bp
read length

9. Sequencing chemistries
DNA base extension
DNA ligation
Church, 2005 9

10. Template clonal amplification
Church, 2005 10

11. Massively parallel sequencing
Church, 2005

12. Chemistry of paired-end sequencing
Double strand DNA is folded into a bridge shape then separated into single strands. The end of each strand is then sequenced.
(Figure courtesy of Illumina) 12

13. Paired-end reads fragment amplification: fragment length 100 - 600 bp
fragment length limited by amplification efficiency
circularization: 500bp - 10kb (sweet spot ~3kb)
fragment length limited by library complexity
Korbel et al. Science 2007 13

14. Features of NGS data Short sequence readsbp
25-35bp (micro-reads)
Huge amount of sequence per run
Up to gigabases per run
Huge number of reads per run
Up to 100’s of millions
Higher error as compared with Sanger sequencing
Error profile different to Sanger 14

15. T1. Roche / 454 FLX system
Pyrosequencing technology. This involves addition of a very small quantity of the ddNTP, which will only fluoresce after it binds to the template. The procedure is repeated base-by-base and one checks which color lights up
Lengths of homopolymer runs (AAA, CCCC, etc) quantified by brightness of signal. This is the largest source of error
variable read-length 15

16. T2. Illumina / Solexa Genome Analyzer
fixed-length short-read sequencer
read properties are very close to traditional capillary sequences
very low INDEL error rate 16

17. T3. AB / SOLiD system 1 2 3 fixed-length short-read sequencer
2nd Base
1st Base 1 2 3
fixed-length short-read sequencer
employs a 2-base encoding system 17

18. T4. Pacific Biosciences Single Molecule Real Time
DNA polymerase fixed in place
Polymerase altered so that as bases are added onto second strand, a base-specific fluorescence signal will be emitted
Single-molecule optical readout finely controlled using waveguides
Long readlengths (>1000bp)
SMRT Technology overview 18

19. Applications

20. Application areas Genome resequencing variant discovery
somatic mutation detection
mutational profiling
De novo sequencing
Identification of protein-bound DNA
chromatin structure
methylation
transcription binding sites
RNA-Seq
expression
transcript discovery
Mikkelsen et al. Nature 2007
Cloonan et al. Nature Methods, 2008

21. SNP and short-INDEL discovery21

22. Mutational profiling in deep 454 data
Pichia stipitis reference sequence
Image from JGI web site
Pichia stipitis is a yeast that efficiently converts xylose to ethanol (bio-fuel production)
one specific mutagenized strain had especially high conversion efficiency
goal was to determine where the mutations were that caused this phenotype
we analyzed 10 runs (~3 million reads) of 454 reads (~20x coverage of the 15MB genome)
found 39 mutations
Smith et al. Genome Research 2008

23. Structural variation detection
structural variations (deletions, insertions, inversions and translocations) from paired-end read map locations
copy number (for amplifications, deletions) from depth of read coverage
Ask Chip to provide images for this one slide 23

24. Identification of protein-bound DNA
genome sequence
aligned reads
Chromatin structure (CHIP-SEQ)
(Mikkelsen et al. Nature 2007)
Transcription binding sites. (Robertson et al. Nature Methods, 2007) 24

25. Novel transcript discovery (genes)
Mortazavi et al. Nature Methods
novel exons
novel transcripts containing known exons 25

26. Novel transcript discovery (miRNAs)
Ruby et al. Cell, 2006 26

27. Expression profiling tag counting (e.g. SAGE, CAGE)
gene
gene
aligned reads
aligned reads
Jones-Rhoads et al. PLoS Genetics, 2007
tag counting (e.g. SAGE, CAGE)
shotgun transcript sequencing 27

28. De novo genome sequencing
Lander et al. Nature 2001
short reads
read pairs
longer reads
assembled sequence contigs 28

29. Technologies / properties / applications
Technology
Roche/454
Illumina/Solexa
AB/SOLiD
Read properties
Read length bp
75-150bp
25-50bp
Error rate
<0.5%
<1.0%
Dominant error type
INDEL
SUB
Quality values available
yes
not really
Paired-end separation
< 10kb (3kb optimal) bp
500bp - 10kb (3kb optimal)
Applications
SNP discovery ● ○
short-INDEL discovery
SV discovery
CHIP-SEQ
small RNA/gene discovery
mRNA Xcript discovery
Expression profiling
De novo sequencing ? 29

30. The Bioinformatics angle

31. Trace extraction
Trace extraction

32. Base calling Base calling machine read-outs are quite different
read length, read accuracy, and sequencing error profiles are variable (and change rapidly as machine hardware, chemistry, optics, and noise filtering improves) 32

33. Base error rate error rate typically 0.4 - 1%
the more errors the aligner allows, the lower the fraction of the reads that can be uniquely aligned 33

34. Error rate grows with each cycle
This phenomenon limits useful read length
A key challenge in sequencing technology is how to get long reads that remain accurate. 34

35. Read mapping read mapping is similar to a jigsaw puzzle…
…where they give you the cover on the box

36. Some pieces are easier to place than others…
pieces that look like each other…
…pieces with unique features

37. Repeats  multiple mapping problem
Lander et al. 2001

38. Dealing with multiple mapping38

39. Mapping quality values
0.8
0.19
0.01 39

40. Paired-end (PE) reads
fragment length: 100 – 600bp
Korbel et al. Science 2007
fragment length: 1 – 10kb
PE reads are now the standard for whole-genome short-read sequencing 40

41. Gapped alignments (for INDELs)41

42. Read mapping programs Many mappers are available
Handling of read pairs
Handling non-unique mapping
Speed and accuracy
Flexibility vis-à-vis sequencing technologies
Stability and support

43. Data storage requirements43

44. Duplicate reads

45. Local misalignments

46. Base quality value recalibration

47. Multiple read types
ABI/cap.
454/FLX
454/GS20
Illumina

48. Alignment visualization
integrating genomic context (e.g. gene annotations)
too much data – indexed browsing
too much detail – color coding, show/hide
structural variant visualization more difficult

49. Standard data formats
SRF/FASTQ
GVF/VCF
SAM/BAM

50. Standard data formats
Reads: FASTQ
Alignments: SAM/BAM
Variants: VCF