1. Deep Sequencing Introduction to Bioinformatics Seminar
November 9th, 2009
Angela Benton, Samuel Darko, Prakriti Mudvari and Prisca Takundwa

2. History of Sequencing
”Sanger Sequencing” developed by Fred Sanger et al in the mid 1970’s
Uses dideoxynucleotides for ”chain termination”, generating fragments of different lengths ending in ddATP, ddGTP, ddCTP or ddTTP

3. History of Sequencing Cont.
A schematic of Sanger sequencing

4. History of Sequencing Cont.
DNA fragments are separated by size by gel electrophoresis
From the gel, the DNA sequence can be determined
Can produce DNA fragments bp long (good), but it’s slow (bad)
Lots of other problems including clone library generation and low throughput
The Human Genome Project used Sanger sequencing, completion took over 10 years

5. Next Generation Sequencers
Next (or 3rd) generation sequencers came onto the scene in the early 2000’s
General characteristics include:
Amplification of genetic material by PCR
Ligation of amplified material to a solid surface
Sequence of the target genetic material is determined using Sequence-by-Synthesis (using labelled nucleotides or pyrosequencing for detection) or Sequence by ligation
Sequencing done in a massively parallel fashion and sequence information is captured by a computer

6. Next Gen. Sequencers Cont.
Sequencing platform
ABI3730xl Genome Analyzer
Roche (454) FLX
Illumina Genome Analyzer
ABI SOLiD
HeliScope
Sequencing chemistry
Automated Sanger sequencing
Pyrosequencing on solid support
Sequencing-by-synthesis with reversible terminators
Sequencing by ligation
Sequencing-by-synthesis with virtual terminators
Template amplification method
In vivo amplification via cloning
Emulsion PCR
Bridge PCR
None (single molecule)
Read length
700–900 bp
200–300 bp
32–40 bp
35 bp
25–35 bp
Sequencing throughput
0.03–0.07 Mb/h
13 Mb/h
25 Mb/h
21–28 Mb/h
83 Mb/h

7. Next Gen. Sequencers Cont.

8. Next Gen. Sequencers Cont.
4/17/2017
Next Gen. Sequencers Cont.
Position
Cycle: G
TEMPLATES C A G T C A 1 2 3 G - - C A - - G
Actual tSMS Image from 1/4 images from a single FOV. Each image uses a CCD camera in the HeliScope (~7,500 strands) T - - C A
Provided to author courtesy of Helicos representative 8 8

9. Next Gen. Sequencers Cont.
Sequencing-by-ligation on SOLiD

10. Illumina Genome Analyzer Time to sequence (days)
Next Gen vs Sanger
Let’s think about the domesticated silkworm genome
The reference genome is about 432Mb large
It was assembled from approximately 8.5 fold coverage
Platform
ABI3730xl Genome Analyzer
Roche (454) FLX
Illumina Genome Analyzer
ABI SOLiD
Helicos Heliscope
Sequencing Speed
Mb/h
13 Mb/h
25 Mb/h
21–28 Mb/h
83 Mb/h
Time to sequence (days)
2185.7
11.8
6.1
5.5
1.8

11. Bioinformatics
Because of the massively parallel nature of next gen sequencers, huge amounts of data are produced quickly requiring terabytes of storage
New bioinformatics tools were developed to utilize the huge number of much shorter reads (~35bp vs ~800bp)
Bowtie - Ultrafast, memory-efficient short read aligner
SOAPdenovo - Part of the SOAP suite, used to build reference genome
TopHat - TopHat is a fast splice junction mapper for RNA- Seq reads

12. Applications Novel whole genome sequencing Whole genome resequencing
The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific
Whole genome resequencing
Complete Resequencing of 40 Genomes Reveals Domestication Events and Genes in Silkworm (Bombyx)
RNA-Seq (transcriptomics)
A Global View of Gene Activity and Alternative Splicing by Deep Sequencing of the Human Transcriptome

13. NEXT-GENERATION SEQUENCING : APPLICATIONS
Prisca Takundwa
NEXT-GENERATION SEQUENCING : APPLICATIONS

14. APPLICATIONS
The potential applications platform for next- generation sequencing is enormous.
Some examples that will be discussed include application in
Cellular Genomes using WGS
Metagenomics
Genomic Medicine
Other novel applications

15. Cellular Genomes
The advent of automation in Sequencing initiated by Craig Venter et al gave rise to sequencing beyond viruses and organelles.
In 1995 Venter’s group at TIGR reported complete sequences of two bacteria, Haemophilus influenzae and Mycoplasma genitalium.

16. Cellular Genomes Significance ;
1st glimpse of the complete instruction set for a living organism
an approximation of the minimal set of genes required for cellular life
Insight into the methods used to come up with these cellular genomes

17. Cellular Genomes Significance
Paved the way for other cellular genomes such as E.coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogoster
Human Genome Project
Next-generation appeal

18. Metagenomics Getting rid of cultures
Introduces diversity, includes all genes and potentially all members contributing to a given environment
Typically use 16S rRNA gene to identify different species and strains
Advantages :
Closes the huge gap in sequence data in non-model species.
Many prokaryotes are human pathogens

19. Metagenomics Some examples
Breitbart et al showed that 2000 liters of sea water contained >5000 different viruses. >1000 of these were found in human stool and majority of these were new species.
Craig Venter’s Global Ocean Voyage

20. Genomic Medicine Sequencing and how it lends itself to medicine
Implications in diagnosis, treatment and prevention
Personalized medicine
$1000 genome
Some examples include Cancer and HIV applications

21. Other Novel Applications
Resequencing
Plants – Sugar beet and Tropical Evergreen Fagaceae
Junk DNA
Drug discovery

22. Transcriptomics
Angela Benton

23. Background
Transcriptome – the complete set of coding and non-coding RNA molecules in a cell at a particular time
Varies between cell types
Transcriptomics – the study of the transcripts in a cell, cell type, organism, etc.

24. Candidate Gene Analysis
Northern blot analysis
Separation of RNA molecules by size
Hybridization of a complementary radioactively- labeled probe
Detection method
Reverse transcriptase PCR (RT-PCR)
RNA molecules reverse transcribed into cDNA
PCR amplified
Quantification method

25. Microarray Technology
High-throughput gene expression profiling
Hybridization of labeled cDNAs to an array of complementary DNA probes
Measurement of expression levels based on hybridization intensity

26. Sequencing-Based Approaches
Full-length cDNA (FLcDNA) sequencing
Complete sequencing of cDNA clone
Expressed sequence tag (EST) sequencing
Single-pass sequencing of cDNA clone
Serial Analysis of Gene Expression (SAGE)
Short sequence tags at 3’ end of transcript
Tags concatenated and sequenced

27. RNA-Seq Alternative to Sanger sequencing
RNA molecules converted into library of cDNA fragments
Adaptors attached to one/both ends
Short sequence reads obtained
Aligned to reference genome and classified as:
Exons
Junctions
Poly-A ends
Can be used to assemble de novo sequences

28. Next Generation Sequencing Applications
Protein-coding gene annotation
Transcriptome sequences can be aligned:
To genome of same species
To genome of related species
Discovery of novel exons and introns
Long read lengths – de novo analyses
Short read lengths – novel splicing events

29. Next Generation Sequencing Applications
Gene expression profiling
SAGE method
5’-RATE method (454 sequencing)
3’-UTR method (454 sequencing)

30. Next Generation Sequencing Applications
Noncoding RNA (ncRNA) discovery
ncRNA not translated into protein product
Role in regulation of development and cell fate determination
Three kinds:
Micro RNAs (miRNAs)
Small interfering RNAs (siRNAs)
Piwi-interacting RNAs (piRNAs)

31. Next Generation Sequencing Applications
Transcript rearrangement discovery
Genome rearrangements common in human cancers
Includes:
Translocations
Inversions
Indels
Copy number variants
Paired-end sequencing
Infers presence of rearrangement

32. Bioinformatic Implications
Large amounts of data generated
Tools are needed to aid in:
Storage
Retrieval
Processing
Interpretation
Integration

33. Bioinformatics of Deep Sequencing
Prakriti Mudvari

34. Bioinformatics of Deep Sequencing

35. The Basics.

36. Creating a Paired End Tag

37. Paired End vs. Unpaired Reads
Millions of reads are generated.
Repetitive regions within the genome cause the reads to be mapped to multiple locations.
Polymorphism in a read can cause it to be mapped to a wrong location.
Discarding ambiguous reads can reduce coverage

38. Illumina Genome Analyzer
Comparison of Output
ABI Genome Analyzer
454
Illumina Genome Analyzer
ABI SOLiD
HeliScope
Read Length bp bp
32-40 bp
35 bp
25-35 bp
Sequencing throughput
Mb/h
13 Mb/h
25 Mb/h
21-28 Mb/h
83 Mb/h

39. Challenges Quality of data Storage Cross Platform Analysis
Data Annotation
Assembly
SNP/Mutation Detection

40. Bioinformatics Tools Alignment of reads to reference genome
Assembly of de novo sequence
Quality Control & Base Calling
Polymorphism detection
Genome browsing and annotation

41. Alignment of reads
Reads generated from sequencing is mapped to a reference genome
Conventional tools like Blast or Blat do not work well with short sequence reads.
Modification of existing alignment algorithms to handle short reads.

42. Alignment Tools Cross_match ELAND Exonerate MAQ Mosaik SHRiMP SOAP
Zoom!

43. Short Oligonucleotide Alignment Program (SOAP)
Maps short oligonucleotides to reference sequence in a gapped or ungapped alignment.
Can be used for single as well as paired end alignments.
Allows at most two mismatches per read or one continuous gap of size 1-3bp when aligning. No mismatches allowed in the flanking region.
Best hit is the one with least number of mismatches or smallest gap.
Iteratively trims the several basepairs at 3’ end, that have highest number of sequencing errors and realigns.
Uses seed and hash-lookup algorithm to accelerate alignment.
Loads reference sequence into memory instead of reads.
Written in C++.

44. Assembly
De novo sequencing involves assembling overlapping reads to form contiguous sequence of DNA.
Done in cases where there’s no genomic information available.

45. Assembly
ABySS
ALLPATHS
Edena
Euler-SR SHARCGS
SHRAP
SSAKE
Velvet

46. Assembly By Short Sequence (ABySS)
Originally developed for de novo assembly of large genomes using short reads.
Is a distributed representation of a de Bruijn graph that allows parallel computation of algorithm across a network of computers.
Assembly is done in two steps.
First possible substrings of a specific length of sequence reads are first generated. Substring dataset are then processed to remove errors and contiguous sequences are built without using paired end information.
Mate pair information is then used to extend the contigs.

47. Assembly By Short Sequence (ABySS)
Use of paired end reads reduces the ambiguity of repetitive regions.
Written in C++ and uses Message Parsing Interface to communicate between nodes.

48. Basecalling
Determination of nucleotide base depending on signal on the trace file produced by a sequencer

49. Basecalling
PyroBayes
Alta-Cyclic
BayesCall

50. Single Nucleotide Polymorphisms (SNP) Detection
Sequence variation caused when a single nucleotide base differs between different members of species or between two chromosomes of an individual.

51. SNP Detection
PbShort
ssahaSNP

52. Other Tools
TagDust: Program for identifying and eliminating artifacts from next generation sequencing data.
ShortRead: Package for input, quality assessment and exploration of high-throughput sequence data.

53. The End
Thank you!
Questions?

54. References
O. Morozova, et al. Applications of New Sequencing Technologies for Transcriptome Analysis. Annu. Rev. Genomics Hum. Genet. 2009
J.C. Vera, et al Rapid transcriptome characterization for a nonmodel organism using 454 pyrosequencing. Mol. Ecol. 17:
N. Cloonan, et al Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat. Methods. 5:
R.D. Morin, et al Application massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. Genome Res. 18(4):610-21
R.K. Thomas, et al High-throughput oncogene mutation profiling in human cancer. Nat. Genet. 39:
Z. Wang, et al RNA-Seq: a revolutionary tool for transcriptomics. Nature Review Genetics. 10(1):57-63.
T.A. Brown Genomics. Garland Science Publishing. Chapter 6.

55. References cont.
Venter, C et al: The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific. PLoS Biology, 2007.
Sultan, M et al: A Global View of Gene Activity and Alternative Splicing by Deep Sequencing of the Human Transcriptome. Science, 2008.
Xia, Q et al: Complete Resequencing of 40 Genomes Reveals Domestication Events and Genes in Silkworm (Bombyx). Science, 2009.
Genome Res November; 18(11): 1851– , Cold Spring Harbor Laboratory PressMapping short DNA sequencing reads and calling variants using mapping quality scoresHeng Li,1 Jue Ruan,2 and Richard Durbin1,3
Multiplex parallel pair-end-ditag sequencing approaches in system biologyYijun Ruan, Chia-Lin Wei * Genome Technology & Biology Group, Genome Institute of Singapore, 60 Biopolis Street, Singapore
"SOAP: short oligonucleotide alignment program" (2008) BIOINFORMATICS,Vol. 24 no , pages 713–714 doi: /bioinformatics/btn025

56. References cont.
Hutchinson, Clyde A. DNA Sequencing : bench to bedside and beyond. Nucleid Acids Research,2007 Vol 35, No
Breitbart, M; Salamon P, Andresen B, Mahaffy JM, Segall AM, Mead D, Azam F, Rohwer F (2002). "Genomic analysis of uncultured marine viral communities". Proceedings of the National Academy USA 99: 14250–14255.
Himmelbauer et al, Plant Genomics in the era of high throughput sequencing: The case of the sugar beet, Next Generation Sequencing, 2009
Kua, CS and Cannon, CH, Comparative genomics of Tropical Evergreen Fagaceae, Next Generation Sequencing, 2009
Liu George, Applications and Case Studies of the Next- Generation Sequencing Technologies in Food, Nutrition and Agriculture, Recent Patents on Food, Nutrition & Agriculture, 2009,1,75-79