Next generation Sequencing or massive parallel sequencing is a high throughput approach to sequence genetic material using the concept of massively parallel processing. It is also called second generation sequencing.This enables researchers a wide variety of applications & study biological systems.
whole genome analysis
history
needs
steps involved
human genome data
NGS
pyrosequencing
illumina
SOLiD
Ion torrent
PacBio
applications
problems
benefits
Next generation Sequencing or massive parallel sequencing is a high throughput approach to sequence genetic material using the concept of massively parallel processing. It is also called second generation sequencing.This enables researchers a wide variety of applications & study biological systems.
whole genome analysis
history
needs
steps involved
human genome data
NGS
pyrosequencing
illumina
SOLiD
Ion torrent
PacBio
applications
problems
benefits
Metagenomics is the study of metagenome, genetics material, recovered directly from environmental sample such as soil, water or faeces.
Metagenomics is based on the genomics analysis of microbial DNA directly
from the communities present in samples
Metagenomics technology – genomics on a large scale will probably lead to great advances in medicine, agriculture, energy production and bioremediation.
Metagenomics can unlock the massive uncultured microbial diversity present in the environment for new molecule for therapeutic and biotechnological application.
Metagenomic studies have identified many novel microbial genes coding for metabolic pathways such as energy acquisition, carbon and nitrogen metabolism in natural environments that were previously considered to lack such metabolism
Jonathan Eisen talk at #UCDavis 10/19/15 on "Microbiomes in Food and Agricult...Jonathan Eisen
Slides for talk on "Microbiomes in Food and Agriculture" by JonathanEisen - note - not all slides were used in talk. These were there to stimulate discussion ...
Metagenomics is the study of metagenome, genetics material, recovered directly from environmental sample such as soil, water or faeces.
Metagenomics is based on the genomics analysis of microbial DNA directly
from the communities present in samples
Metagenomics technology – genomics on a large scale will probably lead to great advances in medicine, agriculture, energy production and bioremediation.
Metagenomics can unlock the massive uncultured microbial diversity present in the environment for new molecule for therapeutic and biotechnological application.
Metagenomic studies have identified many novel microbial genes coding for metabolic pathways such as energy acquisition, carbon and nitrogen metabolism in natural environments that were previously considered to lack such metabolism
Jonathan Eisen talk at #UCDavis 10/19/15 on "Microbiomes in Food and Agricult...Jonathan Eisen
Slides for talk on "Microbiomes in Food and Agriculture" by JonathanEisen - note - not all slides were used in talk. These were there to stimulate discussion ...
DNA Sequencing : Maxam Gilbert and Sanger SequencingVeerendra Nagoria
DNA sequencing is a technique to find out the exact arrangement of Nucleotides to make one strand of DNA. DNA sequencing helps in numerous ways from sequence information to paternity testing, mutation detection etc. Traditionally two approaches were used to solve the problem. First is based of enzymes and Second is based on ddNTPs to sequence the DNA using gel electrophoresis technique.
Describes using emulsion PCR to decorate Ion Sphere Particles (beads) with library molecules for Ion Torrent PGM sequencing. This is from a class Ann taught on Genomic Biotechnology.
Sanger sequencing is a method of DNA sequencing based on the selective incorporation of chain-terminating dideoxynucleotides by DNA polymerase during in vitro DNA replication.
Next-Generation Sequencing an Intro to Tech and Applications: NGS Tech Overvi...QIAGEN
This slidedeck provides a technical overview of DNA/RNA preprocessing, template preparation, sequencing and data analysis. It covers the applications for NGS technologies, including guidelines for how to select the technology that will best address your biological question.
Course: Bioinformatics for Biomedical Research (2014).
Session: 2.1.2- Next Generation Sequencing. Technologies and Applications. Part II: NGS Applications I.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
Personal Genomes: what can I do with my data?Melanie Swan
Biology evolved to be just good enough to survive and genomics provides the critical next-generation toolkit for its greater exploitation. Genomics is already starting to be medically actionable and is likely to become increasingly useful over time. This presentation discusses how your genetic information is already useful today,
A microarray is a laboratory tool used to detect the expression of thousands of genes at the same time. DNA microarrays are microscope slides that are printed with thousands of tiny spots in defined positions, with each spot containing a known DNA sequence or gene.
Advances and Applications Enabled by Single Cell TechnologyQIAGEN
Over the past 5 years, single-cell genomics have become a powerful technology for studying small samples and rare cells, and for dissecting complex populations such as heterogeneous tumors. Single-cell technology is enabling many new insights into diverse research areas from oncology, immunology and microbiology to neuroscience, stem cell and developmental biology. This webinar introduces single-cell technology and summarizes the newest scientific applications in various research areas, all in the context of current literature.
Innovations in Sequencing & Bioinformatics
Talk for
Healthy Central Valley Together Research Workshop
Jonathan A. Eisen University of California, Davis
January 31, 2024 linktr.ee/jonathaneisen
Thoughts on UC Davis' COVID Current ActionsJonathan Eisen
Slides I used for a presentation to Chancellor May's leadership council about the current state of UC Davis' response to COVID and how it could be improved
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.
Evolution of DNA Sequencing by Jonathan Eisen
1. Evolution of Sequencing
Workshop in Applied Phylogenetics
March 8, 2015
Bodega Bay Marine Lab
Jonathan A. Eisen
UC Davis Genome Center
1
2. Notes
• Some slides have been kept in here for
historical information - do not
necessarily use them all in
presentations
• For most of the methods presented, the
source material can be genomic DNA,
PCR amplified DNA, RNA converted into
cDNA, etc.
• I have attempted to include the source
of all materials - apologies when this is
not done or done incorrectly
15
3. Review Papers
16
Mardis ER. Next-generation sequencing platforms.
Annu Rev Anal Chem 2013;6:287-303.
doi: 10.1146/annurev-anchem-062012-092628.
Next-Generation DNA
Sequencing Methods
Elaine R. Mardis
Departments of Genetics and Molecular Microbiology and Genome Sequencing Center,
Washington University School of Medicine, St. Louis MO 63108; email: emardis@wustl.edu
Annu. Rev. Genomics Hum. Genet. 2008.
9:387–402
First published online as a Review in Advance on
June 24, 2008
The Annual Review of Genomics and Human Genetics
is online at genom.annualreviews.org
This article’s doi:
10.1146/annurev.genom.9.081307.164359
Copyright c⃝ 2008 by Annual Reviews.
All rights reserved
1527-8204/08/0922-0387$20.00
Key Words
massively parallel sequencing, sequencing-by-synthesis, resequencing
Abstract
Recent scientific discoveries that resulted from the application of next-
generation DNA sequencing technologies highlight the striking impact
of these massively parallel platforms on genetics. These new meth-
ods have expanded previously focused readouts from a variety of DNA
preparation protocols to a genome-wide scale and have fine-tuned their
resolution to single base precision. The sequencing of RNA also has
transitioned and now includes full-length cDNA analyses, serial analysis
of gene expression (SAGE)-based methods, and noncoding RNA dis-
Click here for quick links to
Annual Reviews content online,
including:
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FurtherANNUAL
REVIEWS
Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromarjournals.annualreviews.org
byUniversidadNacionalAutonomadeMexicoon11/17/09.Forpersonaluseonly.
Annu. Rev. Genomics Hum. Genet. 2008.
9:387–402
First published online as a Review in Advance on
June 24, 2008
The Annual Review of Genomics and Human Geneti
is online at genom.annualreviews.org
This article’s doi:
10.1146/annurev.genom.9.081307.164359
Copyright c⃝ 2008 by Annual Reviews.
All rights reserved
1527-8204/08/0922-0387$20.00
Annu.Rev.Genom.HumanGenet.2008.9:3
byUniversidadNacionalAutonoma• Open Access Review Papers
• http://www.microbialinformaticsj.com/content/2/1/3/
• http://www.hindawi.com/journals/bmri/2012/251364/abs/
• http://m.cancerpreventionresearch.aacrjournals.org/content/
5/7/887.full
4. 17
Approaching to NGS
Discovery of DNA structure
(Cold Spring Harb. Symp. Quant. Biol. 1953;18:123-31)
1953
Sanger sequencing method by F. Sanger
(PNAS ,1977, 74: 560-564)
1977
PCR by K. Mullis
(Cold Spring Harb Symp Quant Biol. 1986;51 Pt 1:263-73)
1983
Development of pyrosequencing
(Anal. Biochem., 1993, 208: 171-175; Science ,1998, 281: 363-365)
1993
1980
1990
2000
2010
Single molecule emulsion PCR 1998
Human Genome Project
(Nature , 2001, 409: 860–92; Science, 2001, 291: 1304–1351)
Founded 454 Life Science 2000
454 GS20 sequencer
(First NGS sequencer)
2005
Founded Solexa 1998
Solexa Genome Analyzer
(First short-read NGS sequencer)
2006
GS FLX sequencer
(NGS with 400-500 bp read lenght)
2008
Hi-Seq2000
(200Gbp per Flow Cell)
2010
Illumina acquires Solexa
(Illumina enters the NGS business)
2006
ABI SOLiD
(Short-read sequencer based upon ligation)
2007
Roche acquires 454 Life Sciences
(Roche enters the NGS business)
2007
NGS Human Genome sequencing
(First Human Genome sequencing based upon NGS technology)
2008
Miseq
Roche Jr
Ion Torrent
PacBio
Oxford
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
Sequencing Technology Timeline
28. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
29. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
30. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
31. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
32. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
33. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
34. Gen 2: Automated Sanger
28
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
35. Automation of Sanger Part I
29
Sanger method with labeled dNTPs
The Sanger mehtods is based on the idea that inhibitors can
terminate elongation of DNA at specific points
36. Many Systems for Sanger Automation
30
Thanks to Robin Coope and Dale Yazuki for comments on 2014 talk
ABI 3700 ABI 3730 ABI 3730xl
Megabase 1000 Megabase 4000 LiCor
38. Some Automated Sanger Highlights
• 1991: ESTs by Venter
• 1995: H. influenzae shotgun genome
• 1996: Yeast, archaeal genomes
• 1998: 1st animal genome - C. elegans
• 1999: Drosophila shotgun genome
• 2000: Arabidopsis genome
• 2000: Human genome
• 2004: Shotgun metagenomics
32
Thanks to Keith Bradnam for C. elegans suggestion
39. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
40. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
41. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
42. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
43. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
454-
Roche
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
44. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
454-
Roche
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
45. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Solexa-
Illumina
454-
Roche
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
46. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
Solexa-
Illumina
454-
Roche
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
47. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
48. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
49. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
50. Gen 3: Clusters not Clones (NextGen)
33
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
53. NextGen Sequencing Outline
36
Next-generation sequencing platforms
Isolation and purification of
target DNA
Sample preparation
Library validation
Cluster generation
on solid-phase
Emulsion PCR
Sequencing by synthesis
with 3’-blocked reversible
terminators
Pyrosequencing Sequencing by ligation
Single colour imaging
Sequencing by synthesis
with 3’-unblocked reversible
terminators
AmplificationSequencingImaging
Four colour imaging
Data analysis
Roche 454Illumina GAII ABi SOLiD Helicos HeliScope
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
57. 454 -> Roche
• 1st “Next-generation” sequencing
system to become commercially
available, in 2004
• Uses pyrosequencing
• Polymerase incorporates nucleotide
• Pyrophosphate released
• Eventually light from luciferase released
• Three main steps in 454 method
• Library prep
• Emulsion PCR
• Sequencing
40
58. 41
Roche 454 Wokflow
From http://acb.qfab.org/acb/ws09/presentations/Day1_DMiller.pdf
http://www.slideshare.net/AGRF_Ltd/ngs-technologies-platforms-and-applications
59. a
b
DNA library preparation
Emulsion PCR
A
A
A B
B
B
4.5 hours
8 hours
Ligation
Selection
(isolate AB
fragments
only)
•Genome fragmented
by nebulization
•No cloning; no colony
picking
•sstDNA library created
with adaptors
•A/B fragments selected
using avidin-biotin
purification
gDNA sstDNA library
gDNA
fragmented by
nebulization
or sonication
Fragments are end-
repaired and ligated to
adaptors containing
universal priming sites
Fragments are denatured and
AB ssDNA are selected by
avidin/biotin purification
(ssDNA library)
From Mardis 2008. Annual Rev. Genetics 9: 387.
Roche 454 Step 1: Libraries
42
60. Anneal sstDNA to an excess of
DNA capture beads
Emulsify beads and PCR
reagents in water-in-oil
microreactors
Clonal amplification occurs
inside microreactors
Break microreactors and
enrich for DNA-positive
beads
b
c
Emulsion PCR
Sequencing
A B
8 hours
7.5 hours
using avidin-biotin
purification
gDNA sstDNA library
sstDNA library Bead-amplified sstDNA library
Roche 454 Step 2: Emulsion PCR
From Mardis 2008. Annual Rev. Genetics 9: 387.
43
61. DNA capture beads reagents in water-in-oil
microreactors
inside microreactors enrich for DNA-positive
beads
Amplified sstDNA library beads Quality filtered bases
c
Sequencing
7.5 hours
sstDNA library Bead-amplified sstDNA library
•Well diameter: average of 44 µm
•400,000 reads obtained in parallel
•A single cloned amplified sstDNA
bead is deposited per well
390 Mardis
Roche 454 Step 3: Pyrosequencing
From Mardis 2008. Annual Rev. Genetics 9: 387.
44
62. Pyrosequencing
44 µm
Pyrosequecning
Reads are recorded as flowgrams
Annu. Rev. Genomics Hum. Genet., 2008, 9: 387-402
Nature Reviews genetics, 2010, 11: 31-46
Sanger
method
-
ABi SOLiD
HeliScope
Nanopore
Roche 454
Illumina GAII
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
Roche 454 Step 3: Pyrosequencing
45
63. Roche 454 Key Issues
• Number of repeated nucleotides
estimated by amount of light ... many
errors
• Reasonable number of failures in EM-
PCR and other steps
46
65. NextGen #2: Solexa
48
Sequecning by synthesis with reversible terminator
anger
ethod
he 454
SOLiD
iScope
nopore
-
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
66. NextGen #2: Solexa Illumina
Sequecning by synthesis with reversible terminator
anger
ethod
he 454
SOLiD
iScope
nopore
-
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
49
67. NextGen #2: Illumina Accessories
50
Cluster station
Genome Analyzer IIxPaired-end module Linux server
Bioanalyzer 2100
Instrumentation
mple
aration
sters
fication
ncing by
thesis
alysis
eline
duction
na GAII
igh
ughput
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
68. Illumina Outline
51
Clusters
amplification
Clusterstation
Wash cluster
station
Clustergeneration
Linearization,
Blocking and
primer
Hybridization
Read 1
Prepare read 2
Read 2
GAIIx&PE
SBSsequencing
Pipeline base call
Data analysis
Sample
preparation and
library validation
Analysis
Sequencing workflow
Sample
preparation
Clusters
amplification
Sequencing by
synthesis
Analysis
pipeline
Introduction
Illumina GAII
High
throughput
From Slideshare
presentation of
Cosentino Cristian
http://
www.slideshare.net/
cosentia/high-
throughput-equencing
69. Illumina Step 1: Prep & Attach DNA
52
termined by user-defined instrument settings,
which permits discrete read lengths of 25–35
the Illumina data from each run, removing
poor-quality sequences.
Adapter
DNA fragment
Dense lawn
of primers
Adapter
Attached
DNA
Adapters
Prepare genomic DNA sample
Randomly fragment genomic DNA
and ligate adapters to both ends of
the fragments.
Attach DNA to surface
Bind single-stranded fragments
randomly to the inside surface
of the flow cell channels.
Nucleotides
a
From Mardis 2008. Annual Rev. Genetics 9: 387.
Step 1: Sample Preparation The DNA sample of interest is sheared to appropriate size (average ~800bp) using a compressed air device known as a
nebulizer. The ends of the DNA are polished, and two unique adapters are ligated to the fragments. Ligated fragments of the size range of 150-200bp
are isolated via gel extraction and amplified using limited cycles of PCR
70. Illumina Step 2: Clusters by Bridge PCR
53
Attached
Prepare genomic DNA sample
Randomly fragment genomic DNA
and ligate adapters to both ends of
the fragments.
Attach DNA to surface
Bind single-stranded fragments
randomly to the inside surface
of the flow cell channels.
Bridge amplification
Add unlabeled nucleotides
and enzyme to initiate solid-
phase bridge amplification.
Denature the double
stranded molecules
Nucleotides
Figure 2
The Illumina sequencing-by-synthesis approach. Cluster strands created by bridge amplification are primed and all four fluorescently
labeled, 3′-OH blocked nucleotides are added to the flow cell with DNA polymerase. The cluster strands are extended by one
nucleotide. Following the incorporation step, the unused nucleotides and DNA polymerase molecules are washed away, a scan buffer is
added to the flow cell, and the optics system scans each lane of the flow cell by imaging units called tiles. Once imaging is completed,
chemicals that effect cleavage of the fluorescent labels and the 3′-OH blocking groups are added to the flow cell, which prepares the
cluster strands for another round of fluorescent nucleotide incorporation.
392 Mardis
• From : http://seqanswers.com/forums/showthread.php?t=21. Steps 2-6: Cluster Generation by Bridge Amplification. In contrast to the 454 and ABI
methods which use a bead-based emulsion PCR to generate "polonies", Illumina utilizes a unique "bridged" amplification reaction that occurs on
the surface of the flow cell. The flow cell surface is coated with single stranded oligonucleotides that correspond to the sequences of the adapters
ligated during the sample preparation stage. Single-stranded, adapter-ligated fragments are bound to the surface of the flow cell exposed to
reagents for polyermase-based extension. Priming occurs as the free/distal end of a ligated fragment "bridges" to a complementary oligo on the
surface. Repeated denaturation and extension results in localized amplification of single molecules in millions of unique locations across the flow
cell surface. This process occurs in what is referred to as Illumina's "cluster station", an automated flow cell processor.
From Mardis 2008. Annual Rev. Genetics 9: 387.
72. 55
25–35 bp, and each sequencing run yields be-
tween 2–4 Gb of DNA sequence data. Once
generation read type has a unique error model
different from that already established for
b
Laser
First chemistry cycle:
determine first base
To initiate the first
sequencing cycle, add
all four labeled reversible
terminators, primers, and
DNA polymerase enzyme
to the flow cell.
Image of first chemistry cycle
After laser excitation, capture the image
of emitted fluorescence from each
cluster on the flow cell. Record the
identity of the first base for each cluster.
Sequence read over multiple chemistry cycles
Repeat cycles of sequencing to determine the sequence
Before initiating the
next chemistry cycle
The blocked 3' terminus
and the fluorophore
from each incorporated
base are removed.
GCTGA...
From Mardis 2008. Annual Rev. Genetics 9: 387.
Illumina Step 3: Sequencing by Synthesis
From : http://seqanswers.com/forums/showthread.php?t=21. Steps 7-12: Sequencing by Synthesis. A flow cell containing millions of unique clusters
is now loaded into the 1G sequencer for automated cycles of extension and imaging. The first cycle of sequencing consists first of the incorporation
of a single fluorescent nucleotide, followed by high resolution imaging of the entire flow cell. These images represent the data collected for the first
base. Any signal above background identifies the physical location of a cluster (or polony), and the fluorescent emission identifies which of the four
bases was incorporated at that position. This cycle is repeated, one base at a time, generating a series of images each representing a single base
extension at a specific cluster. Base calls are derived with an algorithm that identifies the emission color over time. At this time reports of useful
Illumina reads range from 26-50 bases.
74. 57
Laser
terminators, primers, and
DNA polymerase enzyme
to the flow cell.
Image of first chemistry cycle
After laser excitation, capture the image
of emitted fluorescence from each
cluster on the flow cell. Record the
identity of the first base for each cluster.
Sequence read over multiple chemistry cycles
Repeat cycles of sequencing to determine the sequence
of bases in a given fragment a single base at a time.
Before initiating the
next chemistry cycle
The blocked 3' terminus
and the fluorophore
from each incorporated
base are removed.
GCTGA...
Figure 2
(Continued )
www.annualreviews.org • Next-Generation DNA Sequencing Methods 393
From Mardis 2008. Annual Rev. Genetics 9: 387.
Illumina Step 3: Cycling
79. NextGen #3: 454: ABI Solid
62
Sequecning by ligation
Sanger
method
Roche 454
-
HeliScope
Nanopore
ABi SOLiD
Illumina GAII
From Slideshare
presentation of
Cosentino Cristian
http://
www.slideshare.net/
cosentia/high-
throughput-equencing
80. ABI Solid Details
63
3-GG09-20 ARI 25 July 2008 14:57
A C G T
1stbase
2nd base
A
C
G
T
3'TAnnnzzz5'
3'TCnnnzzz5'
3'TGnnnzzz5'
3'TTnnnzzz5'
Cleavage site
Di base probesSOLiD™ substrate
3'
TA
AT
Universal seq primer (n)
3'
P1 adapter Template sequence
POH
Universal seq primer (n–1)
Ligase
Phosphatase
+
1. Prime and ligate
2. Image
4. Cleave off fluor
5. Repeat steps 1–4 to extend sequence
3'
Universal seq primer (n–1)
1. Melt off extended
sequence
2. Primer reset3'
AA AC G
G GG
C C
C
T AA
A GG
CC
T TTT
6. Primer reset
7. Repeat steps 1–5 with new primer
8. Repeat Reset with , n–2, n–3, n–4 primers
TA
AT
AT
3'
TA
AT
3'
Excite Fluorescence
Cleavage agent
P
HO
TA
AA AG AC AAAT
TT TC TG TT AC
TG
CG
GC
3'
3. Cap unextended strands
3'
PO4
1 2 3 4 5 6 7 ... (n cycles)Ligation cycle
3'
3'1 μm
bead
1 μm
bead
1 μm
bead
–1
Universal seq primer (n)
3'
1
Primer round 1
Template
Primer round 2 1 base shift
Glass slide
3'5' Template sequence
1 μm
bead P1 adapter
Read position 35343332313029282726252423222120191817161514131211109876543210
a
The ligase-mediated sequencing approach of the
Applied Biosystems SOLiD sequencer. In a manner
similar to Roche/454 emulsion PCR amplification, DNA
fragments for SOLiD sequencing are amplified on the
surfaces of 1-μm magnetic beads to provide sufficient
signal during the sequencing reactions, and are then
deposited onto a flow cell slide. Ligase-mediated
sequencing begins by annealing a primer to the shared
adapter sequences on each amplified fragment, and
then DNA ligase is provided along with specific
fluorescent- labeled 8mers, whose 4th and 5th bases
are encoded by the attached fluorescent group. Each
ligation step is followed by fluorescence detection, after
which a regeneration step removes bases from the
ligated 8mer (including the fluorescent group) and
concomitantly prepares the extended primer for another
round of ligation. (b) Principles of two-base encoding.
Because each fluorescent group on a ligated 8mer
identifies a two-base combination, the resulting
sequence reads can be screened for base-calling
errors versus true polymorphisms versus single base
deletions by aligning the individual reads to a known
high-quality reference sequence.
From Mardis 2008. Annual Rev.
Genetics 9: 387.
82. Complete Genomics
65
REVIEW
ased the number of false positive gene
ely reduced the number gene candidates
sitosterolemia phenotype were determined after comparison of
the patient’s genome to a collection of reference genomes.
Ultimately, it was determined that the patient failed the standard
omplete Genomics’ DNB array generation and cPAL technology. (A) Design of sequencing fragments, subsequent DNB
f the patterned nanoarray used to localize DNBs illustrate the DNB array formation. (B) Illustration of sequencing with a set
onding to 5 bases from the distinct adapter site. Both standard and extended anchor schemes are shown. Reprinted with
pyright XXXX American Association for the Advancement of Science.
gure 3. Schematic of Complete Genomics’ DNB array generation and cPAL technology. (A) Design of sequencing fragments, subsequent DN
nthesis, and dimensions of the patterned nanoarray used to localize DNBs illustrate the DNB array formation. (B) Illustration of sequencing with a
common probes corresponding to 5 bases from the distinct adapter site. Both standard and extended anchor schemes are shown. Reprinted w
Figure 3. Schematic of Complete
Genomics’ DNB array generation and
cPAL technology. (A) Design of sequencing
fragments, subsequent DNB synthesis, and
dimensions of the patterned nanoarray
used to localize DNBs illustrate the DNB
array formation. (B) Illustration of
sequencing with a set of common probes
corresponding to 5 bases from the distinct
adapter site. Both standard and extended
anchor schemes are shown.
From Niedringhaus et al. Analytical Chemistry 83: 4327. 2011.
83. Comparison in 2008
66
Roche (454) Illumina SOLiD
Chemistry Pyrosequencing Polymerase-based Ligation-based
Amplification Emulsion PCR Bridge Amp Emulsion PCR
Paired ends/sep Yes/3kb Yes/200 bp Yes/3 kb
Mb/run 100 Mb 1300 Mb 3000 Mb
Time/run 7 h 4 days 5 days
Read length 250 bp 32-40 bp 35 bp
Cost per run
(total)
$8439 $8950 $17447
Cost per Mb $84.39 $5.97 $5.81
From “Introduction to Next Generation Sequencing” by Stefan Bekiranov prometheus.cshl.org/twiki/pub/Main/CdAtA08/
CSHL_nextgen.ppt 66
84. Comparison in 2012
67
Roche (454) Illumina SOLiD
Chemistry Pyrosequencing Polymerase-based Ligation-based
Amplification Emulsion PCR Bridge Amp Emulsion PCR
Paired ends/sep Yes/3kb Yes/200 bp Yes/3 kb
Mb/run 100 Mb 1300 Mb 3000 Mb
Time/run 7 h 4 days 5 days
Read length 250 bp 32-40 bp 35 bp
Cost per run
(total)
$8439 $8950 $17447
Cost per Mb $84.39 $5.97 $5.81
From “Introduction to Next Generation Sequencing” by Stefan Bekiranov prometheus.cshl.org/twiki/pub/Main/CdAtA08/
CSHL_nextgen.ppt 67
94. Small Amounts of DNA
77
http://www.epibio.com/docs/default-source/protocols/nextera-dna-sample-prep-kit-(illumina--compatible).pdf?sfvrsn=4
95. Capture Methods
78
High throughput sample preparation
Sample
preparation
Clusters
amplification
Sequencing by
synthesis
Analysis
pipeline
Introduction
Illumina GAII
High
throughput
Nature Methods, 2010, 7: 111-118
RainDance
Microdroplet PCR
Roche Nimblegen
Salid-phase capture with custom-
designed oligonucleotide microarray
Reported 84% of
capture efficiency
Reported 65-90% of capture efficiency
From Slideshare presentation of Cosentino Cristian
http://www.slideshare.net/cosentia/high-throughput-equencing
96. 79
High throughput sample preparation
Sample
preparation
Clusters
amplification
Sequencing by
synthesis
Analysis
pipeline
Introduction
Illumina GAII
High
throughput
Agilent SureSelect
Solution-phase capture with
streptavidin-coated magnetic beads
Reported 60-80% of capture efficiency
From Slideshare presentation of
Cosentino Cristian
http://www.slideshare.net/cosentia/
high-throughput-equencing
Capture Methods
97. Illumina Paired Ends
80
Paired-end technology
Paired-end sequencing works into GA and uses chemicals from the PE
module to perform cluster amplification of the reverse strandSample
preparation
Clusters
amplification
Sequencing by
synthesis
Analysis
pipeline
Introduction
Illumina GAII
High
throughput
From Slideshare
presentation of Cosentino
Cristian
http://www.slideshare.net/
cosentia/high-throughput-
equencing
112. HiC Crosslinking & Sequencing
Beitel CW, Froenicke L, Lang JM, Korf IF, Michelmore
RW, Eisen JA, Darling AE. (2014) Strain- and plasmid-
level deconvolution of a synthetic metagenome by
sequencing proximity ligation products. PeerJ 2:e415
http://dx.doi.org/10.7717/peerj.415
Table 1 Species alignment fractions. The number of reads aligning to each replicon present in the
synthetic microbial community are shown before and after filtering, along with the percent of total
constituted by each species. The GC content (“GC”) and restriction site counts (“#R.S.”) of each replicon,
species, and strain are shown. Bur1: B. thailandensis chromosome 1. Bur2: B. thailandensis chromosome
2. Lac0: L. brevis chromosome, Lac1: L. brevis plasmid 1, Lac2: L. brevis plasmid 2, Ped: P. pentosaceus,
K12: E. coli K12 DH10B, BL21: E. coli BL21. An expanded version of this table can be found in Table S2.
Sequence Alignment % of Total Filtered % of aligned Length GC #R.S.
Lac0 10,603,204 26.17% 10,269,562 96.85% 2,291,220 0.462 629
Lac1 145,718 0.36% 145,478 99.84% 13,413 0.386 3
Lac2 691,723 1.71% 665,825 96.26% 35,595 0.385 16
Lac 11,440,645 28.23% 11,080,865 96.86% 2,340,228 0.46 648
Ped 2,084,595 5.14% 2,022,870 97.04% 1,832,387 0.373 863
BL21 12,882,177 31.79% 2,676,458 20.78% 4,558,953 0.508 508
K12 9,693,726 23.92% 1,218,281 12.57% 4,686,137 0.507 568
E. coli 22,575,903 55.71% 3,894,739 17.25% 9,245,090 0.51 1076
Bur1 1,886,054 4.65% 1,797,745 95.32% 2,914,771 0.68 144
Bur2 2,536,569 6.26% 2,464,534 97.16% 3,809,201 0.672 225
Bur 4,422,623 10.91% 4,262,279 96.37% 6,723,972 0.68 369
Figure 1 Hi-C insert distribution. The distribution of genomic distances between Hi-C read pairs is
shown for read pairs mapping to each chromosome. For each read pair the minimum path length on
the circular chromosome was calculated and read pairs separated by less than 1000 bp were discarded.
The 2.5 Mb range was divided into 100 bins of equal size and the number of read pairs in each bin
was recorded for each chromosome. Bin values for each chromosome were normalized to sum to 1 and
plotted.
E. coli K12 genome were distributed in a similar manner as previously reported (Fig. 1;
(Lieberman-Aiden et al., 2009)). We observed a minor depletion of alignments spanning
the linearization point of the E. coli K12 assembly (e.g., near coordinates 0 and 4686137)
due to edge eVects induced by BWA treating the sequence as a linear chromosome rather
than circular.
10.7717/peerj.415 9/19
Figure 2 Metagenomic Hi-C associations. The log-scaled, normalized number of Hi-C read pairs
associating each genomic replicon in the synthetic community is shown as a heat map (see color scale,
blue to yellow: low to high normalized, log scaled association rates). Bur1: B. thailandensis chromosome
1. Bur2: B. thailandensis chromosome 2. Lac0: L. brevis chromosome, Lac1: L. brevis plasmid 1, Lac2:
L. brevis plasmid 2, Ped: P. pentosaceus, K12: E. coli K12 DH10B, BL21: E. coli BL21.
reference assemblies of the members of our synthetic microbial community with the same
alignment parameters as were used in the top ranked clustering (described above). We first
Figure 3 Contigs associated by Hi-C reads. A graph is drawn with nodes depicting contigs and edges
depicting associations between contigs as indicated by aligned Hi-C read pairs, with the count thereof
depicted by the weight of edges. Nodes are colored to reflect the species to which they belong (see legend)
with node size reflecting contig size. Contigs below 5 kb and edges with weights less than 5 were excluded.
Contig associations were normalized for variation in contig size.
typically represent the reads and variant sites as a variant graph wherein variant sites are
represented as nodes, and sequence reads define edges between variant sites observed in
the same read (or read pair). We reasoned that variant graphs constructed from Hi-C
data would have much greater connectivity (where connectivity is defined as the mean
path length between randomly sampled variant positions) than graphs constructed from
mate-pair sequencing data, simply because Hi-C inserts span megabase distances. Such
Figure 4 Hi-C contact maps for replicons of Lactobacillus brevis. Contact maps show the number of
Hi-C read pairs associating each region of the L. brevis genome. The L. brevis chromosome (Lac0, (A),
Chris Beitel
@datscimed
Aaron Darling
@koadman
115. Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
116. Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
117. Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
118. Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
Gen 4:
Single
Molecule
119. Helicos
Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
Gen 4:
Single
Molecule
120. Pacbio
Helicos
Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
Gen 4:
Single
Molecule
121. Oxford
NanoPore
Pacbio
Helicos
Gen 4: Single Molecule
86
Gen 0:
Proto
Sequencing
Sanger
Maxam-Gilbert
ABI-
Solid
Solexa-
Illumina
454-
Roche
Ion
Torrent
Gen 1:
Manual
Sequencing
Gen 2:
Automated
Sanger
Gen 3:
Clusters
Not
Clones
Gen 4:
Single
Molecule
122. 87
Single Molecule I: Helicos
3rd
Generation Sequencing
y
w for
cular
ent_sequencing
124. 89
Single Molecule II: Pacific Biosciences
Mardis ER. Next-generation sequencing platforms. Annu Rev Anal Chem 2013;6:287-303.
125. 90
Analytical Chemistry REVIEW
Φ29 polymerase. Each amplified product of a circularized
fragment is called a DNA nanoball (DNB). DNBs are selectively
attached to a hexamethyldisilizane (HMDS) coated silicon chip
that is photolithographically patterned with aminosilane active
sites. Figure 3A illustrates the DNB array design.
The use of the DNBs coupled with the highly patterned array
offers several advantages. The production of DNBs increases
signal intensity by simply increasing the number of hybridization
sites available for probing. Also, the size of the DNB is on the
same length scale as the active site or “sticky” spot patterned on
Each hybridization and ligation cycle is followed by fluorescent
imaging of the DNB spotted chip and subsequently regeneration
of the DNBs with a formamide solution. This cycle is repeated
until the entire combinatorial library of probes and anchors is
examined. This formula of the use of unchained reads and
regeneration of the sequencing fragment reduces reagent con-
sumption and eliminates potential accumulation errors that can
arise in other sequencing technologies that require close to
completion of each sequencing reaction.19,52,53
Complete Genomics showcased their DNB array and cPAL
Figure 2. Schematic of PacBio’s real-time single molecule sequencing. (A) The side view of a single ZMW nanostructure containing a single DNA
polymerase (Φ29) bound to the bottom glass surface. The ZMW and the confocal imaging system allow fluorescence detection only at the bottom
surface of each ZMW. (B) Representation of fluorescently labeled nucleotide substrate incorporation on to a sequencing template. The corresponding
temporal fluorescence detection with respect to each of the five incorporation steps is shown below. Reprinted with permission from ref 39. Copyright
2009 American Association for the Advancement of Science.
Figure 2. Schematic of PacBio’s real-time single molecule sequencing. (A) The side view of a single ZMW nanostructure containing
a single DNA polymerase (Φ29) bound to the bottom glass surface. The ZMW and the confocal imaging system allow fluorescence
detection only at the bottom surface of each ZMW. (B) Representation of fluorescently labeled nucleotide substrate incorporation
on to a sequencing template. The corresponding temporal fluorescence detection with respect to each of the five incorporation steps
is shown below.
From Niedringhaus et al. Analytical Chemistry 83: 4327. 2011.
Single Molecule II: Pacific Biosciences
126. Why Finish Genomes?
91
The Value of Finished Bacterial Genomes
Why Are Finished Genomes So Important?
When Sanger sequencing was the only available sequencing technique, it was expensive — but not unusual — to
improve genome drafts until they were good enough to be considered finished. With the availability of short-read
sequencing technologies, draft genomes became cheap and easy to produce, and the majority of researchers
skipped the more labor- and time-intensive task of finishing genomes, with the realization that critical data
may be missing (Figure 3). Finished genomes are crucial for understanding microbes and advancing the field of
microbiology3
because:
• Functional genomic studies demand a high-quality,
complete genome sequence as a starting point
• Comparative genomics is meaningful only in terms
of complete genome sequences
• Understanding genome organization provides
biological insights
• Microbial forensics requires at least one complete
reference genome sequence
• Finished genomes aid in microbial outbreak source
identification and phylogenetic analysis
• A complete genome is a permanent scientific
resource
Figure 3: History of drafted vs. finished genomes (adapted from ref. 2).
Microbial Genetics Using SMRT Sequencing
0
2000
4000
6000
8000
10000
12000
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Numberofgenomes
Drafted Bacterial Genomes
Finished Bacterial Genomes
128. HGAP Assembly from PacBio
93
PacBio assembly CDC assembly
Illumina assemblySanger validation
HGAP Assembler for PacBio Data
http://www.pacificbiosciences.com/pdf/
microbial_primer.pdf
129. Detecting Modified Bases
94
Page 2 www.pacb.com/basemod
processes.
The potential benefits of detecting base modification,
using SMRT sequencing, include:
Single-base resolution detection of a wide
two successive base incorporations, are altered by
the presence of a modified base in the DNA
template
3
. This is observable as an increased space
between fluorescence pulses, which is called the
interpulse duration (IPD), as shown in Figure 2.
Figure 2. Principle of detecting modified DNA bases during SMRT sequencing. The presence of the modified base in the DNA
template (top), shown here for 6-mA, results in a delayed incorporation of the corresponding T nucleotide, i.e. longer
interpulse duration (IPD), compared to a control DNA template lacking the modification (bottom).
3
http://www.pacificbiosciences.com/pdf/microbial_primer.pdf
130. Pink Berry Genomics
PB-PSB1
(Purple sulfur bacteria)
PB-SRB1
(Sulfate reducing bacteria)
(sulfate)
(sulfide)
Wilbanks, E.G. et al (2014). Environmental Microbiology
Lizzy Wilbanks
@lizzywilbanks
131. 99
This diagram shows a protein nanopore set in an electrically resistant membrane bilayer. An ionic current is passed through the
nanopore by setting a voltage across this membrane. If an analyte passes through the pore or near its aperture, this event creates
a characteristic disruption in current. By measuring that current it is possible to identify the molecule in question. For example, this
system can be used to distinguish the four standard DNA bases and G, A, T and C, and also modified bases. It can be used to
identify target proteins, small molecules, or to gain rich molecular information for example to distinguish the enantiomers of
ibuprofen or molecular binding dynamics.
From Oxford Nanopores Web Site
Single Molecule III: Oxford Nanopores
132. • Figure6. BiologicalnanoporeschemeemployedbyOxfordNanopore.
(A)SchematicofRHLproteinnanoporemutantdepictingthepositionsofthe cyclodextrin (at residue 135) and glutamines (at residue
139). (B) A detailed view of the β barrel of the mutant nanopore shows the locations of the arginines (at residue 113) and the
cysteines. (C) Exonuclease sequencing: A processive enzyme is attached to the top of the nanopore to cleave single nucleotides
from the target DNA strand and pass them through the nanopore. (D) A residual current-vs-time signal trace from an RHL
protein nanopore that shows a clear discrimination between single bases (dGMP, dTMP, dAMP, and dCMP). (E) Strand
sequencing: ssDNA is threaded through a protein nanopore and individual bases are identified, as the strand remains intact.
Panels A, B, and D reprinted with permission from ref 91. Copyright 2009 Nature Publishing Group. Panels C and E reprinted
with permission from Oxford Nanopore Technologies (Zoe McDougall).
100
nalytical Chemistry REVIEW
etected across a metal oxide-silicon layered structure. The translocated through a solid-state nanopore. In addition, sever
igure 6. Biological nanopore scheme employed by Oxford Nanopore. (A) Schematic of RHL protein nanopore mutant depicting the positions of t
yclodextrin (at residue 135) and glutamines (at residue 139). (B) A detailed view of the β barrel of the mutant nanopore shows the locations
he arginines (at residue 113) and the cysteines. (C) Exonuclease sequencing: A processive enzyme is attached to the top of the nanopore to cleave sing
ucleotides from the target DNA strand and pass them through the nanopore. (D) A residual current-vs-time signal trace from an RHL protein nanopo
hat shows a clear discrimination between single bases (dGMP, dTMP, dAMP, and dCMP). (E) Strand sequencing: ssDNA is threaded through
rotein nanopore and individual bases are identified, as the strand remains intact. Panels A, B, and D reprinted with permission from ref 91. Copyrig
009 Nature Publishing Group. Panels C and E reprinted with permission from Oxford Nanopore Technologies (Zoe McDougall).
Figure6. Biological nanopores cheme employed by Oxford Nanopore.(A) Schematic of RHL protein nano pore mutant depicting the positions of the cyclodextrin (at residue
135) and glutamines (at residue 139). (B) A detailed view of the β barrel of the mutant nanopore shows the locations of the arginines (at residue 113) and the cysteines. (C)
Exonuclease sequencing: A processive enzyme is attached to the top of the nanopore to cleave single nucleotides from the target DNA strand and pass them through the
nanopore. (D) A residual current-vs-time signal trace from an RHL protein nanopore that shows a clear discrimination between single bases (dGMP, dTMP, dAMP, and
dCMP). (E) Strand sequencing: ssDNA is threaded through a protein nanopore and individual bases are identified, as the strand remains intact. Panels A, B, and D reprinted
with permission from ref 91. Copyright 2009 Nature Publishing Group. Panels C and E reprinted with permission from Oxford Nanopore Technologies (Zoe McDougall).
Single Molecule III: Oxford Nanopores
From Niedringhaus et al. Analytical Chemistry 83: 4327. 2011.
133. 101
Analytical Chemistry REVIEW
would result, in theory, in detectably altered current flow through
the pore. Theoretically, nanopores could also be designed to
measure tunneling current across the pore as bases, each with a
distinct tunneling potential, could be read. The nanopore ap-
lipid bilayer, using ionic current blockage method. The autho
predicted that single nucleotides could be discriminated as lon
as: (1) each nucleotide produces a unique signal signature; (2
the nanopore possesses proper aperture geometry to accomm
Figure 5. Nanopore DNA sequencing using electronic measurements and optical readout as detection methods. (A) In electronic nanopore scheme
signal is obtained through ionic current,73
tunneling current,78
and voltage difference79
measurements. Each method must produce a characteristic sign
to differentiate the four DNA bases. Reprinted with permission from ref 83. Copyright 2008 Annual Reviews. (B) In the optical readout nanopore desig
each nucleotide is converted to a preset oligonucleotide sequence and hybridized with labeled markers that are detected during translocation of the DN
fragment through the nanopore. Reprinted from ref 82. Copyright 2010 American Chemical Society.
Nanopore DNA sequencing using electronic measurements and optical readout as detection methods.(A)In electronic nanopore schemes, signal is obtained
through ionic current,73 tunneling current, and voltage difference measurements. Each method must produce a characteristic signal to differentiate the four
DNA bases. (B) In the optical readout nanopore design, each nucleotide is converted to a preset oligonucleotide sequence and hybridized with labeled
markers that are detected during translocation of the DNA fragment through the nanopore.
Single Molecule III: Oxford Nanopores
From Niedringhaus et al. Analytical Chemistry 83: 4327. 2011.
134. 102
Oxford Nanopores MinIon
“It’s kind of a cute device,” says Jaffe of the MinION, which is roughly the size and shape of a packet of chewing
gum. “It has pretty lights and a fan that hums pleasantly, and plugs into a USB drive.” But his technical review is
mixed. From http://www.nature.com/news/data-from-pocket-sized-genome-sequencer-unveiled-1.14724
136. Yet, Must Accept They Are Not a Myth
104
Pics Provided by Nick Loman
137. Yet, Must Accept They Are Not a Myth
104
Pics Provided by Nick Loman
138. minION prep (via Nick Loman)
105
End-repair (15mins) dA-tailing (15mins)
Fragment (2mins) Clean up (5mins)
Clean up (5mins)
Ligation (10mins) Tether annealing (10mins)
HP motor incubation (30mins)
Total: 92 minutes
Slide Provided by Nick Loman