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Journal Article•DOI•

Sequencing technologies-the next generation

Michael L. Metzker1•
Baylor College of Medicine1
01 Jan 2010-Nature Reviews Genetics (Nature Publishing Group)-Vol. 11, Iss: 1, pp 31-46
TL;DR: A technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments is presented.
Abstract: Demand has never been greater for revolutionary technologies that deliver fast, inexpensive and accurate genome information. This challenge has catalysed the development of next-generation sequencing (NGS) technologies. The inexpensive production of large volumes of sequence data is the primary advantage over conventional methods. Here, I present a technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments. I also outline the broad range of applications for NGS technologies, in addition to providing guidelines for platform selection to address biological questions of interest.

Summary (1 min read)

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Summary

  • DNA sequencing is one of the most important platforms for study in biological systems today.
  • The high-throughput-next generation sequencing technologies delivers fast, inexpensive, and accurate genome information.
  • Next generation sequencing can produce over 100 times more data than methods based on Sanger Sequencing.
  • The next generation sequencing technologies offered from Illumina / Solexa, ABI/SOLiD, 454/Roche, and Helicos has provided unprecedented opportunity for high-throughput functional genomic research.
  • Next generation sequence technologies offer novel and rapid ways for genome-wide characterization and profiling of mRNA's, transcription factor regions, and DNA patterns.

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ABSTRACT
Conclusion and Future Work
Next Generation Sequencing
CONTACT INFO
Data Analysis Comparisons
Downstream Analysis
REFERENCES
DNA sequencing is one of the most important platforms for
study in biological systems today. The high-throughput-next
generation sequencing technologies delivers fast,
inexpensive, and accurate genome information. Next
generation sequencing can produce over 100 times more data
than methods based on Sanger Sequencing. The next
generation sequencing technologies offered from Illumina /
Solexa, ABI/SOLiD, 454/Roche, and Helicos has provided
unprecedented opportunity for high–throughput functional
genomic research. Next generation sequence technologies
offer novel and rapid ways for genome-wide characterization
and profiling of mRNA’s, transcription factor regions, and DNA
patterns.
Fig. 7) This is a plot of the frequency of each percentage covered for all nodes.
BLAST is in blue, MUMmer is in green.
Sequencing Technologies – the Next Generation,
Micahel L. Metzkerh
Next Generation Sequencing Pipeline Development and Data Analysis
Fig. 9) This is a plot of the coverage of each Node. BLAST points are blue,
MUMmer points are red.
Fig. 6) This is a plot of the frequency of each percentage covered for all contigs.
BLAST is in blue, MUMmer is in green.
•  454/Roche – 454 Life Sciences is a Biotechnology company
that is a part of Roche and based in Branford, Connecticut.
The center develops ultra-fast high-throughput DNA
sequencing methods and tools.
•  Illumina/Solexa– Illumina is a company that develops and
manufactures integrated systems for the analysis of gene
variation. Solexa was founded to develop genome
sequencing technology.
•  ABI/SOLiD - (Sequencing by Oligonucleotide Ligation and
Detection) is a next-generation DNA sequencing technology
developed by Life Technologies and has been commercially
available since 2006. This next generation technology
generates hundreds of millions to billions of small sequence
reads at one time.
•  Helicos - Helicos's technology images the extension of
individual DNA molecules using a defined primer and
individual fluorescently labeled nucleotides, which contain a
"virtual terminator" preventing incorporation of multiple
nucleotides per cycle.
Julian Pierre
1
, Jordan Taylor
2
, Amit Upadhyay
3
, Bhanu Rekepalli
3
Fig. 8) This is a plot of the coverage of each Contig. BLAST points are blue,
MUMmer points are red.
Using the coverage of
each individual contig
ID, the results for both
BLAST and MUMmer
were plotted. While
BLAST hit more contigs,
there are more contigs
with a higher coverage
that were hit by
MUMmer.
Using the data gathered
from both BLAST and
MUMmer, the frequency
of the amount covered
for each contig was
plotted. From Fig 6), it
can be inferred that
MUMmer hit more
accurately for contigs.
Fig 4) from main.g2.bx.psu.edu
Once the results were found using both the BLAST and
MUMmer search tools, we created a program to see which
sequencing tool had the most hits per contig. The total
number of contigs in the database file is 160,749 and the
total number of nodes in the query file is 552,305. BLAST
returned a total of 123,070 hits and MUMmer returned a
total of 121,829 hits. From the results, MUMmer hit more
accurately than BLAST while BLAST hit more contigs than
MUMmer.
In Next-Generation Sequencing, data analysis is one of the
most expensive processes. While the cost of genome
sequencing goes down, the cost of analyzing data is still
expensive. In the future, the “$1,000 genome will come with
a $20,000 analysis price tag.”
The same process was
done with the Nodes.
From Fig 7), it can be
inferred that BLAST hit
more accurately with
nodes. However, there
are more BLAST results
with lower coverage.
The future of next generation sequencing can be broken
down into a variety of categories such as personalized
medicine, bio fuels, climate change, and other life science
fields.
•  Personalized Medicine is a medical model that proposes
the customization of medical decision to tailor an
individual
•  Bio Fuels present a source of alternative energy.
Microalgal biofuels use algae to synthesize the fuel. In
order to optimize the process, an understanding of the
gene-function relationship of algae would prove helpful.
•  Climate change is the active study of past and future
theoretical models which uses the past climate data to
make future projections.
In conclusion, we hope to contribute the knowledge we
have gained to contribute to fields such as these.
The same process was
done with the Nodes.
While BLAST hit more
Nodes, there are more
Nodes that hit with a
lower coverage using
BLAST.
1 Texas Southern University, 2 Austin Peay State University, 3 University of Tennessee
Next Gen Sequencing uses a wide array of tools to obtain results based
on the genome sequence. The most widely used Tools are BLAST,
HMMER, and MUMmer.
•  BLAST (Basic Local Alignment Search Tool) is a multi-sequence
alignment tool developed by NIH (National Institute of Health). It is
used find similar regions in different sequences and then compare
their similarities.
•  MUMmer (Maximum Unique Matches) is a rapid alignment system
used for rapidly aligning entire genomes. It can also align incomplete
genomes and can easily handle 1000’s of contigs from a shotgun
sequencing project.
•  HMMER (Hidden Markov Modeler) is used for searching sequence
databases for homologs of protein sequences, and for making protein
sequence alignments. It implements methods using probabilistic
models called profile hidden Markov models (HMMs)
Genome Assembly
Sequence Analysis refers to
the process of subjecting a
DNA, RNA or peptide
sequence to a wide range of
analytical methods to:
•  Compare sequences to find
similarities and infer if they
are Homologous
•  To identify the features of
the sequence such as gene
structure, distribution,
introns and exons, and
regulation of gene
expression
•  Identify Sequence
differences and variations
such as mutations
Fig. 1) This is figure shows three different Next Generation Sequencing methods. [2]
Fig. 2) Taken from A Hitchhiker’s Guide to Next-Generation Sequencing, by Gabe Rudy
Fig. 3) Taken from bio.davidson.edu/courses. Shows alignment results for yeast.
Fig 5) from jcvi.org shows the mapping of chr6 of a Human Genome
Julian Pierre – julz_pierre@yahoo.com
Jordan Taylor – jtaylor74@my.apsu.edu
Amit Upadhyay – aupadhy1@utk.edu
Bhanu Rekepalli – brekapal@utk.edu
•  http://www.roche.com/research_and_development/r_d_overview/
r_d_sites.htm?id=18
•  http://www.pnas.org/content/99/6/3712/F1.expansion.html
•  http://www.yerkes.emory.edu/nhp_genomics_core/Services/
Sequencing.html
•  http://www.illumina.com/technology/solexa_technology.ilmn
•  http://blast.ncbi.nlm.nih.gov/Blast.cgi
•  https://main.g2.bx.psu.edu/u/dan/p/fastq
•  http://ori.dhhs.gov/education/products/n_illinois_u/datamanagement/
datopic.htmll
•  http://www.jcvi.org/medicago/include/images/chr6.BamHI.maps.jpg
•  Gabe Rudy, (2010) A Hitchhiker’s Guide to Next-Generation
Sequencing, :1-9, Golden Helix
•  [1] John D. McPherson, (2009) Next-Generation Gap, 6:1-4, Nature
Methods Supplement
•  [2]Michael L. Metzker, (2010) Sequencing Technologies, - the next
generation, 11:1-5, Nature Reviews
•  Md. Fakruddin,Khanjada Shahnewaj Bin mannan, (2012) Next
Generation sequencing technologies – Principles and prospects,
6:1-9, Research and Reviews in Biosciences
•  Misra N., Panda P. K., Parida B. K., Mishra B. K., (2012)
Phylogenomic Study of Lipid Genes Involved in Mocroalgal Biofuel
Production – Candidate Gene Mining and Metabolic Pathway
Analyses, Evolutionary Bioinformatics 8:545-564, doi: 10.4137/
EBO.S10159
Galaxy is an open, web-based
platform for data intensive
biomedical research. It can be
used on its own free public
server where you can perform,
reproduce, and share complete
analyses.
An example of how Galaxy
reflects its data is shown in Fig 5.
Two FASTA files related to the same nucleotide sequence
were input into both BLAST and MUMmer and the results
were parsed into tables. Then, the coverage of all hit contigs
and nodes from both programs was found.
Citations
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Abstract: The assessment of biological samples is critical for measuring the ‘health’ of New Zealand aquatic environments. Analysis of these samples commonly requires species identification and enumeration, which usually involves microscopy or microbiological methods. These techniques can be time-consuming, laborious, and are dependent on taxonomic expertise. Recent advances in molecular methods provide promising tools for assessing environmental samples. A range of molecular techniques are now used in New Zealand including: fluorescent in situ hybridisation; automated ribosomal intergenic spacer analysis; quantitative polymerase chain reaction; and, most recently, next-generation sequencing. The organisms (or targets) and environments monitored are equally diverse, ranging from cyanobacteria, rotifers and invasive fish in lakes, to macroinvertebrates, and biofilm communities in rivers, to bacteria, micro- and macro-algae and invertebrates in marine ecosystems. Despite research and validation demonstrating their po...

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TL;DR: This report is the first documenting the effective use of an NGS technique to detect pathogenic mutations that underlie hearing loss in an East Asian population.
Abstract: Hereditary hearing loss is one of the most common heterogeneous disorders, and genetic variants that can cause hearing loss have been identified in over sixty genes. Most of these hearing loss genes have been detected using classical genetic methods, typically starting with linkage analysis in large families with hereditary hearing loss. However, these classical strategies are not well suited for mutation analysis in smaller families who have insufficient genetic information. Eighty known hearing loss genes were selected and simultaneously sequenced by targeted next-generation sequencing (NGS) in 8 Korean families with autosomal dominant non-syndromic sensorineural hearing loss. Five mutations in known hearing loss genes, including 1 nonsense and 4 missense mutations, were identified in 5 different genes (ACTG1, MYO1F, DIAPH1, POU4F3 and EYA4), and the genotypes for these mutations were consistent with the autosomal dominant inheritance pattern of hearing loss in each family. No mutational hot-spots were revealed in these Korean families. Targeted NGS allowed for the detection of pathogenic mutations in affected individuals who were not candidates for classical genetic studies. This report is the first documenting the effective use of an NGS technique to detect pathogenic mutations that underlie hearing loss in an East Asian population. Using this NGS technique to establish a database of common mutations in Korean patients with hearing loss and further data accumulation will contribute to the early diagnosis and fundamental therapies for hereditary hearing loss.

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Abstract: During the past three decades, we have witnessed remarkable advances in our understanding of the molecular etiologies of hereditary neurodegenerative diseases, which have been accomplished by 'positional cloning' strategies. The discoveries of the causative genes for hereditary neurodegenerative diseases accelerated not only the studies on the pathophysiologic mechanisms of diseases, but also the studies for the development of disease-modifying therapies. Genome-wide association studies (GWAS) based on the 'common disease-common variants hypothesis' are currently undertaken to elucidate disease-relevant alleles. Although GWAS have successfully revealed numerous susceptibility genes for neurodegenerative diseases, odds ratios associated with risk alleles are generally low and account for only a small proportion of estimated heritability. Recent studies have revealed that the effect sizes of the disease-relevant alleles that are identified based on comprehensive resequencing of large data sets of Parkinson disease are substantially larger than those identified by GWAS. These findings strongly argue for the role of the 'common disease-multiple rare variants hypothesis' in sporadic neurodegenerative diseases. Given the rapidly improving technologies of next-generation sequencing next-generation sequencing (NGS), we expect that NGS will eventually enable us to identify all the variants in an individual's personal genome, in particular, clinically relevant alleles. Beyond this, whole genome resequencing is expected to bring a paradigm shift in clinical practice, where clinical practice including diagnosis and decision-making for appropriate therapeutic procedures is based on the 'personal genome'. The personal genome era is expected to be realized in the near future, and society needs to prepare for this new era.

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