Next generation sequencing –
advancement in Pharmaceutical Research
Human genome sequencing project
completion is considered as a major milestone of genomic research and it had established
a new vision of advance therapeutics. It was mainly accomplished by conventional
approach “Sanger Sequencing” and it had taken rigorous efforts of lab workers
across the globe for a period of 12 years and cost approximately $3 billion.[1,2]
The main limitations of sanger sequencing method was high cost, low speed
and labor intensive nature. Due to these limitations, the sanger sequencing
process was lagging behind to fulfill ever increasing demands of large scale
population based projects of pharmaceutical/genomics research. This vacuum was successfully filled by next
generation sequencing methods as they are cost effective, less time consuming
and capable enough to read millions of DNA sequence in parallel. According to recent facts of National Human
Genome Research Institute an estimated cost for the human genome sequencing
project with NGS is ~$4211 which is a heavy reduction in cost as compare to
first human genome sequenced, and it is became possible due to the rapid
improvement in next generation sequencing methods. [3]
Now
a days NGS has moved forward from the conventional laboratory practices to
applied research, and has been proven as essential tool for ongoing
pharmaceutical research. It is capable enough to address general and
specialized genomic question of mutagenesis, changes in gene expression
behavior, gene regulatory mechanisms for genome wide population based studies of
communicable [4-11] and non-communicable [12-20] diseases.
Its high accuracy, greater depth and wider coverage enable clinician to prepare
a molecular landscape of disease initiation, progression and establishment
along with the therapeutic impact of drug candidate at gene expression level.
NGS provides wide range of assays to serve specific needs of projects and
classified into whole genome sequencing, target sequencing, RNA-Seq, Exome-Seq
and ChIP-Seq. Each category designed for a specific purpose for example whole
genome sequencing generates a complete genomic portfolio of individual whereas
target sequencing or Exome-Seq provides information for a subset of genome
region. RNA-Seq provides quantification value of gene expression and changes in
the gene expression under a disease condition or a drug exposure. On other hand, ChIP-Seq provides gene
regulatory mechanism involved in the change of gene expression due to
occurrence of disease or drug treatment.
In
conclusion, I would say “Deployment of various NGS methods at different
molecular level for large scale patient’s population will provide much wider
and deeper molecular understanding for systemic progression of a disease or
drug response”. Read more Incedo bioinformatics analytic offerings.
References
1. Human Genome Project Archive 1990 – 2003(http://web.ornl.gov/sci/techresources/Human_Genome/project/budget.shtml)
4. Lecuit M, Eloit M. The
diagnosis of infectious diseases by whole genome next generation sequencing: a
new era is opening. Frontiers
in Cellular and Infection Microbiology. 2014;4:25.
doi:10.3389/fcimb.2014.00025.
5. Snitkin, E. S. et al. Tracking a hospital
outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome
sequencing. Sci. Transl. Med. 4, 148ra116 (2012).
6. He, M. et al. Emergence and
global spread of epidemic healthcare-associated Clostridium
difficile. Nature Genet. 45, 109–113 (2013).
7. Mellmann, A. et al. Prospective genomic
characterization of the German enterohemorrhagicEscherichia coli O104:H4 outbreak by
rapid next generation sequencing technology. PLoS ONE 6, e22751 (2011).
8. Rohde, H. et al. Open-source genomic
analysis of Shiga-toxin-producing E. coli O104:H4. N. Engl J. Med. 365, 718–724 (2011).
9. Reuter, S. et al. A pilot study of
rapid whole-genome sequencing for the investigation of a Legionella outbreak. BMJ Open 3, e002175 (2013).
10. Prosperi, M. et al. Molecular
epidemiology of community-associated methicillin-resistant Staphylococcus
aureus in the genomic era: a cross-sectional study. Sci. Rep. 3, 1902(2013).
11. Gardy, J. L. et al. Whole-genome
sequencing and social-network analysis of a tuberculosis outbreak. N. Engl.
J. Med. 364, 730–739 (2011).
12. Lisa H. et
al. Performance
characteristics of next-generation sequencing in clinical mutation detection of
colorectal cancers. Modern Pathology , (31 July 2015) |
doi:10.1038/modpathol.2015.86
13. Wong E.S.Y. et al. Predictive Factors for BRCA1 and BRCA2 Genetic
Testing in an Asian Clinic-Based Population. PLoS ONE 10(7): e0134408 (2015).
doi:10.1371/journal.pone.0134408
14. Meldrum C. et al. . Next-Generation Sequencing for
Cancer Diagnostics: a Practical Perspective. The
Clinical Biochemist Reviews. 2011;32(4):177-195.
15. Gerlinger, M. et al., Intratumor heterogeneity
and branched evolution revealed by multiregion sequencing. N. Engl. J. Med.,
2012, 366(10), 883–892.
16. Banerji, S. et al., Sequence analysis of
mutations and translocations across breast cancer subtypes. Nature, 2012,
486(7403), 405–409.
17. Cancer Genome Atlas Research, Comprehensive
genomic characterization of squamous cell lung cancers. Nature, 2012,
489(7417), 519–525.
18. Ding, L. et al., Clonal evolution in relapsed
acute myeloid leukaemia revealed by whole-genome sequencing. Nature, 2012, 481(7382),
506–510.
19. Seshagiri, S. et al., Recurrent R-spondin
fusions in colon cancer. Nature, 2012, 488(7413), 660–664.
20. Agrawal, N. et al., Exome sequencing of head
and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1.
Science, 2011, 333(6046), 1154–1157.
