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)

2.       http://www.genome.gov/10001772

3.       http://www.genome.gov/pages/der/sequencing_costs_apr2015.xlsx

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.