How Next Generation Sequencing Is Revolutionizing Genomic Research

Since 2005, NGS (Next-generation sequencing) has replaced the Sanger sequencing method as the dominant approach for DNA sequencing. In a little more than one decade, NGS has managed to catalyze the growth of genomics research across the globe. NGS has allowed researchers to explore the lesser-known domains of genomics that were earlier impossible to study due to technical restrictions.

How has NGS benefited genomics studies in the current scenario?

Today, scores of NGS platforms aide researchers and medical professionals. Almost all of them share one technological feature – they enable the parallel sequencing of clonally amplified DNA molecules, or single DNA molecules separated spatially in a flow cell. It allows the high-throughput sequencing (HTS) and analyses of the unknown microbe and eukaryotic genomes. Another shared feature is the generation of massive volumes of data. A single run can generate almost hundreds of megabases worth nucleotide sequences.

The first NGS platform became commercially available to the researchers a little over a decade ago. The commercial availability of HTS platforms opened the door to personalized medicine, precision medicine, and molecular diagnostics. Information on DNA seq analysis is now easy to come by on the web. They have paved the way for several new techniques that can become beneficial for human health and disease control in the near future.

Why does NGS data require a robust analytics platform?

NGS generates a tremendous volume of data. It presents challenges in storage, sorting, management, sharing, and analysis. The bulk of data can range between 15GB to 15 TB depending on the platform. That demands a resource-intensive pipeline for the management and processing of the data. The larger read lengths of NGS data makes the alignment and assembly more challenging than the alignment of Sanger data.

Today, research groups require dedicated software and enough computational power to minimize the errors in the NGS data analyses. The vast amount of information on DNA seq analysis has enabled them to choose the right techniques of NGS data analysis. Some software and tools require only a 64-bit OS with a 16 MB RAM. While others might require a 64-bit Linux OS with 4 GB RAM. Depending on the volume of NGS data, hardware settings, and software compatibility, the typical NGS analysis can from a couple of minutes to hours.

The quality of the NGS data analysis software and its usability will determine the results of a study significantly. The easy-to-access information on DNA seq analysis makes the selection process much more straightforward than before.

How is NGS revolutionizing the future of genomics?

Here’s a glimpse of how the future of genomics is going to look like with a little help from NGS –

A sneak peek at the molecular stethoscope

One of the primary applications of cfDNA was in the field of non-invasive prenatal testing (NIPT). It allows the detection of prenatal DNA from the cfDNA (fetal DNA) in the maternal blood.

It can detect cancer in the earliest possible stages and monitor the progress of the therapy. cfDNA detection and investigation can help in the detection of pathogens in infectious diseases, and transplant monitoring in adults as well.

Linking genotype with phenotype

Today, EMRs contain tons of medical information on the patient. However, this information is only available to the patient’s GP and other specialists. At the same time, global projects like The Cancer Genome Atlas (TCGA) and the 1000 Genomes Project have created humongous databases of information on DNA seq analysis.

There is no communication between the varying phenotype and genome variations. The evolution of high-throughput DNA sequencing can help establish the much-needed link between the genotype and phenotype contained in two or more databases.

Point-of-care testing and treatment for the patients

The advances in sequencing and analysis technology have made it possible to automate the workflows, shorten the turn-around time, and almost eliminate the instrument footprint. Genomic technologies are becoming decentralized.

Information on DNA seq analysis is in the transition from the central reference labs to community labs in hospitals, diagnostics departments, and other healthcare facilities. The physicians (point-of-care) will soon be able to access their patient’s genomic analysis with an exclusive focus on hereditary conditions, genetic abnormalities, and predisposition to certain diseases. It will improve the detection and diagnosis of diseases at the point-of-care.

Clinical trials: Innovation of basket studies

Evolving NGS techniques allow the researchers to know more about the genetic diversity within the population. Targeted therapies have better impacts on the population containing specific biomarkers for certain diseases.

One of the earliest coordinated efforts includes the Lung Cancer Master Protocol. Finding drugs for the management of rare genetic disorders and the treatment of specific types of cancer, won’t be a challenge anymore.

NGS technology is on its way to revolutionizing personalized medicine and targeted therapy.

The scale-up of current genomic research

Researchers will soon have to account for continuously increasing numbers of genomic biomarkers. Their average recurrence will decrease as the sample space of the experiments increase.

To know more about the vast genomic differences in the large population one has to conduct fast, large-scale genomic studies. Today, genomics researchers consider NGS to be an indispensable tool in the large-scale study of genetic diversity.

TCGA and the 1000 Genome Project are moving into larger-scale studies with the aide of NGS.

So, how can NGS help you and your team?

Those were some of the prospects of the application of NGS. Here’s what NGS will be able to help with in the future –

The discovery of 3-dimensional structures of proteins.
Exploration of DNA-protein interactions.

Development of early detection of diseases based on genome-based strategies.

The development of new methods for large scale sequencing of DNA and the efficient storage of genomic data.
Find genetic variations among the population and determine their respective phenotype variations.
Determine genetic and epigenetic modifications in the human genome to understand their roles in pathogenesis.

NGS is a critical technology that has already fostered the development of new methods of diagnosis, prognosis, and treatment.