Let's talk about NGS, baby (part 1)

This week has turned into a busy one. With the J.P. Morgan Healthcare Conference in the Bay Area, there have been a number of announcements from local companies about funding, acquisitions and everyone reviewing what's hot (and what's decidedly not). With all this activity has come interviews and meetings for me, with recruiters and hiring managers reaching out to see if I'm interested in exploring potential fits with their organizations. The thing many have been looking at is my understanding of Next Generation Sequencing (NGS) technologies, given that this arena is decidedly in the "hot" category for product expansion.

Full disclosure: I don't consider myself an NGS expert (though I'm hoping to change this very soon). To date, I've only done one Illumina library prep and missed out on doing the sequence analysis and alignment due to moving across the country and naively believing the bioinformatics staff that the training was straight-forward (turns out it is . . . when you work with someone who is actually interested in training instead of acting like a superior snothead). All that said, one advantage I do have is I know how to present this information to an audience that isn't fluent with the jargon, walking them through what is and is not currently possible.

So the goal of these next few posts is to do just that, giving you a bit of history for context and even talking about what's coming down the pipe for diagnostics and care. Why this is important is because NGS technologies are rapidly moving into the patient care space, meaning that within your lifetime tests and screens for genetic conditions will become an option and fertility is at the top of the list. My hope is that I can at least give you a base-level of understanding; a jumping point so to speak.

For those interested, a more detailed history of DNA sequencing can be found here.

Let's begin.

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On April 25, 1953, Science Magazine published a one-page letter authored by James Watson and Francis Crick titled "Molecular Structure of Nucleic Acids: A structure for Deoxyribose Nucleic Acid." Regardless of your thoughts and feelings regarding how this work was completed, what is undisputed is that the publication of this article, followed a month later by this article published in Nature, marked an end of an era identifying and classifying the molecule responsible for hereditable information and ushered in a new era that lay the groundwork for modern molecular biology.

One immediate question was how does one "read" this molecular code within each molecule, putting together the correct combinations of A,G,T and C. What initially seems like a simple task actually proved to be quite difficult, resulting in slow and laborious work of generating some of the first DNA sequences that would often take years to complete. It would be until about 15-20 years after the structure of DNA was published that the first wave of DNA sequences technologies would online, with the development of the "chain-terminator" sequencing method, later adapted and developed to become "Sanger Sequencing," leading the charge and becoming the predominant method for DNA sequencing.

What set Sanger Sequencing apart for other sequencing technologies is it utilizes a single separation method combined and interpreting the results is pretty easy. Advances in the technique, such as moving to fluorescent dyes and a capillary system as well as the development of a fully automated DNA sequencer helped advance the technology, reducing costs to the method. Despite this, there were some serious limitations to this method, both in time, cost and labor not to mention needing a lot of DNA to complete a single reaction. Though researchers now had the ability to read DNA, creating maps for whole genomes was taking years and insane amounts of money, never mind issues with coverage and poor quality sequences. All of this limiting the impact of many research endeavors.

In the mid-1980s, as the automated DNA sequencer was coming online, a new wave of DNA sequencing technologies was being developed that would overcome the limitations of Sanger sequencing. Using enzymes that would produce light as DNA was being copied, pyrosequencing had obvious advantages over Sanger sequencing, that major one being that DNA sequencing could be analyzed in real time. Despite a real limitation of distinguishing repeating (stretches of As, Cs, Gs, or Ts), pyrosequencing offered several advantages and would lead the charge for "next-generation sequencing," resulting in a number of different platforms that would dominate the market. Arguably the most important one being the Solexia method.

I'm not going to walk you through the finer points of the Solexia sequencing, as that information is readily available on the Illumina website. By what I will say is that when Illumina came on the scene, the fields of genetics and molecular biology evolved seemingly overnight. Whereas before, sequencing was an expensive process where you only did the reactions as the last step to confirm tool generation or as part of an experiment, suddenly sequencing became part of the experiment. Genetics departments became Genomics departments and scientists were finally able to ask questions on a vastly larger scale. As Illumina developed its technology, and competing companies like PacBio (SMRT sequencing), Oxford Nanopore, ThermoFisher (Ion Torrent) as well as companies like10x Genomics and Twist Biosciences came on the scene, the cost of sequencing dropped from thousands of dollars to pennies, the amount of DNA needed to do a sequencing reaction dropped drastically, the quality of reads vastly improved and coverage hit levels previously never seen. And what use to take years was being accomplished in weeks (if not days) and instead of one single genome for reference, thousands of genomes were being made available to researchers. The sky was no longer the limit.

What all of this has meant for biomedical science is that DNA sequencing was no longer limited to the research space. Sometime in the early 2010s, I began hearing the words "precision medicine" at more and more talks, the idea being that a patient's genomic information could be incorporated into healthcare decisions, offering a more personalized care plan. Precision medicine is already being practiced for diseases like cancer, but there's been a push to expand into areas where the diseases have been more complex, such as mental health, diabetes, rare diseases, dietary issues and, of course, fertility.

But like any rapid advance in technology, the rest of the word is still catching up, leading to misunderstandings both from the general public and even healthcare workers what is and is not possible. And with that knowledge comes a realization that a patient's ability to advocate requires them not only to have a based-understanding of what can and is being done but also knowing enough about the process so they can recognize false-promises, sample collection errors (which happen way too often) and navigate seemingly scary results.

To be continued.....