NIPT Thesis (Chapter 2)

Translation of the second chapter of the book Non-Invasive Prenatal Genetic Testing (NIPT) (subtitle: Application of Genomics to Prenatal Testing and Diagnosis) edited by Lieve Paage-Christianens and Hans-Georg Klein (Academic Press, 2018) (Hiro Clinic NIPT tentative translation)

Chapter 2 Understanding the basics of “next-generation sequencing” within the framework of NIPT

Dale Musey, University of South San Francisco

Introduction: Evolution of sequencing technology

The term “next-generation sequencing” (NGS) raises questions such as what was “first-generation sequencing” and how is NGS similar to and different from first-generation sequencing. Sanger pioneered the development of first-generation DNA sequencing in the 1970s (References 1, 2). The sequencing method for which he became famous involved the successful extension of unextendable DNA bases in vitro using a cell growth machine. These modified bases were then added at low concentrations in a reaction that involved minimal interaction with certain components: (1) a high concentration of the extendable bases, (2) the single-stranded DNA to be sequenced, (3) a short oligonucleotide primer that is complementary to the DNA template (where new bases may be synthesized), and (4) a DNA polymerase enzyme that directs the extension reaction. In Sanger’s early sequencing experiments, these four reactions occurred independently, each containing a single non-extendable base (A, T, G, or C). Whenever the polymerase randomly synthesizes one of the non-extendable bases into the nascent DNA molecule (e.g., a non-extendable G synthesizes with a C on the DNA template opposite), it will attempt to terminate synthesis, regenerating a neckless template. Crucially, because all nascent strands are anchored and propagated from the same oligonucleotide primer, the termination point, and therefore the length of the nascent DNA strand, are direct proxies for the base at the 3′ end of the molecule. Using electrophoretic gels to analyze the lengths of terminated molecules in each of the four reactions, it is possible to infer the sequence of the entire template.

Sanger sequencing became slightly more scalable with the introduction of a uniquely pigmented non-extendable base (Fig. 1). Rather than partitioning the four reactions to obtain base-specific information, capillary electrophoresis combined with a fluorescent pigment detector allowed analysis of both the relative sizes of DNA fragments and the identity of the bases where extension had stopped (Refs. 3-5). To criticize these instruments for their inability to measure is to overlook one of their most significant achievements: they were the very instruments that drove the early human genome sequence in the 1990s (Refs. 6-9). However, given the billions of dollars of costs and time required, genome sequencing is likely to remain largely unusable in clinical practice unless a major technological breakthrough occurs.
Next-generation sequencing (NGS) has overcome many of the technical limitations of Sanger and revolutionized genome sequencing (Ref. 10), yet the most popular NGS methodologies share many of their predecessors. As we will discuss in more detail below, next-generation sequencing also exploits extension termination and fluorescent bases, but relies on the ability of DNA polymerase to attach a single base to a nascent DNA molecule at a time. Indeed, next-generation sequencing experiments are in many ways like running millions or even billions of Sanger-style reactions in parallel (hence the nickname “massively parallel sequencing”).

The role of next-generation sequencing

Next-generation sequencing machines are responsible for distilling specially created libraries of DNA molecules into sequences in long text files, each with a single line for each sequenced molecule. The mapping of molecules to text files with next-generation sequencers has been deployed across a wide range of research and clinical applications, from RNA sequencing using broccoli (Reference 11), to ribosomal profiling (deep sequencing of mRNA fragments with ribosomes attached; Reference 12), to DNA sequencing for NIPT testing in pregnant women (Reference 13). These applications of next-generation sequencing are largely categorized by the type of technique used to inject the upstream DNA into the sequencer, known as “library preparation.” The diversity of upstream preparations leads to a broad comparative analysis of downstream examples, one of which is the analytical technique used in NIPT, which will be discussed in detail in Chapter 3. In this chapter, in addition to explaining how each piece of equipment used in next-generation sequencing sequences DNA, we will also look at what sequencing businesses exist from upstream to downstream, focusing on NIPT.

Upstream sequencer

DNA extraction

cfDNA, as the name suggests, is not present in blood cells and must be extracted from plasma. cfDNA fragments are remnants of dead cells (Ref. 14). When a cell undergoes programmed death (known as apoptosis), a set of enzymes join together and digest genomic DNA (Ref. 15). These enzymes can only access DNA that is not confined to nucleosomes, which are made up of histone octamers that control gene expression and genome topology in cells (Ref. 17). The inaccessibility of nucleosomal DNA means that DNA fragments less than 150 nucleotides circulating within nucleosomes survive the apoptotic process, and that DNA fragments that escape from dying cells form cfDNA, which are sequenced and output what are called next-generation sequencing reads, which we will explain in more detail later. To extract cfDNA from plasma, blood must first be centrifuged to separate the plasma, buffy coat (containing the white blood cells), and red blood cells. Approximately 55% of whole blood is plasma. When removing plasma from the centrifuge, it is important to carefully remove the buffy coat. This is because too much maternal DNA in the white blood cells will dilute the rare cfDNA from the placenta, reducing or eliminating the sensitivity of detecting fetal aneuploidies.

Standard commercial DNA extraction techniques can be used to purify plasma samples to obtain sufficient cfDNA for analysis (18, 19). Plasma typically contains only 5–50 ng of concentrated cfDNA per ml, but this low amount of cfDNA in plasma is noteworthy because it has been used to establish the minimum blood volume required for cfDNA-based prenatal testing. If the blood volume is too small to extract sufficient DNA, the extracted sample will contain a low number of genome copies, which may prevent detection of small changes in fetal gene dosage. For example, a 2% change in the dosage of gene 21 is unlikely to be detected if the extracted sample contains 10 genome copies. Conversely, with an efficient extraction method, even low amounts of fetal genome fragments can be used to extract enough genome equivalents to detect fetal chromosomal abnormalities. The number of genome equivalents to be extracted in a DNA extraction depends on the subsequent NIPT test. For whole chromosome sequencing (WGS), the amount of cfDNA required from any given portion of blood is very small, so a very low amount of blood can be drawn from the patient (Reference 13). This allows multiple attempts to extract DNA from a single blood sample. In contrast, prominent techniques such as single nucleotide polymorphism (SNP) require hundreds of genome equivalents per specific region, which allows the balance of alleles to be measured with high precision (WGS and SNPs are discussed in detail in Chapter 3) (Reference 20). For this reason, the amount of blood required for NPIT testing for SNPs is usually larger than for WGS. Since the concentration of cfDNA is very low, it is not trivial to measure whether enough cfDNA has been extracted to perform NIPT.

The amount of DNA extracted can usually be increased by performing PCR(?) before next-generation sequencing. In other words, even if the extraction is inefficient, it is possible to produce a large amount of DNA for sequencing. This means that inefficient extraction does not reflect the depth of next-generation sequencing. Fortunately, the “complexity” of the sequenced data can be used to determine whether the extraction is inefficient. For example, in the case of WGS, efficient extraction results in DNA fragments with zero or one (usually zero) sequence on the genome. This is because the sequence is a Poisson sample from a source pool that is rich in genomic information integrated material (Reference 21). However, in addition to the inefficient extraction, if the source pool of genomic information integrated material is thin, DNA fragments will be placed on chromosomes with a probability of zero or less than one, resulting in low complexity data. Conversely, if the extraction is extremely efficient, PCR may not be needed to produce enough DNA for sequencing. These “PCR-free” library preparations are likely to result in high library complexity, and it will be important to monitor the complexity of the next generation sequencing data to ensure that fetal aneuploidy data are statistically significant.

Library preparation

NGS (Next Generation Sequencing) Machine

in conclusion

NGS (next-generation sequencing) is particularly well-suited for NIPT applications for two subtle but obvious reasons, and some less obvious. The obvious reason is that NGS provides digital, nucleotide-level data that enables depth- and allele-based NIPT workflows. The NIPT workflow requires locating and measuring cfDNA fragments (discussed in more detail in Chapter 3). Crucially, NGS instruments can generate such data quickly and easily, helping NIPT address laboratory, test-taker, and patient constraints. The more subtle reason is that NGS captures signals that are relevant to cfDNA derived from the placenta. For example, NGS, which measures fragment lengths, measures fragment lengths that are generally shorter in the placenta than in the maternal tissue. Fetal fragments are also characterized by DNA methylation, which can be detected by subsequent NGS after bisulfite treatment (Ref. 36: Methylated c bases remain unchanged, but unmethylated c bases are converted to uracil in bisulfite (similar in sequence to thymine). Finally, NGS identifies and reports the location of the ends of cfDNA fragments at single nucleotide determinations, and this end information contains important placental signals because the positions of maternal and placental nucleosomes are structurally different when determining the ends of cfDNA fragments (Ref. 37). Analytical algorithms that extract and amplify these placental signals can be used to sensitively detect fetal chromosomal abnormalities. cfDNA-based NIPT tests are now rapidly becoming a routine part of prenatal clinical diagnostics, mainly due to the maturation of NGS as a means of reading and enumerating cfDNA. The widespread adoption of NIPT in clinical practice will stimulate technological developments to reduce costs and generate large data sets that will lead to the discovery of more nuanced, placenta-specific signals. Thus, the quantification and theorization of cfDNA will continue to develop steadily and rapidly, and such improvements will improve the results of cfDNA-based NIPT and make it more widely available.