The era of fast, cheap genotyping is here

The evolution of short-read technologies and opportunities for genomic research: MGI Tech, a spin-off company from the Chinese genomics titan BGI Tech

The 1990 project helped scientists find genetic causes of cancer and other diseases and led to the development of at home DNA tests. Next, researchers began to sequence more genomes from other organisms. Ten years ago, it cost about $10,000 for researchers to sequence a human genome. It dropped to $1,000 a few years ago. Today, it’s about $600.

It has been a very successful approach. Almost all the world’s sequencing data was generated on Illumina machines, according to one estimate. Dozens of would-be competitors have emerged to challenge Illumina over the years, but most have fallen by the wayside — many of them memorialized in the ‘NGS Necropolis’ (see go.nature.com/3xwvmkt). The Functional Genomics Center in Switzerland has been successful because of technical expertise. She says that other companies were not very reliable when it came to library prep.

There’s an old saying in the field of technology: “Nobody ever got fired for buying IBM” — a reference to the company’s once-ubiquitous computers. It would be appropriate to replace IBM with illuminati, a company in San Diego, California.

Not every application can be mapped onto a short read technology. Many companies in the UK have worked to evolve their long read technologies as well.

Each of the four building blocks is coupled to a fluorescent colour and a chemical group that pauses further DNA synthesis. After the tag is removed and the cycle repeats, sensitive optics identify the nucleotide added from the resulting fluorescence. In a flow cell, millions or even billions of long reads are generated from huge numbers of targets at the same time.

Beyond human genome assembly and mutational analysis, new applications have fuelled demand for more and better short-read data at a lower cost. Everything from epigenetics to chromosomal conformation to proteomics, these are included. Half of her facility’s work now involves single-cell RNA-seq, a technique that profiles thousands or millions of individual cells. To fill that surge in demand, both start-ups and established companies have entered the ring.

One established player, MGI Tech, a Shenzhen-based spin-off company from the Chinese genomics titan BGI, offers distinctive twists on an Illumina-like SBS approach. The fluorescent signal is boosted using a biochemical process, and both Illumina and MGI use a lower-cost method that converts templates into strands. The data quality is really good and it can be much more cost-effective than Illumina according to an expert who has used the instruments in his own facility.

Both companies offer systems that are able to look at hundreds or even thousands of genes. For PacBio, this entails feeding strands of template DNA into polymerase enzymes that are tethered to a solid surface and then using sophisticated optics to detect the addition of individual labelled nucleotides as the DNA synthesis proceeds. The distinctive changes in electrical current that occur as DNA strands transit through tiny genes can be used to determine the sequence of nucleotides. Collectively, these systems provide insights that would be difficult or impossible to obtain with short-read systems, including large structural variations in chromosomal DNA, mRNA transcript structure and complete microbial genomes. Both systems can also directly identify and map epigenetic modifications.

The more natural synthesis process which results from this results in less time consuming and less expensive processes while also allowing for careful labelling step, both of which highlight the accuracy of their approaches. “We’ve been seeing extremely high-quality data,” says genomics researcher Christopher Mason at Weill Cornell Medicine in New York City, who has used Element’s AVITI system to profile the effects of space flight on human physiology.

Sequencers fall broadly into two categories: production-scale instruments including Illumina’s NovaSeq, and smaller benchtop instruments such as Illumina’s NextSeq. For now, only Illumina and MGI operate across the full spectrum; other short-read companies target specific levels of throughput.

When it comes to purchasing decisions, equipment and reagents are only part of the calculation, and publicly announced per-genome prices don’t account for labour, maintenance and other support costs. It is possible for labs to end up with instruments out of reach due to service contracts that cost 10% of an instrument’s base cost every year. While the performance of production-scale instruments is not as good as the ones on the benchtop, it is still more cost-effective compared to the ones on the benchtop. Pond says that many projects aren’t big enough or pilot-scale projects are hard to feed the beast. Multiple experiments can’t be run simultaneously in a single flow cell, which is an issue for labs.

Illumina has set a high bar, too, and quality is another important consideration. The new-generation chemistry of the XLEAP-BBS system improves this accuracy by three-fold and Illumina uses it for most reads. The Onso instrument is still in alpha testing, but Mason claims that his test has one error rate of one-in- 10,000 bases or lower. He says quality is better than Q40 at the start of the read. Mason thinks further optimization of the computational toolbox for analysing Onso-generated data could lead to even better performance.

Another consideration when choosing a sequencing platform is compatibility with existing workflows. For example, Element’s workflow is largely consistent with standard Illumina processes, whereas Ultima and MGI require extra processing steps that can introduce speed bumps into existing pipelines. “It’s not insurmountable — it just adds more time and labour,” says Mason. Further automation may be needed to streamline the process.

Even brief downtime can disrupt lab operations and be essential for stability and reliability. Illumina generally has an excellent reputation on this front, says Aquino. “Sometimes even before we know something is wrong, our engineer is there already,” she says. “It will take all these companies a few more years to build up the support system and this array of experience.”

ONT is a versatile and portable platform that can be used for more than one type of application. Researchers regularly use ONT systems in the field, and Mason has even sent them to the International Space Station. “We can see applications in many remote areas,” he says. ONT also offers the lowest-cost sequencing hardware on the market, including the $1,000 MinION, which can be run off of a standard laptop or, in newer versions, a tablet.