Sequencing trends in early 2017

Every month, ~5,000 unique queries for sequencing are submitted using Genohub’s NGS project matching engine: https://genohub.com/ngs/. Briefly, a user chooses the NGS application they are interested in (e.g. exome, RNA-Seq), the number of reads or coverage they’d like to achieve and the number of samples they plan on sequencing. Genohub’s matching engine, takes this input calculates the sequencing output required to meet the desired coverage and recommends services, filterable by sequencing instrument, read length, and library preparation kit. Results can be sorted by price, turnaround time and selected for immediate ordering.

Every query that’s submitted is recorded giving us a unique perspective into what types of NGS services researchers are actually interested in.

DNA-Seq

First, it’s important to note that DNA-seq is our default option in the matching engine: https://genohub.com/ngs/. Due to this bias, you can’t really compare it to other services being ordered so it’s a good idea to just throw away this data point. Of DNA-seq services that are actually ordered, this breaks down into: whole human genome sequencing, re-sequencing, and metagenomics sequencing. The most frequently used instruments for this service are currently the HiSeq X, HiSeq 3000/4000 and NextSeq. With PacBio’s release of the Sequel, requests have significantly increased this quarter compared to PacBio service requests in the last 4 quarters. We expect this trend to continue through 2017.

RNA-Seq

The pie chart above breaks down the types of RNA-seq services requested in the first three months of 2017. Total RNA-seq represents all applications where rRNA is depleted prior to library preparation, whereas mRNA-seq represents all applications where mRNA is enriched. In 2016, the number of Total RNA-seq projects was half that of this year. We attribute this to a growing interest in non-coding RNA and the availability of higher throughput sequencing runs. As sequencing costs drop and rRNA depletion becomes more affordable, researchers are asking for more biological information.  Today, the Nextseq and HiSeq 3000/4000 are the most commonly used instruments for any RNA-seq application. Counting applications continue to dominate, although requests for de novo transcriptome alignments are steady rising over the previous year. Whereas in the past, 1×50 and 1×75 were the most frequently requested read length for RNA counting applications, around 2x more researchers are requesting paired-end sequencing versus last year.

Methylation analysis

Compared to last year, there is an increased interest in WGBS as compared to RRBS and MeDIP. With the advent of the HiSeq X and it’s compatibility with WGBS applications, more researchers are finding whole genome based applications easier and more informative than reduced representation bisulfite sequencing.

Instrument trends

By far the biggest trend this year was the number of long read requests on the PacBio Sequel. Whereas in the past, Mate-pair library prep was more popular, we’re starting to see this service decline, and long read sequencing be ordered more frequently. Hybrid Ilumina/PacBio reads are also being more frequently ordered to improve the quality of assemblies. Long-reads are being requested to detect functional elements in human genomes that are missed by short-read sequencing. We should add that requests for 10X Genomics services have started to increase, although they are too small right now to make any meaningful comments. We currently don’t have providers offering Oxford Nanopore services on Genohub, so can’t comment here either.

This month NovaSeq services are expected to be available on Genohub. We expect there to be a lag phase as kinks are worked out, before this becomes a popular instrument request.

The future

Having spent the last 4 years receiving sequencing requests and performing consultation, it’s clear that new technology does influence behavior. With reduced sequencing costs, we see clients not only including more control and duplicates, but also looking at RNA-seq from a more global perspective, and beginning to become more interested in long reads. Clients that previously only performed exome-seq are now turning to whole genome sequencing on the HiSeq X. Researchers that normally only look at coding RNA’s are starting to show interest in long non-coding and small RNAs. Overall, faster and cheaper sequencing does tend to promote better science. Gone are the n=1 days of sequencing.