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Illumina NovaSeq 6000

Illumina sequencing platforms

Illumnia sequencing overview

The standard sequence of events for a run involves preparing a DNA library from sample input, attaching library DNA strands to a glass slide known as a flowcell, growing clusters from each DNA strand by bridge PCR and then performing the fluorescence based sequencing on either, the Illumina NovaSeq 6000 or Illumina MiSeq. The data is analysed in the standard Illumina pipeline to produce sequenced 50-300 bp fragments which can then be assembled de-novo or re-mapped to a given sequence depending on the application.

In summary: 

  • During library preparation dsDNA is fragmented to 200-600 bp, alternatively cDNA is synthesized from fragmented mRNA (either polyA or rRNA depleted)
  • Adaptors are ligated to the ends of the strands
  • Strands are attached to a flowcell and each strand is amplified several thousand times to form a cluster of identical sequences
  • A sequencing primer is annealed to the DNA strand
  • Complementary DNA is synthesized to 50 or 300 bp using reversibly blocked fluorescently labelled nucleotides
  • Nucleotide incorporation is imaged for each read and bases are called
  • For paired-end sequencing, the clusters are re-generated after the first read and sequenced from the complementary strand (this gives additional information since the distance between each end of the DNA fragment is known)


Illumina NovaSeq 6000

We use the Illumina NovaSeq 6000 to provide a versatile platform to support a wide variety of applications from bacterial and fungal pathogenomics to whole human genome sequencing.

The NovaSeq 6000 system provides a more scalable, cost effective architecture for sequencing compared to previous generations of short read sequencers. This is achieved using multiple flow cell types and read length combinations. The NovaSeq S Prime (SP), S1, and S2 flow cells provide quick and powerful sequencing for the majority of high-throughput applications. The NovaSeq S4 flow cell, the largest scaling available, enables the highest throughput of sequencing at the most cost-effective price for a range of applications, making in-house whole genome sequencing (WGS) or whole exome sequencing (WES) studies an attractive and affordable option for more projects.

Key features of the Illumina NovaSeq 6000:

  • Cheaper cost per base compared to other Illumina instruments
  • Faster sequencing runs
  • Multiple flow cell and read sizes for a more scalable approach
  • Largest S4 flow cell can sequence
    • ~ 24 - 30 whole human genomes at 30X coverage or
    • ~ 250 exomes at 100X coverage or
    • ~ 200 transcriptomes at 50M reads coverage

Flowcell output / scalability:


Number of Reads

650–800 M 1.3–1.6 B 3.3 B–4.1 B 8-10 B

2 x 50 bp Output

65-80 Gb* 134–167 Gb 333–417 Gb N/A ‡

2 x 100 bp Output

134-167 Gb 266–333 Gb 667–833 Gb 1600–2000 Gb

2 x 150 bp Output

200–250 Gb* 400–500 Gb 1000–1250 Gb 2400–3000 Gb

2 x 250 bp Output

325-400 Gb N/A N/A N/A

* denotes our most popular flowcell which we have instock. Others available on request

Typical applications:

  • De novo genome sequencing (small to large genomes)
  • Genome re-sequencing
  • Amplicon sequencing
  • RNA-seq transcriptome sequencing
  • Epigenetics such as ChIP-Seq, ATAC-Seq, Whole Genome Bisulphite Sequencing (WGBS)
  • Single cell sequencing



Illumina MiSeq

We utilize the Illumina MiSeq for smaller scale projects as well as testing pooled libraries prior to loading on the Illumina NovaSeq 6000. It is capable of automated paired-end reads and up to 15 Gb per run, delivering over 600 bases of sequence data per read.


MiSeq Reagent Kit v2

MiSeq Reagent Kit v3

MiSeq Reagent Kit v2 Micro

MiSeq Reagent Kit v2 Nano

Read Length

2 × 25 bp 2 × 150 bp 2 × 250 bp 2 × 75 bp 2 × 300 bp 2 × 150 bp 2 × 250 bp 2 × 150 bp

Number of Reads

12-15 million 22–25 million   4 million 1 million 


750–850 Mb 4.5–5.1 Gb 7.5–8.5 Gb 3.3–3.8 Gb 13.2–15 Gb 1.2 Gb 500 Mb 300 Mb


Typical applications:

  • Targeted gene sequencing
  • Small genomes
  • Amplicon sequencing
  • 16S metagenomics