Ultra-low input transcriptomics

Robust total transcriptome analysis from single cell level

Detect significant changes in gene-expression:

Gene-expression analysis becomes more informative when small populations are screened. Samples that contain multiple cell types show much variation, mostly reflecting the sample-composition. Selecting cell clusters that differ solely in those aspects that you want to study, are easier to interpret. It allows you to detect significant changes in gene-expression for low abundant transcripts. Discovery of biomarkers and transcription-factors has never been so easy.

The low-input transcriptomics method is specifically designed for input amounts down to 2 pg, generally the amount present in a single cell. This method is applicable for good quality RNA of challenging samples. Therefore, you can rely on uniform transcript coverage, regardless of input amount.

Unique Molecular Identifiers

GenomeScan’s low-input service minimizes the PCR duplication rate. Multiple measurements of the same molecule present the original sample are reduced, and PCR duplicates that do occur are filtered out.

How do we know that all reads arise from different transcripts? This method includes Unique Molecular Identifiers (UMI’s) which are ligated to the mRNA molecules early in the procedure to provide a unique tag. Duplicate reads can easily be filtered out during data-analysis, leading to clean and consistent data-sets.

We will accompany you every step of the way:

Sample specificationsnum1 01 1 Product page   Ultra low input transcriptomics
  • Starting from 2 pg RNA
  • Ideally deliver as much RNA as possible, to allow for QC and normalization
  • Minimally validated RNA input: 2 pg
  • For RNA quality of RIN / RQN ≥7.0
Deliverables2 01 Product page   Ultra low input transcriptomics
  • Sequencing of Total RNA (generally ~40% of total RNA is mRNA)
  • Quality score Q30 of ≥80% for PE 150 reads
  • Turn-around time: 3 weeks
Sequencing3 01 Product page   Ultra low input transcriptomics
  • Sequencing PE 150 on the NovaSeq 6000
  • Data required for Ultra-low input RNA-seq: generally 20 million reads
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The specifications of the data-set that you can expect are listed in your personal quotation.

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Generally, the sequencing quality score (Q score; ≥30 represents high quality) must be ≥80% for PE 150 reads (Illumina’s official guarantee ≥75%). Our average score of 2018 was
Q30 ≥ 90%.

We perform all RNA-seq experiments under ISO/IEC 17025 and ISO 15189.

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Data analysis5 01 Product page   Ultra low input transcriptomics
  • Count table: contains the expression levels (FPKM values) per gene
  • Differential gene-expression analysis
  • Extended data-analysis including PCA plot, heatmap, pathway analysis

We have summarized key information about our ultra-low input transcriptomics service into a product specification sheet, which you can download here.

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Discuss your project with Andre

We have over 15 years of experience in transcriptomics. Talk with us about best practices and how we can help your research.

Photo André rond 01 Product page   Ultra low input transcriptomics

Andre Wijfjes

Manager Customer Support

+31 71 568 1036