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Evaluation of ultra-low input RNA sequencing for the study of human T cell transcriptome.

ABSTRACT: Deeper understanding of T cell biology is crucial for the development of new therapeutics. Human naïve T cells have low RNA content and their numbers can be limiting; therefore we set out to determine the parameters for robust ultra-low input RNA sequencing. We performed transcriptome profiling at different cell inputs and compared three protocols: Switching Mechanism at 5' End of RNA Template technology (SMART) with two different library preparation methods (Nextera and Clontech), and AmpliSeq technology. As the cell input decreased the number of detected coding genes decreased with SMART, while stayed constant with AmpliSeq. However, SMART enables detection of non-coding genes, which is not feasible for AmpliSeq. The detection is dependent on gene abundance, but not transcript length. The consistency between technical replicates and cell inputs was comparable across methods above 1?K but highly variable at 100 cell input. Sensitivity of detection for differentially expressed genes decreased dramatically with decreased cell inputs in all protocols, support that additional approaches, such as pathway enrichment, are important for data interpretation at ultra-low input. Finally, T cell activation signature was detected at 1?K cell input and above in all protocols, with AmpliSeq showing better detection at 100 cells.

SUBMITTER: Wang J

PROVIDER: S-EPMC6559993 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Evaluation of ultra-low input RNA sequencing for the study of human T cell transcriptome.

Wang Jingya J Rieder Sadiye Amcaoglu SA Wu Jincheng J Hayes Susana S Halpin Rebecca A RA de Los Reyes Melissa M Shrestha Yashaswi Y Kolbeck Roland R Raja Rajiv R

Scientific reports 20190611 1

Deeper understanding of T cell biology is crucial for the development of new therapeutics. Human naïve T cells have low RNA content and their numbers can be limiting; therefore we set out to determine the parameters for robust ultra-low input RNA sequencing. We performed transcriptome profiling at different cell inputs and compared three protocols: Switching Mechanism at 5' End of RNA Template technology (SMART) with two different library preparation methods (Nextera and Clontech), and AmpliSeq ...[more]

PMID: 31186477

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Project description:BackgroundNext Generation Sequencing has proven to be an exceptionally powerful tool in the field of genomics and transcriptomics. With recent development it is nowadays possible to analyze ultra-low input sample material down to single cells. Nevertheless, investigating such sample material often limits the analysis to either the genome or transcriptome. We describe here a combined analysis of both types of nucleic acids from the same sample material.MethodsThe method described enables the combined preparation of amplified cDNA as well as amplified whole-genome DNA from an ultra-low input sample material derived from a sub-colony of in-vitro cultivated human embryonic stem cells. cDNA is prepared by the application of oligo-dT coupled magnetic beads for mRNA capture, first strand synthesis and 3'-tailing followed by PCR. Whole-genome amplified DNA is prepared by Phi29 mediated amplification. Illumina sequencing is applied to short fragment libraries prepared from the amplified samples.ResultsWe developed a protocol which enables the combined analysis of the genome as well as the transcriptome by Next Generation Sequencing from ultra-low input samples. The protocol was evaluated by sequencing sub-colony structures from human embryonic stem cells containing 150 to 200 cells. The method can be adapted to any available sequencing system.ConclusionsTo our knowledge, this is the first report where sub-colonies of human embryonic stem cells have been analyzed both at the genomic as well as transcriptome level. The method of this proof of concept study may find useful practical applications for cases where only a limited number of cells are available, e.g. for tissues samples from biopsies, tumor spheres, circulating tumor cells and cells from early embryonic development. The results we present demonstrate that a combined analysis of genomic DNA and messenger RNA from ultra-low input samples is feasible and can readily be applied to other cellular systems with limited material available.

Dataset Information

Evaluation of ultra-low input RNA sequencing for the study of human T cell transcriptome.

Publications

Evaluation of ultra-low input RNA sequencing for the study of human T cell transcriptome.

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