Scientific Poster
April 14, 2017

Optimization & Evaluation of SMART-Seq® v4 kit for Low Input RNA Sequencing

An improved strategy for expression profiling via RNA sequencing from limiting amounts of RNA
Inferring the gene expression status of patients’ tumors via analysis of the residual tumor material is often challenged by the small quantity of tumor cells or tissues available. Recent technological advances in cDNA synthesis, whole transcriptome amplification, and library construction make it possible to routinely analyze transcriptomes from picogram-level of input RNA.

At Q2 Solutions we are constantly looking for new ways to improve the methods we utilize in our lab.  We have recently modified the conventional SMART-seq® protocol to incorporate a library size selection procedure. 

This modification improved the ease in which the libraries could be normalized to equimolar fractions and thus to cluster much more predictable on the flow cell. This modification represents a methodological improvement of transcriptomic analysis from small quantities of total RNA. We also addressed concerns that the modified steps might introduce serious biases, invalidating the existing data analysis approaches. Compared to previous versions of the SMARTer method, the modified SMART-Seq v4 procedure implemented at Q2 Solutions significantly improved the percentage of reads aligned to the transcriptome, as well as the total number of genes detected, all while reducing technical variability. 

To learn more please download our poster from AACR 2017

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