NEXTflex™ qRNA-Seq™ Molecular Indexing for ChIP-Seq and RNA-Seq

Most Next Generation Sequencing (NGS) library prep methods introduce sequence bias with the use of enzyme processing and fragmentation steps can introduce errors in the form of incorrect sequence and misrepresented copy number. With molecular indexed libraries, each molecule is tagged with a molecular index randomly chosen from ~10,000 combinations so that any two identical molecules become distinguishable (with odds of 10,000/1), and can be independently evaluated in later data analysis. Analysis using molecular indexing provides an absolute, digital measurement of gene expression levels, irrespective of common amplification distortions observed in many RNA-Seq experiments. At high sequencing depths, each molecule can be distinguished and the entire library can be analyzed to provide absolute numbers of each molecule. This type of indexing requires no additional steps in RNA-Seq workflow and increases the precision of downstream analysis. Resolving individual clones of molecules is critical for increasing sequencing accuracy, measuring bias, PCR duplication rates and identifying mutations in complex sample types. Toward achieving that goal, we propose the use of molecular indices for all RNA-Seq experiments. We used Arabidopsis thaliana to test the NEXTflex™ qRNA-Seq™ kit as a novel tool for high-throughput gene expression analysis. We tied the characterized late flowering phenotype of the nf-yc3, 4, 9 triple mutant to absolute gene expression levels of known players in the photoperiodic flowering pathway in this mutant background. Results: The central regulator of the photoperiodic flowering hub, FLOWERING LOCUS T exhibited much higher gene expression levels in WT plants than in nf-yc triple mutant plants. Consequently, downstream targets, LEAFY and APETALA 1 showed reduce gene expression levels in nf-yc triple mutant plants resulting in a delayed floral response. Conclusion: Gene expression profiles produced by the NEXTflex™ qRNA-Seq™ system rival the sensitivity of qRT-PCR and microarray expression analysis methods without losing the capability to analyze traditional RNA-Seq data.