Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types
Louise A Huuki-Myers1, Kelsey D Montgomery1, Sang Ho Kwon1,2
1Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Abstract:
We define and identify a new class of control genes for next-generation sequencing called total RNA expression genes (TREGs), which correlate with total RNA abundance in cell types of different sizes and transcriptional activity. We provide a data-driven method to identify TREGs from single-cell RNA sequencing data, allowing the estimation of total amount of RNA when restricted to quantifying a limited number of genes. We demonstrate our method in postmortem human brain using multiplex single-molecule fluorescent in situ hybridization and compare candidate TREGs against classic housekeeping genes. We identify AKT3 as a top TREG across five brain regions.
