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Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue.


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.

SUBMITTER: Huuki-Myers LA 

PROVIDER: S-EPMC10578035 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue.

Huuki-Myers Louise A LA   Montgomery Kelsey D KD   Kwon Sang Ho SH   Page Stephanie C SC   Hicks Stephanie C SC   Maynard Kristen R KR   Collado-Torres Leonardo L  

Genome biology 20231016 1


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-mo  ...[more]

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