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

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...

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Detalles Bibliográficos
Autores principales: Huuki-Myers, Louise A., Montgomery, Kelsey D., Kwon, Sang Ho, Page, Stephanie C., Hicks, Stephanie C., Maynard, Kristen R., Collado-Torres, Leonardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10578035/
https://www.ncbi.nlm.nih.gov/pubmed/37845779
http://dx.doi.org/10.1186/s13059-023-03066-w
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03066-w.

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