A comparison of metabolic labeling and statistical methods to infer genome-wide dynamics of RNA turnover.
Brief Bioinform
; 22(6)2021 11 05.
Article
en En
| MEDLINE
| ID: mdl-34228787
ABSTRACT
Metabolic labeling of newly transcribed RNAs coupled with RNA-seq is being increasingly used for genome-wide analysis of RNA dynamics. Methods including standard biochemical enrichment and recent nucleotide conversion protocols each require special experimental and computational treatment. Despite their immediate relevance, these technologies have not yet been assessed and benchmarked, and no data are currently available to advance reproducible research and the development of better inference tools. Here, we present a systematic evaluation and comparison of four RNA labeling protocols 4sU-tagging biochemical enrichment, including spike-in RNA controls, SLAM-seq, TimeLapse-seq and TUC-seq. All protocols are evaluated based on practical considerations, conversion efficiency and wet lab requirements to handle hazardous substances. We also compute decay rate estimates and confidence intervals for each protocol using two alternative statistical frameworks, pulseR and GRAND-SLAM, for over 11 600 human genes and evaluate the underlying computational workflows for their robustness and ease of use. Overall, we demonstrate a high inter-method reliability across eight use case scenarios. Our results and data will facilitate reproducible research and serve as a resource contributing to a fuller understanding of RNA biology.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Coloración y Etiquetado
/
ARN
/
Regulación de la Expresión Génica
/
Biología Computacional
/
Perfilación de la Expresión Génica
Tipo de estudio:
Guideline
Límite:
Humans
Idioma:
En
Revista:
Brief Bioinform
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
Alemania