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Related Concept Videos

Types of RNA01:23

Types of RNA

Overview
Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in the regulation of gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Identification of RNA-based cell-type markers for stem-cell manufacturing systems with a statistical scoring

Yu Shi1, Weilong Yang1, Haishuang Lin2

  • 1School of Biological Sciences, University of Nebraska, Lincoln, NE, USA.

Gene Reports
|February 14, 2024
PubMed
Summary
This summary is machine-generated.

Researchers developed a scoring system to find RNA biomarkers for stem cell manufacturing. This method efficiently identifies extracellular RNAs (ex-RNAs) and intracellular microRNAs (miRNAs) for monitoring cell quality and purity.

Keywords:
Cell culture and purificationCell-type markersExtracellular RNAs (ex-RNAs)Intracellular microRNAs (miRNAs)

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Area of Science:

  • Biotechnology
  • Molecular Biology
  • Genomics

Background:

  • Cell-type biomarkers are crucial for monitoring stem cell manufacturing processes, ensuring cell purity, quantity, and quality.
  • Current research on specific cell-type markers for stem cell manufacture is limited, posing challenges in efficient and precise biomarker discovery.
  • Key questions involve identifying suitable RNA transcripts as biomarkers and developing efficient methods for their discovery during stem cell culture.

Purpose of the Study:

  • To develop and validate a novel scoring function system for identifying RNA biomarkers from RNA-sequencing (RNA-seq) data.
  • To discover candidate extracellular RNAs (ex-RNAs) and intracellular microRNAs (miRNAs) that can serve as biomarkers in stem cell manufacturing.
  • To efficiently and precisely identify RNA biomarkers for different cell types used in cell manufacturing.

Main Methods:

  • Developed a scoring function system to identify RNA biomarkers using RNA-seq data, particularly for systems with a limited number of cell types.
  • Applied the method to analyze RNA-seq data from extracellular RNAs (ex-RNAs) in cell culture media of six cell types, including human embryonic stem cells.
  • Conducted small RNA-sequencing (smRNA-seq) on intracellular miRNAs from cultured human embryonic stem cells (H9), neural stem cells (NSC), and hESC-derived endothelial cells (EC).

Main Results:

  • Identified a set of candidate ex-RNAs and small-molecule RNAs (smRNAs) as potential biomarkers for various cell types relevant to cell manufacturing.
  • Validated the identified biomarkers using additional datasets and experimental procedures, confirming their reliability.
  • Employed deep-learning-based prediction methods and simulated data to further validate the discovered RNA biomarkers.

Conclusions:

  • The developed scoring function system is effective for identifying RNA biomarkers in stem cell manufacturing.
  • The study successfully identified candidate ex-RNAs and smRNAs as biomarkers for different cell types, aiding in cell manufacturing quality control.
  • The findings provide a foundation for more precise and efficient monitoring of stem cell manufacturing processes using RNA biomarkers.