RNA-Seq analysis reveals pluripotency-associated genes and their interaction networks in human embryonic stem cells

Abstract

Insight into the key genes of pluripotency in human and their interrelationships is necessary for understanding the underlying mechanism of pluripotency and hence their successful application in regenerative medicine. The recent advances in transcriptomics technologies have created new opportunities to decipher the genes involved in pluripotency, genetic network that governs the unique properties of embryonic stem cells and lineage differentiation mechanisms in a deeper scale. There are a large number of experimental studies on human embryonic stem cells (hESCs) being routinely conducted for unfolding the underlying biology of embryogenesis and their clinical prospects.However, the outcome of these studies often lacks consensus due to differences in samples, experimental techniques and/or analysis protocols. A universal stemness gene list is still lacking. In this quest, we compared transcriptomic profiles of pluripotent and non-pluripotent samples from diverse cell lines/types generated through RNA-sequencing (RNA-seq). We used a uniform pipeline for the analysis of raw RNA-seq data in order to reduce the amount of variation. Our analysis revealed a consensus set of 498 pluripotency-associated genes and 432 genes as potential pluripotent cell differentiation markers. Furthermore, we predicted 32 genes as "pluripotency critical genes".Reconstruction and analysis of co-expression networks further highlighted the importance of these genes. Gene ontology (GO) and pathway enrichment analysis, StemChecker and literature survey confirmed the involvement of the genes in the induction and maintenance of pluripotency, though more experimental studies are required for understanding their molecular mechanisms in human.

A versatile and robust cell purification system with an RNA-only circuit composed of microRNA-responsive ON and OFF switches

“…We also performed RNA-seq to investigate the gene expression profile of the iPSCs treated with the same purification process. We quantified the potential target genes of miR-302a-5p predicted by TargetScan ( 29 ) or miRTarBase ( 30 ) and the genes required for pluripotency ( 31 , 32 ). As a result, the expression of miR-302a-5p–targeted genes was maintained, but that of pluripotency-associated genes was slightly decreased after 72 hours, and the expression levels of both miR-302a-5p target and pluripotency-associated genes were similar to control iPSCs after 120 hours (fig.…”

“…For the GO analysis, the genes whose expression level was three times higher than in the untransfected sample with an adjusted P < 0.05 were selected using DESeq2 and analyzed using the clusterProfiler package ( 45 ). Pluripotency critical genes and the human ESC essentialome were obtained from ( 31 ) and ( 32 ), respectively. The candidate target genes of miR-302a-5p were predicted using TargetScan ( 29 ) and miRTarBase ( 30 ).…”

Redox Homeostasis and Regulation in Pluripotent Stem Cells: Uniqueness or Versatility?

“…However, several studies, aimed to compare the transcriptome profile of PSCs and their differentiated progenies or various cells from adult tissues, did not reveal antioxidant enzyme genes in the lists of differentially expressed genes [63,64]. Similarly, genetic screenings or transcriptome profiling did not find principal antioxidant enzymes in the sets of genes that were demonstrated to be crucial for initiation and maintenance of pluripotency [65][66][67]. In addition, functional tests for the PSC resistance to oxidative stress did not confirm the hypothesis about the enhanced antioxidant protection of these cells.…”

SISTEMA: A large and standardized collection of transcriptome data sets for human pluripotent stem cell research

“…Genome-wide expression profiling has been a common end point for these studies for analyzing pluripotency, differentiation and the function of genetic variants associated with monogenic diseases. A growing body of transcriptomic datasets for various hPSC lines and their specific differentiated counterparts has been deposited in public data repositories (Assou et al, 2007;Au and Sebastiano, 2014;Ghosh and Som, 2020;Godoy et al, 2018;Mair et al, 2019;Mallon et al, 2013;Streeter et al, 2017). Despite this wealth of data, exploring gene expression profiles from different experiments is not trivial.…”