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Transcriptome profiling of induced hair cells (iHCs) generated by combined expression of Gfi1, Pou4f3 and Atoh1 during embryonic stem cell differentiation.

Costa A, Henrique D - Genom Data (2015)

Bottom Line: We found that combined activity of three transcription factors, Gfi1, Pou4f3, and Atoh1, can program ESC-derived progenitors towards HC fate with efficiencies of 55%-80%.This approach based on FACS sorting and microarray analysis revealed a highly similar iHC transcriptome to that of endogenous HCs in vivo.The data obtained in this study is available in the Gene Expression Omnibus (GEO) database (accession number GSE60352).

View Article: PubMed Central - PubMed

Affiliation: Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa 1649-028, Portugal.

ABSTRACT
To gain new insights about the genetic networks controlling hair cell (HC) development, we previously developed a direct genetic programming strategy to generate an inexhaustible supply of HC-like cells (induced HCs, iHCs) in vitro, starting from mouse embryonic stem cells (ESC). We found that combined activity of three transcription factors, Gfi1, Pou4f3, and Atoh1, can program ESC-derived progenitors towards HC fate with efficiencies of 55%-80%. These iHCs express several HC markers and exhibit polarized structures that are highly reminiscent of the mechanosensitive hair bundles, with many microvilli-like stereocilia. Here, we describe the experimental design, methodology, and data validation for the microarray analysis used to characterize the transcriptome profile of iHCs at different stages of their differentiation. This approach based on FACS sorting and microarray analysis revealed a highly similar iHC transcriptome to that of endogenous HCs in vivo. The data obtained in this study is available in the Gene Expression Omnibus (GEO) database (accession number GSE60352).

No MeSH data available.


Related in: MedlinePlus

A) Dendrogram showing unsupervised hierarchical clustering of the various expression profiles (16 samples) obtain from iGBM-Myo7a:mVenus reporter-derived EBs (E1, E2, and E3 correspond to three biological replicates). B) Principal component analysis shows the distribution of the 16 expression profiles generated in this microarray. Each point corresponds to an individual sample and the three biological replicates for different Dox treatments are shown with the same color (“Dox”: orange, “Dox + RA”: blue and “No treatment”: black; day 8 and day 12 are labeled with light or dark colors respectively). White circles highlight the three biological replicates and show that these samples occupy similar state space indicating higher similarity in their gene expression profile.
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f0015: A) Dendrogram showing unsupervised hierarchical clustering of the various expression profiles (16 samples) obtain from iGBM-Myo7a:mVenus reporter-derived EBs (E1, E2, and E3 correspond to three biological replicates). B) Principal component analysis shows the distribution of the 16 expression profiles generated in this microarray. Each point corresponds to an individual sample and the three biological replicates for different Dox treatments are shown with the same color (“Dox”: orange, “Dox + RA”: blue and “No treatment”: black; day 8 and day 12 are labeled with light or dark colors respectively). White circles highlight the three biological replicates and show that these samples occupy similar state space indicating higher similarity in their gene expression profile.

Mentions: The 16 scanned arrays were analyzed first with Expression Console software (Affymetrix) using RMA to obtain expression values, and for quality control. Control probe sets were removed and log2 expression values of the remaining 33.710 transcripts were imported into Chipster 2.4 [8]. Unsupervised hierarchical clustering (cluster method: average linkage; distances: Pearson correlation) and principal component analysis of the 16 transcriptome datasets were performed using Chipster 2.4 software. This analysis clearly shows two main branches that correspond to the untreated conditions and to Dox-treated conditions (Fig. 3). The clear segregation between “No Dox“and “Dox” was expected, and validates this global dataset. We next examined the microarray datasets to identify genes whose expression vary significantly among the 4 iHC stages, when compared to the non-induced cells (without Dox) at the same time point. An empirical Bayes two-group test with Benjamini-Hochberg multiple testing correction (P-value < 0.01, expression fold change > 2) [9] was used to identify lists of differentially expressed genes in each stage. These lists are organized accordingly to the variations in expression (up- or down-regulated in relation to the untreated cells) (Table 1). To correlate these differentially expressed gene lists with biological function, we searched for enrichment of gene ontology (GO) functional groups in the up-regulated and down-regulated gene lists using DAVID functional annotation tool (http://david.abcc.ncifcrf.gov/). We found that up-regulated genes are mainly involved in transmission of nerve impulses and sensory perception of mechanical stimulus in the 4 iHCs populations. In contrast, down-regulated genes in all lists are connected to cell cycle and cell division.


Transcriptome profiling of induced hair cells (iHCs) generated by combined expression of Gfi1, Pou4f3 and Atoh1 during embryonic stem cell differentiation.

Costa A, Henrique D - Genom Data (2015)

A) Dendrogram showing unsupervised hierarchical clustering of the various expression profiles (16 samples) obtain from iGBM-Myo7a:mVenus reporter-derived EBs (E1, E2, and E3 correspond to three biological replicates). B) Principal component analysis shows the distribution of the 16 expression profiles generated in this microarray. Each point corresponds to an individual sample and the three biological replicates for different Dox treatments are shown with the same color (“Dox”: orange, “Dox + RA”: blue and “No treatment”: black; day 8 and day 12 are labeled with light or dark colors respectively). White circles highlight the three biological replicates and show that these samples occupy similar state space indicating higher similarity in their gene expression profile.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664721&req=5

f0015: A) Dendrogram showing unsupervised hierarchical clustering of the various expression profiles (16 samples) obtain from iGBM-Myo7a:mVenus reporter-derived EBs (E1, E2, and E3 correspond to three biological replicates). B) Principal component analysis shows the distribution of the 16 expression profiles generated in this microarray. Each point corresponds to an individual sample and the three biological replicates for different Dox treatments are shown with the same color (“Dox”: orange, “Dox + RA”: blue and “No treatment”: black; day 8 and day 12 are labeled with light or dark colors respectively). White circles highlight the three biological replicates and show that these samples occupy similar state space indicating higher similarity in their gene expression profile.
Mentions: The 16 scanned arrays were analyzed first with Expression Console software (Affymetrix) using RMA to obtain expression values, and for quality control. Control probe sets were removed and log2 expression values of the remaining 33.710 transcripts were imported into Chipster 2.4 [8]. Unsupervised hierarchical clustering (cluster method: average linkage; distances: Pearson correlation) and principal component analysis of the 16 transcriptome datasets were performed using Chipster 2.4 software. This analysis clearly shows two main branches that correspond to the untreated conditions and to Dox-treated conditions (Fig. 3). The clear segregation between “No Dox“and “Dox” was expected, and validates this global dataset. We next examined the microarray datasets to identify genes whose expression vary significantly among the 4 iHC stages, when compared to the non-induced cells (without Dox) at the same time point. An empirical Bayes two-group test with Benjamini-Hochberg multiple testing correction (P-value < 0.01, expression fold change > 2) [9] was used to identify lists of differentially expressed genes in each stage. These lists are organized accordingly to the variations in expression (up- or down-regulated in relation to the untreated cells) (Table 1). To correlate these differentially expressed gene lists with biological function, we searched for enrichment of gene ontology (GO) functional groups in the up-regulated and down-regulated gene lists using DAVID functional annotation tool (http://david.abcc.ncifcrf.gov/). We found that up-regulated genes are mainly involved in transmission of nerve impulses and sensory perception of mechanical stimulus in the 4 iHCs populations. In contrast, down-regulated genes in all lists are connected to cell cycle and cell division.

Bottom Line: We found that combined activity of three transcription factors, Gfi1, Pou4f3, and Atoh1, can program ESC-derived progenitors towards HC fate with efficiencies of 55%-80%.This approach based on FACS sorting and microarray analysis revealed a highly similar iHC transcriptome to that of endogenous HCs in vivo.The data obtained in this study is available in the Gene Expression Omnibus (GEO) database (accession number GSE60352).

View Article: PubMed Central - PubMed

Affiliation: Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa 1649-028, Portugal.

ABSTRACT
To gain new insights about the genetic networks controlling hair cell (HC) development, we previously developed a direct genetic programming strategy to generate an inexhaustible supply of HC-like cells (induced HCs, iHCs) in vitro, starting from mouse embryonic stem cells (ESC). We found that combined activity of three transcription factors, Gfi1, Pou4f3, and Atoh1, can program ESC-derived progenitors towards HC fate with efficiencies of 55%-80%. These iHCs express several HC markers and exhibit polarized structures that are highly reminiscent of the mechanosensitive hair bundles, with many microvilli-like stereocilia. Here, we describe the experimental design, methodology, and data validation for the microarray analysis used to characterize the transcriptome profile of iHCs at different stages of their differentiation. This approach based on FACS sorting and microarray analysis revealed a highly similar iHC transcriptome to that of endogenous HCs in vivo. The data obtained in this study is available in the Gene Expression Omnibus (GEO) database (accession number GSE60352).

No MeSH data available.


Related in: MedlinePlus