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GATA-1 genome-wide occupancy associates with distinct epigenetic profiles in mouse fetal liver erythropoiesis.

Papadopoulos GL, Karkoulia E, Tsamardinos I, Porcher C, Ragoussis J, Bungert J, Strouboulis J - Nucleic Acids Res. (2013)

Bottom Line: Our results suggest that GATA-1 associates preferentially with changes of specific epigenetic modifications, such as H4K16, H3K27 acetylation and H3K4 di-methylation.Remarkably, our prediction model explained a high proportion of 62% of variation in gene expression.Hierarchical clustering of the proximity values calculated by the RF model produced a clear separation of upregulated versus downregulated genes and a further separation of downregulated genes in two distinct groups.

View Article: PubMed Central - PubMed

Affiliation: Division of Molecular Oncology, Biomedical Sciences Research Center "Alexander Fleming", Vari GR16672, Greece.

ABSTRACT
We report the genomic occupancy profiles of the key hematopoietic transcription factor GATA-1 in pro-erythroblasts and mature erythroid cells fractionated from day E12.5 mouse fetal liver cells. Integration of GATA-1 occupancy profiles with available genome-wide transcription factor and epigenetic profiles assayed in fetal liver cells enabled as to evaluate GATA-1 involvement in modulating local chromatin structure of target genes during erythroid differentiation. Our results suggest that GATA-1 associates preferentially with changes of specific epigenetic modifications, such as H4K16, H3K27 acetylation and H3K4 di-methylation. Furthermore, we used random forest (RF) non-linear regression to predict changes in the expression levels of GATA-1 target genes based on the genomic features available for pro-erythroblasts and mature fetal liver-derived erythroid cells. Remarkably, our prediction model explained a high proportion of 62% of variation in gene expression. Hierarchical clustering of the proximity values calculated by the RF model produced a clear separation of upregulated versus downregulated genes and a further separation of downregulated genes in two distinct groups. Thus, our study of GATA-1 genome-wide occupancy profiles in mouse primary erythroid cells and their integration with global epigenetic marks reveals three clusters of GATA-1 gene targets that are associated with specific epigenetic signatures and functional characteristics.

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Evaluation of different GATA-1 target gene assignment parameters. (A) Schematic representation of the pipeline used to individually evaluate the association of different gene assignment methods with differential gene expression. The number of genes reported refers to the union of GATA-1 target genes identified in Ter119− and Ter119+ cells. (B) Plot of the R2 values (% of variance explained) of RF regression models trained on the data sets produced by the different gene assignment methods. The number of trees grown is reported in the x-axis.
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gkt167-F2: Evaluation of different GATA-1 target gene assignment parameters. (A) Schematic representation of the pipeline used to individually evaluate the association of different gene assignment methods with differential gene expression. The number of genes reported refers to the union of GATA-1 target genes identified in Ter119− and Ter119+ cells. (B) Plot of the R2 values (% of variance explained) of RF regression models trained on the data sets produced by the different gene assignment methods. The number of trees grown is reported in the x-axis.

Mentions: We combined the gene assignment parameters with the RNA-sequencing expression data obtained in Ter119− and Ter119+ erythroid cells by Wong et al. (45). We scored for GATA-1 peaks found within windows of increasing size (i.e. ±1, ±2, ±5, ±10 and ±20 kb) around a gene’s TSS, or within a region extending from −20 kb from a gene’s TSS to +10 kb from a gene’s TES, or by assigning peaks to the nearest TSS (Figure 2A). The number of potential GATA-1 target genes thus identified varied from 919 to 4551 expressed genes in Ter119− cells and from 1008 to 5080 in Ter119+ cells, depending on the assignment parameters (Figure 2A and Supplementary Table S1).Figure 2.


GATA-1 genome-wide occupancy associates with distinct epigenetic profiles in mouse fetal liver erythropoiesis.

Papadopoulos GL, Karkoulia E, Tsamardinos I, Porcher C, Ragoussis J, Bungert J, Strouboulis J - Nucleic Acids Res. (2013)

Evaluation of different GATA-1 target gene assignment parameters. (A) Schematic representation of the pipeline used to individually evaluate the association of different gene assignment methods with differential gene expression. The number of genes reported refers to the union of GATA-1 target genes identified in Ter119− and Ter119+ cells. (B) Plot of the R2 values (% of variance explained) of RF regression models trained on the data sets produced by the different gene assignment methods. The number of trees grown is reported in the x-axis.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3643580&req=5

gkt167-F2: Evaluation of different GATA-1 target gene assignment parameters. (A) Schematic representation of the pipeline used to individually evaluate the association of different gene assignment methods with differential gene expression. The number of genes reported refers to the union of GATA-1 target genes identified in Ter119− and Ter119+ cells. (B) Plot of the R2 values (% of variance explained) of RF regression models trained on the data sets produced by the different gene assignment methods. The number of trees grown is reported in the x-axis.
Mentions: We combined the gene assignment parameters with the RNA-sequencing expression data obtained in Ter119− and Ter119+ erythroid cells by Wong et al. (45). We scored for GATA-1 peaks found within windows of increasing size (i.e. ±1, ±2, ±5, ±10 and ±20 kb) around a gene’s TSS, or within a region extending from −20 kb from a gene’s TSS to +10 kb from a gene’s TES, or by assigning peaks to the nearest TSS (Figure 2A). The number of potential GATA-1 target genes thus identified varied from 919 to 4551 expressed genes in Ter119− cells and from 1008 to 5080 in Ter119+ cells, depending on the assignment parameters (Figure 2A and Supplementary Table S1).Figure 2.

Bottom Line: Our results suggest that GATA-1 associates preferentially with changes of specific epigenetic modifications, such as H4K16, H3K27 acetylation and H3K4 di-methylation.Remarkably, our prediction model explained a high proportion of 62% of variation in gene expression.Hierarchical clustering of the proximity values calculated by the RF model produced a clear separation of upregulated versus downregulated genes and a further separation of downregulated genes in two distinct groups.

View Article: PubMed Central - PubMed

Affiliation: Division of Molecular Oncology, Biomedical Sciences Research Center "Alexander Fleming", Vari GR16672, Greece.

ABSTRACT
We report the genomic occupancy profiles of the key hematopoietic transcription factor GATA-1 in pro-erythroblasts and mature erythroid cells fractionated from day E12.5 mouse fetal liver cells. Integration of GATA-1 occupancy profiles with available genome-wide transcription factor and epigenetic profiles assayed in fetal liver cells enabled as to evaluate GATA-1 involvement in modulating local chromatin structure of target genes during erythroid differentiation. Our results suggest that GATA-1 associates preferentially with changes of specific epigenetic modifications, such as H4K16, H3K27 acetylation and H3K4 di-methylation. Furthermore, we used random forest (RF) non-linear regression to predict changes in the expression levels of GATA-1 target genes based on the genomic features available for pro-erythroblasts and mature fetal liver-derived erythroid cells. Remarkably, our prediction model explained a high proportion of 62% of variation in gene expression. Hierarchical clustering of the proximity values calculated by the RF model produced a clear separation of upregulated versus downregulated genes and a further separation of downregulated genes in two distinct groups. Thus, our study of GATA-1 genome-wide occupancy profiles in mouse primary erythroid cells and their integration with global epigenetic marks reveals three clusters of GATA-1 gene targets that are associated with specific epigenetic signatures and functional characteristics.

Show MeSH
Related in: MedlinePlus