Differential coregulator requirements for function of the hematopoietic transcription factor GATA-1 at endogenous loci

Abstract

The critical regulator of hematopoiesis GATA-1 recruits diverse coregulators to chromatin, which mediate transcriptional activation and repression. These coregulators include the cell-type-specific multi-zinc finger protein Friend of GATA-1 (FOG-1), the histone acetyltransferase CREB binding protein (CBP), and the key component of the Mediator complex Med1. While FOG-1 is an established GATA-1 coregulator, the importance of interactions between GATA-1 and other coregulators is poorly understood. Furthermore, whether GATA-1 utilizes multiple coregulators at all loci, or if certain coregulators are dedicated to specific loci is unknown. We compared the capacity of GATA-1 to recruit and utilize FOG-1 and Med1 at activated and repressed target genes. Similar to FOG-1, GATA-1 recruited Med1 to activated genes, and the kinetics of FOG-1 and Med1 recruitment were similar. GATA-1 recruited Med1 in Fog1(-/-) cells, indicating that GATA-1-mediated Med1 recruitment is FOG-1-independent. In contrast to FOG-1, GATA-1 evicted Med1 during transcriptional repression. Whereas knocking-down FOG-1 had catastrophic effects on GATA-1-mediated activation and repression, knocking-down Med1 modestly impaired GATA-1 activity only at select loci. These results illustrate both similarities and differences between GATA-1-mediated recruitment of FOG-1 and Med1 to chromatin, with a fundamental difference being the quantitatively greater requirement for FOG-1.

Figure 1.

Med1 is recruited to GATA-1 occupancy sites in GATA-1-activated genes upon induction, and evicted from GATA-1-repressed genes. (A) GATA-1-activated genes. Real-time RT–PCR quantitation of mRNA in G1E–ER-GATA-1 cells treated with 1 µM β-estradiol for 24 h (mean ± standard error, three independent experiments). (B) Quantitative ChIP analysis of GATA-1 and Med1 occupancy at GATA-1-activated genes in G1E–ER-GATA-1 cells treated with 1 µM β-estradiol for 24 h (mean ± standard error, three independent experiments). The locations of chromatin sites analyzed at the respective genes are shown at the top. (C) GATA-1-repressed genes. Real-time RT–PCR quantitation of mRNA in G1E–ER-GATA-1 cells treated with 1 µM β-estradiol for 24 h (mean ± standard error, three independent experiments). (D) Quantitative ChIP analysis of GATA-1 and Med1 occupancy at GATA-1-repressed genes in G1E–ER-GATA-1 cells treated with 1 µM β-estradiol for 24 h (mean ± standard error, three independent experiments). The locations of chromatin sites analyzed at the respective genes are shown at the top.

Figure 2.

Med1 is recruited to endogenous GATA-1-bound target sites. (A) Real-time RT–PCR quantitation of mRNA in MEL cells differentiated for 3 days in 1.5% DMSO (mean ± standard error, three independent experiments). (B) Quantitative ChIP analysis of GATA-1 and Med1 occupancy in MEL cells differentiated for 3 days in 1.5% DMSO (mean ± standard error, three independent experiments). The locations of chromatin sites analyzed at the respective genes are shown at the top.

Figure 3.

GATA-1 recruits Med1 and FOG-1 with similar kinetics. (A) Quantitative ChIP analysis of ER-GATA-1, Med1 and FOG-1 chromatin occupancy at various times post- induction with 1 µM β-estradiol (mean ± standard error, three independent experiments). (B) ChIP controls. Quantitative ChIP analysis of GATA-1, FOG-1 and Med1 occupancy at active (RPII215), and repressed (necdin) genes that are not regulated by GATA-1 (mean ± standard error, three independent experiments).

Figure 4.

GATA-1-mediated Med1 recruitment is FOG-1-independent. (A) Potential FOG-1-dependent and -independent modes of Med1 recruitment. (B) Quantitative ChIP analysis of GATA-1 and Med1 occupancy at select sites in Fog1^−/− cells (mean ± standard error, three independent experiments). (C) Quantitative ChIP analysis of GATA-1 and Med1 occupancy in Fog1^−/− cells stably expressing ER-GATA-1, treated with 1 µM β-estradiol for 48 h (mean ± standard error, three independent experiments).

Figure 5.

Knockdown of Med1 significantly, but modestly, alters expression of select endogenous GATA-1 target genes. (A) Diagram illustrating the knockdown strategy employed. Cells were transfected twice allowing 24 h between transfections, and treated with β-estradiol (shaded period) for 42 h. (B) Knockdown of Med1 mRNA and protein by siRNA treatment, as measured by real-time RT–PCR and semi-quantitative western blotting respectively (mean ± standard error, six independent experiments). Asterisk indicates non-specific band. Right, densitometric quantitation of protein level. (C) Real-time RT–PCR quantification of mRNA in G1E-ER-GATA-1 cells treated with either 240 pmol control siRNA or Med1 siRNA for 48 h and 1 µM β-estradiol for 42 h (mean ± standard error, six independent experiments). The fold change in expression was plotted, with GATA-1 activating β-major, α-globin, Alas2, Epb4.9 and Slc4a1 and repressing Gata2; *P < 0.05.

Figure 6.

FOG-1 knockdown severely dysregulates endogenous GATA-1 target gene expression. (A) siRNA-mediated knockdown of Fog1 mRNA and protein as measured by real-time RT–PCR and semi-quantitative western blotting, respectively (mean ± standard error, six independent experiments). Densitometric quantitation of protein level in whole boiled cell samples. (B) Real-time RT–PCR quantification of mRNA in G1E-ER-GATA-1 cells treated with either 240 pmol control or FOG-1 siRNA for 48 h, and 1 µM β-estradiol for 42 h (mean ± standard error, six independent experiments). The fold change in expression was plotted, with GATA-1 activating β-major, α-globin, Alas2, Epb4.9 and Slc4a1 and repressing Gata2; *P < 0.05.

Figure 7.

FOG-1 knockdown, but not Med1 knockdown, blocks G1E-ER-GATA-1 erythroid maturation. (A) Representative photos of Wright–Giemsa stained G1E-ER-GATA-1 cells treated with either 240 pmol control siRNA and no β-estradiol; or 240 pmol control siRNA, Med1 siRNA or FOG-1 siRNA and 1 µM β-estradiol for 42 h. (B) Quantitation of nuclear area and nuclear area as a percentage of total cellular area (mean ± standard error, 50 cells measured for each condition). *P < 0.0001.