Research resource: A genome-wide study identifies potential new target genes for POU1F1

Abstract

The pituitary transcription factor POU1F1 is required for the differentiation of lactotrope, thyrotrope, and somatotrope cells. Its expression is maintained in the adult and is crucial for the expression of prolactin, GH, and TSHβ-subunit. Different studies indicated that POU1F1 could also have other functions in these cells. The identification of new targets of this factor could be useful to obtain a better understanding of these functions. To address this question we combined data obtained from expression microarrays and from chromatin immunoprecipitation (ChIP)-chips. Gene expression microarray assays were used to detect genes that have their expression modified in somatolactotrope GH4C1 cells by the expression of a dominant-negative form of POU1F1, POU1F1(R271W), and led to the identification of 1346 such genes. ChIP-chip experiments were performed from mouse pituitaries and identified 1671 POU1F1-binding sites in gene-promoter regions. Intersecting the gene expression and the ChIP-chip data yielded 121 potential new direct targets. The initial set of 1346 genes identified using the microarrays, as well as the 121 potential new direct targets, were analyzed with DAVID bioinformatics resource for gene ontology term enrichment and cluster. This analysis revealed enrichment in different terms related to protein synthesis and transport, to apoptosis, and to cell division. The present study represents an integrative genome-wide approach to identify new target genes of POU1F1 and downstream networks controlled by this factor.

Fig. 1.

A, Effect of POU1F1(R271W) on the expression of 17 genes of the 121 potential direct targets in GH4C1 cell line. Total RNA was prepared from GH4C1 cells using a NucleoSpin RNAII kit (Macherey-Nagel), and reverse transcription was performed followed by qPCR. Results were calculated using the ΔΔCt method (29), in which Gapdh was chosen as normalizer because, as evidenced in the microarray data, its level was not affected by the expression of the POU1F1(R271W). The graph represents the fold change in gene expression (n = 3 biological replicates). Numbers above the bars represent the fold change obtained previously in the microarray experiment. Prl was used as positive control. The sequences of the primers used can be found in Supplemental Table 9. Note that the primers used for Crem on this figure detect the ICER isoform of this gene. B, Recruitment of POU1F1 to the promoter of the same 17 genes. ChIP-qPCR was performed using mouse pituitaries and POU1F1 antibody. Gapdh and Prl were used, respectively, as negative and positive controls (n = 3 biological replicates). The sequences of the primers used can be found in Supplemental Table 9. Results were calculated using the fold enrichment method (30). The ΔCt {ΔCt = Ct sample − Ct input} then the ΔΔCt were calculated [ΔΔCt = ΔCt (immune serum) − ΔCt (nonimmune serum)]. The fold difference between experimental sample (immune serum) and negative control (nonimmune serum) was obtained using 2^(−ΔΔCt). Statistically significant differences were determined using Dunnett's multiple comparison tests, and data are expressed as means ± se (*, P < 0.05; **, P < 0.01).

Fig. 2.

A, Effect of POU1F1 R271W on Icer and Crem mRNA expression in GH4C1 cells. Total RNA from cells infected with the lentiviral vectors (with or without the transgene) was isolated by using the RNeasy Kit (QIAGEN), and reverse transcription was performed followed by qPCR. The graph represents the relative fold change (RFC) in mRNA expression (n = 3 biological replicates). The sequences of the primers used can be found in Supplemental Table 9. B and C, Transcriptional activation of Crem P2 (B) and Lmo4 (C) promoters by wild-type and mutant POU1F1 in GH4C1 cells. GH4C1 cells were transfected with pGL3-Crem-P2 (B) or pGL3-Lmo4 (C) and varying amount of pcDNA3-POU1F1 or pcDNA3-POU1F1(R271W). Cells were harvested after 48 h and assayed for luciferase. Transfections were performed in triplicate. Statistically significant differences were determined using Dunnett's multiple comparison tests, and data are expressed as means ± se (*, P < 0.05; **, P < 0,01).