In lymphoblastoid cells the motif for the transcription factor GABPA was the top ranked motif in all four samples, followed by those for the transcription factor BORIS, with the exception of stimulated GM10855 cells, where BORIS was replaced by IRF4. In stimulated lymphoblastoid cells also PU.1like motifs ranked high, whereas in unstimulated lymphoblastoid cells motifs for the transcription factor complex GFI1-STAF did the same. In contrast, both samples of LX2 cells had motifs for the transcription factors JUN, TEAD4 and RUNX as the top ranked. The stimulated LS180 cells also had JUN as the top ranking motif, but unlike for LX2 cells it had HNF4A and GFI1-STAF motifs as the next best ranked. In the small peak set for the unstimulated LS180 cells, motifs for the transcription factors STAT5, CHR and ZFX ranked the highest. Taken together, our de novo searches and DR3-type binding site screenings demonstrated as common findings for all six datasets that i) ligand-stimulated samples show a higher rate of DR3-type sequences than unstimulated samples of the same cellular model, ii) the more VDR peaks a stimulated dataset contains, the lower is the percentage of its DR3-type sequences, iii) by far not all VDR binding sites even at the stimulated state contain a DR3-type sequence and iv) the occurrence of non-DR3-type motifs differ considerably between the cell lines, especially in peaks that lack DR3-type motifs. The genome-wide location of VDR is an essential information for understanding the pleiotropic physiological action of 1,252D3. In this study, we generated VDR ChIP-seq data for LPS-differentiated THP-1 cells. These cells resemble M1-type macrophages and represent another tissue that is important for the interpretation of the immune-modulatory function of 1,252D3. This new VDR ChIP-seq dataset was compared with all the publically available VDR ChIP-seq datasets that we re-analyzed using identical settings and taking the benefit of the recent advances in the relevant bioinformatic tools. Thus, this study also represents the first meta-analysis of VDR ChIP-seq data from six different cell types and sets the basis for a compendium of all VDR binding sites genome-wide. The six ChIP-seq datasets differ largely in their total number of genome-wide VDR binding sites. While the two THP-1 datasets provide only 1,100-1,300 genome-wide VDR locations, the two lymphoblastoid cell lines suggest an up to 10-times higher number. This difference could arise from the number of sequence tags obtained in the ChIP-seq procedure, differences in signal-to-noise ratios or variations in the reference sample or simply from a much higher VDR expression in B lymphocytes than in monocytes/macrophages. However, the more likely explanation is that in B cells more VDR binding sites are accessible, i.e. the level of epigenomics. Nevertheless, it can be questioned, whether the regulation of a few hundred primary VDR target genes.