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The KDM5 family of histone demethylases removes the H3K4 tri-methylation (H3K4me3) mark frequently found at promoter regions of actively transcribed genes and is therefore generally considered to contribute to corepression. In this study, we show that knockdown (KD) of all expressed members of the KDM5 family in white and brown preadipocytes leads to deregulated gene expression and blocks differentiation to mature adipocytes. KDM5 KD leads to a considerable increase in H3K4me3 at promoter regions; however, these changes in H3K4me3 have a limited effect on gene expression per se. By contrast, genome-wide analyses demonstrate that KDM5A is strongly enriched at KDM5-activated promoters, which generally have high levels of H3K4me3 and are associated with highly expressed genes. We show that KDM5-activated genes include a large set of cell cycle regulators and that the KDM5s are necessary for mitotic clonal expansion in 3T3-L1 cells, indicating that KDM5 KD may interfere with differentiation in part by impairing proliferation. Notably, the demethylase activity of KDM5A is required for activation of at least a subset of pro-proliferative cell cycle genes. In conclusion, the KDM5 family acts as dual modulators of gene expression in preadipocytes and is required for early stage differentiation and activation of pro-proliferative cell cycle genes.

RNA-seq is a sensitive and accurate technique to compare steady-state levels of RNA between different cellular states. However, as it does not provide an account of transcriptional activity per se, other technologies are needed to more precisely determine acute transcriptional responses. Here, we have developed an easy, sensitive and accurate novel computational method, IRNA-SEQ: , for genome-wide assessment of transcriptional activity based on analysis of intron coverage from total RNA-seq data. Comparison of the results derived from iRNA-seq analyses with parallel results derived using current methods for genome-wide determination of transcriptional activity, i.e. global run-on (GRO)-seq and RNA polymerase II (RNAPII) ChIP-seq, demonstrate that iRNA-seq provides similar results in terms of number of regulated genes and their fold change. However, unlike the current methods that are all very labor-intensive and demanding in terms of sample material and technologies, iRNA-seq is cheap and easy and requires very little sample material. In conclusion, iRNA-seq offers an attractive novel alternative to current methods for determination of changes in transcriptional activity at a genome-wide level.