Unbiased, Genome-Wide In Vivo Mapping of Transcriptional Regulatory Elements Reveals Sex Differences in Chromatin Structure Associated with Sex-Specific Liver Gene Expression

Abstract

We have used a simple and efficient method to identify condition-specific transcriptional regulatory sites in vivo to help elucidate the molecular basis of sex-related differences in transcription, which are widespread in mammalian tissues and affect normal physiology, drug response, inflammation, and disease. To systematically uncover transcriptional regulators responsible for these differences, we used DNase hypersensitivity analysis coupled with high-throughput sequencing to produce condition-specific maps of regulatory sites in male and female mouse livers and in livers of male mice feminized by continuous infusion of growth hormone (GH). We identified 71,264 hypersensitive sites, with 1,284 showing robust sex-related differences. Continuous GH infusion suppressed the vast majority of male-specific sites and induced a subset of female-specific sites in male livers. We also identified broad genomic regions (up to ∼100 kb) showing sex-dependent hypersensitivity and similar patterns of GH responses. We found a strong association of sex-specific sites with sex-specific transcription; however, a majority of sex-specific sites were >100 kb from sex-specific genes. By analyzing sequence motifs within regulatory regions, we identified two known regulators of liver sexual dimorphism and several new candidates for further investigation. This approach can readily be applied to mapping condition-specific regulatory sites in mammalian tissues under a wide variety of physiological conditions.

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Unbiased, Genome-Wide In Vivo Mapping of Transcriptional Regulatory Elements Reveals Sex Differences in Chromatin Structure Associated with Sex-Specific Liver Gene Expression

Supplemental material for this article may be found at http://mcb.asm.org/.

This work was supported in part by NIH grant DK33765 (to D.J.W.). A.S. received Training Core support from the Superfund Research Program at Boston University (NIH grant 5 P42 ES07381).

We thank Minita Holloway of this laboratory for contributions to initial optimization of the DHS protocol and X. Shirley Liu (Dana-Farber Cancer Institute) for initial discussions about experimental design.

We have no financial interests to declare.