bioRxivCell BiologyPreprint
Single nucleus multi-omics regulatory atlas of the murine pituitary
F. M. Ruf-Zamojski, Z. Zhang, M. Zamojski, G. R. Smith, N. Mendelev, H. Liu, G. Nudelman, M. Moriwaki, H. Pincas, R. Gomez Castanon, V. D. Nair, N. Seenarine, M. A. S. Amper, X. Zhou, L. Ongaro, C. Toufaily, G. Schang, J. R. Nery, A. Bartlett, A. Aldridge, N. Jain, G. V. Childs, O. G. Troyanskaya, J. R. Ecker, J. L. Turgeon, , S. C. Sealfon
Abstract
The pituitary regulates growth, reproduction and other endocrine systems. To investigate transcriptional network epigenetic mechanisms, we generated paired single nucleus (sn) transcriptome and chromatin accessibility profiles in single mouse pituitaries and genome-wide sn methylation datasets. Our analysis provided insight into cell type epigenetics, regulatory circuit and gene control mechanisms. Latent variable pathway analysis detected corresponding transcriptome and chromatin accessibility programs showing both inter-sexual and inter-individual variation. Multi-omics analysis of gene regulatory networks identified cell type-specific regulons whose composition and function were shaped by the promoter accessibility state of target genes. Co-accessibility analysis comprehensively identified putative cis-regulatory regions, including a domain 17kb upstream of Fshb that overlapped the fertility-linked rs11031006 human polymorphism. In vitro CRISPR-deletion at this locus increased Fshb levels, supporting this domains inferred regulatory role. The sn pituitary multi-omics atlas (snpituitaryatlas.princeton.edu) is a public resource for elucidating cell type-specific gene regulatory mechanisms and principles of transcription circuit control.
- organism: mouse
- assay: scRNA-seq
- assay: DNA methylation
- research focus: gene regulatory network inference
- research focus: cell type annotation
- approach: deep learning
- approach: statistical model
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