![Sample our Bioscience journals, sign in here to start your access, Latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5925/TOC-Subject-Sample-2021-Bioscience.jpg"})
ABSTRACT
Obesity perturbs central functions of human adipose tissue, centred on differentiation of preadipocytes to adipocytes, i.e., adipogenesis. The large environmental component of obesity makes it important to elucidate epigenetic regulatory factors impacting adipogenesis. Promoter Capture Hi-C (pCHi-C) has been used to identify chromosomal interactions between promoters and associated regulatory elements. However, long range interactions (LRIs) greater than 1 Mb are often filtered out of pCHi-C datasets, due to technical challenges and their low prevalence. To elucidate the unknown role of LRIs in adipogenesis, we investigated preadipocyte differentiation to adipocytes using pCHi-C and bulk and single nucleus RNA-seq data. We first show that LRIs are reproducible between biological replicates, and they increase >2-fold in frequency across adipogenesis. We further demonstrate that genomic loci containing LRIs are more epigenetically repressed than regions without LRIs, corresponding to lower gene expression in the LRI regions. Accordingly, as preadipocytes differentiate into adipocytes, LRI regions are more likely to contain repressed preadipocyte marker genes; whereas these same LRI regions are depleted of actively expressed adipocyte marker genes. Finally, we show that LRIs can be used to restrict multiple testing of the long-range cis-eQTL analysis to identify variants that regulate genes via LRIs. We exemplify this by identifying a putative long range cis regulatory mechanism at the LYPLAL1/TGFB2 obesity locus. In summary, we identify LRIs that mark repressed regions of the genome, and these interactions increase across adipogenesis, pinpointing developmental regions that need to be repressed in a cell-type specific way for adipogenesis to proceed.
Acknowledgments
This study was funded by the National Institutes of Health (NIH) grant R01HG010505. K.M.G was supported by the NIH-NHLBI grant F31HL142180. C.C. was supported by the NIH NIGMS grant R25GM055052. D.Z.P was supported by the NIH-NCI grant T32LM012424 and NIH-NIDDK grant F31DK118865. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. K.H.P. was funded by the Academy of Finland (grants 335443, 314383), Novo Nordisk Foundation (grants NNF20OC0060547, NNF17OC0027232, NNF10OC1013354), Finnish Medical Foundation, Gyllenberg Foundation, Finnish Diabetes Research Foundation and Government Research Funds.
Author contributions
K.M.G., C.C., and P.P. designed the study. K.M.G. and P.P. generated the pCHi-C and ATAC-seq data and K.M.G., K.H.P., and P.P. generated the twin RNA-seq data used for comparison with public adipogenesis RNA-seq data. K.M., M.L., and P.P. produced the METSIM RNA-seq data. K.M.G., C.C., D.Z.P. and P.P. developed the analytical and statistical approaches. K.M.G., C.C., D.Z.P., and M.A. performed the computational analyses. K.M.G., C.C., and P.P. wrote the manuscript and all authors read, reviewed and/or edited the manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability
The PAd and Diff pCHi-C data and PAd, Diff and Adip ATAC-seq data are available at GEO under accession number GSE129574. The Adip pCHi-C data are available at GEO under accession number GSE129574.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/15592294.2022.2088145
