Cis-regulatory architecture of human ESC-derived hypothalamic neuron differentiation aids in variant-to-gene mapping of relevant complex traits

Matthew C. Pahl, Claudia A. Doege, Kenyaita M. Hodge, Sheridan H. Littleton, Michelle E. Leonard, Sumei Lu, Rick Rausch, James A. Pippin, Maria Caterina De Rosa, Alisha Basak, Jonathan P. Bradfield, Reza K. Hammond, Keith Boehm, Robert I. Berkowitz, Chiara Lasconi, Chun Su, Alessandra Chesi, Matthew E. Johnson, Andrew D. Wells, Benjamin F. Voight, Rudolph L. Leibel, Diana L. Cousminer & Struan F. A. Grant.
Nat Commun. 2021-11-19;12(1):6749.
Abstract
The hypothalamus regulates metabolic homeostasis by influencing behavior and endocrine systems. Given its role governing key traits, such as body weight and reproductive timing, understanding the genetic regulation of hypothalamic development and function could yield insights into disease pathogenesis. However, given its inaccessibility, studying human hypothalamic gene regulation has proven challenging. To address this gap, we generate a high-resolution chromatin architecture atlas of an established embryonic stem cell derived hypothalamic-like neuron model across three stages of in vitro differentiation. We profile accessible chromatin and identify physical contacts between gene promoters and putative cis-regulatory elements to characterize global regulatory landscape changes during hypothalamic differentiation. Next, we integrate these data with GWAS loci for various complex traits, identifying multiple candidate effector genes. Our results reveal common target genes for these traits, potentially affecting core developmental pathways. Our atlas will enable future efforts to determine hypothalamic mechanisms influencing disease susceptibility.
Consortium data used in this publication
Further information and requests for reagents should be directed to and will be fulfilled by the lead contacts, Struan F.A. Grant and Diana L. Cousminer. All reagents and software used are listed in Supplementary Data 9. The raw and processed ATAC-seq, Capture C, and RNA-seq data described in this study are deposited in the gene expression omnibus (GEO) with the accession number GSE152098. Public datasets accessed and used in the study: JASPAR2020: http://jaspar.genereg.net/downloads/; GTEX v7: https://gtexportal.org/home/datasets; Mouse Sorted Hypothalamic ATAC-seq and H3K27ac Chip-seq datasets: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112125; LD reference panels: https://github.com/bulik/ldsc; Molecular Signatures Database (MSigDB) v7: https://www.gsea-msigdb.org/gsea/msigdb/index.jsp. We accessed publicly available GWAS summary stats: age at Menarche: https://www.reprogen.org/data_download.html; anorexia: https://www.med.unc.edu/pgc/download-results/; bipolar disorder: https://www.med.unc.edu/pgc/download-results/; body mass index: https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files; chronotype: http://www.t2diabetesgenes.org/data/; height: https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files; major depressive disorder: https://www.med.unc.edu/pgc/download-results/; post-traumatic stress disorder: https://www.med.unc.edu/pgc/download-results/; pubertal growth: https://egg-consortium.org/; self-reported sleep: http://kp4cd.org/datasets/sleep; accelerometer-associated sleep traits: http://www.t2diabetesgenes.org/data/; type II diabetes: https://cnsgenomics.com/content/data.