mapping of leptin-responsive neuronal populations involved in body weight regulation.

Genome wide association studies (GWAS) in obesity have identified a large number of noncoding loci located near genes expressed in the central nervous system. However, due to the difficulties in isolating and characterizing specific neuronal subpopulations, few obesity-associated SNPs have been functionally characterized. Leptin responsive neurons in the hypothalamus are essential in controlling energy homeostasis and body weight. Here, we combine FACS-sorting of leptin-responsive hypothalamic neuron nuclei with genomic and epigenomic approaches (RNA-seq, ChIP-seq, ATAC-seq) to generate a comprehensive map of leptin-response specific regulatory elements, several of which overlap obesity-associated GWAS variants. We demonstrate the usefulness of our leptin-response neuron regulome, by functionally characterizing a novel enhancer near Socs3, a leptin response-associated transcription factor. We envision our data to serve as a useful resource and a blueprint for functionally characterizing obesity-associated SNPs in the hypothalamus. at 37ºC for 30 minutes. Tagmented DNA was purified with MinElute reaction cleanup kit (Qiagen). The DNA was size-selected using SPRIselect (Beckman Coulter) according to manufacture’s double size selection protocol. DNA:SPRIselect ratio was 5:3 for right side, and 2:3 for left side selection. Library amplification was performed as described previously 47 . Amplified library was further purified with SPRIselect as described above. DNA was quantified using the Qubit DNA HS assay kit and Bioanalyzer (Agilent) using the DNA High Sensitivity kit. Massively parallel sequencing was performed on an Illumina Hiseq 4000. Sequencing reads were mapped to the genome using Bowtie2 48 ; options: --no-unal -X 2000 --no-discordant --no-mixed --local --very-sensitive-local). After duplicate read removal, samples were merged into a GFP positive and GFP negative pool for peak calling with MACS2 43 and reliable peaks were identified using the ENCODE IDR 44 pipeline. As with ChIP-seq, peaks were then partitioned with BEDTools 45 , read coverage obtained using HTSeq 46 and differentially enriched peaks identified using DESeq2 39 . Differentially enriched ATAC-seq peaks were tested for enrichment for novel motifs and known transcription factor binding sites with MEME-ChIP 28 in a similar fashion as the ChIP-seq peaks above. However, due to peak regions being generally smaller, peaks were divided into 200bp windows or smaller using BedTools 45 makewindows command. All ATAC-seq data was deposited in NCBI as