Project description:The LβT2 mouse pituitary cell line has many characteristics of a mature gonadotrope and is a widely used model system for studying developmental processes and the response to gonadotropin-releasing hormone (GnRH). The global epigenetic landscape, which contributes to cell-specific gene regulatory mechanisms, and the single-cell transcriptome response variation of LβT2 cells have not been previously investigated. Here, we integrate the transcriptome and genome-wide chromatin accessibility state of LβT2 cells during GnRH stimulation. Additionally, we examine cell-to-cell variability in the transcriptional response to GnRH using gel-in-emulsion Drop-seq technology. Analysis of a bulk RNA-seq dataset obtained 45 minutes after exposure to either GnRH or vehicle identified 112 transcripts that were regulated > 4-fold by GnRH (FDR < 0.05). The top regulated transcripts constitute, as determined by Bayesian massive public data integration analysis, a human pituitary-relevant coordinated gene program. Chromatin accessibility (ATAC-seq) datasets generated from GnRH-treated LβT2 cells identified more than 58,000 open chromatin regions, some containing notches consistent with bound transcription factor footprints. Study of the most prominent open regions showed that 75% were in transcriptionally active promoters or introns, supporting their involvement in active transcription. Lhb, Cga, and Egr1 showed significantly open chromatin over their promoters. While Fshb was closed over its promoter, several discrete significantly open regions were found at -40 to -90 kb, which may represent novel upstream enhancers. Chromatin accessibility determined by ATAC-seq was associated with high levels of gene expression determined by RNA-seq. We obtained high quality single-cell gel-in-emulsion Drop-seq transcriptome data, with an average of >4000 expressed genes/cell, from 1992 vehicle- and 1889 GnRH-treated cells. While the individual cell expression patterns showed high cell-to-cell variation, representing both biological and measurement variation, the average expression patterns correlated well with bulk RNA-seq data. Computational assignment of each cell to its precise cell cycle phase showed that the response to GnRH was unaffected by cell cycle. To our knowledge, this study represents the first genome-wide epigenetic and single-cell transcriptomic characterization of this important gonadotrope model. The data have been deposited publicly and should provide a resource for hypothesis generation and further study.

Dataset Information

Regulatory Architecture of the L?T2 Gonadotrope Cell Underlying the Response to Gonadotropin-Releasing Hormone.

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