不同亚型巨噬细胞调控绵羊卵巢颗粒细胞的转录组差异特征分析

Comparative transcriptomic analysis of sheep granulosa cells regulated by different macrophage subtypes

摘要:

巨噬细胞是哺乳动物卵巢中最丰富的免疫细胞之一，在卵巢组织内分布广泛，可通过重塑自身免疫表型与功能，参与调控卵巢内环境稳态维持与卵泡发育及激素生成等生理过程。但目前有关绵羊卵巢巨噬细胞调控颗粒细胞的具体机制尚不明确。为揭示绵羊卵巢免疫微环境中巨噬细胞对颗粒细胞(granulosa cells, GC)功能调控的分子基础，本研究构建了M0、M1和M2型绵羊骨髓来源巨噬细胞(bone marrow-derived macrophages, BMDM)与卵巢颗粒细胞的体外Transwell共培养模型，并采集颗粒细胞转录组测序及相关验证数据。数据集包含不同处理组颗粒细胞的转录组测序(RNA sequencing, RNA-seq)原始数据、质控后clean data、参考基因组比对结果、基因表达定量矩阵、差异表达基因结果、GO/KEGG富集分析结果，以及用于细胞鉴定与表达验证的流式检测和qPCR相关信息。样本设置覆盖GC-M0、GC-M1和GC-M2这3个处理组，具有生物学重复，可用于解析不同极化状态巨噬细胞诱导的颗粒细胞转录响应差异。数据采集流程包括骨髓细胞分离、巨噬细胞诱导及极化、颗粒细胞培养、Transwell共培养、RNA提取、文库构建、Illumina高通量测序及后续生物信息学分析。该数据集重点解析了不同极化状态巨噬细胞诱导下颗粒细胞的转录组应答特征与差异，可为研究反刍动物卵泡发育、卵巢免疫调控、巨噬细胞-颗粒细胞互作研究提供基础数据资源，并为相关研究的数据复用、交叉比较和分子机制挖掘研究提供支持。

Abstract:

Macrophages represent one of the most abundant immune cell populations in mammalian ovaries and are widely distributed throughout ovarian tissue. Through remodeling of their immunological phenotype and functional attributes, macrophages contribute to the regulation of ovarian homeostasis, follicular development, and hormone production. However, the specific mechanisms by which ovarian macrophages regulate granulosa cells (GCs) in sheep remain inadequately defined. To investigate the molecular basis underlying macrophage-mediated functional modulation of granulosa cells within the ovarian immune microenvironment of sheep, an in vitro co-culture model was established using sheep bone marrow-derived macrophages (BMDMs) polarized to M0, M1, and M2 phenotypes in conjunction with ovarian granulosa cells. Transcriptomic sequencing of the granulosa cells was subsequently performed, along with corresponding validation experiments. The resultant dataset included raw RNA-sequencing data derived from granulosa cells across distinct treatment groups, post-quality-control clean data, reference genome alignment outputs, gene expression quantification matrices, differentially expressed gene (DEG) profiles, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis results, as well as associated flow cytometry and quantitative PCR (qPCR) data utilized for cell identification and expression validation. The experimental design comprised three treatment groups (GC-M0, GC-M1, and GC-M2), each incorporating biological replicates, thereby enabling systematic analysis of differential transcriptional responses of granulosa cells induced by macrophages under different polarization states. The data acquisition workflow encompassed bone marrow cell isolation, macrophage induction and polarization, granulosa cell culture, Transwell co-culture, RNA extraction, library construction, Illumina high-throughput sequencing, and subsequent bioinformatics analysis. This dataset provides a focused characterization of the transcriptomic response signatures and disparities exhibited by granulosa cells under the influence of differentially polarized macrophages, thereby offering foundational data resources for investigations into ruminant follicular development, ovarian immunoregulation, and macrophage-granulosa cell interactions. Furthermore, it also facilitates data reuse, cross-study comparative analyses, and mechanistic investigation in relevant research domains.