基于小鼠脑海马区分析癫痫发病机制数据

运用基于随机引物扩增的单核转录组测序技术，采用单细胞聚类分析和扰动分析等方法，通过对比分析癫痫小鼠和正常对照小鼠脑海马区组织的单核转录组的数据，分析获得在癫痫发病关联基因的差异变化程度、显著性及其可靠性，获得与癫痫发生相关联的差异基因信息以及关联程度，为癫痫发病机制的解析提供了重要线索，有望为癫痫治疗领域的进展和个体化医学提供宝贵的科学基础。设计专业实验流程模拟小鼠癫痫发作，采集癫痫小鼠和正常对照小鼠脑海马区组织的单核转录组对比数据。数据处理如下：（1）使用STARsolo对测序数据进行基因组比对，生成单核转录组表达矩阵。（2）使用Seurat对表达矩阵数据进行质控、整合、降维和聚类分析，建立正常对照小鼠和癫痫模型小鼠脑海马区的单核图谱；使用scProportion识别对比数据中变化显著的细胞群体，了解癫痫关联显著的细胞类型和细胞群体；（3）基于差异细胞群体，获取在正常和癫痫状态下的基因差异表达变化的关键信息，并进行差异富集分析，以获得小鼠不同细胞类型在正常和癫痫状态下差异基本列表，获得癫痫关联基因的差异表达变化程度、显著性以及显著性的可靠性，为癫痫发病机制解析提供了重要线索。 通过分析与癫痫发病相关联的基因列表以及关联程度，不仅与现有已知癫痫关联基因完全吻合，如Pirb和Sox9等基因；然而列表中其它大多数基因尚未在癫痫研究中得到详细探究，这些基因可能在癫痫的发病机制和病理生理过程中发挥着关键作用，有望作为新的潜在标志物全面表征癫痫的复杂性和多样性，为未来治疗策略和临床诊断提供更多的可能性。

This dataset was generated using single-nucleus transcriptome sequencing based on random primer amplification, combined with methods including single-cell clustering analysis and perturbation analysis. Through comparative analysis of single-nucleus transcriptome data from hippocampal tissues of epileptic mice and normal control mice, we analyzed the magnitude, significance and reliability of differential changes in epilepsy-associated genes, obtained differential gene information associated with epileptogenesis and their correlation strengths, providing important clues for elucidating the pathogenesis of epilepsy, and promising to offer a valuable scientific basis for the progress of epilepsy treatment and personalized medicine.

We designed a professional experimental protocol to simulate epileptic seizures in mice, and collected comparative single-nucleus transcriptome data from hippocampal tissues of epileptic mice and normal control mice. The data processing steps are as follows:
(1) Align the sequencing data to the reference genome using STARsolo to generate the single-nucleus transcriptome expression matrix.
(2) Perform quality control, integration, dimensionality reduction and clustering analysis on the expression matrix using Seurat, and construct the single-nucleus atlases of hippocampal tissues from normal control mice and epileptic model mice; Use scProportion to identify significantly altered cell populations in the comparative dataset, so as to clarify epilepsy-associated cell types and cell populations.
(3) Based on the differential cell populations, obtain key information on gene differential expression changes between normal and epileptic states, and conduct differential enrichment analysis to acquire the differential gene lists of distinct mouse cell types under normal and epileptic conditions, as well as the magnitude, significance and reliability of differential changes in epilepsy-associated genes, providing critical clues for elucidating the pathogenesis of epilepsy.

By analyzing the epilepsy-associated gene lists and their correlation strengths, the results fully align with previously reported epilepsy-associated genes, such as Pirb and Sox9; however, most of the other genes in the lists have not been thoroughly investigated in epilepsy research. These genes may play critical roles in the pathogenesis and pathophysiological processes of epilepsy, and are expected to serve as novel potential biomarkers to comprehensively characterize the complexity and diversity of epilepsy, providing more possibilities for future therapeutic strategies and clinical diagnosis.

搜集汇总

数据集介绍

特点

该数据集基于小鼠脑海马区单核转录组测序数据，分析癫痫发病关联基因的差异表达变化，包含476条记录，为癫痫发病机制研究和治疗提供重要线索。