Wang Yishen, Hong Yiwen, Mao Shudi, Jiang Yukang, Cui Yamei, Pan Jianying, Luo Yan
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, China.
Department of Statistical Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Front Genet. 2022 May 30;13:890672. doi: 10.3389/fgene.2022.890672. eCollection 2022.
To demonstrate an interaction-based method for the refinement of Gene Set Enrichment Analysis (GSEA) results. Intravitreal injection of miR-124-3p antagomir was used to knockdown the expression of miR-124-3p in mouse retina at postnatal day 3 (P3). Whole retinal RNA was extracted for mRNA transcriptome sequencing at P9. After preprocessing the dataset, GSEA was performed, and the leading-edge subsets were obtained. The Apriori algorithm was used to identify the frequent genes or gene sets from the union of the leading-edge subsets. A new statistic was introduced to evaluate the frequent genes or gene sets. Reverse transcription quantitative PCR (RT-qPCR) was performed to validate the expression trend of candidate genes after the knockdown of miR-124-3p. A total of 115,140 assembled transcript sequences were obtained from the clean data. With GSEA, the NOD-like receptor signaling pathway, C-type-like lectin receptor signaling pathway, phagosome, necroptosis, JAK-STAT signaling pathway, Toll-like receptor signaling pathway, leukocyte transendothelial migration, chemokine signaling pathway, NF-kappa B signaling pathway and RIG-I-like signaling pathway were identified as the top 10 enriched pathways, and their leading-edge subsets were obtained. After being refined by the Apriori algorithm and sorted by the value of the modulus of Prkcd, Irf9, Stat3, Cxcl12, Stat1, Stat2, Isg15, Eif2ak2, Il6st, Pdgfra, Socs4 and Csf2ra had the significant number of interactions and the greatest value of to downstream genes among all frequent transactions. Results of RT-qPCR validation for the expression of candidate genes after the knockdown of miR-124-3p showed a similar trend to the RNA-Seq results. This study indicated that using the Apriori algorithm and defining the statistic was a novel way to refine the GSEA results. We hope to convey the intricacies from the computational results to the low-throughput experiments, and to plan experimental investigations specifically.
为了展示一种基于相互作用的方法来优化基因集富集分析（GSEA）结果。在出生后第3天（P3），通过玻璃体内注射miR-124-3p拮抗剂来敲低小鼠视网膜中miR-124-3p的表达。在P9时提取整个视网膜RNA用于mRNA转录组测序。对数据集进行预处理后，进行GSEA，并获得前沿子集。使用Apriori算法从前沿子集的并集中识别频繁出现的基因或基因集。引入了一种新的统计量来评估频繁出现的基因或基因集。进行逆转录定量PCR（RT-qPCR）以验证miR-124-3p敲低后候选基因的表达趋势。从干净数据中总共获得了115,140个组装的转录序列。通过GSEA，NOD样受体信号通路、C型凝集素受体信号通路、吞噬体、坏死性凋亡、JAK-STAT信号通路、Toll样受体信号通路、白细胞跨内皮迁移、趋化因子信号通路、NF-κB信号通路和RIG-I样信号通路被确定为前10个富集通路，并获得了它们的前沿子集。经过Apriori算法优化并按Prkcd、Irf9、Stat3、Cxcl12、Stat1、Stat2、Isg15、Eif2ak2、Il6st、Pdgfra、Socs4和Csf2ra的模值排序后，在所有频繁交易中，它们与下游基因的相互作用数量显著且模值最大。miR-124-3p敲低后候选基因表达的RT-qPCR验证结果与RNA测序结果显示出相似的趋势。本研究表明，使用Apriori算法并定义统计量是优化GSEA结果的一种新方法。我们希望将计算结果的复杂性传达给低通量实验，并具体规划实验研究。
