• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

短时间序列表达转录组数据揭示了鳜鱼血液感染 LPS 和 poly (I:C) 的基因表达模式和潜在生物标志物。

Short time-series expression transcriptome data reveal the gene expression patterns and potential biomarkers of blood infection with LPS and poly (I:C) in Mandarin fish (Siniperca chuatsi).

机构信息

College of Fisheries, Henan Normal University, Xinxiang 453007, Henan, China; Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA; Observation and Research Station on Water Ecosystem in Danjiangkou Reservoir of Henan Province, Nanyang 474450, China.

Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China.

出版信息

Fish Shellfish Immunol. 2024 Oct;153:109806. doi: 10.1016/j.fsi.2024.109806. Epub 2024 Aug 3.

DOI:10.1016/j.fsi.2024.109806
PMID:39102971
Abstract

Blood transcriptomics has emerged as a vital tool for tracking the immune system and supporting disease diagnosis, prognosis, treatment, and research. The present study was conducted to analyze the gene expression profile and potential biomarker candidates using the whole blood of mandarin fish (Siniperca chuatsi) infected with LPS or poly (I:C) at 0 h, 3 h, 6 h, and 12 h. Our data suggest that 310 shared differentially expressed genes (DEGs) were identified among each comparison group after LPS infection, and 137 shared DEGs were identified after poly (I:C) infection. A total of 62 shared DEGs were differentially expressed in all compared groups after LPS or poly (I:C) infection. Pathways analysis for DEGs in all different compared groups showed that cytokine-cytokine receptor interaction was the most enrichment pathway. The expression levels of genes C-X-C chemokine receptor type 2-like (cxcr2), chemokine (C-C motif) receptor 9a (ccr9a), chemokine (C-C motif) receptor 9b (ccr9b), chemokine (C-X-C motif) receptor 4b (cxcr4b), and interleukin 10 receptor alpha (il10ra) were significantly different in all compared groups and most enriched in cytokine-cytokine receptor interaction pathway. The protein-protein interactions analysis among all shared DEGs showed that cxcr4 was the hub gene with the highest degree. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring mandarin fish diseases.

摘要

血液转录组学已成为跟踪免疫系统和支持疾病诊断、预后、治疗和研究的重要工具。本研究旨在分析用 LPS 或 poly (I:C) 感染的鳜鱼(Siniperca chuatsi)全血在 0 h、3 h、6 h 和 12 h 时的基因表达谱和潜在的生物标志物候选物。我们的数据表明,在 LPS 感染后,每个比较组之间共鉴定出 310 个差异表达基因(DEGs),在 poly (I:C) 感染后共鉴定出 137 个差异表达基因。在 LPS 或 poly (I:C) 感染后,所有比较组中共有 62 个差异表达基因。对所有不同比较组中 DEGs 的通路分析表明,细胞因子-细胞因子受体相互作用是最富集的通路。在所有比较组中,基因 C-X-C 趋化因子受体型 2 样(cxcr2)、趋化因子(C-C 基元)受体 9a(ccr9a)、趋化因子(C-C 基元)受体 9b(ccr9b)、趋化因子(C-X-C 基元)受体 4b(cxcr4b)和白细胞介素 10 受体 alpha(il10ra)的表达水平在所有比较组中均显著不同,且在细胞因子-细胞因子受体相互作用通路中最富集。在所有共享 DEGs 之间的蛋白质-蛋白质相互作用分析中,cxcr4 是具有最高度数的枢纽基因。本研究发现的生物标志物候选物在验证后可能成为监测鳜鱼疾病的有效诊断工具。

相似文献

1
Short time-series expression transcriptome data reveal the gene expression patterns and potential biomarkers of blood infection with LPS and poly (I:C) in Mandarin fish (Siniperca chuatsi).短时间序列表达转录组数据揭示了鳜鱼血液感染 LPS 和 poly (I:C) 的基因表达模式和潜在生物标志物。
Fish Shellfish Immunol. 2024 Oct;153:109806. doi: 10.1016/j.fsi.2024.109806. Epub 2024 Aug 3.
2
Transcriptome analysis of immune response against Siniperca chuatsi rhabdovirus infection in mandarin fish Siniperca chuatsi.翘嘴鳜虹彩病毒感染免疫相关转录组分析。
J Fish Dis. 2021 Jun;44(6):675-687. doi: 10.1111/jfd.13329. Epub 2021 Jan 10.
3
The dynamic immune responses of Mandarin fish (Siniperca chuatsi) to ISKNV in early infection based on full-length transcriptome analysis and weighted gene co-expression network analysis.基于全长转录组分析和加权基因共表达网络分析的鳜鱼(Siniperca chuatsi)早期感染传染性脾肾坏死病毒(ISKNV)后的动态免疫反应
Fish Shellfish Immunol. 2022 Mar;122:191-205. doi: 10.1016/j.fsi.2022.02.017. Epub 2022 Feb 11.
4
Identification and functional analysis of the Mandarin fish (Siniperca chuatsi) hypoxia-inducible factor-1α involved in the immune response.鉴定和功能分析鳜鱼(翘嘴鳜)缺氧诱导因子-1α 参与免疫反应。
Fish Shellfish Immunol. 2019 Sep;92:141-150. doi: 10.1016/j.fsi.2019.04.298. Epub 2019 Jun 5.
5
Molecular cloning and functional analyses of C-C motif chemokine ligand 3 (CCL3) in mandarin fish Siniperca chuatsi.中华乌塘鳢 C-C 基序趋化因子配体 3(CCL3)的分子克隆与功能分析
Fish Shellfish Immunol. 2024 Jun;149:109614. doi: 10.1016/j.fsi.2024.109614. Epub 2024 May 6.
6
Genomic and functional characterization of the lect2 gene from Siniperca chuatsi.翘嘴鲌 lect2 基因的基因组和功能特征。
Fish Shellfish Immunol. 2020 Dec;107(Pt A):146-155. doi: 10.1016/j.fsi.2020.09.034. Epub 2020 Sep 28.
7
Expression and antibacterial analysis of galectin-8 and -9 genes in mandarin fish, Siniperca chuatsi.鳜鱼(Siniperca chuatsi)中半乳糖凝集素-8和-9基因的表达及抗菌分析
Fish Shellfish Immunol. 2020 Dec;107(Pt B):463-468. doi: 10.1016/j.fsi.2020.10.028. Epub 2020 Nov 2.
8
Molecular cloning of Y-Box binding protein-1 from mandarin fish and its roles in stress-response and antiviral immunity.从鳜鱼中克隆 Y 盒结合蛋白-1 及其在应激反应和抗病毒免疫中的作用。
Fish Shellfish Immunol. 2019 Oct;93:406-415. doi: 10.1016/j.fsi.2019.07.069. Epub 2019 Jul 29.
9
Characterization of mandarin fish (Siniperca chuatsi) IL-6 and IL-6 signal transducer and the association between their SNPs and resistance to ISKNV disease.鳜鱼(Siniperca chuatsi)IL-6 和 IL-6 信号转导子的特性及其 SNP 与 ISKNV 病抗性的关系。
Fish Shellfish Immunol. 2021 Jun;113:139-147. doi: 10.1016/j.fsi.2021.04.003. Epub 2021 Apr 14.
10
Molecular characterization and expression analysis of the large yellow croaker (Larimichthys crocea) chemokine receptors CXCR2, CXCR3, and CXCR4 after bacterial and poly I:C challenge.大黄鱼(Larimichthys crocea)趋化因子受体 CXCR2、CXCR3 和 CXCR4 在细菌和 poly I:C 刺激后的分子特征和表达分析。
Fish Shellfish Immunol. 2017 Nov;70:228-239. doi: 10.1016/j.fsi.2017.08.029. Epub 2017 Sep 9.