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比较转录组学分析确定了鹅脾脏发育过程中的关键基因和信号通路。

Comparative transcriptomics analysis identifies crucial genes and pathways during goose spleen development.

作者信息

Hu Shenqiang, Song Yang, Li Xiaopeng, Chen Qingliang, Tang Bincheng, Chen Jiasen, Yang Guang, Yan Haoyu, Wang Junqi, Wang Wanxia, Hu Jiwei, He Hua, Li Liang, Wang Jiwen

机构信息

State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.

Key Laboratory of Livestock and Poultry Multi-Omics Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, China.

出版信息

Front Immunol. 2024 Feb 5;15:1327166. doi: 10.3389/fimmu.2024.1327166. eCollection 2024.

DOI:10.3389/fimmu.2024.1327166
PMID:38375472
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10875100/
Abstract

As the largest peripheral lymphoid organ in poultry, the spleen plays an essential role in regulating the body's immune capacity. However, compared with chickens and ducks, information about the age- and breed-related changes in the goose spleen remains scarce. In this study, we systematically analyzed and compared the age-dependent changes in the morphological, histological, and transcriptomic characteristics between Landes goose (LG; ) and Sichuan White goose (SWG; ). The results showed a gradual increase in the splenic weights for both LG and SWG until week 10, while their splenic organ indexes reached the peak at week 6. Meanwhile, the splenic histological indexes of both goose breeds continuously increased with age, reaching the highest levels at week 30. The red pulp (RP) area was significantly higher in SWG than in LG at week 0, while the splenic corpuscle (AL) diameter was significantly larger in LG than in SWG at week 30. At the transcriptomic level, a total of 1710 and 1266 differentially expressed genes (DEGs) between week 0 and week 30 were identified in spleens of LG and SWG, respectively. Meanwhile, a total of 911 and 808 DEGs in spleens between LG and SWG were identified at weeks 0 and 30, respectively. Both GO and KEGG enrichment analysis showed that the age-related DEGs of LG or SWG were dominantly enriched in the Cell cycle, TGF-beta signaling, and Wnt signaling pathways, while most of the breed-related DEGs were enriched in the Neuroactive ligand-receptor interaction, Cytokine-cytokine receptor interaction, ECM-receptor interaction, and metabolic pathways. Furthermore, through construction of protein-protein interaction networks using significant DEGs, it was inferred that three hub genes including , and could play crucial roles in regulating age-dependent goose spleen development while , , and could be crucial for the breed-specific goose spleen development. These data provide novel insights into the splenic developmental differences between Chinese and European domestic geese, and the identified crucial pathways and genes are helpful for a better understanding of the mechanisms regulating goose immune functions.

摘要

作为家禽体内最大的外周淋巴器官,脾脏在调节机体免疫能力方面发挥着至关重要的作用。然而,与鸡和鸭相比,关于鹅脾脏随年龄和品种变化的信息仍然匮乏。在本研究中,我们系统地分析并比较了朗德鹅(LG)和四川白鹅(SWG)脾脏在形态学、组织学和转录组学特征方面的年龄依赖性变化。结果显示,LG和SWG的脾脏重量在第10周前均逐渐增加,而它们的脾脏器官指数在第6周达到峰值。同时,两个鹅品种的脾脏组织学指标均随年龄持续增加,在第30周达到最高水平。第0周时,SWG的红髓(RP)面积显著高于LG,而第30周时,LG的脾小体(AL)直径显著大于SWG。在转录组水平上,LG和SWG脾脏在第0周和第30周之间分别鉴定出1710个和1266个差异表达基因(DEG)。同时,LG和SWG脾脏在第0周和第30周时分别鉴定出911个和808个DEG。基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析均表明,LG或SWG与年龄相关的DEG主要富集在细胞周期、转化生长因子-β(TGF-β)信号通路和Wnt信号通路中,而大多数与品种相关的DEG则富集在神经活性配体-受体相互作用、细胞因子-细胞因子受体相互作用、细胞外基质-受体相互作用和代谢途径中。此外,通过使用显著DEG构建蛋白质-蛋白质相互作用网络,推断出包括 、 和 在内的三个枢纽基因可能在调节鹅脾脏年龄依赖性发育中发挥关键作用,而 、 和 可能对品种特异性鹅脾脏发育至关重要。这些数据为中国和欧洲家鹅脾脏发育差异提供了新的见解,所鉴定出的关键途径和基因有助于更好地理解调节鹅免疫功能的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/a9b9ba8edaee/fimmu-15-1327166-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/ea14c5f8d85f/fimmu-15-1327166-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/bc02e606d8cb/fimmu-15-1327166-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/84e2add846c6/fimmu-15-1327166-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/dd54c03985a9/fimmu-15-1327166-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/6c03e2c01742/fimmu-15-1327166-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/e9b3f65ecf05/fimmu-15-1327166-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/a831ed99a536/fimmu-15-1327166-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/a9b9ba8edaee/fimmu-15-1327166-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/ea14c5f8d85f/fimmu-15-1327166-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/bc02e606d8cb/fimmu-15-1327166-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/84e2add846c6/fimmu-15-1327166-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/0d77d7a0c5de/fimmu-15-1327166-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/dd54c03985a9/fimmu-15-1327166-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/6c03e2c01742/fimmu-15-1327166-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/e9b3f65ecf05/fimmu-15-1327166-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/a831ed99a536/fimmu-15-1327166-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b11b/10875100/a9b9ba8edaee/fimmu-15-1327166-g009.jpg

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