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| Status |
Public on Dec 01, 2023 |
| Title |
The transcriptomic landscape of PBMC in SARS-CoV-2 variants-infected Rhesus monkeys via digital RNA-seq analysis |
| Organism |
Macaca mulatta |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
The ensuing COVID-19 epidemic and the highly frequent mutations of SARS-CoV-2 have brought an immense social burden to all fields of society worldwide, including public health, socioeconomic development, and school education since 2020. Increasing genome evolution and mutation resulted in the birth of variants of concern (VOC), with the latter presenting differential structural features and gene functions associated with specific clinical symptoms or manifestations. Moreover, SARS-CoV-2-induced inflammation, immune response, and other biological processes involve a mountain of gene molecules and signaling pathways, still requiring further and more effort spent on them. Consequently, in this study, we comprehensively illustrate the transcriptomic landscape of different SARS-CoV-2 strains (Prototype, Beta, Delta, and Omicron) at functional clustering results level (GO and KEGG). Through our deep function analysis, we discovered AGE-RAGE signaling pathway in diabetes complications and its related downstream signaling pathways and gene molecules. Moreover, all Alzheimer disease-related gene identified in our study, such as EPHA4, FYN, CASP4 are almost validated in some authoritative journals. In all, our findings in this study provided quite a few candidate hub genes or potentially therapeutic targets, which could be a significant clue for modern precision medicine in the future.
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| Overall design |
Conducting a joint transcriptomic comparison of four SARS-CoV-2 variant infections (Prototype, Beta, Delta, Omicron) is in an effort to depict the total transcriptomic landscape of different SARS-CoV-2 variants at gene function and signalling pathway level.
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| Contributor(s) |
Lin D, Tang C |
| Citation missing |
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| Submission date |
Nov 03, 2023 |
| Last update date |
Dec 01, 2023 |
| Contact name |
Lin dongdong |
| E-mail(s) |
Dongdong0216@student.pumc.edu.cn
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| Phone |
18256786026
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| Organization name |
Peking Union Medical College
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| Street address |
云南省昆明市五华区茭菱路
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| City |
昆明市 |
| State/province |
云南 |
| ZIP/Postal code |
650032 |
| Country |
China |
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| Platforms (1) |
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| Samples (20)
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| Relations |
| BioProject |
PRJNA1035485 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE246985_All_reads_counts.txt.gz |
2.7 Mb |
(ftp)(http) |
TXT |
| GSE246985_RPKM_of_ALL_Genes_with_Pvalue.txt.gz |
5.6 Mb |
(ftp)(http) |
TXT |
| GSE246985_RPKM_of_all_diff_genes.txt.gz |
1.8 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
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