Transcriptomics

Dataset Information

0

Transcriptomic analysis of differential expressed genes of human tonsillar epithelial cells UT-SCC-60B in response to EV71 infection


ABSTRACT: Purpose: The goals of this study are to understand the transcriptional changes of human tonsillar epithelial cells UT-SCC-60B in response to EV71 infection and determine the differential expressed genes Methods: Transcriptional profiles of human tonsillar epithelial cells UT-SCC-60B and human tonsillar epithelial cells infected with EV71 were generated by next generation sequencing, in triplicate, using Illumina X-ten/NovaSeq. The sequence reads that passed quality filters were analyzed abundance of mRNA using StringTie, the FPKM values of genes and transcripts were calculated by Ballgown of R software, alternative splicing events were determined by rMATS Results: Using an optimized data analysis workflow, we mapped more than 36 million sequence reads per sample. Total 11137 gene counts and 26860 transcript counts were identified in human tonsillar epithelial cells, 11347 gene counts and 27994 transcript counts were identified in EV71-infected human tonsillar epithelial cells. Total 96 genes and 499 transcripts were down-regulated, 105 genes and 550 transcripts were up-regulated according the criteria that fold changes are more than 1.5, p value less is than 0.05 and mean of FPKM value is more than 0.5 to defined as the differential expressed genes or differential expressed transcripts. Total 11563 novel genes and 14927 novel transcripts were identified and 3266 novel transcripts had the potential coding probabilities. Finally, total 5742 genes occurred alternative splicing events. Conclusions: Our study represents the first detailed analysis of the transcriptional changes of human tonsillar epithelial cells UT-SCC-60B in response to EV71 infection, this results will provide novel insight into the interaction between human tonsillar epithelial cells and EV71

ORGANISM(S): Homo sapiens

PROVIDER: GSE136668 | GEO | 2019/08/31

REPOSITORIES: GEO

Similar Datasets

| PRJNA563012 | ENA
2012-02-10 | E-MEXP-3415 | biostudies-arrayexpress
2022-11-21 | PXD033555 | Pride
2012-01-30 | GSE23822 | GEO
2015-09-15 | PXD002454 | Pride
2012-01-30 | E-GEOD-23822 | biostudies-arrayexpress
2023-09-26 | GSE234900 | GEO
2019-11-08 | PXD003496 | Pride
2016-01-14 | E-MTAB-3670 | biostudies-arrayexpress
2016-07-03 | E-GEOD-75455 | biostudies-arrayexpress