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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Computational Methods to Study Human Transcript Variants in COVID-19 Infected Lung Cancer Cells.

Jiao Sun1,2, Naima Ahmed Fahmi1,2, Heba Nassereddeen2,3

  • 1Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.

International Journal of Molecular Sciences
|September 28, 2021
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Summary
This summary is machine-generated.

Investigating SARS-CoV-2 infection reveals significant changes in host cell transcriptomes. The study highlights alternative splicing and polyadenylation events as crucial molecular signatures for understanding COVID-19 pathogenesis.

Keywords:
3′-UTRCOVID-19RNA-seqalternative polyadenylationalternative splicingtranscript variants

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Area of Science:

  • Genomics
  • Virology
  • Molecular Biology

Background:

  • Viruses and microbes can reprogram host cell transcriptomes during infection.
  • The COVID-19 pandemic necessitates a deeper understanding of disease mechanisms at the transcriptome level.
  • Research on transcriptome reprogramming via post-transcriptional regulation, including alternative splicing and polyadenylation, is limited.

Purpose of the Study:

  • To investigate transcriptome reprogramming in SARS-CoV-2 infected cells using computational analysis of RNA-seq data.
  • To detect and analyze alternative splicing (AS) and alternative polyadenylation (APA) events in response to SARS-CoV-2 infection.
  • To identify novel molecular signatures and biological pathways associated with COVID-19 pathogenesis.

Main Methods:

  • Utilized computational methods to analyze publicly available RNA-seq data from mock-treated and SARS-CoV-2 infected A549 lung alveolar cells.
  • Detected transcript variants, specifically alternative splicing (AS) and alternative polyadenylation (APA) events.
  • Combined differential gene expression analysis with transcript variant analysis.

Main Results:

  • SARS-CoV-2 infected cells exhibited an increase in AS events and a decrease in APA events compared to mock-treated cells.
  • Most genes with transcript variants were not differentially expressed, indicating a weak correlation between differential gene expression and AS/APA events.
  • Transcript variants were enriched in important biological pathways not identified by differential gene expression analysis alone.

Conclusions:

  • Transcript variants, particularly AS and APA events, serve as valuable molecular signatures for COVID-19 research.
  • These transcript variants reveal biological pathways critical for understanding SARS-CoV-2 pathogenesis, offering new insights beyond traditional gene expression studies.