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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Using big sequencing data to identify chronic SARS-Coronavirus-2 infections.

Sheri Harari1,2, Danielle Miller1,2, Shay Fleishon3

  • 1The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel.

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|January 20, 2024
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Chronic infections in immunocompromised individuals may drive SARS-CoV-2 variant evolution. Researchers identified mutations linked to prolonged infections, predicting future viral evolutionary patterns.

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Area of Science:

  • Virology
  • Genomics
  • Immunology

Background:

  • Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) evolution is marked by emerging divergent variants.
  • Chronic infections in immunocompromised individuals are hypothesized to be a source of these variants, but data is limited.

Purpose of the Study:

  • To identify potential chronic SARS-CoV-2 infections and associated mutations using genomic data.
  • To infer mutations characteristic of chronic infections and assess their evolutionary impact.
  • To develop a method for identifying chronic infections and predicting future viral evolution.

Main Methods:

  • Phylogenetic analysis of millions of SARS-CoV-2 genomes to identify chronic-like clades (≥21 days, identical metadata).
  • Application of language models (LM) to infer chronic-associated mutations, particularly in the spike receptor-binding domain (RBD).
  • Comparison of mutation frequencies and evolutionary success between chronic and global transmission chains.

Main Results:

  • Identified 271 chronic-like clades exhibiting characteristics of prolonged infections.
  • Chronic-associated mutations included high-fitness, immune-evasive RBD mutations, with some unique to chronic settings.
  • High-fitness RBD mutations were 10-20 times more probable in chronic infections than global chains.
  • The majority of BA.1/BA.2 RBD mutations from chronic clades predicted global success.
  • LM inferred hundreds of additional chronic-like clades without metadata.

Conclusions:

  • Chronic SARS-CoV-2 infections are a significant reservoir for the emergence of high-fitness, immune-evasive variants.
  • Genomic surveillance and computational approaches can identify chronic infections and predict viral evolution.
  • Understanding chronic infection dynamics is crucial for anticipating future SARS-CoV-2 evolutionary trajectories.