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Abstract

Immunology and Infection

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published: March 5th, 2022

DOI:

10.3791/62324

1Laboratory of Pathology of Infectious Diseases, Department of Pathology, Medical School, University of São Paulo, 2Scientific Platform Pasteur USP, 3Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, 4Hospital Israelita Albert Einstein

Abstract

Pathogens can cause a wide variety of infectious diseases. The biological processes induced by the host in response to infection determine the severity of the disease. To study such processes, researchers can use high-throughput sequencing techniques (RNA-seq) that measure the dynamic changes of the host transcriptome at different stages of infection, clinical outcomes, or disease severity.This investigation can lead to a better understanding of the diseases, as well as uncovering potential drug targets and treatments. The protocol presented here describes a complete pipeline to analyze RNA-sequencing data from raw reads to functional analysis. The pipeline is divided into five steps: (1) quality control of the data; (2) mapping and annotation of genes; (3) statistical analysis to identify differentially expressed genes and co-expressed genes; (4) determination of the molecular degree of the perturbation of samples; and (5) functional analysis. Step 1 removes technical artifacts that may impact the quality of downstream analyses. In step 2, genes are mapped and annotated according to standard library protocols. The statistical analysis in step 3 identifies genes that are differentially expressed or co-expressed in infected samples, in comparison with non-infected ones. Sample variability and the presence of potential biological outliers are verified using the molecular degree of perturbation approach in step 4. Finally, the functional analysis in step 5 reveals the pathways associated with the disease phenotype. The presented pipeline aims to support researchers through the RNA-seq data analysis from host-pathogen interaction studies and drive future in vitro or in vivo experiments, that are essential to understand the molecular mechanism of infections.

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Keywords High throughput Transcriptome Analysis Host pathogen Interactions Quality Control Sequencing And Annotations Statistical And Co expression Analysis Molecular Degree Of Perturbation Analysis Functional Analysis Docker Container Chikungunya Virus RNA Sequencing Reference Genome Gene Annotation

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