Evidence map›Paper›PMID 39900759›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

RNA-Seq and Gene Set Enrichment Analysis (GSEA) in Peripheral Blood Mononuclear Cells (PBMCs).

Fayuan Wen, Namita Kumari, James G Taylor Vi

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fayuan WenDepartment of Biology, Howard University, Washington, DC, USA.
Namita KumariCenter for Sickle Cell Disease Howard University College of Medicine, Washington, DC, USA.
James G Taylor ViCenter for Sickle Cell Disease Howard University College of Medicine, Washington, DC, USA. james.taylor2@howard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA sequencing (RNA-Seq) and analysis methods like gene set enrichment analysis (GSEA) stand at the forefront of modern molecular biology, offering unparalleled insights into gene expression dynamics and transcriptomic landscapes. In this chapter, we focus on the application of RNA-Seq technology and the GSEA method. First, we provide a real-world workflow for RNA-Seq to unravel the intricate interplay between host factors and HIV-1 infection within peripheral blood mononuclear cells (PBMCs). We elucidate the core principles of RNA-Seq and its pivotal role in identifying HIV-1 restriction factors and understanding their regulatory mechanisms in PBMCs. We provide the essential steps of the RNA-Seq workflow tailored to PBMCs, encompassing sample preparation, library construction, sequencing, and advanced bioinformatics. We underscore how RNA-Seq enables precise quantification of gene expression levels, detection of alternative splicing, and exploration of novel transcripts pertinent to HIV-1 restriction. Moreover, we delve into the intricacies of HIV-1 restriction factor discovery using RNA-Seq data, shedding light on the diverse repertoire of PBMC host defense mechanisms. We discuss the challenges of RNA-Seq data analysis, including normalization, differential expression analysis, and the integration of multi-omics datasets, and propose strategies to mitigate these barriers. Next, we provide an overview of GSEA, a powerful computational method that extends beyond traditional differential gene expression analysis. This tool can provide deeper insights into the functional significance of gene expression changes. By leveraging curated gene sets representing biological pathways, molecular functions, or cellular processes, GSEA enables the identification of coordinated changes in gene expression within predefined gene sets. In our example, we applied GSEA in transcriptomic studies, highlighting its ability to uncover subtle yet coordinated changes in gene expression that may not be evident by individual gene analysis. We demonstrate how GSEA enhances our understanding of complex biological phenomena, informs hypothesis generation, and identifies potential therapeutic targets. Overall, RNA-Seq and GSEA are indispensable tools for elucidating the complex interactions in host cells altered by physiologic processes, disease states or infectious agents like HIV-1, thereby advancing our ability to identify potential targets for therapeutic interventions.

Indexed as

Computational BiologyLeukocytes, MononuclearRNA-SeqSequence Analysis, RNAGene Expression ProfilingHigh-Throughput Nucleotide SequencingHIV-1HIV InfectionsHumansTranscriptomeWorkflowDifferential gene expression analysisGene Set Enrichment Analysis (GSEA)HIV-1Peripheral blood mononuclear cells (PBMCs)RNA sequencing (RNA-Seq)

Identifiers

PMID39900759

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.