Evidence map›Paper›PMID 38629067›Full record

ArticleFrontiers in immunology2024

Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset.

Paola Forabosco, Mauro Pala, Francesca Crobu, Maria Antonietta Diana, Mara Marongiu, Roberto Cusano, Andrea Angius, Maristella Steri, Valeria Orrù, David Schlessinger and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 34% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

13 authors at 3 institutions in 2 countries.

Paola ForaboscoIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Mauro PalaIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Francesca CrobuIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Maria Antonietta DianaIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Mara MarongiuIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Roberto CusanoCRS4-Next Generation Sequencing (NGS) Core, Parco POLARIS, Cagliari, Italy.
Andrea AngiusIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Maristella SteriIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Valeria OrrùIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
David SchlessingerLaboratory of Genetics and Genomics, National Institute on Aging, National Institutes of Health (NIH), Baltimore, MA, United States.
Edoardo FiorilloIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Marcella DevotoIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Francesco CuccaIstituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
Institute of Genetic and Biomedical Research · ITNational Institute on Aging · USSardegna Ricerche (Italy) · IT

Funding

NIDA NIH HHS HHSN271201100005C
6 · The paper itself

Abstract

Gene co-expression network analysis enables identification of biologically meaningful clusters of co-regulated genes (modules) in an unsupervised manner. We present here the largest study conducted thus far of co-expression networks in white blood cells (WBC) based on RNA-seq data from 624 individuals. We identify 41 modules, 13 of them related to specific immune-related functions and cell types (e.g. neutrophils, B and T cells, NK cells, and plasmacytoid dendritic cells); we highlight biologically relevant lncRNAs for each annotated module of co-expressed genes. We further characterize with unprecedented resolution the modules in T cell sub-types, through the availability of 95 immune phenotypes obtained by flow cytometry in the same individuals. This study provides novel insights into the transcriptional architecture of human leukocytes, showing how network analysis can advance our understanding of coding and non-coding gene interactions in immune system cells.

Indexed as

Gene Regulatory NetworksTranscriptomeGene Expression ProfilingHumansLeukocytesRNA-Seqimmune systemlncRNAnetwork analysisRNA-seqWGCNAwhite blood cells

Identifiers

PMID38629067
PMCPMC11018966
OpenAlexW4393442526

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.