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

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 individua...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Paola Forabosco [verfasserIn] Mauro Pala [verfasserIn] Francesca Crobu [verfasserIn] Maria Antonietta Diana [verfasserIn] Mara Marongiu [verfasserIn] Roberto Cusano [verfasserIn] Andrea Angius [verfasserIn] Maristella Steri [verfasserIn] Valeria Orrù [verfasserIn] David Schlessinger [verfasserIn] Edoardo Fiorillo [verfasserIn] Marcella Devoto [verfasserIn] Francesco Cucca [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	immune system network analysis WGCNA lncRNA RNA-seq white blood cells

Übergeordnetes Werk:	In: Frontiers in Immunology - Frontiers Media S.A., 2011, 15(2024)
Übergeordnetes Werk:	volume:15 ; year:2024

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fimmu.2024.1350111

Katalog-ID:	DOAJ092481329

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520			\|a 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.
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allfieldsSound	10.3389/fimmu.2024.1350111 doi (DE-627)DOAJ092481329 (DE-599)DOAJ3199be89b03f4f1bac21ab97e924be4c DE-627 ger DE-627 rakwb eng RC581-607 Paola Forabosco verfasserin aut Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. immune system network analysis WGCNA lncRNA RNA-seq white blood cells Immunologic diseases. Allergy Mauro Pala verfasserin aut Francesca Crobu verfasserin aut Maria Antonietta Diana verfasserin aut Mara Marongiu verfasserin aut Roberto Cusano verfasserin aut Andrea Angius verfasserin aut Maristella Steri verfasserin aut Valeria Orrù verfasserin aut David Schlessinger verfasserin aut Edoardo Fiorillo verfasserin aut Marcella Devoto verfasserin aut Marcella Devoto verfasserin aut Francesco Cucca verfasserin aut Francesco Cucca verfasserin aut In Frontiers in Immunology Frontiers Media S.A., 2011 15(2024) (DE-627)657998354 (DE-600)2606827-8 16643224 nnns volume:15 year:2024 https://doi.org/10.3389/fimmu.2024.1350111 kostenfrei https://doaj.org/article/3199be89b03f4f1bac21ab97e924be4c kostenfrei https://www.frontiersin.org/articles/10.3389/fimmu.2024.1350111/full kostenfrei https://doaj.org/toc/1664-3224 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2024
language	English
source	In Frontiers in Immunology 15(2024) volume:15 year:2024
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topic_facet	immune system network analysis WGCNA lncRNA RNA-seq white blood cells Immunologic diseases. Allergy
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container_title	Frontiers in Immunology
authorswithroles_txt_mv	Paola Forabosco @@aut@@ Mauro Pala @@aut@@ Francesca Crobu @@aut@@ Maria Antonietta Diana @@aut@@ Mara Marongiu @@aut@@ Roberto Cusano @@aut@@ Andrea Angius @@aut@@ Maristella Steri @@aut@@ Valeria Orrù @@aut@@ David Schlessinger @@aut@@ Edoardo Fiorillo @@aut@@ Marcella Devoto @@aut@@ Francesco Cucca @@aut@@
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callnumber-first	R - Medicine
author	Paola Forabosco
spellingShingle	Paola Forabosco misc RC581-607 misc immune system misc network analysis misc WGCNA misc lncRNA misc RNA-seq misc white blood cells misc Immunologic diseases. Allergy Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset
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topic_title	RC581-607 Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset immune system network analysis WGCNA lncRNA RNA-seq white blood cells
topic	misc RC581-607 misc immune system misc network analysis misc WGCNA misc lncRNA misc RNA-seq misc white blood cells misc Immunologic diseases. Allergy
topic_unstemmed	misc RC581-607 misc immune system misc network analysis misc WGCNA misc lncRNA misc RNA-seq misc white blood cells misc Immunologic diseases. Allergy
topic_browse	misc RC581-607 misc immune system misc network analysis misc WGCNA misc lncRNA misc RNA-seq misc white blood cells misc Immunologic diseases. Allergy
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title	Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset
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title_full	Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset
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author_browse	Paola Forabosco Mauro Pala Francesca Crobu Maria Antonietta Diana Mara Marongiu Roberto Cusano Andrea Angius Maristella Steri Valeria Orrù David Schlessinger Edoardo Fiorillo Marcella Devoto Francesco Cucca
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title_sort	transcriptome organization of white blood cells through gene co-expression network analysis in a large rna-seq dataset
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title_auth	Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset
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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset
url	https://doi.org/10.3389/fimmu.2024.1350111 https://doaj.org/article/3199be89b03f4f1bac21ab97e924be4c https://www.frontiersin.org/articles/10.3389/fimmu.2024.1350111/full https://doaj.org/toc/1664-3224
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author2	Mauro Pala Francesca Crobu Maria Antonietta Diana Mara Marongiu Roberto Cusano Andrea Angius Maristella Steri Valeria Orrù David Schlessinger Edoardo Fiorillo Marcella Devoto Francesco Cucca
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up_date	2024-07-04T01:29:39.986Z
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Transcriptome organization of white blood cells through gene co-expression network analysis in a large RNA-seq dataset

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