Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data

Matthew C Altman; Darawan Rinchai; Nicole Baldwin; Mohammed Toufiq; Elizabeth Whalen; Mathieu Garand; Basirudeen Syed Ahamed Kabeer; Mohamed Alfaki; Scott R Presnell; Prasong Khaenam; Aaron Ayllón-Benítez; Fleur Mougin; Patricia Thébault; Laurent Chiche; Noemie Jourde-Chiche; J Theodore Phillips; Goran Klintmalm; Anne O'Garra; Matthew Berry; Chloe Bloom; Robert J Wilkinson; Christine M Graham; Marc Lipman; Ganjana Lertmemongkolchai; Davide Bedognetti; Rodolphe Thiebaut; Farrah Kheradmand; Asuncion Mejias; Octavio Ramilo; Karolina Palucka; Virginia Pascual; Jacques Banchereau; Damien Chaussabel

doi:10.1038/s41467-021-24584-w

Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data

Nat Commun. 2021 Jul 19;12(1):4385. doi: 10.1038/s41467-021-24584-w.

Authors

Matthew C Altman^#^{1

2}, Darawan Rinchai^#³, Nicole Baldwin⁴, Mohammed Toufiq⁵, Elizabeth Whalen⁶, Mathieu Garand⁵, Basirudeen Syed Ahamed Kabeer⁵, Mohamed Alfaki⁵, Scott R Presnell⁶, Prasong Khaenam⁶, Aaron Ayllón-Benítez⁷, Fleur Mougin⁷, Patricia Thébault⁸, Laurent Chiche⁹, Noemie Jourde-Chiche¹⁰, J Theodore Phillips⁴, Goran Klintmalm⁴, Anne O'Garra^{11

12}, Matthew Berry¹³, Chloe Bloom¹², Robert J Wilkinson^{14

15

16}, Christine M Graham¹¹, Marc Lipman¹⁷, Ganjana Lertmemongkolchai¹⁸, Davide Bedognetti⁵, Rodolphe Thiebaut⁷, Farrah Kheradmand¹⁹, Asuncion Mejias²⁰, Octavio Ramilo²⁰, Karolina Palucka^{4

21}, Virginia Pascual^{4

22}, Jacques Banchereau^{4

21}, Damien Chaussabel^{23

24}

Affiliations

¹ Systems Immunology, Benaroya Research Institute, Seattle, WA, USA. [email protected].
² Division of Allergy and Infectious Diseases, University of Washington, Seattle, WA, USA. [email protected].
³ Research Branch, Sidra Medicine, Doha, Qatar. [email protected].
⁴ Baylor Institute for Immunology Research, Baylor Research Institute, Dallas, TX, USA.
⁵ Research Branch, Sidra Medicine, Doha, Qatar.
⁶ Systems Immunology, Benaroya Research Institute, Seattle, WA, USA.
⁷ Inserm U1219 Bordeaux Population Health Research Center, Bordeaux University, Bordeaux, France.
⁸ LaBRI, CNRS UMR5800, Bordeaux University, Bordeaux, France.
⁹ Department of Internal Medicine, Hopital Européen, Marseille, France.
¹⁰ Aix-Marseille University, C2VN, INSERM 1263, INRA 1260, Marseille, France.
¹¹ Laboratory of Immunoregulation and Infection, The Francis Crick Institute, London, UK.
¹² National Heart and Lung Institute, Imperial College London, London, UK.
¹³ Royal Cornwall Hospitals NHS Trust, Truro, UK.
¹⁴ The Francis Crick Institute, London, UK.
¹⁵ Department of Infectious Disease, Imperial College, London, UK.
¹⁶ Wellcome Center for Infectious Diseases Research in Africa and Department of Medicine, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town Observatory, 7925, Cape Town, Republic of South Africa.
¹⁷ UCL Respiratory, Division of Medicine, University College London, London, UK.
¹⁸ Centre for Research and Development of Medical Diagnostic Laboratories, Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand.
¹⁹ Baylor College of Medicine & Center for Translational Research on Inflammatory Diseases, Michael E. DeBakey VAMC, Houston, TX, USA.
²⁰ Abigail Wexner Research Institute at Nationwide Children's Hospital and the Ohio State University School of Medicine, Columbus, OH, USA.
²¹ The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
²² Weill Cornell Medicine, New York, NY, USA.
²³ Systems Immunology, Benaroya Research Institute, Seattle, WA, USA. [email protected].
²⁴ Research Branch, Sidra Medicine, Doha, Qatar. [email protected].

^# Contributed equally.

Abstract

As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via: https://drinchai.shinyapps.io/BloodGen3Module/ .

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Bacteria
Blood Chemical Analysis* / methods
Blood* / immunology
Cluster Analysis
Computational Biology / methods
Gene Expression Profiling / methods*
Gene Regulatory Networks
Humans
Transcriptome*

Abstract

Publication types

MeSH terms

Grants and funding