Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Michael D. Morgan; Etienne Patin; Bernd Jagla; Milena Hasan; Lluís Quintana-Murci; John C. Marioni

doi:10.1371/journal.pgen.1008686

Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Michael D. Morgan^* (Corresponding Author), Etienne Patin, Bernd Jagla, Milena Hasan, Lluís Quintana-Murci, John C. Marioni^* (Corresponding Author)

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

Identifying the factors that shape protein expression variability in complex multi-cellular
organisms has primarily focused on promoter architecture and regulation of single-cell
expression in cis. However, this targeted approach has to date been unable to identify major
regulators of cell-to-cell gene expression variability in humans. To address this, we have
combined single-cell protein expression measurements in the human immune system using
flow cytometry with a quantitative genetics analysis. For the majority of proteins whose vari-
ability in expression has a heritable component, we find that genetic variants act in trans,
with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Ran-
domization that these variability-Quantitative Trait Loci might be driven by the cis regulation
of upstream genes. This indicates that natural selection may balance the impact of gene
regulation in cis with downstream impacts on expression variability in trans.

Original language	English
Article number	e1008686.
Number of pages	19
Journal	PLoS Genetics
Volume	16
Issue number	3
Early online date	13 Mar 2020
DOIs	https://doi.org/10.1371/journal.pgen.1008686
Publication status	Published - Mar 2020

Bibliographical note

The authors wish to thank Dr Arianne Richard and Dr Luis Barreiro for their critical reading of the manuscript. The authors also wish to extend their gratitude to TwinsUK for sharing data. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London.

Data Availability Statement

Genotype data from the Milieu Intérieur cohort are available via managed access in the European Genome-Phenome Archive (EGAD00010001489). TwinsUK genotype data are available by approval via the TwinsUK data access committee (https://twinsuk.ac.uk/). All summary statistics are publicly available via:https://content.cruk.cam.ac.uk/jmlab/VariabilityGenetics/. Processing and analysis code are publicly available via https://github.com/MarioniLab/VariabilityGenetics2019.

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title = "Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels",

abstract = "Identifying the factors that shape protein expression variability in complex multi-cellularorganisms has primarily focused on promoter architecture and regulation of single-cellexpression in cis. However, this targeted approach has to date been unable to identify majorregulators of cell-to-cell gene expression variability in humans. To address this, we havecombined single-cell protein expression measurements in the human immune system usingflow cytometry with a quantitative genetics analysis. For the majority of proteins whose vari-ability in expression has a heritable component, we find that genetic variants act in trans,with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Ran-domization that these variability-Quantitative Trait Loci might be driven by the cis regulationof upstream genes. This indicates that natural selection may balance the impact of generegulation in cis with downstream impacts on expression variability in trans.",

author = "Morgan, {Michael D.} and Etienne Patin and Bernd Jagla and Milena Hasan and Llu{\'i}s Quintana-Murci and Marioni, {John C.}",

note = "The authors wish to thank Dr Arianne Richard and Dr Luis Barreiro for their critical reading of the manuscript. The authors also wish to extend their gratitude to TwinsUK for sharing data. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy{\textquoteright}s and St Thomas{\textquoteright} NHS Foundation Trust in partnership with King{\textquoteright}s College London.",

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AU - Quintana-Murci, Lluís

AU - Marioni, John C.

N1 - The authors wish to thank Dr Arianne Richard and Dr Luis Barreiro for their critical reading of the manuscript. The authors also wish to extend their gratitude to TwinsUK for sharing data. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London.

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Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels

Abstract

Bibliographical note

Data Availability Statement

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