Publicação
Partitioning stable and unstable expression level variation in cell populations
| Resumo: | Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τT, that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance R2a. Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk. |
|---|---|
| Autores principais: | Guzella, Thiago S. |
| Outros Autores: | Barreto, Vasco M.; Carneiro, Jorge |
| Assunto: | Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868984126561845248 |
|---|---|
| author | Guzella, Thiago S. |
| author2 | Barreto, Vasco M. Carneiro, Jorge |
| author2_role | author author |
| author_facet | Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge |
| author_role | author |
| contributor_name_str_mv | NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM) Centro de Estudos de Doenças Crónicas (CEDOC) PLOS - Public Library of Science RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Guzella, Thiago S.\"},{\"Person.name\":\"Barreto, Vasco M.\"},{\"Person.name\":\"Carneiro, Jorge\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM) Centro de Estudos de Doenças Crónicas (CEDOC) PLOS - Public Library of Science RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge |
| datacite.date.Accepted.fl_str_mv | 2020-08-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2020-10-17T00:19:31Z |
| datacite.date.embargoed.fl_str_mv | 2020-10-17T00:19:31Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| datacite.titles.title.fl_str_mv | Partitioning stable and unstable expression level variation in cell populations A theoretical framework and its application to the T cell receptor |
| dc.contributor.none.fl_str_mv | NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM) Centro de Estudos de Doenças Crónicas (CEDOC) PLOS - Public Library of Science RUN |
| dc.creator.none.fl_str_mv | Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge |
| dc.date.Accepted.fl_str_mv | 2020-08-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2020-10-17T00:19:31Z |
| dc.date.embargoed.fl_str_mv | 2020-10-17T00:19:31Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/105762 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| dc.title.fl_str_mv | Partitioning stable and unstable expression level variation in cell populations A theoretical framework and its application to the T cell receptor |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Phenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τT, that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance R2a. Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/6567392e-bc8f-4289-9674-ba87902a290c/download |
| id | run_e89e4b3ef015d37ff2dad3361ba8ed79 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/105762 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/105762 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Guzella, Thiago S. Barreto, Vasco M. Carneiro, Jorge |
| publishDate | 2020 |
| repo_facet_str | urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL |
| reponame_str | Repositório Institucional da UNL |
| repository_id_str | urn:repositoryAcronym:run |
| service_str_mv | urn:repositoryAcronym:run |
| spelling | engenPhenotypic variation in the copy number of gene products expressed by cells or tissues has been the focus of intense investigation. To what extent the observed differences in cellular expression levels are persistent or transient is an intriguing question. Here, we develop a quantitative framework that resolves the expression variation into stable and unstable components. The difference between the expression means in two cohorts isolated from any cell population is shown to converge to an asymptotic value, with a characteristic time, τT, that measures the timescale of the unstable dynamics. The asymptotic difference in the means, relative to the initial value, measures the stable proportion of the original population variance R2a. Empowered by this insight, we analysed the T-cell receptor (TCR) expression variation in CD4 T cells. About 70% of TCR expression variance is stable in a diverse polyclonal population, while over 80% of the variance in an isogenic TCR transgenic population is volatile. In both populations the TCR levels fluctuate with a characteristic time of 32 hours. This systematic characterisation of the expression variation dynamics, relying on time series of cohorts’ means, can be combined with technologies that measure gene or protein expression in single cells or in bulk.application/pdfenPartitioning stable and unstable expression level variation in cell populationsSubtitleenA theoretical framework and its application to the T cell receptorGuzella, Thiago S.Barreto, Vasco M.Carneiro, JorgeNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)Centro de Estudos de Doenças Crónicas (CEDOC)PLOS - Public Library of ScienceHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptISSNIsPartOf1553-734XURNIsPartOfPURE: 19991635URNIsPartOfPURE UUID: eee5f28c-3932-4411-ac6e-5cf6b3d737a9URNIsPartOfScopus: 85090768535URNIsPartOfPubMed: 32841238URNIsPartOfWOS: 000565612000001DOIIsPartOf10.1371/journal.pcbi.10079102020-10-17T00:19:31Z2020-082020-08-01T00:00:00ZHandlehttp://hdl.handle.net/10362/105762http://purl.org/coar/access_right/c_abf2open accessEcology, Evolution, Behavior and SystematicsModelling and SimulationEcologyMolecular BiologyGeneticsCellular and Molecular NeuroscienceComputational Theory and Mathematics2830255 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/6567392e-bc8f-4289-9674-ba87902a290c/download |
| spellingShingle | Partitioning stable and unstable expression level variation in cell populations Guzella, Thiago S. Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| status | SINGLETON |
| subject.fl_str_mv | Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| title | Partitioning stable and unstable expression level variation in cell populations |
| title_full | Partitioning stable and unstable expression level variation in cell populations |
| title_fullStr | Partitioning stable and unstable expression level variation in cell populations |
| title_full_unstemmed | Partitioning stable and unstable expression level variation in cell populations |
| title_short | Partitioning stable and unstable expression level variation in cell populations |
| title_sort | Partitioning stable and unstable expression level variation in cell populations |
| topic | Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| topic_facet | Ecology, Evolution, Behavior and Systematics Modelling and Simulation Ecology Molecular Biology Genetics Cellular and Molecular Neuroscience Computational Theory and Mathematics |
| url | http://hdl.handle.net/10362/105762 |
| visible | 1 |