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Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State
Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombina...
Autores principales: | , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2757904/ https://www.ncbi.nlm.nih.gov/pubmed/19834560 http://dx.doi.org/10.1371/journal.pgen.1000692 |
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author | Gerrits, Alice Li, Yang Tesson, Bruno M. Bystrykh, Leonid V. Weersing, Ellen Ausema, Albertina Dontje, Bert Wang, Xusheng Breitling, Rainer Jansen, Ritsert C. de Haan, Gerald |
author_facet | Gerrits, Alice Li, Yang Tesson, Bruno M. Bystrykh, Leonid V. Weersing, Ellen Ausema, Albertina Dontje, Bert Wang, Xusheng Breitling, Rainer Jansen, Ritsert C. de Haan, Gerald |
author_sort | Gerrits, Alice |
collection | PubMed |
description | Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombinant inbred mouse strains. This analysis allowed us to analyze eQTL robustness/sensitivity across different cellular differentiation states. Although we identified a large number (365) of “static” eQTLs that were consistently active in all four cell types, we found a much larger number (1,283) of “dynamic” eQTLs showing cell-type–dependence. Of these, 140, 45, 531, and 295 were preferentially active in stem, progenitor, erythroid, and myeloid cells, respectively. A detailed investigation of those dynamic eQTLs showed that in many cases the eQTL specificity was associated with expression changes in the target gene. We found no evidence for target genes that were regulated by distinct eQTLs in different cell types, suggesting that large-scale changes within functional regulatory networks are uncommon. Our results demonstrate that heritable differences in gene expression are highly sensitive to the developmental stage of the cell population under study. Therefore, future genetical genomics studies should aim at studying multiple well-defined and highly purified cell types in order to construct as comprehensive a picture of the changing functional regulatory relationships as possible. |
format | Text |
id | pubmed-2757904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-27579042009-10-16 Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State Gerrits, Alice Li, Yang Tesson, Bruno M. Bystrykh, Leonid V. Weersing, Ellen Ausema, Albertina Dontje, Bert Wang, Xusheng Breitling, Rainer Jansen, Ritsert C. de Haan, Gerald PLoS Genet Research Article Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombinant inbred mouse strains. This analysis allowed us to analyze eQTL robustness/sensitivity across different cellular differentiation states. Although we identified a large number (365) of “static” eQTLs that were consistently active in all four cell types, we found a much larger number (1,283) of “dynamic” eQTLs showing cell-type–dependence. Of these, 140, 45, 531, and 295 were preferentially active in stem, progenitor, erythroid, and myeloid cells, respectively. A detailed investigation of those dynamic eQTLs showed that in many cases the eQTL specificity was associated with expression changes in the target gene. We found no evidence for target genes that were regulated by distinct eQTLs in different cell types, suggesting that large-scale changes within functional regulatory networks are uncommon. Our results demonstrate that heritable differences in gene expression are highly sensitive to the developmental stage of the cell population under study. Therefore, future genetical genomics studies should aim at studying multiple well-defined and highly purified cell types in order to construct as comprehensive a picture of the changing functional regulatory relationships as possible. Public Library of Science 2009-10-16 /pmc/articles/PMC2757904/ /pubmed/19834560 http://dx.doi.org/10.1371/journal.pgen.1000692 Text en Gerrits et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Gerrits, Alice Li, Yang Tesson, Bruno M. Bystrykh, Leonid V. Weersing, Ellen Ausema, Albertina Dontje, Bert Wang, Xusheng Breitling, Rainer Jansen, Ritsert C. de Haan, Gerald Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State |
title | Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State |
title_full | Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State |
title_fullStr | Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State |
title_full_unstemmed | Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State |
title_short | Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State |
title_sort | expression quantitative trait loci are highly sensitive to cellular differentiation state |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2757904/ https://www.ncbi.nlm.nih.gov/pubmed/19834560 http://dx.doi.org/10.1371/journal.pgen.1000692 |
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