Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation
Human Multipotent Stromal Cells (MSCs) are a valuable resource for regenerative medicine and are widely studied. They can be isolated from a variety of tissues and differentiate into multiple cell types (multi-potent). Many reports have been published using human MSCs and to be able to compare outco...
Main Authors: | , , , , , |
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Format: | Journal article |
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Public Library of Science
2018
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_version_ | 1797084730649214976 |
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author | Brinkhof, B Jia, H Zhang, B Cui, Z Ye, H Wang, H |
author_facet | Brinkhof, B Jia, H Zhang, B Cui, Z Ye, H Wang, H |
author_sort | Brinkhof, B |
collection | OXFORD |
description | Human Multipotent Stromal Cells (MSCs) are a valuable resource for regenerative medicine and are widely studied. They can be isolated from a variety of tissues and differentiate into multiple cell types (multi-potent). Many reports have been published using human MSCs and to be able to compare outcome, or be able to identify differences between MSCs, several cell surface markers have been proposed. Nevertheless, still many differences remain. Gene expression is known to be different between cell stage and origin. Furthermore, cells cultured on a culture dish (2D) show different gene expression profiles as compared to cells grown on scaffolds (3D). Even the RNA extraction method and the selection of genes used for normalisation have a role in gene expression profiling. To be able to compare gene expression data from samples cultured in different dimensions and RNA extracted using a variety of protocols we set out to define a set of reference genes suitable to normalise qPCR data from a very heterogeneous sample set. Hereto, Trizol was used to extract RNA from human MSCs cultured in 3D and 2D to validate newly designed and previously published primer sets. Subsequently, RNA from fresh human MSC samples and samples stored in RLT-buffer, Trizol or RNAlater was extracted using RNeasy and Trizol methods. All samples have been used to rank the candidate reference genes according to their stability after qPCR enabling identification of the most suitable reference gene(s) for normalisation of a heterogeneous sample set. The most stably expressed reference genes indicated superior normalisation of MSC marker gene expression over the least stable reference genes. |
first_indexed | 2024-03-07T01:59:06Z |
format | Journal article |
id | oxford-uuid:9cba843a-8a95-4864-a330-0e67cacfb79e |
institution | University of Oxford |
last_indexed | 2024-03-07T01:59:06Z |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | dspace |
spelling | oxford-uuid:9cba843a-8a95-4864-a330-0e67cacfb79e2022-03-27T00:38:03ZImproving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9cba843a-8a95-4864-a330-0e67cacfb79eSymplectic Elements at OxfordPublic Library of Science2018Brinkhof, BJia, HZhang, BCui, ZYe, HWang, HHuman Multipotent Stromal Cells (MSCs) are a valuable resource for regenerative medicine and are widely studied. They can be isolated from a variety of tissues and differentiate into multiple cell types (multi-potent). Many reports have been published using human MSCs and to be able to compare outcome, or be able to identify differences between MSCs, several cell surface markers have been proposed. Nevertheless, still many differences remain. Gene expression is known to be different between cell stage and origin. Furthermore, cells cultured on a culture dish (2D) show different gene expression profiles as compared to cells grown on scaffolds (3D). Even the RNA extraction method and the selection of genes used for normalisation have a role in gene expression profiling. To be able to compare gene expression data from samples cultured in different dimensions and RNA extracted using a variety of protocols we set out to define a set of reference genes suitable to normalise qPCR data from a very heterogeneous sample set. Hereto, Trizol was used to extract RNA from human MSCs cultured in 3D and 2D to validate newly designed and previously published primer sets. Subsequently, RNA from fresh human MSC samples and samples stored in RLT-buffer, Trizol or RNAlater was extracted using RNeasy and Trizol methods. All samples have been used to rank the candidate reference genes according to their stability after qPCR enabling identification of the most suitable reference gene(s) for normalisation of a heterogeneous sample set. The most stably expressed reference genes indicated superior normalisation of MSC marker gene expression over the least stable reference genes. |
spellingShingle | Brinkhof, B Jia, H Zhang, B Cui, Z Ye, H Wang, H Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation |
title | Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation |
title_full | Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation |
title_fullStr | Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation |
title_full_unstemmed | Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation |
title_short | Improving characterisation of human Multipotent Stromal Cells cultured in 2D and 3D: Design and evaluation of primer sets for accurate gene expression normalisation |
title_sort | improving characterisation of human multipotent stromal cells cultured in 2d and 3d design and evaluation of primer sets for accurate gene expression normalisation |
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