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Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells

Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS inte...

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Autores principales: Pelleri, Maria Chiara, Cattani, Chiara, Vitale, Lorenza, Antonaros, Francesca, Strippoli, Pierluigi, Locatelli, Chiara, Cocchi, Guido, Piovesan, Allison, Caracausi, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5928158/
https://www.ncbi.nlm.nih.gov/pubmed/29740474
http://dx.doi.org/10.3389/fgene.2018.00125
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author Pelleri, Maria Chiara
Cattani, Chiara
Vitale, Lorenza
Antonaros, Francesca
Strippoli, Pierluigi
Locatelli, Chiara
Cocchi, Guido
Piovesan, Allison
Caracausi, Maria
author_facet Pelleri, Maria Chiara
Cattani, Chiara
Vitale, Lorenza
Antonaros, Francesca
Strippoli, Pierluigi
Locatelli, Chiara
Cocchi, Guido
Piovesan, Allison
Caracausi, Maria
author_sort Pelleri, Maria Chiara
collection PubMed
description Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues.
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spelling pubmed-59281582018-05-08 Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells Pelleri, Maria Chiara Cattani, Chiara Vitale, Lorenza Antonaros, Francesca Strippoli, Pierluigi Locatelli, Chiara Cocchi, Guido Piovesan, Allison Caracausi, Maria Front Genet Genetics Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues. Frontiers Media S.A. 2018-04-24 /pmc/articles/PMC5928158/ /pubmed/29740474 http://dx.doi.org/10.3389/fgene.2018.00125 Text en Copyright © 2018 Pelleri, Cattani, Vitale, Antonaros, Strippoli, Locatelli, Cocchi, Piovesan and Caracausi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Pelleri, Maria Chiara
Cattani, Chiara
Vitale, Lorenza
Antonaros, Francesca
Strippoli, Pierluigi
Locatelli, Chiara
Cocchi, Guido
Piovesan, Allison
Caracausi, Maria
Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
title Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
title_full Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
title_fullStr Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
title_full_unstemmed Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
title_short Integrated Quantitative Transcriptome Maps of Human Trisomy 21 Tissues and Cells
title_sort integrated quantitative transcriptome maps of human trisomy 21 tissues and cells
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5928158/
https://www.ncbi.nlm.nih.gov/pubmed/29740474
http://dx.doi.org/10.3389/fgene.2018.00125
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