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Genomic expression during human myelopoiesis
BACKGROUND: Human myelopoiesis is an exciting biological model for cellular differentiation since it represents a plastic process where multipotent stem cells gradually limit their differentiation potential, generating different precursor cells which finally evolve into distinct terminally different...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2045681/ https://www.ncbi.nlm.nih.gov/pubmed/17683550 http://dx.doi.org/10.1186/1471-2164-8-264 |
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author | Ferrari, Francesco Bortoluzzi, Stefania Coppe, Alessandro Basso, Dario Bicciato, Silvio Zini, Roberta Gemelli, Claudia Danieli, Gian Antonio Ferrari, Sergio |
author_facet | Ferrari, Francesco Bortoluzzi, Stefania Coppe, Alessandro Basso, Dario Bicciato, Silvio Zini, Roberta Gemelli, Claudia Danieli, Gian Antonio Ferrari, Sergio |
author_sort | Ferrari, Francesco |
collection | PubMed |
description | BACKGROUND: Human myelopoiesis is an exciting biological model for cellular differentiation since it represents a plastic process where multipotent stem cells gradually limit their differentiation potential, generating different precursor cells which finally evolve into distinct terminally differentiated cells. This study aimed at investigating the genomic expression during myeloid differentiation through a computational approach that integrates gene expression profiles with functional information and genome organization. RESULTS: Gene expression data from 24 experiments for 8 different cell types of the human myelopoietic lineage were used to generate an integrated myelopoiesis dataset of 9,425 genes, each reliably associated to a unique genomic position and chromosomal coordinate. Lists of genes constitutively expressed or silent during myelopoiesis and of genes differentially expressed in commitment phase of myelopoiesis were first identified using a classical data analysis procedure. Then, the genomic distribution of myelopoiesis genes was investigated integrating transcriptional and functional characteristics of genes. This approach allowed identifying specific chromosomal regions significantly highly or weakly expressed, and clusters of differentially expressed genes and of transcripts related to specific functional modules. CONCLUSION: The analysis of genomic expression during human myelopoiesis using an integrative computational approach allowed discovering important relationships between genomic position, biological function and expression patterns and highlighting chromatin domains, including genes with coordinated expression and lineage-specific functions. |
format | Text |
id | pubmed-2045681 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-20456812007-10-31 Genomic expression during human myelopoiesis Ferrari, Francesco Bortoluzzi, Stefania Coppe, Alessandro Basso, Dario Bicciato, Silvio Zini, Roberta Gemelli, Claudia Danieli, Gian Antonio Ferrari, Sergio BMC Genomics Research Article BACKGROUND: Human myelopoiesis is an exciting biological model for cellular differentiation since it represents a plastic process where multipotent stem cells gradually limit their differentiation potential, generating different precursor cells which finally evolve into distinct terminally differentiated cells. This study aimed at investigating the genomic expression during myeloid differentiation through a computational approach that integrates gene expression profiles with functional information and genome organization. RESULTS: Gene expression data from 24 experiments for 8 different cell types of the human myelopoietic lineage were used to generate an integrated myelopoiesis dataset of 9,425 genes, each reliably associated to a unique genomic position and chromosomal coordinate. Lists of genes constitutively expressed or silent during myelopoiesis and of genes differentially expressed in commitment phase of myelopoiesis were first identified using a classical data analysis procedure. Then, the genomic distribution of myelopoiesis genes was investigated integrating transcriptional and functional characteristics of genes. This approach allowed identifying specific chromosomal regions significantly highly or weakly expressed, and clusters of differentially expressed genes and of transcripts related to specific functional modules. CONCLUSION: The analysis of genomic expression during human myelopoiesis using an integrative computational approach allowed discovering important relationships between genomic position, biological function and expression patterns and highlighting chromatin domains, including genes with coordinated expression and lineage-specific functions. BioMed Central 2007-08-03 /pmc/articles/PMC2045681/ /pubmed/17683550 http://dx.doi.org/10.1186/1471-2164-8-264 Text en Copyright © 2007 Ferrari et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ferrari, Francesco Bortoluzzi, Stefania Coppe, Alessandro Basso, Dario Bicciato, Silvio Zini, Roberta Gemelli, Claudia Danieli, Gian Antonio Ferrari, Sergio Genomic expression during human myelopoiesis |
title | Genomic expression during human myelopoiesis |
title_full | Genomic expression during human myelopoiesis |
title_fullStr | Genomic expression during human myelopoiesis |
title_full_unstemmed | Genomic expression during human myelopoiesis |
title_short | Genomic expression during human myelopoiesis |
title_sort | genomic expression during human myelopoiesis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2045681/ https://www.ncbi.nlm.nih.gov/pubmed/17683550 http://dx.doi.org/10.1186/1471-2164-8-264 |
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