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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...

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Autores principales: Ferrari, Francesco, Bortoluzzi, Stefania, Coppe, Alessandro, Basso, Dario, Bicciato, Silvio, Zini, Roberta, Gemelli, Claudia, Danieli, Gian Antonio, Ferrari, Sergio
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
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.
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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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