We performed an innovative systematic meta-analysis of 60 gene expression profiles of whole normal human brain, to provide a quantitative transcriptome reference map of it, i.e. a reference typical value of expression for each of the 39,250 known, mapped and 26,026 uncharacterized (unmapped) transcripts. To this aim, we used the software named Transcriptome Mapper (TRAM), which is able to generate transcriptome maps based on gene expression data from multiple sources. We also analyzed differential expression by comparing the brain transcriptome with those derived from human foetal brain gene expression, from a pool of human tissues (except the brain) and from the two normal human brain regions cerebellum and cerebral cortex, which are two of the main regions severely affected when cognitive impairment occurs, as happens in the case of trisomy 21. Data were downloaded from microarray databases, processed and analyzed using TRAM software and validated in vitro by assaying gene expression through several magnitude orders by ‘real-time’ reverse transcription polymerase chain reaction (RT-PCR). The excellent agreement between in silico and experimental data suggested that our transcriptome maps may be a useful quantitative reference benchmark for gene expression studies related to the human brain. Furthermore, our analysis yielded biological insights about those genes which have an intrinsic over-/under-expression in the brain, in addition offering a basis for the regional analysis of gene expression. This could be useful for the study of chromosomal alterations associated to cognitive impairment, such as trisomy 21, the most common genetic cause of intellectual disability.

A quantitative transcriptome reference map of the normal human brain / Caracausi M; Vitale L; Pelleri MC; Piovesan A; Bruno S; Strippoli P. - In: NEUROGENETICS. - ISSN 1364-6745. - STAMPA. - 15:4(2014), pp. 267-287. [10.1007/s10048-014-0419-8]

A quantitative transcriptome reference map of the normal human brain

CARACAUSI, MARIA;VITALE, LORENZA;PELLERI, MARIA CHIARA;PIOVESAN, ALLISON;BRUNO, SAMANTHA;STRIPPOLI, PIERLUIGI
2014

Abstract

We performed an innovative systematic meta-analysis of 60 gene expression profiles of whole normal human brain, to provide a quantitative transcriptome reference map of it, i.e. a reference typical value of expression for each of the 39,250 known, mapped and 26,026 uncharacterized (unmapped) transcripts. To this aim, we used the software named Transcriptome Mapper (TRAM), which is able to generate transcriptome maps based on gene expression data from multiple sources. We also analyzed differential expression by comparing the brain transcriptome with those derived from human foetal brain gene expression, from a pool of human tissues (except the brain) and from the two normal human brain regions cerebellum and cerebral cortex, which are two of the main regions severely affected when cognitive impairment occurs, as happens in the case of trisomy 21. Data were downloaded from microarray databases, processed and analyzed using TRAM software and validated in vitro by assaying gene expression through several magnitude orders by ‘real-time’ reverse transcription polymerase chain reaction (RT-PCR). The excellent agreement between in silico and experimental data suggested that our transcriptome maps may be a useful quantitative reference benchmark for gene expression studies related to the human brain. Furthermore, our analysis yielded biological insights about those genes which have an intrinsic over-/under-expression in the brain, in addition offering a basis for the regional analysis of gene expression. This could be useful for the study of chromosomal alterations associated to cognitive impairment, such as trisomy 21, the most common genetic cause of intellectual disability.
2014
A quantitative transcriptome reference map of the normal human brain / Caracausi M; Vitale L; Pelleri MC; Piovesan A; Bruno S; Strippoli P. - In: NEUROGENETICS. - ISSN 1364-6745. - STAMPA. - 15:4(2014), pp. 267-287. [10.1007/s10048-014-0419-8]
Caracausi M; Vitale L; Pelleri MC; Piovesan A; Bruno S; Strippoli P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/379086
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