The understanding of the genetic basis of the Parkinson's disease (PD) and the correlation between genotype and phenotype has revolutionized our knowledge about the pathogenetic mechanisms of neurodegeneration, opening up exciting new therapeutic and neuroprotective perspectives. Genomic knowledge of PD is still in its early stages and can provide a good start for studies of the molecular mechanisms that underlie the gene expression variations and the epigenetic mechanisms that may contribute to the complex and characteristic phenotype of PD. In this study we used the software TRAM (Transcriptome Mapper) to analyse publicly available microarray data of a total of 151 PD patients and 130 healthy controls substantia nigra (SN) samples, to identify chromosomal segments and gene loci differential expression. In particular, we separately analyzed PD patients and controls data from post-mortem snap-frozen SN whole tissue and from laser microdissected midbrain dopamine (DA) neurons, to better characterize the specific DA neuronal expression profile associated with the late-stage Parkinson's condition. The default "Map" mode analysis resulted in 10 significantly over/under-expressed segments, mapping on 8 different chromosomes for SN whole tissue and in 4 segments mapping on 4 different chromosomes for DA neurons. In conclusion, TRAM software allowed us to confirm the deregulation of some genomic regions and loci involved in key molecular pathways related to neurodegeneration, as well as to provide new insights about genes and non-coding RNA transcripts not yet associated with the disease.

Meta-analysis of Parkinson's disease transcriptome data using TRAM software: Whole substantia nigra tissue and single dopamine neuron differential gene expression / Mariani, Elisa; Frabetti, Flavia; Tarozzi, Andrea; Pelleri, Maria Chiara; Pizzetti, Fabrizio; Casadei, Raffaella. - In: PLOS ONE. - ISSN 1932-6203. - ELETTRONICO. - 11:9(2016), pp. 0161567-0161567. [10.1371/journal.pone.0161567]

Meta-analysis of Parkinson's disease transcriptome data using TRAM software: Whole substantia nigra tissue and single dopamine neuron differential gene expression

MARIANI, ELISA;FRABETTI, FLAVIA;TAROZZI, ANDREA;PELLERI, MARIA CHIARA;PIZZETTI, FABRIZIO;CASADEI, RAFFAELLA
2016

Abstract

The understanding of the genetic basis of the Parkinson's disease (PD) and the correlation between genotype and phenotype has revolutionized our knowledge about the pathogenetic mechanisms of neurodegeneration, opening up exciting new therapeutic and neuroprotective perspectives. Genomic knowledge of PD is still in its early stages and can provide a good start for studies of the molecular mechanisms that underlie the gene expression variations and the epigenetic mechanisms that may contribute to the complex and characteristic phenotype of PD. In this study we used the software TRAM (Transcriptome Mapper) to analyse publicly available microarray data of a total of 151 PD patients and 130 healthy controls substantia nigra (SN) samples, to identify chromosomal segments and gene loci differential expression. In particular, we separately analyzed PD patients and controls data from post-mortem snap-frozen SN whole tissue and from laser microdissected midbrain dopamine (DA) neurons, to better characterize the specific DA neuronal expression profile associated with the late-stage Parkinson's condition. The default "Map" mode analysis resulted in 10 significantly over/under-expressed segments, mapping on 8 different chromosomes for SN whole tissue and in 4 segments mapping on 4 different chromosomes for DA neurons. In conclusion, TRAM software allowed us to confirm the deregulation of some genomic regions and loci involved in key molecular pathways related to neurodegeneration, as well as to provide new insights about genes and non-coding RNA transcripts not yet associated with the disease.
2016
Meta-analysis of Parkinson's disease transcriptome data using TRAM software: Whole substantia nigra tissue and single dopamine neuron differential gene expression / Mariani, Elisa; Frabetti, Flavia; Tarozzi, Andrea; Pelleri, Maria Chiara; Pizzetti, Fabrizio; Casadei, Raffaella. - In: PLOS ONE. - ISSN 1932-6203. - ELETTRONICO. - 11:9(2016), pp. 0161567-0161567. [10.1371/journal.pone.0161567]
Mariani, Elisa; Frabetti, Flavia; Tarozzi, Andrea; Pelleri, Maria Chiara; Pizzetti, Fabrizio; Casadei, Raffaella
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/569855
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