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.

In humans, sexual dimorphism can manifest in many ways and it is widely studied in several knowledge fields. It is increasing the evidence that also cells differ according to sex, a correlation still little studied and poorly considered when cells are used in scientific research. Specifically, our interest is on the sex-related dimorphism on the human mesenchymal stem cells (hMSCs) transcriptome. A systematic meta-analysis of hMSC microarrays was performed by using the Transcriptome Mapper (TRAM) software. This bioinformatic tool was used to integrate and normalize datasets from multiple sources and allowed us to highlight chromosomal segments and genes differently expressed in hMSCs derived from adipose tissue (hADSCs) of male and female donors. Chromosomal segments and differentially expressed genes in male and female hADSCs resulted to be related to several processes as inflammation, adipogenic and neurogenic differentiation and cell communication. Obtained results lead us to hypothesize that the donor sex of hADSCs is a variable influencing a wide range of stem cell biologic processes. We believe that it should be considered in biologic research and stem cell therapy.

Background: Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input. Results: TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified. Conclusions: TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.

Parkinson’s disease (PD) is one of the most common progressive neurodegenerative diseases. Clinical and epidemiological studies indicate that sex differences, as well as genetic components and ageing, can influence the prevalence, age at onset and symptomatology of PD. This study undertook a systematic meta-analysis of substantia nigra microarray data using the Transcriptome Mapper (TRAM) software to integrate and normalize a total of 10 suitable datasets from multiple sources. Four different analyses were performed according to default parameters, to better define the segments differentially expressed between PD patients and healthy controls, when comparing men and women data sets. The results suggest a possible regulation of specific sex-biased systems in PD susceptibility. TRAM software allowed us to highlight the different activation of some genomic regions and loci involved in molecular pathways related to neurodegeneration and neuroinflammatory mechanisms.

Cellular senescence plays a very important role in organismal aging increasing with age and in age-related diseases (ARDs). This process involves physiological, structural, biochemical, and molecular changes of cells, leading to a characteristic trait referred to “senescence-associated secretory phenotype (SASP).” In particular, with aging, stem cells (SCs) in situ exhibit a diminished capacity of self-renewal and show a decline in their functionality. The identification of interventions able to prevent the accumulation of senescent SCs in the organism or to pretreat cultured multipotent mesenchymal stromal cells (MSCs) prior to employing them for cell therapy is a main purpose of medical research. Many approaches have been investigated and resulted effective to prevent or counteract SC senescence in humans, as well as other animal models. In this work, we have reviewed the chance of using a number of herb-derived products as novel tools in the treatment of cell senescence, highlighting the efficacy of these agents, often still far from being clearly understood.

Microglia represent the primary immune defense system within the central nervous system and play a role in the inflammatory processes occurring in numerous disorders, such as Parkinson’s disease (PD). PD onset and progression are associated with factors considered possible causes of neuroinflammation, i.e. genetic mutations. In vitro models of microglial cells were established to identify specific molecular targets in PD through the analysis of gene expression data. Recently, the Human Microglial Clone 3 cell line (HMC3) has been characterized and a new human microglia model has emerged. Here we perform RT-qPCR analyses to evaluate the expression of ten reference genes in HMC3, untreated or stimulated to a pro-inflammatory status. The comparative ∆C_T method, BestKeeper, Normfinder, geNorm and RefFinder algorithms were used to assess the stability of the candidate genes. The results showed that the most suitable internal controls are HPRT1, RPS18 and B2M genes. In addition, the most stable and unstable reference genes were used to normalize the expression of a gene of interest in HMC3, resulting in a difference in the statistical significance in cells treated with Rotenone. This is the first reference gene validation study in HMC3 cell line in pro-inflammatory status and can contribute to more reliable gene expression analysis in the field of neurodegenerative and neuroinflammatory research.