Gene co-expression analyses: an overview from microarray collections in Arabidopsis thaliana

4noBioinformatics web-based resources and databases are precious references for most biological laboratories worldwide. However, the quality and reliability of the information they provide depends on them being used in an appropriate way that takes into account their specific features. Huge collections of gene expression data are currently publicly available, ready to support the understanding of gene and genome functionalities. In this context, tools and resources for gene co-expression analyses have flourished to exploit the ‘guilty by association' principle, which assumes that genes with correlated expression profiles are functionally related. In the case of Arabidopsis thaliana, the reference species in plant biology, the resources available mainly consist of microarray results. After a general overview of such resources, we tested and compared the results they offer for gene co-expression analysis. We also discuss the effect on the results when using different data sets, as well as different data normalization approaches and parameter settings, which often consider different metrics for establishing co-expression. A dedicated example analysis of different gene pools, implemented by including/excluding mutant samples in a reference data set, showed significant variation of gene co-expression occurrence, magnitude and direction. We conclude that, as the heterogeneity of the resources and methods may produce different results for the same query genes, the exploration of more than one of the available resources is strongly recommended. The aim of this article is to show how best to integrate data sources and/or merge outputs to achieve robust analyses and reliable interpretations, thereby making use of diverse data resources an opportunity for added value.openembargoed_20170219Di Salle, Pasquale; Incerti, Guido; Colantuono, Chiara; Chiusano, Maria LuisaDi Salle, Pasquale; Incerti, Guido; Colantuono, Chiara; Chiusano, Maria Luis

Auditory cortex hypoperfusion: a metabolic hallmark in Beta Thalassemia

Abstract Background Sensorineural hearing loss in beta-thalassemia is common and it is generally associated with iron chelation therapy. However, data are scarce, especially on adult populations, and a possible involvement of the central auditory areas has not been investigated yet. We performed a multicenter cross-sectional audiological and single-center 3Tesla brain perfusion MRI study enrolling 77 transfusion-dependent/non transfusion-dependent adult patients and 56 healthy controls. Pure tone audiometry, demographics, clinical/laboratory and cognitive functioning data were recorded. Results Half of patients (52%) presented with high-frequency hearing deficit, with overt hypoacusia (Pure Tone Average (PTA) > 25 dB) in 35%, irrespective of iron chelation or clinical phenotype. Bilateral voxel clusters of significant relative hypoperfusion were found in the auditory cortex of beta-thalassemia patients, regardless of clinical phenotype. In controls and transfusion-dependent (but not in non-transfusion-dependent) patients, the relative auditory cortex perfusion values increased linearly with age (p < 0.04). Relative auditory cortex perfusion values showed a significant U-shaped correlation with PTA values among hearing loss patients, and a linear correlation with the full scale intelligence quotient (right side p = 0.01, left side p = 0.02) with its domain related to communication skills (right side p = 0.04, left side p = 0.07) in controls but not in beta-thalassemia patients. Audiometric test results did not correlate to cognitive test scores in any subgroup. Conclusions In conclusion, primary auditory cortex perfusion changes are a metabolic hallmark of adult beta-thalassemia, thus suggesting complex remodeling of the hearing function, that occurs regardless of chelation therapy and before clinically manifest hearing loss. The cognitive impact of perfusion changes is intriguing but requires further investigations

Analisi di co-espressione in A.thaliana

Abstract The plant cell is a very coordinated system, with a central nucleus, organelles and structures, interacting continuously to perform the tasks needed to the cell growth, survival and replication. Genomes in fact store the instructions to define the cells, according to their genetic program. Most of cell activities are in fact the result of a work performed by multiple partners, collaborating in a serial or parallel way. All these efforts require hence a strong coordination among the gene functionalities too. This work aims to investigate the gene expression, in particular, the genes which are co-expressed, their roles and the main bioinformatics approaches exploited to analyze them. In order to perform this study, we have exploited the genome of Arabidopsis thaliana, a plant species very well studied and with a genome sequence made available in 2000 [The Arabidopsis Genome Initiative, 2000]. Because of this and thanks to the huge amount of data derived for this plant, Arabidopsis thaliana is considered the reference organism in plant genomic and constantly exploited for comparative analyses with other species. A. thaliana was established as a model plant genome because of its easy management properties, such as a small diploid genome, the small size and the high seeds production through self-pollination. However this plant has shown a very complex genome structure, with a hard to count number of gene duplications and chromosomes shuffles. The gathering of information about the co-expressed genes has inevitably led us to challenge some important questions in bioinformatics, as the research of 4 a network identification method able to group genes with a biological meaning, and the evaluation of the statistical components exploited to define genes as co-expressed. This effort has hence required the comparison of the public available platforms concerning the co-expression issue. As result of these activities, we have also tried to produce a new network profiling approach, inspired by social networks and able to underline quickly the genes in relation inside the genome. The comparison of the platforms concerning the co-expression has instead revealed a not uniform behavior of the genes according to the co-expression identification methods, underlining the need of data mining analyses not only through a single and specific dataset, but trying to compare the highest number of resources available

pATsi: Paralogs and Singleton Genes from

Arabidopsis thaliana is widely accepted as a model species in plant biology. Its genome, due to its small size and diploidy, was the first to be sequenced among plants, making this species also a reference for plant comparative genomics. Nevertheless, the evolutionary mechanisms that shaped the Arabidopsis genome are still controversial. Indeed, duplications, translocations, inversions, and gene loss events that contributed to the current organization are difficult to be traced. A reliable identification of paralogs and single-copy genes is essential to understand these mechanisms. Therefore, we implemented a dedicated pipeline to identify paralog genes and classify single-copy genes into opportune categories. PATsi, a web-accessible database, was organized to allow the straightforward access to the paralogs organized into networks and to the classification of single-copy genes. This permits to efficiently explore the gene collection of Arabidopsis for evolutionary investigations and comparative genomics

Brain iron content in systemic iron overload: a beta-thalassemia quantitative MRI study

Multisystem iron poisoning is a major concern for long-term beta-thalassemia management. Quantitative MRI-based techniques routinely show iron overload in heart, liver, endocrine glands and kidneys. However, data on the brain are conflicting and monitoring of brain iron content is still matter of debate