Investigação de novos genes candidatos a reguladores do ritmo circadiano identificados a partir de mineração de dados de expressão gênica em cérebro de mamíferos

Abstract

Circadian rhythms are a biological phenomena that is repeated with frequency of approximately 24 hours. At the molecular level, these cyclic phenomena are controlled by a set of central genes called clock genes. The involvement of clock genes and clock-controlled genes in the circadian rhythms of mammals began to be understood since the 90s, with the discovery of the genes: Clock, Bmal1, Cry1, Cry2, Per1, Per2 and Per3, Rora, Rorb, Rorc, Nr1d1 and Nr1d2. Different approaches and methods have been used in the identification of genes involved with the circadian rhythm. A more current approach known as data mining arose from bioinformatics, and it is defined as an analysis of large data sets with the objective of finding new relationships between them, summarizing them comprehensibly and usefully in generating new knowledge, it has been used in the discovery of these functional molecules and their involvement in this timing system. The Chrono gene, for example, has been identified as an important component of the circadian timing system in mammals, using a computational approach based on data mining. In this study, we used gene expression data in wide range of human and murine cerebellum, available via the Allen Brain Atlas portal as a predictive method for the identification of genes that have circadian oscillation or function, through the correlation of spatial expression (Pearson's r) with 19 major circadian genes (Bmal1, Bmal2, Clock, Cry1, Cry2, Csnk1a, Csnk1d, Csnk1e, Fblx3, Fblx21, Npas2, Nr1d1, Nr1d2, Per1, Per2, Per3, Rora, Rorb and Rorc). 2% of the genes with the extreme values of correlations in the two species were were compared with data on a large scale studies with transcriptoma, proteoma, ChiP-seq, RNAi and protein-protein interaction, and their functional interactions were analyzed through the online portal STRING. Our results show that 19,907 genes in the cerebellum of Mus musculus and 29,176 genes in the cerebellum of Homo sapiens have spatial expression profiles related to one or more of the 19 circadian genes investigated and 14,242 genes common to both species. The distribution of correlation data considering the genes that present or not circadian variation previously identified shows a profile where the number of genes that exhibit changes also tend to have larger correlation values, positive or negative, to both species. The comparison of average values of r in module (| r |) of these groups showed significantly higher values for the group that shows circadian variation (p < 0.0001) for the mice data. Furthermore, 2% of the genes with larger values of | r | showed a higher frequency of genes with circadian variation in almost all circadian studies analyzed, except in the study of RNAi, for M. musculus and H. sapiens, compared to the group of 2% of the genes with r values closer to negative and positive zeros. The 100 genes related to higher values of | r | obtained for M. musculus were ranked based on the sum of these values with the correlation values obtained for the corresponding homologous gene in H. sapiens in order to select candidate genes for future experimental studies. The Cartpt gene occupies the first position of the chart, with the highest result of the sum of the values of | r | obtained for M. musculus and H. sapiens, being a strong candidate to control the feeding rhythm in mammalian cerebellum. This gene has been associated with food circadian rhythm in mice. Per2, Cry2 and Rora, three circadian genes are on this list. Gpr149, Ptprr, Nipal4 are among the 10 best-ranked and present no prior evidence of involvement with the rhythm, constituting as new candidates for circadian genes in mammalian cerebellum. The strategy used has the potential to identify important genes for the circadian rhythm in specific structures of the human and mice’s brain. However, analysis of gene expression and functional assays are needed to validate the involvement of these candidate genes.