Gene expression analysis in hereditary diseases using the tool Automatic and Serial Analysis of CO-expression (ASACO)

Resumen

Motivation: In recent years, Bioinformatics has positioned itself as a highly demanded discipline within the scientific field thanks

to the recent advances which have allowed a significant growth in the information available about gene sequences and gene

expression. Specifically, gene expression analysis has proven to be a very useful technique for creating knowledge about

different complex hereditary diseases by obtaining new data that allows us to understand their actions, similarities with other

pathologies, genetic changes and even regulatory drugs. The main purpose of this project is to analyze genes for which

functional information is not available and to functionally annotate them with a new tool based on transcriptomic data to obtain

relevant data about the diseases in which they are involved.

Methods: For the present project the tool Automatic and Serial Analysis of CO-expression (ASACO) developed by the

UPOBioinfo Group, in the Bioinformatics Unit of the CABD (Centro Andaluz de Biolog a del Desarrollo) is used. This tool analyzes

the expression of a gene giving putative both positive and negative correlators.The procedure has first been performed with a

gene that has sufficient functional information to be used as a positive control for the study. Firstly, the gene is selected in UniProt

database, it is analyzed with ASACO (ASACO algorithm, pvalue < 0.05 and Fold Change 1 ) and the functional information

available in the database is compared to the one obtained with the tool. In addition, the genes involved in the biological pathways

in which the gene participates are compared with the positively and negatively co-rrelated genes found by ASACO.At the same

time, all the information acquired is reviewed in relation to the available bibliography on the subject so that it allows us to

understand the new data and draw relevant conclusions. Finally, the specificity and sensitivity of the assay are calculated. Next,

this procedure will be repeated starting with a list of 4 or 5 genes for which functional information is not available.

Results: The preliminary results with a well-known gene showed that its positive correlators had related functions with this gene.

Conclusions: Therefore, we expect to contribute to the creation of knowledge in the study of several hereditary diseases whose

genes do not present functional information and to demonstrate the usefulness and value provided by the used tool.