Automatic identification of GO-Terms related to ripening fruit of tomato based on machine learning and its application in a breeding program

CACCHIARELLI, P.; SPETALE, F.; GUILLERMO R. PRATTA; ELIZABETH, TAPIA

Querétaro

Conferencia; ISCB-LA SOIBIO BioNetMX 2022 (ISCB-Latin America SoIBio BioNetMX Conference on Bioinformatics 2022); 2022

SOIBIO

Tomato quality is one of the most important factors that helps ensure a consistent marketing of tomato fruit. The genome sequencing of tomatoes has provided powerful insights into the molecular changes in fruit ripening,. Fruit ripening is a part of a complex developmental process that is highly coordinated and includes changes in color, texture, taste and flavor. The automatic identification of biological functionalities of genes during the ripening process is important because it detects a list of GO-Terms and genes related to maturation and reveals potential differential attributes to assist with greater certainty the breeding program in tomato. Given that gene expression revealed by massive RNA-seq is a metric measuremente, estimation of gene action by Quantitative Genetics analysis provides a direct application to identify promising parents and hybrid taking the additive and non additive genetic effects on RNA levels as a slection criteria in breeding programs. An analysis of the global expression of genes was developed through the technique of massive sequencing of RNA-seq and phenotypic characterization in parent genotypes and their hybrid. The goal was to identify GO-Terms of biological processes related to fruit ripening in which genes with differential expression are involved and analyze their gene action. The study of genes was obtained with transcriptional profiles in three mainly ripening stages (Breaker, Mature Green and Red Ripe) and then a new analysis was carried out with the AgriGO tool in order to characterize and identify genes involved in these development stages. In addition, this enrichment analysis allows exploring the biological processes related to fruit ripening in which differential expression transcripts participate. Comparison into the biological processes domain between these three genotypes generated a list of consensus GO-Terms, of which 4 were detected (GO:0044699, GO:0008152, GO:0044710 and GO:0005975). On the other hand, 20 genes were randomly selected from the total of 2,744 genes to estimate the additive and non additive dominance genetic varianceseffects. This result showed 17 genes with negative overdominance from the parent with the lowest value, and the others showed partial dominance towards lower values. Thus, 60% of the genes were related to the value of the dominant parent cv. Caimanta and the remaining 40% are close to wild accession. This first approach was proposed to identify GO-Terms related to a development stage in the fruit of tomato and detect potential genes of interest to continúe with the breeding program and to obtain new varieties of tomatoes.