Bioinformatic identification of sequence variants by integrating omic data to design functional DNA markers in tomato

GOYTIA BERTERO VALENTINA; CACCHIARELLI, PAOLO; PRATTA, GUILLERMO R.; ARCE, DÉBORA P.

Rosario

Congreso; XIII Argentine Congress of Bioinformatics and Computational Biology (XIII CAB2C); 2023

A2B2C - SOIBIO - RIABIO

The cultivated tomato (Solanum lycopersicum) is one of the most agriculturally important vegetables. Dueto its limited genetic variability, related wild species are often used in breeding programs to expand theavailable diversity. From previous experiments, we were able to obtain the genome and transcriptomeof the cv. Caimanta (S. lycopersicum, C) and LA0722 (S. pimpinellifolium, P) progenitors. As an originalcontribution of this experiment, we analyzed proteins obtained through GC-MS and subsequentlyassigned their respective expression levels, obtained from a previous RNAseq experiment, allowing us toidentify induced genes (IG) during the fruit maturation process in both genotypes (C and P).The objective of this study was to develop molecular markers (MMs) from the detected IG, with aparticular focus on Heat Shock Proteins (HSPs), a biologically significant superfamily that functions asmolecular chaperones, folding other proteins and preventing their denaturation. To achieve theproposed objective, protein sequences (https://solgenomics.net/) of 9 selected chaperones(SOLYC03G113930, HSP20 - SOLYC04G082720, HSP20 - SOLYC05G014280, HSP20 - SOLYC06G076570,HSP20 - SOLYC07G006180, RIPENING REGULATED PROTEIN - SOLYC07G042250, CHAPERONINE21 -SOLYC09G011030, HSP70 - SOLYC09G075950, HSP70 - SOLYC12G056780, HSP20) were obtained.Subsequently, a BLASTn was performed on both progenitors to detect the start and end positions of thegenes. 1000 bases were added to each start coordinate to extract the DNA sequences corresponding tothe chaperones from the genomes of C and P.Comparing these regions through sequence alignment using the Needle program(https://www.ebi.ac.uk/Tools/psa/emboss_needle/) revealed numerous Single NucleotidePolymorphisms (SNPs) in the 9 analyzed genes. Developing MMs from omics data is expected to yieldfunctional markers that can be used