Back

Exploring the Repetitive DNA Diversity in Solanum betaceum (Solanaceae)

Sader, M. A.; Vaio, M.; Trenchi, A.; Zapata, M. J.; Chiarini, F.; Lopez, A.; Urdampilleta, J.

2025-08-30 genomics
10.1101/2025.08.26.672483 bioRxiv
Show abstract

The Solanaceae family, known for its diverse and economically important crops, includes the genus Solanum, which comprises 1,245 species. Solanum betaceum (tree tomato), native to the Andes and cultivated globally, is a promising species due to its nutritional value and market potential. The Cyphomandra clade, which includes the tree tomato, is characterized by huge genomes and chromosomes, with repetitive DNA elements (e.g., retrotransposons and satellite DNA) playing crucial roles in genomic and evolutionary studies. Despite its importance, genetic research on S. betaceum remains limited. This study addresses this knowledge gap by characterizing the repetitive DNA fraction to better understand intraspecific variation and develop molecular markers. Samples from five populations in northwestern Argentina were cultivated, and genome size was assessed via flow cytometry. Illumina HiSeq sequencing combined with RepeatExplorer analysis was used to identify repetitive DNA elements. Cytogenetic techniques, including CMA/DAPI staining and fluorescence in situ hybridization (FISH), were employed to detect satellite DNA patterns. Genome size analysis revealed slight variation among populations. Repetitive DNA accounted for 63.5% of the genome, with Ty3-gypsy retrotransposons being the most abundant (51.44%). Satellite DNA and rDNA were less prevalent, comprising 0.93% and 0.30% of the genome, respectively. Population comparisons showed consistent proportions of repetitive DNA overall, with notable differences in Ty3-gypsy-Tekay and satellite DNA fractions. This study provides a detailed profile of the repetitive DNA landscape in S. betaceum, uncovering intraspecific differences and delivering valuable genomic insights for future breeding and conservation efforts.

Published in TAXON · not in our set (fewer than 10 published preprints to learn from) · training set

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.