A new database of chestnut DNA fingerprints for genetic diversity assessment, precise varietal identification, and traceability

The European chestnut (Castanea sativa Mill., Fagaceae) is ecologically and economically important, particularly in countries like Italy, Greece, Spain, and Turkey, where it supports rural economies and ecosystems. Accurate varietal recognition is crucial for managing chestnut groves but is hindered by the limitations of traditional methods, which require costly expertise and struggle to identify young, dormant, or scion trees. Recent advances in molecular tools, particularly single nucleotide polymorphism (SNP) markers identified through Kompetitive Allele-Specific PCR (KASP) technology, have transformed cultivar identification. To harness this potential, we developed KASTRACKdb, a genetic fingerprinting database for European chestnut that now integrates genotypic and phenotypic data for 150 chestnut accessions. Designed to translate KASP analysis results into practical and actionable insights, KASTRACKdb serves as a powerful tool for cultivar identification and management. The database offers three primary query modes and is designed for continuous upgrades, serving a crucial role in cataloguing the genetic diversity of chestnut trees, characterized by broad geographic distributions and significant genetic variation. This diversity is critical for conservation and breeding programs, enabling precise varietal identification and traceability to protect intellectual property, verify authenticity, and support the commercialization of high-value cultivars. Database URL: KASTRACKdb is available online at https://kastrack.crea.gov.it/kastrackdb/?lang=en.

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Database
Published
2025-01-01
DOI
https://doi.org/10.1093/database/baaf056
Primary Topic
Plant and Fungal Interactions Research
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article
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article

A new database of chestnut DNA fingerprints for genetic diversity assessment, precise varietal identification, and traceability

Angelina Nunziata, Alessandro Maisto, Nunzio D’Agostino, Domenico Gentile et al.
Database
Plant and Fungal Interactions Research
article

A new database of chestnut DNA fingerprints for genetic diversity assessment, precise varietal identification, and traceability

Angelina Nunziata, Alessandro Maisto, Nunzio D’Agostino, Domenico Gentile, Ivan Fruggiero, Sara Passaro
article en

Abstract

The European chestnut (Castanea sativa Mill., Fagaceae) is ecologically and economically important, particularly in countries like Italy, Greece, Spain, and Turkey, where it supports rural economies and ecosystems. Accurate varietal recognition is crucial for managing chestnut groves but is hindered by the limitations of traditional methods, which require costly expertise and struggle to identify young, dormant, or scion trees. Recent advances in molecular tools, particularly single nucleotide polymorphism (SNP) markers identified through Kompetitive Allele-Specific PCR (KASP) technology, have transformed cultivar identification. To harness this potential, we developed KASTRACKdb, a genetic fingerprinting database for European chestnut that now integrates genotypic and phenotypic data for 150 chestnut accessions. Designed to translate KASP analysis results into practical and actionable insights, KASTRACKdb serves as a powerful tool for cultivar identification and management. The database offers three primary query modes and is designed for continuous upgrades, serving a crucial role in cataloguing the genetic diversity of chestnut trees, characterized by broad geographic distributions and significant genetic variation. This diversity is critical for conservation and breeding programs, enabling precise varietal identification and traceability to protect intellectual property, verify authenticity, and support the commercialization of high-value cultivars. Database URL: KASTRACKdb is available online at https://kastrack.crea.gov.it/kastrackdb/?lang=en.

DatabaseVol. 2025
Cereal Research Centre (IT), Department of Agricultural Sciences (RU), University of Naples Federico II (IT)
Openalex Percentile: Top 77%
Plant and Fungal Interactions Research
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