From Shell to Sequence: Optimizing DNA Extraction and PCR for Pen Shell Identification

Pinna nobilis, an ecologically significant and critically endangered bivalve endemic to the Mediterranean Sea, has been classified as “Critically Endangered” by IUCN due to habitat degradation, climate change, and mass mortality events caused by the protozoan parasite Haplosporidium pinnae. Effective conservation efforts require robust molecular tools for species identification and genetic monitoring, necessitating the development of optimized DNA extraction and amplification protocols for a non-invasive sampling protocol. In this study, we evaluated multiple DNA extraction methods—Chelex-100, the sodium chloride (NaCl) method, a modified CTAB protocol, and a commercial kit, NucleoSpin Tissue Kit—using minute shell fragments from both ethanol-preserved and air-dried (dead) samples. We optimized key parameters, including incubation times, temperatures, and sample preparation, to determine the most effective protocol for obtaining high-quality DNA suitable for downstream applications. Additionally, we assessed different PCR strategies, including nested and semi-nested approaches targeting the COI gene marker, to enhance species identification. To further refine the methodology, we evaluated novel specific primers for nested PCR, improving sensitivity and specificity in detecting P. nobilis DNA from minute and degraded samples. Our results provide an optimized, cost-effective, and time-efficient workflow for non-invasive molecular identification of P. nobilis, with broad implications for conservation genetics, biodiversity monitoring, and species recovery programs.

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Publication Details

Journal
Water
Published
2025-04-13
DOI
https://doi.org/10.3390/w17081162
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
0.00

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article

From Shell to Sequence: Optimizing DNA Extraction and PCR for Pen Shell Identification

Maria Kamilari, Charikleia Papaioannou, Alexis Ramfos, John Α. Theodorou et al.
Water
Identification and Quantification in Food
article

From Shell to Sequence: Optimizing DNA Extraction and PCR for Pen Shell Identification

Maria Kamilari, Charikleia Papaioannou, Alexis Ramfos, John Α. Theodorou, Ioannis Α. Giantsis, Costas Batargias, Efthimios Spinos, Antonios A. Augustinos
article en

Abstract

Pinna nobilis, an ecologically significant and critically endangered bivalve endemic to the Mediterranean Sea, has been classified as “Critically Endangered” by IUCN due to habitat degradation, climate change, and mass mortality events caused by the protozoan parasite Haplosporidium pinnae. Effective conservation efforts require robust molecular tools for species identification and genetic monitoring, necessitating the development of optimized DNA extraction and amplification protocols for a non-invasive sampling protocol. In this study, we evaluated multiple DNA extraction methods—Chelex-100, the sodium chloride (NaCl) method, a modified CTAB protocol, and a commercial kit, NucleoSpin Tissue Kit—using minute shell fragments from both ethanol-preserved and air-dried (dead) samples. We optimized key parameters, including incubation times, temperatures, and sample preparation, to determine the most effective protocol for obtaining high-quality DNA suitable for downstream applications. Additionally, we assessed different PCR strategies, including nested and semi-nested approaches targeting the COI gene marker, to enhance species identification. To further refine the methodology, we evaluated novel specific primers for nested PCR, improving sensitivity and specificity in detecting P. nobilis DNA from minute and degraded samples. Our results provide an optimized, cost-effective, and time-efficient workflow for non-invasive molecular identification of P. nobilis, with broad implications for conservation genetics, biodiversity monitoring, and species recovery programs.

WaterVol. 17(8)
University of Patras (GR), Aristotle University of Thessaloniki (GR)
University of Patras
Openalex Percentile: Top 93%
Identification and Quantification in Food
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