Background
The Manila clam (Ruditapes philippinarum) is one of the most widely cultivated bivalve species globally, valued for its rapid growth, environmental tolerance, and economic importance in coastal aquaculture. Its production is increasingly challenged by disease outbreaks, rising temperatures, and other environmental stressors linked to climate change. Selective breeding, supported by genomic tools, offers a powerful approach to enhance resilience, productivity, and key commercial traits in this species.
Previously, we have developed and validated a high-density SNP array for the Manila clam to enable large-scale genomic analyses supporting selective breeding. SNP discovery was conducted using low-coverage whole-genome sequencing across multiple European populations, followed by the design and validation of a 49K Axiom�� SNP array. The platform demonstrated high call rates and robustness across diverse experimental cohorts, providing a comprehensive resource for downstream analyses of heritable traits, including growth, disease resistance, and thermal tolerance.
Methods
To complement genomic data, a large-scale phenotyping effort was undertaken using computed tomography (CT) scanning of 1000 clam shells. A purpose-built holder was designed and iteratively refined to ensure consistent positioning and optimal scan quality. High-resolution scans were used to extract detailed morphometric parameters, including shell width, depth, thickness, and density, enabling precise quantitative characterization of shell structure.
Results
The CT-derived data provides a novel, high-resolution characterization of shell morphology and allows deeper investigation into which morphological traits are most strongly influenced by genetic variation, strengthening the integration of phenotypic and genomic datasets for selective breeding applications.