ArticleScientific data2025
Genomes of two indigenous clams Anomalocardia flexuosa (Linnaeus, 1767) and Meretrix petechialis (Lamarck, 1818).
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Chromosome-level genomes of hard clams Meretrix lamarckii (Deshayes, 1853) and Meretrix meretrix (Linnaeus, 1758).Scientific data · 2026Article
- High-quality chromosome-level genome of three Meretrix species using Nanopore and Hi-C technologies.Scientific data · 2025Article
- Genomes of two indigenous clams Anomalocardia flexuosa (Linnaeus, 1767) and Meretrix petechialis (Lamarck, 1818).Scientific data · 2025Article
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Clam digging has a long history in Hong Kong, but unregulated clam digging activities depletes clam populations and threatens the ecosystem. Population genomics is useful to unravel the connectivity of clams at different geographical locations and to provide necessary conservation measures; and yet, only limited number of clams in Hong Kong have genomic resources. Here, we present chromosomal-level genome assemblies for two clams commonly found in Hong Kong, Anomalocardia flexuosa and Meretrix petechialis, using a combination of PacBio HiFi and Omni-C reads. For A. flexuosa, we assembled the genome into 19 pseudochromosomes with a genome size of 1.09 Gb (scaffold N50 = 58.5 Mb), and BUSCO scores of 94.4%. A total of 20,881 gene models were also predicted using the transcriptomes generated in this study. For M. petechialis, the genome was mainly assembled into 19 pseudochromosomes with a genome size of 1.04 Gb (scaffold N50 = 53.5 Mb), and BUSCO scores of 95.7%. A total of 20,084 gene models were also predicted using the transcriptomes generated in this study. The two new genomic resources established in this study will be useful for further study of biology, ecology, and evolution of clams, as well as setting up a foundation for evidence-informed decision making in conservation measures and implementation.
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