A newly developed 20K SNP array reveals QTLs for disease resistance to Cryptocaryon irritans in tiger pufferfish (Takifugu rubripes)

Yangzhen Li, Clemence Fraslin, Yong Chi, Robert Mukiibi, Yuanri Hu, Jialin Wang, Weiguo Li, Weidong Li, Ross Houston, Diego Robledo, Songlin Chen

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

This study describes the development and application of a 20 K single nucleotide polymorphism (SNP) array in fugu (Takifugu rubripes). The main goal of this newly developed SNP array is to enhance selective breeding practice via the incorporation of genomic information. Fugu is one of the economic aquaculture species and mainly threatened by parasite disease. The performance of the array was evaluated in a farmed pufferfish population challenged with Cryptocaryon irritans and benchmarked against whole-genome sequencing of a subset of the animals. The array showed very high call rates, consistency between technical replicates, and concordance with genome-resequencing data. Heritability estimates using pedigree and SNP datasets demonstrated a significant genetic component of resistance to C. irritans, with heritability estimates ranging from 0.53 to 0.67, and prediction accuracies were significantly improved with the use of genomic data. Genome-wide association study identified two putative quantitative trait loci (QTLs) on chromosomes 3 and 17. Our findings suggest resistance to C. irritans can be rapidly increased in fugu populations by selective breeding, further expedited via the application of genetic markers. Therefore, they represent a valuable resource for selective breeding programmes aimed at enhancing disease resistance in fugu aquaculture
Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalAquaculture
Volume595
Issue number2
Early online date18 Sept 2024
DOIs
Publication statusE-pub ahead of print - 18 Sept 2024

Keywords / Materials (for Non-textual outputs)

  • SNP array
  • Heritability
  • Genomic prediction
  • GWASQTL
  • Selective breeding

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