Genomics Applied to Aquaculture
We develop genomic resources (e.g. genome assemblies and functional annotations) and methods (e.g. for SV detection and imputation) and apply omic methods for applications in aquaculture, including to characterize and diagnose disease agents and understand their evolution and transmission, to study fish immune and vaccination responses, and to establish associations between genomic and trait variation.
Representative recent papers:
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​Gundappa MK, Robledo D, Hamilton A, Houston RD, Prendergast JGD, Macqueen DJ. 2025. High performance imputation of structural and single nucleotide variants using low-coverage whole genome sequencing. Genet. Sel. Evol. 57, 16. https://doi.org/10.1186/s12711-025-00962-6
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Johnston IA^, Kent MP, Boudinot, P, Looseley M, Bargelloni L, Faggion S, Merino GA, Ilsley GR, Bobe J, Tsigenopoulos CS, Robertson R, Harrison PW, Martinez M, Robledo D, Macqueen DJ *, Lien S *. 2024. Advancing fish breeding in aquaculture through genome functional annotation. Aquaculture. 740589. doi: 10.1016/j.aquaculture.2024.740589. * Equal senior author position and shared correspondence.
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Ruiz Daniels R, Taylor RT, Robledo D, Macqueen DJ. 2023. Single cell genomics as a transformative approach for aquaculture research and innovation. Reviews in Aquaculture. https://doi.org/10.1111/raq.12806
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Gundappa MK, Peñaloza C, Regan T, Boutet I, Tanguy A, Houston RD, Bean TP, Macqueen DJ. 2022. Chromosome level reference genome for European flat oyster (Ostrea edulis L.). Evol Appl. https://doi.org/10.1111/eva.13460
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Houston RD, Bean TP, Macqueen DJ, Gundappa MK, Yehwa J, Jenkins TL, Counter Selly S-L, Martin SAM, Stevens J, Santos E, Davie A, Robledo R. Harnessing genomics to fast-track genetic improvement in aquaculture. Nat. Rev. Genet. 21: 389–409
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Bayesian phylogeny of salmonid alphavirus genomes built from an 11,681 bp alignment and analyzed in BEAST2 using the best fit nucleotide substitution model (TIM2 + G4), a relaxed molecular clock model, tip-dating, and a coalescent Bayesian Skyline population model. A discrete phylogeographical analysis was performed using ancestral reconstruction with branch colors indicating the estimated geographic location of each node. Statistical support for key nodes is indicated by posterior probability values in bold, and the ancestral location probability in brackets. From Gallagher et al. 2020. Front. Microbiol.