journal article Open Access Apr 18, 2025

The Genomics Revolution in Nonmodel Species: Predictions vs. Reality for Salmonids

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Abstract
ABSTRACT
The increasing feasibility of whole‐genome sequencing has been highly anticipated, promising to transform our understanding of the biology of nonmodel species. Notably, dramatic cost reductions beginning around 2007 with the advent of high‐throughput sequencing inspired publications heralding the ‘genomics revolution’, with predictions about its future impacts. Although such predictions served as useful guideposts, value is added when statements are evaluated with the benefit of hindsight. Here, we review 10 key predictions made early in the genomics revolution, highlighting those realised while identifying challenges limiting others. We focus on predictions concerning applied aspects of genomics and examples involving salmonid species which, due to their socioeconomic and ecological significance, have been frontrunners in applications of genomics in nonmodel species. Predicted outcomes included enhanced analytical power, deeper insights into the genetic basis of phenotype and fitness variation, disease management and breeding program advancements. Although many predictions have materialised, several expectations remain unmet due to technological, analytical and knowledge barriers. Additionally, largely unforeseen advancements, including the identification and management applicability of large‐effect loci, close‐kin mark–recapture, environmental DNA and gene editing have added under‐anticipated value. Finally, emerging innovations in artificial intelligence and bioinformatics offer promising new directions. This retrospective evaluation of the impacts of the genomic revolution offers insights into the future of genomics for nonmodel species.
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Published
Apr 18, 2025
Vol/Issue
34(23)
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Cite This Article
Samuel A. May, Samuel W. Rosenbaum, Devon E. Pearse, et al. (2025). The Genomics Revolution in Nonmodel Species: Predictions vs. Reality for Salmonids. Molecular Ecology, 34(23). https://doi.org/10.1111/mec.17758