Rainbow and Steelhead Trout

Using genomic data and novel analytical tools to understand rainbow trout/steelhead life-history variation and enhance conservation and management.

Campus: UCSC

PI(s): Palkovacs

Background: Rainbow trout/steelhead (Oncorhynchus mykiss) are affected by habitat fragmentation and other anthropogenic impacts, including dams, water diversions, hatchery domestication selection and stocking of non-native hatchery trout. We are using conservation genomics approaches to address the following questions:

  • How are populations isolated by migration barriers genetically related and what are the genomic consequences of secondary contact and introgression? Do migratory adfluvial populations above dams share genomic characteristics with coastal anadromous populations, and how might they contribute to conservation of ESA-listed anadromous steelhead?
  • How does divergence of migratory life-histories affect variation at the genome level? How might adaptive genomic variation be incorporated into management plans and hatchery breeding programs for anadromous steelhead (e.g., marker-assisted selection)?
  • What are the genomic consequences of inbreeding and hatchery domestication selection, particularly on life history traits (e.g., age-of-return, run timing).


  • There are two draft genome assemblies available for the species, including a published one (Berthelot et al. 2014) and an unpublished one (M. Miller, UC Davis, pers. comm.). Because of a relatively recent genome duplication event, these assemblies are largely unordered.
  • We are collaborating on a project to combine this existing genome sequence data with data from a Dovetail Genomics ‘chicago’ library to provide a greatly improved reference genome assembly. We expect completion of this in <6 months.
  • We have developed several panels of 96 SNP loci for the species, one for population structure and pedigree reconstruction work and one associated with adaptive genomic variation, including on chromosome Omy5 (Pearse et al. 2014). We have genotype data from >80,000 individual fish with the first panel and >5,000 individuals for the second one, both from diverse populations from Russia to Mexico.
  • We have used SNP panel data to construct several thousand multi-generation pedigrees for steelhead from hatcheries in the Central Valley and Russian River (Abadia-Cardoso et al. 2013).
  • We have long-term movement data from >10,000 tagged juvenile mykiss over 10 years from a population at the UCSC Landels-Hill Big Creek Natural Reserve. Spatial movement data for tagged individuals is being used to evaluate population dynamics and phenotypic development of alternative life-histories associated with adaptive genomic variation.
  • We have >400 historical samples of steelhead from the Smithsonian Institution collected ~100 years ago (Pearse et al. 2011).
  • We have funding to support work on population structure and hatchery introgression in coastal steelhead, life-history variation in hatchery steelhead in the Central Valley and Russian River, and adaptive genomic variation in salmonid fishes impacted by Central Valley water projects. We have an externally funded graduate student working on adaptive genomic variation in steelhead.
  • We have collaborations with partners at UC Davis, Oregon State University, Humboldt State University as well as state and federal agencies (CDF&W, USFWS, USDA, US Bureau of Reclamation), which will provide expanded research opportunities, including sharing of identified targets of adaptive genomic selection and collections of additional samples.

Approach: The improved genome assembly will be completed during the next several months, after which we will first focus on aligning and annotating regions containing SNPs known to be associated with key life-history traits. In particular, the large suite of RAD-SNPs in strong linkage disequilibrium on chromosome Omy5 likely represent a master control region associated with expression of migratory behavior, and understanding the genomic structure of this region is a critical next step. We will also assess the distribution of genomic sequence variation in the Omy5 and other adaptive genomic regions by re-sequencing both whole genomic and transcriptomic libraries from individuals expressing alternative life-histories, which will allow identification of genes under selection associated with alternative migration strategies. We will also evaluate genomic change in California steelhead populations over the last ~100 years, through comparative genomic analysis of contemporary populations and historical samples taken in 1897 and 1909.