About the blog author: Devon Pearse (he/him) is a research geneticist at the NOAA Fisheries Southwest Fisheries Science Center working as part of the Molecular Ecology and Genetic Analysis Team, and adjunct professor of Ecology and Evolutionary Biology at UC Santa Cruz in the Fisheries Cooperative Program. He loves kayaking and rafting adventures on free-flowing rivers and plays upright bass in a honky-tonk band. Follow Devon’s research on Instagram and Twitter. [Note: The following are my personal reflections after working on this paper and are solely my own. For additional discussion of this work, please see the blog post by coauthor Tasha Thompson – Behind the Science: Through the Rapids with Chinook Salmon Run-timing Genetics]
In February of 2020, just as the SARS-CoV-2 virus was first migrating to the US, I was among a group of about 20 scientists—mostly population geneticists—participating in two days of intense discussions in a small room in Seattle, WA (Little did we know that this would be the last ‘normal’ scientific meeting we would have for more than two years!).
Our group, a mix of researchers from university, government, and other research centers, was invited to consider the implications of our collective data on one phenotypic trait—run-timing, the seasonality of salmon migrating upriver to spawn—that has come into the conservation crosshairs due to recent genomic data from multiple studies showing that run-timing is controlled almost entirely by variation in and around a single genetic locus, GREB1L/ROCK1, in Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss).
How is genetic variation distributed among the fundamental biological units—individuals, populations, species— and how can we best conserve it given that knowledge? As ‘genetics’ has become ‘genomics’, the exponential increase in data has transformed our ability to answer this seemingly simple question and, importantly, to differentiate neutral variation from ‘adaptive genomic variation’ associated with phenotypic traits. Today we have a far more detailed picture of the distributions of neutral and adaptive genetic variation than we did in 1973 when the Endangered Species Act (ESA) was passed. Now, a newly published review that was conceived at that February 2020 workshop asks the fundamental question ‘Should information from adaptive loci be used to reconfigure Conservation Units (CUs), even if this conflicts with overall patterns of genetic differentiation?’ (Waples et al. 2022)
Run-timing variation in Pacific Salmon: Perspectives from the front line
Pacific Salmon have long been on the front lines of conservation science due to their importance as food and cultural resources and their need for free-flowing rivers, creating direct conflict with human demands for water and power in western North America. Early genetic analysis using allozymes built the foundations of our understanding of their structured yet interconnected populations and lead to the initial designations of conservation units. They also shaped views on the underlying genetic basis of life-history variation, especially run-timing. But despite likely genotyping nearly a million individual Pacific salmon (Allendorf 2017), these data did not provide the resolution to probe the specific genomic basis of phenotypic traits.
The core of our paper is a deep dive into what we now know based on the existing genomic data on the effects of GREB1L/ROCK1 on run-timing in Chinook salmon and steelhead, highlighting scientific consensus, critical uncertainty, and implications for conservation and management. The latter have been remarkably contentious, dividing the opinions of both scientists and state and federal rule makers.
A key issue is whether the genetic architecture of a trait—in this case a single large-effect locus—influences its vulnerability, creating the need for directed conservation. Such large-effect loci are increasingly being discovered in diverse taxa, yet as a scientific community we are far from a consensus on how they may impact approaches to conservation of biodiversity under different polices.
Another key point discussed by Waples et al. (2022) is the potential for identification of multiple loci of major effect for multiple traits within the same species. While GREB1L operates similarly within both Chinook salmon and steelhead, only in steelhead is there another locus of major effect, a large chromosomal inversion complex associated with a second life-history trait: remaining in freshwater as a resident rainbow trout versus migrating to sea as a steelhead (Pearse et al. 2019). The presence of these two loci of major effect within a single species highlights the complexity of incorporating the full diversity of adaptive genomic variation into conservation.
One take home from all of this is that focusing conservation efforts on strictly delineated ‘units’—however they are defined—creates challenges in the face of the biological diversity of nature. While the ESA provides for protection of conservation units within biological species, even so-called ‘good’ biological species may hybridize and share adaptive variation, creating a mosaic landscape of genomic diversity. Clearly, creating policies that separate dynamic, interconnected, biological systems into binary units will not be straightforward and there can be no single correct way to do so (Allendorf 2018).
Resolution
So, in the end does it matter?
While the increasingly deep scientific insights from genomic data are intoxicating, lack of scientific knowledge is often not the limiting factor for conservation. Waples et al. (2022) provides a window into the practice of conservation genomics in a group with proportionately more data and research investment per species than any other protected taxon (Evans et al. 2016). However, it is sobering to think about scaling up the cost and effort required to conduct such a detailed analysis on full diversity of species in need of conservation: Massive efforts like the California Conservation Genomics Project and much larger Earth Biogenome Project are paving the way, assembling de novo chromosome-scale genomes and resequencing hundreds of individual genomes of species of concern. Yet all these data cannot truly benefit conservation efforts unless we take action to preserve the basic ecosystem processes that naturally support biodiversity and “…the factors that make it possible – large livable habitats and natural patterns of connectivity among them” (Kardos et al. 2021).
As for me, I am really happy to be teaching a curiosity-based graduate seminar in which we marvel at the amazing evolutionary insights provided by the genomics revolution over the past 20 years, regardless of their conservation implications!
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