Genetic basis of adult migration timing in anadromous steelhead discovered through multivariate association testing

Proceedings of the Royal Society B Biological Sciences, Journal Year: 2016, Volume and Issue: 283(1830), P. 20153064 - 20153064

Published: May 11, 2016

Migration traits are presumed to be complex and involve interaction among multiple genes. We used both univariate analyses a multivariate random forest (RF) machine learning algorithm conduct association mapping of 15 239 single nucleotide polymorphisms (SNPs) for adult migration-timing phenotype in steelhead ( Oncorhynchus mykiss ). Our study focused on model natural population that exhibits two distinct life histories with high levels admixture nature. Neutral divergence was limited between fish exhibiting summer- winter-run migration owing interbreeding, but mixed linear found three SNPs from major effect gene significantly associated timing p < 0.000005) explained 46% trait variation. Alignment the annotated Salmo salar genome provided evidence all localize within 46 kb region overlapping GREB1-like (an oestrogen target gene) chromosome Ssa03. Additionally, RF identified these plus additional up 60% These candidate may provide ability predict facilitate conservation management this species, demonstrates benefit studies.

Language: Английский

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Detecting Polygenic Evolution: Problems, Pitfalls, and Promises

Trends in Genetics, Journal Year: 2016, Volume and Issue: 32(3), P. 155 - 164

Published: Jan. 22, 2016

Language: Английский

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The Peril of Gene-Targeted Conservation

Trends in Ecology & Evolution, Journal Year: 2018, Volume and Issue: 33(11), P. 827 - 839

Published: Sept. 18, 2018

Language: Английский

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A practical introduction to Random Forest for genetic association studies in ecology and evolution

Molecular Ecology Resources, Journal Year: 2018, Volume and Issue: 18(4), P. 755 - 766

Published: March 5, 2018

Abstract Large genomic studies are becoming increasingly common with advances in sequencing technology, and our ability to understand how variation influences phenotypic between individuals has never been greater. The exploration of such relationships first requires the identification associations molecular markers phenotypes. Here, we explore use Random Forest ( RF ), a powerful machine‐learning algorithm, discern loci underlying both discrete quantitative traits, particularly when studying wild or nonmodel organisms. is used ecological population genetics because, unlike traditional methods, it can efficiently analyse thousands simultaneously account for nonadditive interactions. However, understanding power limitations important its proper implementation interpretation results. We therefore provide practical introduction algorithm identifying phenotypes, discussing topics as data limitations, initiation optimization, well interpretation. also short R tutorials examples, aim providing guide algorithm. Topics discussed here intended serve an entry point ecologists interested employing identify trait sets.

Language: Английский

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Ecological and Evolutionary Consequences of Environmental Change and Management Actions for Migrating Fish

Frontiers in Ecology and Evolution, Journal Year: 2019, Volume and Issue: 7

Published: July 10, 2019

Migration strategies in fishes comprise a rich, ecologically important, and socioeconomically valuable example of biological diversity. The variation flexibility migration is evident between within individuals, populations, species, thereby provides useful model system that continues to inform how ecological evolutionary processes mould biodiversity systems respond environmental heterogeneity change. Migrating are targeted by commercial recreational fishing impact the functioning aquatic ecosystems. Sadly, many species migrating fish under increasing threat exploitation, pollution, habitat destruction, dispersal barriers, overfishing, ongoing climate change brings modified, novel, more variable extreme conditions selection regimes. All this calls for protection, sustainable utilization adaptive management. However, situation complicated further actions aimed at mitigating devastating effects such threats. Changes river connectivity associated with removal barriers as dams construction fishways, together compensatory breeding supplemental stocking can on gene flow selection. How turn affects dynamics, genetic structure, diversity, potential, viability spawning populations remains largely unknown. In narrative review we describe discuss patterns, causes, consequences scientifically interesting concern key issues framework evolution maintenance We showcase solutions questions define - whether or not migrate, why where when migrate may depend individual characteristics conditions. explore links strategies, threats overexploitation, makeovers, management differently influence vulnerability depending their strategies. Our goal provide broad overview knowledge emerging area, spur future research development informed management, ultimately promote protection

Language: Английский

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