Description from NSF award abstract:
One of the strongest impacts there is on ocean species is reduction in population size due to fishing. Even for species that are not overfished, harvest takes a large fraction of the biggest and fastest growing individuals. As a result, fishing exerts strong natural selection on fish population, selecting for slow growing, small individuals. Experiments in artificial fishing have shown rapid evolution of growth rates, maturation size and other traits for lab populations. The classic Conover-Munsch experiments ten years ago showed the power of fishing to generate rapid evolution. However, no analysis of the genetic impact of fishing under such controlled conditions has been done, and no investigation of the way whole genomes respond to strong fisheries evolution has been attempted. Luckily, the Conover-Munsch samples - from the fish used in their classic experiment - have been preserved, and modern genomic techniques are now available that can analyze the way fisheries-induced evolution shaped the genetic diversity and genome architecture of these populations. Strong selection is known in other systems to leave a legacy of deleterious changes in the genome. The results of this study will be important components of understanding the long-term effects of fishing because they will for the first time allow a mechanistic understanding of how natural selection works on fish populations. The project will also compare the changes that occur after the relaxation of fishing pressure to estimate if there is a legacy of deleterious genome changes in fished species that impedes their recovery. The data from this study will show how fishing creates change at loci under selection, and also how this strong selection generates other, non-adaptive shifts because of genetic hitchhiking and inbreeding.
The investigators will use next generation DNA sequencing to sequence the protein coding regions of the Conover-Munsch fish samples. They will discover, document and compare genetic variants across the genome in lines selected for large size, in lines selected for small size, and in the original populations in order to chart evolutionary changes at the genomic level imposed by fishing. They will use outlier analyses to pinpoint loci at which strong selection has acted to change allele frequencies. They will compare these changes to changes in fish populations after the relaxation of fishing in order to distinguish evolutionary changes that are easily reversible from those that are not. In addition, they will also compare genetic changes induced by fishing to those that occur naturally along an environmental gradient on the US east coast. Preliminary data indicate that many of the genetic variants selected for in the fisheries experiment are old variants - estimated by patterns of linkage disequilibrium - already present in the original population. Working on the genetics of the natural gradient will show which of these variants have been selected by evolutionary forces in the native environment, and subsequently been favored by the novel evolutionary pressure of fishing.
Dataset | Latest Version Date | Current State |
---|---|---|
NCBI accession numbers and associated metadata for raw low-coverage genomic sequence reads from 876 different Atlantic silverside individuals | 2019-02-04 | Final no updates expected |
Atlantic silverside (Menidia menidia) cDNA transcriptome and TSA accessions from specimens collected at Poquott Beach, New York in June of 2013 (Fishery Genome Changes project) | 2017-04-06 | Final no updates expected |
Lead Principal Investigator: Stephen R. Palumbi
Stanford University - Hopkins (Stanford-HMS)
Data Management Plan received by BCO-DMO on 30 May 2014. (49.98 KB)
12/12/2014