Dataset Information

Resolving fine-scale population structure and fishery exploitation using sequenced microsatellites in a northern fish.

ABSTRACT: The resiliency of populations and species to environmental change is dependent on the maintenance of genetic diversity, and as such, quantifying diversity is central to combating ongoing widespread reductions in biodiversity. With the advent of next-generation sequencing, several methods now exist for resolving fine-scale population structure, but the comparative performance of these methods for genetic assignment has rarely been tested. Here, we evaluate the performance of sequenced microsatellites and a single nucleotide polymorphism (SNP) array to resolve fine-scale population structure in a critically important salmonid in north eastern Canada, Arctic Charr (Salvelinus alpinus). We also assess the utility of sequenced microsatellites for fisheries applications by quantifying the spatial scales of movement and exploitation through genetic assignment of fishery samples to rivers of origin and comparing these results with a 29-year tagging dataset. Self-assignment and simulation-based analyses of 111 genome-wide microsatellite loci and 500 informative SNPs from 28 populations of Arctic Charr in north-eastern Canada identified largely river-specific genetic structure. Despite large differences (~4X) in the number of loci surveyed between panels, mean self-assignment accuracy was similar with the microsatellite loci and the SNP panel (>90%). Subsequent analysis of 996 fishery-collected samples using the microsatellite panel revealed that larger rivers contribute greater numbers of individuals to the fishery and that coastal fisheries largely exploit individuals originating from nearby rivers, corroborating results from traditional tagging experiments. Our results demonstrate the efficacy of sequence-based microsatellite genotyping to advance understanding of fine-scale population structure and harvest composition in northern and understudied species.

SUBMITTER: Layton KKS

PROVIDER: S-EPMC7232759 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Resolving fine-scale population structure and fishery exploitation using sequenced microsatellites in a northern fish.

Layton Kara K S KKS Dempson Brian B Snelgrove Paul V R PVR Duffy Steven J SJ Messmer Amber M AM Paterson Ian G IG Jeffery Nicholas W NW Kess Tony T Horne John B JB Salisbury Sarah J SJ Ruzzante Daniel E DE Bentzen Paul P Côté David D Nugent Cameron M CM Ferguson Moira M MM Leong Jong S JS Koop Ben F BF Bradbury Ian R IR

Evolutionary applications 20200220 5

The resiliency of populations and species to environmental change is dependent on the maintenance of genetic diversity, and as such, quantifying diversity is central to combating ongoing widespread reductions in biodiversity. With the advent of next-generation sequencing, several methods now exist for resolving fine-scale population structure, but the comparative performance of these methods for genetic assignment has rarely been tested. Here, we evaluate the performance of sequenced microsatell ...[more]

PMID: 32431752

Similar Datasets

Project description:BackgroundIllumina's sequencing platforms are currently the most utilised sequencing systems worldwide. The technology has rapidly evolved over recent years and provides high throughput at low costs with increasing read-lengths and true paired-end reads. However, data from any sequencing technology contains noise and our understanding of the peculiarities and sequencing errors encountered in Illumina data has lagged behind this rapid development.ResultsWe conducted a systematic investigation of errors and biases in Illumina data based on the largest collection of in vitro metagenomic data sets to date. We evaluated the Genome Analyzer II, HiSeq and MiSeq and tested state-of-the-art low input library preparation methods. Analysing in vitro metagenomic sequencing data allowed us to determine biases directly associated with the actual sequencing process. The position- and nucleotide-specific analysis revealed a substantial bias related to motifs (3mers preceding errors) ending in "GG". On average the top three motifs were linked to 16 % of all substitution errors. Furthermore, a preferential incorporation of ddGTPs was recorded. We hypothesise that all of these biases are related to the engineered polymerase and ddNTPs which are intrinsic to any sequencing-by-synthesis method. We show that quality-score-based error removal strategies can on average remove 69 % of the substitution errors - however, the motif-bias remains.ConclusionSingle-nucleotide polymorphism changes in bacterial genomes can cause significant changes in phenotype, including antibiotic resistance and virulence, detecting them within metagenomes is therefore vital. Current error removal techniques are not designed to target the peculiarities encountered in Illumina sequencing data and other sequencing-by-synthesis methods, causing biases to persist and potentially affect any conclusions drawn from the data. In order to develop effective diagnostic and therapeutic approaches we need to be able to identify systematic sequencing errors and distinguish these errors from true genetic variation.

Project description:Abstract Aquaculture is growing rapidly worldwide, and sustainability is dependent on an understanding of current genetic variation and levels of connectivity among populations. Genetic data are essential to mitigate the genetic and ecological impacts of aquaculture on wild populations and guard against unintended human‐induced loss of intraspecific diversity in aquacultured lines. Impacts of disregarding genetics can include loss of diversity within and between populations and disruption of local adaptation patterns, which can lead to a decrease in fitness. The northern hard clam, Mercenaria mercenaria (Linnaeus, 1758), is an economically valuable aquaculture species along the North American Atlantic and Gulf coasts. Hard clams have a pelagic larval phase that allows for dispersal, but the level of genetic connectivity among geographic areas is not well understood. To better inform the establishment of site‐appropriate aquaculture brood stocks, this study used DArTseq™ genotyping by sequencing to characterize the genetic stock structure of wild clams sampled along the east coast of North America and document genetic diversity within populations. Samples were collected from 15 locations from Prince Edward Island, Canada, to South Carolina, USA. Stringent data filtering resulted in 4960 single nucleotide polymorphisms from 448 individuals. Five genetic breaks separating six genetically distinct populations were identified: Canada, Maine, Massachusetts, Mid‐Atlantic, Chesapeake Bay, and the Carolinas (FST 0.003–0.046; p < 0.0001). This is the first study to assess population genetic structure of this economically important hard clam along a large portion of its native range with high‐resolution genomic markers, enabling identification of previously unrecognized population structure. Results of this study not only broaden insight into the factors shaping the current distribution of M. mercenaria but also reveal the genetic population dynamics of a species with a long pelagic larval dispersal period along the North American Atlantic and Gulf coasts.

Dataset Information

Resolving fine-scale population structure and fishery exploitation using sequenced microsatellites in a northern fish.

Publications

Resolving fine-scale population structure and fishery exploitation using sequenced microsatellites in a northern fish.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets