Genotyping‐in‐Thousands by sequencing (GT‐seq) is a method that uses next‐generation sequencing of multiplexed PCR products to generate genotypes from relatively small panels (50–500) of targeted single‐nucleotide polymorphisms (SNPs) for thousands of individuals in a single Illumina HiSeq lane. This method uses only unlabelled oligos and PCR master mix in two thermal cycling steps for amplification of targeted SNP loci. During this process, sequencing adapters and dual barcode sequence tags are incorporated into the amplicons enabling thousands of individuals to be pooled into a single sequencing library. Post sequencing, reads from individual samples are split into individual files using their unique combination of barcode sequences. Genotyping is performed with a simple perl script which counts amplicon‐specific sequences for each allele, and allele ratios are used to determine the genotypes. We demonstrate this technique by genotyping 2068 individual steelhead trout (Oncorhynchus mykiss) samples with a set of 192 SNP markers in a single library sequenced in a single Illumina HiSeq lane. Genotype data were 99.9% concordant to previously collected TaqMan™ genotypes at the same 192 loci, but call rates were slightly lower with GT‐seq (96.4%) relative to Taqman (99.0%). Of the 192 SNPs, 187 were genotyped in ≥90% of the individual samples and only 3 SNPs were genotyped in <70% of samples. This study demonstrates amplicon sequencing with GT‐seq greatly reduces the cost of genotyping hundreds of targeted SNPs relative to existing methods by utilizing a simple library preparation method and massive efficiency of scale.

Genotyping-in-Thousands By Sequencing (GT-seq): A Cost Effective SNP Genotyping Method Based on Custom Amplicon Sequencing - Rainbow Trout

Biological invasions are increasing globally in number and extent despite efforts to restrict their spread. Knowledge of incursion pathways is necessary to prevent new invasions and to design effective biosecurity protocols at source and recipient locations. This study uses genome-wide single nucleotide polymorphisms (SNPs) to determine the origin of 115 incursive Aedes aegypti(yellow fever mosquito) detected at international ports in Australia and New Zealand. We also genotyped mosquitoes at three point mutations in the voltage-sensitive sodium channel (Vssc) gene: V1016G, F1534C and S989P. These mutations confer knockdown resistance to synthetic pyrethroid insecticides, widely used for controlling invertebrate pests. We first delineated reference populations using Ae. aegypti sampled from 15 locations in Asia, South America, Australia and the Pacific Islands. Incursives were assigned to these populations using discriminant analysis of principal components (DAPC) and an assignment test with a support vector machine predictive model. Bali, Indonesia, was the most common origin of Ae. aegypti detected in Australia, while Ae. aegypti detected in New Zealand originated from Pacific Islands such as Fiji. Most incursives had the same allelic genotype across the three Vsscgene point mutations, which confers strong resistance to synthetic pyrethroids, the only insecticide class used in current, widely implemented aircraft disinsection protocols endorsed by the World Health Organization (WHO). Additionally, all internationally assigned Ae. aegypti had Vssc point mutations linked to pyrethroid resistance that are not found in Australian populations. These findings demonstrate that protocols for preventing introductions of invertebrates must consider insecticide resistance, and highlight the usefulness of genomic data sets for managing global biosecurity objectives.

/pdf/tracking-genetic-invasions-genome-wide-single-nucleotide-1duwuo08i6.pdf

Tracking genetic invasions: Genome-wide single nucleotide polymorphisms reveal the source of pyrethroid-resistant Aedes aegypti (yellow fever mosquito) incursions at international ports.

Atlantic herring, Clupea harengus, have complex population structures. Mixing of populations is known, but the extent of connectivity is still unclear. Phenotypic plasticity results in divergent phenotypes in response to environmental factors. A marked salinity gradient occurs from Atlantic Ocean (salinity 35) into the Baltic Sea (salinity range 2-12). Herring from both habitats display phenotypic and genetic variability. To explore how genetic factors and salinity influence phenotypic traits like growth, number of vertebrae and otolith shape an experimental population consisting of Atlantic purebreds and Atlantic/Baltic F1 hybrids were incubated and co-reared at two different salinities, 16 and 35, for three years. The F1-generation was repeatedly sampled to evaluate temporal variation. A von Bertalanffy growth model indicated that reared Atlantic purebreds had a higher maximum length (26.2 cm) than Atlantic/Baltic hybrids (24.8 cm) at salinity 35, but not at salinity 16 (25.0 and 24.8 cm, respectively). In contrast, Atlantic/Baltic hybrids achieved larger size-at-age than the wild caught Baltic parental group. Mean vertebral counts and otolith aspect ratios were higher for reared Atlantic purebreds than Atlantic/Baltic hybrids, consistent with the differences between parental groups. There were no significant differences in vertebral counts and otolith aspect ratios between herring with the same genotype but raised in different salinities. A Canonical Analysis of Principal Coordinates was applied to analyze the variation in wavelet coefficients that described otolith shape. The first discriminating axis identified the differences between Atlantic purebreds and Atlantic/Baltic hybrids, while the second axis represented salinity differences. Assigning otoliths based on genetic groups (Atlantic purebreds vs. Atlantic/Baltic hybrids) yielded higher classification success (~90%) than based on salinities (16 vs. 35; ~60%). Our results demonstrate that otolith shape and vertebral counts have a significant genetic component and are therefore useful for studies on population dynamics and connectivity.

/pdf/genetic-factors-have-a-major-effect-on-growth-number-of-nh4k4289ga.pdf

Genetic factors have a major effect on growth, number of vertebrae and otolith shape in Atlantic herring (Clupea harengus)

Resolving stock structure is crucial for fisheries conservation to ensure that the spatial implementation of management is commensurate with that of biological population units. To address this in the economically important European lobster (Homarus gammarus), genetic structure was explored across the species' range using a small panel of single nucleotide polymorphisms (SNPs) previously isolated from restriction-site-associated DNA sequencing; these SNPs were selected to maximize differentiation at a range of both broad and fine scales. After quality control and filtering, 1,278 lobsters from 38 sampling sites were genotyped at 79 SNPs. The results revealed a pronounced phylogeographic break between the Atlantic and Mediterranean basins, while structure within the Mediterranean was also apparent, partitioned between lobsters from the central Mediterranean and the Aegean Sea. In addition, a genetic cline across the north-east Atlantic was revealed using both putatively neutral and outlier SNPs, but the precise driver(s) of this clinal pattern-isolation by distance, secondary contact, selection across an environmental gradient, or a combination of these factors-remains undetermined. Putatively neutral markers differentiated lobsters from Oosterschelde, an estuary on the Dutch coast, a finding likely explained by past bottlenecks and limited gene flow with adjacent North Sea populations. Building on the findings of our spatial genetic analysis, we were able to test the accuracy of assigning lobsters at various spatial scales, including to basin of origin (Atlantic or Mediterranean), region of origin and sampling location. The predictive model assembled using 79 SNPs correctly assigned 99.7% of lobsters not used to build the model to their basin of origin, but accuracy decreased to region of origin and again to sampling location. These results are of direct relevance to managers of lobster fisheries and hatcheries, and provide the basis for a genetic tool for tracing the origin of European lobsters in the food supply chain.

Single nucleotide polymorphisms reveal a genetic cline across the north-east Atlantic and enable powerful population assignment in the European lobster.

Seasonal habitat-use differences among Lake Erie’s walleye stocks

Summary
1.The use of biomarkers (e.g., genetic, microchemical, and morphometric characteristics) to discriminate among and assign individuals to a population can benefit species conservation and management by facilitating our ability to understand population structure and demography.

2.Tools that can evaluate the reliability of large genomic datasets for population discrimination and assignment, as well as allow their integration with non-genetic markers for the same purpose, are lacking. Our R package, assignPOP, provides both functions in a supervised machine-learning framework.

3.assignPOP uses Monte-Carlo and K-fold cross-validation procedures, as well as principal component analysis (PCA), to estimate assignment accuracy and membership probabilities, using training (i.e., baseline source population) and test (i.e., validation) datasets that are independent. A user then can build a specified predictive model based on the relative sizes of these datasets and classification functions, including linear discriminant analysis, support vector machine, naive Bayes, decision tree, and random forest.

4.assignPOP can benefit any researcher who seeks to use genetic or non-genetic data to infer population structure and membership of individuals. assignPOP is a freely available R package under the GPL license, and can be downloaded from CRAN or at https://github.com/alexkychen/assignPOP. A comprehensive tutorial can also be found at https://alexkychen.github.io/assignPOP/.

This article is protected by copyright. All rights reserved.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/2041-210X.12897

assignPOP: An r package for population assignment using genetic, non‐genetic, or integrated data in a machine‐learning framework

RAD-Seq Refines Previous Estimates of Genetic Structure in Lake Erie Walleye

Otolith microchemistry shows natal philopatry of walleye in western Lake Erie

Using Genomic Data to Guide Walleye Management in the Great Lakes

Mixed-stock analyses using genetic markers have informed fisheries management in cases where strong genetic differentiation occurs among local spawning populations, yet many fisheries are supported by multiple spawning stocks that are weakly differentiated. Freshwater fisheries exemplify this problem, with many harvested populations supported by multiple stocks of young evolutionary age that are isolated across small spatial scales. As a result, attempts to conduct genetic mixed-stock analyses of inland fisheries have often been unsuccessful. Advances in genomic sequencing now offer the ability to discriminate among populations with weak population structure by providing the necessary resolution to conduct mixed-stock assignment among previously indistinguishable stocks. We demonstrate the use of genomic data to conduct a mixed-stock analysis of Lake Eries commercial and recreational walleye (Sander vitreus) fisheries and estimate the relative harvest of weakly differentiated stocks (pairwise FST < 0.01). We used RAD-capture (Rapture) to sequence and genotype individuals at 12,081 loci that had been previously determined to be capable of discriminating between western and eastern basin stocks with 95% reassignment accuracy, which was not possible in the past with microsatellite markers. Genetic assignment of 1,075 fish harvested from recreational and commercial fisheries in the eastern basin indicated that western basin stocks constituted the majority of individuals harvested during peak walleye fishing season (July - September). Composition of harvest changed seasonally, with eastern basin fish comprising much of the early season harvest (May - June). Clear spatial structure in harvest composition existed; more easterly sites contained more individuals of east basin origin than did westerly sites. Our study provides important stock contribution estimates for Lake Erie fishery management and demonstrates the power of genomic data to facilitate mixed-stock analysis in exploited fish populations with weak population structure or limited existing genetic resources.

/pdf/mixed-stock-analysis-in-the-age-of-genomics-rapture-cvvnwpms4s.pdf

Mixed-stock analysis in the age of genomics: Rapture genotyping enables evaluation of stock-specific exploitation in a freshwater fish population with weak genetic structure

Kuan-Yu Chen

Papers

assignPOP: An r package for population assignment using genetic, non‐genetic, or integrated data in a machine‐learning framework

RAD-Seq Refines Previous Estimates of Genetic Structure in Lake Erie Walleye

Otolith microchemistry shows natal philopatry of walleye in western Lake Erie

Using Genomic Data to Guide Walleye Management in the Great Lakes

Mixed-stock analysis in the age of genomics: Rapture genotyping enables evaluation of stock-specific exploitation in a freshwater fish population with weak genetic structure