Finding markers that make a difference: DNA pooling and SNP-arrays identify population informative markers for genetic stock identification

Genetic diversity and breed-informative SNPs identification in domestic pig populations using coding SNPs

Background: The use of breed-informative genetic markers, specifically coding Single Nucleotide Polymorphisms (SNPs), is crucial for breed traceability, authentication of meat and dairy products, and the preservation and improvement of pig breeds. By identifying breed informative markers, we aimed to gain insights into the genetic mechanisms that influence production traits, enabling informed decisions in animal management and promoting sustainable pig production to meet the growing demand for animal products. Methods: Our dataset consists of 300 coding SNPs genotyped from three Italian commercial pig populations: Landrace, Yorkshire, and Duroc. Firstly, we analyzed the genetic diversity among the populations. Then, we applied a discriminant analysis of principal components to identify the most informative SNPs for discriminating between these populations. Lastly, we conducted a functional enrichment analysis to identify the most enriched pathways related to the genetic variation observed in the pig populations. Results: The alpha diversity indexes revealed a high genetic diversity within the three breeds. The higher proportion of observed heterozygosity than expected revealed an excess of heterozygotes in the populations that was supported by negative values of the fixation index (FIS) and deviations from the Hardy-Weinberg equilibrium. The Euclidean distance, the pairwise FST, and the pairwise Nei's GST genetic distances revealed that Yorkshire and Landrace breeds are genetically the closest, with distance values of 2.242, 0.029, and 0.033, respectively. Conversely, Landrace and Duroc breeds showed the highest genetic divergence, with distance values of 2.815, 0.048, and 0.052, respectively. We identified 28 significant SNPs that are related to phenotypic traits and these SNPs were able to differentiate between the pig breeds with high accuracy. The Functional Enrichment Analysis of the informative SNPs highlighted biological functions related to DNA packaging, chromatin integrity, and the preparation of DNA into higher-order structures. Conclusion: Our study sheds light on the genetic underpinnings of phenotypic variation among three Italian pig breeds, offering potential insights into the mechanisms driving breed differentiation. By prioritizing breed-specific coding SNPs, our approach enables a more focused analysis of specific genomic regions relevant to the research question compared to analyzing the entire genome.

A web tool for the global identification of pig breeds

BACKGROUND

Natural and artificial selection for more than 9000 years have led to a variety of domestic pig breeds. Accurate identification of pig breeds is important for breed conservation, sustainable breeding, pork traceability, and local resource registration.

RESULTS

We evaluated the performance of four selectors and six classifiers for breed identification using a wide range of pig breeds (N = 91). The internal cross-validation and external independent testing showed that partial least squares regression (PLSR) was the most effective selector and partial least squares-discriminant analysis (PLS-DA) was the most powerful classifier for breed identification among many breeds. Five-fold cross-validation indicated that using PLSR as the selector and PLS-DA as the classifier to discriminate 91 pig breeds yielded 98.4% accuracy with only 3K single nucleotide polymorphisms (SNPs). We also constructed a reference dataset with 124 pig breeds and used it to develop the web tool iDIGs ( http://alphaindex.zju.edu.cn/iDIGs_en/ ) as a comprehensive application for global pig breed identification. iDIGs allows users to (1) identify pig breeds without a reference population and (2) design small panels to discriminate several specific pig breeds.

CONCLUSIONS

In this study, we proved that breed identification among a wide range of pig breeds is feasible and we developed a web tool for such pig breed identification.

Single Nucleotide Polymorphism Markers with Applications in Conservation and Exploitation of Aquatic Natural Populations

Simple Summary

In recent decades, societies, states and local authorities have become increasingly aware that for effective long-term management and protection of aquatic ecosystems and populations, it is necessary to take into account the genetic changes occurring in these populations. One type of high-resolution molecular marker suitable for studying the neutral and adaptive genetic diversity of populations is single nucleotide polymorphism (SNP). This review is an attempt to show the benefits of using SNPs to recognize natural populations of aquatic animals and detect the threats to them from accidentally or intentionally released farm animals, fishery and global climate changes. It is postulated that conservation actions should protect not only pristine natural populations that are endangered or overfished, but also protect populations of non-threatened species from unnecessarily released semi-domesticated animals. The enhancement of natural populations with farmed material usually reduces their genetic diversity. Experimental size-selective catches of artificially created populations have caused evolutionary changes in the life cycles of fishes. However, fishery-induced evolution in natural populations is difficult to observe. The negative measurable effects on populations can be expected when the number of breeding individuals is reduced below 100, which occurs very rarely in the sea and more often in fragmented freshwater streams, ponds and seasonal rivers.

Abstract

An increasing number of aquatic species have been studied for genetic polymorphism, which extends the knowledge on their natural populations. One type of high-resolution molecular marker suitable for studying the genetic diversity of large numbers of individuals is single nucleotide polymorphism (SNP). This review is an attempt to show the range of applications of SNPs in studies of natural populations of aquatic animals. In recent years, SNPs have been used in the genetic analysis of wild and enhanced fish and invertebrate populations in natural habitats, exploited migratory species in the oceans, migratory anadromous and freshwater fish and demersal species. SNPs have been used for the identification of species and their hybrids in natural environments, to study the genetic consequences of restocking for conservation purposes and the negative effects on natural populations of fish accidentally escaping from culture. SNPs are very useful for identifying genomic regions correlated with phenotypic variants relevant for wildlife protection, management and aquaculture. Experimental size-selective catches of populations created in tanks have caused evolutionary changes in life cycles of fishes. The research results have been discussed to clarify whether the fish populations in natural conditions can undergo changes due to selective harvesting targeting the fastest-growing fishes.

A new GTSeq resource to facilitate multijurisdictional research and management of walleye Sander vitreus

Conservation and management professionals often work across jurisdictional boundaries to identify broad ecological patterns. These collaborations help to protect populations whose distributions span political borders. One common limitation to multijurisdictional collaboration is consistency in data recording and reporting. This limitation can impact genetic research, which relies on data about specific markers in an organism's genome. Incomplete overlap of markers between separate studies can prevent direct comparisons of results. Standardized marker panels can reduce the impact of this issue and provide a common starting place for new research. Genotyping-in-thousands (GTSeq) is one approach used to create standardized marker panels for nonmodel organisms. Here, we describe the development, optimization, and early assessments of a new GTSeq panel for use with walleye (Sander vitreus) from the Great Lakes region of North America. High genome-coverage sequencing conducted using RAD capture provided genotypes for thousands of single nucleotide polymorphisms (SNPs). From these markers, SNP and microhaplotype markers were chosen, which were informative for genetic stock identification (GSI) and kinship analysis. The final GTSeq panel contained 500 markers, including 197 microhaplotypes and 303 SNPs. Leave-one-out GSI simulations indicated that GSI accuracy should be greater than 80% in most jurisdictions. The false-positive rates of parent-offspring and full-sibling kinship identification were found to be low. Finally, genotypes could be consistently scored among separate sequencing runs >94% of the time. Results indicate that the GTSeq panel that we developed should perform well for multijurisdictional walleye research throughout the Great Lakes region.

Lack of genetic differentiation in yellowfin tuna has conservation implications in the Eastern Pacific Ocean

Yellowfin tuna, Thunnus albacares, is an important global fishery and of particular importance in the Eastern Pacific Ocean (EPO). According to the 2019 Inter-American Tropical Tuna Commission (IATTC) assessment, yellowfin tuna within the EPO is a single stock, and is being managed as one stock. However, previous studies indicate site fidelity, or limited home ranges, of yellowfin tuna which suggests the potential for multiple yellowfin tuna stocks within the EPO, which was supported by a population genetic study using microsatellites. If numerous stocks are present, management at the wrong spatial scales could cause the loss of minor yellowfin tuna populations in the EPO. In this study we used double digestion RADseq to assess the genetic structure of yellowfin tuna in the EPO. A total of 164 yellowfin tuna from Cabo San Lucas, México, and the Galápagos Islands and Santa Elena, Ecuador, were analysed using 18,011 single nucleotide polymorphisms. Limited genetic differentiation (F_ST = 0.00058–0.00328) observed among the sampling locations (México, Ecuador, Peru, and within Ecuador) is consistent with presence of a single yellowfin tuna population within the EPO. Our findings are consistent with the IATTC assessment and provide further evidence of the need for transboundary cooperation for the successful management of this important fishery throughout the EPO.

In-field genetic stock identification of overwintering coho salmon in the Gulf of Alaska: Evaluation of Nanopore sequencing for remote real-time deployment

Genetic stock identification (GSI) from genotyping‐by‐sequencing of single nucleotide polymorphism (SNP) loci has become the gold standard for stock of origin identification in Pacific salmon. The sequencing platforms currently applied require large batch sizes and multiday processing in specialized facilities to perform genotyping by the thousands. However, recent advances in third‐generation single‐molecule sequencing platforms, such as the Oxford Nanopore minION, provide base calling on portable, pocket‐sized sequencers and promise real‐time, in‐field stock identification of variable batch sizes. Here we evaluate utility and comparability to established GSI platforms of at‐sea stock identification of coho salmon (Oncorhynchus kisutch) using targeted SNP amplicon sequencing on the minION platform during a high‐sea winter expedition to the Gulf of Alaska. As long read sequencers are not optimized for short amplicons, we concatenate amplicons to increase coverage and throughput. Nanopore sequencing at‐sea yielded data sufficient for stock assignment for 50 out of 80 individuals. Nanopore‐based SNP calls agreed with Ion Torrent‐based genotypes in 83.25%, but assignment of individuals to stock of origin only agreed in 61.5% of individuals, highlighting inherent challenges of Nanopore sequencing, such as resolution of homopolymer tracts and indels. However, poor representation of assayed salmon in the queried baseline data set contributed to poor assignment confidence on both platforms. Future improvements will focus on lowering turnaround time and cost, increasing accuracy and throughput, as well as augmentation of the existing baselines. If successfully implemented, Nanopore sequencing will provide an alternative method to the large‐scale laboratory approach by providing mobile small batch genotyping to diverse stakeholders.

Selection of genome-wide SNPs for pooled allelotyping assays useful for population monitoring

Parasitic worms are serious pests of humans, livestock and crops worldwide. Multiple management strategies are employed in order to reduce their impact, and some of these may affect their genome and population allelic frequency distribution. The evolution of chemical resistance, ecological changes, and pest dispersal have allowed an increasing number of pests to become difficult to control with current management methods. Their lifestyle limits the use of ecological and individual-based management of populations. There is a need to develop rapid, affordable, and simple diagnostics to assess the efficacy of management strategies and delay the evolution of resistance to these strategies. This study presents a multi-locus, equal-representation, whole genome pooled SNPs selection approach as a monitoring tool for the ovine nematode parasite Haemonchus contortus. The SNP selection method used two reference genomes of different quality, then validated these SNPs against a high-quality recent genome assembly. From over 11 million high-quality SNPs identified, 334 SNPs were selected, of which 262 were species-specific, yielded similar allele frequencies when assessed as multiple individuals or as pools of individuals, and suitable to distinguish mixed nematode isolate pools from single isolate pools. As a proof-of-concept, 21 Australian H. contortus populations with various phenotypes and genotypes were screened. This analysis confirmed the overall low-level of genetic differentiation between populations collected from the field, but clearly identifying highly inbred populations, and populations showing genetic signatures associated with chemical resistance. The analysis showed that 66% of the SNPs were necessary for stability in assessing population genetic patterns, and SNP pairs did not show linkage according to allelic frequencies across the 21 populations. This method demonstrates that ongoing monitoring of parasite allelic frequencies and genetic changes can be achieved as a management assessment tool to identify drug-treatment failure, population incursions, and inbreeding signatures due to selection. The SNP selection method could also be applied to other parasite species.

The details are in the genome-wide SNPs: Fine scale evolution of the Malaysian weedy rice

Weedy rice (Oryza spp.) is a major nuisance to rice farmers from all over the world. Although the emergence of weedy rice in East Malaysia on the island of Borneo is very recent, the threat to rice yield has reached an alarming stage. Using 47,027 genotyping-by-sequencing (GBS)-derived SNPs and candidate gene analysis of the plant architecture domestication gene TAC1, we assessed the genetic variations and evolutionary origin of weedy rice in East Malaysia. Our findings revealed two major evolutionary paths for genetically distinct weedy rice types. Whilst the cultivar-like weedy rice are very likely to be the weedy descendant of local coexisting cultivars, the wild-like weedy rice appeared to have arisen through two possible routes: (i) accidental introduction from Peninsular Malaysia weedy rice populations, and (ii) weedy descendants of coexisting cultivars. The outcome of our genetic analyses supports the notion that Sabah cultivars and Peninsular Malaysia weedy rice are the potential progenitors of Sabah weedy rice. Similar TAC1 haplotypes were shared between Malaysian cultivated and weedy rice populations, which further supported the findings of our GBS-SNP analyses. These different strains of weedy rice have convergently evolved shared traits, such as seeds shattering and open tillers. A comparison with our previous simple-sequence repeat-based population genetic analyses highlights the strength of genome-wide SNPs, including detection of admixtures and low-level introgression events. These findings could inform better strategic management for controlling the spread of weedy rice in the region.

Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array

Genebanks harbor original landraces carrying many original favorable alleles for mitigating biotic and abiotic stresses. Their genetic diversity remains, however, poorly characterized due to their large within genetic diversity. We developed a high-throughput, cheap and labor saving DNA bulk approach based on single-nucleotide polymorphism (SNP) Illumina Infinium HD array to genotype landraces. Samples were gathered for each landrace by mixing equal weights from young leaves, from which DNA was extracted. We then estimated allelic frequencies in each DNA bulk based on fluorescent intensity ratio (FIR) between two alleles at each SNP using a two step-approach. We first tested either whether the DNA bulk was monomorphic or polymorphic according to the two FIR distributions of individuals homozygous for allele A or B, respectively. If the DNA bulk was polymorphic, we estimated its allelic frequency by using a predictive equation calibrated on FIR from DNA bulks with known allelic frequencies. Our approach: (i) gives accurate allelic frequency estimations that are highly reproducible across laboratories, (ii) protects against false detection of allele fixation within landraces. We estimated allelic frequencies of 23,412 SNPs in 156 landraces representing American and European maize diversity. Modified Roger's genetic Distance between 156 landraces estimated from 23,412 SNPs and 17 simple sequence repeats using the same DNA bulks were highly correlated, suggesting that the ascertainment bias is low. Our approach is affordable, easy to implement and does not require specific bioinformatics support and laboratory equipment, and therefore should be highly relevant for large-scale characterization of genebanks for a wide range of species.

Rapture facilitates inexpensive and high-throughput parent-based tagging in salmonids

Accurate methods for tracking individuals are crucial to the success of fisheries and aquaculture management. Management of migratory salmonid populations, which are important for the health of many economies, ecosystems, and indigenous cultures, is particularly dependent on data gathered from tagged fish. However, the physical tagging methods currently used have many challenges including cost, variable marker retention, and information limited to tagged individuals. Genetic tracking methods combat many of the problems associated with physical tags, but have their own challenges including high cost, potentially difficult marker design, and incompatibility of markers across species. Here we show the feasibility of a new genotyping method for parent-based tagging (PBT), where individuals are tracked through the inherent genetic relationships with their parents. We found that Rapture sequencing, a combination of restriction-site associated DNA and capture sequencing, provides sufficient data for parentage assignment. Additionally, the same capture bait set, which targets specific restriction-site associated DNA loci, can be used for both Rainbow Trout Oncorhynchus mykiss and Chinook Salmon Oncorhynchus tshawytscha. We input 248 single nucleotide polymorphisms from 1,121 samples to parentage assignment software and compared parent-offspring relationships of the spawning pairs recorded in a hatchery. Interestingly, our results suggest sperm contamination during hatchery spawning occurred in the production of 14% of offspring, further confirming the need for genetic tagging in accurately tracking individuals. PBT with Rapture successfully assigned progeny to parents with a 98.86% accuracy with sufficient genetic data. Cost for this pilot study was approximately $3 USD per sample. As costs vary based on the number of markers used and individuals sequenced, we expect that when implemented at a large-scale, per sample costs could be further decreased. We conclude that Rapture PBT provides a cost-effective and accurate alternative to the physical coded wire tags, and other genetic-based methods.

DNA Methylation Changes in the Sperm of Captive-Reared Fish: A Route to Epigenetic Introgression in Wild Populations

Interbreeding between hatchery-reared and wild fish, through deliberate stocking or escapes from fish farms, can result in rapid phenotypic and gene expression changes in hybrids, but the underlying mechanisms are unknown. We assessed if one generation of captive breeding was sufficient to generate inter- and/or transgenerational epigenetic modifications in Atlantic salmon. We found that the sperm of wild and captive-reared males differed in methylated regions consistent with early epigenetic signatures of domestication. Some of the epigenetic marks that differed between hatchery and wild males affected genes related to transcription, neural development, olfaction, and aggression, and were maintained in the offspring beyond developmental reprogramming. Our findings suggest that rearing in captivity may trigger epigenetic modifications in the sperm of hatchery fish that could explain the rapid phenotypic and genetic changes observed among hybrid fish. Epigenetic introgression via fish sperm represents a previously unappreciated mechanism that could compromise locally adapted fish populations.

Conservation and Management of Salmon in the Age of Genomics

Salmon were among the first nonmodel species for which systematic population genetic studies of natural populations were conducted, often to support management and conservation. The genomics revolution has improved our understanding of the evolutionary ecology of salmon in two major ways: (a) Large increases in the numbers of genetic markers (from dozens to 10⁴-10⁶) provide greater power for traditional analyses, such as the delineation of population structure, hybridization, and population assignment, and (b) qualitatively new insights that were not possible with traditional genetic methods can be achieved by leveraging detailed information about the structure and function of the genome. Studies of the first type have been more common to date, largely because it has taken time for the necessary tools to be developed to fully understand the complex salmon genome. We expect that the next decade will witness many new studies that take full advantage of salmonid genomic resources.

Determination of Varying Group Sizes for Pooling Procedure

Pooling is an attractive strategy in screening infected specimens, especially for rare diseases. An essential step of performing the pooled test is to determine the group size. Sometimes, equal group size is not appropriate due to population heterogeneity. In this case, varying group sizes are preferred and could be determined while individual information is available. In this study, we propose a sequential procedure to determine varying group sizes through fully utilizing available information. This procedure is data driven. Simulations show that it has good performance in estimating parameters.

Spatial dynamics and mixing of bluefin tuna in the Atlantic Ocean and Mediterranean Sea revealed using next-generation sequencing

The Atlantic bluefin tuna is a highly migratory species emblematic of the challenges associated with shared fisheries management. In an effort to resolve the species' stock dynamics, a genomewide search for spatially informative single nucleotide polymorphisms (SNPs) was undertaken, by way of sequencing reduced representation libraries. An allele frequency approach to SNP discovery was used, combining the data of 555 larvae and young-of-the-year (LYOY) into pools representing major geographical areas and mapping against a newly assembled genomic reference. From a set of 184,895 candidate loci, 384 were selected for validation using 167 LYOY. A highly discriminatory genotyping panel of 95 SNPs was ultimately developed by selecting loci with the most pronounced differences between western Atlantic and Mediterranean Sea LYOY. The panel was evaluated by genotyping a different set of LYOY (n = 326), and from these, 77.8% and 82.1% were correctly assigned to western Atlantic and Mediterranean Sea origins, respectively. The panel revealed temporally persistent differentiation among LYOY from the western Atlantic and Mediterranean Sea (F_ST  = 0.008, p = .034). The composition of six mixed feeding aggregations in the Atlantic Ocean and Mediterranean Sea was characterized using genotypes from medium (n = 184) and large (n = 48) adults, applying population assignment and mixture analyses. The results provide evidence of persistent population structuring across broad geographic areas and extensive mixing in the Atlantic Ocean, particularly in the mid-Atlantic Bight and Gulf of St. Lawrence. The genomic reference and genotyping tools presented here constitute novel resources useful for future research and conservation efforts.

Global genotype flow in Cercospora beticola populations confirmed through genotyping-by-sequencing

Genotyping-by-sequencing (GBS) was conducted on 333 Cercospora isolates collected from Beta vulgaris (sugar beet, table beet and swiss chard) in the USA and Europe. Cercospora beticola was confirmed as the species predominantly isolated from leaves with Cercospora leaf spot (CLS) symptoms. However, C. cf. flagellaris also was detected at a frequency of 3% in two table beet fields in New York. Resolution of the spatial structure and identification of clonal lineages in C. beticola populations using genome-wide single nucleotide polymorphisms (SNPs) obtained from GBS was compared to genotyping using microsatellites. Varying distance thresholds (bitwise distance = 0, 1.854599 × 10-4, and 1.298 × 10-3) were used for delineation of clonal lineages in C. beticola populations. Results supported previous reports of long distance dispersal of C. beticola through genotype flow. The GBS-SNP data set provided higher resolution in discriminating clonal lineages; however, genotype identification was impacted by filtering parameters and the distance threshold at which the multi-locus genotypes (MLGs) were contracted to multi-locus lineages. The type of marker or different filtering strategies did not impact estimates of population differentiation and structure. Results emphasize the importance of robust filtering strategies and designation of distance thresholds for delineating clonal lineages in population genomics analyses that depend on individual assignment and identification of clonal lineages. Detection of recurrent clonal lineages shared between the USA and Europe, even in the relaxed-filtered SNP data set and with a conservative distance threshold for contraction of MLGs, provided strong evidence for global genotype flow in C. beticola populations. The implications of intercontinental migration in C. beticola populations for CLS management are discussed.

Applications of random forest feature selection for fine-scale genetic population assignment

Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine‐learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F_ST ranking for selection of single nucleotide polymorphisms (SNP) for fine‐scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon (Salmo salar) and a published SNP data set for Alaskan Chinook salmon (Oncorhynchus tshawytscha). In each species, we identified the minimum panel size required to obtain a self‐assignment accuracy of at least 90% using each method to create panels of 50–700 markers Panels of SNPs identified using random forest‐based methods performed up to 7.8 and 11.2 percentage points better than F_ST‐selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self‐assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F_ST‐selected panels. Our results demonstrate a role for machine‐learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.

Estimating genomic diversity and population differentiation - an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri

BACKGROUND

Microsatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq).

RESULTS

Our analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR-H e) was not significantly correlated with genome-wide SNP diversity estimates (SNP-H e and θ Watterson) in A. halleri. Instead, microsatellite allelic richness (A r) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations (F ST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genome-wide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation.

CONCLUSIONS

We recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal.

SNPs selected by information content outperform randomly selected microsatellite loci for delineating genetic identification and introgression in the endangered dark European honeybee (Apis mellifera mellifera)

The honeybee (Apis mellifera) has been threatened by multiple factors including pests and pathogens, pesticides and loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the genetic integrity of the native A. m. mellifera (M-lineage) is endangered due to trading and intensive queen breeding with commercial subspecies of eastern European ancestry (C-lineage). Effective conservation actions require reliable molecular tools to identify pure-bred A. m. mellifera colonies. Microsatellites have been preferred for identification of A. m. mellifera stocks across conservation centres. However, owing to high throughput, easy transferability between laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolving power of a widely utilized microsatellite set to detect structure and introgression with that of different sets that combine a variable number of SNPs selected for their information content and genomic proximity to the microsatellite loci. Contrary to every SNP data set, microsatellites did not discriminate between the two lineages in the PCA space. Mean introgression proportions were identical across the two marker types, although at the individual level, microsatellites' performance was relatively poor at the upper range of Q-values, a result reflected by their lower precision. Our results suggest that SNPs are more accurate and powerful than microsatellites for identification of A. m. mellifera colonies, especially when they are selected by information content.

From population genomics to conservation and management: a workflow for targeted analysis of markers identified using genome-wide approaches in Atlantic salmon Salmo salar

A genotyping assay for the Ion Torrent Ion PGM platform was developed for fast and cost-effective targeted genotyping of key single nucleotide polymorphisms (SNPs) earlier identified using a genome-wide SNP array in Atlantic salmon Salmo salar. The method comprised a simple primer design step for multiplex-polymerase chain reaction (PCR), followed by two rounds of Ion Torrent Ion PGM sequencing to empirically evaluate marker efficiency in large multiplexes and to optimise or exclude them when necessary. Of 282 primer pairs initially tested, 217 were successfully amplified, indicating good amplification success (>75%). These markers included the sdy partial gene product to determine genetic sex, as well as three additional modules comprising SNPs for assessing neutral genetic variation (N_SNP = 150), examining functional genetic variation associated with sea age at maturity (N_SNP = 5), and for performing genetic subpopulation assignment (N_SNP = 61). The assay was primarily developed to monitor long-term genetic changes in S. salar from the Teno River, but modules are likely suitable for application in a wide range of S. salar populations. Furthermore, the fast and versatile assay development pipeline offers a strategy for developing targeted sequencing assays in any species.

Single nucleotide polymorphisms to discriminate different classes of hybrid between wild Atlantic salmon and aquaculture escapees

Many wild Atlantic salmon (Salmo salar) populations are threatened by introgressive hybridization from domesticated fish that have escaped from aquaculture facilities. A detailed understanding of the hybridization dynamics between wild salmon and aquaculture escapees requires discrimination of different hybrid classes; however, markers currently available to discriminate the two types of parental genome have limited power to do this. Using a high‐density Atlantic salmon single nucleotide polymorphism (SNP) array, in combination with pooled‐sample allelotyping and an F_st outlier approach, we identified 200 SNPs that differentiated an important Atlantic salmon stock from the escapees potentially hybridizing with it. By simulating multiple generations of wild–escapee hybridization, involving wild populations in two major phylogeographic lineages and a genetically diverse set of escapees, we showed that both the complete set of SNPs and smaller subsets could reliably assign individuals to different hybrid classes up to the third hybrid (F3) generation. This set of markers will be a useful tool for investigating the genetic interactions between native wild fish and aquaculture escapees in many Atlantic salmon populations.

Atlantic salmon populations reveal adaptive divergence of immune related genes - a duplicated genome under selection

Background

Populations of Atlantic salmon display highly significant genetic differences with unresolved molecular basis. These differences may result from separate postglacial colonization patterns, diversifying natural selection and adaptation, or a combination. Adaptation could be influenced or even facilitated by the recent whole genome duplication in the salmonid lineage which resulted in a partly tetraploid species with duplicated genes and regions.

Results

In order to elucidate the genes and genomic regions underlying the genetic differences, we conducted a genome wide association study using whole genome resequencing data from eight populations from Northern and Southern Norway. From a total of ~4.5 million sequencing-derived SNPs, more than 10 % showed significant differentiation between populations from these two regions and ten selective sweeps on chromosomes 5, 10, 11, 13–15, 21, 24 and 25 were identified. These comprised 59 genes, of which 15 had one or more differentiated missense mutation. Our analysis showed that most sweeps have paralogous regions in the partially tetraploid genome, each lacking the high number of significant SNPs found in the sweeps. The most significant sweep was found on Chr 25 and carried several missense mutations in the antiviral mx genes, suggesting that these populations have experienced differing viral pressures. Interestingly the second most significant sweep, found on Chr 5, contains two genes involved in the NF-KB pathway (nkap and nkrf), which is also a known pathogen target that controls a large number of processes in animals.

Conclusion

Our results show that natural selection acting on immune related genes has contributed to genetic divergence between salmon populations in Norway. The differences between populations may have been facilitated by the plasticity of the salmon genome. The observed signatures of selection in duplicated genomic regions suggest that the recently duplicated genome has provided raw material for evolutionary adaptation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2867-z) contains supplementary material, which is available to authorized users.

Genomewide introgressive hybridization patterns in wild Atlantic salmon influenced by inadvertent gene flow from hatchery releases

Many salmonid fish populations are threatened by genetic homogenization, primarily due to introgressive hybridization with hatchery-reared conspecifics. By applying genomewide analysis using two molecular marker types (1986 SNPs and 17 microsatellites), we assessed the genetic impacts of inadvertent gene flow via straying from hatchery releases on wild populations of Atlantic salmon in the Gulf of Finland, Baltic Sea, over 16 years (1996-2012). Both microsatellites and SNPs revealed congruent population genetic structuring, indicating that introgression changed the genetic make-up of wild populations by increasing genetic diversity and reducing genetic divergence. However, the degree of genetic introgression varied among studied populations, being higher in the eastern part and lower in the western part of Estonia, which most likely reflects the history of past stocking activities. Using kernel smoothing and permutation testing, we detected considerable heterogeneity in introgression patterns across the genome, with a large number of regions exhibiting nonrandom introgression widely dispersed across the genome. We also observed substantial variation in nonrandom introgression patterns within populations, as the majority of genomic regions showing elevated or reduced introgression were not consistently detected among temporal samples. This suggests that recombination, selection and stochastic processes may contribute to complex nonrandom introgression patterns. Our results suggest that (i) some genomic regions in Atlantic salmon are more vulnerable to introgressive hybridization, while others show greater resistance to unidirectional gene flow; and (ii) the hybridization of previously separated populations leads to complex and dynamic nonrandom introgression patterns that most likely have functional consequences for indigenous populations.

Establishing the evolutionary compatibility of potential sources of colonizers for overfished stocks: a population genomics approach

Identifying fish stock structure is fundamental to pinpoint stocks that might contribute colonizers to overfished stocks. However, a stock's potential to contribute to rebuilding hinges on demographic connectivity, a challenging parameter to measure. With genomics as a new tool, fisheries managers can detect signatures of natural selection and thus identify fishing areas likely to contribute evolutionarily compatible colonizers to an overfished area (i.e. colonizers that are not at a fitness disadvantage in the overfished area and able to reproduce at optimal rates). Identifying evolutionarily compatible stocks would help narrow the focus on establishing demographic connectivity where it matters. Here, we genotype 4723 SNPs in 616 orange roughy (Hoplostethus atlanticus) across five fishing areas off the Tasmanian coast in Australia. We ask whether these areas form a single genetic unit, and test for signatures of local adaptation. Results from amova, structure, discriminant analysis of principal components, BAYESASS and isolation by distance suggest that sampled locations are subjected to geneflow amounts that are above what is needed to establish 'drift connectivity'. However, it remains unclear whether there is a single panmictic population or several highly connected populations. Most importantly, we did not find any evidence of local adaptation, suggesting that the examined orange roughy stocks are evolutionarily compatible. The data have helped test an assumption of the orange roughy management programme and to formulate hypotheses regarding stock demographic connectivity. Overall, our results demonstrate the potential of genomics to inform fisheries management, even when evidence for stock structure is sparse.

Reduced SNP panels for genetic identification and introgression analysis in the dark honey bee (Apis mellifera mellifera)

Beekeeping activities, especially queen trading, have shaped the distribution of honey bee (Apis mellifera) subspecies in Europe, and have resulted in extensive introductions of two eastern European C-lineage subspecies (A. m. ligustica and A. m. carnica) into the native range of the M-lineage A. m. mellifera subspecies in Western Europe. As a consequence, replacement and gene flow between native and commercial populations have occurred at varying levels across western European populations. Genetic identification and introgression analysis using molecular markers is an important tool for management and conservation of honey bee subspecies. Previous studies have monitored introgression by using microsatellite, PCR-RFLP markers and most recently, high density assays using single nucleotide polymorphism (SNP) markers. While the latter are almost prohibitively expensive, the information gained to date can be exploited to create a reduced panel containing the most ancestry-informative markers (AIMs) for those purposes with very little loss of information. The objective of this study was to design reduced panels of AIMs to verify the origin of A. m. mellifera individuals and to provide accurate estimates of the level of C-lineage introgression into their genome. The discriminant power of the SNPs using a variety of metrics and approaches including the Weir & Cockerham’s F_ST, an F_ST-based outlier test, Delta, informativeness (I_n), and PCA was evaluated. This study shows that reduced AIMs panels assign individuals to the correct origin and calculates the admixture level with a high degree of accuracy. These panels provide an essential tool in Europe for genetic stock identification and estimation of admixture levels which can assist management strategies and monitor honey bee conservation programs.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.