Next-generation RAD sequencing identifies thousands of SNPs for assessing hybridization between rainbow and westslope cutthroat trout

The increased numbers of genetic markers produced by genomic techniques have the potential to both identify hybrid individuals and localize chromosomal regions responding to selection and contributing to introgression. We used restriction-site-associated DNA sequencing to identify a dense set of candidate SNP loci with fixed allelic differences between introduced rainbow trout (Oncorhynchus mykiss) and native westslope cutthroat trout (Oncorhynchus clarkii lewisi). We distinguished candidate SNPs from homeologs (paralogs resulting from whole-genome duplication) by detecting excessively high observed heterozygosity and deviations from Hardy-Weinberg proportions. We identified 2923 candidate species-specific SNPs from a single Illumina sequencing lane containing 24 barcode-labelled individuals. Published sequence data and ongoing genome sequencing of rainbow trout will allow physical mapping of SNP loci for genome-wide scans and will also provide flanking sequence for design of qPCR-based TaqMan(?) assays for high-throughput, low-cost hybrid identification using a subset of 50-100 loci. This study demonstrates that it is now feasible to identify thousands of informative SNPs in nonmodel species quickly and at reasonable cost, even if no prior genomic information is available.     

Rapid genotyping of soybean cultivars using high throughput sequencing

Soybean (Glycine max) breeding involves improving commercially grown varieties by introgressing important agronomic traits from poor yielding accessions and/or wild relatives of soybean while minimizing the associated yield drag. Molecular markers associated with these traits are instrumental in increasing the efficiency of producing such crosses and Single Nucleotide Polymorphisms (SNPs) are particularly well suited for this task, owing to high density in the non-genic regions and thus increased likelihood of finding a tightly linked marker to a given trait. A rapid method to develop SNP markers that can differentiate specific loci between any two parents in soybean is thus highly desirable. In this study we investigate such a protocol for developing SNP markers between multiple soybean accessions and the reference Williams 82 genome. To restrict sampling frequency reduced representation libraries (RRLs) of genomic DNA were generated by restriction digestion followed by library construction. We chose to sequence four accessions Dowling (PI 548663), Dwight (PI 597386), Komata (PI200492) and PI 594538A for their agronomic importance as well as Williams 82 as a control.MseI was chosen to digest genomic DNA based on predictions that it will cut sparingly in the mathematically defined high-copy-number regions of the genome. All RRLs were sequenced on the Illumina genome analyzer. Reads were aligned to the Glyma1 reference assembly and SNP calls made from the alignments. We identified from 4294 to 14550 SNPs between the four accessions and the Williams 82 reference. In addition a small number of SNPs (1142) were found by aligning Williams 82 reads to the reference assembly (Glyma1) suggesting limited genetic variation within the Williams 82 line. The SNP data allowed us to estimate genetic diversity between the four lines and Williams 82. Restriction digestion of soybean genomic DNA with MseI followed by high throughput sequencing provides a rapid and reproducible method for generating SNP markers.     

A fair fight between molecular marker types in a seascape genetics setting

From its inception, population genetics has been nearly as concerned with the genetic data type—to which analyses are brought to bear—as it is with the analysis methods themselves. The field has traversed allozymes, microsatellites, segregating sites in multilocus alignments and, currently, single nucleotide polymorphisms (SNPs) generated by high‐throughput genomic sequencing methods, primarily whole genome sequencing and reduced representation library (RRL) sequencing. As each emerging data type has gained traction, it has been compared to existing methods, based on its relative ability to discern population structural complexity at increasing levels of resolution. However, this is usually done by comparing the gold standard in one data type to the gold standard in the new data type. These gold standards frequently differ in power and in sampling density, both across a genome and throughout a spatial range. In this issue of Molecular Ecology, D’Aloia et al. apply the high‐throughput approach as fully as possible to microsatellites, nuclear loci and SNPs genotyped through an RRL method; this is coupled with a spatially dense sampling scheme. Completing a battery of population genetics analyses across data types (including a series of down‐sampled data sets), the authors find that SNP data are slightly more sensitive to fine‐scale genetic structure, and the results are more resilient to down‐sampling than microsatellites and nonrepetitive nuclear loci. However, their results are far from an unqualified victory for RRL SNP data over all previous data types: the authors note that modest additions to the microsatellites and nuclear loci data sets may provide the necessary analytical power to delineate the fine‐scale genetic structuring identified by SNPs. As always, as the field begins to fully embrace the newest thing, good science reminds us that traditional data types are far from useless, especially when combined with a well‐designed sampling scheme.     

Identification of novel single nucleotide polymorphisms (SNPs) in deer (Odocoileus spp.) using the BovineSNP50 BeadChip

Single nucleotide polymorphisms (SNPs) are growing in popularity as a genetic marker for investigating evolutionary processes. A panel of SNPs is often developed by comparing large quantities of DNA sequence data across multiple individuals to identify polymorphic sites. For non-model species, this is particularly difficult, as performing the necessary large-scale genomic sequencing often exceeds the resources available for the project. In this study, we trial the Bovine SNP50 BeadChip developed in cattle (Bos taurus) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and O. virginianus (white-tailed deer) in the Pacific Northwest. We found that 38.7% of loci could be genotyped, of which 5% (n = 1068) were polymorphic. Of these 1068 polymorphic SNPs, a mixture of putatively neutral loci (n = 878) and loci under selection (n = 190) were identified with the F(ST)-outlier method. A range of population genetic analyses were implemented using these SNPs and a panel of 10 microsatellite loci. The three types of deer could readily be distinguished with both the SNP and microsatellite datasets. This study demonstrates that commercially developed SNP chips are a viable means of SNP discovery for non-model organisms, even when used between very distantly related species (the Bovidae and Cervidae families diverged some 25.1-30.1 million years before present).     

Multiple target loci assembly sequencing (mTAS)

Here we present multiple target loci assembly sequencing (mTAS), a method for examining multiple genomic loci in a single DNA sequencing read. The key to the success of mTAS target sequencing is the uniform amplification of multiple target genomic loci into a single DNA fragment using polymerase cycling assembly (PCA). Using this strategy, we successfully collected multiloci sequence information from a single DNA sequencing run. We applied mTAS to examine 29 different sets of human genomic loci, each containing from 2 to 11 single-nucleotide polymorphisms (SNP) present at different exons. We believe mTAS can be used to reduce the cost of Sanger sequencing-based genetic analysis.     

Haplotype-based approach for noninvasive prenatal diagnosis of congenital adrenal hyperplasia by maternal plasma DNA sequencing

Prenatal diagnosis of congenital adrenal hyperplasia (CAH) is of clinical significance because in utero treatment is available to prevent virilization of an affected female fetus. However, traditional prenatal diagnosis of CAH relies on genetic testing of fetal genomic DNA obtained using amniocentesis or chorionic villus sampling, which is associated with an increased risk of miscarriage. The aim of this study was to demonstrate the feasibility of a new haplotype-based approach for the noninvasive prenatal testing of CAH due to 21-hydroxylase deficiency. Parental haplotypes were constructed using target-region sequencing data of the parents and the proband. With the assistance of the parental haplotypes, we recovered fetal haplotypes using a hidden Markov model (HMM) through maternal plasma DNA sequencing. In the genomic region around the CYP21A2 gene, the fetus inherited the paternal haplotype ‘0’ alleles linked to the mutant CYP21A2 gene, but the maternal haplotype ‘1’ alleles linked to the wild-type gene. The fetus was predicted to be an unaffected carrier of CAH, which was confirmed by genetic analysis of fetal genomic DNA from amniotic fluid cells. This method was further validated by comparing the inferred SNP genotypes with the direct sequencing data of fetal genomic DNA. The result showed an accuracy of 96.41% for the inferred maternal alleles and an accuracy of 97.81% for the inferred paternal alleles. The haplotype-based approach is feasible for noninvasive prenatal testing of CAH.     

Sequencing improves our ability to study threatened migratory species: Genetic population assignment in California's Central Valley Chinook salmon

Effective conservation and management of migratory species requires accurate identification of unique populations, even as they mix along their migratory corridors. While telemetry has historically been used to study migratory animal movement and habitat use patterns, genomic tools are emerging as a superior alternative in many ways, allowing large‐scale application at reduced costs. Here, we demonstrate the usefulness of genomic resources for identifying single‐nucleotide polymorphisms (SNPs) that allow fast and accurate identification of the imperiled Chinook salmon in the Great Central Valley of California. We show that 80 well‐chosen loci, drawn from a pool of over 11,500 SNPs developed from restriction site‐associated DNA sequencing, can accurately identify Chinook salmon runs and select populations within run. No other SNP panel for Central Valley Chinook salmon has been able to achieve the high accuracy of assignment we show here. This panel will greatly improve our ability to study and manage this ecologically, economically, and socially important species and demonstrates the great utility of using genomics to study migratory species.     

A resource of genome‐wide single‐nucleotide polymorphisms generated by RAD tag sequencing in the critically endangered European eel

Reduced representation genome sequencing such as restriction‐site‐associated DNA (RAD) sequencing is finding increased use to identify and genotype large numbers of single‐nucleotide polymorphisms (SNPs) in model and nonmodel species. We generated a unique resource of novel SNP markers for the European eel using the RAD sequencing approach that was simultaneously identified and scored in a genome‐wide scan of 30 individuals. Whereas genomic resources are increasingly becoming available for this species, including the recent release of a draft genome, no genome‐wide set of SNP markers was available until now. The generated SNPs were widely distributed across the eel genome, aligning to 4779 different contigs and 19 703 different scaffolds. Significant variation was identified, with an average nucleotide diversity of 0.00529 across individuals. Results varied widely across the genome, ranging from 0.00048 to 0.00737 per locus. Based on the average nucleotide diversity across all loci, long‐term effective population size was estimated to range between 132 000 and 1 320 000, which is much higher than previous estimates based on microsatellite loci. The generated SNP resource consisting of 82 425 loci and 376 918 associated SNPs provides a valuable tool for future population genetics and genomics studies and allows for targeting specific genes and particularly interesting regions of the eel genome.     

Development of gene-targeted SNP markers for genomic mapping in Pacific abalone Haliotis discus hannai Ino

Useful and novel DNA markers are needed for aquaculture genetics and breeding. In this study, we report the discovery and development of gene-targeted single nucleotide polymorphisms (SNPs) for genomic mapping in the Pacific abalone Haliotis discus hannai Ino. Single EST or EST-contigs from 66 genes that had positive BLASTx matches (E-value ≤ 1e-8) were used for polymerase chain reaction (PCR) amplification. PCR products from the two parents of one mapping family were directly sequenced, and 83 SNP loci were found from 17 genes. Allele-specific PCR (AS-PCR) was developed and optimized for genotyping of 11 SNP loci in 120 progeny of the mapping family. Nine of the loci conformed to the expected Mendelian ratio of 1:1 based on the χ² test (P > 0.05) and could potentially be used for linkage map construction. Our data also indicate that the sequencing of two parents may be a practical strategy for the discovery of informative SNPs for linkage mapping in a particular mapping population.     

Transcriptome-based single nucleotide polymorphism markers for genome mapping in Japanese pear (Pyrus pyrifolia Nakai)

The development of single nucleotide polymorphism (SNP) markers in Japanese pear (Pyrus pyrifolia Nakai) offers the opportunity to use DNA markers for marker-assisted selection in breeding programs because of their high abundance, codominant inheritance, and potential for automated high-throughput analysis. We developed a 1,536-SNP bead array without a reference genome sequence from more than 44,000 base changes on the basis of a large-scale expressed sequence tag (EST) analysis combined with 454 genome sequencing data of Japanese pear ‘Housui’. Among the 1,536 SNPs on the array, 756 SNPs were genotyped, and 609 SNP loci were mapped to linkage groups on a genetic linkage map of ‘Housui’, based on progeny of an interspecific cross between European pear (Pyrus communis L.) ‘Bartlett’ and ‘Housui’. The newly constructed genetic linkage map consists of 951 loci, comprising 609 new SNPs, 110 pear genomic simple sequence repeats (SSRs), 25 pear EST–SSRs, 127 apple SSRs, 61 pear SNPs identified by the “potential intron polymorphism” method, and 19 other loci. The map covers 22 linkage groups spanning 1341.9 cM with an average distance of 1.41 cM between markers and is anchored to reference genetic linkage maps of European pears and apples. A total of 514 contigs containing mapped SNP loci showed significant similarity to known proteins by functional annotation analysis.     

SNP discovery in nonmodel organisms: strand bias and base‐substitution errors reduce conversion rates

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep‐sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize ‘bycatch’—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand‐bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single‐copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.     

Conservation genomics of anadromous Atlantic salmon across its North American range: outlier loci identify the same patterns of population structure as neutral loci

Anadromous Atlantic salmon (Salmo salar) is a species of major conservation and management concern in North America, where population abundance has been declining over the past 30 years. Effective conservation actions require the delineation of conservation units to appropriately reflect the spatial scale of intraspecific variation and local adaptation. Towards this goal, we used the most comprehensive genetic and genomic database for Atlantic salmon to date, covering the entire North American range of the species. The database included microsatellite data from 9142 individuals from 149 sampling locations and data from a medium‐density SNP array providing genotypes for >3000 SNPs for 50 sampling locations. We used neutral and putatively selected loci to integrate adaptive information in the definition of conservation units. Bayesian clustering with the microsatellite data set and with neutral SNPs identified regional groupings largely consistent with previously published regional assessments. The use of outlier SNPs did not result in major differences in the regional groupings, suggesting that neutral markers can reflect the geographic scale of local adaptation despite not being under selection. We also performed assignment tests to compare power obtained from microsatellites, neutral SNPs and outlier SNPs. Using SNP data substantially improved power compared to microsatellites, and an assignment success of 97% to the population of origin and of 100% to the region of origin was achieved when all SNP loci were used. Using outlier SNPs only resulted in minor improvements to assignment success to the population of origin but improved regional assignment. We discuss the implications of these new genetic resources for the conservation and management of Atlantic salmon in North America.     

Causes and analytical impacts of missing data in RADseq phylogenetics: Insights from an African frog (Afrixalus)

Restriction site‐associated DNA sequencing (RADseq) has emerged as a useful tool in systematics and population genomics. A common feature of RADseq data sets is that they contain missing data that arise from multiple sources including genealogical sampling bias, assembly methodology and sequencing error. Many RADseq studies have demonstrated that allowing sites (single nucleotide polymorphisms, SNPs) with missing data can increase support for phylogenetic hypotheses. Two non‐mutually exclusive explanations for this observation are that (a) larger data sets contain more phylogenetic information; and (b) excluding missing data disproportionally removes sites with the highest mutation rates, causing the exclusion of characters that are likely variable and informative. Using a RADseq data set derived from the East African banana frog, Afrixalus fornasini (up to 1.1 million SNPs), we found that missing data thresholds were positively correlated with the proportion of parsimony‐informative sites and mean branch support. Using three proxies for estimating site‐specific rate, we found that the most conservative missing data strategies excluded rapidly evolving sites, with four‐state sites present only when allowing ≥60% missing data per SNP. Topological similarity among estimated phylogenies was highest for the data sets with ≥60% missing data per SNP. Our results suggest that several desirable phylogenetic qualities were observed when allowing ≥60% missing data per SNP. However, at the highest missing data thresholds (80% and 90% missing data per SNP), we observed differences in performance between high‐ and mixed‐weight DNA extraction samples, which may indicate there are trade‐offs to consider when using degraded genomic template with RADseq protocols.     

SNP development from RNA‐seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA‐seq is one such technique for the discovery of SNPs and development of markers for large‐scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black‐faced blenny), a small rocky‐shore fish from the Mediterranean Sea. RNA‐seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time‐consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.     

Detection and characterization of SNPs useful for identity control and parentage testing in major European dairy breeds

We propose the use of single nucleotide polymorphisms (SNPs) instead of polymorphic microsatellite markers for individual identification and parentage control in cattle. To this end, we present an initial set of 37 SNP markers together with a gender-specific SNP for identity control and parentage testing in the Holstein, Fleckvieh and Braunvieh breeds. To obtain suitable SNPs, a total of 91.13 kb of random genomic DNA was screened yielding 531 SNPs. These, and 43 previously identified SNPs, were subjected to the following selection criteria: (1) the frequency of the minor allele must be larger than 0.1 in at least two of the three examined breeds, and (2) markers should not be linked closely. Allele frequencies were estimated by analysing sequencing traces of pooled DNA or by genotyping individual DNA samples. The selected SNP loci were physically mapped by radiation hybrid mapping or by fluorescence in situ hybridization, and tested against the neutral mutation hypothesis. The presented marker set theoretically allows probabilities of identity less than 10(-13) for individual verification and exclusion powers exceeding 99.99% for parentage testing.     

Two Different High Throughput Sequencing Approaches Identify Thousands of De Novo Genomic Markers for the Genetically Depleted Bornean Elephant

High throughput sequencing technologies are being applied to an increasing number of model species with a high-quality reference genome. The application and analyses of whole-genome sequence data in non-model species with no prior genomic information are currently under way. Recent sequencing technologies provide new opportunities for gathering genomic data in natural populations, laying the empirical foundation for future research in the field of conservation and population genomics. Here we present the case study of the Bornean elephant, which is the most endangered subspecies of Asian elephant and exhibits very low genetic diversity. We used two different sequencing platforms, the Roche 454 FLX (shotgun) and Illumina, GAIIx (Restriction site associated DNA, RAD) to evaluate the feasibility of the two methodologies for the discovery of de novo markers (single nucleotide polymorphism, SNPs and microsatellites) using low coverage data. Approximately, 6,683 (shotgun) and 14,724 (RAD) SNPs were detected within our elephant sequence dataset. Genotyping of a representative sample of 194 SNPs resulted in a SNP validation rate of ∼ 83 to 94% and 17% of the loci were polymorphic with a low diversity (H _o = 0.057). Different numbers of microsatellites were identified through shotgun (27,226) and RAD (868) techniques. Out of all di-, tri-, and tetra-microsatellite loci, 1,706 loci had sufficient flanking regions (shotgun) while only 7 were found with RAD. All microsatellites were monomorphic in the Bornean but polymorphic in another elephant subspecies. Despite using different sample sizes, and the well known differences in the two platforms used regarding sequence length and throughput, the two approaches showed high validation rate. The approaches used here for marker development in a threatened species demonstrate the utility of high throughput sequencing technologies as a starting point for the development of genomic tools in a non-model species and in particular for a species with low genetic diversity.     

SNPs by AFLP (SBA): a rapid SNP isolation strategy for non-model organisms

Despite the great potential of single nucleotide polymorphism (SNP) markers in evolutionary studies, in particular for inferring population genetic parameters, SNP analysis has almost exclusively been limited to humans and ‘genomic model’ organisms, due to the lack of available sequence data in non-model organisms. Here, we describe a rapid and cost effective method to isolate candidate SNPs in non-model organisms. This SNP isolation strategy consists basically in the direct sequencing of amplified fragment length polymorphism bands. In a first application of this method, 10 unique DNA fragments that contained 24 SNPs were discovered in 11.11 kb of sequenced genomic DNA of a non-model species, the brown trout (Salmo trutta).     

Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium

As large-scale sequencing efforts turn from single genome sequencing to polymorphism discovery, single nucleotide polymorphisms (SNPs) are becoming an increasingly important class of population genetic data. But because of the ascertainment biases introduced by many methods of SNP discovery, most SNP data cannot be analyzed using classical population genetic methods. Statistical methods must instead be developed that can explicitly take into account each method of SNP discovery. Here we review some of the current methods for analyzing SNPs and derive sampling distributions for single SNPs and pairs of SNPs for some common SNP discovery schemes. We also show that the ascertainment scheme has a large effect on the estimation of linkage disequilibrium and recombination, and describe some methods of correcting for ascertainment biases when estimating recombination rates from SNP data.