A simple route to single-nucleotide polymorphisms in a nonmodel species: identification and characterization of SNPs in the Artic ringed seal (Pusa hispida hispida)

Although single-nucleotide polymorphisms (SNPs) have become the marker of choice in the field of human genetics, these markers are only slowly emerging in ecological, evolutionary and conservation genetic analyses of nonmodel species. This is partly because of difficulties associated with the discovery and characterization of SNP markers. Herein, we adopted a simple straightforward approach to identifying SNPs, based on screening of a random genomic library. In total, we identified 768 SNPs in the ringed seal, Pusa hispida hispida, in samples from Greenland and Svalbard. Using three seal samples, SNPs were discovered at a rate of one SNP per 402 bp, whereas re-sequencing of 96 seals increased the density to one SNP per 29 bp. Although applicable to any species of interest, the approach is especially well suited for SNP discovery in nonmodel organisms and is easily implemented in any standard genetics laboratory, circumventing the need for prior genomic data and use of next-generation sequencing facilities.     

Discovery of single-nucleotide polymorphisms (SNPs) in the uncharacterized genome of the ascomycete Ophiognomonia clavigignenti-juglandacearum from 454 sequence data

The benefits from recent improvement in sequencing technologies, such as the Roche GS FLX (454) pyrosequencing, may be even more valuable in non-model organisms, such as many plant pathogenic fungi of economic importance. One application of this new sequencing technology is the rapid generation of genomic information to identify putative single-nucleotide polymorphisms (SNPs) to be used for population genetic, evolutionary, and phylogeographic studies on non-model organisms. The focus of this research was to sequence, assemble, discover and validate SNPs in a fungal genome using 454 pyrosequencing when no reference sequence is available. Genomic DNA from eight isolates of Ophiognomonia clavigignenti-juglandacearum was pooled in one region of a four-region sequencing run on a Roche 454 GS FLX. This yielded 71 million total bases comprising 217,000 reads, 80% of which collapsed into 16,125,754 bases in 30,339 contigs upon assembly. By aligning reads from multiple isolates, we detected 298 SNPs using Roche's GS Mapper. With no reference sequence available, however, it was difficult to distinguish true polymorphisms from sequencing error. Eagleview software was used to manually examine each contig that contained one or more putative SNPs, enabling us to discard all but 45 of the original 298 putative SNPs. Of those 45 SNPs, 13 were validated using standard Sanger sequencing. This research provides a valuable genetic resource for research into the genus Ophiognomonia, demonstrates a framework for the rapid and cost-effective discovery of SNP markers in non-model organisms and should prove especially useful in the case of asexual or clonal fungi with limited genetic variability.     

SNP Discovery Using Next Generation Transcriptomic Sequencing in Atlantic Herring (Clupea harengus)

The introduction of Next Generation Sequencing (NGS) has revolutionised population genetics, providing studies of non-model species with unprecedented genomic coverage, allowing evolutionary biologists to address questions previously far beyond the reach of available resources. Furthermore, the simple mutation model of Single Nucleotide Polymorphisms (SNPs) permits cost-effective high-throughput genotyping in thousands of individuals simultaneously. Genomic resources are scarce for the Atlantic herring (Clupea harengus), a small pelagic species that sustains high revenue fisheries. This paper details the development of 578 SNPs using a combined NGS and high-throughput genotyping approach. Eight individuals covering the species distribution in the eastern Atlantic were bar-coded and multiplexed into a single cDNA library and sequenced using the 454 GS FLX platform. SNP discovery was performed by de novo sequence clustering and contig assembly, followed by the mapping of reads against consensus contig sequences. Selection of candidate SNPs for genotyping was conducted using an in silico approach. SNP validation and genotyping were performed simultaneously using an Illumina 1,536 GoldenGate assay. Although the conversion rate of candidate SNPs in the genotyping assay cannot be predicted in advance, this approach has the potential to maximise cost and time efficiencies by avoiding expensive and time-consuming laboratory stages of SNP validation. Additionally, the in silico approach leads to lower ascertainment bias in the resulting SNP panel as marker selection is based only on the ability to design primers and the predicted presence of intron-exon boundaries. Consequently SNPs with a wider spectrum of minor allele frequencies (MAFs) will be genotyped in the final panel. The genomic resources presented here represent a valuable multi-purpose resource for developing informative marker panels for population discrimination, microarray development and for population genomic studies in the wild.     

Mass production of SNP markers in a nonmodel passerine bird through RAD sequencing and contig mapping to the zebra finch genome

Here, we present an adaptation of restriction‐site‐associated DNA sequencing (RAD‐seq) to the Illumina HiSeq2000 technology that we used to produce SNP markers in very large quantities at low cost per unit in the Réunion grey white‐eye (Zosterops borbonicus), a nonmodel passerine bird species with no reference genome. We sequenced a set of six pools of 18–25 individuals using a single sequencing lane. This allowed us to build around 600 000 contigs, among which at least 386 000 could be mapped to the zebra finch (Taeniopygia guttata) genome. This yielded more than 80 000 SNPs that could be mapped unambiguously and are evenly distributed across the genome. Thus, our approach provides a good illustration of the high potential of paired‐end RAD sequencing of pooled DNA samples combined with comparative assembly to the zebra finch genome to build large contigs and characterize vast numbers of informative SNPs in nonmodel passerine bird species in a very efficient and cost‐effective way.     

Reference-free SNP calling: improved accuracy by preventing incorrect calls from repetitive genomic regions

ABSTRACT: BACKGROUND: Single nucleotide polymorphisms (SNPs) are the most abundant type of genetic variation in eukaryotic genomes and have recently become the marker of choice in a wide variety of ecological and evolutionary studies. The advent of next-generation sequencing (NGS) technologies has made it possible to efficiently genotype a large number of SNPs in the non-model organisms with no or limited genomic resources. Most NGS-based genotyping methods require a reference genome to perform accurate SNP calling. Little effort, however, has yet been devoted to developing or improving algorithms for accurate SNP calling in the absence of a reference genome. RESULTS: Here we describe an improved maximum likelihood (ML) algorithm called iML, which can achieve high genotyping accuracy for SNP calling in the non-model organisms without a reference genome. The iML algorithm incorporates the mixed Poisson/normal model to detect composite read clusters and can efficiently prevent incorrect SNP calls resulting from repetitive genomic regions. Through analysis of simulation and real sequencing datasets, we demonstrate that in comparison with ML or a threshold approach, iML can remarkably improve the accuracy of de novo SNP genotyping and is especially powerful for the reference-free genotyping in diploid genomes with high repeat contents. CONCLUSIONS: The iML algorithm can efficiently prevent incorrect SNP calls resulting from repetitive genomic regions, and thus outperforms the original ML algorithm by achieving much higher genotyping accuracy. Our algorithm is therefore very useful for accurate de novo SNP genotyping in the non-model organisms without a reference genome.     

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.     

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.     

Optimization of the genotyping‐by‐sequencing strategy for population genomic analysis in conifers

Flexibility and low cost make genotyping‐by‐sequencing (GBS) an ideal tool for population genomic studies of nonmodel species. However, to utilize the potential of the method fully, many parameters affecting library quality and single nucleotide polymorphism (SNP) discovery require optimization, especially for conifer genomes with a high repetitive DNA content. In this study, we explored strategies for effective GBS analysis in pine species. We constructed GBS libraries using HpaII, PstI and EcoRI‐MseI digestions with different multiplexing levels and examined the effect of restriction enzymes on library complexity and the impact of sequencing depth and size selection of restriction fragments on sequence coverage bias. We tested and compared UNEAK, Stacks and GATK pipelines for the GBS data, and then developed a reference‐free SNP calling strategy for haploid pine genomes. Our GBS procedure proved to be effective in SNP discovery, producing 7000–11 000 and 14 751 SNPs within and among three pine species, respectively, from a PstI library. This investigation provides guidance for the design and analysis of GBS experiments, particularly for organisms for which genomic information is lacking.