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.     

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.     

Application of high-resolution DNA melting for genotyping in lepidopteran non-model species: Ostrinia furnacalis (Crambidae)

Development of an ideal marker system facilitates a better understanding of the genetic diversity in lepidopteran non-model organisms, which have abundant species, but relatively limited genomic resources. Single nucleotide polymorphisms (SNPs) discovered within single-copy genes have proved to be desired markers, but SNP genotyping by current techniques remain laborious and expensive. High resolution melting (HRM) curve analysis represents a simple, rapid and inexpensive genotyping method that is primarily confined to clinical and diagnostic studies. In this study, we evaluated the potential of HRM analysis for SNP genotyping in the lepidopteran non-model species Ostrinia furnacalis (Crambidae). Small amplicon and unlabeled probe assays were developed for the SNPs, which were identified in 30 females of O. furnacalis from 3 different populations by our direct sequencing. Both assays were then applied to genotype 90 unknown female DNA by prior mixing with known wild-type DNA. The genotyping results were compared with those that were obtained using bi-directional sequencing analysis. Our results demonstrated the efficiency and reliability of the HRM assays. HRM has the potential to provide simple, cost-effective genotyping assays and facilitates genotyping studies in any non-model lepidopteran species of interest.     

Reference-free detection of isolated SNPs

Detecting single nucleotide polymorphisms (SNPs) between genomes is becoming a routine task with next-generation sequencing. Generally, SNP detection methods use a reference genome. As non-model organisms are increasingly investigated, the need for reference-free methods has been amplified. Most of the existing reference-free methods have fundamental limitations: they can only call SNPs between exactly two datasets, and/or they require a prohibitive amount of computational resources. The method we propose, discoSnp, detects both heterozygous and homozygous isolated SNPs from any number of read datasets, without a reference genome, and with very low memory and time footprints (billions of reads can be analyzed with a standard desktop computer). To facilitate downstream genotyping analyses, discoSnp ranks predictions and outputs quality and coverage per allele. Compared to finding isolated SNPs using a state-of-the-art assembly and mapping approach, discoSnp requires significantly less computational resources, shows similar precision/recall values, and highly ranked predictions are less likely to be false positives. An experimental validation was conducted on an arthropod species (the tick Ixodes ricinus) on which de novo sequencing was performed. Among the predicted SNPs that were tested, 96% were successfully genotyped and truly exhibited polymorphism.     

Genomic DNA Enrichment Using Sequence Capture Microarrays: a Novel Approach to Discover Sequence Nucleotide Polymorphisms (SNP) in Brassica napus L

Targeted genomic selection methodologies, or sequence capture, allow for DNA enrichment and large-scale resequencing and characterization of natural genetic variation in species with complex genomes, such as rapeseed canola (Brassica napus L., AACC, 2n=38). The main goal of this project was to combine sequence capture with next generation sequencing (NGS) to discover single nucleotide polymorphisms (SNPs) in specific areas of the B. napus genome historically associated (via quantitative trait loci –QTL– analysis) to traits of agronomical and nutritional importance. A 2.1 million feature sequence capture platform was designed to interrogate DNA sequence variation across 47 specific genomic regions, representing 51.2 Mb of the Brassica A and C genomes, in ten diverse rapeseed genotypes. All ten genotypes were sequenced using the 454 Life Sciences chemistry and to assess the effect of increased sequence depth, two genotypes were also sequenced using Illumina HiSeq chemistry. As a result, 589,367 potentially useful SNPs were identified. Analysis of sequence coverage indicated a four-fold increased representation of target regions, with 57% of the filtered SNPs falling within these regions. Sixty percent of discovered SNPs corresponded to transitions while 40% were transversions. Interestingly, fifty eight percent of the SNPs were found in genic regions while 42% were found in intergenic regions. Further, a high percentage of genic SNPs was found in exons (65% and 64% for the A and C genomes, respectively). Two different genotyping assays were used to validate the discovered SNPs. Validation rates ranged from 61.5% to 84% of tested SNPs, underpinning the effectiveness of this SNP discovery approach. Most importantly, the discovered SNPs were associated with agronomically important regions of the B. napus genome generating a novel data resource for research and breeding this crop species.     

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.     

SNP discovery using Paired‐End RAD‐tag sequencing on pooled genomic DNA of Sisymbrium austriacum (Brassicaceae)

Single nucleotide polymorphisms SNPs are rapidly replacing anonymous markers in population genomic studies, but their use in non model organisms is hampered by the scarcity of cost‐effective approaches to uncover genome‐wide variation in a comprehensive subset of individuals. The screening of one or only a few individuals induces ascertainment bias. To discover SNPs for a population genomic study of the Pyrenean rocket (Sisymbrium austriacum subsp. chrysanthum), we undertook a pooled RAD‐PE (Restriction site Associated DNA Paired‐End sequencing) approach. RAD tags were generated from the PstI‐digested pooled genomic DNA of 12 individuals sampled across the species distribution range and paired‐end sequenced using Illumina technology to produce ~24.5 Mb of sequences, covering ~7% of the specie's genome. Sequences were assembled into ~76 000 contigs with a mean length of 323 bp (N₅₀ = 357 bp, sequencing depth = 24x). In all, >15 000 SNPs were called, of which 47% were annotated in putative genic regions based on homology with the Arabidopsis thaliana genome. Gene ontology (GO) slim categorization demonstrated that the identified SNPs covered extant genic variation well. The validation of 300 SNPs on a larger set of individuals using a KASPar assay underpinned the utility of pooled RAD‐PE as an inexpensive genome‐wide SNP discovery technique (success rate: 87%). In addition to SNPs, we discovered >600 putative SSR markers.     

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).     

Genome-wide identification of SNPs and copy number variation in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.) using genotyping-by-sequencing (GBS)

Next-generation sequencing technologies have increased markedly the throughput of genetic studies, allowing the identification of several thousands of SNPs within a single experiment. Even though sequencing cost is rapidly decreasing, the price for whole-genome re-sequencing of a large number of individuals is still costly, especially in plants with a large and highly redundant genome. In recent years, several reduced representation library approaches have been developed for reducing the sequencing cost per individual. Among them, genotyping-by-sequencing (GBS) represents a simple, cost-effective, and highly multiplexed alternative for species with or without an available reference genome. However, this technology requires specific optimization for each species, especially for the restriction enzyme (RE) used. Here we report on the application of GBS in a test experiment with 18 genotypes of wild and domesticated Phaseolus vulgaris. After an in silico digestion with different RE of the P. vulgaris genome reference sequence, we selected CviAII as the most suitable RE for GBS in common bean based on the high frequency and even distribution of restriction sites. A total of 44,875 SNPs, 1940 deletions, and 1693 insertions were identified, with 50 % of the variants located in genic sequences and tagging 11,027 genes. SNP and InDel distributions were positively correlated with gene density across the genome. In addition, we were able to also identify putative copy number variations of genomic segments between different genotypes. In conclusion, GBS with the CviAII enzyme results in thousands of evenly spaced markers and provides a reliable, high-throughput, and cost-effective approach for genotyping both wild and domesticated common beans.     

Single‐nucleotide polymorphism discovery in Leptographium longiclavatum,a mountain pine beetle‐associated symbiotic fungus,using whole‐genome resequencing

Single‐nucleotide polymorphisms (SNPs) are rapidly becoming the standard markers in population genomics studies; however, their use in nonmodel organisms is limited due to the lack of cost‐effective approaches to uncover genome‐wide variation, and the large number of individuals needed in the screening process to reduce ascertainment bias. To discover SNPs for population genomics studies in the fungal symbionts of the mountain pine beetle (MPB), we developed a road map to discover SNPs and to produce a genotyping platform. We undertook a whole‐genome sequencing approach of Leptographium longiclavatum in combination with available genomics resources of another MPB symbiont, Grosmannia clavigera. We sequenced 71 individuals pooled into four groups using the Illumina sequencing technology. We generated between 27 and 30 million reads of 75 bp that resulted in a total of 1, 181 contigs longer than 2 kb and an assembled genome size of 28.9 Mb (N₅₀ = 48 kb, average depth = 125x). A total of 9052 proteins were annotated, and between 9531 and 17 266 SNPs were identified in the four pools. A subset of 206 genes (containing 574 SNPs, 11% false positives) was used to develop a genotyping platform for this species. Using this roadmap, we developed a genotyping assay with a total of 147 SNPs located in 121 genes using the Illumina^® Sequenom iPLEX Gold. Our preliminary genotyping (success rate = 85%) of 304 individuals from 36 populations supports the utility of this approach for population genomics studies in other MPB fungal symbionts and other fungal nonmodel species.     

Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform

Next-generation sequencing (NGS) technologies are revolutionizing both medical and biological research through generation of massive SNP data sets for identifying heritable genome variation underlying key traits, from rare human diseases to important agronomic phenotypes in crop species. We evaluated the performance of genotyping-by-sequencing (GBS), one of the emerging NGS-based platforms, for genotyping two economically important conifer species, lodgepole pine (Pinus contorta) and white spruce (Picea glauca). Both species have very large genomes (>20,000 Mbp), are highly heterozygous, and lack reference sequences. From a small set (six accessions each) of independent replicated DNA samples and a 48-plex read depth, we obtained ~60,000 SNPs per species. After stringent filtering, we obtained 17,765 and 17,845 high-coverage SNPs without missing data for lodgepole pine and white spruce, respectively. Our results demonstrated that GBS is a robust and suitable method for genotyping conifers. The application of GBS to forest tree breeding and genomic selection is discussed.