A high-density SNP genetic linkage map for the silver-lipped pearl oyster,Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection

Background

The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters.

Results

A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes.

Conclusions

This high-density SNP genetic map is the first comprehensive linkage map for any pearl oyster species. It provides an essential genomic tool facilitating studies investigating the genomic architecture of complex trait variation and identifying quantitative trait loci for economically important traits useful in genetic selection programs within the P. maxima pearling industry. Furthermore, this map provides a foundation for further research aiming to improve our understanding of the dynamic process of biomineralization, and pearl oyster evolution and synteny.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-810) contains supplementary material, which is available to authorized users.     

High-throughput SNP discovery and genotyping in durum wheat (<Emphasis Type="Italic">Triticum durum</Emphasis> Desf.)

We describe the application of complexity reduction of polymorphic sequences (CRoPS^®) technology for the discovery of SNP markers in tetraploid durum wheat (Triticum durum Desf.). A next-generation sequencing experiment was carried out on reduced representation libraries obtained from four durum cultivars. SNP validation and minor allele frequency (MAF) estimate were carried out on a panel of 12 cultivars, and the feasibility of genotyping these SNPs in segregating populations was tested using the Illumina Golden Gate (GG) technology. A total of 2,659 SNPs were identified on 1,206 consensus sequences. Among the 768 SNPs that were chosen irrespective of their genomic repetitiveness level and assayed on the Illumina BeadExpress genotyping system, 275 (35.8%) SNPs matched the expected genotypes observed in the SNP discovery phase. MAF data indicated that the overall SNP informativeness was high: a total of 196 (71.3%) SNPs had MAF >0.2, of which 76 (27.6%) showed MAF >0.4. Of these SNPs, 157 were mapped in one of two mapping populations (Meridiano × Claudio and Colosseo × Lloyd) and integrated into a common genetic map. Despite the relatively low genotyping efficiency of the GG assay, the validated CRoPS-derived SNPs showed valuable features for genomics and breeding applications such as a uniform distribution across the wheat genome, a prevailing single-locus codominant nature and a high polymorphism. Here, we report a new set of 275 highly robust genome-wide Triticum SNPs that are readily available for breeding purposes.     

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821–0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825–0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.     

Design and Characterization of a 52K SNP Chip for Goats

The success of Genome Wide Association Studies in the discovery of sequence variation linked to complex traits in humans has increased interest in high throughput SNP genotyping assays in livestock species. Primary goals are QTL detection and genomic selection. The purpose here was design of a 50–60,000 SNP chip for goats. The success of a moderate density SNP assay depends on reliable bioinformatic SNP detection procedures, the technological success rate of the SNP design, even spacing of SNPs on the genome and selection of Minor Allele Frequencies (MAF) suitable to use in diverse breeds. Through the federation of three SNP discovery projects consolidated as the International Goat Genome Consortium, we have identified approximately twelve million high quality SNP variants in the goat genome stored in a database together with their biological and technical characteristics. These SNPs were identified within and between six breeds (meat, milk and mixed): Alpine, Boer, Creole, Katjang, Saanen and Savanna, comprising a total of 97 animals. Whole genome and Reduced Representation Library sequences were aligned on >10 kb scaffolds of the de novo goat genome assembly. The 60,000 selected SNPs, evenly spaced on the goat genome, were submitted for oligo manufacturing (Illumina, Inc) and published in dbSNP along with flanking sequences and map position on goat assemblies (i.e. scaffolds and pseudo-chromosomes), sheep genome V2 and cattle UMD3.1 assembly. Ten breeds were then used to validate the SNP content and 52,295 loci could be successfully genotyped and used to generate a final cluster file. The combined strategy of using mainly whole genome Next Generation Sequencing and mapping on a contig genome assembly, complemented with Illumina design tools proved to be efficient in producing this GoatSNP50 chip. Advances in use of molecular markers are expected to accelerate goat genomic studies in coming years.     

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.     

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.     

A catalogue of validated single nucleotide polymorphisms in bovine orthologs of mammalian imprinted genes and associations with beef production traits

Genetic (or ‘genomic’) imprinting, a feature of approximately 100 mammalian genes, results in monoallelic expression from one of the two parentally inherited chromosomes. To date, most studies have been directed on imprinted genes in murine or human models; however, there is burgeoning interest in the effects of imprinted genes in domestic livestock species. In particular, attention has focused on imprinted genes that influence foetal growth and development and that are associated with several economically important production traits in cattle, sheep and pigs. We have re-sequenced regions in 20 candidate bovine imprinted genes in order to validate single nucleotide polymorphisms (SNPs) that may influence important production traits in cattle. Putative SNPs detected via re-sequencing were subsequently re-formatted for high-throughput SNP genotyping in 185 cattle samples comprising 138 performance-tested European Bos taurus (all Limousin bulls), 29 African B. taurus and 18 Indian B. indicus samples. Analysis of the resulting genotypic data identified 117 validated SNPs. Preliminary genotype–phenotype association analyses using 83 SNPs that were polymorphic in the Limousin samples with minor allele frequencies ⩾0.05 revealed significant associations between two candidate bovine imprinted genes and a range of important beef production traits: average daily gain, average feed intake, live weight, feed conversion ratio, residual feed intake and residual gain. These genes were the Ras protein-specific guanine nucleotide releasing factor gene (RASGRF1) and the zinc finger, imprinted 2 gene (ZIM2). Despite the relatively small sample size used in these analyses, the observed associations with production traits are supported by the purported biological function of the RASGRF1 and ZIM2 gene products. These results support the hypothesis that imprinted genes contribute significantly to important complex production traits in cattle. Furthermore, these SNPs may be usefully incorporated into future marker-assisted and genomic selection breeding schemes.     

Identification and Analysis of Genome-Wide SNPs Provide Insight into Signatures of Selection and Domestication in Channel Catfish (Ictalurus punctatus)

Domestication and selection for important performance traits can impact the genome, which is most often reflected by reduced heterozygosity in and surrounding genes related to traits affected by selection. In this study, analysis of the genomic impact caused by domestication and artificial selection was conducted by investigating the signatures of selection using single nucleotide polymorphisms (SNPs) in channel catfish (Ictalurus punctatus). A total of 8.4 million candidate SNPs were identified by using next generation sequencing. On average, the channel catfish genome harbors one SNP per 116 bp. Approximately 6.6 million, 5.3 million, 4.9 million, 7.1 million and 6.7 million SNPs were detected in the Marion, Thompson, USDA103, Hatchery strain, and wild population, respectively. The allele frequencies of 407,861 SNPs differed significantly between the domestic and wild populations. With these SNPs, 23 genomic regions with putative selective sweeps were identified that included 11 genes. Although the function for the majority of the genes remain unknown in catfish, several genes with known function related to aquaculture performance traits were included in the regions with selective sweeps. These included hypoxia-inducible factor 1β· HIFιβ ¨ and the transporter gene ATP-binding cassette sub-family B member 5 (ABCB5). HIF1β· is important for response to hypoxia and tolerance to low oxygen levels is a critical aquaculture trait. The large numbers of SNPs identified from this study are valuable for the development of high-density SNP arrays for genetic and genomic studies of performance traits in catfish.     

Novel SNPs in the bovine ADIPOQ and PPARGC1A genes are associated with carcass traits in Hanwoo (Korean cattle)

Adiponectin (ADIPOQ) modulates several biological processes including energy homeostasis, glucose and lipid metabolism. The bovine ADIPOQ gene was located near the QTL affecting marbling, ribeye muscle area and fat thickness on BTA1. The gene encoding peroxisome proliferator-activated receptor-γ coactivator-1α (PPARGC1A) was located within the QTL region of the traits on BTA6. Moreover, its protein product has various biological functions such as cellular energy homeostasis, including adaptive thermogenesis, adipogenesis and gluconeogenesis. Therefore, the ADIPOQ and PPARGC1A genes are a positional and functional candidate gene for carcass traits in beef cattle. The objectives of this study were to identify polymorphisms in the bovine ADIPOQ and PPARGC1A genes, to evaluate their associations with carcass traits in Hanwoo (Korean cattle) population. We identified nine SNPs in the ADIPOQ gene. Two SNPs (DQ156119: g.1436T > C and DQ156119: g.1454A > G) in the promoter region were recognized as new SNPs identified in Hanwoo. Association analysis indicated that the g.1454A > G SNP genotype was significantly associated with effects on LMA (P = 0.004) and BF (P = 0.021). The ADIPOQ haplotype was also found to have significant effect on the LMA. In the PPARGC1A gene, we identified 11 SNPs in the two unexplored regions (intron 3 and 5). Among them, seven SNPs were located in intron 3 and four SNPs were located in intron 5. Of these 11 putative novel SNPs, two SNPs (AY839822: g.292C > T and AY839823: g.1064C > T) with minor allele frequency (MAF) > 0.20 were examined for associations with carcass traits. The association analysis revealed that both SNPs in PPARGC1A gene were significantly associated with LMA (P < 0.05). These findings suggest that the SNPs of bovine ADIPOQ and PPARGC1A genes may be a useful molecular marker for selection of carcass traits in Hanwoo.     

SNP Discovery and Chromosome Anchoring Provide the First Physically-Anchored Hexaploid Oat Map and Reveal Synteny with Model Species

A physically anchored consensus map is foundational to modern genomics research; however, construction of such a map in oat (Avena sativa L., 2n = 6x = 42) has been hindered by the size and complexity of the genome, the scarcity of robust molecular markers, and the lack of aneuploid stocks. Resources developed in this study include a modified SNP discovery method for complex genomes, a diverse set of oat SNP markers, and a novel chromosome-deficient SNP anchoring strategy. These resources were applied to build the first complete, physically-anchored consensus map of hexaploid oat. Approximately 11,000 high-confidence in silico SNPs were discovered based on nine million inter-varietal sequence reads of genomic and cDNA origin. GoldenGate genotyping of 3,072 SNP assays yielded 1,311 robust markers, of which 985 were mapped in 390 recombinant-inbred lines from six bi-parental mapping populations ranging in size from 49 to 97 progeny. The consensus map included 985 SNPs and 68 previously-published markers, resolving 21 linkage groups with a total map distance of 1,838.8 cM. Consensus linkage groups were assigned to 21 chromosomes using SNP deletion analysis of chromosome-deficient monosomic hybrid stocks. Alignments with sequenced genomes of rice and Brachypodium provide evidence for extensive conservation of genomic regions, and renewed encouragement for orthology-based genomic discovery in this important hexaploid species. These results also provide a framework for high-resolution genetic analysis in oat, and a model for marker development and map construction in other species with complex genomes and limited resources.     

Development and testing of a combined species SNP array for the European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata)

SNP arrays are powerful tools for high-resolution studies of the genetic basis of complex traits, facilitating both selective breeding and population genomic research. The European seabass (Dicentrarchus labrax) and the gilthead seabream (Sparus aurata) are the two most important fish species for Mediterranean aquaculture. While selective breeding programmes increasingly underpin stock supply for this industry, genomic selection is not yet widespread. Genomic selection has major potential to expedite genetic gain, particularly for traits practically impossible to measure on selection candidates, such as disease resistance and fillet characteristics. The aim of our study was to design a combined-species 60 K SNP array for European seabass and gilthead seabream, and to test its performance on farmed and wild populations from numerous locations throughout the species range. To achieve this, high coverage Illumina whole-genome sequencing of pooled samples was performed for 24 populations of European seabass and 27 populations of gilthead seabream. This resulted in a database of ~20 million SNPs per species, which were then filtered to identify high-quality variants and create the final set for the development of the ‘MedFish’ SNP array. The array was then tested by genotyping a subset of the discovery populations, highlighting a high conversion rate to functioning polymorphic assays on the array (92% in seabass; 89% in seabream) and repeatability (99.4–99.7%). The platform interrogates ~30 K markers in each species, includes features such as SNPs previously shown to be associated with performance traits, and is enriched for SNPs predicted to have high functional effects on proteins. The array was demonstrated to be effective at detecting population structure across a wide range of fish populations from diverse geographical origins, and to examine the extent of haplotype sharing among Mediterranean farmed fish populations. In conclusion, the new MedFish array enables efficient and accurate high-throughput genotyping for genome-wide distributed SNPs for each fish species, and will facilitate stock management, population genomics approaches, and acceleration of selective breeding through genomic selection.     

Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology

Background

The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay.

Methodology/Principal Findings

A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina''s Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274.

Conclusions/Significance

Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs.     

A whole‐genome SNP array (RICE6K) for genomic breeding in rice

The advances in genotyping technology provide an opportunity to use genomic tools in crop breeding. As compared to field selections performed in conventional breeding programmes, genomics‐based genotype screen can potentially reduce number of breeding cycles and more precisely integrate target genes for particular traits into an ideal genetic background. We developed a whole‐genome single nucleotide polymorphism (SNP) array, RICE6K, based on Infinium technology, using representative SNPs selected from more than four million SNPs identified from resequencing data of more than 500 rice landraces. RICE6K contains 5102 SNP and insertion–deletion (InDel) markers, about 4500 of which were of high quality in the tested rice lines producing highly repeatable results. Forty‐five functional markers that are located inside 28 characterized genes of important traits can be detected using RICE6K. The SNP markers are evenly distributed on the 12 chromosomes of rice with the average density of 12 SNPs per 1 Mb and can provide information for polymorphisms between indica and japonica subspecies as well as varieties within indica and japonica groups. Application tests of RICE6K showed that the array is suitable for rice germplasm fingerprinting, genotyping bulked segregating pools, seed authenticity check and genetic background selection. These results suggest that RICE6K provides an efficient and reliable genotyping tool for rice genomic breeding.     

Development of a high-throughput SNP array for sea cucumber (Apostichopus japonicus) and its application in genomic selection with MCP regularized deep neural networks

High-throughput single nucleotide polymorphism (SNP) genotyping assays are powerful tools for genetic studies and genomic breeding applications for many species. Though large numbers of SNPs have been identified in sea cucumber (Apostichopus japonicus), but, as yet, no high-throughput genotyping platform is available for this species. In this study, we designed and developed a high-throughput 24 K SNP genotyping array named HaishenSNP24K for A. japonicus, based on the multi-objective-local optimization (MOLO) algorithm and HD-Marker genotyping method. The SNP array exhibited a relatively high genotyping call rate (> 96%), genotyping accuracy (>95%) and exhibited highly polymorphic in sea cucumber populations. In addition, we also assessed its application in genomic selection (GS). Deep neural networks (DNN) that can capture the complicated interactions of genes have been proposed as a promising tool in GS for SNP-based genomic prediction of complex traits in animal breeding. To overcome the problem of over-fitting when using the HaishenSNP24K array as high-dimensional DNN input, we developed minmax concave penalty (MCP) regularization for sparse deep neural networks (DNN-MCP) that finds an optimal sparse structure of a DNN by minimizing the square error subject to the non-convex penalty MCP on the parameters (weights and biases). Compared to two linear models, namely RR-GBLUP and Bayes B, and the nonlinear model DNN, DNN-MCP has greatly improved the genomic prediction ability for three quantitative traits (e.g., wet weight, dry weight and survival time) in the sea cucumber population. To the best of our knowledge, this is the first work to develop a high-throughput SNP array for A. japonicus and a new model DNN-MCP for genomic prediction of complex traits in GS. The present results provide evidence that supports the HaishenSNP24K array with DNN-MCP will be valuable for genetic studies and molecular breeding in A. japonicus.     

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.     

The development of genome-wide single nucleotide polymorphisms in blue wildebeest using the DArTseq platform

Blue wildebeest (Connochaetes taurinus taurinus) are economically important antelope that are widely utilised in the South African wildlife industry. However, very few genomic resources are available for blue wildebeest that can assist in breeding management and facilitate research. This study aimed to develop a set of genome-wide single nucleotide polymorphism (SNP) markers for blue wildebeest. The DArTseq genotyping platform, commonly used in polyploid plant species, was selected for SNP discovery. A limited number of published articles have described the use of the DArTseq platform in animals and, therefore, this study also provided a unique opportunity to assess the performance of the DArTseq platform in an animal species. A total of 20,563 SNPs, each located within a 69 bp sequence, were generated. The developed SNP markers had a high average scoring reproducibility (>99%) and a low percentage missing data (~9.21%) compared to other reduced representation sequencing approaches that have been used in animal studies. Furthermore, the number of candidate SNPs per nucleotide position decreased towards the 3′ end of sequence reads, and the ratio of transitions (Ts) to transversions (Tv) remained similar for each read position. These observations indicate that there was no read position bias, such as the identification of false SNPs due to low sequencing quality, towards the tail-end of sequencing reads. The DArTseq platform was also successful in identifying a large number of informative SNPs with desirable polymorphism parameters such as a high minor allele frequency (MAF). The Bos taurus genome was used for the in silico mapping of the marker sequences and a total of 6020 (29.28%) sequences were successfully mapped against the bovine genome. The marker sequences mapped to all of the bovine chromosomes establishing the genome-wide distribution of the SNPs. Moreover, the high observed Ts:Tv ratio (2.84:1) indicate that the DArTseq platform targeted gene-rich regions of the blue wildebeest genome. Finally, functional annotation of the marker sequences revealed a wide range of different putative functions indicating that these SNP markers can be useful in functional gene studies. The DArTseq platform, therefore, represents a high-throughput, robust and cost-effective genotyping platform, which may find adoption in several other African antelope and animal species.     

Large Genomic Region Free of GWAS-Based Common Variants Contains Fertility-Related Genes

DNA variants, such as single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), are unevenly distributed across the human genome. Currently, dbSNP contains more than 6 million human SNPs, and whole-genome genotyping arrays can assay more than 4 million of them simultaneously. In our study, we first questioned whether published genome-wide association studies (GWASs) assays cover all regions well in the genome. Using dbSNP build 135 data, we identified 50 genomic regions longer than 100 Kb that do not contain any common SNPs, i.e., those with minor allele frequency (MAF)≥1%. Secondly, because conserved regions are generally of functional importance, we tested genes in those large genomic regions without common SNPs. We found 97 genes and were enriched for reproduction function. In addition, we further filtered out regions with CNVs listed in the Database of Genomic Variants (DGV), segmental duplications from Human Genome Project and common variants identified by personal genome sequencing (UCSC). No region survived after those filtering. Our analysis suggests that, while there may not be many large genomic regions free of common variants, there are still some “holes” in the current human genomic map for common SNPs. Because GWAS only focused on common SNPs, interpretation of GWAS results should take this limitation into account. Particularly, two recent GWAS of fertility may be incomplete due to the map deficit. Additional SNP discovery efforts should pay close attention to these regions.