High-throughput genotyping in citrus accessions using an SNP genotyping array

We developed a 384 multiplexed SNP array, named CitSGA-1, for the genotyping of Citrus cultivars, and evaluated the performance and reliability of the genotyping. SNPs were surveyed by direct sequence comparison of the sequence tagged site (STS) fragment amplified from genomic DNA of cultivars representing the genetic diversity of citrus breeding in Japan. Among 1497 SNPs candidates, 384 SNPs for a high-throughput genotyping array were selected based on physical parameters of Illumina’s bead array criteria. The assay using CitSGA-1 was applied to a hybrid population of 88 progeny and 103 citrus accessions for breeding in Japan, which resulted in 73,726 SNP calls. A total of 351 SNPs (91 %) could call different genotypes among the DNA samples, resulting in a success rate for the assay comparable to previously reported rates for other plant species. To confirm the reliability of SNP genotype calls, parentage analysis was applied, and it indicated that the number of reliable SNPs and corresponding STSs were 276 and 213, respectively. The multiplexed SNP genotyping array reported here will be useful for the efficient construction of linkage map, for the detection of markers for marker-assisted breeding, and for the identification of cultivars.     

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.     

Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array

High‐density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene‐associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome‐wide distributed SNPs that are represented in populations of diverse geographical origin. We used density‐based spatial clustering algorithms to enable high‐throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model‐free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low‐intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.     

Retention of gene diversity during the spread of a non‐native plant species

Spatial expansion, which is a crucial stage in the process to successful biological invasion, is anticipated to profoundly affect the magnitude and spatial distribution of genetic diversity in novel colonized areas. Here, we show that, contrasting common expectations, Pyrenean rocket (Sisymbrium austriacum), retained SNP diversity as this introduced plant species descended in the Meuse River Basin. Allele frequencies did not mirror between‐population distances along the predominant expansion axis. Reconstruction of invasion history based on the genotypes of historical herbarium specimens indicated no influence of additional introductions or multiple points of entry on this nongradual pattern. Assignment analysis suggested the admixture of distant upstream sources in recently founded downstream populations. River dynamics seem to have facilitated occasional long‐distance dispersal which brought diversity to the expansion front and so maintained evolutionary potential. Our findings highlight the merit of a historical framework in interpreting extant patterns of genetic diversity in introduced species and underscore the need to integrate long‐distance dispersal events in theoretical work on the genetic consequences of range expansion.     

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Background

The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum.

Results

Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, inter-population differentiation, and the degree to which allele frequencies are correlated between populations.

Conclusions

The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.     

Farmers without borders—genetic structuring in century old barley (Hordeum vulgare)

The geographic distribution of genetic diversity can reveal the evolutionary history of a species. For crop plants, phylogeographic patterns also indicate how seed has been exchanged and spread in agrarian communities. Such patterns are, however, easily blurred by the intense seed trade, plant improvement and even genebank conservation during the twentieth century, and discerning fine-scale phylogeographic patterns is thus particularly challenging. Using historical crop specimens, these problems are circumvented and we show here how high-throughput genotyping of historical nineteenth century crop specimens can reveal detailed geographic population structure. Thirty-one historical and nine extant accessions of North European landrace barley (Hordeum vulgare L.), in total 231 individuals, were genotyped on a 384 single nucleotide polymorphism assay. The historical material shows constant high levels of within-accession diversity, whereas the extant accessions show more varying levels of diversity and a higher degree of total genotype sharing. Structure, discriminant analysis of principal components and principal component analysis cluster the accessions in latitudinal groups across country borders in Finland, Norway and Sweden. F_ST statistics indicate strong differentiation between accessions from southern Fennoscandia and accessions from central or northern Fennoscandia, and less differentiation between central and northern accessions. These findings are discussed in the context of contrasting historical records on intense within-country south to north seed movement. Our results suggest that although seeds were traded long distances, long-term cultivation has instead been of locally available, possibly better adapted, genotypes.     

A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array

Background

High density genotyping data are indispensable for genomic analyses of complex traits in animal and crop species. Maize is one of the most important crop plants worldwide, however a high density SNP genotyping array for analysis of its large and highly dynamic genome was not available so far.

Results

We developed a high density maize SNP array composed of 616,201 variants (SNPs and small indels). Initially, 57 M variants were discovered by sequencing 30 representative temperate maize lines and then stringently filtered for sequence quality scores and predicted conversion performance on the array resulting in the selection of 1.2 M polymorphic variants assayed on two screening arrays. To identify high-confidence variants, 285 DNA samples from a broad genetic diversity panel of worldwide maize lines including the samples used for sequencing, important founder lines for European maize breeding, hybrids, and proprietary samples with European, US, semi-tropical, and tropical origin were used for experimental validation. We selected 616 k variants according to their performance during validation, support of genotype calls through sequencing data, and physical distribution for further analysis and for the design of the commercially available Affymetrix® Axiom® Maize Genotyping Array. This array is composed of 609,442 SNPs and 6,759 indels. Among these are 116,224 variants in coding regions and 45,655 SNPs of the Illumina® MaizeSNP50 BeadChip for study comparison. In a subset of 45,974 variants, apart from the target SNP additional off-target variants are detected, which show only a minor bias towards intermediate allele frequencies. We performed principal coordinate and admixture analyses to determine the ability of the array to detect and resolve population structure and investigated the extent of LD within a worldwide validation panel.

Conclusions

The high density Affymetrix® Axiom® Maize Genotyping Array is optimized for European and American temperate maize and was developed based on a diverse sample panel by applying stringent quality filter criteria to ensure its suitability for a broad range of applications. With 600 k variants it is the largest currently publically available genotyping array in crop species.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-823) contains supplementary material, which is available to authorized users.     

Museum specimens provide reliable SNP data for population genomic analysis of a widely distributed but threatened cockatoo species

Natural history museums harbour a plethora of biological specimens which are of potential use in population and conservation genetic studies. Although technical advancements in museum genomics have enabled genome‐wide markers to be generated from aged museum specimens, the suitability of these data for robust biological inference is not well characterized. The aim of this study was to test the utility of museum specimens in population and conservation genomics by assessing the biological and technical validity of single nucleotide polymorphism (SNP) data derived from such samples. To achieve this, we generated thousands of SNPs from 47 red‐tailed black cockatoo (Calyptorhychus banksii) traditional museum samples (i.e. samples that were not collected with the primary intent of DNA analysis) and 113 fresh tissue samples (cryopreserved liver/muscle) using a restriction site‐associated DNA marker approach (DArTseq^?). Thousands of SNPs were successfully generated from most of the traditional museum samples (with a mean age of 44 years, ranging from 5 to 123 years), although 38% did not provide useful data. These SNPs exhibited higher error rates and contained significantly more missing data compared with SNPs from fresh tissue samples, likely due to considerable DNA fragmentation. However, based on simulation results, the level of genotyping error had a negligible effect on inference of population structure in this species. We did identify a bias towards low diversity SNPs in older samples that appears to compromise temporal inferences of genetic diversity. This study demonstrates the utility of a RADseq‐based method to produce reliable genome‐wide SNP data from traditional museum specimens.     

Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.     

Invasion history of <Emphasis Type="Italic">Cardamine hirsuta</Emphasis> in Japan inferred from genetic analyses of herbarium specimens and current populations

Multiple introductions of a species are thought to enhance its invasion success by increasing genotypic diversity; this involves frequent crossing among different lineages. However, genetic diversity through crossing is less likely in autogamous species. To understand the impact of multiple introductions on the colonization success of autogamous species, we studied hairy bittercress, Cardamine hirsuta, which invaded Japan several decades ago. We detected temporal changes in its population structure using nine microsatellite markers amplified from leaf samples collected from 87 sites between 2009 and 2010, and herbarium specimens collected between 1988 and 2007. To examine whether the phenotypic variation corresponded with the genetic population structure, we also investigated the geographic variation in the lateral stamen number of this species across 49 sites. The present populations can be divided into three genetic groups, which are distributed in northern, eastern, and western Japan. This finding suggests that there are three invasive lineages (North, East, and West) in Japan. The geographic variation in lateral stamen number corresponded to the distributions of these lineages. The former distributions of the North and West lineages mostly corresponded to those found at present, but they were also historically found in eastern Japan. However, the East lineage has apparently expanded into eastern Japan, resulting in a change in dominant lineages over only a few decades. For the autogamous C. hirsuta, multiple introductions contributed toward colonization success over a wider range, which was associated with a local change in the dominant lineages.     

Availability of short microsatellite markers from butterfly museums and private specimens

Knowledge of the temporal changes in genetic diversity and structure is important for identifying factors causing a decline in threatened insect species, and for establishing conservation programs for these species. Thus, there is recently an increasing interest in the restoration of genetic diversity in conservation programs using DNA data from historical museum specimens. For butterfly specimens, we measured the yields and fragment sizes of the extracted DNA and investigated the genotyping success probability of nine short microsatellite markers (allele size 73–191 bp). We used leg samples of specimens of a medium‐sized butterfly species, Melitaea ambigua (Lepidoptera; Nymphalidae), collected from the 1960s to the 2010s. The yields of specimen‐extracted DNA longer than 150 bp decreased with increasing specimen age. There were negative correlations between the genotyping success probability and specimen age for each of all microsatellite markers. A negative correlation was also observed between the genotyping success probability and allele size of each microsatellite marker. We conclude that short microsatellite markers and analysis of recently obtained specimens are particularly suitable for microsatellite analysis of butterfly specimens.     

Fresh is best: Accurate SNP genotyping from koala scats

Maintaining genetic diversity is a crucial component in conserving threatened species. For the iconic Australian koala, there is little genetic information on wild populations that is not either skewed by biased sampling methods (e.g., sampling effort skewed toward urban areas) or of limited usefulness due to low numbers of microsatellites used. The ability to genotype DNA extracted from koala scats using next‐generation sequencing technology will not only help resolve location sample bias but also improve the accuracy and scope of genetic analyses (e.g., neutral vs. adaptive genetic diversity, inbreeding, and effective population size). Here, we present the successful SNP genotyping (1272 SNP loci) of koala DNA extracted from scat, using a proprietary DArTseq^? protocol. We compare genotype results from two‐day‐old scat DNA and 14‐day‐old scat DNA to a blood DNA template, to test accuracy of scat genotyping. We find that DNA from fresher scat results in fewer loci with missing information than DNA from older scat; however, 14‐day‐old scat can still provide useful genetic information, depending on the research question. We also find that a subset of 209 conserved loci can accurately identify individual koalas, even from older scat samples. In addition, we find that DNA sequences identified from scat samples through the DArTseq^? process can provide genetic identification of koala diet species, bacterial and viral pathogens, and parasitic organisms.     

Ultrahigh-Density Linkage Map for Cultivated Cucumber (Cucumis sativus L.) Using a Single-Nucleotide Polymorphism Genotyping Array

Genotyping arrays are tools for high-throughput genotyping, which is beneficial in constructing saturated genetic maps and therefore high-resolution mapping of complex traits. Since the report of the first cucumber genome draft, genetic maps have been constructed mainly based on simple-sequence repeats (SSRs) or on combinations of SSRs and sequence-related amplified polymorphism (SRAP). In this study, we developed the first cucumber genotyping array consisting of 32,864 single-nucleotide polymorphisms (SNPs). These markers cover the cucumber genome with a median interval of ~2 Kb and have expected genotype calls in parents/F₁ hybridizations as a training set. The training set was validated with Fluidigm technology and showed 96% concordance with the genotype calls in the parents/F₁ hybridizations. Application of the genotyping array was illustrated by constructing a 598.7 cM genetic map based on a ‘9930’ × ‘Gy14’ recombinant inbred line (RIL) population comprised of 11,156 SNPs. Marker collinearity between the genetic map and reference genomes of the two parents was estimated at R² = 0.97. We also used the array-derived genetic map to investigate chromosomal rearrangements, regional recombination rate, and specific regions with segregation distortions. Finally, 82% of the linkage-map bins were polymorphic in other cucumber variants, suggesting that the array can be applied for genotyping in other lines. The genotyping array presented here, together with the genotype calls of the parents/F₁ hybridizations as a training set, should be a powerful tool in future studies with high-throughput cucumber genotyping. An ultrahigh-density linkage map constructed by this genotyping array on RIL population may be invaluable for assembly improvement, and for mapping important cucumber QTLs.     

Development of an integrated 200K SNP genotyping array and application for genetic mapping,genome assembly improvement and genome wide association studies in pear (Pyrus)

Pear (Pyrus; 2n = 34), the third most important temperate fruit crop, has great nutritional and economic value. Despite the availability of many genomic resources in pear, it is challenging to genotype novel germplasm resources and breeding progeny in a timely and cost‐effective manner. Genotyping arrays can provide fast, efficient and high‐throughput genetic characterization of diverse germplasm, genetic mapping and breeding populations. We present here 200K AXIOM^® PyrSNP, a large‐scale single nucleotide polymorphism (SNP) genotyping array to facilitate genotyping of Pyrus species. A diverse panel of 113 re‐sequenced pear genotypes was used to discover SNPs to promote increased adoption of the array. A set of 188 diverse accessions and an F₁ population of 98 individuals from ‘Cuiguan’ × ‘Starkrimson’ was genotyped with the array to assess its effectiveness. A large majority of SNPs (166 335 or 83%) are of high quality. The high density and uniform distribution of the array SNPs facilitated prediction of centromeric regions on 17 pear chromosomes, and significantly improved the genome assembly from 75.5% to 81.4% based on genetic mapping. Identification of a gene associated with flowering time and candidate genes linked to size of fruit core via genome wide association studies showed the usefulness of the array in pear genetic research. The newly developed high‐density SNP array presents an important tool for rapid and high‐throughput genotyping in pear for genetic map construction, QTL identification and genomic selection.     

Evaluation of SNP Data from the Malus Infinium Array Identifies Challenges for Genetic Analysis of Complex Genomes of Polyploid Origin

High throughput arrays for the simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) have made the rapid genetic characterisation of plant genomes and the development of saturated linkage maps a realistic prospect for many plant species of agronomic importance. However, the correct calling of SNP genotypes in divergent polyploid genomes using array technology can be problematic due to paralogy, and to divergence in probe sequences causing changes in probe binding efficiencies. An Illumina Infinium II whole-genome genotyping array was recently developed for the cultivated apple and used to develop a molecular linkage map for an apple rootstock progeny (M432), but a large proportion of segregating SNPs were not mapped in the progeny, due to unexpected genotype clustering patterns. To investigate the causes of this unexpected clustering we performed BLAST analysis of all probe sequences against the ‘Golden Delicious’ genome sequence and discovered evidence for paralogous annealing sites and probe sequence divergence for a high proportion of probes contained on the array. Following visual re-evaluation of the genotyping data generated for 8,788 SNPs for the M432 progeny using the array, we manually re-scored genotypes at 818 loci and mapped a further 797 markers to the M432 linkage map. The newly mapped markers included the majority of those that could not be mapped previously, as well as loci that were previously scored as monomorphic, but which segregated due to divergence leading to heterozygosity in probe annealing sites. An evaluation of the 8,788 probes in a diverse collection of Malus germplasm showed that more than half the probes returned genotype clustering patterns that were difficult or impossible to interpret reliably, highlighting implications for the use of the array in genome-wide association studies.     

The USDA Barley Core Collection: Genetic Diversity,Population Structure,and Potential for Genome-Wide Association Studies

New sources of genetic diversity must be incorporated into plant breeding programs if they are to continue increasing grain yield and quality, and tolerance to abiotic and biotic stresses. Germplasm collections provide a source of genetic and phenotypic diversity, but characterization of these resources is required to increase their utility for breeding programs. We used a barley SNP iSelect platform with 7,842 SNPs to genotype 2,417 barley accessions sampled from the USDA National Small Grains Collection of 33,176 accessions. Most of the accessions in this core collection are categorized as landraces or cultivars/breeding lines and were obtained from more than 100 countries. Both STRUCTURE and principal component analysis identified five major subpopulations within the core collection, mainly differentiated by geographical origin and spike row number (an inflorescence architecture trait). Different patterns of linkage disequilibrium (LD) were found across the barley genome and many regions of high LD contained traits involved in domestication and breeding selection. The genotype data were used to define ‘mini-core’ sets of accessions capturing the majority of the allelic diversity present in the core collection. These ‘mini-core’ sets can be used for evaluating traits that are difficult or expensive to score. Genome-wide association studies (GWAS) of ‘hull cover’, ‘spike row number’, and ‘heading date’ demonstrate the utility of the core collection for locating genetic factors determining important phenotypes. The GWAS results were referenced to a new barley consensus map containing 5,665 SNPs. Our results demonstrate that GWAS and high-density SNP genotyping are effective tools for plant breeders interested in accessing genetic diversity in large germplasm collections.     

Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays

High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Automated SNP genotype clustering algorithm to improve data completeness in high-throughput SNP genotyping datasets from custom arrays

High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be advisable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays

High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.