Characterization of a Wheat Breeders’ Array suitable for high‐throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum)

Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism‐based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high‐density Affymetrix Axiom^® genotyping array (the Wheat Breeders’ Array), in a high‐throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders’ Array is also suitable for generating high‐density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site ‘CerealsDB’.     

Rapid identification of homozygosity and site of wild relative introgressions in wheat through chromosome‐specific KASP genotyping assays

For future food security, it is important that wheat, one of the most widely consumed crops in the world, can survive the threat of abiotic and biotic stresses. New genetic variation is currently being introduced into wheat through introgressions from its wild relatives. For trait discovery, it is necessary that each introgression is homozygous and hence stable. Breeding programmes rely on efficient genotyping platforms for marker‐assisted selection (MAS). Recently, single nucleotide polymorphism (SNP)‐based markers have been made available on high‐throughput Axiom^® SNP genotyping arrays. However, these arrays are inflexible in their design and sample numbers, making their use unsuitable for long‐term MAS. SNPs can potentially be converted into Kompetitive allele‐specific PCR (KASP?) assays that are comparatively cost‐effective and efficient for low‐density genotyping of introgression lines. However, due to the polyploid nature of wheat, KASP assays for homoeologous SNPs can have difficulty in distinguishing between heterozygous and homozygous hybrid lines in a backcross population. To identify co‐dominant SNPs, that can differentiate between heterozygotes and homozygotes, we PCR‐amplified and sequenced genomic DNA from potential single‐copy regions of the wheat genome and compared them to orthologous copies from different wild relatives. A panel of 620 chromosome‐specific KASP assays have been developed that allow rapid detection of wild relative segments and provide information on their homozygosity and site of introgression in the wheat genome. A set of 90 chromosome‐nonspecific assays was also produced that can be used for genotyping introgression lines. These multipurpose KASP assays represent a powerful tool for wheat breeders worldwide.     

Discovery and development of exome‐based,co‐dominant single nucleotide polymorphism markers in hexaploid wheat (Triticum aestivum L.)

Globally, wheat is the most widely grown crop and one of the three most important crops for human and livestock feed. However, the complex nature of the wheat genome has, until recently, resulted in a lack of single nucleotide polymorphism (SNP)‐based molecular markers of practical use to wheat breeders. Recently, large numbers of SNP‐based wheat markers have been made available via the use of next‐generation sequencing combined with a variety of genotyping platforms. However, many of these markers and platforms have difficulty distinguishing between heterozygote and homozygote individuals and are therefore of limited use to wheat breeders carrying out commercial‐scale breeding programmes. To identify exome‐based co‐dominant SNP‐based assays, which are capable of distinguishing between heterozygotes and homozygotes, we have used targeted re‐sequencing of the wheat exome to generate large amounts of genomic sequences from eight varieties. Using a bioinformatics approach, these sequences have been used to identify 95 266 putative single nucleotide polymorphisms, of which 10 251 were classified as being putatively co‐dominant. Validation of a subset of these putative co‐dominant markers confirmed that 96% were true polymorphisms and 65% were co‐dominant SNP assays. The new co‐dominant markers described here are capable of genotypic classification of a segregating locus in polyploid wheat and can be used on a variety of genotyping platforms; as such, they represent a powerful tool for wheat breeders. These markers and related information have been made publically available on an interactive web‐based database to facilitate their use on genotyping programmes worldwide.     

Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

Single nucleotide polymorphism (SNP) data can be obtained using one of the numerous uniplex or multiplex SNP genotyping platforms that combine a variety of chemistries, detection methods, and reaction formats. Kompetitive Allele Specific PCR (KASP) is one of the uniplex SNP genotyping platforms, and has evolved to be a global benchmark technology. However, there are no publications relating either to the technology itself or to its application in crop improvement programs. In this review, we provide an overview of the different aspects of the KASP genotyping platform, discuss its application in crop improvement, and compare it with the chip-based Illumina GoldenGate platform. The International Maize and Wheat Improvement Center routinely uses KASP, generating in excess of a million data points annually for crop improvement purposes. We found that (1) 81 % of the SNPs used in a custom-designed GoldenGate assay were transferable to KASP; (2) using KASP, negative controls (no template) consistently clustered together and rarely produced signals exceeding the threshold values for allele calling, in contrast to the situation observed using GoldenGate assays; (3) KASP’s average genotyping error in positive control DNA samples was 0.7–1.6 %, which is lower than that observed using GoldenGate (2.0–2.4 %); (4) KASP genotyping costs for marker-assisted recurrent selection were 7.9–46.1 % cheaper than those of the BeadXpress and GoldenGate platforms; and (5) KASP offers cost-effective and scalable flexibility in applications that require small to moderate numbers of markers, such as quality control analysis, quantitative trait loci (QTL) mapping in bi-parental populations, marker-assisted recurrent selection, marker-assisted backcrossing, and QTL fine mapping.     

Single nucleotide polymorphism genotyping in polyploid wheat with the Illumina GoldenGate assay

Single nucleotide polymorphisms (SNPs) are indispensable in such applications as association mapping and construction of high-density genetic maps. These applications usually require genotyping of thousands of SNPs in a large number of individuals. Although a number of SNP genotyping assays are available, most of them are designed for SNP genotyping in diploid individuals. Here, we demonstrate that the Illumina GoldenGate assay could be used for SNP genotyping of homozygous tetraploid and hexaploid wheat lines. Genotyping reactions could be carried out directly on genomic DNA without the necessity of preliminary PCR amplification. A total of 53 tetraploid and 38 hexaploid homozygous wheat lines were genotyped at 96 SNP loci. The genotyping error rate estimated after removal of low-quality data was 0 and 1% for tetraploid and hexaploid wheat, respectively. Developed SNP genotyping assays were shown to be useful for genotyping wheat cultivars. This study demonstrated that the GoldenGate assay is a very efficient tool for high-throughput genotyping of polyploid wheat, opening new possibilities for the analysis of genetic variation in wheat and dissection of genetic basis of complex traits using association mapping approach. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Multiplexed single nucleotide polymorphism genotyping by oligonucleotide ligation and flow cytometry

BACKGROUND: We have developed a rapid, high throughput method for single nucleotide polymorphism (SNP) genotyping that employs an oligonucleotide ligation assay (OLA) and flow cytometric analysis of fluorescent microspheres. METHODS: A fluoresceinated oligonucleotide reporter sequence is added to a "capture" probe by OLA. Capture probes are designed to hybridize both to genomic "targets" amplified by polymerase chain reaction and to a separate complementary DNA sequence that has been coupled to a microsphere. These sequences on the capture probes are called "ZipCodes". The OLA-modified capture probes are hybridized to ZipCode complement-coupled microspheres. The use of microspheres with different ratios of red and orange fluorescence makes a multiplexed format possible where many SNPs may be analyzed in a single tube. Flow cytometric analysis of the microspheres simultaneously identifies both the microsphere type and the fluorescent green signal associated with the SNP genotype. RESULTS: Application of this methodology is demonstrated by the multiplexed genotyping of seven CEPH DNA samples for nine SNP markers located near the ApoE locus on chromosome 19. The microsphere-based SNP analysis agreed with genotyping by sequencing in all cases. CONCLUSIONS: Multiplexed SNP genotyping by OLA with flow cytometric analysis of fluorescent microspheres is an accurate and rapid method for the analysis of SNPs.     

High-throughput single nucleotide polymorphism genotyping in wheat (Triticum spp.)

Over the past few years, considerable progress has been made in high-throughput single nucleotide polymorphism (SNP) genotyping technologies, largely through the investment of the human genetics community. These technologies are well adapted to diploid species. For plant breeding purposes, it is important to determine whether these genotyping methods are adapted to polyploidy, as most major crops are former or recent polyploids. To address this problem, we tested the capacity of the multiplex technology SNPlex™ with a set of 47 wheat SNPs to genotype DNAs of 1314 lines that were organized in four 384-well plates. These lines represented different taxa of tetra- and hexaploid Triticum species and their wild diploid relatives. We observed 40 markers which gave less than 20% missing data. Different methods, based on either Sanger sequencing or the MassARRAY^® genotyping technology, were then used to validate the genotypes obtained by SNPlex™ for 11 markers. The concordance of the genotypes obtained by SNPlex™ with the results obtained by the different validation methods was 96%, except for one discarded marker. Furthermore, a mapping study on six markers showed the expected genetic positions previously described. To conclude, this study showed that high-throughput genotyping technologies developed for diploid species can be used successfully in polyploids, although there is a need for manual reading. For the first time in wheat species, a core of 39 SNPs is available that can serve as the basis for the development of a complete SNPlex™ set of 48 markers.     

Accelerating public sector rice breeding with high-density KASP markers derived from whole genome sequencing of <Emphasis Type="Italic">indica</Emphasis> rice

Few public sector rice breeders have the capacity to use NGS-derived markers in their breeding programmes despite rapidly expanding repositories of rice genome sequence data. They rely on >?18,000 mapped microsatellites (SSRs) for marker-assisted selection (MAS) using gel analysis. Lack of knowledge about target SNP and InDel variant loci has hampered the uptake by many breeders of Kompetitive allele-specific PCR (KASP), a proprietary technology of LGC genomics that can distinguish alleles at variant loci. KASP is a cost-effective single-step genotyping technology, cheaper than SSRs and more flexible than genotyping by sequencing (GBS) or array-based genotyping when used in selection programmes. Before this study, there were 2015 rice KASP marker loci in the public domain, mainly identified by array-based screening, leaving large proportions of the rice genome with no KASP coverage. Here we have addressed the urgent need for a wide choice of appropriate rice KASP assays and demonstrated that NGS can detect many more KASP to give full genome coverage. Through re-sequencing of nine indica rice breeding lines or released varieties, this study has identified 2.5 million variant sites. Stringent filtering of variants generated 1.3 million potential KASP assay designs, including 92,500 potential functional markers. This strategy delivers a 650-fold increase in potential selectable KASP markers at a density of 3.1 per 1 kb in the indica crosses analysed and 377,178 polymorphic KASP design sites on average per cross. This knowledge is available to breeders and has been utilised to improve the efficiency of public sector breeding in Nepal, enabling identification of polymorphic KASP at any region or quantitative trait loci in relevant crosses. Validation of 39 new KASP was carried out by genotyping progeny from a range of crosses to show that they detected segregating alleles. The new KASP have replaced SSRs to aid trait selection during marker-assisted backcrossing in these crosses, where target traits include rice blast and BLB resistance loci. Furthermore, we provide the software for plant breeders to generate KASP designs from their own datasets.     

Rapid identification of an adult plant stripe rust resistance gene in hexaploid wheat by high-throughput SNP array genotyping of pooled extremes

Key message

High-throughput SNP array analysis of pooled extreme phenotypes in a segregating population by KASP marker genotyping permitted rapid, cost-effective location of a stripe rust resistance QTL in wheat.

Abstract

German wheat cultivar “Friedrichswerther” has exhibited high levels of adult plant resistance (APR) to stripe rust in field environments for many years. F_2:3 lines and F₆ recombinant inbred line (RILs) populations derived from a cross between Friedrichswerther and susceptible landrace Mingxian 169 were evaluated in the field in 2013, 2016 and 2017. Illumina 90K iSelect SNP arrays were used to genotype bulked extreme pools and parents; 286 of 1135 polymorphic SNPs were identified on chromosome 6B. Kompetitive Allele-Specific PCR (KASP) markers were used to verify the chromosome region associated with the resistance locus. A linkage map was constructed with 18 KASP-SNP markers, and a major effect QTL was identified within a 1.4 cM interval flanked by KASP markers IWB71602 and IWB55937 in the region 6BL3-0-0.36. The QTL, named QYr.nwafu-6BL, was stable across environments, and explained average 54.4 and 47.8% of the total phenotypic variation in F_2:3 lines and F₆ RILs, respectively. On the basis of marker genotypes, pedigree analysis and relative genetic distance QYr.nwafu-6BL is likely to be a new APR QTL. Combined high-throughput SNP array genotyping of pooled extremes and validation by KASP assays lowers sequencing costs compared to genome-wide association studies with SNP arrays, and more importantly, permits rapid isolation of major effect QTL in hexaploid wheat as well as improving accuracy of mapping in the QTL region. QYr.nwafu-6BL with flanking KASP markers developed and verified in a subset of 236 diverse lines can be used in marker-assisted selection to improve stripe rust resistance in breeding programs.

     

Using Next Generation Sequencing for Multiplexed Trait-Linked Markers in Wheat

With the advent of next generation sequencing (NGS) technologies, single nucleotide polymorphisms (SNPs) have become the major type of marker for genotyping in many crops. However, the availability of SNP markers for important traits of bread wheat ( Triticum aestivum L.) that can be effectively used in marker-assisted selection (MAS) is still limited and SNP assays for MAS are usually uniplex. A shift from uniplex to multiplex assays will allow the simultaneous analysis of multiple markers and increase MAS efficiency. We designed 33 locus-specific markers from SNP or indel-based marker sequences that linked to 20 different quantitative trait loci (QTL) or genes of agronomic importance in wheat and analyzed the amplicon sequences using an Ion Torrent Proton Sequencer and a custom allele detection pipeline to determine the genotypes of 24 selected germplasm accessions. Among the 33 markers, 27 were successfully multiplexed and 23 had 100% SNP call rates. Results from analysis of "kompetitive allele-specific PCR" (KASP) and sequence tagged site (STS) markers developed from the same loci fully verified the genotype calls of 23 markers. The NGS-based multiplexed assay developed in this study is suitable for rapid and high-throughput screening of SNPs and some indel-based markers in wheat.     

High‐density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool

In wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheat's secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra‐high‐density Axiom^® genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site.     

Sequence Polymorphism Discovery in Wheat Microsatellite Flanking Regions using Pyrophosphate Sequencing

Sequence polymorphisms such as insertion/deletions (indels) and single nucleotide polymorphisms (SNP) are suitable for automated analysis of molecular markers and useful for cultivar identification, genetic mapping and trait association. While they are abundant, their initial discovery, comprising detection, validation and characterisation of sequence polymorphisms, is time consuming and expensive. This is especially true for multi-allellic hexaploid wheat. We investigated simple sequence repeat (SSR) flanking regions as a source for sequence polymorphisms in wheat. SSRs have a potentially high polymorphic frequency, there are a large number of highly characterised markers available, tested primers are published and most are single locus. Of 126 markers investigated, polymorphisms were found in 33 (26%) when tested in 10 wheat varieties. No new primers needed to be designed, the published primer sequences were used as PCR primers and then as sequencing primers. Polymorphism was detected by resequencing using a modification of pyrophosphate sequencing (Pyrosequencing^®) which yielded quality sequencing from the first base after the primer with up to 80 bases of information. Our method of pyrophosphate sequencing of SSRs, although not suitable for full-length sequencing, is an attractive method to directly find sequence polymorphism in varieties of interest using the abundant, well characterised and published SSR markers.     

Genomic selection prediction models comparing sequence capture and SNP array genotyping methods

The successful application of genomic selection (GS) approaches is dependent on genetic makers derived from high-throughput and low-cost genotyping methods. Recent GS studies in trees have predominantly relied on SNP arrays as the source of genotyping, though this technology has a high entry cost. The recent development of alternative genotyping platforms, tailored to specific species and with low entry cost, has become possible due to advances in next-generation sequencing and genome complexity reduction methods such as sequence capture. However, the performance of these new platforms in GS models has not yet been evaluated, or compared to models developed from SNP arrays. Here, we evaluate the impact of these genotyping technologies on the development of GS prediction models for a Eucalyptus breeding population composed of 739 trees phenotyped for 13 wood quality and growth traits. Genotyping data obtained with both methods were compared for linkage disequilibrium, minor allele frequency, and missing data. Phenotypic prediction methods RR-BLUP and BayesB were employed, while predictive ability using cross validation was used to evaluate the performance of GS models derived from the different genotyping platforms. Differences in linkage disequilibrium patterns, minor allele frequency, missing data, and marker distribution were detected between sequence capture and SNP arrays. However, RR-BLUP and BayesB GS models resulted in similar predictive abilities. These results demonstrate that both genotyping methods are equivalent for genomic prediction of the traits evaluated. Sequence capture offers an alternative for species where SNP arrays are not available, or for when the initial development cost is too high.     

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High‐throughput SNP arrays, or ‘SNP chips’, can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb ( http://snpdb.appliedbioinformatics.com.au ), a database for SNP array data produced by the Illumina Infinium? hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop‐breeding activities.     

Sequence‐based SNP genotyping in durum wheat

Marker development for marker‐assisted selection in plant breeding is increasingly based on next‐generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence‐based genotyping (SBG), which couples AFLP^®‐based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre‐existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre‐existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map‐size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10‐cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high‐throughput and high‐quality marker discovery and genotyping for complex genomes such as that of durum wheat.     

A System for Distinguishing Octoploid Strawberry Cultivars Using High-Throughput SNP Genotyping

Cultivated strawberry (Fragaria × ananassa) is an important commercial berry crop grown throughout the world. Improved strawberry cultivars are developed to meet the needs of consumers and breeders. Strawberries are usually propagated through runners, which sometimes lead to mislabeling or misinterpretation of cultivars. However, perfect identification of strawberry cultivars is essential for germplasm maintenance and for breeding programs. Molecular marker technology has been widely used to distinguish cultivars of other crops, but marker development in octoploid strawberries is complicated. Therefore, SNP marker with high-density and even distribution in the genome has been used currently as efficient DNA markers. In this report, previously published high-quality poly high resolution (PHR) SNPs from the 90 K Axiom® SNP array were utilized to develop a Fluidigm 24 SNPs genotyping system. Hundred nine (109) octoploid strawberry cultivars were screened using this 24 SNPs chip set. In addition, 24 SNPs were mapped to six chromosomes of diploid strawberry (Fragaria vesca). Our developed SNPs fluidigm genotyping is automatable, easy and reliable for processing and interpretation of data. Thus, this high-throughput SNP genotyping system will be a useful tool for distinguishing strawberry cultivars and find out parent-offspring relationship.     

Mapping‐by‐sequencing in complex polyploid genomes using genic sequence capture: a case study to map yellow rust resistance in hexaploid wheat

Previously we extended the utility of mapping‐by‐sequencing by combining it with sequence capture and mapping sequence data to pseudo‐chromosomes that were organized using wheat–Brachypodium synteny. This, with a bespoke haplotyping algorithm, enabled us to map the flowering time locus in the diploid wheat Triticum monococcum L. identifying a set of deleted genes (Gardiner et al., 2014). Here, we develop this combination of gene enrichment and sliding window mapping‐by‐synteny analysis to map the Yr6 locus for yellow stripe rust resistance in hexaploid wheat. A 110 MB NimbleGen capture probe set was used to enrich and sequence a doubled haploid mapping population of hexaploid wheat derived from an Avalon and Cadenza cross. The Yr6 locus was identified by mapping to the POPSEQ chromosomal pseudomolecules using a bespoke pipeline and algorithm (Chapman et al., 2015). Furthermore the same locus was identified using newly developed pseudo‐chromosome sequences as a mapping reference that are based on the genic sequence used for sequence enrichment. The pseudo‐chromosomes allow us to demonstrate the application of mapping‐by‐sequencing to even poorly defined polyploidy genomes where chromosomes are incomplete and sub‐genome assemblies are collapsed. This analysis uniquely enabled us to: compare wheat genome annotations; identify the Yr6 locus – defining a smaller genic region than was previously possible; associate the interval with one wheat sub‐genome and increase the density of SNP markers associated. Finally, we built the pipeline in iPlant, making it a user‐friendly community resource for phenotype mapping.     

Sequence-based genotyping for marker discovery and co-dominant scoring in germplasm and populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n?=?222 samples) and lettuce (n?=?87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike.     

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.