Identification and validation of a core set of informative genic SSR and SNP markers for assaying functional diversity in barley

A ‘core set’ of 28 simple sequence repeat (SSR) and 28 single nucleotide polymorphism (SNP) markers for barley was developed after screening six diverse genotypes (DGs) representing six countries (Afghanistan, Pakistan, Algeria, Egypt, Jordan and Syria) with 50 SSR and 50 SNP markers derived from expressed sequence tags (ESTs). The markers of the core set are single locus with very high quality amplifications, high polymorphism information content (PIC) and are distributed across the barley genome. PIC values for the selected SSR and SNP markers ranged between 0.32–0.72 (average 0.58) and 0.28–0.50 (average 0.42), respectively. To make the SNP genotyping cost effective, CAPS (cleaved amplified polymorphic sequence) and indel assays were developed for 23 markers and the remaining 5 SNP markers were optimized for pyrosequencing. A high coefficient of correlations (r = 0.96, P < 0.005) between the genetic similarity matrices of SSR and SNP genotyping data of the core set on diverse genotypes (DGs) and their similar groupings according to the geographical distribution in both SSR and SNP phenograms with high bootstrap values underline the utility and reliability of the core set. A comparative allelic and sequence diversity for SSR and SNP markers between the DGs and six elite parental genotypes (PGs) of mapping populations showed comparable diverse nature of two germplasm sets. However, unique SNPs and indels were observed in both germplasm sets providing more datapoints for analysing haplotypes in a better way for the corresponding SNP marker. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

A pipeline for high throughput detection and mapping of SNPs from EST databases

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation.     

Development of a SNP genotyping panel for genetic monitoring of the laboratory mouse

We have developed a genotyping system for detecting genetic contamination in the laboratory mouse based on assaying single-nucleotide polymorphism (SNP) markers positioned on all autosomes and the X chromosome. This system provides a fast, reliable, and cost-effective way for genetic monitoring, while maintaining a very high degree of confidence. We describe the allelic distribution of 235 SNPs in 48 mouse strains, thereby creating a database of polymorphisms useful for genotyping purposes. The SNP markers used in this study were chosen from publicly available SNP databases. Four genotyping methods were evaluated, and dynamic two-tube allele-specific PCR assays were developed for each marker and tested on a set of 48 inbred mouse strains. The minimal number of assays sufficient to distinguish groups consisting of different numbers of mouse strains was estimated, and a panel of 28 SNPs sufficient to distinguish virtually all of the inbred strains tested was selected. Amplifluor SNP detection assays were developed for these markers and tested on an extended list of 96 strains. This panel was used as a genetic quality control approach to monitor the genotypes of nearly 300 inbred, wild-derived, congenic, consomic, and recombinant inbred strains maintained at The Jackson Laboratory. We have concluded that this marker panel is sufficient for genetic contamination monitoring in colonies containing a large number of genetically diverse mouse strains and that reduced versions of the panel could be implemented in facilities housing a lower number of strains.     

Development and assessment of simple PCR markers for SNP genotyping in barley

Simple molecular marker assays underpin routine plant breeding and research activities in many laboratories worldwide. With the rapid growth of single nucleotide polymorphism (SNP) resources for many important crop plants, the availability of routine, low-tech marker assays for genotyping SNPs is of increased importance. In this study, we demonstrate that temperature-switch PCR (TSP) supports the rapid development of robust, allele-specific PCR markers for codominant SNP genotyping on agarose gel. A total of 87 TSP markers for assessing gene diversity in barley were developed and used to investigate the efficacy for marker development, assay reliably and genotyping accuracy. The TSP markers described provide good coverage of the barley genome, are simple to use, easy to interpret and score, and are amenable to assay automation. They provide a resource of informative SNP markers for assessing genetic relationships among individuals, populations and gene pools of cultivated barley (Hordeum vulgare L.) and its wild relative H. spontaneum K. Koch. TSP markers provide opportunities to use available SNP resources for marker-assisted breeding and plant genetic research, and to generate information that can be integrated with SNP data from different sources and studies. TSP markers are expected to provide similar advantages for any animal or plant species. M. J. Hayden and T. Tabone contributed equally to this work.     

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.     

High-throughput genotyping with the GoldenGate assay in the complex genome of soybean

Large numbers of single nucleotide polymorphism (SNP) markers are now available for a number of crop species. However, the high-throughput methods for multiplexing SNP assays are untested in complex genomes, such as soybean, that have a high proportion of paralogous genes. The Illumina GoldenGate assay is capable of multiplexing from 96 to 1,536 SNPs in a single reaction over a 3-day period. We tested the GoldenGate assay in soybean to determine the success rate of converting verified SNPs into working assays. A custom 384-SNP GoldenGate assay was designed using SNPs that had been discovered through the resequencing of five diverse accessions that are the parents of three recombinant inbred line (RIL) mapping populations. The 384 SNPs that were selected for this custom assay were predicted to segregate in one or more of the RIL mapping populations. Allelic data were successfully generated for 89% of the SNP loci (342 of the 384) when it was used in the three RIL mapping populations, indicating that the complex nature of the soybean genome had little impact on conversion of the discovered SNPs into usable assays. In addition, 80% of the 342 mapped SNPs had a minor allele frequency >10% when this assay was used on a diverse sample of Asian landrace germplasm accessions. The high success rate of the GoldenGate assay makes this a useful technique for quickly creating high density genetic maps in species where SNP markers are rapidly becoming available. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the USDA and does not imply approval of a product to the exclusion of others that may be suitable.     

Establishment of a high-efficiency SNP-based framework marker set for Arabidopsis

The major goal of this project was the establishment of a tool for rapid mapping of new mutations and genotyping in Arabidopsis consisting of at least 100 evenly spaced framework markers. We assembled a single nucleotide polymorphism (SNP)-based marker set consisting of 112 polymorphic sites with average spacing of 1.15 Mbp derived from an SNP database that we recently developed. This information was used to set up efficient SNP detection reactions based on multiplexed primer extension assays. The 112 Columbia (Col-0)/C24 framework markers were used to assemble 18 multiplexed SNaPshot assays with which up to eight separate loci can be genotyped in a single-tube/single-capillary format. In addition, for 110 framework markers matrix-assisted laser desorption/ionization time of flight (MALDI-ToF) assays have been established for high throughput analyses. We demonstrated the usefulness and the robustness of both procedures of this tool by genotyping 48 BC3F1 individuals created between the accessions Col-0 and C24. Subsets of 10-62 of the established markers discriminate between various combinations of the accessions Col-0, C24, Landsberg erecta (Ler), Cape Verdi Islands (Cvi) and Niederzenz (Nd). Using a subset of 17 evenly distributed and established SNP markers that are also polymorphic between Ler and Col-0, we were able to rapidly map a mutant gene (tbr1) to an interval of 2.3 Mbp in an Ler (tbr1) x Col-0 cross.     

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.     

Future tools for association mapping in crop plants

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping. These include autoSNPdb for SNP discovery from assembled sequence data; TAGdb for the identification of gene specific paired read Illumina GAII data; CMap3D for the comparison of mapped genetic and physical markers; and BAC and Gene Annotator for the online annotation of genes and genomic sequences.     

MAP-O-MAT: internet-based linkage mapping

SUMMARY: MAP-O-MAT is a web-based server for automated linkage mapping of human polymorphic DNA markers. MAP-O-MAT facilitates the verification of order and map distances for custom mapping sets using genotype data from the CEPH database, and from the Marshfield, SNP Consortium and Rutgers linkage maps (exclusive to the deCODE genotyping data). The CRI-MAP program is used for likelihood calculations and some mapping algorithms, and physical map positions are provided from the human genome assembly. AVAILABILITY: MAP-O-MAT is located at http://compgen.rutgers.edu/mapomat/ CONTACT: matise@biology.rutgers.edu.     

Online resources for SNP analysis

The major online single nucleotide polymorphism (SNP) databases freely available as research tools for genetic analysis are explained, reviewed, and compared. An outline is given of the search strategies that can be used with the most extensive current SNP databases: National Centre for Biotechnology Information (NCBI) dbSNP and HapMap to help the user secure the most appropriate data for the research needs of clinical genetics and population genetics research. A range of online tools that can be useful in designing SNP genotyping assays are also detailed.     

Large-Scale Development of Cost-Effective Single-Nucleotide Polymorphism Marker Assays for Genetic Mapping in Pigeonpea and Comparative Mapping in Legumes

Single-nucleotide polymorphisms (SNPs, >2000) were discovered by using RNA-seq and allele-specific sequencing approaches in pigeonpea (Cajanus cajan). For making the SNP genotyping cost-effective, successful competitive allele-specific polymerase chain reaction (KASPar) assays were developed for 1616 SNPs and referred to as PKAMs (pigeonpea KASPar assay markers). Screening of PKAMs on 24 genotypes [23 from cultivated species and 1 wild species (Cajanus scarabaeoides)] defined a set of 1154 polymorphic markers (77.4%) with a polymorphism information content (PIC) value from 0.04 to 0.38. One thousand and ninety-four PKAMs showed polymorphisms between parental lines of the reference mapping population (C. cajan ICP 28 × C. scarabaeoides ICPW 94). By using high-quality marker genotyping data on 167 F₂ lines from the population, a comprehensive genetic map comprising 875 PKAMs with an average inter-marker distance of 1.11 cM was developed. Previously mapped 35 simple sequence repeat markers were integrated into the PKAM map and an integrated genetic map of 996.21 cM was constructed. Mapped PKAMs showed a higher degree of synteny with the genome of Glycine max followed by Medicago truncatula and Lotus japonicus and least with Vigna unguiculata. These PKAMs will be useful for genetics research and breeding applications in pigeonpea and for utilizing genome information from other legume species.     

High-throughput genotyping and mapping of single nucleotide polymorphisms in loblolly pine (Pinus taeda L.)

The development and application of genomic tools to loblolly pine (Pinus taeda L.) offer promising insights into the organization and structure of conifer genomes. The application of a high-throughput genotyping assay across diverse forest tree species, however, is currently limited taxonomically. This is despite the ongoing development of genome-scale projects aiming at the construction of expressed sequence tag (EST) libraries and the resequencing of EST-derived unigenes for a diverse array of forest tree species. In this paper, we report on the application of Illumina’s high-throughput GoldenGate™ SNP genotyping assay to a loblolly pine mapping population. Single nucleotide polymorphisms (SNPs) were identified through resequencing of previously identified wood quality, drought tolerance, and disease resistance candidate genes prior to genotyping. From that effort, a 384 multiplexed SNP assay was developed for high-throughput genotyping. Approximately 67% of the 384 SNPs queried converted into high-quality genotypes for the 48 progeny samples. Of those 257 successfully genotyped SNPs, 70 were segregating within the mapping population. A total of 27 candidate genes were subsequently mapped onto the existing loblolly pine consensus map, which consists of 12 linkage groups spanning a total map distance of 1,227.6 cM. The ability of SNPs to be mapped to the same position as fragment-based markers previously developed within the same candidate genes, as well as the pivotal role that SNPs currently play in the dissection of complex phenotypic traits, illustrate the usefulness of high-throughput SNP genotyping technologies to the continued development of pine genomics. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Conversion of array‐based single nucleotide polymorphic markers for use in targeted genotyping by sequencing in hexaploid wheat (Triticum aestivum)

Wheat breeders and academics alike use single nucleotide polymorphisms (SNP s) as molecular markers to characterize regions of interest within the hexaploid wheat genome. A number of SNP ‐based genotyping platforms are available, and their utility depends upon factors such as the available technologies, number of data points required, budgets and the technical expertise required. Unfortunately, markers can rarely be exchanged between existing and newly developed platforms, meaning that previously generated data cannot be compared, or combined, with more recently generated data sets. We predict that genotyping by sequencing will become the predominant genotyping technology within the next 5–10 years. With this in mind, to ensure that data generated from current genotyping platforms continues to be of use, we have designed and utilized SNP ‐based capture probes from several thousand existing and publicly available probes from Axiom® and KASP ? genotyping platforms. We have validated our capture probes in a targeted genotyping by sequencing protocol using 31 previously genotyped UK elite hexaploid wheat accessions. Data comparisons between targeted genotyping by sequencing, Axiom® array genotyping and KASP ? genotyping assays, identified a set of 3256 probes which reliably bring together targeted genotyping by sequencing data with the previously available marker data set. As such, these probes are likely to be of considerable value to the wheat community. The probe details, full probe sequences and a custom built analysis pipeline may be freely downloaded from the CerealsDB website (http://www.cerealsdb.uk.net/cerealgenomics/CerealsDB /sequence_capture.php).     

DEco‐TILLING: an inexpensive method for single nucleotide polymorphism discovery that reduces ascertainment bias

Genetic markers that measure DNA variation are important for population genetics research, resource management and other applications. Single nucleotide polymorphisms (SNP) are becoming a popular marker because they are abundant and because rapid and efficient assays can be developed to detect them. However, with the exception of a few organisms, most species have little DNA sequence information available and relatively few SNPs have been developed for species that lack sequence data. Methods to find SNPs can be expensive and incorporate substantial ascertainment bias, which may result in failure to discover SNPs that are useful or efficient for addressing specific questions. We have developed a system to detect SNPs that we call DEco‐TILLING, which is derived from Eco‐TILLING (targeting induced local lesions in genomes). The DEco‐TILLING method facilitates the development of useful genotyping assays rapidly and inexpensively and can reduce ascertainment bias.     

An imputed genotype resource for the laboratory mouse

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrated that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high-density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains. The data are available for bulk download or query at /. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.