In the last 20 years, we have observed an exponential growth of the DNA sequence data and simular increase in the volume of DNA polymorphism data generated by numerous molecular marker technologies. Most of the investment, and therefore progress, concentrated on human genome and genomes of selected model species. Diversity Arrays Technology (DArT), developed over a decade ago, was among the first "democratizing" genotyping technologies, as its performance was primarily driven by the level of DNA sequence variation in the species rather than by the level of financial investment. DArT also proved more robust to genome size and ploidy-level differences among approximately 60 organisms for which DArT was developed to date compared to other high-throughput genotyping technologies. The success of DArT in a number of organisms, including a wide range of "orphan crops," can be attributed to the simplicity of underlying concepts: DArT combines genome complexity reduction methods enriching for genic regions with a highly parallel assay readout on a number of "open-access" microarray platforms. The quantitative nature of the assay enabled a number of applications in which allelic frequencies can be estimated from DArT arrays. A typical DArT assay tests for polymorphism tens of thousands of genomic loci with the final number of markers reported (hundreds to thousands) reflecting the level of DNA sequence variation in the tested loci. Detailed DArT methods, protocols, and a range of their application examples as well as DArT's evolution path are presented.
Despite a substantial investment in the development of panels of single nucleotide polymorphism (SNP) markers, the simple sequence repeat (SSR) technology with a limited multiplexing capability remains a standard, even for applications requiring whole-genome information. Diversity arrays technology (DArT) types hundreds to thousands of genomic loci in parallel, as previously demonstrated in a number diploid plant species. Here we show that DArT performs similarly well for the hexaploid genome of bread wheat (Triticum aestivum L.). The methodology previously used to generate DArT fingerprints of barley also generated a large number of high-quality markers in wheat (99.8% allele-calling concordance and approximately 95% call rate). The genetic relationships among bread wheat cultivars revealed by DArT coincided with knowledge generated with other methods, and even closely related cultivars could be distinguished. To verify the Mendelian behaviour of DArT markers, we typed a set of 90 Cranbrook x Halberd doubled haploid lines for which a framework (FW) map comprising a total of 339 SSR, restriction fragment length polymorphism (RFLP) and amplified fragment length polymorphism (AFLP) markers was available. We added an equal number of DArT markers to this data set and also incorporated 71 sequence tagged microsatellite (STM) markers. A comparison of logarithm of the odds (LOD) scores, call rates and the degree of genome coverage indicated that the quality and information content of the DArT data set was comparable to that of the combined SSR/RFLP/AFLP data set of the FW map.
BackgroundRye (Secale cereale L.) is an economically important crop, exhibiting unique features such as outstanding resistance to biotic and abiotic stresses and high nutrient use efficiency. This species presents a challenge to geneticists and breeders due to its large genome containing a high proportion of repetitive sequences, self incompatibility, severe inbreeding depression and tissue culture recalcitrance. The genomic resources currently available for rye are underdeveloped in comparison with other crops of similar economic importance. The aim of this study was to create a highly saturated, multilocus linkage map of rye via consensus mapping, based on Diversity Arrays Technology (DArT) markers.Methodology/Principal FindingsRecombinant inbred lines (RILs) from 5 populations (564 in total) were genotyped using DArT markers and subjected to linkage analysis using Join Map 4.0 and Multipoint Consensus 2.2 software. A consensus map was constructed using a total of 9703 segregating markers. The average chromosome map length ranged from 199.9 cM (2R) to 251.4 cM (4R) and the average map density was 1.1 cM. The integrated map comprised 4048 loci with the number of markers per chromosome ranging from 454 for 7R to 805 for 4R. In comparison with previously published studies on rye, this represents an eight-fold increase in the number of loci placed on a consensus map and a more than two-fold increase in the number of genetically mapped DArT markers.Conclusions/SignificanceThrough the careful choice of marker type, mapping populations and the use of software packages implementing powerful algorithms for map order optimization, we produced a valuable resource for rye and triticale genomics and breeding, which provides an excellent starting point for more in-depth studies on rye genome organization.
BackgroundImplementation of molecular breeding in rye (Secale cereale L.) improvement programs depends on the availability of high-density molecular linkage maps. However, the number of sequence-specific PCR-based markers available for the species is limited. Diversity Arrays Technology (DArT) is a microarray-based method allowing for detection of DNA polymorphism at several thousand loci in a single assay without relying on DNA sequence information. The objective of this study was the development and application of Diversity Arrays technology for rye.ResultsUsing the PstI/TaqI method of complexity reduction we created a rye diversity panel from DNA of 16 rye varieties and 15 rye inbred lines, including parents of a mapping population consisting of 82 recombinant inbred lines. The usefulness of a wheat diversity panel for identification of DArT markers for rye was also demonstrated. We identified 1022 clones that were polymorphic in the genotyped ILs and varieties and 1965 clones that differentiated the parental lines L318 and L9 and segregated in the mapping population. Hierarchical clustering and ordination analysis were performed based on the 1022 DArT markers to reveal genetic relationships between the rye varieties and inbred lines included in the study. Chromosomal location of 1872 DArT markers was determined using wheat-rye addition lines and 1818 DArT markers (among them 1181 unique, non-cosegregating) were placed on a genetic linkage map of the cross L318 × L9, providing an average density of one unique marker every 2.68 cM. This is the most saturated rye linkage map based solely on transferable markers available at the moment, providing rye breeders and researches with a better choice of markers and a higher probability of finding polymorphic markers in the region of interest.ConclusionThe Diversity Arrays Technology can be efficiently and effectively used for rye genome analyses - assessment of genetic similarity and linkage mapping. The 11520-clone rye genotyping panel with several thousand markers with determined chromosomal location and accessible through an inexpensive genotyping service is a valuable resource for studies on rye genome organization and in molecular breeding of the species.
Motivation Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. Availability and implementation More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.
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