Characterization of Germplasm, Diversity Studies and Population Genetics/Genomics
DArTseq is routinely deployed for characterization of parental materials and variety of genebanks. Examples include analysis of 150K wheat and 80K maize accessions from CIMMYT germplasm collection. Large numbers of other cereals, various forest trees, vegetables, horticulture plants as well as large number of natural plant and animal populations have also been analyzed with DArTseq.
Genetic and Consensus Mapping
Genetic maps have been produced for numerous species with wheat dominating this particular application (over 500 mapping populations processed). DArT has developed map construction and consensus mapping software to deal with tens of thousands of markers in each map. For example wheat and brassica consensus maps have already over 100,000 DArTseq markers.
Accelerated Introgression from Wild Germplasm
Most cultivated crops suffer from limited genetic diversity due to intense selection pressures during domestication and variety development process. DArTseq was applied in a large number of crops to introgress genome segments with valuable alleles into adopted backgrounds. Wheat, sorghum, barley and practically all legume crops are those most routinely improved genetically using wild relatives and DArTseq platform.
DNA methylation-based epigenetic changes can be detected and analysed with Silico DArTseq markers. These markers have been used to identify and characterize novel plant varieties arising as ‘sports’ from existing cultivars. It is particularly useful to breeders of vegetatively propagated horticultural species, as apples and industrial crops like oil palm.
The largest volume of our projects is deployed in Genomic Selection of many plant species. DArTseq produces genome profiles of any density required for specific type of material (low and high LD) and breeding strategy. A number of algorithms for GS were integrated with imputation algorithms and data visualization methods as KDCompute pipelines.
QTL and Association Mapping (GWAS)
DArT has developed methods of linking phenotypes with marker profiles using Statistical Machine Learning approaches in combination with more traditional statistical methods. This technology has been applied to a large number of plants for a variety of qualitative and quantitative traits. DArT offers GWAS statistical analysis (and other downstream data processing) either free of charge or for a small additional fee.
Gene Tagging and Cloning
Using our Quantitative Bulk Segregant Analysis/distribution tail genotyping approach, we are able to identify a large number of tightly linked markers to a target gene; even land within a gene given sufficient number of gamete equivalents and 100% accurate phenotyping is available. This approach has been successfully used to target disease resistance in pineapple, color determination in custard apples and leaf necrosis in maize.
Genetic ID (quality assurance and PBR protection)
DArTseq has been used to comprehensively characterize a large reference set of Australian and international wheat, barley and maize varieties. DArTseq genetic ID methods enable the rapid and cost effective identification of crops. The platform has been applied to wheat and maize varieties grown in Ethiopia and several tropical plants from Africa (cassava, rice, sweet potato, maize).