Development and Application of Droplet Digital PCR Tools for the Detection of Transgenes in Pastures and Pasture-Based Products

Implementation of molecular biotechnology, such as transgenic technologies, in forage species can improve agricultural profitability through achievement of higher productivity, better use of resources such as soil nutrients, water, or light, and reduced environmental impact. Development of detection and quantification techniques for genetically modified plants are necessary to comply with traceability and labeling requirements prior to regulatory approval for release. Real-time PCR has been the standard method used for detection and quantification of genetically modified events, and droplet digital PCR is a recent alternative technology that offers a higher accuracy. Evaluation of both technologies was performed using a transgenic high-energy forage grass as a case study. Two methods for detection and quantification of the transgenic cassette, containing modified fructan biosynthesis genes, and a selectable marker gene, hygromycin B phosphotransferase used for transformation, were developed. Real-time PCR was assessed using two detection techniques, SYBR Green I and fluorescent probe-based methods. A range of different agricultural commodities were tested including fresh leaves, tillers, seeds, pollen, silage and hay, simulating a broad range of processed agricultural commodities that are relevant in the commercial use of genetically modified pastures. The real-time and droplet digital PCR methods were able to detect both exogenous constructs in all agricultural products. However, a higher sensitivity and repeatability in transgene detection was observed with the droplet digital PCR technology. Taking these results more broadly, it can be concluded that the droplet digital PCR technology provides the necessary resolution for quantitative analysis and detection, allowing absolute quantification of the target sequence at the required limits of detection across all jurisdictions globally. The information presented here provides guidance and resources for pasture-based biotechnology applications that are required to comply with traceability requirements

Comparison of homoeolocus organisation in paired BAC clones from white clover (Trifolium repens L.) and microcolinearity with model legume species

<p>Abstract</p> <p>Background</p> <p>White clover (<it>Trifolium repens </it>L.) is an outbreeding allotetraploid species and an important forage legume in temperate grassland agriculture. Comparison of sub-genome architecture and study of nucleotide sequence diversity within allopolyploids provides insight into evolutionary divergence mechanisms, and is also necessary for the development of whole-genome sequencing strategies. This study aimed to evaluate the degree of divergence between the O and P' sub-genomes of white clover through sequencing of BAC clones containing paired homoeoloci. The microsyntenic relationships between the genomes of white clover and the model legumes <it>Lotus japonicus </it>and <it>Medicago truncatula </it>as well as <it>Arabidopsis thaliana </it>were also characterised.</p> <p>Results</p> <p>A total of four paired homoeologous BACs were selected and sequenced to generate 173 kb of overlapping sequence between the O and P' sub-genomes. Equivalent gene content was generally observed, apart from small-scale deletions, in contrast to conservation of intergenic sequences, which varied between the four selected regions. Measurement of the number of synonymous substitutions between homoeologous genes led to estimation of a 4.2 million year divergence time between the two sub-genomes. Microsynteny was observed between the genomes of white clover and <it>L. japonicus </it>for all four targeted regions, but corresponding <it>M. truncatula </it>genomic regions were only identified for two BAC pairs.</p> <p>Conclusions</p> <p>This study describes the first analysis of sub-genome structural conservation across selected genomic regions in white clover. Although the high levels of sequence conservation between the O and P' sub-genomes would complicate efforts for whole genome sequence assembly, the conserved microsynteny with model legume genomes, especially that of <it>L. japonicus</it>, will be highly valuable for the future of white clover genomics and molecular breeding.</p

New Computational Tools for Brassica Genome Research

With the increasing quantities of Brassica genomic data being entered into the public domain and in preparation for the complete Brassica genome sequencing effort, there is a growing requirement for the structuring and detailed bioinformatic analysis of Brassica genomic information within a user-friendly database. At the Plant Biotechnology Centre, Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data, to aid its application to agricultural biotechnology research. These tools include a sequence database, ASTRA, a sequence processing pipeline incorporating annotation against GenBank, SwissProt and Arabidopsis Gene Ontology (GO) data and tools for molecular marker discovery and comparative genome analysis. All sequences are mined for simple sequence repeat (SSR) molecular markers using ‘SSR primer’ and mapped onto the complete Arabidopsis thaliana genome by sequence comparison. The database may be queried using a text-based search of sequence annotation or GO terms, BLAST comparison against resident sequences, or by the position of candidate orthologues within the Arabidopsis genome. Tools have also been developed and applied to the discovery of single nucleotide polymorphism (SNP) molecular markers and the in silico mapping of Brassica BAC end sequences onto the Arabidopsis genome. Planned extensions to this resource include the integration of gene expression data and the development of an EnsEMBL-based genome viewer

Brassica ASTRA: an integrated database for Brassica genomic research

Brassica ASTRA is a public database for genomic information on Brassica species. The database incorporates expressed sequences with Swiss-Prot and GenBank comparative sequence annotation as well as secondary Gene Ontology (GO) annotation derived from the comparison with Arabidopsis TAIR GO annotations. Simple sequence repeat molecular markers are identified within resident sequences and mapped onto the closely related Arabidopsis genome sequence. Bacterial artificial chromosome (BAC) end sequences derived from the Multinational Brassica Genome Project are also mapped onto the Arabidopsis genome sequence enabling users to identify candidate Brassica BACs corresponding to syntenic regions of Arabidopsis. This information is maintained in a MySQL database with a web interface providing the primary means of interrogation. The database is accessible at http://hornbill.cspp.latrobe.edu.au

Molecular characterisation and genetic mapping of candidate genes for qualitative disease resistance in perennial ryegrass (Lolium perenne L.)

<p>Abstract</p> <p>Background</p> <p>Qualitative pathogen resistance in both dicotyledenous and monocotyledonous plants has been attributed to the action of resistance (R) genes, including those encoding nucleotide binding site – leucine rich repeat (NBS-LRR) proteins and receptor-like kinase enzymes. This study describes the large-scale isolation and characterisation of candidate R genes from perennial ryegrass. The analysis was based on the availability of an expressed sequence tag (EST) resource and a functionally-integrated bioinformatics database.</p> <p>Results</p> <p>Amplification of R gene sequences was performed using template EST data and information from orthologous candidate using a degenerate consensus PCR approach. A total of 102 unique partial R genes were cloned, sequenced and functionally annotated. Analysis of motif structure and R gene phylogeny demonstrated that <it>Lolium </it>R genes cluster with putative ortholoci, and evolved from common ancestral origins. Single nucleotide polymorphisms (SNPs) predicted through resequencing of amplicons from the parental genotypes of a genetic mapping family were validated, and 26 distinct R gene loci were assigned to multiple genetic maps. Clusters of largely non-related NBS-LRR genes were located at multiple distinct genomic locations and were commonly found in close proximity to previously mapped defence response (DR) genes. A comparative genomics analysis revealed the co-location of several candidate R genes with disease resistance quantitative trait loci (QTLs).</p> <p>Conclusion</p> <p>This study is the most comprehensive analysis to date of qualitative disease resistance candidate genes in perennial ryegrass. SNPs identified within candidate genes provide a valuable resource for mapping in various ryegrass pair cross-derived populations and further germplasm analysis using association genetics. In parallel with the use of specific pathogen virulence races, such resources provide the means to identify gene-for-gene mechanisms for multiple host pathogen-interactions and ultimately to obtain durable field-based resistance.</p

SSRPrimer and SSR Taxonomy Tree: Biome SSR discovery

Simple sequence repeat (SSR) molecular genetic markers have become important tools for a broad range of applications such as genome mapping and genetic diversity studies. SSRs are readily identified within DNA sequence data and PCR primers can be designed for their amplification. These PCR primers frequently cross amplify within related species. We report a web-based tool, SSR Primer, that integrates SPUTNIK, an SSR repeat finder, with Primer3, a primer design program, within one pipeline. On submission of multiple FASTA formatted sequences, the script screens each sequence for SSRs using SPUTNIK. Results are then parsed to Primer3 for locus specific primer design. We have applied this tool for the discovery of SSRs within the complete GenBank database, and have designed PCR amplification primers for over 13 million SSRs. The SSR Taxonomy Tree server provides web-based searching and browsing of species and taxa for the visualisation and download of these SSR amplification primers. These tools are available at

SNPServer: a real-time SNP discovery tool

SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at