Estimating the duration and cost of weed eradication programmes

Two prerequisites for realistically embarking upon an eradication programme are that cost-benefit analysis favours this strategy over other management options and that sufficient resources are available to carry the programme through to completion. These are not independent criteria, but it is our view that too little attention has been paid to estimating the investment required to complete weed eradication programmes. We deal with this problem by using a two-pronged approach: 1) developing a stochastic dynamic model that provides an estimation of programme duration; and 2) estimating the inputs required to delimit a weed incursion and to prevent weed reproduction over a sufficiently long period to allow extirpation of all infestations. The model is built upon relationships that capture the time-related detection of new infested areas, rates of progression of infestations from the active to the monitoring stage, rates of reversion of infestations from the monitoring to active stage, and the frequency distribution of time since last detection for all infestations. This approach is applied to the branched broomrape (Orobanche ramosa) eradication programme currently underway in South Australia. This programme commenced in 1999 and currently 7450 ha are known to be infested with the weed. To date none of the infestations have been eradicated. Given recent (2008) levels of investment and current eradication methods, model predictions are that it would take, on average, an additional 73 years to eradicate this weed at an average additional cost (NPV) of $AU67.9m. When the model was run for circumstances in 2003 and 2006, the average programme duration and total cost (NPV) were predicted to be 159 and 94 years, and $AU91.3m and $AU72.3m, respectively. The reduction in estimated programme length and cost may represent progress towards the eradication objective, although eradication of this species still remains a long term prospect.

Rapid genome wide mapping of phosphine resistance loci by a simple regional averaging analysis in the red flour beetle, Tribolium castaneum

Background Next-generation sequencing technology is an important tool for the rapid, genome-wide identification of genetic variations. However, it is difficult to resolve the ‘signal’ of variations of interest and the ‘noise’ of stochastic sequencing and bioinformatic errors in the large datasets that are generated. We report a simple approach to identify regional linkage to a trait that requires only two pools of DNA to be sequenced from progeny of a defined genetic cross (i.e. bulk segregant analysis) at low coverage (<10×) and without parentage assignment of individual SNPs. The analysis relies on regional averaging of pooled SNP frequencies to rapidly scan polymorphisms across the genome for differential regional homozygosity, which is then displayed graphically. Results Progeny from defined genetic crosses of Tribolium castaneum (F4 and F19) segregating for the phosphine resistance trait were exposed to phosphine to select for the resistance trait while the remainders were left unexposed. Next generation sequencing was then carried out on the genomic DNA from each pool of selected and unselected insects from each generation. The reads were mapped against the annotated T. castaneum genome from NCBI (v3.0) and analysed for SNP variations. Since it is difficult to accurately call individual SNP frequencies when the depth of sequence coverage is low, variant frequencies were averaged across larger regions. Results from regional SNP frequency averaging identified two loci, tc_rph1 on chromosome 8 and tc_rph2 on chromosome 9, which together are responsible for high level resistance. Identification of the two loci was possible with only 5-7× average coverage of the genome per dataset. These loci were subsequently confirmed by direct SNP marker analysis and fine-scale mapping. Individually, homozygosity of tc_rph1 or tc_rph2 results in only weak resistance to phosphine (estimated at up to 1.5-2.5× and 3-5× respectively), whereas in combination they interact synergistically to provide a high-level resistance >200×. The tc_rph2 resistance allele resulted in a significant fitness cost relative to the wild type allele in unselected beetles over eighteen generations. Conclusion We have validated the technique of linkage mapping by low-coverage sequencing of progeny from a simple genetic cross. The approach relied on regional averaging of SNP frequencies and was used to successfully identify candidate gene loci for phosphine resistance in T. castaneum. This is a relatively simple and rapid approach to identifying genomic regions associated with traits in defined genetic crosses that does not require any specialised statistical analysis.