Development of a New Zealand database of plant virus and virus-like organisms.

The recent 8th Australasian plant virology workshop in Rotorua, New Zealand, discussed the development of a New Zealand database of plant virus and virus-like organisms. Key points of discussion included: (i) the purpose of such a database; (ii) who would benefit from the information in a database; (iii) the scope of a database and its associated collections; (iv) database information and format; and (v) potential funding of such a database. From the workshop and further research, we conclude that the preservation and verification of specimens within the collections and the development of a New Zealand database of plant virus and virus-like organisms is essential. Such a collection will help to fulfil statutory requirements in New Zealand and assist in fulfilling international obligations under the International Plant Protection Convention. Sustaining such a database will assist New Zealand virologists and statutory bodies to undertake scientifically sound research. Establishing reliable records and an interactive database will help to ensure accurate and timely diagnoses of diseases caused by plant viruses and virus-like organisms. Detection of new incursions and their diagnosis will be further enhanced by the use of such reference collections and their associated database. Connecting and associating this information to similar overseas databases would assist international collaborations and allow access to the latest taxonomic and diagnostic resources. Associated scientists working in the areas of plant breeding, export phytosanitary assurance and in the area of the conservation estate would also benefit from access to verified specimens of plant viruses and virus-like organisms. We conclude that funding of a New Zealand database of virus and virus-like organisms and its associated collections should be based partly on Crown funds, as it is a nationally significant biological resource.

A genome-wide association study of tick burden and milk composition in cattle.

To study the genetic basis of tick burden and milk production and their interrelationship, we collected a sample of 1961 cattle with multiple tick counts from northern Australia of which 973 had dairy production data in the Australian Dairy Herd Information Service database. We calculated heritabilities, genetic and phenotypic correlations for these traits and showed a negative relationship between tick counts and milk and milk component yield. Tests of polymorphisms of four genes associated with milk yield, ABCG2, DGAT1, GHR and PRLR, showed no statistically significant effect on tick burden but highly significant associations to milk component yield in these data and we confirmed separate effects for GHR and PRLR on bovine chromosome 20. To begin to identify some of the molecular genetic bases for these traits, we genotyped a sample of 189 of these cattle for 7397 single nucleotide polymorphisms in a genome-wide association study. Although the allele effects for adjusted milk fat and protein yield were highly correlated (r = 0.66), the correlations of allele effects of these milk component yields and tick burden were small (|r| <= 0.10). These results agree in general with the phenotypic correlations between tick counts and milk component yield and suggest that selection on markers for tick burden or milk component yield may have no undesirable effect on the other trait.

CRC27012 A National Diagnostic Database for Emergency Plant Pests

Development of a national diagnostic database for Emergency Plant Pests which will be web-accessible.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

SorGSD: a sorghum genome SNP database

Sorghum (Sorghum bicolor) is one of the most important cereal crops globally and a potential energy plant for biofuel production. In order to explore genetic gain for a range of important quantitative traits, such as drought and heat tolerance, grain yield, stem sugar accumulation, and biomass production, via the use of molecular breeding and genomic selection strategies, knowledge of the available genetic variation and the underlying sequence polymorphisms, is required.