The global distribution of Banana bunchy top virus reveals little evidence for frequent recent, human-mediated long distance dispersal events

Banana bunchy top virus (BBTV; family Nanoviridae, genus Babuvirus) is a multi-component single-stranded DNA virus, which infects banana plants in many regions of the world, often resulting in large-scale crop losses. Weanalyzed 171 banana leaf samples from fourteen countries and recovered, cloned, and sequenced 855 complete BBTV components including ninety-four full genomes. Importantly, full genomes were determined from eight countries, where previously no full genomes were available (Samoa, Burundi, Republic of Congo, Democratic Republic of Congo, Egypt, Indonesia, the Philippines, and the USA [HI]). Accounting for recombination and genome component reassortment, we examined the geographic structuring of global BBTV populations to reveal that BBTV likely originated in Southeast Asia, that the current global hotspots of BBTV diversity are Southeast Asia/Far East and India, and that BBTV populations circulating elsewhere in the world have all potentially originated from infrequent introductions. Most importantly, we find that rather than the current global BBTV distribution being due to increases in human-mediated movements of bananas over the past few decades, it is more consistent with a pattern of infrequent introductions of the virus to different parts of the world over the past 1,000 years.

Distribution and characterization of Poleroviruses affecting food legumes in Central/West Asia and North Africa (CWANA) region and Australia

During the past 15 years, surveys to identify virus diseases affecting cool-season food legume crops in Australia and 11 CWANA countries (Algeria, China, Egypt, Ethiopia, Lebanon, Morocco, Sudan, Syria, Tunisia, Uzbekistan and Yemen) were conducted. More than 20,000 samples were collected and tested for the presence of 14 legume viruses by the tissue-blot immunoassay (TBIA) using a battery of antibodies, including the following Luteovirus monoclonal antibodies (McAbs): a broad-spectrum legume Luteovirus (5G4), BLRV, BWYV, SbDV and CpCSV. A total of 195 Luteovirus samples were selected for further testing by RT-PCR using 7 primers (one is degenerate, and can detect a wide range of Luteoviridae virus species and the other six are species-specific primers) at the Virology Laboratory, QDAF, Australia, during 2014. A total of 145 DNA fragments (represented 105 isolates) were sequenced. The following viruses were characterized based on molecular analysis: BLRV from Lebanon, Morocco, Tunisia and Uzbekistan; SbDV from Australia, Syria and Uzbekistan; BWYV from Algeria, China, Ethiopia, Lebanon, Morocco, Sudan, Tunisia and Uzbekistan; CABYV from Algeria, Lebanon, Syria, Sudan and Uzbekistan; CpCSV from Algeria, Ethiopia, Lebanon, Morocco, Syria and Tunisia, and unknown Luteoviridae species from Algeria, Ethiopia, Morocco, Sudan, Uzbekistan and Yemen. This study has clearly shown that there are a number of Polerovirus species, in addition to BWYV, all can produce yellowing/stunting symptoms in pulses (e.g. CABYV, CpCSV, and other unknown Polerovirus species). Based on our knowledge this is the first report of CABYV affecting food legumes. Moreover, there was about 95% agreement between results obtained from serological analysis (TBIA) and molecular analysis for the detection of BLRV and SbDV. Whereas, TBIA results were not accurate when using CpCSV and BWYV McAbs . It seems that the McAbs for CpCSV and BWYV used in this study and those available worldwide, are not virus species specific. Both antibodies, reacted with other Polerovirus species (e.g. CABYV, and unknown Polerovirus). This highlights the need for more accurate characterization of existing antibodies and where necessary the development of better, virus-specific antibodies to enable their use for accurate diagnosis of Poleroviruses.

‘How to’ guide for measuring fan performance and efficiency in meat chicken sheds

This ‘how to’ guide provides readers with method to measure fan performance and energy efficiency of fans installed in meat chicken sheds. These methods are also useful for identifying fans that are under-performing or require maintenance. For more information about fan energy efficiency, a complementary report is available on the RIRDC website ‘Review of fan efficiency in meat chicken sheds’ (RIRDC Publication No. 15/018). A spreadsheet was also developed under this project for comparing and ranking fans against others in terms of energy efficiency, air flow and costs (‘Tunnel Ventilation Fan Comparison Spreadsheet’), and is available on the RIRDC website.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.