Viruses of banana in East Africa

Bananas are one of the world's most important food crops, providing sustenance and income for millions of people in developing countries and supporting large export industries. Viruses are considered major constraints to banana production, germplasm multiplication and exchange, and to genetic improvement of banana through traditional breeding. In Africa, the two most important virus diseases are bunchy top, caused by Banana bunchy top virus (BBTV), and banana streak disease, caused by Banana streak virus (BSV). BBTV is a serious production constraint in a number of countries within/bordering East Africa, such as Burundi, Democratic Republic of Congo, Malawi, Mozambique, Rwanda and Zambia, but is not present in Kenya, Tanzania and Uganda. Additionally, epidemics of banana streak disease are occurring in Kenya and Uganda. The rapidly growing tissue culture (TC) industry within East Africa, aiming to provide planting material to banana farmers, has stimulated discussion about the need for virus indexing to certify planting material as virus-free. Diagnostic methods for BBTV and BSV have been reported and, for BBTV, PCR-based assays are reliable and relatively straightforward. However for BSV, high levels of serological and genetic variability and the presence of endogenous virus sequences within the banana genome complicate diagnosis. Uganda has been shown to contain the greatest diversity in BSV isolates found anywhere in the world. A broad-spectrum diagnostic test for BSV detection, which can discriminate between endogenous and episomal BSV sequences, is a priority. This PhD project aimed to establish diagnostic methods for banana viruses, with a particular focus on the development of novel methods for BSV detection, and to use these diagnostic methods for the detection and characterisation of banana viruses in East Africa. A novel rolling-circle amplification (RCA) method was developed for the detection of BSV. Using samples of Banana streak MY virus (BSMYV) and Banana streak OL virus (BSOLV) from Australia, this method was shown to distinguish between endogenous and episomal BSV sequences in banana plants. The RCA assay was used to screen a collection of 56 banana samples from south-west Uganda for BSV. RCA detected at least five distinct BSV isolates in these samples, including BSOLV and Banana streak GF virus (BSGFV) as well as three BSV isolates (Banana streak Uganda-I, -L and -M virus) for which only partial sequences had been previously reported. These latter three BSV had only been detected using immuno-capture (IC)-PCR and thus were possible endogenous sequences. In addition to its ability to detect BSV, the RCA protocol was also demonstrated to detect other viruses within the family Caulimoviridae, including Sugar cane bacilliform virus, and Cauliflower mosaic virus. Using the novel RCA method, three distinct BSV isolates from both Kenya and Uganda were identified and characterised. The complete genome of these isolates was sequenced and annotated. All six isolates were shown to have a characteristic badnavirus genome organisation with three open reading frames (ORFs) and the large polyprotein encoded by ORF 3 was shown to contain conserved amino acid motifs for movement, aspartic protease, reverse transcriptase and ribonuclease H activities. As well, several sequences important for expression and replication of the virus genome were identified including the conserved tRNAmet primer binding site present in the intergenic region of all badnaviruses. Based on the International Committee on Taxonomy of Viruses (ICTV) guidelines for species demarcation in the genus Badnavirus, these six isolates were proposed as distinct species, and named Banana streak UA virus (BSUAV), Banana streak UI virus (BSUIV), Banana streak UL virus (BSULV), Banana streak UM virus (BSUMV), Banana streak CA virus (BSCAV) and Banana streak IM virus (BSIMV). Using PCR with species-specific primers designed to each isolate, a genotypically diverse collection of 12 virus-free banana cultivars were tested for the presence of endogenous sequences. For five of the BSV no amplification was observed in any cultivar tested, while for BSIMV, four positive samples were identified in cultivars with a B-genome component. During field visits to Kenya, Tanzania and Uganda, 143 samples were collected and assayed for BSV. PCR using nine sets of species-specific primers, and RCA, were compared for BSV detection. For five BSV species with no known endogenous counterpart (namely BSCAV, BSUAV, BSUIV, BSULV and BSUMV), PCR was used to detect 30 infections from the 143 samples. Using RCA, 96.4% of these samples were considered positive, with one additional sample detected using RCA which was not positive using PCR. For these five BSV, PCR and RCA were both useful for identifying infected samples, irrespective of the host cultivar genotype (Musa A- or B-genome components). For four additional BSV with known endogenous counterparts in the M. balbisiana genome (BSOLV, BSGFV, BSMYV and BSIMV), PCR was shown to detect 75 infections from the 143 samples. In 30 samples from cultivars with an A-only genome component there was 96.3% agreement between PCR positive samples and detection using RCA, again demonstrating either PCR or RCA are suitable methods for detection. However, in 45 samples from cultivars with some B-genome component, the level of agreement between PCR positive samples and RCA positive samples was 70.5%. This suggests that, in cultivars with some B-genome component, many infections were detected using PCR which were the result of amplification of endogenous sequences. In these latter cases, RCA or another method which discriminates between endogenous and episomal sequences, such as immuno-capture PCR, is needed to diagnose episomal BSV infection. Field visits were made to Malawi and Rwanda to collect local isolates of BBTV for validation of a PCR-based diagnostic assay. The presence of BBTV in samples of bananas with bunchy top disease was confirmed in 28 out of 39 samples from Malawi and all nine samples collected in Rwanda, using PCR and RCA. For three isolates, one from Malawi and two from Rwanda, the complete nucleotide sequences were determined and shown to have a similar genome organisation to previously published BBTV isolates. The two isolates from Rwanda had at least 98.1% nucleotide sequence identity between each of the six DNA components, while the similarity between isolates from Rwanda and Malawi was between 96.2% and 99.4% depending on the DNA component. At the amino acid level, similarities in the putative proteins encoded by DNA-R, -S, -M, - C and -N were found to range between 98.8% to 100%. In a phylogenetic analysis, the three East African isolates clustered together within the South Pacific subgroup of BBTV isolates. Nucleotide sequence comparison to isolates of BBTV from outside Africa identified India as the possible origin of East African isolates of BBTV.

The Lake of the Cemetery

This is brief paper written in the "here and now" as the event happened and describes the early morning journey of the author by balsa wood raft to the breeding colony of greater flamingoes (Phoenicopterus ruber) on the island of Isabela in the Galapagos archipelago in 1976. Isabela comprises five volcanoes in a north south alignment. The Lake of the Cemetary is close to the site of a former penal colony which is now the only village on the island. The ethological observations at the bird colony are discussed.

One-year delayed effect of fog on malaria transmission : a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.

A unique isolate of beak and feather disease virus isolated from budgerigars (Melopsittacus undulatus) in South Africa

Beak and feather disease virus (BFDV), the causative agent of psittacine beak and feather disease (PBFD) infects psittaciformes worldwide. We provide an annotated sequence record of three full-length unique genomes of BFDV isolates from budgerigars (Melopsittacus undulatus) from a breeding farm in South Africa. The isolates share >99% nucleotide sequence identity with each other and ~96% nucleotide sequence identity to two recent isolates (Melopsittacus undulatus) from Thailand but only between 91. 6 and 86. 6% identity with all other full-length BFDV sequences. Maximum-likelihood analysis and recombination analysis suggest that the South African budgerigar BFDV isolates are unique to budgerigars, are non-recombinant in origin, and represent a new genotype of BFDV. © 2010 Springer-Verlag.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Narrative : family trauma or challenge and resilience in the Galapagos Archipelago

The chapter is a "here and now" narration in the first person as witnessed and experienced by the author during field work in the Galapagos Islands in 1976-79. The story begins on the most remote volcanic island of Fernandina where the breeding biology of Flightless cormorants was being studied. A small selection of the many potentially life threatening situations and challenges is described including stories related to the birth of their son.

Comprehensive evaluation of DNA barcoding for the molecular species identification of forensically important Australian Sarcophagidae (Diptera)

Carrion-breeding Sarcophagidae (Diptera) can be used to estimate the post-mortem interval (PMI) in forensic cases. Difficulties with accurate morphological identifications at any life stage and a lack of documented thermobiological profiles have limited their current usefulness of these flies. The molecular-based approach of DNA barcoding, which utilises a 648-bp fragment of the mitochondrial cytochrome oxidase subunit I gene, was previously evaluated in a pilot study for the discrimination between 16 Australian sarcophagids. The current study comprehensively evaluated DNA barcoding on a larger taxon set of 588 adult Australian sarcophagids. A total of 39 of the 84 known Australian species were represented by 580 specimens, which includes 92% of potentially forensically important species. A further eight specimens could not be reliably identified, but included as six unidentifable taxa. A neighbour-joining phylogenetic tree was generated and nucleotide sequence divergences were calculated using the Kimura-two-parameter distance model. All species except Sarcophaga (Fergusonimyia) bancroftorum, known for high morphological variability, were resolved as reciprocally monophyletic (99.2% of cases), with most having bootstrap support of 100. Excluding S. bancroftorum, the mean intraspecific and interspecific variation ranged from 0.00-1.12% and 2.81-11.23%, respectively, allowing for species discrimination. DNA barcoding was therefore validated as a suitable method for the molecular identification of the Australian Sarcophagidae, which will aid in the implementation of this fauna in forensic entomology.

The complete mitochondrial genome of the flesh fly, Sarcophaga impatiens Walker (Diptera: Sarcophagidae)

Approximately 2500 fly species comprise the Sarcophagidae family worldwide. The complete mitochondrial genome of the carrion-breeding, forensically important Sarcophaga impatiens Walker (Diptera: Sarcophagidae) from Australia was sequenced. The 15,169 bp circular genome contains the 37 genes found in a typical Metazoan genome: 13 protein-coding genes, 2 ribosomal RNA genes and 22 transfer RNA genes. It also contains one non-coding A+T-rich region. The arrangement of the genes was the same as that found in the ancestral insect. All the protein initiation codons are ATN, except for cox1 that begins with TCG (encoding S). The 22 tRNA anticodons of S. impatiens are consistent with those observed in Drosophila yakuba, and all form the typical cloverleaf structure, except for tRNA-Ser(AGN) that lacks the DHU arm. The mitochondrial genome of Sarcophaga presented will be valuable for resolving phylogenetic relationships within the family Sarcophagidae and the order Diptera, and could be used to identify favourable genetic markers for species identifications for forensic purposes.

Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates

Background: A random QTL effects model uses a function of probabilities that two alleles in the same or in different animals at a particular genomic position are identical by descent (IBD). Estimates of such IBD probabilities and therefore, modeling and estimating QTL variances, depend on marker polymorphism, strength of linkage and linkage disequilibrium of markers and QTL, and the relatedness of animals in the pedigree. The effect of relatedness of animals in a pedigree on IBD probabilities and their characteristics was examined in a simulation study. Results: The study based on nine multi-generational family structures, similar to a pedigree structure of a real dairy population, distinguished by an increased level of inbreeding from zero to 28 % across the studied population. Highest inbreeding level in the pedigree, connected with highest relatedness, was accompanied by highest IBD probabilities of two alleles at the same locus, and by lower relative variation coefficients. Profiles of correlation coefficients of IBD probabilities along the marked chromosomal segment with those at the true QTL position were steepest when the inbreeding coefficient in the pedigree was highest. Precision of estimated QTL location increased with increasing inbreeding and pedigree relatedness. A method to assess the optimum level of inbreeding for QTL detection is proposed, depending on population parameters. Conclusions: An increased overall relationship in a QTL mapping design has positive effects on precision of QTL position estimates. But the relationship of inbreeding level and the capacity for QTL detection depending on the recombination rate of QTL and adjacent informative marker is not linear. © 2010 Freyer et al., licensee BioMed Central Ltd.

Wetlands, climate zones and Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia, but the linkages of the wetlands and climate zones with BFV transmission remain unclear. We aimed to examine the relationship between the wetlands, climate zones and BFV risk in Queensland, Australia. Data on the wetlands, climate zones, population and BFV cases for the period 1992 to 2008 were obtained from relevant government agencies. BFV risk was grouped as low-, medium- and high-level based on BFV incidence percentiles. The buffer zones around each BFV case were made using 1, 5, 10, 15, 20, 25 and 50 km distances. We performed a discriminant analysis to determine the differences between wetland classes and BFV risk within each climate zone. The discriminant analyses show that saline 1, riverine and saline tidal influence were the most significant contributors to BFV risk in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. These models had classification accuracies of 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV risk varies with wetland class and climate zone. The discriminant analysis is a useful tool to quantify the links between wetlands, climate zones and BFV risk.

Mapping quantitative trait loci in a wild population using linkage and linkage disequilibrium analyses

Historical information can be used, in addition to pedigree, traits and genotypes, to map quantitative trait locus (QTL) in general populations via maximum likelihood estimation of variance components. This analysis is known as linkage disequilibrium (LD) and linkage mapping, because it exploits both linkage in families and LD at the population level. The search for QTL in the wild population of Soay sheep on St. Kilda is a proof of principle. We analysed the data from a previous study and confirmed some of the QTLs reported. The most striking result was the confirmation of a QTL affecting birth weight that had been reported using association tests but not when using linkage-based analyses. Copyright © Cambridge University Press 2010.

Mapping of multiple quantitative trait loci affecting bovine spongiform encephalopathy

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y ps) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches.

On the prediction of simultaneous inbreeding coefficients at multiple loci

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.