Cytorhabdovirus phosphoprotein shows RNA silencing suppressor activity in plants, but not in insect cells

RNA silencing in plants and insects provides an antiviral defense and as a countermeasure most viruses encode RNA silencing suppressors (RSS). For the family Rhabdoviridae, no detailed functional RSS studies have been reported in plant hosts and insect vectors. In agroinfiltrated Nicotiana benthamiana leaves we show for the first time for a cytorhabdovirus, lettuce necrotic yellows virus (LNYV), that one of the nucleocapsid core proteins, phosphoprotein (P) has relatively weak local RSS activity and delays systemic silencing of a GFP reporter. Analysis of GFP small RNAs indicated that the P protein did not prevent siRNA accumulation. To explore RSS activity in insects, we used a Flock House virus replicon system in Drosophila S2 cells. In contrast to the plant host, LNYV P protein did not exhibit RSS activity in the insect cells. Taken together our results suggest that P protein may target plant-specific components of RNA silencing post siRNA biogenesis.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Estimating winter crop area across seasons and regions using time-sequential MODIS imagery.

The wheat grain industry is Australia's second largest agricultural export commodity. There is an increasing demand for accurate, objective and near real-time crop production information by industry. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to capture reflectance over large areas at acceptable pixel scale, cost and accuracy. The use of multi-temporal MODIS-enhanced vegetation index (EVI) imagery to determine crop area was investigated in this article. Here the rigour of the harmonic analysis of time-series (HANTS) and early-season metric approaches was assessed when extrapolating over the entire Queensland (QLD) cropping region for the 2005 and 2006 seasons. Early-season crop area estimates, at least 4 months before harvest, produced high accuracy at pixel and regional scales with percent errors of -8.6% and -26% for the 2005 and 2006 seasons, respectively. In discriminating among crops at pixel and regional scale, the HANTS approach showed high accuracy. The errors for specific area estimates for wheat, barley and chickpea were 9.9%, -5.2% and 10.9% (for 2005) and -2.8%, -78% and 64% (for 2006), respectively. Area estimates of total winter crop, wheat, barley and chickpea resulted in coefficient of determination (R(2)) values of 0.92, 0.89, 0.82 and 0.52, when contrasted against the actual shire-scale data. A significantly high coefficient of determination (0.87) was achieved for total winter crop area estimates in August across all shires for the 2006 season. Furthermore, the HANTS approach showed high accuracy in discriminating cropping area from non-cropping area and highlighted the need for accurate and up-to-date land use maps. The extrapolability of these approaches to determine total and specific winter crop area estimates, well before flowering, showed good utility across larger areas and seasons. Hence, it is envisaged that this technology might be transferable to different regions across Australia.

First complete genome sequence of a capsicum chlorosis tospovirus isolate from Australia with an unusually large S RNA intergenic region

The first complete genome sequence of capsicum chlorosis virus (CaCV) from Australia was determined using a combination of Illumina HiSeq RNA and Sanger sequencing technologies. Australian CaCV had a tripartite genome structure like other CaCV isolates. The large (L) RNA was 8913 nucleotides (nt) in length and contained a single open reading frame (ORF) of 8634 nt encoding a predicted RNA-dependent RNA polymerase (RdRp) in the viral-complementary (vc) sense. The medium (M) and small (S) RNA segments were 4846 and 3944 nt in length, respectively, each containing two non-overlapping ORFs in ambisense orientation, separated by intergenic regions (IGR). The M segment contained ORFs encoding the predicted non-structural movement protein (NSm; 927 nt) and precursor of glycoproteins (GP; 3366 nt) in the viral sense (v) and vc strand, respectively, separated by a 449-nt IGR. The S segment coded for the predicted nucleocapsid (N) protein (828 nt) and non-structural suppressor of silencing protein (NSs; 1320 nt) in the vc and v strand, respectively. The S RNA contained an IGR of 1663 nt, being the largest IGR of all CaCV isolates sequenced so far. Comparison of the Australian CaCV genome with complete CaCV genome sequences from other geographic regions showed highest sequence identity with a Taiwanese isolate. Genome sequence comparisons and phylogeny of all available CaCV isolates provided evidence for at least two highly diverged groups of CaCV isolates that may warrant re-classification of AIT-Thailand and CP-China isolates as unique tospoviruses, separate from CaCV.

Identification of I-7 expands the repertoire of genes for resistance to Fusarium wilt in tomato to three resistance gene classes

The tomato I-3 and I-7 genes confer resistance to Fusarium oxysporum f. sp. lycopersici (Fol) race 3 and were introgressed into the cultivated tomato, Solanum lycopersicum, from the wild relative Solanum pennellii. I-3 has been identified previously on chromosome 7 and encodes an S-receptor-like kinase, but little is known about I-7. Molecular markers have been developed for the marker-assisted breeding of I-3, but none are available for I-7. We used an RNA-seq and single nucleotide polymorphism (SNP) analysis approach to map I-7 to a small introgression of S. pennellii DNA (c. 210 kb) on chromosome 8, and identified I-7 as a gene encoding a leucine-rich repeat receptor-like protein (LRR-RLP), thereby expanding the repertoire of resistance protein classes conferring resistance to Fol. Using an eds1 mutant of tomato, we showed that I-7, like many other LRR-RLPs conferring pathogen resistance in tomato, is EDS1 (Enhanced Disease Susceptibility 1) dependent. Using transgenic tomato plants carrying only the I-7 gene for Fol resistance, we found that I-7 also confers resistance to Fol races 1 and 2. Given that Fol race 1 carries Avr1, resistance to Fol race 1 indicates that I-7-mediated resistance, unlike I-2- or I-3-mediated resistance, is not suppressed by Avr1. This suggests that Avr1 is not a general suppressor of Fol resistance in tomato, leading us to hypothesize that Avr1 may be acting against an EDS1-independent pathway for resistance activation. The identification of I-7 has allowed us to develop molecular markers for marker-assisted breeding of both genes currently known to confer Fol race 3 resistance (I-3 and I-7). Given that I-7-mediated resistance is not suppressed by Avr1, I-7 may be a useful addition to I-3 in the tomato breeder's toolbox.