A Mutant \u3cem\u3edec-1\u3c/em\u3e Transgene Induces Dominant Female Sterility in \u3cem\u3eDrosophila melanogaster\u3c/em\u3e

The Drosophila dec-1 gene produces three proproteins required for female fertility and eggshell assembly. The three proproteins are distinguished by their C termini. Fc106, the most abundant proprotein, is cleaved within the vitelline membrane to three mature derivatives in a developmentally regulated manner. To define sequences within fc106 that are critical for its function, we created wild-type and mutant versions of an fc106 cDNA transgene. The functional consequences of the mutations were assessed in dec-14, a female-sterile splicing mutant that does not produce the fc106 isoform. The fertility of dec-14 females was restored by the introduction of either a wild-type transgene or a transgene bearing a C-terminal deletion that included fc106-specific sequences. Surprisingly, the removal of internal coding sequences created an aberrant DEC-1 proprotein that induced female sterility when introduced into wild-type flies. Dominant female sterility was not associated with larger deletions that included the fc106 N terminus, suggesting that abnormal juxtaposition of N- and C-terminal sequences in the aberrant proprotein interfered with endogenous DEC-1 proteins. Changes in the fractionation behavior of the endogenous fc106 C-terminal derivative, s60, and morphological changes in the endochorion in response to expression of the aberrant proprotein support this interpretation

Transgenesis and Genomics in Molecular Breeding of Forage Plants

Forage plant breeding has been largely based on phenotypic selection following sexual recombination of natural genetic variation found between and within ecotypes. Advances in plant genetic manipulation over the last 15 years have provided convincing evidence that these powerful technologies can complement and enhance plant breeding programs. Significant progress in the establishment of the methodologies required for the molecular breeding of forage plants has been made. Examples of current products and approaches for the application of these methodologies to forage grass and legume improvement are outlined. Large-scale genomic analysis of many organisms is under way with human, arabidopsis and rice genome sequences almost completed. Forage plant breeding is just now entering the genome era. The plethora of new technologies and tools now available for high-throughput gene discovery and genome-wide gene expression analysis have opened up opportunities for innovative applications in the identification, functional characterisation and use of genes of value in forage production systems and beyond. Examples of these opportunities, such as ‘molecular phenotyping’, ‘symbio-genomics’ and ‘xeno-genomics’ are introduced

Scenario Analysis: Risk and Return of Aluminium Tolerant Lucerne

Lucerne (Medicago sativa) yield is limited by aluminium stress associated with acid soils (Campbell et al. 1988; Scott et al. 2008). With the aid of transgenic technologies, the development of aluminium tolerant (Al Tol) lucerne is proposed. Modelled scenario analysis was conducted to explore the potential net benefits of Al Tol lucerne as part of a grazing system for a sheep production system in the high rainfall zone of south west Victoria

Development and Field Evaluation of Transgenic Ryegrass (\u3ci\u3eLolium\u3c/i\u3e Spp.) with Down-Regulation of Main Pollen Allergens

Ryegrass (Lolium spp.) pollen is a widespread source of airborne allergens and is a major cause of hayfever and seasonal allergic asthma, which affect approximately 25% of the population in cool temperate climates. The main allergens of ryegrass pollen are the proteins Lol p 1 and Lol p 2. These proteins belong to two major classes of grass pollen allergens to which over 90% of pollen-allergic patients are sensitive. The functional role in planta of these pollen allergen proteins remains largely unknown. The generation, analysis and field evaluation of transgenic plants with reduced levels of the main ryegrass pollen allergens, Lol p 1 and Lol p 2 in the most important worldwide cultivated ryegrass species, perennial ryegrass (L. perenne L.) and Italian ryegrass (L. multiflorum Lam.) are described

Orally active antischistosomal early leads identified from the open access malaria box.

BACKGROUND: Worldwide hundreds of millions of schistosomiasis patients rely on treatment with a single drug, praziquantel. Therapeutic limitations and the threat of praziquantel resistance underline the need to discover and develop next generation drugs. METHODOLOGY: We studied the antischistosomal properties of the Medicines for Malaria Venture (MMV) malaria box containing 200 diverse drug-like and 200 probe-like compounds with confirmed in vitro activity against Plasmodium falciparum. Compounds were tested against schistosomula and adult Schistosoma mansoni in vitro. Based on in vitro performance, available pharmacokinetic profiles and toxicity data, selected compounds were investigated in vivo. PRINCIPAL FINDINGS: Promising antischistosomal activity (IC50: 1.4-9.5 µM) was observed for 34 compounds against schistosomula. Three compounds presented IC50 values between 0.8 and 1.3 µM against adult S. mansoni. Two promising early leads were identified, namely a N,N'-diarylurea and a 2,3-dianilinoquinoxaline. Treatment of S. mansoni infected mice with a single oral 400 mg/kg dose of these drugs resulted in significant worm burden reductions of 52.5% and 40.8%, respectively. CONCLUSIONS/SIGNIFICANCE: The two candidates identified by investigating the MMV malaria box are characterized by good pharmacokinetic profiles, low cytotoxic potential and easy chemistry and therefore offer an excellent starting point for antischistosomal drug discovery and development

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points

A Comparison of Satellite-Based Multilayered Cloud Detection Methods

Both techniques show skill in detecting multilayered clouds, but they disagree more than 50% of the time. BTD method tends to detect more ML clouds than CO2 method and has slightly higher detection accuracy. CO2 method might be better for minimizing false positives, but further study is needed. Neither method as been optimized for GOES data. BTD technique developed on AVHRR, better BTD signals & resolution. CO2 developed on MODIS, better resolution & 4 CO2 channels. Many additional comparisons with ARSCL data will be used to optimize both techniques. A combined technique will be examined using MODIS & Meteosat-8 data. After optimization, the techniques will be implemented in the ARM operational satellite cloud processing

Ryegrass ASTRA: a Web-Based Resource for \u3cem\u3eLolium\u3c/em\u3e EST Analysis

Perennial ryegrass (Lolium perenne L.) is a major grass species of temperate pastoral agriculture

Gene Discovery and Molecular Dissection of Lignin Biosynthesis in Perennial Ryegrass (Lolium Perenne)

Lignification of plant cell walls has been identified as a major factor limiting forage digestibility. It limits the amount of digestible energy available to livestock, resulting in an incomplete utilisation of cellulose and hemicellulose by ruminant animals. Modification of the lignin profile of ryegrasses (Lolium spp.) and fescues (Festuca spp.) is undertaken through modulating the expression of genes encoding enzymes involved in the biosynthesis of monolignols

Metabolome Analysis of the Interaction Between Perennial Ryegrass (\u3cem\u3eLolium Perenne\u3c/em\u3e) and the Fungal Endophyte \u3cem\u3eNeotyphodium Lolii\u3c/em\u3e

Perennial ryegrass (Lolium perenne L.) and tall fescue (Festuca arundinacea Schreb.) frequently contain endophytic fungi (Neotyphodium lolii in perennial ryegrass and N. coenophialum in tall fescue). The presence of the endophyte has been shown to improve seedling vigour, persistence and drought tolerance in marginal environments as well as provide protection against some insect pests. Endophyte-infected grasses also produce a wide range of metabolites, including ergopeptine alkaloids, indole-isoprenoid lolitrems, pyrrolizidine alkaloids, and pyrrolopyrazine alkaloids. In contrast to information on alkaloids and animal toxicosis, the beneficial physiological aspects of the endophyte/grass interactions have not been well characterised. The physiological mechanisms which lead to increased plant vigour and enhanced tolerance to abiotic stresses unrelated to the reduction in pest damage to endophyte-infected grasses are unknown. Recent technological advances in metabolomics enable dynamic changes in the metabolome of an organism under varying experimental conditions to be studied. This provides opportunities for the investigation and validation of each and every detected metabolite, investigation of known metabolic pathways through searching of databases of known metabolites, molecular formula determination of unknown metabolites and creation of pathways from novel metabolites