24 resultados para Non-inherited maternal alleles

em eResearch Archive - Queensland Department of Agriculture


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Postnatal myofibre characteristics and muscle mass are largely determined during fetal development and may be significantly affected by epigenetic parent-of-origin effects. However, data on such effects in prenatal muscle development that could help understand unexplained variation in postnatal muscle traits are lacking. In a bovine model we studied effects of distinct maternal and paternal genomes, fetal sex, and non-genetic maternal effects on fetal myofibre characteristics and muscle mass. Data from 73 fetuses (Day153, 54% term) of four genetic groups with purebred and reciprocal cross Angus and Brahman genetics were analyzed using general linear models. Parental genomes explained the greatest proportion of variation in myofibre size of Musculus semitendinosus (80-96%) and in absolute and relative weights of M. supraspinatus, M. longissimus dorsi, M. quadriceps femoris and M. semimembranosus (82-89% and 56-93%, respectively). Paternal genome in interaction with maternal genome (P<0.05) explained most genetic variation in cross sectional area (CSA) of fast myotubes (68%), while maternal genome alone explained most genetic variation in CSA of fast myofibres (93%, P<0.01). Furthermore, maternal genome independently (M. semimembranosus, 88%, P<0.0001) or in combination (M. supraspinatus, 82%; M. longissimus dorsi, 93%; M. quadriceps femoris, 86%) with nested maternal weight effect (5-6%, P<0.05), was the predominant source of variation for absolute muscle weights. Effects of paternal genome on muscle mass decreased from thoracic to pelvic limb and accounted for all (M. supraspinatus, 97%, P<0.0001) or most (M. longissimus dorsi, 69%, P<0.0001; M. quadriceps femoris, 54%, P<0.001) genetic variation in relative weights. An interaction between maternal and paternal genomes (P<0.01) and effects of maternal weight (P<0.05) on expression of H19, a master regulator of an imprinted gene network, and negative correlations between H19 expression and fetal muscle mass (P<0.001), suggested imprinted genes and miRNA interference as mechanisms for differential effects of maternal and paternal genomes on fetal muscle.

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The Brix content of pineapple fruit can be non-invasively predicted from the second derivative of near infrared reflectance spectra. Correlations obtained using a NIRSystems 6500 spectrophotometer through multiple linear regression and modified partial least squares analyses using a post-dispersive configuration were comparable with that from a pre-dispersive configuration in terms of accuracy (e.g. coefficient of determination, R2, 0.73; standard error of cross validation, SECV, 1.01°Brix). The effective depth of sample assessed was slightly greater using the post-dispersive technique (about 20 mm for pineapple fruit), as expected in relation to the higher incident light intensity, relative to the pre-dispersive configuration. The effect of such environmental variables as temperature, humidity and external light, and instrumental variables such as the number of scans averaged to form a spectrum, were considered with respect to the accuracy and precision of the measurement of absorbance at 876 nm, as a key term in the calibration for Brix, and predicted Brix. The application of post-dispersive near infrared technology to in-line assessment of intact fruit in a packing shed environment is discussed.

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The potential of near infra-red (NIR) spectroscopy for non-invasive measurement of fruit quality of pineapple (Ananas comosus var. Smooth Cayenne) and mango (Magnifera indica var. Kensington) fruit was assessed. A remote reflectance fibre optic probe, placed in contact with the fruit skin surface in a light-proof box, was used to deliver monochromatic light to the fruit, and to collect NIR reflectance spectra (760–2500 nm). The probe illuminated and collected reflected radiation from an area of about 16 cm2. The NIR spectral attributes were correlated with pineapple juice Brix and with mango flesh dry matter (DM) measured from fruit flesh directly underlying the scanned area. The highest correlations for both fruit were found using the second derivative of the spectra (d2 log 1/R) and an additive calibration equation. Multiple linear regression (MLR) on pineapple fruit spectra (n = 85) gave a calibration equation using d2 log 1/R at wavelengths of 866, 760, 1232 and 832 nm with a multiple coefficient of determination (R2) of 0.75, and a standard error of calibration (SEC) of 1.21 °Brix. Modified partial least squares (MPLS) regression analysis yielded a calibration equation with R2 = 0.91, SEC = 0.69, and a standard error of cross validation (SECV) of 1.09 oBrix. For mango, MLR gave a calibration equation using d2 log 1/R at 904, 872, 1660 and 1516 nm with R2 = 0.90, and SEC = 0.85% DM and a bias of 0.39. Using MPLS analysis, a calibration equation with R2 = 0.98, SEC = 0.54 and SECV = 1.19 was obtained. We conclude that NIR technology offers the potential to assess fruit sweetness in intact whole pineapple and DM in mango fruit, respectively, to within 1° Brix and 1% DM, and could be used for the grading of fruit in fruit packing sheds.

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The Queensland Shark Control Program (QSCP) aims to protect swimmers at ten beach areas on the east coast of Queensland between Cairns (17°S) and the Gold coast (28°S). Since its inception in 1962 it has deployed shark nets and baited drumlines in a `mixed gear strategy' that adapts the type of gear to the characteristics of a site (e .g . extreme tidal range, high energy wave action, or proximity of turtle breeding areas) . The policy has provided swimmer protection, and the incidental capture of non-target species has been lower than that resulting from deployment of nets alone (Dudley 1997; Gribble et al. 1998b). The QSCP is the only major public-safety shark-control program to routinely use mixed gear. Both the New South Wales (Holt 1998) and KwaZulu-Natal (Dudley 1998) programs use nets exclusively, although the KwaZulu-Natal program has recently tested drumlines on an experimental basis (Dudley 1998; Dudley, personal communication).

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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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Fusarium wilt of banana is a potentially devastating disease throughout the world. Options for control of the causal organism, Fusarium oxysporum f.sp. cubense (Foc) are limited. Suppressive soil sites have previously been identified where, despite the presence of Foc, Fusarium wilt does not develop. In order to understand some aspects of this disease suppression, endophytic Fusarium oxysporum isolates were obtained from banana roots. These isolates were genetically characterized and compared with an isolate of Fusarium oxysporum previously identified as being capable of suppressing Fusarium wilt of banana in glasshouse trials. Three additional isolates were selected for glasshouse trials to assess suppression of Fusarium wilt in two different cultivars of banana, Cavendish and Lady Finger. One isolate (BRIP 29089) was identified as a potential biocontrol organism, reducing the disease severity of Fusarium wilt in Lady Finger and Cavendish cultivars. Interestingly, one isolate (BRIP 45952) increased Fusarium wilt disease severity on Cavendish. The implications of an isolate of Fusarium oxysporum, non-pathogenic on banana, increasing disease severity and the potential role of non-pathogenic isolates of Fusarium oxysporum in disease complexes are discussed.

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A previously published partial sequence of pineapple bacilliform virus was shown to be from a retrotransposon (family Metaviridae) and not from a badnavirus as previously thought. Two newly discovered sequence groups isolated from pineapple were associated with bacilliform virions and were transmitted by mealybugs. Phylogenetic analyses indicated that they were members of new badnavirus species. A third caulimovirid sequence was also amplified from pineapple, but available evidence suggests that this DNA is not encapsidated, but more likely derived from an endogenous virus.

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This study compares estimates of the census size of the spawning population with genetic estimates of effective current and long-term population size for an abundant and commercially important marine invertebrate, the brown tiger prawn (Penaeus esculentus). Our aim was to focus on the relationship between genetic effective and census size that may provide a source of information for viability analyses of naturally occurring populations. Samples were taken in 2001, 2002 and 2003 from a population on the east coast of Australia and temporal allelic variation was measured at eight polymorphic microsatellite loci. Moments-based and maximum-likelihood estimates of current genetic effective population size ranged from 797 to 1304. The mean long-term genetic effective population size was 9968. Although small for a large population, the effective population size estimates were above the threshold where genetic diversity is lost at neutral alleles through drift or inbreeding. Simulation studies correctly predicted that under these experimental conditions the genetic estimates would have non-infinite upper confidence limits and revealed they might be overestimates of the true size. We also show that estimates of mortality and variance in family size may be derived from data on average fecundity, current genetic effective and census spawning population size, assuming effective population size is equivalent to the number of breeders. This work confirms that it is feasible to obtain accurate estimates of current genetic effective population size for abundant Type III species using existing genetic marker technology.

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1. Mammalian predators are controlled by poison baiting in many parts of the world, often to alleviate their impacts on agriculture or the environment. Although predator control can have substantial benefits, the poisons used may also be potentially harmful to other wildlife. 2. Impacts on non-target species must be minimized, but can be difficult to predict or quantify. Species and individuals vary in their sensitivity to toxins and their propensity to consume poison baits, while populations vary in their resilience. Wildlife populations can accrue benefits from predator control, which outweigh the occasional deaths of non-target animals. We review recent advances in Australia, providing a framework for assessing non-target effects of poisoning operations and for developing techniques to minimize such effects. We also emphasize that weak or circumstantial evidence of non-target effects can be misleading. 3. Weak evidence that poison baiting presents a potential risk to non-target species comes from measuring the sensitivity of species to the toxin in the laboratory. More convincing evidence may be obtained by quantifying susceptibility in the field. This requires detailed information on the propensity of animals to locate and consume poison baits, as well as the likelihood of mortality if baits are consumed. Still stronger evidence may be obtained if predator baiting causes non-target mortality in the field (with toxin detected by post-mortem examination). Conclusive proof of a negative impact on populations of non-target species can be obtained only if any observed non-target mortality is followed by sustained reductions in population density. 4. Such proof is difficult to obtain and the possibility of a population-level impact cannot be reliably confirmed or dismissed without rigorous trials. In the absence of conclusive evidence, wildlife managers should adopt a precautionary approach which seeks to minimize potential risk to non-target individuals, while clarifying population-level effects through continued research.

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Leaf carbon (C) content, leaf nitrogen (N) content, and C:N ratio are especially useful for understanding plant-herbivore interactions and may be important in developing control methods for the invasive riparian plant Arundo donax L. We measured C content, N content, C:N ratio, and chlorophyll index (SPAD 502 reading) for 768 leaves from A. donax collected over a five year period at several locations in California, Nevada, and Texas. Leaf N was more variable than leaf C, and thus we developed a linear regression equation for estimating A. donax leaf N from the leaf chlorophyll index (SPAD reading). When applied to two independent data sets, the equation (leaf N content % = -0.63 + 0.08 x SPAD) produced realistic estimates that matched seasonal and spatial trends reported from a natural A. donax population. Used in conjunction with the handheld SPAD 502 meter, the equation provides a rapid, non-destructive method for estimating A. donax leaf quality.

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Bovine herpesvirus 1 (BoHV-1) is an economically important pathogen of cattle associated with respiratory and reproductive disease. To further develop BoHV-1 as a vaccine vector, a study was conducted to identify the essential and non-essential genes required for in vitro viability. Randominsertion mutagenesis utilizing a Tn5 transposition system and targeted gene deletion were employed to construct gene disruption and gene deletion libraries, respectively, of an infectious clone of BoHV-1. Transposon insertion position and confirmation of gene deletion were determined by direct sequencing. The essential or non-essential requirement of either transposed or deleted open reading frames (ORFs) was assessed by transfection of respective BoHV-1 DNA into host cells. Of the 73 recognized ORFs encoded by the BoHV-1 genome, 33 were determined to be essential and 36 to be non-essential for virus viability in cell culture; determining the requirement of the two dual copy ORFs was inconclusive. The majority of ORFs were shown to conform to the in vitro requirements of BoHV-1 homologues encoded by human herpesvirus 1 (HHV-1). However, ORFs encoding glycoprotein K (UL53), regulatory, membrane, tegument and capsid proteins (UL54, UL49.5, UL49, UL35, UL20, UL16 and UL7) were shown to differ in requirement when compared to HHV-1-encoded homologues.

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Aconophora compressa (Hemiptera: Membracidae), a biological control agent introduced against the weed Lantana camara (Verbenaceae) in Australia, has since been observed on several non-target plant species, including native mangrove Avicennia marina (Acanthaceae). In this study we evaluated the suitability of two native mangroves, A. marina and Aegiceras corniculatum (Myrsinaceae), for the survival and development of A. compressa through no-choice field cage studies. The longevity of females was significantly higher on L. camara (57.7 ± 3.8 days) than on A. marina (43.3 ± 3.3 days) and A. corniculatum (45.7 ± 3.8 days). The proportion of females laying eggs was highest on L. camara (72%) followed by A. marina (36%) and A. corniculatum (17%). More egg batches per female were laid on L. camara than on A. marina and A. corniculatum. Though more nymphs per shoot emerged on L. camara (29.9 ± 2.8) than on A. marina (13 ± 4.8) and A. corniculatum (10 ± 5.3), the number of nymphs that developed through to adults was not significantly different. The duration of nymphal development was longer on A. marina (67 ± 5.8 days) than on L. camara (48 ± 4 days) and A. corniculatum (43 ± 4.6 days). The results, which are in contrast to those from previous glasshouse and quarantine trials, provide evidence that A. compressa adults can survive, lay eggs and complete nymphal development on the two non-target native mangroves in the field under no-choice condition.

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Identification of major contributors to odour annoyance in areas with multiple emission sources is necessary to address and resolve odour disputes. In an effort to develop an appropriate tool for this task, odour samples were collected on-site at a piggery and an abattoir (the major odour sources in the area) and at surrounding off-site areas, then analysed using a commercial non-specific chemical sensor array to develop an odour fingerprint database. The developed odour fingerprint database was analysed using two pattern recognition algorithms including a partial least squares-discriminant analysis (PLS-DA) and a Kohonen self-organising map (KSOM). The KSOM model could identify odour samples sourced from the piggery shed 15, piggery pond 8, piggery pond 9, abattoir, motel and others with mean percentage values of 77.5, 65.0, 90.2, 75.7, 44.8 and 64.6%, respectively.

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A commercial non-specific gas sensor array system was evaluated in terms of its capability to monitor the odour abatement performance of a biofiltration system developed for treating emissions from a commercial piggery building. The biofiltration system was a modular system comprising an inlet ducting system, humidifier and closed-bed biofilter. It also included a gravimetric moisture monitoring and water application system for precise control of moisture content of an organic woodchip medium. Principal component analysis (PCA) of the sensor array measurements indicated that the biofilter outlet air was significantly different to both inlet air of the system and post-humidifier air. Data pre-processing techniques including normalising and outlier handling were applied to improve the odour discrimination performance of the non-specific gas sensor array. To develop an odour quantification model using the sensor array responses of the non-specific sensor array, PCA regression, artificial neural network (ANN) and partial least squares (PLS) modelling techniques were applied. The correlation coefficient (r(2)) values of the PCA, ANN, and PLS models were 0.44, 0.62 and 0.79, respectively.

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Grass (monocots) and non-grass (dicots) proportions in ruminant diets are important nutritionally because the non-grasses are usually higher in nutritive value, particularly protein, than the grasses, especially in tropical pastures. For ruminants grazing tropical pastures where the grasses are C-4 species and most non-grasses are C-3 species, the ratio of C-13/C-12 in diet and faeces, measured as delta C-13 parts per thousand, is proportional to dietary non-grass%. This paper describes the development of a faecal near infrared (NIR) spectroscopy calibration equation for predicting faecal delta C-13 from which dietary grass and non-grass proportions can be calculated. Calibration development used cattle faeces derived from diets containing only C-3 non-grass and C-4 grass components, and a series of expansion and validation steps was employed to develop robustness and predictive reliability. The final calibration equation contained 1637 samples and faecal delta C-13 range (parts per thousand) of [12.27]-[27.65]. Calibration statistics were: standard error of calibration (SEC) of 0.78, standard error of cross-validation (SECV) of 0.80, standard deviation (SD) of reference values of 3.11 and R-2 of 0.94. Validation statistics for the final calibration equation applied to 60 samples were: standard error of prediction (SEP) of 0.87, bias of -0.15, R-2 of 0.92 and RPD of 3.16. The calibration equation was also tested on faeces from diets containing C-4 non-grass species or temperate C-3 grass species. Faecal delta C-13 predictions indicated that the spectral basis of the calibration was not related to C-13/C-12 ratios per se but to consistent differences between grasses and non-grasses in chemical composition and that the differences were modified by photosynthetic pathway. Thus, although the calibration equation could not be used to make valid faecal delta C-13 predictions when the diet contained either C-3 grass or C-4 non-grass, it could be used to make useful estimates of dietary non-grass proportions. It could also be ut :sed to make useful estimates of non-grass in mixed C-3 grass/non-grass diets by applying a modified formula to calculate non-grass from predicted faecal delta C-13. The development of a robust faecal-NIR calibration equation for estimating non-grass proportions in the diets of grazing cattle demonstrated a novel and useful application of NIR spectroscopy in agriculture.