138 resultados para genetic relationships
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Genetic and phenotypic parameters are presented for production traits, greasy fleece weight (GFW), yield (YLD), clean fleece weight (CFW), average fibre diameter (DIAM) and liveweight (LWT), in 15 month old medium Peppin Merino sheep at Longreach and Julia Creek, Queensland. Heritabilities for GFW, YLD, CFW, DIAM and LWT were respectively 0.35, 0.62, 0.34, 0.74, and 0.37 for Longreach and 0.23, 0.52, 0.20, 0.67 and 0.56 for Julia Creek. Most estimates were consistent with other reported values. AAABG 13th Conference; Proceedings of the Association for the Advancement of Animal Breeding and Genetics.
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Genetic and phenotypic parameters for respiration rate (RR) and rectal temperature (RT) are presented for weaner and hogget Merino rams, at Longreach and Julia Creek, Queensland. Heritability estimates for RT and RR at both sites and at both ages ranged from moderate to very high. Phenotypic and genetic correlations between these characters are also reported. AAABG 14th Conference; Proceedings of the Association for the Advancement of Animal Breeding and Genetics. AAABG
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Large variations in growth and feed conversion efficiency occur between cattle in feedlots. We aimed to test whether different behaviours of cattle may reflect some of these production differences.
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The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.
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Representational Difference Analysis (RDA) is an established technique used for isolation of specific genetic differences between or within bacterial species. This method was used to investigate the genetic basis of serovar-specificity and the relationship between serovar and virulence in Haemophilus parasuis. An RDA clone library of 96 isolates was constructed using H. parasuis strains H425(P) (serovar 12) and HS1967 (serovar 4). To screen such a large clone library to determine which clones are strain-specific would typically involved separately labelling each clone for use in Southern hybridisation against genomic DNA from each of the strains. In this study, a novel application of reverse Southern hybridisation was used to screen the RDA library: genomic DNA from each strain was labelled and used to probe the library to identify strain-specific clones. This novel approach represents a significant improvement in methodology that is rapid and efficient.
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The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.
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Seventy three isolates of Pythium aphanidermatum obtained from cucumber from four different regions of Oman and 16 isolates of muskmelon from the Batinah region in Oman were characterized for aggressiveness, sensitivity to metalaxyl and genetic diversity using AFLP fingerprinting. Twenty isolates of P. aphanidermatum from diverse hosts from different countries were also included in the study. Most isolates from Oman were found to be aggressive on cucumber seedlings and all were highly sensitive to metalaxyl (EC50 < 0•80 µg mL−1). Isolates from cucumber and muskmelon were as aggressive as each other on both hosts (P > 0.05), which implies a lack of host specialization in P. aphanidermatum on these two hosts in Oman. AFLP analysis of all isolates using four primer-pair combinations resolved 152 bands, of which 61 (~40%) were polymorphic. Isolates of P. aphanidermatum from Oman and other countries exhibited high genetic similarity (mean = 94.1%) and produced 59 different AFLP profiles. Analysis of molecular variance indicated that most AFLP variation among populations of P. aphanidermatum in Oman was associated with geographical regions (FST = 0.118; P < 0.0001), not hosts (FST = -0.004; P = 0.4323). These data were supported by the high rate of recovery (24%) of identical phenotypes between cucumber and muskmelon fields in the same region as compared to the low recovery (10%) across regions in Oman, which suggests more frequent movement of Pythium inoculum among muskmelon and cucumber fields in the same region compared to movement across geographically separated regions. However, recovering clones among regions and different countries may imply circulation of Pythium inoculum via common sources in Oman and also intercontinental spread of isolates.
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A total of 24 isolates of Pythium spinosum from cucumber obtained from five regions in Oman were characterized for genetic diversity using amplified fragment length polymorphism (AFLP) fingerprinting and three isolates from the Netherlands, South Africa and Japan were included for comparison. Isolates from Oman were also characterized for aggressiveness on cucumber seedlings and sensitivity to metalaxyl. Identity of all isolates was confirmed using sequences of the internal transcribed spacer (ITS) region of the ribosomal DNA (rDNA), which showed more than 99% nucleotide similarity among all isolates. Using six primer-pair combinations, AFLP fingerprinting resolved 295 AFLP markers of which 193 were polymorphic among isolates from other countries and only six were polymorphic among isolates of P. spinosum from Oman. Seven different AFLP phenotypes of P. spinosum were recovered in Oman; two of them were found to contain over 79% of isolates and one was recovered from all regions in Oman. Phenotypes from Oman showed very high (?99%) levels of genetic similarity to each other compared to moderate (mean =53%) levels of genetic similarity with phenotypes from other countries. In addition, all isolates from Oman were found to be highly sensitive to metalaxyl and all were aggressive on cucumber seedlings at 25°C. The high genetic similarity among phenotypes of P. spinosum in Oman as well as recovering two major clones across regions may suggest that P. spinosum has been recently introduced in Oman via a common source.
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Prediction of the initiation, appearance and emergence of leaves is critically important to the success of simulation models of crop canopy development and some aspects of crop ontogeny. Data on leaf number and crop ontogeny were collected on five cultivars of maize differing widely in maturity and genetic background grown under natural and extended photoperiods, and planted on seven sowing dates from October 1993 to March 1994 at Gatton, South-east Queensland. The same temperature coefficients were established for crop ontogeny before silking, and the rates of leaf initiation, leaf tip appearance and full leaf expansion, the base, optimum and maximum temperatures for each being 8, 34 and 40 degrees C. After silking, the base temperature for ontogeny was 0 degrees C, but the optimum and maximum temperatures remained unchanged. The rates of leaf initiation, appearance of leaf tips and full leaf expansion varied in a relatively narrow range across sowing times and photoperiod treatments, with average values of 0.040 leaves (degrees Cd)-1, 0.021 leaves (degrees Cd)-1, and 0.019 leaves (degrees Cd)-1, respectively. The relationships developed in this study provided satisfactory predictions of leaf number and crop ontogeny (tassel initiation to silking, emergence to silking and silking to physiological maturity) when assessed using independent data from Gatton (South eastern Queensland), Katherine and Douglas Daly (Northern Territory), Walkamin (North Queensland) and Kununurra (Western Australia).
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Grain samples from a combined intermediate and advanced stage barley breeding trial series, grown at two sites in two consecutive years were assessed for detailed grain quality and ruminant feed quality. The results indicated that there were significant genetic and environmental effects for “feed” traits as measured using grain hardness, acid detergent fibre (ADF), starch and in-sacco dry matter digestibility (ISDMD) assays. In addition, there was strong genotypic discrimination for the regressed feed performance traits, namely Net Energy (NE) and Average Daily Gain (ADG). There was considerable variation in genetic correlations for all traits based on variance from the cultivars used, sites or laboratory processing effects. There was a high level of heritability ranging from 89% to 88% for retention, 60% to 80% for protein and 56% to 68% for ADF. However, there were only low to moderate levels of heritability for the feed traits, with starch 30–39%, ISDMD 55–63%, ADF 56–68%, particle size 47–73%, 31–48% NE and ADG 44–51%. These results suggest that there were real differences in the feed performance of barleys and that selection for cattle feed quality is potentially a viable option for breeding programs.
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Barley hull plays an important role in malt and feed quality and processing. In this study we measured the variation in hull con-tent along with other grain quality traits namely, kernel discolouration and degree of pre-harvest sprouting, in a single map-ping population. There were significant (p < 0.05) genetic as well as environment effects. In addition, heritability was calculated for hull content to be 29% and 47% for two years’ data. From the analysis, major QTL markers were identified in con-trolling the expression of hull content on chromosomes 2 (2H), and 6 (6H) with significant (P < 0.05) LOD scores of 5.4 and 3.46 respectively. Minor QTLs were identified on 1 (7H), 4 (4H), 5 (1H) and 7 (5H). The region at marker Bmac310 on 4(4H) could be associated with dormancy gene SD4. A number of the QTLs also coincided with regions for either kernel discolouration or preharvest sprouting resistance (dormancy). The results indicate that variation exists for hull content, which is influenced by both growing environment as well as genetically, although the genetic variance explained less than half of the total variance. Further, hull content also impacts on other grain quality attributes including dormancy, sprouting resistance and kernel appearance.
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In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.
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Pineapple mealybug wilt-associated virus 1 (PMWaV-1), 2 (PMWaV-2) and -3 (PMWaV-3) have been detected in Australian commercial pineapple crops, along with a previously undescribed ampelovirus, for which the name Pineapple mealybug wilt-associated virus 5 (PMWaV-5) is proposed. Partial sequences extending from open reading frame 1b through to the heat shock protein homologue were obtained for PMWaV-1, -3 and -5. Phylogenetic analyses of selected regions of these sequences indicated that PMWaV-5 is a distinct species and most closely related to PMWaV-1. The amino acid sequence variation observed in the RNA-dependent RNA polymerase region of PMWaV-1 isolates was 95.8–98.4% and of PMWaV-3 isolates was 92.2–99.5%. In surveys of mealybug wilt disease (MWD) affected crops, none of the four viruses was clearly associated with the disease at all survey sites. A statistically significant association (P < 0.001) between the presence of PMWaV-2 and symptoms was observed at one survey site (site 3), but the virus was at a low incidence at the remaining three survey sites. By contrast, although PMWaV-1 and -3 were equally distributed between symptomless and MWD-affected plants at site 3, there was a statistically significant (P < 0.001) association between each of these two viruses and MWD at sites 1 and 4. At site 2, there was a statistically significant (P < 0.001) association only between PMWaV-3 and MWD. PMWaV-1 was the most commonly found of the four viruses and conversely PMWaV-5 was only occasionally found. Australian isolates of PMWaV-1, -2 and -3 were transmitted by the mealybug species Dysmicoccus brevipes.
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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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Background: Cultivated peanut or groundnut (Arachis hypogaea L.) is the fourth most important oilseed crop in the world, grown mainly in tropical, subtropical and warm temperate climates. Due to its origin through a single and recent polyploidization event, followed by successive selection during breeding efforts, cultivated groundnut has a limited genetic background. In such species, microsatellite or simple sequence repeat (SSR) markers are very informative and useful for breeding applications. The low level of polymorphism in cultivated germplasm, however, warrants a need of larger number of polymorphic microsatellite markers for cultivated groundnut. Results: A microsatellite- enriched library was constructed from the genotype TMV2. Sequencing of 720 putative SSR-positive clones from a total of 3,072 provided 490 SSRs. 71.2% of these SSRs were perfect type, 13.1% were imperfect and 15.7% were compound. Among these SSRs, the GT/CA repeat motifs were the most common (37.6%) followed by GA/CT repeat motifs (25.9%). The primer pairs could be designed for a total of 170 SSRs and were optimized initially on two genotypes. 104 (61.2%) primer pairs yielded scorable amplicon and 46 (44.2%) primers showed polymorphism among 32 cultivated groundnut genotypes. The polymorphic SSR markers detected 2 to 5 alleles with an average of 2.44 per locus. The polymorphic information content (PIC) value for these markers varied from 0.12 to 0.75 with an average of 0.46. Based on 112 alleles obtained by 46 markers, a phenogram was constructed to understand the relationships among the 32 genotypes. Majority of the genotypes representing subspecies hypogaea were grouped together in one cluster, while the genotypes belonging to subspecies fastigiata were grouped mainly under two clusters. Conclusion. Newly developed set of 104 markers extends the repertoire of SSR markers for cultivated groundnut. These markers showed a good level of PIC value in cultivated germplasm and therefore would be very useful for germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships in cultivated groundnut as well as related Arachis species.