9 resultados para 4-component gaussian basis sets
em eResearch Archive - Queensland Department of Agriculture
Resumo:
Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.
Resumo:
Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.
Resumo:
Compared to grain sorghums, sweet sorghums typically have lower grain yield and thick, tall stalks which accumulate high levels of sugar (sucrose, fructose and glucose). Unlike commercial grain sorghum (S. bicolor ssp. bicolor) cultivars, which are usually F1 hybrids, commercial sweet sorghums were selected as wild accessions or have undergone limited plant breeding. Although all sweet sorghums are classified within S. bicolor ssp. bicolor, their genetic relationship with grain sorghums is yet to be investigated. Ninety-five genotypes, including 31 sweet sorghums and 64 grain sorghums, representing all five races within the subspecies bicolor, were screened with 277 polymorphic amplified fragment length polymorphism (AFLP) markers. Cluster analysis separated older sweet sorghum accessions (collected in mid 1800s) from those developed and released during the early to mid 1900s. These groups were emphasised in a principle component analysis of the results such that sweet sorghum lines were largely distinguished from the others, particularly by a group of markers located on sorghum chromosomes SBI-08 and SBI-10. Other studies have shown that QTL and ESTs for sugar-related traits, as well as for height and anthesis, map to SBI-10. Although the clusters obtained did not group clearly on the basis of racial classification, the sweet sorghum lines often cluster with grain sorghums of similar racial origin thus suggesting that sweet sorghum is of polyphyletic origin within S. bicolor ssp. bicolor.
Resumo:
In parts of Australia, sorghum grain is a cheaper alternative to other cereal grains but its use and nutritive value in sheep feeding systems is not well understood. The aim of this work was to compare growth and carcass characteristics for crossbred lambs consuming several simple, sorghum-based diets. The treatments were: (1) whole sorghum grain, (2) whole sorghum grain + urea and ammonium sulfate, (3) cracked sorghum grain + urea and ammonium sulfate, (4) expanded sorghum grain + urea and ammonium sulfate, (5) whole sorghum grain + cottonseed meal, and (6) whole sorghum grain + whole cottonseed. Nine lambs were slaughtered initially to provide baseline carcass data and the remaining 339 lambs were gradually introduced to the concentrate diets over 14 days before being fed concentrates and wheaten hay ad libitum for 41, 56 or 76 days. Neither cracking nor expanding whole sorghum grain with added non-protein nitrogen (N) resulted in significantly (P > 0.05) increased final liveweight, growth rates or carcass weights for lambs, or in decreased days on feed to reach 18-kg carcass weight, although carcass fat depth was significantly (P < 0.05) increased compared with the whole sorghum plus non-protein N diet. However, expanding sorghum grain significantly (P < 0.05) reduced faecal starch concentrations compared with whole or cracked sorghum diets with added non-protein N (79 v. 189 g/kg DM after 59 days on feed). Lambs fed whole sorghum grain without an additional N source had significantly (P < 0.05) lower concentrate intake and required significantly (P < 0.05) more days on feed to reach a carcass weight of 18 kg than for all diets containing added N. These lambs also had significantly (P < 0.05) lower carcass weight and fat depth than for lambs consuming whole sorghum plus true protein diets. Substituting sources of true protein (cottonseed meal and whole cottonseed) for non-protein N (urea and ammonium sulfate) did not significantly (P > 0.05) affect concentrate intakes or carcass weights of lambs although carcass fat depth was significantly (P < 0.05) increased and the days to reach 18-kg carcass weight were significantly (P < 0.05) decreased for the whole sorghum plus cottonseed meal diet. In conclusion, processing sorghum grain by cracking or expanding did not significantly improve lamb performance. While providing an additional N source with sorghum grain significantly increased lamb performance, there was no benefit in final carcass weight of lambs from substituting sources of true protein for non-protein N.
Resumo:
To study the genetic basis of tick burden and milk production and their interrelationship, we collected a sample of 1961 cattle with multiple tick counts from northern Australia of which 973 had dairy production data in the Australian Dairy Herd Information Service database. We calculated heritabilities, genetic and phenotypic correlations for these traits and showed a negative relationship between tick counts and milk and milk component yield. Tests of polymorphisms of four genes associated with milk yield, ABCG2, DGAT1, GHR and PRLR, showed no statistically significant effect on tick burden but highly significant associations to milk component yield in these data and we confirmed separate effects for GHR and PRLR on bovine chromosome 20. To begin to identify some of the molecular genetic bases for these traits, we genotyped a sample of 189 of these cattle for 7397 single nucleotide polymorphisms in a genome-wide association study. Although the allele effects for adjusted milk fat and protein yield were highly correlated (r = 0.66), the correlations of allele effects of these milk component yields and tick burden were small (|r| <= 0.10). These results agree in general with the phenotypic correlations between tick counts and milk component yield and suggest that selection on markers for tick burden or milk component yield may have no undesirable effect on the other trait.
Resumo:
The Juvenile Wood Initiative (JWI) project has been running successfully since July 2003 under a Research Agreement with FWPA and Letters of Association with the consortium partners STBA (Southern Tree Breeding Association), ArborGen and FPQ (Forestry Plantations Queensland). Over the last five and half years, JWI scientists in CSIRO, FPQ, and STBA have completed all 12 major milestones and 28 component milestones according to the project schedule. We have made benchmark progress in understanding the genetic control of wood formation and interrelationships among wood traits. The project has made 15 primary scientific findings and several results have been adopted by industry as summarized below. This progress was detailed in 10 technical reports to funding organizations and industry clients. Team scientists produced 16 scientific manuscripts (8 published, 1 in press, 2 submitted, and several others in the process of submission) and 15 conference papers or presentations. Primary Scientific Findings. The 15 major scientific findings related to wood science, inheritance and the genetic basis of juvenile wood traits are: 1. An optimal method to predict stiffness of standing trees in slash/Caribbean pine is to combine gravimetric basic density from 12 mm increment cores with a standing tree prediction of MoE using a time of flight acoustic tool. This was the most accurate and cheapest way to rank trees for breeding selection for slash/Caribbean hybrid pine. This method was also recommended for radiata pine. 2. Wood density breeding values were predicted for the first time in the STBA breeding population using a large sample of 7,078 trees (increment cores) and it was estimated that selection of the best 250 trees for deployment will produce wood density gains of 12.4%. 3. Large genetic variation for a suite of wood quality traits including density, MFA, spiral grain, shrinkage, acoustic and non-acoustic stiffness (MoE) for clear wood and standing trees were observed. Genetic gains of between 8 and 49% were predicted for these wood quality traits with selection intensity between 1 to 10% for radiata pine. 4. Site had a major effect on juvenile-mature wood transition age and the effect of selective breeding for a shorter juvenile wood formation phase was only moderate (about 10% genetic gain with 10% selection intensity, equivalent to about 2 years reduction of juvenile wood). 5. The study found no usable site by genotype interactions for the wood quality traits of density, MFA and MoE for both radiata and slash/Caribbean pines, suggesting that assessment of wood properties on one or two sites will provide reliable estimates of the genetic worth of individuals for use in future breeding. 6. There were significant and sizable genotype by environment interactions between the mainland and Tasmanian regions and within Tasmania for DBH and branch size. 7. Strong genetic correlations between rings for density, MFA and MoE for both radiata and slash/Caribbean pines were observed. This suggests that selection for improved wood properties in the innermost rings would also result in improvement of wood properties in the subsequent rings, as well as improved average performance of the entire core. 8. Strong genetic correlations between pure species and hybrid performance for each of the wood quality traits were observed in the hybrid pines. Parental performance can be used to identify the hybrid families which are most likely to have superior juvenile wood properties of the slash/Caribbean F1 hybrid in southeast Queensland. 9. Large unfavourable genetic correlations between growth and wood quality traits were a prominent feature in radiata pine, indicating that overcoming this unfavourable genetic correlation will be a major technical issue in progressing radiata pine breeding. 10. The project created the first radiata pine 18 k cDNA microarray and generated 5,952 radiata pine xylogenesis expressed sequence tags (ESTs) which assembled into 3,304 unigenes. 11. A total of 348 genes were identified as preferentially expressed genes in earlywood or latewood while a total of 168 genes were identified as preferentially expressed genes in either juvenile or mature wood. 12. Juvenile earlywood has a distinct transcriptome relative to other stages of wood development. 13. Discovered rapid decay of linkage disequilibrium (LD) in radiata pine with LD decaying to approximately 50% within 1,700 base pairs (within a typical gene). A total of 913 SNPS from sequencing 177,380 base pairs were identified for association genetic studies. 14. 149 SNPs from 44 genes and 255 SNPs from a further 51 genes (total 95 genes) were selected for association analysis with 62 wood traits, and 30 SNPs were shortlisted for their significant association with variation of wood quality traits (density, MFA and MoE) with individual significant SNPs accounting for between 1.9 and 9.7% of the total genetic variation in traits. 15. Index selection using breeding objectives was the most profitable selection method for radiata pine, but in the long term it may not be the most effective in dealing with negative genetic correlations between wood volume and quality traits. A combination of economic and biological approaches may be needed to deal with the strong adverse correlation.
Resumo:
Age at puberty is an important component of reproductive performance in beef cattle production systems. Brahman cattle are typically late-pubertal relative to Bos taurus cattle and so it is of economic relevance to select for early age at puberty. To assist selection and elucidate the genes underlying puberty, we performed a genome-wide association study (GWAS) using the BovineSNP50 chip (similar to 54 000 polymorphisms) in Brahman bulls (n = 1105) and heifers (n = 843) and where the heifers were previously analysed in a different study. In a new attempt to generate unbiased estimates of single-nucleotide polymorphism (SNP) effects and proportion of variance explained by each SNP, the available data were halved on the basis of year and month of birth into a calibration and validation set. The traits that defined age at puberty were, in heifers, the age at which the first corpus luteum was detected (AGECL, h(2) = 0.56 +/- 0.11) and in bulls, the age at a scrotal circumference of 26 cm (AGE26, h(2) = 0.78 +/- 0.10). At puberty, heifers were on average older (751 +/- 142 days) than bulls (555 +/- 101 days), but AGECL and AGE26 were genetically correlated (r = 0.20 +/- 0.10). There were 134 SNPs associated with AGECL and 146 SNPs associated with AGE26 (P < 0.0001). From these SNPs, 32 (similar to 22%) were associated (P < 0.0001) with both traits. These top 32 SNPs were all located on Chromosome BTA 14, between 21.95 Mb and 28.4 Mb. These results suggest that the genes located in that region of BTA 14 play a role in pubertal development in Brahman cattle. There are many annotated genes underlying this region of BTA 14 and these are the subject of current research. Further, we identified a region on Chromosome X where markers were associated (P < 1.00E-8) with AGE26, but not with AGECL. Information about specific genes and markers add value to our understanding of puberty and potentially contribute to genomic selection. Therefore, identifying these genes contributing to genetic variation in AGECL and AGE26 can assist with the selection for early onset of puberty.
Resumo:
Targets for improvements in water quality entering the Great Barrier Reef (GBR) have been set through the Reef Water Quality Protection Plan (Reef Plan). To measure and report on progress towards the targets set a program has been established that combines monitoring and modelling at paddock through to catchment and reef scales; the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (Paddock to Reef Program). This program aims to provide evidence of links between land management activities, water quality and reef health. Five lines of evidence are used: the effectiveness of management practices to improve water quality; the prevalence of management practice adoption and change in catchment indicators; long-term monitoring of catchment water quality; paddock & catchment modelling to provide a relative assessment of progress towards meeting targets; and finally marine monitoring of GBR water quality and reef ecosystem health. This paper outlines the first four lines of evidence. (C) 2011 Elsevier Ltd. All rights reserved.