55 resultados para Rice -- Genetics

em eResearch Archive - Queensland Department of Agriculture


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Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.

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Submergence stress regularly affects 15 million hectares or more of rainfed lowland rice areas in South and Southeast Asia. A major QTL on chromosome 9, Sub1, has provided the opportunity to apply marker assisted backcrossing (MAB) to develop submergence tolerant versions of rice cultivars that are widely grown in the region. In the present study, molecular markers that were tightly linked with Sub1, flanking Sub1, and unlinked to Sub1 were used to apply foreground, recombinant, and background selection, respectively, in backcrosses between a submergence-tolerant donor and the widely grown recurrent parent Swarna. By the BC2F2 generation a submergence tolerant plant was identified that possessed Swarna type simple sequence repeat (SSR) alleles on all fragments analyzed except the tip segment of rice chromosome 9 that possessed the Sub1 locus. A BC3F2 double recombinant plant was identified that was homozygous for all Swarna type alleles except for an approximately 2.3-3.4 Mb region surrounding the Sub1 locus. The results showed that the mega variety Swarna could be efficiently converted to a submergence tolerant variety in three backcross generations, involving a time of two to three years. Polymorphic markers for foreground and recombinant selection were identified for four other mega varieties to develop a wider range of submergence tolerant varieties to meet the needs of farmers in the flood-prone regions. This approach demonstrates the effective use of marker assisted selection for a major QTL in a molecular breeding program.

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Spontaneous sequence changes and the selection of beneficial mutations are driving forces of gene diversification and key factors of evolution. In highly dynamic co-evolutionary processes such as plant-pathogen interactions, the plant's ability to rapidly adapt to newly emerging pathogens is paramount. The hexaploid wheat gene Lr34, which encodes an ATP-binding cassette (ABC) transporter, confers durable field resistance against four fungal diseases. Despite its extensive use in breeding and agriculture, no increase in virulence towards Lr34 has been described over the last century. The wheat genepool contains two predominant Lr34 alleles of which only one confers disease resistance. The two alleles, located on chromosome 7DS, differ by only two exon-polymorphisms. Putatively functional homoeologs and orthologs of Lr34 are found on the B-genome of wheat and in rice and sorghum, but not in maize, barley and Brachypodium. In this study we present a detailed haplotype analysis of homoeologous and orthologous Lr34 genes in genetically and geographically diverse selections of wheat, rice and sorghum accessions. We found that the resistant Lr34 haplotype is unique to the wheat D-genome and is not found in the B-genome of wheat or in rice and sorghum. Furthermore, we only found the susceptible Lr34 allele in a set of 252 Ae. tauschii genotypes, the progenitor of the wheat D-genome. These data provide compelling evidence that the Lr34 multi-pathogen resistance is the result of recent gene diversification occurring after the formation of hexaploid wheat about 8,000 years ago.

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Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

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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.

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Three indoor, sheeted bag-stack fumigations of paddy rice using aluminium phosphide were undertaken in Guangdong Province, southern China. We measured the effect of two types of sheeting (polyvinylchloride [PVC] or polyethylene [PE]) and two types of floor sealing (clips or fixing into a slot with a rubber pipe) on phosphine concentration and retention. The aim was to test the feasibility of retaining fumigant at a sufficient concentration for long enough to control known resistant insect pests. Each stack was pressure tested and phosphine concentrations measured daily during the fumigation. Cages of test insects in culture medium, including resistant and susceptible strains, were placed inside each stack and could be observed through the clear sheeting. Highest concentrations for the longest period were obtained in a PVC-covered stack that included a ground sheet and wall sheets sealed to the floor with rubber pipes. A similar PVC-covered stack sealed to the floor with clips instead of pipe did not retain gas as efficiently and required re-dosing. A PE-covered stack, with no ground sheet but also with wall sheets sealed to the floor with pipe, produced an acceptable fumigation. Susceptible Rhyzopertha dominica were controlled in 2 days and the most resistant strain in 15 days. Resistant Cryptolestes ferrugineus survived until day 21. The paddy was still free of insect infestation 7 months later when the bag-stack was opened to mill the rice. Pressure half-lives correlated with gas concentration and retention. Sorption appeared to be a major limiting factor, reducing potential fumigant dosage by about 50%. The trials demonstrated the feasibility of sealing bag-stacks to a standard high enough to control all known resistant strains.

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Using an established genetic map, a single gene conditioning covered smut resistance, Ruh.7H, was mapped to the telomere region of chromosome 7HS in an Alexis/Sloop doubled haploid barley population. The closest marker to Ruh.7H, abg704 was 7.5 cM away. Thirteen loci on the distal end of 7HS with potential to contain single nucleotide polymorphisms (SNPs) were identified by applying a comparative genomics approach using rice sequence data. Of these, one locus produced polymorphic co-dominant bands of different size while two further loci contained SNPs that were identified using the recently developed high resolution melting (HRM) technique. Two of these markers flanked Ruh.7H with the proximal marker located 3.8 cM and the distal marker 2.7 cM away. This is the first report on the application of the HRM technique to SNP detection and to rapid scoring of known cleaved amplified polymorphic sequence (CAPS) markers in plants. This simple, precise post-PCR technique should find widespread use in the fine-mapping of genetic regions of interest in complex cereal and other plant genomes.

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Global amphibian decline by chytridiomycosis is a major environmental disaster that has been attributed to either recent fungal spread or environmental change that promotes disease. Here, we present a population genetic comparison of Batrachochytrium dendrobatidis isolates from an intensively studied region of frog decline, the Sierra Nevada of California. In support of a novel pathogen, we find low diversity, no amphibian-host specificity, little correlation between fungal genotype and geography, local frog extirpation by a single fungal genotype, and evidence of human-assisted fungus migration. In support of endemism, at a local scale, we find some diverse, recombining populations. Therefore neither epidemic spread nor endemism alone explains this particular amphibian decline. Recombination raises the possibility of resistant sporangia and a mechanism for rapid spread as well as persistence that could greatly complicate global control of the pathogen.

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This paper is the first of a series that investigates whether new cropping systems with permanent raised beds (PRBs) or Flat land could be successfully used to increase farmers' incomes from rainfed crops in Lombok in Eastern Indonesia. This paper discusses the rice phase of the cropping system. Low grain yields of dry-seeded rice (Oryza sativa) grown on Flat land on Vertisols in the rainfed region of southern Lombok, Eastern Indonesia, are probably mainly due to (a) erratic rainfall (870-1220 mm/yr), with water often limiting at sensitive growth stages, (b) consistently high temperatures (average maximum - 31 C), and (c) low solar radiation. Farmers are therefore poor, and labour is hard and costly, as all operations are manual. Two replicated field experiments were run at Wakan (annual rainfall = 868 mm) and Kawo (1215 mm) for 3 years (2001/2002 to 2003/2004) on Vertisols in southern Lombok. Dry-seeded rice was grown in 4 treatments with or without manual tillage on (a) PRBs, 1.2 m wide, 200 mm high, separated by furrows 300 mm wide, 200 mill deep, with no rice sown in the well-graded furrows, and (b) well-graded Flat land. Excess surface water was harvested from each treatment and used for irrigation after the vegetative stage of the rice. All operations were manual. There were no differences between treatments in grain yield of rice (mean grain yield = 681 g/m(2)) which could be partly explained by total number of tillers/hill and mean panicle length, but not number of productive tillers/hill, plant height or weight of 1000 grains. When the data from both treatments on PRBs and from both treatments on Flat land, each year at each site were analysed, there were also no differences in grain yield of rice (g/m(2)). When rainfall in the wet season up to harvest was over 1000 mm (Year 2; Wakan, Kawo), or plants were water-stressed during crop establishment (Year 1; Wakan) or during grain-fill (Year 3: Kawo), there were significant differences in grain yield (g/1.5 m(2)) between treatments; generally the grain yield (g/1.5 m(2)) on PRBs with or without tillage was less than that on Flat land with or without tillage. However, when the data from both treatments on PRBs and from both treatments on Flat land, each year at each site, were analysed, the greater grain yield of dry-seeded rice on Flat land (mean yield 1 092 g/1.5 m(2)) than that on PRBs (mean 815 g/1.5 m(2)) was mainly because there were 25% more plants on Flat land. Overall when the data in the 2 outer rows and the 2 inner rows on PRBs were each combined, there was a higher number of productive tillers in the combined outer rows (mean 20.7 tillers/hill) compared with that in the combined inner rows on each PRB (mean 18.2 tillers/hill). However, there were no differences in grain yield between combined rows (mean 142 g/m row). Hence with a gap of 500 mm (the distance between the outer rows of plants on adjacent raised beds), plants did not compensate in grain yield for missing plants in furrows. This suggests that rice (a) also sown in furrows, or (b) sown in 7 rows with narrower row-spacing, or (c) sown in 6 rows with slightly wider row-spacing, and narrower gap between outer rows on adjacent beds, may further increase grain yield (g/1.5 m(2)) in this system of PRBs. The growth and the grain yield (y in g/m(2)) of rainfed rice (with rainfall on-site the only source of water for irrigation) depended mainly on the rainfall (x in mm) in the wet season up to harvest (due either to site or year) with y = 1. 1x -308; r(2) = 0.54; p < 0.005. However, 280 mm (i.e. 32%) of the rainfall was not directly used to produce grain (i.e. when y = 0 g/m(2)). Manual tillage did not affect growth and grain yield of rice (g/m(2); g/1.5 m(2)), either on PRB or on Flat land.

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The genetics of heifer performance in tropical 'wet' and 'dry' seasons, and relationships with steer performance, were studied in Brahman (BRAH) and Tropical Composite (TCOMP) (50% Bos indicus, African Sanga or other tropically adapted Bos taurus; 50% non-tropically adapted Bos taurus) cattle of northern Australia. Data were from 2159 heifers (1027 BRAH, 1132 TCOMP), representing 54 BRAH and 51 TCOMP sires. Heifers were assessed after post-weaning 'wet' (ENDWET) and 'dry' (ENDDRY) seasons. Steers were assessed post-weaning, at feedlot entry, over a 70-day feed test, and after similar to 120-day finishing. Measures studied in both heifers and steers were liveweight (LWT), scanned rump fat, rib fat and M. longissimus area (SEMA), body condition score (CS), hip height (HH), serum insulin-like growth factor-I concentration (IGF-I), and average daily gains (ADG). Additional steer measures were scanned intra-muscular fat%, flight time, and daily (DFI) and residual feed intake (RFI). Uni- and bivariate analyses were conducted for combined genotypes and for individual genotypes. Genotype means were predicted for a subset of data involving 34 BRAH and 26 TCOMP sires. A meta-analysis of genetic correlation estimates examined how these were related to the difference between measurement environments for specific traits. There were genotype differences at the level of means, variances and genetic correlations. BRAH heifers were significantly (P < 0.05) faster-growing in the 'wet' season, slower-growing in the 'dry' season, lighter at ENDDRY, and taller and fatter with greater CS and IGF-I at both ENDWET and ENDDRY. Heritabilities were generally in the 20 to 60% range for both genotypes. Phenotypic and genetic variances, and genetic correlations, were commonly lower for BRAH. Differences were often explained by the long period of tropical adaptation of B. indicus. Genetic correlations were high between corresponding measures at ENDWET and ENDDRY, positive between fat and muscle measures in TCOMP but negative in BRAH (mean of 13 estimates 0.50 and -0.19, respectively), and approximately zero between steer feedlot ADG and heifer ADG in BRAH. Numerous genetic correlations between heifers and steers differed substantially from unity, especially in BRAH, suggesting there may be scope to select differently in the sexes where that would aid the differing roles of heifers and steers in production. Genetic correlations declined as measurement environments became more different, the rates of decline (environment sensitivity) sometimes differing with genotype. Similar measures (LWT, HH and ADG; IGF-I at ENDWET in TCOMP) were genetically correlated with steer DFI in heifers as in steers. Heifer SEMA was genetically correlated with steer feedlot RFI in BRAH (0.75 +/- 0.27 at ENDWET, 0.66 +/- 0.24 at ENDDRY). Selection to reduce steer RFI would reduce SEMA in BRAH heifers but otherwise have only small effects on heifers before their first joining.

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A total of 2115 heifers from two tropical genotypes (1007 Brahman and 1108 Tropical Composite) raised in four locations in northern Australia were ovarian-scanned every 4-6 weeks to determine the age at the first-observed corpus luteum (CL) and this was used to de. ne the age at puberty for each heifer. Other traits recorded at each time of ovarian scanning were liveweight, fat depths and body condition score. Reproductive tract size was measured close to the start of the first joining period. Results showed significant effects of location and birth month on the age at first CL and associated puberty traits. Genotypes did not differ significantly for the age or weight at first CL; however, Brahman were fatter at first CL and had a small reproductive tract size compared with that of Tropical Composite. Genetic analyses estimated the age at first CL to be moderately to highly heritable for Brahman (0.57) and Tropical Composite (0.52). The associated traits were also moderately heritable, except for reproductive tract size in Brahmans (0.03) and for Tropical Composite, the presence of an observed CL on the scanning day closest to the start of joining (0.07). Genetic correlations among puberty traits were mostly moderate to high and generally larger in magnitude for Brahman than for Tropical Composite. Genetic correlations between the age at CL and heifer- and steer-production traits showed important genotype differences. For Tropical Composite, the age at CL was negatively correlated with the heifer growth rate in their first postweaning wet season (-0.40) and carcass marbling score (-0.49), but was positively correlated with carcass P8 fat depth (0.43). For Brahman, the age at CL was moderately negatively genetically correlated with heifer measures of bodyweight, fatness, body condition score and IGF-I, in both their first postweaning wet and second dry seasons, but was positively correlated with the dry-season growth rate. For Brahman, genetic correlations between the age at CL and steer traits showed possible antagonisms with feedlot residual feed intake (-0.60) and meat colour (0.73). Selection can be used to change the heifer age at puberty in both genotypes, with few major antagonisms with steer- and heifer- production traits.

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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.

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Background and Aims: The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. Methods: The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Key Results: Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. Conclusions: This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.

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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.

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Rice flower, an Australian native species, has been cultivated in appreciable quantities as a cut flower crop since 1991. Although the plant can be highly productive, achieving consistently high commercial yields can prove elusive. Rice Flower production guidelines for growers is essential reading for producers who would aspire to grow and market rice flower well. For anyone with an interest in new crop development, this book provides a valuable insight into the intricacies of growing an indigenous species commercially.