985 resultados para genetic transformation


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Background Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

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In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.

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In Uganda, vitamin A deficiency (VAD) and iron deficiency anaemia (IDA) are major public health problems with between 15-32% of children under 5 years of age showing VAD and 73% being anaemic. This is largely due to the fact that the staple food crop of the country, banana, is low in pro-vitamin A and iron, therefore leading to dietary deficiencies. Although worldwide progress has been made to control VAD and IDA through supplementation, food fortification and diet diversification, their long term sustainability and impact in developing countries such as Uganda is limited. The approach taken by researchers at Queensland University of Technology (QUT), Australia, in collaboration with the National Agricultural Research Organization (NARO), Uganda, to address this problem, is to generate consumer acceptable banana varieties with significantly increased levels of pro-vitamin A and iron in the fruit using genetic engineering techniques. Such an approach requires the use of suitable, well characterised genes and promoters for targeted transgene expression. Recently, a new banana phytoene synthase gene (APsy2a) involved in the synthesis of pro-vitamin A (pVA) carotenoids was isolated from a high â-carotene banana (F’ei cv Asupina). In addition, sequences of banana ferritin, an iron storage protein, have been isolated from Cavendish banana. The aim of the research described in this thesis was to evaluate the function of these genes to assess their suitability for the biofortification of banana fruit. In addition, a range of banana-derived promoters were characterised to determine their suitability for controlling the expression of transgenes in banana fruit. Due to the time constraints involved with generating transgenic banana fruit, rice was used as the model crop to investigate the functionality of the banana-derived APsy2a and ferritin genes. Using Agrobacterium-mediated transformation, rice callus was transformed with APsy2a +/- the bacterial-derived carotene desaturase gene (CrtI) each under the control of the constitutive maize poly-ubiquitin promoter (ZmUbi) or seed-specific rice glutelin1 (Gt1) promoter. The maize phytoene synthase (ZmPsy1) gene was included as a control. On selective media, with the exception of ZmUbi-CrtI-transgenic callus, all antibiotic resistant callus displayed a yellow-orange colour from which the presence of â-carotene was demonstrated using Raman spectroscopy. Although the regeneration of plants from yellow-orange callus was difficult, 16 transgenic plants were obtained and characterised from callus transformed with ZmUbi-APys2a alone. At least 50% of the T1 seeds developed a yellow-orange coloured callus which was found to contain levels of â-carotene ranging from 4.6-fold to 72-fold higher than that in non-transgenic rice callus. Using the seed-specific Gt1 promoter, 38 transgenic rice plants were generated from APsy2a-CrtI-transformed callus while 32 plants were regenerated from ZmPsy1-CrtI-transformed callus. However, when analysed for presence of transgene by PCR, all transgenic plants contained the APsy2a, ZmPsy1 or CrtI transgene, with none of the plants found to be co-transformed. Using Raman spectroscopy, no â-carotene was detected in-situ in representative T1 seeds. To investigate the potential of the banana-derived ferritin gene (BanFer1) to enhance iron content, rice callus was transformed with constitutively expressed BanFer1 using the soybean ferritin gene (SoyFer) as a control. A total of 12 and 11 callus lines independently transformed with BanFer1 and SoyFer, respectively, were multiplied and transgene expression was verified by RT-PCR. Pearl’s Prussian blue staining for in-situ detection of ferric iron showed a stronger blue colour in rice callus transformed with BanFer1 compared to SoyFer. Using flame atomic absorption spectrometry, the highest mean amount of iron quantified in callus transformed with BanFer1 was 30-fold while that obtained using the SoyFer was 14-fold higher than the controls. In addition, ~78% of BanFer1-transgenic callus lines and ~27% of SoyFer-transgenic callus lines had significantly higher iron content than the non-transformed controls. Since the genes used for enhancing micronutrient content need to be expressed in banana fruit, the activity of a range of banana-derived, potentially fruit-active promoters in banana was investigated. Using uidA (GUS) as a reporter gene, the function of the Expansin1 (MaExp1), Expansin1 containing the rice actin intron (MaExp1a), Expansin4 (MaExp4), Extensin (MaExt), ACS (MaACS), ACO (MaACO), Metallothionein (MaMT2a) and phytoene synthase (APsy2a) promoters were transiently analysed in intact banana fruit using two transformation methods, particle bombardment and Agrobacterium-mediated infiltration (agro-infiltration). Although a considerable amount of variation in promoter activity was observed both within and between experiments, similar trends were obtained using both transformation methods. The MaExp1 and MaExp1a directed high levels of GUS expression in banana fruit which were comparable to those observed from the ZmUbi and Banana bunchy top virus-derived BT4 promoters that were included as positive controls. Lower levels of promoter activity were obtained in both methods using the MaACO and MaExt promoters while the MaExp4, MaACS, and APsy2a promoters directed the lowest GUS activity in banana fruit. An attempt was subsequently made to use agro-infiltration to assess the expression of pVA biosynthesis genes in banana fruit by infiltrating fruit with constructs in which the ZmUbi promoter controlled the expression of APsy2a +/- CrtI, and with the maize phytoene synthase gene (ZmPsy1) included as a control. Unfortunately, the large amount of variation and inconsistency observed within and between experiments precluded any meaningful conclusions to be drawn. The final component of this research was to assess the level of promoter activity and specificity in non-target tissue. These analyses were done on leaves obtained from glasshouse-grown banana plants stably transformed with MaExp1, MaACO, APsy2a, BT4 and ZmUbi promoters driving the expression of the GUS gene in addition to leaves from a selection of the same transgenic plants which were growing in a field trial in North Queensland. The results from both histochemical and fluorometric GUS assays showed that the MaExp1 and MaACO promoters directed very low GUS activities in leaves of stably transformed banana plants compared to the constitutive ZmUbi and BT4 promoters. In summary, the results from this research provide evidence that the banana phytoene synthase gene (APsy2a) and the banana ferritin gene (BanFer1) are functional, since the constitutive over-expression of each of these transgenes led to increased levels of pVA carotenoids (for APsy2a) and iron content (for BanFer1) in transgenic rice callus. Further work is now required to determine the functionality of these genes in stably-transformed banana fruit. This research also demonstrated that the MaExp1 and MaACO promoters are fruit-active but have low activity in non-target tissue (leaves), characteristics that make them potentially useful for the biofortification of banana fruit. Ultimately, however, analysis of fruit from field-grown transgenic plants will be required to fully evaluate the suitability of pVA biosynthesis genes and the fruit-active promoters for fruit biofortification.

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To evaluate the timing of mutations in BRAF (v-raf murine sarcoma viral oncogene homolog B1) during melanocytic neoplasia, we carried out mutation analysis on microdissected melanoma and nevi samples. We observed mutations resulting in the V599E amino-acid substitution in 41 of 60 (68%) melanoma metastases, 4 of 5 (80%) primary melanomas and, unexpectedly, in 63 of 77 (82%) nevi. These data suggest that mutational activation of the RAS/RAF/MAPK pathway in nevi is a critical step in the initiation of melanocytic neoplasia but alone is insufficient for melanoma tumorigenesis.

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This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

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We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.