High-efficiency silencing of a β-glucuronidase gene in rice is correlated with repetitive transgene structure but is independent of DNA methylation

Two transgenic callus lines of rice, stably expressing a β-glucuronidase (GUS) gene, were supertransformed with a set of constructs designed to silence the resident GUS gene. An inverted-repeat (i/r) GUS construct, designed to produce mRNA with self-complementarity, was much more effective than simple sense and antisense constructs at inducing silencing. Supertransforming rice calluses with a direct-repeat (d/r) construct, although not as effective as those with the i/r construct, was also substantially more effective in silencing the resident GUS gene than the simple sense and antisense constructs. DNA hybridisation analyses revealed that every callus line supertransformed with either simple sense or antisense constructs, and subsequently showing GUS silencing, had the silence-inducing transgenes integrated into the plant genome in inverted-repeat configurations. The silenced lines containing i/r and d/r constructs did not necessarily have inverted-repeat T-DNA insertions. There was significant methylation of the GUS sequences in most of the silenced lines but not in the unsilenced lines. However, demethylation treatment of silenced lines with 5-azacytidine did not reverse the post-transcriptional gene silencing (PTGS) of GUS. Whereas the levels of RNA specific to the resident GUS gene were uniformly low in the silenced lines, RNA specific to the inducer transgenes accumulated to a substantial level, and the majority of the i/r RNA was unpolyadenylated. Altogether, these results suggest that both sense- and antisense-mediated gene suppression share a similar molecular basis, that unpolyadenylated RNA plays an important role in PTGS, and that methylation is not essential for PTGS.

Soybean dwarf luteovirus contains the third variant genome type in the luteovirus group

Complementary DNAs covering the entire RNA genome of soybean dwarf luteovirus (SDV) were cloned and sequenced. Computer analysis of the 5861 nucleotide sequence revealed five major open reading frames (ORFs) possessing conservation of sequence and organisation with known luteovirus sequences. Comparative analyses of the genome structure show that SDV shares sequence homology and features of gene organisation with barley yellow dwarf virus (PAV isolate) in the 5' half of the genome, yet is more closely related to potato leafroll virus in its 3' coding regions. In addition, SDV differs from other known luteoviruses in possessing an exceptionally long 3' terminal sequence with no apparent coding capacity. We conclude from these data that the SDV genome represents a third variant genome type in the luteovirus group.

Characterisation of the subgenomic RNAs of an Australian isolate of barley yellow dwarf luteovirus

We have characterised the subgenomic RNAs of an Australian isolate of BYDV-PAV. Northern blot analyses of infected plants and protoplasts have shown that this isolate synthesises three subgenomic RNAs. Precise mapping of the transcription start sites of all three subgenomic RNAs and translational analyses of subgenomic RNA 2 and 3 have revealed a number of features. First, the transcription start site of subgenomic RNA 1 in this isolate differs markedly from the start site determined for an Illinois isolate of BYDV-PAV. Second, the start sites of subgenomic RNA 1 and 2 occur at a sequence that closely resembles the 5' end sequence of the genomic RNA (5'AGUGAAGA). Third, subgenomic RNA 2 appears to express ORF 6 of BYDV-PAV but the gene product is truncated due to the appearance of a new stop codon in the sequence. Last, subgenomic RNA 3, which is abundantly transcribed and encapsidated by the virus particle, appears to have no coding ability. We postulate that this novel subgenomic RNA has a regulatory function.

Association between xenobiotic gene polymorphisms and non-Hodgkin's lymphoma risk

The last four decades have seen a significant increase in the incidence of non-Hodgkin's lymphoma (NHL) as a possible result of increasing environmental carcinogen exposure, particularly pesticides and solvents. Based on the increasing evidence for an association between carcinogen exposure-related cancer risk and xenobiotic gene polymorphisms, we have undertaken a case-control study of xenobiotic gene polymorphisms in individuals with a diagnosis of NHL. Polymorphisms of six xenobiotic genes (CYP1A1, GSTT1, GSTM1, PON1, NAT1, NAT2) were characterized in 169 individuals with NHL and 205 normal controls using polymerase chain reaction-based methods. Polymorphic frequencies were compared using Fisher's exact tests, and odds ratios for NHL risk were calculated. Among the NHL group, the incidence of GSTT1 null and PON1 BB genotypes were significantly increased compared with controls, 34% vs 14%, and 24% vs 11% respectively. Adjusted odds ratios calculated from multivariate analyses demonstrated that GSTT1 null conferred a fourfold increase in NHL risk (OR = 4.27; 95% CI, 2.40-7.61, P < 0.001) and PON1 BB a 2.9-fold increase (OR = 2.92; 95% CI, 1.49-5.72, P = 0.002). Furthermore, GSTT1 null combined with PON1 BB or GSTM1 null conferred an additional risk of NHL. This is the first time that a PON1 gene polymorphism has been shown to be associated with cancer risk. We conclude that the two polymorphisms, GSTT1 null and PON1 BB, are common genetic traits that pose low individual risk but may be important determinants of overall population NHL risk, particularly among groups exposed to NHL-related carcinogens.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

Multilocus sequence analysis provides insights into molecular epidemiology of Chlamydia pecorum infections in Australian sheep, cattle and koalas

Chlamydia pecorum is a significant pathogen of domestic livestock and wildlife. We have developed a C. pecorum-specific multilocus sequence analysis (MLSA) scheme to examine the genetic diversity of and relationships between Australian sheep, cattle, and koala isolates. An MLSA of seven concatenated housekeeping gene fragments was performed using 35 isolates, including 18 livestock isolates (11 Australian sheep, one Australian cow, and six U.S. livestock isolates) and 17 Australian koala isolates. Phylogenetic analyses showed that the koala isolates formed a distinct clade, with limited clustering with C. pecorum isolates from Australian sheep. We identified 11 MLSA sequence types (STs) among Australian C. pecorum isolates, 10 of them novel, with koala and sheep sharing at least one identical ST (designated ST2013Aa). ST23, previously identified in global C. pecorum livestock isolates, was observed here in a subset of Australian bovine and sheep isolates. Most notably, ST23 was found in association with multiple disease states and hosts, providing insights into the transmission of this pathogen between livestock hosts. The complexity of the epidemiology of this disease was further highlighted by the observation that at least two examples of sheep were infected with different C. pecorum STs in the eyes and gastrointestinal tract. We have demonstrated the feasibility of our MLSA scheme for understanding the host relationship that exists between Australian C. pecorum strains and provide the first molecular epidemiological data on infections in Australian livestock hosts.

QUT Library advances the use of open public tools to navigate genetic inventions and builds research networks

Many emerging economies are dangling the patent system to stimulate bio-technological innovations with the ultimate premise that these will improve their economic and social growth. The patent system mandates full disclosure of the patented invention in exchange of a temporary exclusive patent right. Recently, however, patent offices have fallen short of complying with such a mandate, especially for genetic inventions. Most patent offices provide only static information about disclosed patent sequences and even some do not keep track of the sequence listing data in their own database. The successful partnership of QUT Library and Cambia exemplifies advocacy in Open Access, Open Innovation and User Participation. The library extends its services to various departments within the university, builds and encourages research networks to complement skills needed to make a contribution in the real world.

Whole-genome sequencing reveals untapped genetic potential in Africa’s indigenous cereal crop sorghum

Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16–45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.

Genetic analysis of GRIA2 and GRIA4 genes in migraine

Background Migraine is a brain disorder affecting ∼12% of the Caucasian population. Genes involved in neurological, vascular, and hormonal pathways have all been implicated in predisposing individuals to developing migraine. The migraineur presents with disabling head pain and varying symptoms of nausea, emesis, photophobia, phonophobia, and occasionally visual sensory disturbances. Biochemical and genetic studies have demonstrated dysfunction of neurotransmitters: serotonin, dopamine, and glutamate in migraine susceptibility. Glutamate mediates the transmission of excitatory signals in the mammalian central nervous system that affect normal brain function including cognition, memory and learning. The aim of this study was to investigate polymorphisms in the GRIA2 and GRIA4 genes, which encode subunits of the ionotropic AMPA receptor for association in an Australian Caucasian population. Methods Genotypes for each polymorphism were determined using high resolution melt analysis and the RFLP method. Results Statistical analysis showed no association between migraine and the GRIA2 and GRIA4 polymorphisms investigated. Conclusions Although the results of this study showed no significant association between the tested GRIA gene variants and migraine in our Australian Caucasian population further investigation of other components of the glutamatergic system may help to elucidate if there is a relationship between glutamatergic dysfunction and migraine.

Genetic polymorphisms in miRNAs targeting the estrogen receptor and their effect on breast cancer risk

Breast cancer is the cancer that most commonly affects women worldwide. This type of cancer is genetically complex, but is strongly linked to steroid hormone signalling systems. Because microRNAs act as translational regulators of multiple genes, including the steroid nuclear receptors, single nucleotide polymorphisms (SNPs) in microRNAs genes can have potentially wide-ranging influences on breast cancer development. Thus, this study was conducted to investigate the relationships between six SNPs (rs6977848, rs199981120, rs185641358, rs113054794, rs66461782, and rs12940701) located in four miRNA genes predicted to target the estrogen receptor (miR-148a, miR-221, miR-186, and miR-152) and breast cancer risk in Caucasian Australian women. By using high resolution melt analysis (HRM) and polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), 487 samples including 225 controls and 262 cases were genotyped. Analysis of their genotype and allele frequencies indicated that the differences between case and control populations was not significant for rs6977848, rs66461782, and rs12940701 because their p-values are 0.81, 0.93, 0.1 which are all above the threshold value (p=0.05). Our data thus suggests that these SNPs do not affect breast cancer risk in the tested population. In addition, rs199981120, rs185641358, and rs113054794 could not be found in this population, suggesting that these SNPs do not occur in Caucasian Australians.

Proteomic and other analyses to determine the functional consequences of deregulated kallikrein-related peptidase (KLK) expression in prostate and ovarian cancer

Rapidly developing proteomic tools are improving detection of deregulated kallikrein-related peptidase (KLK) expression, at the protein level, in prostate and ovarian cancer, as well as facilitating the determination of functional consequences downstream. Mass spectrometry (MS)-driven proteomics uniquely allows for the detection, identification and quantification of thousands of proteins in a complex protein pool, and this has served to identify certain KLKs as biomarkers for these diseases. In this review we describe applications of this technology in KLK biomarker discovery, and elucidate MS-based techniques which have been used for unbiased, global screening of KLK substrates within complex protein pools. Although MS-based KLK degradomic studies are limited to date, they helped to discover an array of novel KLK substrates. Substrates identified by MS-based degradomics are reported with improved confidence over those determined by incubating a purified or recombinant substrate and protease of interest, in vitro. We propose that these novel proteomic approaches represent the way forward for KLK research, in order to correlate proteolysis of biological substrates with tissue-related consequences, toward clinical targeting of KLK expression and function for cancer diagnosis, prognosis and therapies.

Quantitative genetic parameters for body traits at different ages in a cultured stock of giant freshwater prawn (Macrobrachium rosenbergii) selected for fast growth

The aim of the current study was to estimate heritabilities and correlations for body traits at different ages (Weeks 10 and 18 after stocking) in a giant freshwater prawn (Macrobrachium rosenbergii) population selected for fast growth rate in Vietnam. The dataset consisted of 4650 body records (2432 and 2218 records collected at Weeks 10 and 18, respectively) in the full pedigree comprising a total of 18 387 records. Variance and covariance components were estimated using restricted maximum likelihood fitting a multi-trait animal model. Estimates of heritability for body traits (bodyweight, body length, cephalothorax length, abdominal length, cephalothorax width and abdominal width) were moderate and ranged from 0.06 to 0.11 and from 0.11 to 0.22 at Weeks 10 and 18, respectively. Body-trait heritabilities estimated at Week 10 were not significantly lower than at Week 18. Genetic correlations between body traits within age and genetic correlations for body traits between ages were generally high. Our results suggested that selection for high growth rate in GFP can be undertaken successfully before full market size has been reached.

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

A new grouping genetic algorithm for the MapReduce placement problem in cloud computing

MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NPcomplete. Thus, in this paper we propose a new grouping genetic algorithm for the mappers/reducers placement problem in cloud computing. Compared with the original one, our grouping genetic algorithm uses an innovative coding scheme and also eliminates the inversion operator which is an essential operator in the original grouping genetic algorithm. The new grouping genetic algorithm is evaluated by experiments and the experimental results show that it is much more efficient than four popular algorithms for the problem, including the original grouping genetic algorithm.

Composite SaaS scaling in cloud computing using a hybrid genetic algorithm

A Software-as-a-Service or SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. Components in a composite SaaS may need to be scaled – replicated or deleted, to accommodate the user’s load. It may not be necessary to replicate all components of the SaaS, as some components can be shared by other instances. On the other hand, when the load is low, some of the instances may need to be deleted to avoid resource underutilisation. Thus, it is important to determine which components are to be scaled such that the performance of the SaaS is still maintained. Extensive research on the SaaS resource management in Cloud has not yet addressed the challenges of scaling process for composite SaaS. Therefore, a hybrid genetic algorithm is proposed in which it utilises the problem’s knowledge and explores the best combination of scaling plan for the components. Experimental results demonstrate that the proposed algorithm outperforms existing heuristic-based solutions.