436 research outputs found

    SNPInterForest: A new method for detecting epistatic interactions

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    <p>Abstract</p> <p>Background</p> <p>Multiple genetic factors and their interactive effects are speculated to contribute to complex diseases. Detecting such genetic interactive effects, i.e., epistatic interactions, however, remains a significant challenge in large-scale association studies.</p> <p>Results</p> <p>We have developed a new method, named SNPInterForest, for identifying epistatic interactions by extending an ensemble learning technique called random forest. Random forest is a predictive method that has been proposed for use in discovering single-nucleotide polymorphisms (SNPs), which are most predictive of the disease status in association studies. However, it is less sensitive to SNPs with little marginal effect. Furthermore, it does not natively exhibit information on interaction patterns of susceptibility SNPs. We extended the random forest framework to overcome the above limitations by means of (i) modifying the construction of the random forest and (ii) implementing a procedure for extracting interaction patterns from the constructed random forest. The performance of the proposed method was evaluated by simulated data under a wide spectrum of disease models. SNPInterForest performed very well in successfully identifying pure epistatic interactions with high precision and was still more than capable of concurrently identifying multiple interactions under the existence of genetic heterogeneity. It was also performed on real GWAS data of rheumatoid arthritis from the Wellcome Trust Case Control Consortium (WTCCC), and novel potential interactions were reported.</p> <p>Conclusions</p> <p>SNPInterForest, offering an efficient means to detect epistatic interactions without statistical analyses, is promising for practical use as a way to reveal the epistatic interactions involved in common complex diseases.</p

    An Improvement of Shotgun Proteomics Analysis by Adding Next-Generation Sequencing Transcriptome Data in Orange

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    BACKGROUND: Shotgun proteomics data analysis usually relies on database search. Because commonly employed protein sequence databases of most species do not contain sufficient protein information, the application of shotgun proteomics to the research of protein sequence profile remains a big challenge, especially to the species whose genome has not been sequenced yet. METHODOLOGY/PRINCIPAL FINDINGS: In this paper, we present a workflow with integrated database to partly address this problem. First, we downloaded the homologous species database. Next, we identified the transcriptome of the sample, created a protein sequence database based on the transcriptome data, and integtrated it with homologous species database. Lastly, we developed a workflow for identifying peptides simultaneously from shotgun proteomics data. CONCLUSIONS/SIGNIFICANCE: We used datasets from orange leaves samples to demonstrate our workflow. The results showed that the integrated database had great advantage on orange shotgun proteomics data analysis compared to the homologous species database, an 18.5% increase in number of proteins identification

    A meta-analysis of long-term effects of conservation agriculture on maize grain yield under rain-fed conditions

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    Conservation agriculture involves reduced tillage, permanent soil cover and crop rotations to enhance soil fertility and to supply food from a dwindling land resource. Recently, conservation agriculture has been promoted in Southern Africa, mainly for maize-based farming systems. However, maize yields under rain-fed conditions are often variable. There is therefore a need to identify factors that influence crop yield under conservation agriculture and rain-fed conditions. Here, we studied maize grain yield data from experiments lasting 5 years and more under rain-fed conditions. We assessed the effect of long-term tillage and residue retention on maize grain yield under contrasting soil textures, nitrogen input and climate. Yield variability was measured by stability analysis. Our results show an increase in maize yield over time with conservation agriculture practices that include rotation and high input use in low rainfall areas. But we observed no difference in system stability under those conditions. We observed a strong relationship between maize grain yield and annual rainfall. Our meta-analysis gave the following findings: (1) 92% of the data show that mulch cover in high rainfall areas leads to lower yields due to waterlogging; (2) 85% of data show that soil texture is important in the temporal development of conservation agriculture effects, improved yields are likely on well-drained soils; (3) 73% of the data show that conservation agriculture practices require high inputs especially N for improved yield; (4) 63% of data show that increased yields are obtained with rotation but calculations often do not include the variations in rainfall within and between seasons; (5) 56% of the data show that reduced tillage with no mulch cover leads to lower yields in semi-arid areas; and (6) when adequate fertiliser is available, rainfall is the most important determinant of yield in southern Africa. It is clear from our results that conservation agriculture needs to be targeted and adapted to specific biophysical conditions for improved impact

    Identification of a Cryptic Prokaryotic Promoter within the cDNA Encoding the 5′ End of Dengue Virus RNA Genome

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    Infectious cDNA clones of RNA viruses are important research tools, but flavivirus cDNA clones have proven difficult to assemble and propagate in bacteria. This has been attributed to genetic instability and/or host cell toxicity, however the mechanism leading to these difficulties has not been fully elucidated. Here we identify and characterize an efficient cryptic bacterial promoter in the cDNA encoding the dengue virus (DENV) 5′ UTR. Following cryptic transcription in E. coli, protein expression initiated at a conserved in-frame AUG that is downstream from the authentic DENV initiation codon, yielding a DENV polyprotein fragment that was truncated at the N-terminus. A more complete understanding of constitutive viral protein expression in E. coli might help explain the cloning and propagation difficulties generally observed with flavivirus cDNA

    Developing community-driven quality improvement initiatives to enhance chronic disease care in Indigenous communities in Canada : the FORGE AHEAD program protocol

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    BACKGROUND: Given the dramatic rise and impact of chronic diseases and gaps in care in Indigenous peoples in Canada, a shift from the dominant episodic and responsive healthcare model most common in First Nations communities to one that places emphasis on proactive prevention and chronic disease management is urgently needed. METHODS: The Transformation of Indigenous Primary Healthcare Delivery (FORGE AHEAD) Program partners with 11 First Nations communities across six provinces in Canada to develop and evaluate community-driven quality improvement (QI) initiatives to enhance chronic disease care. FORGE AHEAD is a 5-year research program (2013-2017) that utilizes a pre-post mixed-methods observational design rooted in participatory research principles to work with communities in developing culturally relevant innovations and improved access to available services. This intensive program incorporates a series of 10 inter-related and progressive program activities designed to foster community-driven initiatives with type 2 diabetes mellitus as the action disease. Preparatory activities include a national community profile survey, best practice and policy literature review, and readiness tool development. Community-level intervention activities include community and clinical readiness consultations, development of a diabetes registry and surveillance system, and QI activities. With a focus on capacity building, all community-level activities are driven by trained community members who champion QI initiatives in their community. Program wrap-up activities include readiness tool validation, cost-analysis and process evaluation. In collaboration with Health Canada and the Aboriginal Diabetes Initiative, scale-up toolkits will be developed in order to build on lessons-learned, tools and methods, and to fuel sustainability and spread of successful innovations. DISCUSSION: The outcomes of this research program, its related cost and the subsequent policy recommendations, will have the potential to significantly affect future policy decisions pertaining to chronic disease care in First Nations communities in Canada. TRIAL REGISTRATION: Current ClinicalTrial.gov protocol ID NCT02234973 . Date of Registration: July 30, 2014

    Regulation of BRCA1 expression and its relationship to sporadic breast cancer

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    Germ-line mutations in the BRCA1 tumour suppressor gene contribute to familial breast tumour formation, but there is no evidence for direct mutation of the BRCA1 gene in the sporadic form of the disease. In contrast, decreased expression of the BRCA1 gene has been shown to be common in sporadic tumours, and the magnitude of the decrease correlates with disease progression. BRCA1 expression is also tightly regulated during normal breast development. Determining how these developmental regulators of BRCA1 expression are co-opted during breast tumourigenesis could lead to a better understanding of sporadic breast cancer aetiology and the generation of novel therapeutic strategies aimed at preventing sporadic breast tumour progression

    Association of C1QB gene polymorphism with schizophrenia in Armenian population

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    <p>Abstract</p> <p>Background</p> <p>Schizophrenia is a complex, multifactorial psychiatric disorder. Our previous findings indicated that altered functional activity of the complement system, a major mediator of the immune response, is implicated in the pathogenesis of schizophrenia. In order to explore whether these alterations are genetically determined or not, in the present study we evaluated the possible association of complement C1Q component gene variants with susceptibility to schizophrenia in Armenian population, focusing on four frequent single nucleotide polymorphisms (SNPs) of <it>C1QA </it>and <it>C1QB </it>genes.</p> <p>Methods</p> <p>In the present study four SNPs of the complement C1Q component genes (<it>C1QA</it>: rs292001, <it>C1QB </it>rs291982, rs631090, rs913243) were investigated in schizophrenia-affected and healthy subjects. Unrelated Caucasian individuals of Armenian nationality, 225 schizophrenic patients and the same number of age- and sex-matched healthy subjects, were genotyped. Genotyping was performed using polymerase chain reaction with sequence-specific primers (PCR-SSP) and quantitative real-time (qRT) PCR methods.</p> <p>Results</p> <p>While there was no association between <it>C1QA </it>rs292001, <it>C1QB </it>rs913243 and rs631090 genetic variants and schizophrenia, the <it>C1QB </it>rs291982*G minor allele was significantly overrepresented in schizophrenic patients (G allele frequency 58%) when compared to healthy subjects (46%, OR = 1.64, <it>p</it><sub>corr </sub>= 0.0008). Importantly, the susceptibility for schizophrenia was particularly associated with <it>C1QB </it>rs291982 GG genotype (OR = 2.5, <it>p</it><sub>corrected </sub>= 9.6E-5).</p> <p>Conclusions</p> <p>The results obtained suggest that <it>C1QB </it>gene may be considered as a relevant candidate gene for susceptibility to schizophrenia, and its rs291982*G minor allele might represent a risk factor for schizophrenia at least in Armenian population. Replication in other centers/populations is necessary to verify this conclusion.</p
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