An integrated gene annotation and transcriptional profiling approach towards the full gene content of the Drosophila genome

BACKGROUND: While the genome sequences for a variety of organisms are now available, the precise number of the genes encoded is still a matter of debate. For the human genome several stringent annotation approaches have resulted in the same number of potential genes, but a careful comparison revealed only limited overlap. This indicates that only the combination of different computational prediction methods and experimental evaluation of such in silico data will provide more complete genome annotations. In order to get a more complete gene content of the Drosophila melanogaster genome, we based our new D. melanogaster whole-transcriptome microarray, the Heidelberg FlyArray, on the combination of the Berkeley Drosophila Genome Project (BDGP) annotation and a novel ab initio gene prediction of lower stringency using the Fgenesh software. RESULTS: Here we provide evidence for the transcription of approximately 2,600 additional genes predicted by Fgenesh. Validation of the developmental profiling data by RT-PCR and in situ hybridization indicates a lower limit of 2,000 novel annotations, thus substantially raising the number of genes that make a fly. CONCLUSIONS: The successful design and application of this novel Drosophila microarray on the basis of our integrated in silico/wet biology approach confirms our expectation that in silico approaches alone will always tend to be incomplete. The identification of at least 2,000 novel genes highlights the importance of gathering experimental evidence to discover all genes within a genome. Moreover, as such an approach is independent of homology criteria, it will allow the discovery of novel genes unrelated to known protein families or those that have not been strictly conserved between species

Early epigenetic downregulation of microRNA-192 expression promotes pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDAC) is characterized by very early metastasis, suggesting the hypothesis that metastasis-associated changes may occur prior to actual tumor formation. In this study, we identified miR-192 as an epigenetically regulated suppressor gene with predictive value in this disease. miR-192 was downregulated by promoter methylation in both PDAC and chronic pancreatitis, the latter of which is a major risk factor for the development of PDAC. Functional studies in vitro and in vivo in mouse models of PDAC showed that overexpression of miR-192 was sufficient to reduce cell proliferation and invasion. Mechanistic analyses correlated changes in miR-192 promoter methylation and expression with epithelial–mesenchymal transition. Cell proliferation and invasion were linked to altered expression of the miR-192 target gene SERPINE1 that is encoding the protein plasminogen activator inhibitor-1 (PAI-1), an established regulator of these properties in PDAC cells. Notably, our data suggested that invasive capacity was altered even before neoplastic transformation occurred, as triggered by miR-192 downregulation. Overall, our results highlighted a role for miR-192 in explaining the early metastatic behavior of PDAC and suggested its relevance as a target to develop for early diagnostics and therapy. Cancer Res; 76(14); 4149–59. ©2016 AACR

Somatic mutations in exocrine pancreatic tumors: association with patient survival.

KRAS mutations are major factors involved in initiation and maintenance of pancreatic tumors. The impact of different mutations on patient survival has not been clearly defined. We screened tumors from 171 pancreatic cancer patients for mutations in KRAS and CDKN2A genes. Mutations in KRAS were detected in 134 tumors, with 131 in codon 12 and only 3 in codon 61. The GGT>GAT (G12D) was the most frequent mutation and was present in 60% (80/134). Deletions and mutations in CDKN2A were detected in 43 tumors. Analysis showed that KRAS mutations were associated with reduced patient survival in both malignant exocrine and ductal adenocarcinomas (PDAC). Patients with PDACs that had KRAS mutations showed a median survival of 17 months compared to 30 months for those without mutations (log-rank P = 0.07) with a multivariate hazard ratio (HR) of 2.19 (95%CI 1.09-4.42). The patients with G12D mutation showed a median survival of 16 months (log-rank-test P = 0.03) and an associated multivariate HR 2.42 (95%CI 1.14-2.67). Although, the association of survival in PDAC patients with CDKN2A aberrations in tumors was not statistically significant, the sub-group of patients with concomitant KRAS mutations and CDKN2A alterations in tumors were associated with a median survival of 13.5 months compared to 22 months without mutation (log-rank-test P = 0.02) and a corresponding HR of 3.07 (95%CI 1.33-7.10). Our results are indicative of an association between mutational status and survival in PDAC patients, which if confirmed in subsequent studies can have potential clinical application

Searching for Tissue-Specific Expression Pattern-Linked Nucleotides of UGT1A Isoforms

UDP-glucuronosyltransferases 1A isoforms belong to a superfamily of microsomal enzymes responsible for glucuronidation of numerous endogenous and exogenous compounds. The nine functional UGT1A isoforms are encoded by a single UGT1A gene locus with multiple first exons. The expression of the UGT1A transcripts was measured by quantitative RT-PCR in 23 normal human tissues. The tissue-specific expression patterns were observed in 13 tissues. To understand the regulation mechanism that is responsible for the tissue-specific expression patterns, we scanned the DNA sequence alignments of the putative promoter regions, exon 1 sequences and intron 1 sequences for those expression-pattern-linked nucleotides. Using one of the expression-pattern-linked nucleotides for livers as an example, we showed that a database comprised of these expression-pattern-linked nucleotides could be used to generate focused hypotheses on the problem of tissue-specific expression, which is critical for tissue-specific pharmacodynamics of anticancer drugs

Deterministic Classifiers Accuracy Optimization for Cancer Microarray Data

The objective of this study was to improve classification accuracy in cancer microarray gene expression data using a collection of machine learning algorithms available in WEKA. State of the art deterministic classification methods, such as: Kernel Logistic Regression, Support Vector Machine, Stochastic Gradient Descent and Logistic Model Trees were applied on publicly available cancer microarray datasets aiming to discover regularities that provide insights to help characterization and diagnosis correctness on each cancer typology. The implemented models, relying on 10-fold cross-validation, parameterized to enhance accuracy, reached accuracy above 90%. Moreover, although the variety of methodologies, no significant statistic differences were registered between them, at significance level 0.05, confirming that all the selected methods are effective for this type of analysis.info:eu-repo/semantics/publishedVersio

Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data

<p>Abstract</p> <p>Background</p> <p>Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net.</p> <p>We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone.</p> <p>Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution.</p> <p>Results</p> <p>Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (<it>L</it>₁) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error.</p> <p>Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations.</p> <p>Conclusions</p> <p>The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters.</p> <p>The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'.</p> <p>We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets.</p

Multiple Oncogenic Pathway Signatures Show Coordinate Expression Patterns in Human Prostate Tumors

BACKGROUND: Gene transcription patterns associated with activation of oncogenes Myc, c-Src, beta-catenin, E2F3, H-Ras, HER2, EGFR, MEK, Raf, MAPK, Akt, and cyclin D1, as well as of the cell cycle and of androgen signaling have been generated in previous studies using experimental models. It was not clear whether genes in these "oncogenic signatures" would show coordinate expression patterns in human prostate tumors, particularly as most of the signatures were derived from cell types other than prostate. PRINCIPAL FINDINGS: The above oncogenic pathway signatures were examined in four different gene expression profile datasets of human prostate tumors (representing approximately 250 patients in all), using both Q1-Q2 and one-sided Fisher's exact enrichment analysis methods. A significant fraction (approximately 5%) of genes up-regulated experimentally by Myc, c-Src, HER2, Akt, or androgen were co-expressed in human tumors with the oncogene or biomarker corresponding to the pathway signature. Genes down-regulated experimentally, however, did not show anticipated patterns of anti-enrichment in the human tumors. CONCLUSIONS: Significant subsets of the genes in these experimentally-derived oncogenic signatures are relevant to the study of human prostate cancer. Both molecular biologists and clinical researchers could focus attention on the relatively small number of genes identified here as having coordinate patterns that arise from both the experimental system and the human disease system

Single-Step Selection of Bivalent Aptamers Validated by Comparison with SELEX Using High-Throughput Sequencing

The identification of nucleic acid aptamers would be advanced if they could be obtained after fewer rounds of selection and amplification. In this paper the identification of bivalent aptamers for thrombin by SELEX and single-step selection are compared using next generation sequencing and motif finding informatics. Results show that similar aptamers are identified by both methods. This is significant because it shows that next generation sequencing and motif finding informatics have the potential to simplify the selection of aptamers by avoiding multiple rounds of enzymatic transcription and amplification

Genotypic resistance testing in HIV by arrayed primer extension

The analysis of mutations that are associated with the occurrence of drug resistance is important for monitoring the antiretroviral therapy of patients infected with human immunodeficiency virus (HIV). Here, we describe the establishment and successful application of Arrayed Primer Extension (APEX) for genotypic resistance testing in HIV as a rapid and economical alternative to standard sequencing. The assay is based on an array of oligonucleotide primers that are immobilised via their 5′-ends. Upon hybridisation of template DNA, a primer extension reaction is performed in the presence of the four dideoxynucleotides, each labelled with a distinct fluorophore. The inserted label immediately indicates the sequence at the respective position. Any mutation changes the colour pattern. We designed a microarray for the analysis of 26 and 33 codons in the HIV protease and reverse transcriptase, respectively, which are of special interest with respect to drug resistance. The enormous genome variability of HIV represents a big challenge for genotypic resistance tests, which include a hybridisation step, both in terms of specificity and probe numbers. The use of degenerated oligonucleotides resulted in a significant reduction in the number of primers needed. For validation, DNA of 94 and 48 patients that exhibited resistance to inhibitors of HIV protease and reverse transcriptase, respectively, were analysed. The validation included HIV subtype B, prevalent in industrialised countries, as well as non-subtype B samples that are more common elsewhere

Agrobacterium rhizogenes-Mediated Transformation of the Parasitic Plant Phtheirospermum japonicum

Background: Plants within the Orobanchaceae are an agriculturally important group of parasites that attack economically important crops to obtain water and nutrients from their hosts. Despite their agricultural importance, molecular mechanisms of the parasitism are poorly understood. Methodology/Principal Findings: We developed transient and stable transformation systems for Phtheirospermum japonicum, a facultative parasitic plant in the Orobanchaceae. The transformation protocol was established by a combination of sonication and acetosyringone treatments using the hairy-root-inducing bacterium, Agrobacterium rhizogenes and young seedlings. Transgenic hairy roots of P. japonicum were obtained from cotyledons 2 to 3 weeks after A. rhizogenes inoculation. The presence and the expression of transgenes in P. japonicum were verified by genomic PCR, Southern blot and RT-PCR methods. Transgenic roots derived from A. rhizogenes-mediated transformation were able to develop haustoria on rice and maize roots. Transgenic roots also formed apparently competent haustoria in response to 2,6dimethoxy-1,4-benzoquinone (DMBQ), a haustorium-inducing chemical. Using this system, we introduced a reporter gene with a Cyclin B1 promoter into P. japonicum, and visualized cell division during haustorium formation. Conclusions: We provide an easy and efficient method for hairy-root transformation of P. japonicum. Transgenic marker analysis revealed that cell divisions during haustorium development occur 24 h after DMBQ treatment. The protocol