Methods for selecting fixed-effect models for heterogeneous codon evolution, with comments on their application to gene and genome data.

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Bao, Le; Gu, Hong; Dunn, Katherine A; Bielawski, Joseph P

2007-02-08

Models of codon evolution have proven useful for investigating the strength and direction of natural selection. In some cases, a priori biological knowledge has been used successfully to model heterogeneous evolutionary dynamics among codon sites. These are called fixed-effect models, and they require that all codon sites are assigned to one of several partitions which are permitted to have independent parameters for selection pressure, evolutionary rate, transition to transversion ratio or codon frequencies. For single gene analysis, partitions might be defined according to protein tertiary structure, and for multiple gene analysis partitions might be defined according to a gene's functional category. Given a set of related fixed-effect models, the task of selecting the model that best fits the data is not trivial. In this study, we implement a set of fixed-effect codon models which allow for different levels of heterogeneity among partitions in the substitution process. We describe strategies for selecting among these models by a backward elimination procedure, Akaike information criterion (AIC) or a corrected Akaike information criterion (AICc). We evaluate the performance of these model selection methods via a simulation study, and make several recommendations for real data analysis. Our simulation study indicates that the backward elimination procedure can provide a reliable method for model selection in this setting. We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria). Fixed-effect models have advantages and disadvantages. Fixed-effect models are desirable when data partitions are known to exhibit significant heterogeneity or when a statistical test of such heterogeneity is desired. They have the disadvantage of requiring a priori

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

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Landfors Mattias

2010-10-01

Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

Science.gov (United States)

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is

Selection of Phototransduction Genes in Homo sapiens.

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Christopher, Mark; Scheetz, Todd E; Mullins, Robert F; Abràmoff, Michael D

2013-08-13

We investigated the evidence of recent positive selection in the human phototransduction system at single nucleotide polymorphism (SNP) and gene level. SNP genotyping data from the International HapMap Project for European, Eastern Asian, and African populations was used to discover differences in haplotype length and allele frequency between these populations. Numeric selection metrics were computed for each SNP and aggregated into gene-level metrics to measure evidence of recent positive selection. The level of recent positive selection in phototransduction genes was evaluated and compared to a set of genes shown previously to be under recent selection, and a set of highly conserved genes as positive and negative controls, respectively. Six of 20 phototransduction genes evaluated had gene-level selection metrics above the 90th percentile: RGS9, GNB1, RHO, PDE6G, GNAT1, and SLC24A1. The selection signal across these genes was found to be of similar magnitude to the positive control genes and much greater than the negative control genes. There is evidence for selective pressure in the genes involved in retinal phototransduction, and traces of this selective pressure can be demonstrated using SNP-level and gene-level metrics of allelic variation. We hypothesize that the selective pressure on these genes was related to their role in low light vision and retinal adaptation to ambient light changes. Uncovering the underlying genetics of evolutionary adaptations in phototransduction not only allows greater understanding of vision and visual diseases, but also the development of patient-specific diagnostic and intervention strategies.

Genetic signature of strong recent positive selection at interleukin-32 gene in goat

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Akhtar Rasool Asif

2017-07-01

Full Text Available Objective Identification of the candidate genes that play key roles in phenotypic variations can provide new information about evolution and positive selection. Interleukin (IL-32 is involved in many biological processes, however, its role for the immune response against various diseases in mammals is poorly understood. Therefore, the current investigation was performed for the better understanding of the molecular evolution and the positive selection of single nucleotide polymorphisms in IL-32 gene. Methods By using fixation index (FST based method, IL-32 (9375 gene was found to be outlier and under significant positive selection with the provisional combined allocation of mean heterozygosity and FST. Using nucleotide sequences of 11 mammalian species from National Center for Biotechnology Information database, the evolutionary selection of IL-32 gene was determined using Maximum likelihood model method, through four models (M1a, M2a, M7, and M8 in Codeml program of phylogenetic analysis by maximum liklihood. Results IL-32 is detected under positive selection using the FST simulations method. The phylogenetic tree revealed that goat IL-32 was in close resemblance with sheep IL-32. The coding nucleotide sequences were compared among 11 species and it was found that the goat IL-32 gene shared identity with sheep (96.54%, bison (91.97%, camel (58.39%, cat (56.59%, buffalo (56.50%, human (56.13%, dog (50.97%, horse (54.04%, and rabbit (53.41% respectively. Conclusion This study provides evidence for IL-32 gene as under significant positive selection in goat.

An Efficient Ensemble Learning Method for Gene Microarray Classification

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Alireza Osareh

2013-01-01

Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

Prospective identification of malaria parasite genes under balancing selection.

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Kevin K A Tetteh

Full Text Available Endemic human pathogens are subject to strong immune selection, and interrogation of pathogen genome variation for signatures of balancing selection can identify important target antigens. Several major antigen genes in the malaria parasite Plasmodium falciparum have shown such signatures in polymorphism-versus-divergence indices (comparing with the chimpanzee parasite P. reichenowi, and in allele frequency based indices.To compare methods for prospective identification of genes under balancing selection, 26 additional genes known or predicted to encode surface-exposed proteins of the invasive blood stage merozoite were first sequenced from a panel of 14 independent P. falciparum cultured lines and P. reichenowi. Six genes at the positive extremes of one or both of the Hudson-Kreitman-Aguade (HKA and McDonald-Kreitman (MK indices were identified. Allele frequency based analysis was then performed on a Gambian P. falciparum population sample for these six genes and three others as controls. Tajima's D (TjD index was most highly positive for the msp3/6-like PF10_0348 (TjD = 1.96 as well as the positive control ama1 antigen gene (TjD = 1.22. Across the genes there was a strong correlation between population TjD values and the relative HKA indices (whether derived from the population or the panel of cultured laboratory isolates, but no correlation with the MK indices.Although few individual parasite genes show significant evidence of balancing selection, analysis of population genomic and comparative sequence data with the HKA and TjD indices should discriminate those that do, and thereby identify likely targets of immunity.

A feature selection approach for identification of signature genes from SAGE data

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Silva Paulo JS

2007-05-01

Full Text Available Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS or the recent Sequencing-By-Synthesis (SBS technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

Statistical approach for selection of biologically informative genes.

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Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

Recent adaptive events in human brain revealed by meta-analysis of positively selected genes.

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Yue Huang

Full Text Available BACKGROUND AND OBJECTIVES: Analysis of positively-selected genes can help us understand how human evolved, especially the evolution of highly developed cognitive functions. However, previous works have reached conflicting conclusions regarding whether human neuronal genes are over-represented among genes under positive selection. METHODS AND RESULTS: We divided positively-selected genes into four groups according to the identification approaches, compiling a comprehensive list from 27 previous studies. We showed that genes that are highly expressed in the central nervous system are enriched in recent positive selection events in human history identified by intra-species genomic scan, especially in brain regions related to cognitive functions. This pattern holds when different datasets, parameters and analysis pipelines were used. Functional category enrichment analysis supported these findings, showing that synapse-related functions are enriched in genes under recent positive selection. In contrast, immune-related functions, for instance, are enriched in genes under ancient positive selection revealed by inter-species coding region comparison. We further demonstrated that most of these patterns still hold even after controlling for genomic characteristics that might bias genome-wide identification of positively-selected genes including gene length, gene density, GC composition, and intensity of negative selection. CONCLUSION: Our rigorous analysis resolved previous conflicting conclusions and revealed recent adaptation of human brain functions.

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

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Serafini Maria

2003-11-01

Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Recursive Cluster Elimination (RCE for classification and feature selection from gene expression data

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Showe Louise C

2007-05-01

Full Text Available Abstract Background Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that are important for distinguishing the different sample classes being compared, poses a challenging problem in high dimensional data analysis. We describe a new procedure for selecting significant genes as recursive cluster elimination (RCE rather than recursive feature elimination (RFE. We have tested this algorithm on six datasets and compared its performance with that of two related classification procedures with RFE. Results We have developed a novel method for selecting significant genes in comparative gene expression studies. This method, which we refer to as SVM-RCE, combines K-means, a clustering method, to identify correlated gene clusters, and Support Vector Machines (SVMs, a supervised machine learning classification method, to identify and score (rank those gene clusters for the purpose of classification. K-means is used initially to group genes into clusters. Recursive cluster elimination (RCE is then applied to iteratively remove those clusters of genes that contribute the least to the classification performance. SVM-RCE identifies the clusters of correlated genes that are most significantly differentially expressed between the sample classes. Utilization of gene clusters, rather than individual genes, enhances the supervised classification accuracy of the same data as compared to the accuracy when either SVM or Penalized Discriminant Analysis (PDA with recursive feature elimination (SVM-RFE and PDA-RFE are used to remove genes based on their individual discriminant weights. Conclusion SVM-RCE provides improved classification accuracy with complex microarray data sets when it is compared to the classification accuracy of the same datasets using either SVM-RFE or PDA-RFE. SVM-RCE identifies clusters of correlated genes that when considered together

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

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Hala Alshamlan

2015-01-01

Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

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Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Natural Selection in Virulence Genes of Francisella tularensis.

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Gunnell, Mark K; Robison, Richard A; Adams, Byron J

2016-06-01

A fundamental tenet of evolution is that alleles that are under negative selection are often deleterious and confer no evolutionary advantage. Negatively selected alleles are removed from the gene pool and are eventually extinguished from the population. Conversely, alleles under positive selection do confer an evolutionary advantage and lead to an increase in the overall fitness of the organism. These alleles increase in frequency until they eventually become fixed in the population. Francisella tularensis is a zoonotic pathogen and a potential biothreat agent. The most virulent type of F. tularensis, Type A, is distributed across North America with Type A.I occurring mainly in the east and Type A.II appearing mainly in the west. F. tularensis is thought to be a genome in decay (losing genes) because of the relatively large number of pseudogenes present in its genome. We hypothesized that the observed frequency of gene loss/pseudogenes may be an artifact of evolution in response to a changing environment, and that genes involved in virulence should be under strong positive selection. To test this hypothesis, we sequenced and compared whole genomes of Type A.I and A.II isolates. We analyzed a subset of virulence and housekeeping genes from several F. tularensis subspecies genomes to ascertain the presence and extent of positive selection. Eleven previously identified virulence genes were screened for positive selection along with 10 housekeeping genes. Analyses of selection yielded one housekeeping gene and 7 virulence genes which showed significant evidence of positive selection at loci implicated in cell surface structures and membrane proteins, metabolism and biosynthesis, transcription, translation and cell separation, and substrate binding and transport. Our results suggest that while the loss of functional genes through disuse could be accelerated by negative selection, the genome decay in Francisella could also be the byproduct of adaptive evolution

Gene selection and classification for cancer microarray data based on machine learning and similarity measures

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Liu Qingzhong

2011-12-01

Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

Gene selection for cancer classification with the help of bees.

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Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

2016-08-10

Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

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Qingzhong Liu

Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

Confirming candidate genes for longevity in Drosophila melanogaster using two different genetic backgrounds and selection methods

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Wit, Janneke; Frydenberg, Jane; Sarup, Pernille Merete

2013-01-01

usually focussed on one sex and on flies originating from one genetic background, and results from different studies often do not overlap. Using D. melanogaster selected for increased longevity we aimed to find robust longevity related genes by examining gene expression in both sexes of flies originating......Elucidating genes that affect life span or that can be used as biomarkers for ageing has received attention in diverse studies in recent years. Using model organisms and various approaches several genes have been linked to the longevity phenotype. For Drosophila melanogaster those studies have...... from different genetic backgrounds. Further, we compared expression changes across three ages, when flies were young, middle aged or old, to examine how candidate gene expression changes with the onset of ageing. We selected 10 genes based on their expression differences in prior microarray studies...

ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.

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Brett A McKinney

Full Text Available Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k for each gene to optimize the Relief-F test statistics (importance scores for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to

A metaheuristic optimization framework for informative gene selection

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Kaberi Das

Full Text Available This paper presents a metaheuristic framework using Harmony Search (HS with Genetic Algorithm (GA for gene selection. The internal architecture of the proposed model broadly works in two phases, in the first phase, the model allows the hybridization of HS with GA to compute and evaluate the fitness of the randomly selected solutions of binary strings and then HS ranks the solutions in descending order of their fitness. In the second phase, the offsprings are generated using crossover and mutation operations of GA and finally, those offsprings were selected for the next generation whose fitness value is more than their parents evaluated by SVM classifier. The accuracy of the final gene subsets obtained from this model has been evaluated using SVM classifiers. The merit of this approach is analyzed by experimental results on five benchmark datasets and the results showed an impressive accuracy over existing feature selection approaches. The occurrence of gene subsets selected from this model have also been computed and the most often selected gene subsets with the probability of [0.1–0.9] have been chosen as optimal sets of informative genes. Finally, the performance of those selected informative gene subsets have been measured and established through probabilistic measures. Keywords: Gene Selection, Metaheuristic, Harmony Search Algorithm, Genetic Algorithm, SVM

Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

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Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

Evaluation of gene importance in microarray data based upon probability of selection

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Fu Li M

2005-03-01

Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification.

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Xu, Jiucheng; Mu, Huiyu; Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC 2 ), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.

A dual selection based, targeted gene replacement tool for Magnaporthe grisea and Fusarium oxysporum.

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Khang, Chang Hyun; Park, Sook-Young; Lee, Yong-Hwan; Kang, Seogchan

2005-06-01

Rapid progress in fungal genome sequencing presents many new opportunities for functional genomic analysis of fungal biology through the systematic mutagenesis of the genes identified through sequencing. However, the lack of efficient tools for targeted gene replacement is a limiting factor for fungal functional genomics, as it often necessitates the screening of a large number of transformants to identify the desired mutant. We developed an efficient method of gene replacement and evaluated factors affecting the efficiency of this method using two plant pathogenic fungi, Magnaporthe grisea and Fusarium oxysporum. This method is based on Agrobacterium tumefaciens-mediated transformation with a mutant allele of the target gene flanked by the herpes simplex virus thymidine kinase (HSVtk) gene as a conditional negative selection marker against ectopic transformants. The HSVtk gene product converts 5-fluoro-2'-deoxyuridine to a compound toxic to diverse fungi. Because ectopic transformants express HSVtk, while gene replacement mutants lack HSVtk, growing transformants on a medium amended with 5-fluoro-2'-deoxyuridine facilitates the identification of targeted mutants by counter-selecting against ectopic transformants. In addition to M. grisea and F. oxysporum, the method and associated vectors are likely to be applicable to manipulating genes in a broad spectrum of fungi, thus potentially serving as an efficient, universal functional genomic tool for harnessing the growing body of fungal genome sequence data to study fungal biology.

Novel method to load multiple genes onto a mammalian artificial chromosome.

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Anna Tóth

Full Text Available Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

Novel method to load multiple genes onto a mammalian artificial chromosome.

Science.gov (United States)

Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

2014-01-01

Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

Minimal gene selection for classification and diagnosis prediction based on gene expression profile

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Alireza Mehridehnavi

2013-01-01

Conclusion: We have shown that the use of two most significant genes based on their S/N ratios and selection of suitable training samples can lead to classify DLBCL patients with a rather good result. Actually with the aid of mentioned methods we could compensate lack of enough number of patients, improve accuracy of classifying and reduce complication of computations and so running time.

Genes under positive selection in Escherichia coli

DEFF Research Database (Denmark)

Petersen, Lise; Bollback, Jonathan P; Dimmic, Matt

2007-01-01

We used a comparative genomics approach to identify genes that are under positive selection in six strains of Escherichia coli and Shigella flexneri, including five strains that are human pathogens. We find that positive selection targets a wide range of different functions in the E. coli genome......, including cell surface proteins such as beta barrel porins, presumably because of the involvement of these genes in evolutionary arms races with other bacteria, phages, and/or the host immune system. Structural mapping of positively selected sites on trans-membrane beta barrel porins reveals...... that the residues under positive selection occur almost exclusively in the extracellular region of the proteins that are enriched with sites known to be targets of phages, colicins, or the host immune system. More surprisingly, we also find a number of other categories of genes that show very strong evidence...

Translational selection in human: More pronounced in housekeeping genes

KAUST Repository

Ma, Lina

2014-07-10

Background: Translational selection is a ubiquitous and significant mechanism to regulate protein expression in prokaryotes and unicellular eukaryotes. Recent evidence has shown that translational selection is weakly operative in highly expressed genes in human and other vertebrates. However, it remains unclear whether translational selection acts differentially on human genes depending on their expression patterns.Results: Here we report that human housekeeping (HK) genes that are strictly defined as genes that are expressed ubiquitously and consistently in most or all tissues, are under stronger translational selection.Conclusions: These observations clearly show that translational selection is also closely associated with expression pattern. Our results suggest that human HK genes are more efficiently and/or accurately translated into proteins, which will inevitably open up a new understanding of HK genes and the regulation of gene expression.Reviewers: This article was reviewed by Yuan Yuan, Baylor College of Medicine; Han Liang, University of Texas MD Anderson Cancer Center (nominated by Dr Laura Landweber) Eugene Koonin, NCBI, NLM, NIH, United States of America Sandor Pongor, International Centre for Genetic Engineering and biotechnology (ICGEB), Italy. © 2014 Ma et al.; licensee BioMed Central Ltd.

Gene expression network reconstruction by convex feature selection when incorporating genetic perturbations.

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Benjamin A Logsdon

Full Text Available Cellular gene expression measurements contain regulatory information that can be used to discover novel network relationships. Here, we present a new algorithm for network reconstruction powered by the adaptive lasso, a theoretically and empirically well-behaved method for selecting the regulatory features of a network. Any algorithms designed for network discovery that make use of directed probabilistic graphs require perturbations, produced by either experiments or naturally occurring genetic variation, to successfully infer unique regulatory relationships from gene expression data. Our approach makes use of appropriately selected cis-expression Quantitative Trait Loci (cis-eQTL, which provide a sufficient set of independent perturbations for maximum network resolution. We compare the performance of our network reconstruction algorithm to four other approaches: the PC-algorithm, QTLnet, the QDG algorithm, and the NEO algorithm, all of which have been used to reconstruct directed networks among phenotypes leveraging QTL. We show that the adaptive lasso can outperform these algorithms for networks of ten genes and ten cis-eQTL, and is competitive with the QDG algorithm for networks with thirty genes and thirty cis-eQTL, with rich topologies and hundreds of samples. Using this novel approach, we identify unique sets of directed relationships in Saccharomyces cerevisiae when analyzing genome-wide gene expression data for an intercross between a wild strain and a lab strain. We recover novel putative network relationships between a tyrosine biosynthesis gene (TYR1, and genes involved in endocytosis (RCY1, the spindle checkpoint (BUB2, sulfonate catabolism (JLP1, and cell-cell communication (PRM7. Our algorithm provides a synthesis of feature selection methods and graphical model theory that has the potential to reveal new directed regulatory relationships from the analysis of population level genetic and gene expression data.

Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

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Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

2016-01-15

As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species. Copyright © 2015 Elsevier B.V. All rights reserved.

Construction of human antibody gene libraries and selection of antibodies by phage display.

Science.gov (United States)

Frenzel, André; Kügler, Jonas; Wilke, Sonja; Schirrmann, Thomas; Hust, Michael

2014-01-01

Antibody phage display is the most commonly used in vitro selection technology and has yielded thousands of useful antibodies for research, diagnostics, and therapy.The prerequisite for successful generation and development of human recombinant antibodies using phage display is the construction of a high-quality antibody gene library. Here, we describe the methods for the construction of human immune and naive scFv gene libraries.The success also depends on the panning strategy for the selection of binders from these libraries. In this article, we describe a panning strategy that is high-throughput compatible and allows parallel selection in microtiter plates.

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

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Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

2009-01-01

Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

Positive selection on gene expression in the human brain

DEFF Research Database (Denmark)

Khaitovich, Philipp; Tang, Kun; Franz, Henriette

2006-01-01

Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

A GMM-IG framework for selecting genes as expression panel biomarkers.

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Wang, Mingyi; Chen, Jake Y

2010-01-01

The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies. We developed a new framework, Gaussian Mixture Modeling-Coupled Information Gain (GMM-IG). In this framework, we first apply a two-component Gaussian mixture model (GMM) to estimate the conditional probability distributions of gene expression data between two different types of samples, for example, normal versus cancer. An expectation-maximization algorithm is then used to estimate the maximum likelihood parameters of a mixture of two Gaussian models in the feature space and determine the underlying expression levels of genes. Gene expression results from different studies are discretized, based on GMM estimations and then unified. Significantly differentially-expressed genes are filtered and assessed with information gain (IG) measures. DNA microarray experimental data for lung cancers from three different prior studies was processed using the new GMM-IG method. Target gene markers from a gene expression panel were selected and compared with several conventional computational biomarker data analysis methods. GMM-IG showed consistently high accuracy for several classification assessments. A high reproducibility of gene selection results was also determined from statistical validations. Our study shows that the GMM-IG framework can overcome poor reliability issues from single-study DNA microarray experiment while maintaining high accuracies by combining true signals from multiple studies. We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

Directory of Open Access Journals (Sweden)

Nisrine Jrad

2009-01-01

rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers.

When natural selection gives gene function the cold shoulder.

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Cutter, Asher D; Jovelin, Richard

2015-11-01

It is tempting to invoke organismal selection as perpetually optimizing the function of any given gene. However, natural selection can drive genic functional change without improvement of biochemical activity, even to the extinction of gene activity. Detrimental mutations can creep in owing to linkage with other selectively favored loci. Selection can promote functional degradation, irrespective of genetic drift, when adaptation occurs by loss of gene function. Even stabilizing selection on a trait can lead to divergence of the underlying molecular constituents. Selfish genetic elements can also proliferate independent of any functional benefits to the host genome. Here we review the logic and evidence for these diverse processes acting in genome evolution. This collection of distinct evolutionary phenomena - while operating through easily understandable mechanisms - all contribute to the seemingly counterintuitive notion that maintenance or improvement of a gene's biochemical function sometimes do not determine its evolutionary fate. © 2015 WILEY Periodicals, Inc.

A general method for identifying major hybrid male sterility genes in Drosophila.

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Zeng, L W; Singh, R S

1995-10-01

The genes responsible for hybrid male sterility in species crosses are usually identified by introgressing chromosome segments, monitored by visible markers, between closely related species by continuous backcrosses. This commonly used method, however, suffers from two problems. First, it relies on the availability of markers to monitor the introgressed regions and so the portion of the genome examined is limited to the marked regions. Secondly, the introgressed regions are usually large and it is impossible to tell if the effects of the introgressed regions are the result of single (or few) major genes or many minor genes (polygenes). Here we introduce a simple and general method for identifying putative major hybrid male sterility genes which is free of these problems. In this method, the actual hybrid male sterility genes (rather than markers), or tightly linked gene complexes with large effects, are selectively introgressed from one species into the background of another species by repeated backcrosses. This is performed by selectively backcrossing heterozygous (for hybrid male sterility gene or genes) females producing fertile and sterile sons in roughly equal proportions to males of either parental species. As no marker gene is required for this procedure, this method can be used with any species pairs that produce unisexual sterility. With the application of this method, a small X chromosome region of Drosophila mauritiana which produces complete hybrid male sterility (aspermic testes) in the background of D. simulans was identified. Recombination analysis reveals that this region contains a second major hybrid male sterility gene linked to the forked locus located at either 62.7 +/- 0.66 map units or at the centromere region of the X chromosome of D. mauritiana.

Ageing Drosophila selected for longevity retain a young gene expression profile

DEFF Research Database (Denmark)

Sarup, Pernille Merete

and longevity selected lines. Among the latter genes we found a clear overrepresentation of genes involved in immune functions supporting the hypothesis of the life shortening effect of an overactive immune system (inflammaging). Eighty-four genes were differentially expressed at the same physiological age...... between control and longevity selected lines, and the overlap between the same chronological and physiological age gene lists counted 40 candidate genes for increased longevity. Among these were genes with functions in starvation resistance, a regulator of immune responses and several genes which have......  We have investigated how the gene-expression profile of longevity selected lines of Drosophila melanogaster differed from control lines in young, middle-aged and old male flies. 530 genes were differentially expressed between selected and control flies at the same chronological age. We used...

Cytogenetic analysis and mapping of leaf rust resistance in Aegilops speltoides Tausch derived bread wheat line Selection2427 carrying putative gametocidal gene(s).

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Niranjana, M; Vinod; Sharma, J B; Mallick, Niharika; Tomar, S M S; Jha, S K

2017-12-01

Leaf rust (Puccinia triticina) is a major biotic stress affecting wheat yields worldwide. Host-plant resistance is the best method for controlling leaf rust. Aegilops speltoides is a good source of resistance against wheat rusts. To date, five Lr genes, Lr28, Lr35, Lr36, Lr47, and Lr51, have been transferred from Ae. speltoides to bread wheat. In Selection2427, a bread wheat introgresed line with Ae. speltoides as the donor parent, a dominant gene for leaf rust resistance was mapped to the long arm of chromosome 3B (LrS2427). None of the Lr genes introgressed from Ae. speltoides have been mapped to chromosome 3B. Since none of the designated seedling leaf rust resistance genes have been located on chromosome 3B, LrS2427 seems to be a novel gene. Selection2427 showed a unique property typical of gametocidal genes, that when crossed to other bread wheat cultivars, the F 1 showed partial pollen sterility and poor seed setting, whilst Selection2427 showed reasonable male and female fertility. Accidental co-transfer of gametocidal genes with LrS2427 may have occurred in Selection2427. Though LrS2427 did not show any segregation distortion and assorted independently of putative gametocidal gene(s), its utilization will be difficult due to the selfish behavior of gametocidal genes.

GAP1, a novel selection and counter-selection marker for multiple gene disruptions in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Regenberg, Birgitte; Hansen, J.

2000-01-01

the GAP1 gene. This is caused by recombination between two Salmonella typuimurium hisG direct repeats embracing GAP1, and will result in a sub-population of gap1 cells. Such cells are selected on a medium containing D-histidine, and may subsequently be used for a second gene disruption. Hence, multiple...... flanked by short (60 bp) stretches of the gene in question. Through homologous recombination, the cassette will integrate into the target gene, which is thus replaced by GAP1, and mutants are selected for on minimal L-citrulline medium. When propagated under non-selective conditions, some cells will lose...... gene disruptions can be made fast, cheaply and easily in a gap1 strain, with two positive selection steps for each disruption. Copyright (C) 2000 John Wiley & Sons, Ltd....

Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

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Noma, Hisashi; Matsui, Shigeyuki

2013-05-20

The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

A comparative study of three different gene expression analysis methods.

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Choe, Jae Young; Han, Hyung Soo; Lee, Seon Duk; Lee, Hanna; Lee, Dong Eun; Ahn, Jae Yun; Ryoo, Hyun Wook; Seo, Kang Suk; Kim, Jong Kun

2017-12-04

TNF-α regulates immune cells and acts as an endogenous pyrogen. Reverse transcription polymerase chain reaction (RT-PCR) is one of the most commonly used methods for gene expression analysis. Among the alternatives to PCR, loop-mediated isothermal amplification (LAMP) shows good potential in terms of specificity and sensitivity. However, few studies have compared RT-PCR and LAMP for human gene expression analysis. Therefore, in the present study, we compared one-step RT-PCR, two-step RT-LAMP and one-step RT-LAMP for human gene expression analysis. We compared three gene expression analysis methods using the human TNF-α gene as a biomarker from peripheral blood cells. Total RNA from the three selected febrile patients were subjected to the three different methods of gene expression analysis. In the comparison of three gene expression analysis methods, the detection limit of both one-step RT-PCR and one-step RT-LAMP were the same, while that of two-step RT-LAMP was inferior. One-step RT-LAMP takes less time, and the experimental result is easy to determine. One-step RT-LAMP is a potentially useful and complementary tool that is fast and reasonably sensitive. In addition, one-step RT-LAMP could be useful in environments lacking specialized equipment or expertise.

Positive-negative-selection-mediated gene targeting in rice

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Zenpei eShimatani

2015-01-01

Full Text Available Gene targeting (GT refers to the designed modification of genomic sequence(s through homologous recombination (HR. GT is a powerful tool both for the study of gene function and for molecular breeding. However, in transformation of higher plants, non-homologous end joining (NHEJ occurs overwhelmingly in somatic cells, masking HR-mediated GT. Positive-negative selection (PNS is an approach for finding HR-mediated GT events because it can eliminate NHEJ effectively by expression of a negative-selection marker gene. In rice—a major crop worldwide—reproducible PNS-mediated GT of endogenous genes has now been successfully achieved. The procedure is based on strong PNS using diphtheria toxin A-fragment as a negative marker, and has succeeded in the directed modification of several endogenous rice genes in various ways. In addition to gene knock-outs and knock-ins, a nucleotide substitution in a target gene was also achieved recently. This review presents a summary of the development of the rice PNS system, highlighting its advantages. Different types of gene modification and gene editing aimed at developing new plant breeding technology (NPBT based on PNS are discussed.

Altering the selection capabilities of common cloning vectors via restriction enzyme mediated gene disruption

Science.gov (United States)

2013-01-01

Background The cloning of gene sequences forms the basis for many molecular biological studies. One important step in the cloning process is the isolation of bacterial transformants carrying vector DNA. This involves a vector-encoded selectable marker gene, which in most cases, confers resistance to an antibiotic. However, there are a number of circumstances in which a different selectable marker is required or may be preferable. Such situations can include restrictions to host strain choice, two phase cloning experiments and mutagenesis experiments, issues that result in additional unnecessary cloning steps, in which the DNA needs to be subcloned into a vector with a suitable selectable marker. Results We have used restriction enzyme mediated gene disruption to modify the selectable marker gene of a given vector by cloning a different selectable marker gene into the original marker present in that vector. Cloning a new selectable marker into a pre-existing marker was found to change the selection phenotype conferred by that vector, which we were able to demonstrate using multiple commonly used vectors and multiple resistance markers. This methodology was also successfully applied not only to cloning vectors, but also to expression vectors while keeping the expression characteristics of the vector unaltered. Conclusions Changing the selectable marker of a given vector has a number of advantages and applications. This rapid and efficient method could be used for co-expression of recombinant proteins, optimisation of two phase cloning procedures, as well as multiple genetic manipulations within the same host strain without the need to remove a pre-existing selectable marker in a previously genetically modified strain. PMID:23497512

A novel mutual information-based Boolean network inference method from time-series gene expression data.

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Shohag Barman

Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.

Selective Constraints on Coding Sequences of Nervous System Genes Are a Major Determinant of Duplicate Gene Retention in Vertebrates.

Science.gov (United States)

Roux, Julien; Liu, Jialin; Robinson-Rechavi, Marc

2017-11-01

The evolutionary history of vertebrates is marked by three ancient whole-genome duplications: two successive rounds in the ancestor of vertebrates, and a third one specific to teleost fishes. Biased loss of most duplicates enriched the genome for specific genes, such as slow evolving genes, but this selective retention process is not well understood. To understand what drives the long-term preservation of duplicate genes, we characterized duplicated genes in terms of their expression patterns. We used a new method of expression enrichment analysis, TopAnat, applied to in situ hybridization data from thousands of genes from zebrafish and mouse. We showed that the presence of expression in the nervous system is a good predictor of a higher rate of retention of duplicate genes after whole-genome duplication. Further analyses suggest that purifying selection against the toxic effects of misfolded or misinteracting proteins, which is particularly strong in nonrenewing neural tissues, likely constrains the evolution of coding sequences of nervous system genes, leading indirectly to the preservation of duplicate genes after whole-genome duplication. Whole-genome duplications thus greatly contributed to the expansion of the toolkit of genes available for the evolution of profound novelties of the nervous system at the base of the vertebrate radiation. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A hybrid computational method for the discovery of novel reproduction-related genes.

Science.gov (United States)

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

"Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

Science.gov (United States)

Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

2008-02-01

The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

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Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

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Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

2013-01-01

DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

Genes under positive selection in a model plant pathogenic fungus, Botrytis.

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Aguileta, Gabriela; Lengelle, Juliette; Chiapello, Hélène; Giraud, Tatiana; Viaud, Muriel; Fournier, Elisabeth; Rodolphe, François; Marthey, Sylvain; Ducasse, Aurélie; Gendrault, Annie; Poulain, Julie; Wincker, Patrick; Gout, Lilian

2012-07-01

The rapid evolution of particular genes is essential for the adaptation of pathogens to new hosts and new environments. Powerful methods have been developed for detecting targets of selection in the genome. Here we used divergence data to compare genes among four closely related fungal pathogens adapted to different hosts to elucidate the functions putatively involved in adaptive processes. For this goal, ESTs were sequenced in the specialist fungal pathogens Botrytis tulipae and Botrytis ficariarum, and compared with genome sequences of Botrytis cinerea and Sclerotinia sclerotiorum, responsible for diseases on over 200 plant species. A maximum likelihood-based analysis of 642 predicted orthologs detected 21 genes showing footprints of positive selection. These results were validated by resequencing nine of these genes in additional Botrytis species, showing they have also been rapidly evolving in other related species. Twenty of the 21 genes had not previously been identified as pathogenicity factors in B. cinerea, but some had functions related to plant-fungus interactions. The putative functions were involved in respiratory and energy metabolism, protein and RNA metabolism, signal transduction or virulence, similarly to what was detected in previous studies using the same approach in other pathogens. Mutants of B. cinerea were generated for four of these genes as a first attempt to elucidate their functions. Copyright © 2012 Elsevier B.V. All rights reserved.

Construction and applications of exon-trapping gene-targeting vectors with a novel strategy for negative selection.

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Saito, Shinta; Ura, Kiyoe; Kodama, Miho; Adachi, Noritaka

2015-06-30

Targeted gene modification by homologous recombination provides a powerful tool for studying gene function in cells and animals. In higher eukaryotes, non-homologous integration of targeting vectors occurs several orders of magnitude more frequently than does targeted integration, making the gene-targeting technology highly inefficient. For this reason, negative-selection strategies have been employed to reduce the number of drug-resistant clones associated with non-homologous vector integration, particularly when artificial nucleases to introduce a DNA break at the target site are unavailable or undesirable. As such, an exon-trap strategy using a promoterless drug-resistance marker gene provides an effective way to counterselect non-homologous integrants. However, constructing exon-trapping targeting vectors has been a time-consuming and complicated process. By virtue of highly efficient att-mediated recombination, we successfully developed a simple and rapid method to construct plasmid-based vectors that allow for exon-trapping gene targeting. These exon-trap vectors were useful in obtaining correctly targeted clones in mouse embryonic stem cells and human HT1080 cells. Most importantly, with the use of a conditionally cytotoxic gene, we further developed a novel strategy for negative selection, thereby enhancing the efficiency of counterselection for non-homologous integration of exon-trap vectors. Our methods will greatly facilitate exon-trapping gene-targeting technologies in mammalian cells, particularly when combined with the novel negative selection strategy.

Reference gene selection for molecular studies of dormancy in wild oat (Avena fatua L. caryopses by RT-qPCR method.

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Izabela Ruduś

Full Text Available Molecular studies of primary and secondary dormancy in Avena fatua L., a serious weed of cereal and other crops, are intended to reveal the species-specific details of underlying molecular mechanisms which in turn may be useable in weed management. Among others, quantitative real-time PCR (RT-qPCR data of comparative gene expression analysis may give some insight into the involvement of particular wild oat genes in dormancy release, maintenance or induction by unfavorable conditions. To assure obtaining biologically significant results using this method, the expression stability of selected candidate reference genes in different data subsets was evaluated using four statistical algorithms i.e. geNorm, NormFinder, Best Keeper and ΔCt method. Although some discrepancies in their ranking outputs were noticed, evidently two ubiquitin-conjugating enzyme homologs, AfUBC1 and AfUBC2, as well as one homolog of glyceraldehyde 3-phosphate dehydrogenase AfGAPDH1 and TATA-binding protein AfTBP2 appeared as more stably expressed than AfEF1a (translation elongation factor 1α, AfGAPDH2 or the least stable α-tubulin homolog AfTUA1 in caryopses and seedlings of A. fatua. Gene expression analysis of a dormancy-related wild oat transcription factor VIVIPAROUS1 (AfVP1 allowed for a validation of candidate reference genes performance. Based on the obtained results it can be recommended that the normalization factor calculated as a geometric mean of Cq values of AfUBC1, AfUBC2 and AfGAPDH1 would be optimal for RT-qPCR results normalization in the experiments comprising A. fatua caryopses of different dormancy status.

Reference gene selection for molecular studies of dormancy in wild oat (Avena fatua L.) caryopses by RT-qPCR method.

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Ruduś, Izabela; Kępczyński, Jan

2018-01-01

Molecular studies of primary and secondary dormancy in Avena fatua L., a serious weed of cereal and other crops, are intended to reveal the species-specific details of underlying molecular mechanisms which in turn may be useable in weed management. Among others, quantitative real-time PCR (RT-qPCR) data of comparative gene expression analysis may give some insight into the involvement of particular wild oat genes in dormancy release, maintenance or induction by unfavorable conditions. To assure obtaining biologically significant results using this method, the expression stability of selected candidate reference genes in different data subsets was evaluated using four statistical algorithms i.e. geNorm, NormFinder, Best Keeper and ΔCt method. Although some discrepancies in their ranking outputs were noticed, evidently two ubiquitin-conjugating enzyme homologs, AfUBC1 and AfUBC2, as well as one homolog of glyceraldehyde 3-phosphate dehydrogenase AfGAPDH1 and TATA-binding protein AfTBP2 appeared as more stably expressed than AfEF1a (translation elongation factor 1α), AfGAPDH2 or the least stable α-tubulin homolog AfTUA1 in caryopses and seedlings of A. fatua. Gene expression analysis of a dormancy-related wild oat transcription factor VIVIPAROUS1 (AfVP1) allowed for a validation of candidate reference genes performance. Based on the obtained results it can be recommended that the normalization factor calculated as a geometric mean of Cq values of AfUBC1, AfUBC2 and AfGAPDH1 would be optimal for RT-qPCR results normalization in the experiments comprising A. fatua caryopses of different dormancy status.

A Cancer Gene Selection Algorithm Based on the K-S Test and CFS

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Qiang Su

2017-01-01

Full Text Available Background. To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S test and correlation-based feature selection (CFS principles. The algorithm selects distinguished genes first using the K-S test, and then, it uses CFS to select genes from those selected by the K-S test. Results. We adopted support vector machines (SVM as the classification tool and used the criteria of accuracy to evaluate the performance of the classifiers on the selected gene subsets. This approach compared the proposed gene subset selection algorithm with the K-S test, CFS, minimum-redundancy maximum-relevancy (mRMR, and ReliefF algorithms. The average experimental results of the aforementioned gene selection algorithms for 5 gene expression datasets demonstrate that, based on accuracy, the performance of the new K-S and CFS-based algorithm is better than those of the K-S test, CFS, mRMR, and ReliefF algorithms. Conclusions. The experimental results show that the K-S test-CFS gene selection algorithm is a very effective and promising approach compared to the K-S test, CFS, mRMR, and ReliefF algorithms.

A scan for positively selected genes in the genomes of humans and chimpanzees.

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Rasmus Nielsen

2005-06-01

Full Text Available Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved in sensory perception or immune defenses. However, the group of genes that show the strongest evidence for positive selection also includes a surprising number of genes involved in tumor suppression and apoptosis, and of genes involved in spermatogenesis. We hypothesize that positive selection in some of these genes may be driven by genomic conflict due to apoptosis during spermatogenesis. Genes with maximal expression in the brain show little or no evidence for positive selection, while genes with maximal expression in the testis tend to be enriched with positively selected genes. Genes on the X chromosome also tend to show an elevated tendency for positive selection. We also present polymorphism data from 20 Caucasian Americans and 19 African Americans for the 50 annotated genes showing the strongest evidence for positive selection. The polymorphism analysis further supports the presence of positive selection in these genes by showing an excess of high-frequency derived nonsynonymous mutations.

Use of Maximum Likelihood-Mixed Models to select stable reference genes: a case of heat stress response in sheep

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Salces Judit

2011-08-01

Full Text Available Abstract Background Reference genes with stable expression are required to normalize expression differences of target genes in qPCR experiments. Several procedures and companion software have been proposed to find the most stable genes. Model based procedures are attractive because they provide a solid statistical framework. NormFinder, a widely used software, uses a model based method. The pairwise comparison procedure implemented in GeNorm is a simpler procedure but one of the most extensively used. In the present work a statistical approach based in Maximum Likelihood estimation under mixed models was tested and compared with NormFinder and geNorm softwares. Sixteen candidate genes were tested in whole blood samples from control and heat stressed sheep. Results A model including gene and treatment as fixed effects, sample (animal, gene by treatment, gene by sample and treatment by sample interactions as random effects with heteroskedastic residual variance in gene by treatment levels was selected using goodness of fit and predictive ability criteria among a variety of models. Mean Square Error obtained under the selected model was used as indicator of gene expression stability. Genes top and bottom ranked by the three approaches were similar; however, notable differences for the best pair of genes selected for each method and the remaining genes of the rankings were shown. Differences among the expression values of normalized targets for each statistical approach were also found. Conclusions Optimal statistical properties of Maximum Likelihood estimation joined to mixed model flexibility allow for more accurate estimation of expression stability of genes under many different situations. Accurate selection of reference genes has a direct impact over the normalized expression values of a given target gene. This may be critical when the aim of the study is to compare expression rate differences among samples under different environmental

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

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Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cartilage-selective genes identified in genome-scale analysis of non-cartilage and cartilage gene expression

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Cohn Zachary A

2007-06-01

Full Text Available Abstract Background Cartilage plays a fundamental role in the development of the human skeleton. Early in embryogenesis, mesenchymal cells condense and differentiate into chondrocytes to shape the early skeleton. Subsequently, the cartilage anlagen differentiate to form the growth plates, which are responsible for linear bone growth, and the articular chondrocytes, which facilitate joint function. However, despite the multiplicity of roles of cartilage during human fetal life, surprisingly little is known about its transcriptome. To address this, a whole genome microarray expression profile was generated using RNA isolated from 18–22 week human distal femur fetal cartilage and compared with a database of control normal human tissues aggregated at UCLA, termed Celsius. Results 161 cartilage-selective genes were identified, defined as genes significantly expressed in cartilage with low expression and little variation across a panel of 34 non-cartilage tissues. Among these 161 genes were cartilage-specific genes such as cartilage collagen genes and 25 genes which have been associated with skeletal phenotypes in humans and/or mice. Many of the other cartilage-selective genes do not have established roles in cartilage or are novel, unannotated genes. Quantitative RT-PCR confirmed the unique pattern of gene expression observed by microarray analysis. Conclusion Defining the gene expression pattern for cartilage has identified new genes that may contribute to human skeletogenesis as well as provided further candidate genes for skeletal dysplasias. The data suggest that fetal cartilage is a complex and transcriptionally active tissue and demonstrate that the set of genes selectively expressed in the tissue has been greatly underestimated.

Gene selection using hybrid binary black hole algorithm and modified binary particle swarm optimization.

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Pashaei, Elnaz; Pashaei, Elham; Aydin, Nizamettin

2018-04-14

In cancer classification, gene selection is an important data preprocessing technique, but it is a difficult task due to the large search space. Accordingly, the objective of this study is to develop a hybrid meta-heuristic Binary Black Hole Algorithm (BBHA) and Binary Particle Swarm Optimization (BPSO) (4-2) model that emphasizes gene selection. In this model, the BBHA is embedded in the BPSO (4-2) algorithm to make the BPSO (4-2) more effective and to facilitate the exploration and exploitation of the BPSO (4-2) algorithm to further improve the performance. This model has been associated with Random Forest Recursive Feature Elimination (RF-RFE) pre-filtering technique. The classifiers which are evaluated in the proposed framework are Sparse Partial Least Squares Discriminant Analysis (SPLSDA); k-nearest neighbor and Naive Bayes. The performance of the proposed method was evaluated on two benchmark and three clinical microarrays. The experimental results and statistical analysis confirm the better performance of the BPSO (4-2)-BBHA compared with the BBHA, the BPSO (4-2) and several state-of-the-art methods in terms of avoiding local minima, convergence rate, accuracy and number of selected genes. The results also show that the BPSO (4-2)-BBHA model can successfully identify known biologically and statistically significant genes from the clinical datasets. Copyright © 2018 Elsevier Inc. All rights reserved.

Rapid and targeted introgression of genes into popular wheat cultivars using marker-assisted background selection.

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Harpinder S Randhawa

Full Text Available A marker-assisted background selection (MABS-based gene introgression approach in wheat (Triticum aestivum L. was optimized, where 97% or more of a recurrent parent genome (RPG can be recovered in just two backcross (BC generations. A four-step MABS method was developed based on 'Plabsim' computer simulations and wheat genome structure information. During empirical optimization of this method, double recombinants around the target gene were selected in a step-wise fashion during the two BC cycles followed by selection for recurrent parent genotype on non-carrier chromosomes. The average spacing between carrier chromosome markers was <4 cM. For non-carrier chromosome markers that flanked each of the 48 wheat gene-rich regions, this distance was approximately 12 cM. Employed to introgress seedling stripe rust (Puccinia striiformis f. sp. tritici resistance gene Yr15 into the spring wheat cultivar 'Zak', marker analysis of 2,187 backcross-derived progeny resulted in the recovery of a BC(2F(2ratio3 plant with 97% of the recurrent parent genome. In contrast, only 82% of the recurrent parent genome was recovered in phenotypically selected BC(4F(7 plants developed without MABS. Field evaluation results from 17 locations indicated that the MABS-derived line was either equal or superior to the recurrent parent for the tested agronomic characteristics. Based on these results, MABS is recommended as a strategy for rapidly introgressing a targeted gene into a wheat genotype in just two backcross generations while recovering 97% or more of the recurrent parent genotype.

A Comparison of Selective Pressures in Plant X-Linked and Autosomal Genes.

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Krasovec, Marc; Nevado, Bruno; Filatov, Dmitry A

2018-05-03

Selection is expected to work differently in autosomal and X-linked genes because of their ploidy difference and the exposure of recessive X-linked mutations to haploid selection in males. However, it is not clear whether these expectations apply to recently evolved sex chromosomes, where many genes retain functional X- and Y-linked gametologs. We took advantage of the recently evolved sex chromosomes in the plant Silene latifolia and its closely related species to compare the selective pressures between hemizygous and non-hemizygous X-linked genes as well as between X-linked genes and autosomal genes. Our analysis, based on over 1000 genes, demonstrated that, similar to animals, X-linked genes in Silene evolve significantly faster than autosomal genes—the so-called faster-X effect. Contrary to expectations, faster-X divergence was detectable only for non-hemizygous X-linked genes. Our phylogeny-based analyses of selection revealed no evidence for faster adaptation in X-linked genes compared to autosomal genes. On the other hand, partial relaxation of purifying selection was apparent on the X-chromosome compared to the autosomes, consistent with a smaller genetic diversity in S. latifolia X-linked genes (π x = 0.016; π aut = 0.023). Thus, the faster-X divergence in S. latifolia appears to be a consequence of the smaller effective population size rather than of a faster adaptive evolution on the X-chromosome. We argue that this may be a general feature of “young” sex chromosomes, where the majority of X-linked genes are not hemizygous, preventing haploid selection in heterogametic sex.

Evidence for natural selection at the melanocortin-3 receptor gene in European and African populations.

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Yoshiuchi, Issei

2016-08-01

Obesity is increasing steadily in worldwide prevalence and is known to cause serious health problems in association with type 2 diabetes mellitus (T2DM), including hypertension, stroke, and cardiovascular diseases. According to the thrifty gene hypothesis, the natural selection of obesity-related genes is important during feast and famine because they control body weight and fat levels. Past human adaptations to environmental changes in food supply, lifestyle, and geography may have influenced the selection of genes associated with the metabolism of glucose, lipids, and energy. The melanocortin-3 receptor gene (MC3R) is associated with obesity, with MC3R-deficient mice showing increased fat mass. MC3R variations are also linked with childhood obesity and insulin resistance. Here, we aimed to uncover evidence of selection at MC3R. We performed a three-step method to detect selection at MC3R using HapMap population data. We used Wright's F statistics as a measure of population differentiation, the long-range haplotype test to identify extended haplotypes, and the integrated haplotype score (iHS) to detect selection at MC3R. We observed high population differentiation between European and African populations at two MC3R childhood obesity- and insulin resistance-associated single-nucleotide polymorphisms (rs3746619 and rs3827103) using Wright's F statistics. The iHS revealed evidence of natural selection at MC3R. These findings provide evidence for natural selection at MC3R. Further investigation is warranted into adaptive evolution at T2DM- and obesity-associated genes.

Selection on the Major Color Gene Melanocortin-1-Receptor Shaped the Evolution of the Melanocortin System Genes

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Linda Dib

2017-12-01

Full Text Available Modular genetic systems and networks have complex evolutionary histories shaped by selection acting on single genes as well as on their integrated function within the network. However, uncovering molecular coevolution requires the detection of coevolving sites in sequences. Detailed knowledge of the functions of each gene in the system is also necessary to identify the selective agents driving coevolution. Using recently developed computational tools, we investigated the effect of positive selection on the coevolution of ten major genes in the melanocortin system, responsible for multiple physiological functions and human diseases. Substitutions driven by positive selection at the melanocortin-1-receptor (MC1R induced more coevolutionary changes on the system than positive selection on other genes in the system. Contrarily, selection on the highly pleiotropic POMC gene, which orchestrates the activation of the different melanocortin receptors, had the lowest coevolutionary influence. MC1R and possibly its main function, melanin pigmentation, seems to have influenced the evolution of the melanocortin system more than functions regulated by MC2-5Rs such as energy homeostasis, glucocorticoid-dependent stress and anti-inflammatory responses. Although replication in other regulatory systems is needed, this suggests that single functional aspects of a genetic network or system can be of higher importance than others in shaping coevolution among the genes that integrate it.

When Is Hub Gene Selection Better than Standard Meta-Analysis?

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Langfelder, Peter; Mischel, Paul S.; Horvath, Steve

2013-01-01

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to

When is hub gene selection better than standard meta-analysis?

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Peter Langfelder

Full Text Available Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data. Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA in three comprehensive and unbiased empirical studies: (1 Finding genes predictive of lung cancer survival, (2 finding methylation markers related to age, and (3 finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1. However, standard meta-analysis methods perform as good as (if not better than a consensus network approach in terms of validation success (criterion 2. The article also reports a comparison of meta-analysis techniques

When is hub gene selection better than standard meta-analysis?

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Langfelder, Peter; Mischel, Paul S; Horvath, Steve

2013-01-01

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to

Positive selection on MHC class II DRB and DQB genes in the bank vole (Myodes glareolus).

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Scherman, Kristin; Råberg, Lars; Westerdahl, Helena

2014-05-01

The major histocompatibility complex (MHC) class IIB genes show considerable sequence similarity between loci. The MHC class II DQB and DRB genes are known to exhibit a high level of polymorphism, most likely maintained by parasite-mediated selection. Studies of the MHC in wild rodents have focused on DRB, whilst DQB has been given much less attention. Here, we characterised DQB genes in Swedish bank voles Myodes glareolus, using full-length transcripts. We then designed primers that specifically amplify exon 2 from DRB (202 bp) and DQB (205 bp) and investigated molecular signatures of natural selection on DRB and DQB alleles. The presence of two separate gene clusters was confirmed using BLASTN and phylogenetic analysis, where our seven transcripts clustered according to either DQB or DRB homologues. These gene clusters were again confirmed on exon 2 data from 454-amplicon sequencing. Our DRB primers amplify a similar number of alleles per individual as previously published DRB primers, though our reads are longer. Traditional d N/d S analyses of DRB sequences in the bank vole have not found a conclusive signal of positive selection. Using a more advanced substitution model (the Kumar method) we found positive selection in the peptide binding region (PBR) of both DRB and DQB genes. Maximum likelihood models of codon substitutions detected positively selected sites located in the PBR of both DQB and DRB. Interestingly, these analyses detected at least twice as many positively selected sites in DQB than DRB, suggesting that DQB has been under stronger positive selection than DRB over evolutionary time.

A comparative study of covariance selection models for the inference of gene regulatory networks.

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Stifanelli, Patrizia F; Creanza, Teresa M; Anglani, Roberto; Liuzzi, Vania C; Mukherjee, Sayan; Schena, Francesco P; Ancona, Nicola

2013-10-01

The inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. In this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) 'ℓ(2C)' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ℓ(2C) outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. Software implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip. Copyright © 2013 The Authors. Published by

A large-scale benchmark of gene prioritization methods.

Science.gov (United States)

Guala, Dimitri; Sonnhammer, Erik L L

2017-04-21

In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. While prospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate the performance of gene prioritization tools, a strategy for retrospective benchmarking has been missing, and new tools usually only provide internal validations. The Gene Ontology(GO) contains genes clustered around annotation terms. This intrinsic property of GO can be utilized in construction of robust benchmarks, objective to the problem domain. We demonstrate how this can be achieved for network-based gene prioritization tools, utilizing the FunCoup network. We use cross-validation and a set of appropriate performance measures to compare state-of-the-art gene prioritization algorithms: three based on network diffusion, NetRank and two implementations of Random Walk with Restart, and MaxLink that utilizes network neighborhood. Our benchmark suite provides a systematic and objective way to compare the multitude of available and future gene prioritization tools, enabling researchers to select the best gene prioritization tool for the task at hand, and helping to guide the development of more accurate methods.

Whole-gene positive selection, elevated synonymous substitution rates, duplication, and indel evolution of the chloroplast clpP1 gene.

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Per Erixon

Full Text Available BACKGROUND: Synonymous DNA substitution rates in the plant chloroplast genome are generally relatively slow and lineage dependent. Non-synonymous rates are usually even slower due to purifying selection acting on the genes. Positive selection is expected to speed up non-synonymous substitution rates, whereas synonymous rates are expected to be unaffected. Until recently, positive selection has seldom been observed in chloroplast genes, and large-scale structural rearrangements leading to gene duplications are hitherto supposed to be rare. METHODOLOGY/PRINCIPLE FINDINGS: We found high substitution rates in the exons of the plastid clpP1 gene in Oenothera (the Evening Primrose family and three separate lineages in the tribe Sileneae (Caryophyllaceae, the Carnation family. Introns have been lost in some of the lineages, but where present, the intron sequences have substitution rates similar to those found in other introns of their genomes. The elevated substitution rates of clpP1 are associated with statistically significant whole-gene positive selection in three branches of the phylogeny. In two of the lineages we found multiple copies of the gene. Neighboring genes present in the duplicated fragments do not show signs of elevated substitution rates or positive selection. Although non-synonymous substitutions account for most of the increase in substitution rates, synonymous rates are also markedly elevated in some lineages. Whereas plant clpP1 genes experiencing negative (purifying selection are characterized by having very conserved lengths, genes under positive selection often have large insertions of more or less repetitive amino acid sequence motifs. CONCLUSIONS/SIGNIFICANCE: We found positive selection of the clpP1 gene in various plant lineages to correlated with repeated duplication of the clpP1 gene and surrounding regions, repetitive amino acid sequences, and increase in synonymous substitution rates. The present study sheds light on the

Selection on meiosis genes in diploid and tetraploid Arabidopsis arenosa.

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Wright, Kevin M; Arnold, Brian; Xue, Katherine; Šurinová, Maria; O'Connell, Jeremy; Bomblies, Kirsten

2015-04-01

Meiotic chromosome segregation is critical for fertility across eukaryotes, and core meiotic processes are well conserved even between kingdoms. Nevertheless, recent work in animals has shown that at least some meiosis genes are highly diverse or strongly differentiated among populations. What drives this remains largely unknown. We previously showed that autotetraploid Arabidopsis arenosa evolved stable meiosis, likely through reduced crossover rates, and that associated with this there is strong evidence for selection in a subset of meiosis genes known to affect axis formation, synapsis, and crossover frequency. Here, we use genome-wide data to study the molecular evolution of 70 meiosis genes in a much wider sample of A. arenosa. We sample the polyploid lineage, a diploid lineage from the Carpathian Mountains, and a more distantly related diploid lineage from the adjacent, but biogeographically distinct Pannonian Basin. We find that not only did selection act on meiosis genes in the polyploid lineage but also independently on a smaller subset of meiosis genes in Pannonian diploids. Functionally related genes are targeted by selection in these distinct contexts, and in two cases, independent sweeps occurred in the same loci. The tetraploid lineage has sustained selection on more genes, has more amino acid changes in each, and these more often affect conserved or potentially functional sites. We hypothesize that Pannonian diploid and tetraploid A. arenosa experienced selection on structural proteins that mediate sister chromatid cohesion, the formation of meiotic chromosome axes, and synapsis, likely for different underlying reasons. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Novel ‘Gene Insertion/Marker Out’ (GIMO) Method for Transgene Expression and Gene Complementation in Rodent Malaria Parasites

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Sajid, Mohammed; Chevalley-Maurel, Séverine; Ramesar, Jai; Klop, Onny; Franke-Fayard, Blandine M. D.; Janse, Chris J.; Khan, Shahid M.

2011-01-01

Research on the biology of malaria parasites has greatly benefited from the application of reverse genetic technologies, in particular through the analysis of gene deletion mutants and studies on transgenic parasites that express heterologous or mutated proteins. However, transfection in Plasmodium is limited by the paucity of drug-selectable markers that hampers subsequent genetic modification of the same mutant. We report the development of a novel ‘gene insertion/marker out’ (GIMO) method for two rodent malaria parasites, which uses negative selection to rapidly generate transgenic mutants ready for subsequent modifications. We have created reference mother lines for both P. berghei ANKA and P. yoelii 17XNL that serve as recipient parasites for GIMO-transfection. Compared to existing protocols GIMO-transfection greatly simplifies and speeds up the generation of mutants expressing heterologous proteins, free of drug-resistance genes, and requires far fewer laboratory animals. In addition we demonstrate that GIMO-transfection is also a simple and fast method for genetic complementation of mutants with a gene deletion or mutation. The implementation of GIMO-transfection procedures should greatly enhance Plasmodium reverse-genetic research. PMID:22216235

Sexual selection, genetic conflict, selfish genes, and the atypical patterns of gene expression in spermatogenic cells.

Science.gov (United States)

Kleene, Kenneth C

2005-01-01

This review proposes that the peculiar patterns of gene expression in spermatogenic cells are the consequence of powerful evolutionary forces known as sexual selection. Sexual selection is generally characterized by intense competition of males for females, an enormous variety of the strategies to maximize male reproductive success, exaggerated male traits at all levels of biological organization, co-evolution of sexual traits in males and females, and conflict between the sexual advantage of the male trait and the reproductive fitness of females and the individual fitness of both sexes. In addition, spermatogenesis is afflicted by selfish genes that promote their transmission to progeny while causing deleterious effects. Sexual selection, selfish genes, and genetic conflict provide compelling explanations for many atypical features of gene expression in spermatogenic cells including the gross overexpression of certain mRNAs, transcripts encoding truncated proteins that cannot carry out basic functions of the proteins encoded by the same genes in somatic cells, the large number of gene families containing paralogous genes encoding spermatogenic cell-specific isoforms, the large number of testis-cancer-associated genes that are expressed only in spermatogenic cells and malignant cells, and the overbearing role of Sertoli cells in regulating the number and quality of spermatozoa.

Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don.

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Xiao, Zheng; Sun, Xiaobo; Liu, Xiaoqing; Li, Chang; He, Lisi; Chen, Shangping; Su, Jiale

2016-01-01

The quantitative real-time polymerase chain reaction (qRT-PCR) approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder, and BestKeeper. The results showed that EF1- α (elongation factor 1-alpha), 18S (18s ribosomal RNA), and RPL3 (ribosomal protein L3) were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin ( TUB ) was the least stable. ACT5 (actin), RPL3 , 18S , and EF1- α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle . Furthermore, the expression profiles of RmPSY (phytoene synthase) and RmPDS (phytoene dehydrogenase) were assessed using EF1- α, 18S , ACT5 , RPL3 , and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle .

Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don

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Zheng Xiao

2016-10-01

Full Text Available The quantitative real-time polymerase chain reaction (qRT-PCR approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder and BestKeeper. The results showed that EF1-α (elongation factor 1-alpha, 18S (18s ribosomal RNA and RPL3 (ribosomal protein L3 were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin (TUB was the least stable. ACT5 (actin, RPL3, 18S and EF1-α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle. Furthermore, the expression profiles of RmPSY (phytoene synthase and RmPDS (phytoene dehydrogenase were assessed using EF1-α, 18S, ACT5, and RPL3 and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle.

Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

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Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

2015-01-01

Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

Pearl millet transformation system using the positive selectable marker gene phosphomannose isomerase

CSIR Research Space (South Africa)

O'Kennedy, MM

2004-04-01

Full Text Available of the transgene. Similar to results obtained from previous studies with maize and wheat, the manA gene was shown to be a superior selectable marker gene for improving transformation efficiencies when compared to antibiotic or herbicide selectable marker genes....

A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

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Qihua Tan

2009-01-01

Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

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Sapna Kumari

Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

Selection for the compactness of highly expressed genes in Gallus gallus

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Zhou Ming

2010-05-01

Full Text Available Abstract Background Coding sequence (CDS length, gene size, and intron length vary within a genome and among genomes. Previous studies in diverse organisms, including human, D. Melanogaster, C. elegans, S. cerevisiae, and Arabidopsis thaliana, indicated that there are negative relationships between expression level and gene size, CDS length as well as intron length. Different models such as selection for economy model, genomic design model, and mutational bias hypotheses have been proposed to explain such observation. The debate of which model is a superior one to explain the observation has not been settled down. The chicken (Gallus gallus is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. As D. Melanogaster, chicken has a larger effective population size, selection for chicken genome is expected to be more effective in increasing protein synthesis efficiency. Therefore, in this study the chicken was used as a model organism to elucidate the interaction between gene features and expression pattern upon selection pressure. Results Based on different technologies, we gathered expression data for nuclear protein coding, single-splicing genes from Gallus gallus genome and compared them with gene parameters. We found that gene size, CDS length, first intron length, average intron length, and total intron length are negatively correlated with expression level and expression breadth significantly. The tissue specificity is positively correlated with the first intron length but negatively correlated with the average intron length, and not correlated with the CDS length and protein domain numbers. Comparison analyses showed that ubiquitously expressed genes and narrowly expressed genes with the similar expression levels do not differ in compactness. Our data provided evidence that the genomic design model can not, at least in part, explain our observations. We grouped all somatic-tissue-specific genes

Selection of appropriate reference genes for the detection of rhythmic gene expression via quantitative real-time PCR in Tibetan hulless barley.

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Jing Cai

Full Text Available Hulless barley (Hordeum vulgare L. var. nudum. hook. f. has been cultivated as a major crop in the Qinghai-Tibet plateau of China for thousands of years. Compared to other cereal crops, the Tibetan hulless barley has developed stronger endogenous resistances to survive in the severe environment of its habitat. To understand the unique resistant mechanisms of this plant, detailed genetic studies need to be performed. The quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR is the most commonly used method in detecting gene expression. However, the selection of stable reference genes under limited experimental conditions was considered to be an essential step for obtaining accurate results in qRT-PCR. In this study, 10 candidate reference genes-ACT (Actin, E2 (Ubiquitin conjugating enzyme 2, TUBα (Alpha-tubulin, TUBβ6 (Beta-tubulin 6, GAPDH (Glyceraldehyde 3-phosphate dehydrogenase, EF-1α (Elongation factor 1-alpha, SAMDC (S-adenosylmethionine decarboxylase, PKABA1 (Gene for protein kinase HvPKABA1, PGK (Phosphoglycerate kinase, and HSP90 (Heat shock protein 90-were selected from the NCBI gene database of barley. Following qRT-PCR amplifications of all candidate reference genes in Tibetan hulless barley seedlings under various stressed conditions, the stabilities of these candidates were analyzed by three individual software packages including geNorm, NormFinder, and BestKeeper. The results demonstrated that TUBβ6, E2, TUBα, and HSP90 were generally the most suitable sets under all tested conditions; similarly, TUBα and HSP90 showed peak stability under salt stress, TUBα and EF-1α were the most suitable reference genes under cold stress, and ACT and E2 were the most stable under drought stress. Finally, a known circadian gene CCA1 was used to verify the service ability of chosen reference genes. The results confirmed that all recommended reference genes by the three software were suitable for gene expression

Selection of appropriate reference genes for the detection of rhythmic gene expression via quantitative real-time PCR in Tibetan hulless barley.

Science.gov (United States)

Cai, Jing; Li, Pengfei; Luo, Xiao; Chang, Tianliang; Li, Jiaxing; Zhao, Yuwei; Xu, Yao

2018-01-01

Hulless barley (Hordeum vulgare L. var. nudum. hook. f.) has been cultivated as a major crop in the Qinghai-Tibet plateau of China for thousands of years. Compared to other cereal crops, the Tibetan hulless barley has developed stronger endogenous resistances to survive in the severe environment of its habitat. To understand the unique resistant mechanisms of this plant, detailed genetic studies need to be performed. The quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is the most commonly used method in detecting gene expression. However, the selection of stable reference genes under limited experimental conditions was considered to be an essential step for obtaining accurate results in qRT-PCR. In this study, 10 candidate reference genes-ACT (Actin), E2 (Ubiquitin conjugating enzyme 2), TUBα (Alpha-tubulin), TUBβ6 (Beta-tubulin 6), GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), EF-1α (Elongation factor 1-alpha), SAMDC (S-adenosylmethionine decarboxylase), PKABA1 (Gene for protein kinase HvPKABA1), PGK (Phosphoglycerate kinase), and HSP90 (Heat shock protein 90)-were selected from the NCBI gene database of barley. Following qRT-PCR amplifications of all candidate reference genes in Tibetan hulless barley seedlings under various stressed conditions, the stabilities of these candidates were analyzed by three individual software packages including geNorm, NormFinder, and BestKeeper. The results demonstrated that TUBβ6, E2, TUBα, and HSP90 were generally the most suitable sets under all tested conditions; similarly, TUBα and HSP90 showed peak stability under salt stress, TUBα and EF-1α were the most suitable reference genes under cold stress, and ACT and E2 were the most stable under drought stress. Finally, a known circadian gene CCA1 was used to verify the service ability of chosen reference genes. The results confirmed that all recommended reference genes by the three software were suitable for gene expression analysis

Detecting negative selection on recurrent mutations using gene genealogy

Science.gov (United States)

2013-01-01

Background Whether or not a mutant allele in a population is under selection is an important issue in population genetics, and various neutrality tests have been invented so far to detect selection. However, detection of negative selection has been notoriously difficult, partly because negatively selected alleles are usually rare in the population and have little impact on either population dynamics or the shape of the gene genealogy. Recently, through studies of genetic disorders and genome-wide analyses, many structural variations were shown to occur recurrently in the population. Such “recurrent mutations” might be revealed as deleterious by exploiting the signal of negative selection in the gene genealogy enhanced by their recurrence. Results Motivated by the above idea, we devised two new test statistics. One is the total number of mutants at a recurrently mutating locus among sampled sequences, which is tested conditionally on the number of forward mutations mapped on the sequence genealogy. The other is the size of the most common class of identical-by-descent mutants in the sample, again tested conditionally on the number of forward mutations mapped on the sequence genealogy. To examine the performance of these two tests, we simulated recurrently mutated loci each flanked by sites with neutral single nucleotide polymorphisms (SNPs), with no recombination. Using neutral recurrent mutations as null models, we attempted to detect deleterious recurrent mutations. Our analyses demonstrated high powers of our new tests under constant population size, as well as their moderate power to detect selection in expanding populations. We also devised a new maximum parsimony algorithm that, given the states of the sampled sequences at a recurrently mutating locus and an incompletely resolved genealogy, enumerates mutation histories with a minimum number of mutations while partially resolving genealogical relationships when necessary. Conclusions With their

GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

Science.gov (United States)

Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

2018-01-01

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

Antibody-directed lentiviral gene transduction for live-cell monitoring and selection of human iPS and hES cells.

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Dai-tze Wu

Full Text Available The identification of stem cells within a mixed population of cells is a major hurdle for stem cell biology--in particular, in the identification of induced pluripotent stem (iPS cells during the reprogramming process. Based on the selective expression of stem cell surface markers, a method to specifically infect stem cells through antibody-conjugated lentiviral particles has been developed that can deliver both visual markers for live-cell imaging as well as selectable markers to enrich for iPS cells. Antibodies recognizing SSEA4 and CD24 mediated the selective infection of the iPS cells over the parental human fibroblasts, allowing for rapid expansion of these cells by puromycin selection. Adaptation of the vector allows for the selective marking of human embryonic stem (hES cells for their removal from a population of differentiated cells. This method has the benefit that it not only identifies stem cells, but that specific genes, including positive and negative selection markers, regulatory genes or miRNA can be delivered to the targeted stem cells. The ability to specifically target gene delivery to human pluripotent stem cells has broad applications in tissue engineering and stem cell therapies.

The roles of gene duplication, gene conversion and positive selection in rodent Esp and Mup pheromone gene families with comparison to the Abp family.

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Karn, Robert C; Laukaitis, Christina M

2012-01-01

Three proteinaceous pheromone families, the androgen-binding proteins (ABPs), the exocrine-gland secreting peptides (ESPs) and the major urinary proteins (MUPs) are encoded by large gene families in the genomes of Mus musculus and Rattus norvegicus. We studied the evolutionary histories of the Mup and Esp genes and compared them with what is known about the Abp genes. Apparently gene conversion has played little if any role in the expansion of the mouse Class A and Class B Mup genes and pseudogenes, and the rat Mups. By contrast, we found evidence of extensive gene conversion in many Esp genes although not in all of them. Our studies of selection identified at least two amino acid sites in β-sheets as having evolved under positive selection in the mouse Class A and Class B MUPs and in rat MUPs. We show that selection may have acted on the ESPs by determining K(a)/K(s) for Exon 3 sequences with and without the converted sequence segment. While it appears that purifying selection acted on the ESP signal peptides, the secreted portions of the ESPs probably have undergone much more rapid evolution. When the inner gene converted fragment sequences were removed, eleven Esp paralogs were present in two or more pairs with K(a)/K(s) >1.0 and thus we propose that positive selection is detectable by this means in at least some mouse Esp paralogs. We compare and contrast the evolutionary histories of all three mouse pheromone gene families in light of their proposed functions in mouse communication.

Positive selection in the SLC11A1 gene in the family Equidae

DEFF Research Database (Denmark)

Bayerova, Zuzana; Janova, Eva; Matiasovic, Jan

2016-01-01

Immunity-related genes are a suitable model for studying effects of selection at the genomic level. Some of them are highly conserved due to functional constraints and purifying selection, while others are variable and change quickly to cope with the variation of pathogens. The SLC11A1 gene encodes...... a transporter protein mediating antimicrobial activity of macrophages. Little is known about the patterns of selection shaping this gene during evolution. Although it is a typical evolutionarily conserved gene, functionally important polymorphisms associated with various diseases were identified in humans...... and other species. We analyzed the genomic organization, genetic variation, and evolution of the SLC11A1 gene in the family Equidae to identify patterns of selection within this important gene. Nucleotide SLC11A1 sequences were shown to be highly conserved in ten equid species, with more than 97 % sequence...

Research progress in machine learning methods for gene-gene interaction detection.

Science.gov (United States)

Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

2018-03-20

Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

Effect of the absolute statistic on gene-sampling gene-set analysis methods.

Science.gov (United States)

Nam, Dougu

2017-06-01

Gene-set enrichment analysis and its modified versions have commonly been used for identifying altered functions or pathways in disease from microarray data. In particular, the simple gene-sampling gene-set analysis methods have been heavily used for datasets with only a few sample replicates. The biggest problem with this approach is the highly inflated false-positive rate. In this paper, the effect of absolute gene statistic on gene-sampling gene-set analysis methods is systematically investigated. Thus far, the absolute gene statistic has merely been regarded as a supplementary method for capturing the bidirectional changes in each gene set. Here, it is shown that incorporating the absolute gene statistic in gene-sampling gene-set analysis substantially reduces the false-positive rate and improves the overall discriminatory ability. Its effect was investigated by power, false-positive rate, and receiver operating curve for a number of simulated and real datasets. The performances of gene-set analysis methods in one-tailed (genome-wide association study) and two-tailed (gene expression data) tests were also compared and discussed.

The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

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Xinguo Lu

2018-01-01

Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

Self-assembled pentablock copolymers for selective and sustained gene delivery

Energy Technology Data Exchange (ETDEWEB)

Zhang, Bingqi [Iowa State Univ., Ames, IA (United States)

2011-05-15

The poly(diethylaminoethyl methacrylate) (PDEAEM) - Pluronic F127 - PDEAEM pentablock copolymer (PB) gene delivery vector system has been found to possess an inherent selectivity in transfecting cancer cells over non-cancer cells in vitro, without attaching any targeting ligands. In order to understand the mechanism of this selective transfection, three possible intracellular barriers to transfection were investigated in both cancer and non-cancer cells. We concluded that escape from the endocytic pathway served as the primary intracellular barrier for PB-mediated transfection. Most likely, PB vectors were entrapped and rendered non-functional in acidic lysosomes of non-cancer cells, but survived in less acidic lysosomes of cancer cells. The work highlights the importance of identifying intracellular barriers for different gene delivery systems and provides a new paradigm for designing targeting vectors based on intracellular differences between cell types, rather than through the use of targeting ligands. The PB vector was further developed to simultaneously deliver anticancer drugs and genes, which showed a synergistic effect demonstrated by significantly enhanced gene expression in vitro. Due to the thermosensitive gelation behavior, the PB vector packaging both drug and gene was also investigated for its in vitro sustained release properties by using polyethylene glycol diacrylate as a barrier gel to mimic the tumor matrix in vivo. Overall, this work resulted in the development of a gene delivery vector for sustained and selective gene delivery to tumor cells for cancer therapy.

Population Level Purifying Selection and Gene Expression Shape Subgenome Evolution in Maize.

Science.gov (United States)

Pophaly, Saurabh D; Tellier, Aurélien

2015-12-01

The maize ancestor experienced a recent whole-genome duplication (WGD) followed by gene erosion which generated two subgenomes, the dominant subgenome (maize1) experiencing fewer deletions than maize2. We take advantage of available extensive polymorphism and gene expression data in maize to study purifying selection and gene expression divergence between WGD retained paralog pairs. We first report a strong correlation in nucleotide diversity between duplicate pairs, except for upstream regions. We then show that maize1 genes are under stronger purifying selection than maize2. WGD retained genes have higher gene dosage and biased Gene Ontologies consistent with previous studies. The relative gene expression of paralogs across tissues demonstrates that 98% of duplicate pairs have either subfunctionalized in a tissuewise manner or have diverged consistently in their expression thereby preventing functional complementation. Tissuewise subfunctionalization seems to be a hallmark of transcription factors, whereas consistent repression occurs for macromolecular complexes. We show that dominant gene expression is a strong determinant of the strength of purifying selection, explaining the inferred stronger negative selection on maize1 genes. We propose a novel expression-based classification of duplicates which is more robust to explain observed polymorphism patterns than the subgenome location. Finally, upstream regions of repressed genes exhibit an enrichment in transposable elements which indicates a possible mechanism for expression divergence. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Repeated adaptive introgression at a gene under multiallelic balancing selection.

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Vincent Castric

2008-08-01

Full Text Available Recently diverged species typically have incomplete reproductive barriers, allowing introgression of genetic material from one species into the genomic background of the other. The role of natural selection in preventing or promoting introgression remains contentious. Because of genomic co-adaptation, some chromosomal fragments are expected to be selected against in the new background and resist introgression. In contrast, natural selection should favor introgression for alleles at genes evolving under multi-allelic balancing selection, such as the MHC in vertebrates, disease resistance, or self-incompatibility genes in plants. Here, we test the prediction that negative, frequency-dependent selection on alleles at the multi-allelic gene controlling pistil self-incompatibility specificity in two closely related species, Arabidopsis halleri and A. lyrata, caused introgression at this locus at a higher rate than the genomic background. Polymorphism at this gene is largely shared, and we have identified 18 pairs of S-alleles that are only slightly divergent between the two species. For these pairs of S-alleles, divergence at four-fold degenerate sites (K = 0.0193 is about four times lower than the genomic background (K = 0.0743. We demonstrate that this difference cannot be explained by differences in effective population size between the two types of loci. Rather, our data are most consistent with a five-fold increase of introgression rates for S-alleles as compared to the genomic background, making this study the first documented example of adaptive introgression facilitated by balancing selection. We suggest that this process plays an important role in the maintenance of high allelic diversity and divergence at the S-locus in flowering plant families. Because genes under balancing selection are expected to be among the last to stop introgressing, their comparison in closely related species provides a lower-bound estimate of the time since the

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer

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Rosa Aghdam

2017-12-01

Full Text Available Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/.

Selective Gene Delivery for Integrating Exogenous DNA into Plastid and Mitochondrial Genomes Using Peptide-DNA Complexes.

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Yoshizumi, Takeshi; Oikawa, Kazusato; Chuah, Jo-Ann; Kodama, Yutaka; Numata, Keiji

2018-05-14

Selective gene delivery into organellar genomes (mitochondrial and plastid genomes) has been limited because of a lack of appropriate platform technology, even though these organelles are essential for metabolite and energy production. Techniques for selective organellar modification are needed to functionally improve organelles and produce transplastomic/transmitochondrial plants. However, no method for mitochondrial genome modification has yet been established for multicellular organisms including plants. Likewise, modification of plastid genomes has been limited to a few plant species and algae. In the present study, we developed ionic complexes of fusion peptides containing organellar targeting signal and plasmid DNA for selective delivery of exogenous DNA into the plastid and mitochondrial genomes of intact plants. This is the first report of exogenous DNA being integrated into the mitochondrial genomes of not only plants, but also multicellular organisms in general. This fusion peptide-mediated gene delivery system is a breakthrough platform for both plant organellar biotechnology and gene therapy for mitochondrial diseases in animals.

Selective modes determine evolutionary rates, gene compactness and expression patterns in Brassica.

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Guo, Yue; Liu, Jing; Zhang, Jiefu; Liu, Shengyi; Du, Jianchang

2017-07-01

It has been well documented that most nuclear protein-coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K a ) and the rates of synonymous substitution (K s ) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue-specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K a /K s ), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes

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Lotz Meredith J

2008-01-01

Full Text Available Abstract Background Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures × time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. Results We found that the optimal imputation algorithms (LSA, LLS, and BPCA are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Conclusion Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes.

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Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

2008-01-10

Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity

A probabilistic method for testing and estimating selection differences between populations.

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He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

2015-12-01

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. © 2015 He et al.; Published by Cold Spring Harbor Laboratory Press.

Positive selection in the SLC11A1 gene in the family Equidae.

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Bayerova, Zuzana; Janova, Eva; Matiasovic, Jan; Orlando, Ludovic; Horin, Petr

2016-05-01

Immunity-related genes are a suitable model for studying effects of selection at the genomic level. Some of them are highly conserved due to functional constraints and purifying selection, while others are variable and change quickly to cope with the variation of pathogens. The SLC11A1 gene encodes a transporter protein mediating antimicrobial activity of macrophages. Little is known about the patterns of selection shaping this gene during evolution. Although it is a typical evolutionarily conserved gene, functionally important polymorphisms associated with various diseases were identified in humans and other species. We analyzed the genomic organization, genetic variation, and evolution of the SLC11A1 gene in the family Equidae to identify patterns of selection within this important gene. Nucleotide SLC11A1 sequences were shown to be highly conserved in ten equid species, with more than 97 % sequence identity across the family. Single nucleotide polymorphisms (SNPs) were found in the coding and noncoding regions of the gene. Seven codon sites were identified to be under strong purifying selection. Codons located in three regions, including the glycosylated extracellular loop, were shown to be under diversifying selection. A 3-bp indel resulting in a deletion of the amino acid 321 in the predicted protein was observed in all horses, while it has been maintained in all other equid species. This codon comprised in an N-glycosylation site was found to be under positive selection. Interspecific variation in the presence of predicted N-glycosylation sites was observed.

Analysis of polymorphisms and selective pressures on ama1 gene ...

Indian Academy of Sciences (India)

Chuen Yang Chua

2017-09-05

Sep 5, 2017 ... The presence of purifying selection and low nucleotide diversity ... (2000) studied the gene substitution of ama1 ... in the gene coding for AMA-1 protein in Plasmodium ... Health Malaysia. ...... X. Asembo Bay Cohort Project.

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

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Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

2017-12-01

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

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Lu, Tao

2016-01-01

The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion.

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Zhao, Shanrong; Zhang, Ying; Gamini, Ramya; Zhang, Baohong; von Schack, David

2018-03-19

To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

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Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

2016-12-01

The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

Balancing selection on immunity genes: review of the current literature and new analysis in Drosophila melanogaster.

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Croze, Myriam; Živković, Daniel; Stephan, Wolfgang; Hutter, Stephan

2016-08-01

Balancing selection has been widely assumed to be an important evolutionary force, yet even today little is known about its abundance and its impact on the patterns of genetic diversity. Several studies have shown examples of balancing selection in humans, plants or parasites, and many genes under balancing selection are involved in immunity. It has been proposed that host-parasite coevolution is one of the main forces driving immune genes to evolve under balancing selection. In this paper, we review the literature on balancing selection on immunity genes in several organisms, including Drosophila. Furthermore, we performed a genome scan for balancing selection in an African population of Drosophila melanogaster using coalescent simulations of a demographic model with and without selection. We find very few genes under balancing selection and only one novel candidate gene related to immunity. Finally, we discuss the possible causes of the low number of genes under balancing selection. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

Genome-wide analysis of positively selected genes in seasonal and non-seasonal breeding species.

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Yuhuan Meng

Full Text Available Some mammals breed throughout the year, while others breed only at certain times of year. These differences in reproductive behavior can be explained by evolution. We identified positively-selected genes in two sets of species with different degrees of relatedness including seasonal and non-seasonal breeding species, using branch-site models. After stringent filtering by sum of pairs scoring, we revealed that more genes underwent positive selection in seasonal compared with non-seasonal breeding species. Positively-selected genes were verified by cDNA mapping of the positive sites with the corresponding cDNA sequences. The design of the evolutionary analysis can effectively lower the false-positive rate and thus identify valid positive genes. Validated, positively-selected genes, including CGA, DNAH1, INVS, and CD151, were related to reproductive behaviors such as spermatogenesis and cell proliferation in non-seasonal breeding species. Genes in seasonal breeding species, including THRAP3, TH1L, and CMTM6, may be related to the evolution of sperm and the circadian rhythm system. Identification of these positively-selected genes might help to identify the molecular mechanisms underlying seasonal and non-seasonal reproductive behaviors.

Bacterial evolution through the selective loss of beneficial Genes. Trade-offs in expression involving two loci.

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Zinser, Erik R; Schneider, Dominique; Blot, Michel; Kolter, Roberto

2003-01-01

The loss of preexisting genes or gene activities during evolution is a major mechanism of ecological specialization. Evolutionary processes that can account for gene loss or inactivation have so far been restricted to one of two mechanisms: direct selection for the loss of gene activities that are disadvantageous under the conditions of selection (i.e., antagonistic pleiotropy) and selection-independent genetic drift of neutral (or nearly neutral) mutations (i.e., mutation accumulation). In this study we demonstrate with an evolved strain of Escherichia coli that a third, distinct mechanism exists by which gene activities can be lost. This selection-dependent mechanism involves the expropriation of one gene's upstream regulatory element by a second gene via a homologous recombination event. Resulting from this genetic exchange is the activation of the second gene and a concomitant inactivation of the first gene. This gene-for-gene expression tradeoff provides a net fitness gain, even if the forfeited activity of the first gene can play a positive role in fitness under the conditions of selection. PMID:12930738

Bacterial evolution through the selective loss of beneficial Genes. Trade-offs in expression involving two loci.

Science.gov (United States)

Zinser, Erik R; Schneider, Dominique; Blot, Michel; Kolter, Roberto

2003-08-01

The loss of preexisting genes or gene activities during evolution is a major mechanism of ecological specialization. Evolutionary processes that can account for gene loss or inactivation have so far been restricted to one of two mechanisms: direct selection for the loss of gene activities that are disadvantageous under the conditions of selection (i.e., antagonistic pleiotropy) and selection-independent genetic drift of neutral (or nearly neutral) mutations (i.e., mutation accumulation). In this study we demonstrate with an evolved strain of Escherichia coli that a third, distinct mechanism exists by which gene activities can be lost. This selection-dependent mechanism involves the expropriation of one gene's upstream regulatory element by a second gene via a homologous recombination event. Resulting from this genetic exchange is the activation of the second gene and a concomitant inactivation of the first gene. This gene-for-gene expression tradeoff provides a net fitness gain, even if the forfeited activity of the first gene can play a positive role in fitness under the conditions of selection.

A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

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Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

2013-01-01

Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

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Ching Lee Koo

2013-01-01

Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

Evidence for positive selection on the leptin gene in Cetacea and Pinnipedia.

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Li Yu

Full Text Available The leptin gene has received intensive attention and scientific investigation for its importance in energy homeostasis and reproductive regulation in mammals. Furthermore, study of the leptin gene is of crucial importance for public health, particularly for its role in obesity, as well as for other numerous physiological roles that it plays in mammals. In the present work, we report the identification of novel leptin genes in 4 species of Cetacea, and a comparison with 55 publicly available leptin sequences from mammalian genome assemblies and previous studies. Our study provides evidence for positive selection in the suborder Odontoceti (toothed whales of the Cetacea and the family Phocidae (earless seals of the Pinnipedia. We also detected positive selection in several leptin gene residues in these two lineages. To test whether leptin and its receptor evolved in a coordinated manner, we analyzed 24 leptin receptor gene (LPR sequences from available mammalian genome assemblies and other published data. Unlike the case of leptin, our analyses did not find evidence of positive selection for LPR across the Cetacea and Pinnipedia lineages. In line with this, positively selected sites identified in the leptin genes of these two lineages were located outside of leptin receptor binding sites, which at least partially explains why co-evolution of leptin and its receptor was not observed in the present study. Our study provides interesting insights into current understanding of the evolution of mammalian leptin genes in response to selective pressures from life in an aquatic environment, and leads to a hypothesis that new tissue specificity or novel physiologic functions of leptin genes may have arisen in both odontocetes and phocids. Additional data from other species encompassing varying life histories and functional tests of the adaptive role of the amino acid changes identified in this study will help determine the factors that promote the adaptive

Flies selected for longevity retain a young gene expression profile

DEFF Research Database (Denmark)

Sarup, Pernille Merete; Sørensen, Peter; Loeschcke, Volker

2011-01-01

  We investigated correlated responses in the transcriptomes of longevity-selected lines of Drosophila melanogaster to identify pathways that affect life span in metazoan systems. We evaluated the gene expression profile in young, middle-aged, and old male flies, finding that 530 genes were...

Selecting and validating reference genes for quantitative real-time PCR in Plutella xylostella (L.).

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You, Yanchun; Xie, Miao; Vasseur, Liette; You, Minsheng

2018-05-01

Gene expression analysis provides important clues regarding gene functions, and quantitative real-time PCR (qRT-PCR) is a widely used method in gene expression studies. Reference genes are essential for normalizing and accurately assessing gene expression. In the present study, 16 candidate reference genes (ACTB, CyPA, EF1-α, GAPDH, HSP90, NDPk, RPL13a, RPL18, RPL19, RPL32, RPL4, RPL8, RPS13, RPS4, α-TUB, and β-TUB) from Plutella xylostella were selected to evaluate gene expression stability across different experimental conditions using five statistical algorithms (geNorm, NormFinder, Delta Ct, BestKeeper, and RefFinder). The results suggest that different reference genes or combinations of reference genes are suitable for normalization in gene expression studies of P. xylostella according to the different developmental stages, strains, tissues, and insecticide treatments. Based on the given experimental sets, the most stable reference genes were RPS4 across different developmental stages, RPL8 across different strains and tissues, and EF1-α across different insecticide treatments. A comprehensive and systematic assessment of potential reference genes for gene expression normalization is essential for post-genomic functional research in P. xylostella, a notorious pest with worldwide distribution and a high capacity to adapt and develop resistance to insecticides.

Selection of reference genes for gene expression studies in heart failure for left and right ventricles.

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Li, Mengmeng; Rao, Man; Chen, Kai; Zhou, Jianye; Song, Jiangping

2017-07-15

Real-time quantitative reverse transcriptase-PCR (qRT-PCR) is a feasible tool for determining gene expression profiles, but the accuracy and reliability of the results depends on the stable expression of selected housekeeping genes in different samples. By far, researches on stable housekeeping genes in human heart failure samples are rare. Moreover the effect of heart failure on the expression of housekeeping genes in right and left ventricles is yet to be studied. Therefore we aim to provide stable housekeeping genes for both ventricles in heart failure and normal heart samples. In this study, we selected seven commonly used housekeeping genes as candidates. By using the qRT-PCR, the expression levels of ACTB, RAB7A, GAPDH, REEP5, RPL5, PSMB4 and VCP in eight heart failure and four normal heart samples were assessed. The stability of candidate housekeeping genes was evaluated by geNorm and Normfinder softwares. GAPDH showed the least variation in all heart samples. Results also indicated the difference of gene expression existed in heart failure left and right ventricles. GAPDH had the highest expression stability in both heart failure and normal heart samples. We also propose using different sets of housekeeping genes for left and right ventricles respectively. The combination of RPL5, GAPDH and PSMB4 is suitable for the right ventricle and the combination of GAPDH, REEP5 and RAB7A is suitable for the left ventricle. Copyright © 2017 Elsevier B.V. All rights reserved.

Natural selection on protein-coding genes in the human genome

DEFF Research Database (Denmark)

Bustamente, Carlos D.; Fledel-Alon, Adi; Williamson, Scott

2005-01-01

, showing an excess of deleterious variation within local populations 9, 10 . Here we contrast patterns of coding sequence polymorphism identified by direct sequencing of 39 humans for over 11,000 genes to divergence between humans and chimpanzees, and find strong evidence that natural selection has shaped......Comparisons of DNA polymorphism within species to divergence between species enables the discovery of molecular adaptation in evolutionarily constrained genes as well as the differentiation of weak from strong purifying selection 1, 2, 3, 4 . The extent to which weak negative and positive darwinian...... selection have driven the molecular evolution of different species varies greatly 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 , with some species, such as Drosophila melanogaster, showing strong evidence of pervasive positive selection 6, 7, 8, 9 , and others, such as the selfing weed Arabidopsis thaliana...

Selection and validation of reference genes for quantitative gene expression analyses in various tissues and seeds at different developmental stages in Bixa orellana L.

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Moreira, Viviane S; Soares, Virgínia L F; Silva, Raner J S; Sousa, Aurizangela O; Otoni, Wagner C; Costa, Marcio G C

2018-05-01

Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana , coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, ΔCt method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA , for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.

Selection and validation of endogenous reference genes for qRT-PCR analysis in leafy spurge (Euphorbia esula.

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Wun S Chao

Full Text Available Quantitative real-time polymerase chain reaction (qRT-PCR is the most important tool in measuring levels of gene expression due to its accuracy, specificity, and sensitivity. However, the accuracy of qRT-PCR analysis strongly depends on transcript normalization using stably expressed reference genes. The aim of this study was to find internal reference genes for qRT-PCR analysis in various experimental conditions for seed, adventitious underground bud, and other organs of leafy spurge. Eleven candidate reference genes (BAM4, PU1, TRP-like, FRO1, ORE9, BAM1, SEU, ARF2, KAPP, ZTL, and MPK4 were selected from among 171 genes based on expression stabilities during seed germination and bud growth. The other ten candidate reference genes were selected from three different sources: (1 3 stably expressed leafy spurge genes (60S, bZIP21, and MD-100 identified from the analyses of leafy spurge microarray data; (2 3 orthologs of Arabidopsis "general purpose" traditional reference genes (GAPDH_1, GAPDH_2, and UBC; and (3 4 orthologs of Arabidopsis stably expressed genes (UBC9, SAND, PTB, and F-box identified from Affymetrix ATH1 whole-genome GeneChip studies. The expression stabilities of these 21 genes were ranked based on the C(T values of 72 samples using four different computation programs including geNorm, Normfinder, BestKeeper, and the comparative ΔC(T method. Our analyses revealed SAND, PTB, ORE9, and ARF2 to be the most appropriate reference genes for accurate normalization of gene expression data. Since SAND and PTB were obtained from 4 orthologs of Arabidopsis, while ORE9 and ARF2 were selected from 171 leafy spurge genes, it was more efficient to identify good reference genes from the orthologs of other plant species that were known to be stably expressed than that of randomly testing endogenous genes. Nevertheless, the two newly identified leafy spurge genes, ORE9 and ARF2, can serve as orthologous candidates in the search for reference genes

Selection of Suitable Endogenous Reference Genes for Relative Copy Number Detection in Sugarcane

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Bantong Xue

2014-05-01

Full Text Available Transgene copy number has a great impact on the expression level and stability of exogenous gene in transgenic plants. Proper selection of endogenous reference genes is necessary for detection of genetic components in genetically modification (GM crops by quantitative real-time PCR (qPCR or by qualitative PCR approach, especially in sugarcane with polyploid and aneuploid genomic structure. qPCR technique has been widely accepted as an accurate, time-saving method on determination of copy numbers in transgenic plants and on detection of genetically modified plants to meet the regulatory and legislative requirement. In this study, to find a suitable endogenous reference gene and its real-time PCR assay for sugarcane (Saccharum spp. hybrids DNA content quantification, we evaluated a set of potential “single copy” genes including P4H, APRT, ENOL, CYC, TST and PRR, through qualitative PCR and absolute quantitative PCR. Based on copy number comparisons among different sugarcane genotypes, including five S. officinarum, one S. spontaneum and two S. spp. hybrids, these endogenous genes fell into three groups: ENOL-3—high copy number group, TST-1 and PRR-1—medium copy number group, P4H-1, APRT-2 and CYC-2—low copy number group. Among these tested genes, P4H, APRT and CYC were the most stable, while ENOL and TST were the least stable across different sugarcane genotypes. Therefore, three primer pairs of P4H-3, APRT-2 and CYC-2 were then selected as the suitable reference gene primer pairs for sugarcane. The test of multi-target reference genes revealed that the APRT gene was a specific amplicon, suggesting this gene is the most suitable to be used as an endogenous reference target for sugarcane DNA content quantification. These results should be helpful for establishing accurate and reliable qualitative and quantitative PCR analysis of GM sugarcane.

Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

KAUST Repository

Abusamra, Heba; Bajic, Vladimir B.

2016-01-01

decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we

Actin gene identification from selected medicinal plants for their use as internal controls for gene expression studies

International Nuclear Information System (INIS)

Mufti, F.U.D.; Banaras, S.

2015-01-01

Internal control genes are the constitutive genes which maintain the basic cellular functions and regularly express in both normal and stressed conditions in living organisms. They are used in normalization of gene expression studies in comparative analysis of target genes, as their expression remains comparatively unchanged in all varied conditions. Among internal control genes, actin is considered as a candidate gene for expression studies due to its vital role in shaping cytoskeleton and plant physiology. Unfortunately most of such knowledge is limited to only model plants or crops, not much is known about important medicinal plants. Therefore, we selected seven important medicinal wild plants for molecular identification of actin gene. We used gene specific primers designed from the conserved regions of several known orthologues or homologues of actin genes from other plants. The amplified products of 370-380 bp were sequenced and submitted to GeneBank after their confirmation using different bioinformatics tools. All the novel partial sequences of putative actin genes were submitted to GeneBank (Parthenium hysterophorus (KJ774023), Fagonia indica (KJ774024), Rhazya stricta (KJ774025), Whithania coagulans (KJ774026), Capparis decidua (KJ774027), Verbena officinalis (KJ774028) and Aerva javanica (KJ774029)). The comparisons of these partial sequences by Basic Local Alignment Search Tool (BLAST) and phylogenetic trees demonstrated high similarity with known actin genes of other plants. Our findings illustrated highly conserved nature of actin gene among these selected plants. These novel partial fragments of actin genes from these wild medicinal plants can be used as internal controls for future gene expression studies of these important plants after precise validations of their stable expression in such plants. (author)

Identification of Subtype-Specific Prognostic Genes for Early-Stage Lung Adenocarcinoma and Squamous Cell Carcinoma Patients Using an Embedded Feature Selection Algorithm.

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Suyan Tian

Full Text Available The existence of fundamental differences between lung adenocarcinoma (AC and squamous cell carcinoma (SCC in their underlying mechanisms motivated us to postulate that specific genes might exist relevant to prognosis of each histology subtype. To test on this research hypothesis, we previously proposed a simple Cox-regression model based feature selection algorithm and identified successfully some subtype-specific prognostic genes when applying this method to real-world data. In this article, we continue our effort on identification of subtype-specific prognostic genes for AC and SCC, and propose a novel embedded feature selection method by extending Threshold Gradient Descent Regularization (TGDR algorithm and minimizing on a corresponding negative partial likelihood function. Using real-world datasets and simulated ones, we show these two proposed methods have comparable performance whereas the new proposal is superior in terms of model parsimony. Our analysis provides some evidence on the existence of such subtype-specific prognostic genes, more investigation is warranted.

Adaptive L1/2 Shooting Regularization Method for Survival Analysis Using Gene Expression Data

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Xiao-Ying Liu

2013-01-01

Full Text Available A new adaptive L1/2 shooting regularization method for variable selection based on the Cox’s proportional hazards mode being proposed. This adaptive L1/2 shooting algorithm can be easily obtained by the optimization of a reweighed iterative series of L1 penalties and a shooting strategy of L1/2 penalty. Simulation results based on high dimensional artificial data show that the adaptive L1/2 shooting regularization method can be more accurate for variable selection than Lasso and adaptive Lasso methods. The results from real gene expression dataset (DLBCL also indicate that the L1/2 regularization method performs competitively.

Selection of Reference Genes for qRT-PCR Analysis of Gene Expression in Stipa grandis during Environmental Stresses.

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Dongli Wan

Full Text Available Stipa grandis P. Smirn. is a dominant plant species in the typical steppe of the Xilingole Plateau of Inner Mongolia. Selection of suitable reference genes for the quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR is important for gene expression analysis and research into the molecular mechanisms underlying the stress responses of S. grandis. In the present study, 15 candidate reference genes (EF1 beta, ACT, GAPDH, SamDC, CUL4, CAP, SNF2, SKIP1, SKIP5, SKIP11, UBC2, UBC15, UBC17, UCH, and HERC2 were evaluated for their stability as potential reference genes for qRT-PCR under different stresses. Four algorithms were used: GeNorm, NormFinder, BestKeeper, and RefFinder. The results showed that the most stable reference genes were different under different stress conditions: EF1beta and UBC15 during drought and salt stresses; ACT and GAPDH under heat stress; SKIP5 and UBC17 under cold stress; UBC15 and HERC2 under high pH stress; UBC2 and UBC15 under wounding stress; EF1beta and UBC17 under jasmonic acid treatment; UBC15 and CUL4 under abscisic acid treatment; and HERC2 and UBC17 under salicylic acid treatment. EF1beta and HERC2 were the most suitable genes for the global analysis of all samples. Furthermore, six target genes, SgPOD, SgPAL, SgLEA, SgLOX, SgHSP90 and SgPR1, were selected to validate the most and least stable reference genes under different treatments. Our results provide guidelines for reference gene selection for more accurate qRT-PCR quantification and will promote studies of gene expression in S. grandis subjected to environmental stress.

Comparison of normalization methods for the analysis of metagenomic gene abundance data.

Science.gov (United States)

Pereira, Mariana Buongermino; Wallroth, Mikael; Jonsson, Viktor; Kristiansson, Erik

2018-04-20

In shotgun metagenomics, microbial communities are studied through direct sequencing of DNA without any prior cultivation. By comparing gene abundances estimated from the generated sequencing reads, functional differences between the communities can be identified. However, gene abundance data is affected by high levels of systematic variability, which can greatly reduce the statistical power and introduce false positives. Normalization, which is the process where systematic variability is identified and removed, is therefore a vital part of the data analysis. A wide range of normalization methods for high-dimensional count data has been proposed but their performance on the analysis of shotgun metagenomic data has not been evaluated. Here, we present a systematic evaluation of nine normalization methods for gene abundance data. The methods were evaluated through resampling of three comprehensive datasets, creating a realistic setting that preserved the unique characteristics of metagenomic data. Performance was measured in terms of the methods ability to identify differentially abundant genes (DAGs), correctly calculate unbiased p-values and control the false discovery rate (FDR). Our results showed that the choice of normalization method has a large impact on the end results. When the DAGs were asymmetrically present between the experimental conditions, many normalization methods had a reduced true positive rate (TPR) and a high false positive rate (FPR). The methods trimmed mean of M-values (TMM) and relative log expression (RLE) had the overall highest performance and are therefore recommended for the analysis of gene abundance data. For larger sample sizes, CSS also showed satisfactory performance. This study emphasizes the importance of selecting a suitable normalization methods in the analysis of data from shotgun metagenomics. Our results also demonstrate that improper methods may result in unacceptably high levels of false positives, which in turn may lead

Genomic consequences of selection on self-incompatibility genes

DEFF Research Database (Denmark)

Schierup, Mikkel Heide; Vekemans, Xavier

2008-01-01

closely related species. We review recent empirical studies demonstrating these features and relate the empirical findings to theoretical predictions. We show how these features are being exploited in searches for other genes under multi-allelic balancing selection and for inference on recent breakdown...

Network-Based Method for Identifying Co- Regeneration Genes in Bone, Dentin, Nerve and Vessel Tissues.

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Chen, Lei; Pan, Hongying; Zhang, Yu-Hang; Feng, Kaiyan; Kong, XiangYin; Huang, Tao; Cai, Yu-Dong

2017-10-02

Bone and dental diseases are serious public health problems. Most current clinical treatments for these diseases can produce side effects. Regeneration is a promising therapy for bone and dental diseases, yielding natural tissue recovery with few side effects. Because soft tissues inside the bone and dentin are densely populated with nerves and vessels, the study of bone and dentin regeneration should also consider the co-regeneration of nerves and vessels. In this study, a network-based method to identify co-regeneration genes for bone, dentin, nerve and vessel was constructed based on an extensive network of protein-protein interactions. Three procedures were applied in the network-based method. The first procedure, searching, sought the shortest paths connecting regeneration genes of one tissue type with regeneration genes of other tissues, thereby extracting possible co-regeneration genes. The second procedure, testing, employed a permutation test to evaluate whether possible genes were false discoveries; these genes were excluded by the testing procedure. The last procedure, screening, employed two rules, the betweenness ratio rule and interaction score rule, to select the most essential genes. A total of seventeen genes were inferred by the method, which were deemed to contribute to co-regeneration of at least two tissues. All these seventeen genes were extensively discussed to validate the utility of the method.

FCERI AND HISTAMINE METABOLISM GENE VARIABILITY IN SELECTIVE RESPONDERS TO NSAIDS

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Gemma Amo

2016-09-01

Full Text Available The high-affinity IgE receptor (Fcε RI is a heterotetramer of three subunits: Fcε RIα, Fcε RIβ and Fcε RIγ (αβγ2 encoded by three genes designated as FCER1A, FCER1B (MS4A2 and FCER1G, respectively. Recent evidence points to FCERI gene variability as a relevant factor in the risk of developing allergic diseases. Because Fcε RI plays a key role in the events downstream of the triggering factors in immunological response, we hypothesized that FCERI gene variants might be related with the risk of, or with the clinical response to, selective (IgE mediated non-steroidal anti-inflammatory (NSAID hypersensitivity.From a cohort of 314 patients suffering from selective hypersensitivity to metamizole, ibuprofen, diclofenac, paracetamol, acetylsalicylic acid (ASA, propifenazone, naproxen, ketoprofen, dexketoprofen, etofenamate, aceclofenac, etoricoxib, dexibuprofen, indomethacin, oxyphenylbutazone or piroxicam, and 585 unrelated healthy controls that tolerated these NSAIDs, we analyzed the putative effects of the FCERI SNPs FCER1A rs2494262, rs2427837 and rs2251746; FCER1B rs1441586, rs569108 and rs512555; FCER1G rs11587213, rs2070901 and rs11421. Furthermore, in order to identify additional genetic markers which might be associated with the risk of developing selective NSAID hypersensitivity, or which may modify the putative association of FCERI gene variations with risk, we analyzed polymorphisms known to affect histamine synthesis or metabolism, such as rs17740607, rs2073440, rs1801105, rs2052129, rs10156191, rs1049742 and rs1049793 in the HDC, HNMT and DAO genes.No major genetic associations with risk or with clinical presentation, and no gene-gene interactions, or gene-phenotype interactions (including age, gender, IgE concentration, antecedents of atopy, culprit drug or clinical presentation were identified in patients. However, logistic regression analyses indicated that the presence of antecedents of atopy and the DAO SNP rs2052129 (GG

Allopatric integrations selectively change host transcriptomes, leading to varied expression efficiencies of exotic genes in Myxococcus xanthus.

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Zhu, Li-Ping; Yue, Xin-Jing; Han, Kui; Li, Zhi-Feng; Zheng, Lian-Shuai; Yi, Xiu-Nan; Wang, Hai-Long; Zhang, You-Ming; Li, Yue-Zhong

2015-07-22

Exotic genes, especially clustered multiple-genes for a complex pathway, are normally integrated into chromosome for heterologous expression. The influences of insertion sites on heterologous expression and allotropic expressions of exotic genes on host remain mostly unclear. We compared the integration and expression efficiencies of single and multiple exotic genes that were inserted into Myxococcus xanthus genome by transposition and attB-site-directed recombination. While the site-directed integration had a rather stable chloramphenicol acetyl transferase (CAT) activity, the transposition produced varied CAT enzyme activities. We attempted to integrate the 56-kb gene cluster for the biosynthesis of antitumor polyketides epothilones into M. xanthus genome by site-direction but failed, which was determined to be due to the insertion size limitation at the attB site. The transposition technique produced many recombinants with varied production capabilities of epothilones, which, however, were not paralleled to the transcriptional characteristics of the local sites where the genes were integrated. Comparative transcriptomics analysis demonstrated that the allopatric integrations caused selective changes of host transcriptomes, leading to varied expressions of epothilone genes in different mutants. With the increase of insertion fragment size, transposition is a more practicable integration method for the expression of exotic genes. Allopatric integrations selectively change host transcriptomes, which lead to varied expression efficiencies of exotic genes.

Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease

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Maria V. Fernández

2018-04-01

Full Text Available Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235 with late-onset Alzheimer disease (LOAD. After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L as candidate genes for familial LOAD.

Estimation of genetic variability and selection response for clutch length in dwarf brown-egg layers carrying or not the naked neck gene

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Tixier-Boichard Michèle

2003-03-01

Full Text Available Abstract In order to investigate the possibility of using the dwarf gene for egg production, two dwarf brown-egg laying lines were selected for 16 generations on average clutch length; one line (L1 was normally feathered and the other (L2 was homozygous for the naked neck gene NA. A control line from the same base population, dwarf and segregating for the NA gene, was maintained during the selection experiment under random mating. The average clutch length was normalized using a Box-Cox transformation. Genetic variability and selection response were estimated either with the mixed model methodology, or with the classical methods for calculating genetic gain, as the deviation from the control line, and the realized heritability, as the ratio of the selection response on cumulative selection differentials. Heritability of average clutch length was estimated to be 0.42 ± 0.02, with a multiple trait animal model, whereas the estimates of the realized heritability were lower, being 0.28 and 0.22 in lines L1 and L2, respectively. REML estimates of heritability were found to decline with generations of selection, suggesting a departure from the infinitesimal model, either because a limited number of genes was involved, or their frequencies were changed. The yearly genetic gains in average clutch length, after normalization, were estimated to be 0.37 ± 0.02 and 0.33 ± 0.04 with the classical methods, 0.46 ± 0.02 and 0.43 ± 0.01 with animal model methodology, for lines L1 and L2 respectively, which represented about 30% of the genetic standard deviation on the transformed scale. Selection response appeared to be faster in line L2, homozygous for the NA gene, but the final cumulated selection response for clutch length was not different between the L1 and L2 lines at generation 16.

Enhanced gene ranking approaches using modified trace ratio algorithm for gene expression data

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Shruti Mishra

Full Text Available Microarray technology enables the understanding and investigation of gene expression levels by analyzing high dimensional datasets that contain few samples. Over time, microarray expression data have been collected for studying the underlying biological mechanisms of disease. One such application for understanding the mechanism is by constructing a gene regulatory network (GRN. One of the foremost key criteria for GRN discovery is gene selection. Choosing a generous set of genes for the structure of the network is highly desirable. For this role, two suitable methods were proposed for selection of appropriate genes. The first approach comprises a gene selection method called Information gain, where the dataset is reformed and fused with another distinct algorithm called Trace Ratio (TR. Our second method is the implementation of our projected modified TR algorithm, where the scoring base for finding weight matrices has been re-designed. Both the methods' efficiency was shown with different classifiers that include variants of the Artificial Neural Network classifier, such as Resilient Propagation, Quick Propagation, Back Propagation, Manhattan Propagation and Radial Basis Function Neural Network and also the Support Vector Machine (SVM classifier. In the study, it was confirmed that both of the proposed methods worked well and offered high accuracy with a lesser number of iterations as compared to the original Trace Ratio algorithm. Keywords: Gene regulatory network, Gene selection, Information gain, Trace ratio, Canonical correlation analysis, Classification

Methods for the Isolation of Genes Encoding Novel PHA Metabolism Enzymes from Complex Microbial Communities.

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Cheng, Jiujun; Nordeste, Ricardo; Trainer, Maria A; Charles, Trevor C

2017-01-01

Development of different PHAs as alternatives to petrochemically derived plastics can be facilitated by mining metagenomic libraries for diverse PHA cycle genes that might be useful for synthesis of bio-plastics. The specific phenotypes associated with mutations of the PHA synthesis pathway genes in Sinorhizobium meliloti and Pseudomonas putida, allows the use of powerful selection and screening tools to identify complementing novel PHA synthesis genes. Identification of novel genes through their function rather than sequence facilitates the functional proteins that may otherwise have been excluded through sequence-only screening methodology. We present here methods that we have developed for the isolation of clones expressing novel PHA metabolism genes from metagenomic libraries.

Methods for the isolation of genes encoding novel PHB cycle enzymes from complex microbial communities.

Science.gov (United States)

Nordeste, Ricardo F; Trainer, Maria A; Charles, Trevor C

2010-01-01

Development of different PHAs as alternatives to petrochemically derived plastics can be facilitated by mining metagenomic libraries for diverse PHA cycle genes that might be useful for synthesis of bioplastics. The specific phenotypes associated with mutations of the PHA synthesis pathway genes in Sinorhizobium meliloti allows for the use of powerful selection and screening tools to identify complementing novel PHA synthesis genes. Identification of novel genes through their function rather than sequence facilitates finding functional proteins that may otherwise have been excluded through sequence-only screening methodology. We present here methods that we have developed for the isolation of clones expressing novel PHA metabolism genes from metagenomic libraries.

[Methylation of selected tumor-supressor genes in benign and malignant ovarian tumors].

Science.gov (United States)

Cul'bová, M; Lasabová, Z; Stanclová, A; Tilandyová, P; Zúbor, P; Fiolka, R; Danko, J; Visnovský, J

2011-09-01

To evaluate the usefullness of examination of methylation status of selected tumor-supressor genes in early diagnosis of ovarian cancer. Prospective clinical study. Department of Gynecology and Obstetrics, Department of Molecular Biology, Jessenius Medical Faculty, Commenius University, Martin, Slovak Republic. In this study we analyzed hypermethylation of 5 genes RASSF1A, GSTP, E-cadherin, p16 and APC in ovarian tumor samples from 34 patients - 13 patients with epithelial ovarian cancer, 2 patients with border-line ovarian tumors, 12 patients with benign lesions of ovaries and 7 patients with healthy ovarian tissue. The methylation status of promoter region of tumor-supressor genes was determined by Methylation Specific Polymerase Chain Reaction (MSP) using a nested two-step approach with bisulfite modified DNA template and specific primers. Gene methylation analysis revealed hypermethylation of gene RASSF1A (46%) and GSTP (8%) only in malignant ovarian tissue samples. Ecad, p16 and APC genes were methylated both in maignant and benign tissue samples. Methylation positivity in observed genes was present independently to all clinical stages of ovarian cancer and to tumor grades. However, there was observed a trend of increased number and selective involvement of methylated genes with increasing disease stages. Furthermore, there was no association between positive methylation status and histological subtypes of ovarian carcinomas. RASSF1A and GSTP promoter methylation positivity is associated with ovarian cancer. The revealed gene-selective methylation positivity and the increased number of methylated genes with advancing disease stages could be considered as a useful molecular marker for early detection of ovarian cancer. However, there is need to find diagnostic approach of specifically and frequently methylated genes to determining a methylation phenotype for early detection of ovarian malignancies.

Development of a rapid method for direct detection of tet(M) genes in soil from Danish farmland

DEFF Research Database (Denmark)

Agersø, Yvonne; Sengeløv, Gitte; Jensen, Lars Bogø

2004-01-01

. The tet(M) gene was directly detected in 10-80% of the samples from the various farmland soils and could be detected in all samples tested after selective enrichment. To validate the obtained results, the method was applied to garden soil samples where lower prevalence of resistance was found. Result......A method for direct detection of antibiotic resistance genes in soil samples has been developed. The tetracycline resistance gene, tet(M), was used as a model. The method was validated on Danish farmland soil that had repeatedly been treated with pig manure slurry containing resistant bacteria......: A detection limit of 10(2)-10(3) copies of the tet(M) gene per gram of soil (in a Bacillus cereus group bacterium) was achieved. tet(M) gene was detected in soil samples with the highest prevalence on farmland treated with pig manure slurry....

Investigation of the molecular relationship between breast cancer and obesity by candidate gene prioritization methods

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Saba Garshasbi

2015-10-01

Full Text Available Background: Cancer and obesity are two major public health concerns. More than 12 million cases of cancer are reported annually. Many reports confirmed obesity as a risk factor for cancer. The molecular relationship between obesity and breast cancer has not been clear yet. The purpose of this study was to investigate priorities of effective genes in the molecular relationship between obesity and breast cancer. Methods: In this study, computer simulation method was used for prioritizing the genes that involved in the molecular links between obesity and breast cancer in laboratory of systems biology and bioinformatics (LBB, Tehran University, Tehran, Iran, from March to July 2014. In this study, ENDEAVOUR software was used for prioritizing the genes and integrating multiple data sources was used for data analysis. Training genes were selected from effective genes in obesity and/or breast cancer. Two groups of candidate genes were selected. The first group was included the existential genes in 5 common region chromosomes (between obesity and breast cancer and the second group was included the results of genes microarray data analysis of research Creighton, et al (In 2012 on patients with breast cancer. The microarray data were analyzed with GER2 software (R online software on GEO website. Finally, both training and candidate genes were entered in ENDEAVOUR software package. Results: The candidate genes were prioritized to four style and five genes in ten of the first priorities were repeated twice. In other word, the outcome of prioritizing of 72 genes (Product of microarray data analysis and genes of 5 common chromosome regions (Between obesity and breast cancer showed, 5 genes (TNFRSF10B, F2, IGFALS, NTRK3 and HSP90B1 were the priorities in the molecular connection between obesity and breast cancer. Conclusion: There are some common genes between breast cancer and obesity. So, molecular relationship is confirmed. In this study the possible effect

Link-based quantitative methods to identify differentially coexpressed genes and gene Pairs

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Ye Zhi-Qiang

2011-08-01

Full Text Available Abstract Background Differential coexpression analysis (DCEA is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance. Results We developed two link-based quantitative methods, DCp and DCe, to identify differentially coexpressed genes and gene pairs (links. Bearing the uniqueness of exploiting the quantitative coexpression change of each gene pair in the coexpression networks, both methods proved to be superior to currently popular methods in simulation studies. Re-mining of a publicly available type 2 diabetes (T2D expression dataset from the perspective of differential coexpression analysis led to additional discoveries than those from differential expression analysis. Conclusions This work pointed out the critical weakness of current popular DCEA methods, and proposed two link-based DCEA algorithms that will make contribution to the development of DCEA and help extend it to a broader spectrum.

HMM-Based Gene Annotation Methods

Energy Technology Data Exchange (ETDEWEB)

Haussler, David; Hughey, Richard; Karplus, Keven

1999-09-20

Development of new statistical methods and computational tools to identify genes in human genomic DNA, and to provide clues to their functions by identifying features such as transcription factor binding sites, tissue, specific expression and splicing patterns, and remove homologies at the protein level with genes of known function.

A high efficiency gene disruption strategy using a positive-negative split selection marker and electroporation for Fusarium oxysporum.

Science.gov (United States)

Liang, Liqin; Li, Jianqiang; Cheng, Lin; Ling, Jian; Luo, Zhongqin; Bai, Miao; Xie, Bingyan

2014-11-01

The Fusarium oxysporum species complex consists of fungal pathogens that cause serial vascular wilt disease on more than 100 cultivated species throughout the world. Gene function analysis is rapidly becoming more and more important as the whole-genome sequences of various F. oxysporum strains are being completed. Gene-disruption techniques are a common molecular tool for studying gene function, yet are often a limiting step in gene function identification. In this study we have developed a F. oxysporum high-efficiency gene-disruption strategy based on split-marker homologous recombination cassettes with dual selection and electroporation transformation. The method was efficiently used to delete three RNA-dependent RNA polymerase (RdRP) genes. The gene-disruption cassettes of three genes can be constructed simultaneously within a short time using this technique. The optimal condition for electroporation is 10μF capacitance, 300Ω resistance, 4kV/cm field strength, with 1μg of DNA (gene-disruption cassettes). Under these optimal conditions, we were able to obtain 95 transformants per μg DNA. And after positive-negative selection, the transformants were efficiently screened by PCR, screening efficiency averaged 85%: 90% (RdRP1), 85% (RdRP2) and 77% (RdRP3). This gene-disruption strategy should pave the way for high throughout genetic analysis in F. oxysporum. Copyright © 2014 Elsevier GmbH. All rights reserved.

Targeting of breast metastases using a viral gene vector with tumour-selective transcription.

LENUS (Irish Health Repository)

Rajendran, Simon

2012-01-31

BACKGROUND: Adeno-associated virus (AAV) vectors have significant potential as gene delivery vectors for cancer gene therapy. However, broad AAV2 tissue tropism results in nonspecific gene expression. MATERIALS AND METHODS: We investigated use of the C-X-C chemokine receptor type 4 (CXCR4) promoter to restrict AAV expression to tumour cells, in subcutaneous MCF-7 xenograft mouse models of breast cancer and in patient samples, using bioluminescent imaging and flow cytometric analysis. RESULTS: Higher transgene expression levels were observed in subcutaneous MCF-7 tumours relative to normal tissue (muscle) using the CXCR4 promoter, unlike a ubiquitously expressing Cytomegalovirus promoter construct, with preferential AAVCXCR4 expression in epithelial tumour and CXCR4-positive cells. Transgene expression following intravenously administered AAVCXCR4 in a model of liver metastasis was detected specifically in livers of tumour bearing mice. Ex vivo analysis using patient samples also demonstrated higher AAVCXCR4 expression in tumour compared with normal liver tissue. CONCLUSION: This study demonstrates for the first time, the potential for systemic administration of AAV2 vector for tumour-selective gene therapy.

Flexible metabolic pathway construction using modular and divisible selection gene regulators

DEFF Research Database (Denmark)

Rugbjerg, Peter; Myling-Petersen, Nils; Sommer, Morten Otto Alexander

2015-01-01

Genetic selections are important to biological engineering. Although selectable traits are limited,currently each trait only permits simultaneous introduction of a single DNA fragment. Complex pathwayand strain construction however depends on rapid, combinatorial introduction of many genes thaten...

Combining gene prediction methods to improve metagenomic gene annotation

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Rosen Gail L

2011-01-01

Full Text Available Abstract Background Traditional gene annotation methods rely on characteristics that may not be available in short reads generated from next generation technology, resulting in suboptimal performance for metagenomic (environmental samples. Therefore, in recent years, new programs have been developed that optimize performance on short reads. In this work, we benchmark three metagenomic gene prediction programs and combine their predictions to improve metagenomic read gene annotation. Results We not only analyze the programs' performance at different read-lengths like similar studies, but also separate different types of reads, including intra- and intergenic regions, for analysis. The main deficiencies are in the algorithms' ability to predict non-coding regions and gene edges, resulting in more false-positives and false-negatives than desired. In fact, the specificities of the algorithms are notably worse than the sensitivities. By combining the programs' predictions, we show significant improvement in specificity at minimal cost to sensitivity, resulting in 4% improvement in accuracy for 100 bp reads with ~1% improvement in accuracy for 200 bp reads and above. To correctly annotate the start and stop of the genes, we find that a consensus of all the predictors performs best for shorter read lengths while a unanimous agreement is better for longer read lengths, boosting annotation accuracy by 1-8%. We also demonstrate use of the classifier combinations on a real dataset. Conclusions To optimize the performance for both prediction and annotation accuracies, we conclude that the consensus of all methods (or a majority vote is the best for reads 400 bp and shorter, while using the intersection of GeneMark and Orphelia predictions is the best for reads 500 bp and longer. We demonstrate that most methods predict over 80% coding (including partially coding reads on a real human gut sample sequenced by Illumina technology.

Global patterns of diversity and selection in human tyrosinase gene.

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Hudjashov, Georgi; Villems, Richard; Kivisild, Toomas

2013-01-01

Global variation in skin pigmentation is one of the most striking examples of environmental adaptation in humans. More than two hundred loci have been identified as candidate genes in model organisms and a few tens of these have been found to be significantly associated with human skin pigmentation in genome-wide association studies. However, the evolutionary history of different pigmentation genes is rather complex: some loci have been subjected to strong positive selection, while others evolved under the relaxation of functional constraints in low UV environment. Here we report the results of a global study of the human tyrosinase gene, which is one of the key enzymes in melanin production, to assess the role of its variation in the evolution of skin pigmentation differences among human populations. We observe a higher rate of non-synonymous polymorphisms in the European sample consistent with the relaxation of selective constraints. A similar pattern was previously observed in the MC1R gene and concurs with UV radiation-driven model of skin color evolution by which mutations leading to lower melanin levels and decreased photoprotection are subject to purifying selection at low latitudes while being tolerated or even favored at higher latitudes because they facilitate UV-dependent vitamin D production. Our coalescent date estimates suggest that the non-synonymous variants, which are frequent in Europe and North Africa, are recent and have emerged after the separation of East and West Eurasian populations.

Genetic diversity of selected genes that are potentially economically important in feral sheep of New Zealand

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Sedcole J Richard

2010-12-01

Full Text Available Abstract Background Feral sheep are considered to be a source of genetic variation that has been lost from their domestic counterparts through selection. Methods This study investigates variation in the genes KRTAP1-1, KRT33, ADRB3 and DQA2 in Merino-like feral sheep populations from New Zealand and its offshore islands. These genes have previously been shown to influence wool, lamb survival and animal health. Results All the genes were polymorphic, but no new allele was identified in the feral populations. In some of these populations, allele frequencies differed from those observed in commercial Merino sheep and other breeds found in New Zealand. Heterozygosity levels were comparable to those observed in other studies on feral sheep. Our results suggest that some of the feral populations may have been either inbred or outbred over the duration of their apparent isolation. Conclusion The variation described here allows us to draw some conclusions about the likely genetic origin of the populations and selective pressures that may have acted upon them, but they do not appear to be a source of new genetic material, at least for these four genes.

Mining method selection by integrated AHP and PROMETHEE method.

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Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

2012-03-01

Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

A complex selection signature at the human AVPR1B gene

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Cagliani Rachele

2009-06-01

Full Text Available Abstract Background The vasopressin receptor type 1b (AVPR1B is mainly expressed by pituitary corticotropes and it mediates the stimulatory effects of AVP on ACTH release; common AVPR1B haplotypes have been involved in mood and anxiety disorders in humans, while rodents lacking a functional receptor gene display behavioral defects and altered stress responses. Results Here we have analyzed the two exons of the gene and the data we present suggest that AVPR1B has been subjected to natural selection in humans. In particular, analysis of exon 2 strongly suggests the action of balancing selection in African populations and Europeans: the region displays high nucleotide diversity, an excess of intermediate-frequency alleles, a higher level of within-species diversity compared to interspecific divergence and a genealogy with common haplotypes separated by deep branches. This relatively unambiguous situation coexists with unusual features across exon 1, raising the possibility that a nonsynonymous variant (Gly191Arg in this region has been subjected to directional selection. Conclusion Although the underlying selective pressure(s remains to be identified, we consider this to be among the first documented examples of a gene involved in mood disorders and subjected to natural selection in humans; this observation might add support to the long-debated idea that depression/low mood might have played an adaptive role during human evolution.

A complex selection signature at the human AVPR1B gene.

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Cagliani, Rachele; Fumagalli, Matteo; Pozzoli, Uberto; Riva, Stefania; Cereda, Matteo; Comi, Giacomo P; Pattini, Linda; Bresolin, Nereo; Sironi, Manuela

2009-06-01

The vasopressin receptor type 1b (AVPR1B) is mainly expressed by pituitary corticotropes and it mediates the stimulatory effects of AVP on ACTH release; common AVPR1B haplotypes have been involved in mood and anxiety disorders in humans, while rodents lacking a functional receptor gene display behavioral defects and altered stress responses. Here we have analyzed the two exons of the gene and the data we present suggest that AVPR1B has been subjected to natural selection in humans. In particular, analysis of exon 2 strongly suggests the action of balancing selection in African populations and Europeans: the region displays high nucleotide diversity, an excess of intermediate-frequency alleles, a higher level of within-species diversity compared to interspecific divergence and a genealogy with common haplotypes separated by deep branches. This relatively unambiguous situation coexists with unusual features across exon 1, raising the possibility that a nonsynonymous variant (Gly191Arg) in this region has been subjected to directional selection. Although the underlying selective pressure(s) remains to be identified, we consider this to be among the first documented examples of a gene involved in mood disorders and subjected to natural selection in humans; this observation might add support to the long-debated idea that depression/low mood might have played an adaptive role during human evolution.

Lentiviral gene ontology (LeGO) vectors equipped with novel drug-selectable fluorescent proteins: new building blocks for cell marking and multi-gene analysis.

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Weber, K; Mock, U; Petrowitz, B; Bartsch, U; Fehse, B

2010-04-01

Vector-encoded fluorescent proteins (FPs) facilitate unambiguous identification or sorting of gene-modified cells by fluorescence-activated cell sorting (FACS). Exploiting this feature, we have recently developed lentiviral gene ontology (LeGO) vectors (www.LentiGO-Vectors.de) for multi-gene analysis in different target cells. In this study, we extend the LeGO principle by introducing 10 different drug-selectable FPs created by fusing one of the five selection marker (protecting against blasticidin, hygromycin, neomycin, puromycin and zeocin) and one of the five FP genes (Cerulean, eGFP, Venus, dTomato and mCherry). All tested fusion proteins allowed both fluorescence-mediated detection and drug-mediated selection of LeGO-transduced cells. Newly generated codon-optimized hygromycin- and neomycin-resistance genes showed improved expression as compared with their ancestors. New LeGO constructs were produced at titers >10(6) per ml (for non-concentrated supernatants). We show efficient combinatorial marking and selection of various cells, including mesenchymal stem cells, simultaneously transduced with different LeGO constructs. Inclusion of the cytomegalovirus early enhancer/chicken beta-actin promoter into LeGO vectors facilitated robust transgene expression in and selection of neural stem cells and their differentiated progeny. We suppose that the new drug-selectable markers combining advantages of FACS and drug selection are well suited for numerous applications and vector systems. Their inclusion into LeGO vectors opens new possibilities for (stem) cell tracking and functional multi-gene analysis.

Recurrent selection on the Winters sex-ratio genes in Drosophila simulans.

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Kingan, Sarah B; Garrigan, Daniel; Hartl, Daniel L

2010-01-01

Selfish genes, such as meiotic drive elements, propagate themselves through a population without increasing the fitness of host organisms. X-linked (or Y-linked) meiotic drive elements reduce the transmission of the Y (X) chromosome and skew progeny and population sex ratios, leading to intense conflict among genomic compartments. Drosophila simulans is unusual in having a least three distinct systems of X chromosome meiotic drive. Here, we characterize naturally occurring genetic variation at the Winters sex-ratio driver (Distorter on the X or Dox), its progenitor gene (Mother of Dox or MDox), and its suppressor gene (Not Much Yang or Nmy), which have been previously mapped and characterized. We survey three North American populations as well as 13 globally distributed strains and present molecular polymorphism data at the three loci. We find that all three genes show signatures of selection in North America, judging from levels of polymorphism and skews in the site-frequency spectrum. These signatures likely result from the biased transmission of the driver and selection on the suppressor for the maintenance of equal sex ratios. Coalescent modeling indicates that the timing of selection is more recent than the age of the alleles, suggesting that the driver and suppressor are coevolving under an evolutionary "arms race." None of the Winters sex-ratio genes are fixed in D. simulans, and at all loci we find ancestral alleles, which lack the gene insertions and exhibit high levels of nucleotide polymorphism compared to the derived alleles. In addition, we find several "null" alleles that have mutations on the derived Dox background, which result in loss of drive function. We discuss the possible causes of the maintenance of presence-absence polymorphism in the Winters sex-ratio genes.

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

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Teng Shaolei

2013-01-01

Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

B lymphocyte selection and age-related changes in VH gene usage in mutant Alicia rabbits.

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Zhu, X; Boonthum, A; Zhai, S K; Knight, K L

1999-09-15

Young Alicia rabbits use VHa-negative genes, VHx and VHy, in most VDJ genes, and their serum Ig is VHa negative. However, as Alicia rabbits age, VHa2 allotype Ig is produced at high levels. We investigated which VH gene segments are used in the VDJ genes of a2 Ig-secreting hybridomas and of a2 Ig+ B cells from adult Alicia rabbits. We found that 21 of the 25 VDJ genes used the a2-encoding genes, VH4 or VH7; the other four VDJ genes used four unknown VH gene segments. Because VH4 and VH7 are rarely found in VDJ genes of normal or young Alicia rabbits, we investigated the timing of rearrangement of these genes in Alicia rabbits. During fetal development, VH4 was used in 60-80% of nonproductively rearranged VDJ genes, and VHx and VHy together were used in 10-26%. These data indicate that during B lymphopoiesis VH4 is preferentially rearranged. However, the percentage of productive VHx- and VHy-utilizing VDJ genes increased from 38% at day 21 of gestation to 89% at birth (gestation day 31), whereas the percentage of VH4-utilizing VDJ genes remained at 15%. These data suggest that during fetal development, either VH4-utilizing B-lineage cells are selectively eliminated, or B cells with VHx- and VHy-utilizing VDJ genes are selectively expanded, or both. The accumulation of peripheral VH4-utilizing a2 B cells with age indicates that these B cells might be selectively expanded in the periphery. We discuss the possible selection mechanisms that regulate VH gene segment usage in rabbit B cells during lymphopoiesis and in the periphery.

A Selection Method for COTS Systems

DEFF Research Database (Denmark)

Hedman, Jonas

new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing feature...... behind the method is that improved understanding of organizational' ends' or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends' (e.g. improved organizational effectiveness) and ‘means' (e.g. implementing COTS systems). This way of approaching...

Expression stability and selection of optimal reference genes for gene expression normalization in early life stage rainbow trout exposed to cadmium and copper.

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Shekh, Kamran; Tang, Song; Niyogi, Som; Hecker, Markus

2017-09-01

Gene expression analysis represents a powerful approach to characterize the specific mechanisms by which contaminants interact with organisms. One of the key considerations when conducting gene expression analyses using quantitative real-time reverse transcription-polymerase chain reaction (qPCR) is the selection of appropriate reference genes, which is often overlooked. Specifically, to reach meaningful conclusions when using relative quantification approaches, expression levels of reference genes must be highly stable and cannot vary as a function of experimental conditions. However, to date, information on the stability of commonly used reference genes across developmental stages, tissues and after exposure to contaminants such as metals is lacking for many vertebrate species including teleost fish. Therefore, in this study, we assessed the stability of expression of 8 reference gene candidates in the gills and skin of three different early life-stages of rainbow trout after acute exposure (24h) to two metals, cadmium (Cd) and copper (Cu) using qPCR. Candidate housekeeping genes were: beta actin (b-actin), DNA directed RNA polymerase II subunit I (DRP2), elongation factor-1 alpha (EF1a), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), glucose-6-phosphate dehydrogenase (G6PD), hypoxanthine phosphoribosyltransferase (HPRT), ribosomal protein L8 (RPL8), and 18S ribosomal RNA (18S). Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method were employed to systematically evaluate the expression stability of these candidate genes under control and exposed conditions as well as across three different life-stages. Finally, stability of genes was ranked by taking geometric means of the ranks established by the different methods. Stability of reference genes was ranked in the following order (from lower to higher stability): HPRT

Selecting patients with young-onset colorectal cancer for mismatch repair gene analysis

DEFF Research Database (Denmark)

Walker, M; O'Sullivan, B; Perakath, B

2007-01-01

BACKGROUND: Young patients with colorectal cancer are at increased risk of carrying a germline mutation in mismatch repair (MMR) genes. This study investigated the role of clinical criteria and immunohistochemistry for MMR proteins in selecting young patients for mutation testing. METHODS: A cohort...... of 56 consecutive patients with colorectal cancer aged less than 45 years were stratified into three groups based on clinical criteria: 'Amsterdam criteria', 'high risk' and 'young onset only'. Immunohistochemistry for four MMR proteins was carried out and the rate of compliance with clinical guidelines...

Selection of reference genes for qPCR in hairy root cultures of peanut

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Medrano Giuliana

2011-10-01

Full Text Available Abstract Background Hairy root cultures produced via Agrobacterium rhizogenes-mediated transformation have emerged as practical biological models to elucidate the biosynthesis of specialized metabolites. To effectively understand the expression patterns of the genes involved in the metabolic pathways of these compounds, reference genes need to be systematically validated under specific experimental conditions as established by the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments guidelines. In the present report we describe the first validation of reference genes for RT-qPCR in hairy root cultures of peanut which produce stilbenoids upon elicitor treatments. Results A total of 21 candidate reference genes were evaluated. Nineteen genes were selected based on previous qPCR studies in plants and two were from the T-DNAs transferred from A. rhizogenes. Nucleotide sequences of peanut candidate genes were obtained using their homologous sequences in Arabidopsis. To identify the suitable primers, calibration curves were obtained for each candidate reference gene. After data analysis, 12 candidate genes meeting standard efficiency criteria were selected. The expression stability of these genes was analyzed using geNorm and NormFinder algorithms and a ranking was established based on expression stability of the genes. Candidate reference gene expression was shown to have less variation in methyl jasmonate (MeJA treated root cultures than those treated with sodium acetate (NaOAc. Conclusions This work constitutes the first effort to validate reference genes for RT-qPCR in hairy roots. While these genes were selected under conditions of NaOAc and MeJA treatment, we anticipate these genes to provide good targets for reference genes for hairy roots under a variety of stress conditions. The lead reference genes were a gene encoding for a TATA box binding protein (TBP2 and a gene encoding a ribosomal protein (RPL8C. A

Diagnosis of Neisseria gonorrhoeae among pregnant women by culture method and PCR on cppB gene

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Jalal Mardaneh

2013-11-01

Full Text Available Background: Neisseria gonorrhoeae is a human obligate pathogen and the etiological agent of gonorrhea. Health irreparable complications resulting from gonorrhea disease occur mainly in pregnant women and neonates. Aim of this study was diagnosis of Neisseria gonorrhoeae among pregnant women with using culture and molecular method by amplification of cppB gene with PCR. Material and Methods: In this cross-sectional study, two endocervical swab specimens were obtained from 1100 pregnant women who referred to Shiraz Hospitals. Culture on nonselective and selective media and nucleic acid amplification test (NAAT were performed for detection of Neisseria gonorrhoeae cppB gene. Results: All endocervical swabs cultures on selective and nonselective media were negative for Neisseria gonorrhoeae. Among examined endocervical swabs, 13samples (1.18% were positive by nucleic acid amplification of Neisseria gonorrgoeae cppB gene. Conclusion: Negative results of culture and positive results of PCR in this study indicate that however culture is gold standard method for detection of Neisseria gonorrhoeae but due to bacterial autolysis, poor sampling techniques and improper specimen storage and transport, its value decline as compared with Nucleic acid amplification test (NAAT.

Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L..

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Roberta Fogliatto Mariot

Full Text Available Potato (Solanum tuberosum yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3 and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A. According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

Selection of reference genes for transcriptional analysis of edible tubers of potato (Solanum tuberosum L.).

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Mariot, Roberta Fogliatto; de Oliveira, Luisa Abruzzi; Voorhuijzen, Marleen M; Staats, Martijn; Hutten, Ronald C B; Van Dijk, Jeroen P; Kok, Esther; Frazzon, Jeverson

2015-01-01

Potato (Solanum tuberosum) yield has increased dramatically over the last 50 years and this has been achieved by a combination of improved agronomy and biotechnology efforts. Gene studies are taking place to improve new qualities and develop new cultivars. Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is a bench-marking analytical tool for gene expression analysis, but its accuracy is highly dependent on a reliable normalization strategy of an invariant reference genes. For this reason, the goal of this work was to select and validate reference genes for transcriptional analysis of edible tubers of potato. To do so, RT-qPCR primers were designed for ten genes with relatively stable expression in potato tubers as observed in RNA-Seq experiments. Primers were designed across exon boundaries to avoid genomic DNA contamination. Differences were observed in the ranking of candidate genes identified by geNorm, NormFinder and BestKeeper algorithms. The ranks determined by geNorm and NormFinder were very similar and for all samples the most stable candidates were C2, exocyst complex component sec3 (SEC3) and ATCUL3/ATCUL3A/CUL3/CUL3A (CUL3A). According to BestKeeper, the importin alpha and ubiquitin-associated/ts-n genes were the most stable. Three genes were selected as reference genes for potato edible tubers in RT-qPCR studies. The first one, called C2, was selected in common by NormFinder and geNorm, the second one is SEC3, selected by NormFinder, and the third one is CUL3A, selected by geNorm. Appropriate reference genes identified in this work will help to improve the accuracy of gene expression quantification analyses by taking into account differences that may be observed in RNA quality or reverse transcription efficiency across the samples.

A Scan for Positively Selected Genes in the Genomes of Humans and Chimpanzees

DEFF Research Database (Denmark)

Nielsen, Rasmus; Bustamente, Carlos; Clark, Andrew G.

2005-01-01

Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect...... such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved...

A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

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Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

2016-06-01

This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Selection in the dopamine receptor 2 gene: a candidate SNP study

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Tobias Göllner

2015-08-01

Full Text Available Dopamine is a major neurotransmitter in the human brain and is associated with various diseases. Schizophrenia, for example, is treated by blocking the dopamine receptors type 2. Shaner, Miller & Mintz (2004 stated that schizophrenia was the low fitness variant of a highly variable mental trait. We therefore explore whether the dopamine receptor 2 gene (DRD2 underwent any selection processes. We acquired genotype data of the 1,000 Genomes project (phase I, which contains 1,093 individuals from 14 populations. We included single nucleotide polymorphisms (SNPs with two minor allele frequencies (MAFs in the analysis: MAF over 0.05 and over 0.01. This is equivalent to 151 SNPs (MAF > 0.05 and 246 SNPs (MAF > 0.01 for DRD2. We used two different approaches (an outlier approach and a Bayesian approach to detect loci under selection. The combined results of both approaches yielded nine (MAF > 0.05 and two candidate SNPs (MAF > 0.01, under balancing selection. We also found weak signs for directional selection on DRD2, but in our opinion these were too weak to draw any final conclusions on directional selection in DRD2. All candidates for balancing selection are in the intronic region of the gene and only one (rs12574471 has been mentioned in the literature. Two of our candidate SNPs are located in specific regions of the gene: rs80215768 lies within a promoter flanking region and rs74751335 lies within a transcription factor binding site. We strongly encourage research on our candidate SNPs and their possible effects.

Selecting Question-Specific Genes to Reduce Incongruence in Phylogenomics: A Case Study of Jawed Vertebrate Backbone Phylogeny.

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Chen, Meng-Yun; Liang, Dan; Zhang, Peng

2015-11-01

Incongruence between different phylogenomic analyses is the main challenge faced by phylogeneticists in the genomic era. To reduce incongruence, phylogenomic studies normally adopt some data filtering approaches, such as reducing missing data or using slowly evolving genes, to improve the signal quality of data. Here, we assembled a phylogenomic data set of 58 jawed vertebrate taxa and 4682 genes to investigate the backbone phylogeny of jawed vertebrates under both concatenation and coalescent-based frameworks. To evaluate the efficiency of extracting phylogenetic signals among different data filtering methods, we chose six highly intractable internodes within the backbone phylogeny of jawed vertebrates as our test questions. We found that our phylogenomic data set exhibits substantial conflicting signal among genes for these questions. Our analyses showed that non-specific data sets that are generated without bias toward specific questions are not sufficient to produce consistent results when there are several difficult nodes within a phylogeny. Moreover, phylogenetic accuracy based on non-specific data is considerably influenced by the size of data and the choice of tree inference methods. To address such incongruences, we selected genes that resolve a given internode but not the entire phylogeny. Notably, not only can this strategy yield correct relationships for the question, but it also reduces inconsistency associated with data sizes and inference methods. Our study highlights the importance of gene selection in phylogenomic analyses, suggesting that simply using a large amount of data cannot guarantee correct results. Constructing question-specific data sets may be more powerful for resolving problematic nodes. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Expression of Root Genes in Arabidopsis Seedlings Grown by Standard and Improved Growing Methods.

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Qu, Yanli; Liu, Shuai; Bao, Wenlong; Xue, Xian; Ma, Zhengwen; Yokawa, Ken; Baluška, František; Wan, Yinglang

2017-05-03

Roots of Arabidopsis thaliana seedlings grown in the laboratory using the traditional plant-growing culture system (TPG) were covered to maintain them in darkness. This new method is based on a dark chamber and is named the improved plant-growing method (IPG). We measured the light conditions in dark chambers, and found that the highest light intensity was dramatically reduced deeper in the dark chamber. In the bottom and side parts of dark chambers, roots were almost completely shaded. Using the high-throughput RNA sequencing method on the whole RNA extraction from roots, we compared the global gene expression levels in roots of seedlings from these two conditions and identified 141 differently expressed genes (DEGs) between them. According to the KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment, the flavone and flavonol biosynthesis and flavonoid biosynthesis pathways were most affected among all annotated pathways. Surprisingly, no genes of known plant photoreceptors were identified as DEGs by this method. Considering that the light intensity was decreased in the IPG system, we collected four sections (1.5 cm for each) of Arabidopsis roots grown in TPG and IPG conditions, and the spatial-related differential gene expression levels of plant photoreceptors and polar auxin transporters, including CRY1 , CRY2 , PHYA , PHYB , PHOT1 , PHOT2 , and UVR8 were analyzed by qRT-PCR. Using these results, we generated a map of the spatial-related expression patterns of these genes under IPG and TPG conditions. The expression levels of light-related genes in roots is highly sensitive to illumination and it provides a background reference for selecting an improved culture method for laboratory-maintained Arabidopsis seedlings.

Tagging of blast resistance gene(s) to DNA markers and marker-assisted selection (MAS) in rice improvement

International Nuclear Information System (INIS)

Zhuang, J.Y.; Lu, J.; Qian, H.R.; Lin, H.X.; Zheng, K.L.

1998-01-01

This paper reports progress made on the tagging of blast resistance gene(s) to DNA markers and on the initiation of marker-assisted selection (MAS) for blast resistance in rice improvement. A pair of near isogenic lines, K8OR and K79S, were developed using a Chinese landrace Hong-jiao-zhan as the resistance donor. Ten putatively positive markers were identified by screening 177 mapped DNA markers. Using the F 2 population of 143 plants and the derived F 3 lines, three Restriction Fragment Length Polymorphism (RFLP) markers (RG81, RG869 and RZ397) on chromosome 12 of rice were identified to be closely linked to the blast resistance gene Pi-12(t). The genetic distance between Pi-12(t) and the closest marker RG869 was 5.1 cM. By employing the bulk segregant analysis (BSA) procedure, six of 199 arbitrary primers were found to produce positive Randomly Amplified Polymorphic DNA (RAPD) bands. Tight linkage between Pi-12(t) and three RAPD bands, each from a different primer, was confirmed after amplification of DNA of all F 2 individuals. Two fragments were cloned and sequenced, and two sequence characterised amplified re-ion (SCAR) markers were established. In two other F 3 populations, Xian-feng I/Tetep and Xian-feng, 1/Hong-jiao-zhan, the blast resistance was found to be controlled by interactions of two or more genes. One resistance gene was located in the vicinity of RG81 in both populations. Work to identify other gene(s) is currently under way. Marker assisted selection for blast resistance was initiated. Crosses were made between elite varieties and blast resistance donors to develop populations for DNA marker-assisted selection of blast resistance. In addition, 48 varieties widely used in current rice breeding programs were provided by rice breeders. DNA marker-based polymorphism among, these varieties and resistance donors were analysed to produce a database for future MAS program. (author)

Antibiosis and bmyB Gene Presence As Prevalent Traits for the Selection of Efficient Bacillus Biocontrol Agents against Crown Gall Disease

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Olfa Frikha-Gargouri

2017-08-01

Full Text Available This study aimed to improve the screening method for the selection of Bacillus biocontrol agents against crown gall disease. The relationship between the strain biocontrol ability and their in vitro studied traits was investigated to identify the most important factors to be considered for the selection of effective biocontrol agents. In fact, previous selection procedure relying only on in vitro antibacterial activity was shown to be not suitable in some cases. A direct plant-protection strategy was performed to screen the 32 Bacillus biocontrol agent candidates. Moreover, potential in vitro biocontrol traits were investigated including biofilm formation, motility, hemolytic activity, detection of lipopeptide biosynthetic genes (sfp, ituC and bmyB and production of antibacterial compounds. The obtained results indicated high correlations of the efficiency of the biocontrol with the reduction of gall weight (p = 0.000 and the antibacterial activity in vitro (p = 0.000. Moreover, there was strong correlations of the efficiency of the biocontrol (p = 0.004 and the reduction in gall weight (p = 0.000 with the presence of the bmyB gene. This gene directs the synthesis of the lipopeptide bacillomycin belonging to the iturinic family of lipopeptides. These results were also confirmed by the two-way hierarchical cluster analysis and the correspondence analysis showing the relatedness of these four variables. According to the obtained results a new screening procedure of Bacillus biocontrol agents against crown gall disease could be advanced consisting on two step selection procedure. The first consists on selecting strains with high antibacterial activity in vitro or those harbouring the bmyB gene. Further selection has to be performed on tomato plants in vivo. Moreover, based on the results of the biocontrol assay, five potent strains exhibiting high biocontrol abilities were selected. They were identified as Bacillus subtilis or Bacillus

An evolutionarily conserved gene family encodes proton-selective ion channels.

Science.gov (United States)

Tu, Yu-Hsiang; Cooper, Alexander J; Teng, Bochuan; Chang, Rui B; Artiga, Daniel J; Turner, Heather N; Mulhall, Eric M; Ye, Wenlei; Smith, Andrew D; Liman, Emily R

2018-03-02

Ion channels form the basis for cellular electrical signaling. Despite the scores of genetically identified ion channels selective for other monatomic ions, only one type of proton-selective ion channel has been found in eukaryotic cells. By comparative transcriptome analysis of mouse taste receptor cells, we identified Otopetrin1 (OTOP1), a protein required for development of gravity-sensing otoconia in the vestibular system, as forming a proton-selective ion channel. We found that murine OTOP1 is enriched in acid-detecting taste receptor cells and is required for their zinc-sensitive proton conductance. Two related murine genes, Otop2 and Otop3 , and a Drosophila ortholog also encode proton channels. Evolutionary conservation of the gene family and its widespread tissue distribution suggest a broad role for proton channels in physiology and pathophysiology. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Multiplex Real-Time PCR for Detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL) Genes from Selective Enrichments from Animals and Retail Meat

Science.gov (United States)

Velasco, Valeria; Sherwood, Julie S.; Rojas-García, Pedro P.; Logue, Catherine M.

2014-01-01

The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL) genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat). The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus), mecA (associated with methicillin resistance) and PVL (virulence factor), and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68–0.88 (from substantial to almost perfect agreement) and 0.29–0.77 (from fair to substantial agreement) for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0–0.49 (from no agreement beyond that expected by chance to moderate agreement) for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA) using

Multiplex real-time PCR for detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL genes from selective enrichments from animals and retail meat.

Directory of Open Access Journals (Sweden)

Valeria Velasco

Full Text Available The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat. The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus, mecA (associated with methicillin resistance and PVL (virulence factor, and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68-0.88 (from substantial to almost perfect agreement and 0.29-0.77 (from fair to substantial agreement for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0-0.49 (from no agreement beyond that expected by chance to moderate agreement for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA

Sexual selection and magic traits in speciation with gene flow

Directory of Open Access Journals (Sweden)

Maria R. SERVEDIO, Michael KOPP

2012-06-01

Full Text Available The extent to which sexual selection is involved in speciation with gene flow remains an open question and the subject of much research. Here, we propose that some insight can be gained from considering the concept of magic traits (i.e., traits involved in both reproductive isolation and ecological divergence. Both magic traits and other, “non-magic”, traits can contribute to speciation via a number of specific mechanisms. We argue that many of these mechanisms are likely to differ widely in the extent to which they involve sexual selection. Furthermore, in some cases where sexual selection is present, it may be prone to inhibit rather than drive speciation. Finally, there are a priori reasons to believe that certain categories of traits are much more effective than others in driving speciation. The combination of these points suggests a classification of traits that may shed light on the broader role of sexual selection in speciation with gene flow. In particular, we suggest that sexual selection can act as a driver of speciation in some scenarios, but may play a negligible role in potentially common categories of magic traits, and may be likely to inhibit speciation in common categories of non-magic traits [Current Zoology 58 (3: 507–513, 2012].

Differential selection on carotenoid biosynthesis genes as a function of gene position in the metabolic pathway: a study on the carrot and dicots.

Directory of Open Access Journals (Sweden)

Jérémy Clotault

Full Text Available Selection of genes involved in metabolic pathways could target them differently depending on the position of genes in the pathway and on their role in controlling metabolic fluxes. This hypothesis was tested in the carotenoid biosynthesis pathway using population genetics and phylogenetics.Evolutionary rates of seven genes distributed along the carotenoid biosynthesis pathway, IPI, PDS, CRTISO, LCYB, LCYE, CHXE and ZEP, were compared in seven dicot taxa. A survey of deviations from neutrality expectations at these genes was also undertaken in cultivated carrot (Daucus carota subsp. sativus, a species that has been intensely bred for carotenoid pattern diversification in its root during its cultivation history. Parts of sequences of these genes were obtained from 46 individuals representing a wide diversity of cultivated carrots. Downstream genes exhibited higher deviations from neutral expectations than upstream genes. Comparisons of synonymous and nonsynonymous substitution rates between genes among dicots revealed greater constraints on upstream genes than on downstream genes. An excess of intermediate frequency polymorphisms, high nucleotide diversity and/or high differentiation of CRTISO, LCYB1 and LCYE in cultivated carrot suggest that balancing selection may have targeted genes acting centrally in the pathway.Our results are consistent with relaxed constraints on downstream genes and selection targeting the central enzymes of the carotenoid biosynthesis pathway during carrot breeding history.

The utility of optical detection system (qPCR) and bioinformatics methods in reference gene expression analysis

Science.gov (United States)

Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; PlÄ der, Wojciech; Przybecki, Zbigniew

2016-09-01

Real-time quantitative polymerase chain reaction is consider as the most reliable method for gene expression studies. However, the expression of target gene could be misinterpreted due to improper normalization. Therefore, the crucial step for analysing of qPCR data is selection of suitable reference genes, which should be validated experimentally. In order to choice the gene with stable expression in the designed experiment, we performed reference gene expression analysis. In this study genes described in the literature and novel genes predicted as control genes, based on the in silico analysis of transcriptome data were used. Analysis with geNorm and NormFinder algorithms allow to create the ranking of candidate genes and indicate the best reference for flower morphogenesis study. According to the results, genes CACS and CYCL were characterised the most stable expression, but the least suitable genes were TUA and EF.

Selection of Highly Expressed Gene Variants in Escherichia coli Using Translationally Coupled Antibiotic Selection Markers

DEFF Research Database (Denmark)

Rennig, Maja; Daley, Daniel O.; Nørholm, Morten H. H.

2018-01-01

Strategies to select highly expressed variants of a protein coding sequence are usually based on trial-and-error approaches, which are time-consuming and expensive. We address this problem using translationally coupled antibiotic resistance markers. The system requires that the target gene can...

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

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Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

2016-01-11

Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

"Every Gene Is Everywhere but the Environment Selects": Global Geolocalization of Gene Sharing in Environmental Samples through Network Analysis.

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Fondi, Marco; Karkman, Antti; Tamminen, Manu V; Bosi, Emanuele; Virta, Marko; Fani, Renato; Alm, Eric; McInerney, James O

2016-05-13

The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as "everything is everywhere but the environment selects." While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Selection-independent generation of gene knockout mouse embryonic stem cells using zinc-finger nucleases.

Directory of Open Access Journals (Sweden)

Anna Osiak

Full Text Available Gene knockout in murine embryonic stem cells (ESCs has been an invaluable tool to study gene function in vitro or to generate animal models with altered phenotypes. Gene targeting using standard techniques, however, is rather inefficient and typically does not exceed frequencies of 10(-6. In consequence, the usage of complex positive/negative selection strategies to isolate targeted clones has been necessary. Here, we present a rapid single-step approach to generate a gene knockout in mouse ESCs using engineered zinc-finger nucleases (ZFNs. Upon transient expression of ZFNs, the target gene is cleaved by the designer nucleases and then repaired by non-homologous end-joining, an error-prone DNA repair process that introduces insertions/deletions at the break site and therefore leads to functional null mutations. To explore and quantify the potential of ZFNs to generate a gene knockout in pluripotent stem cells, we generated a mouse ESC line containing an X-chromosomally integrated EGFP marker gene. Applying optimized conditions, the EGFP locus was disrupted in up to 8% of ESCs after transfection of the ZFN expression vectors, thus obviating the need of selection markers to identify targeted cells, which may impede or complicate downstream applications. Both activity and ZFN-associated cytotoxicity was dependent on vector dose and the architecture of the nuclease domain. Importantly, teratoma formation assays of selected ESC clones confirmed that ZFN-treated ESCs maintained pluripotency. In conclusion, the described ZFN-based approach represents a fast strategy for generating gene knockouts in ESCs in a selection-independent fashion that should be easily transferrable to other pluripotent stem cells.

Examination of Signatures of Recent Positive Selection on Genes Involved in Human Sialic Acid Biology.

Science.gov (United States)

Moon, Jiyun M; Aronoff, David M; Capra, John A; Abbot, Patrick; Rokas, Antonis

2018-03-28

Sialic acids are nine carbon sugars ubiquitously found on the surfaces of vertebrate cells and are involved in various immune response-related processes. In humans, at least 58 genes spanning diverse functions, from biosynthesis and activation to recycling and degradation, are involved in sialic acid biology. Because of their role in immunity, sialic acid biology genes have been hypothesized to exhibit elevated rates of evolutionary change. Consistent with this hypothesis, several genes involved in sialic acid biology have experienced higher rates of non-synonymous substitutions in the human lineage than their counterparts in other great apes, perhaps in response to ancient pathogens that infected hominins millions of years ago (paleopathogens). To test whether sialic acid biology genes have also experienced more recent positive selection during the evolution of the modern human lineage, reflecting adaptation to contemporary cosmopolitan or geographically-restricted pathogens, we examined whether their protein-coding regions showed evidence of recent hard and soft selective sweeps. This examination involved the calculation of four measures that quantify changes in allele frequency spectra, extent of population differentiation, and haplotype homozygosity caused by recent hard and soft selective sweeps for 55 sialic acid biology genes using publicly available whole genome sequencing data from 1,668 humans from three ethnic groups. To disentangle evidence for selection from confounding demographic effects, we compared the observed patterns in sialic acid biology genes to simulated sequences of the same length under a model of neutral evolution that takes into account human demographic history. We found that the patterns of genetic variation of most sialic acid biology genes did not significantly deviate from neutral expectations and were not significantly different among genes belonging to different functional categories. Those few sialic acid biology genes that

Tracing evolutionary relicts of positive selection on eight malaria-related immune genes in mammals.

Science.gov (United States)

Huang, Bing-Hong; Liao, Pei-Chun

2015-07-01

Plasmodium-induced malaria widely infects primates and other mammals. Multiple past studies have revealed that positive selection could be the main evolutionary force triggering the genetic diversity of anti-malaria resistance-associated genes in human or primates. However, researchers focused most of their attention on the infra-generic and intra-specific genome evolution rather than analyzing the complete evolutionary history of mammals. Here we extend previous research by testing the evolutionary link of natural selection on eight candidate genes associated with malaria resistance in mammals. Three of the eight genes were detected to be affected by recombination, including TNF-α, iNOS and DARC. Positive selection was detected in the rest five immunogenes multiple times in different ancestral lineages of extant species throughout the mammalian evolution. Signals of positive selection were exposed in four malaria-related immunogenes in primates: CCL2, IL-10, HO1 and CD36. However, selection signals of G6PD have only been detected in non-primate eutherians. Significantly higher evolutionary rates and more radical amino acid replacement were also detected in primate CD36, suggesting its functional divergence from other eutherians. Prevalent positive selection throughout the evolutionary trajectory of mammalian malaria-related genes supports the arms race evolutionary hypothesis of host genetic response of mammalian immunogenes to infectious pathogens. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

A Double Selection Approach to Achieve Specific Expression of Toxin Genes for Ovarian Cancer Gene Therapy

National Research Council Canada - National Science Library

Curiel, David T; Siegal, Gene; Wang, Minghui

2007-01-01

...) to achieve efficient and selective gene transfer to target tumor cells. Proposed herein is a strategy to modify one candidate vector, recombinant adenovirus, such that it embodies the requisite properties of efficacy and specificity...

Bayesian nonparametric variable selection as an exploratory tool for discovering differentially expressed genes.

Science.gov (United States)

Shahbaba, Babak; Johnson, Wesley O

2013-05-30

High-throughput scientific studies involving no clear a priori hypothesis are common. For example, a large-scale genomic study of a disease may examine thousands of genes without hypothesizing that any specific gene is responsible for the disease. In these studies, the objective is to explore a large number of possible factors (e.g., genes) in order to identify a small number that will be considered in follow-up studies that tend to be more thorough and on smaller scales. A simple, hierarchical, linear regression model with random coefficients is assumed for case-control data that correspond to each gene. The specific model used will be seen to be related to a standard Bayesian variable selection model. Relatively large regression coefficients correspond to potential differences in responses for cases versus controls and thus to genes that might 'matter'. For large-scale studies, and using a Dirichlet process mixture model for the regression coefficients, we are able to find clusters of regression effects of genes with increasing potential effect or 'relevance', in relation to the outcome of interest. One cluster will always correspond to genes whose coefficients are in a neighborhood that is relatively close to zero and will be deemed least relevant. Other clusters will correspond to increasing magnitudes of the random/latent regression coefficients. Using simulated data, we demonstrate that our approach could be quite effective in finding relevant genes compared with several alternative methods. We apply our model to two large-scale studies. The first study involves transcriptome analysis of infection by human cytomegalovirus. The second study's objective is to identify differentially expressed genes between two types of leukemia. Copyright © 2012 John Wiley & Sons, Ltd.

Prediction of Genes Related to Positive Selection Using Whole-Genome Resequencing in Three Commercial Pig Breeds

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HyoYoung Kim

2015-12-01

Full Text Available Selective sweep can cause genetic differentiation across populations, which allows for the identification of possible causative regions/genes underlying important traits. The pig has experienced a long history of allele frequency changes through artificial selection in the domestication process. We obtained an average of 329,482,871 sequence reads for 24 pigs from three pig breeds: Yorkshire (n = 5, Landrace (n = 13, and Duroc (n = 6. An average read depth of 11.7 was obtained using whole-genome resequencing on an Illumina HiSeq2000 platform. In this study, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio tests were implemented to detect genes experiencing positive selection for the genome-wide resequencing data generated from three commercial pig breeds. In our results, 26, 7, and 14 genes from Yorkshire, Landrace, and Duroc, respectively were detected by two kinds of statistical tests. Significant evidence for positive selection was identified on genes ST6GALNAC2 and EPHX1 in Yorkshire, PARK2 in Landrace, and BMP6, SLA-DQA1, and PRKG1 in Duroc.These genes are reportedly relevant to lactation, reproduction, meat quality, and growth traits. To understand how these single nucleotide polymorphisms (SNPs related positive selection affect protein function, we analyzed the effect of non-synonymous SNPs. Three SNPs (rs324509622, rs80931851, and rs80937718 in the SLA-DQA1 gene were significant in the enrichment tests, indicating strong evidence for positive selection in Duroc. Our analyses identified genes under positive selection for lactation, reproduction, and meat-quality and growth traits in Yorkshire, Landrace, and Duroc, respectively.

Drug and cell type-specific regulation of genes with different classes of estrogen receptor beta-selective agonists.

Directory of Open Access Journals (Sweden)

Sreenivasan Paruthiyil

2009-07-01

Full Text Available Estrogens produce biological effects by interacting with two estrogen receptors, ERalpha and ERbeta. Drugs that selectively target ERalpha or ERbeta might be safer for conditions that have been traditionally treated with non-selective estrogens. Several synthetic and natural ERbeta-selective compounds have been identified. One class of ERbeta-selective agonists is represented by ERB-041 (WAY-202041 which binds to ERbeta much greater than ERalpha. A second class of ERbeta-selective agonists derived from plants include MF101, nyasol and liquiritigenin that bind similarly to both ERs, but only activate transcription with ERbeta. Diarylpropionitrile represents a third class of ERbeta-selective compounds because its selectivity is due to a combination of greater binding to ERbeta and transcriptional activity. However, it is unclear if these three classes of ERbeta-selective compounds produce similar biological activities. The goals of these studies were to determine the relative ERbeta selectivity and pattern of gene expression of these three classes of ERbeta-selective compounds compared to estradiol (E(2, which is a non-selective ER agonist. U2OS cells stably transfected with ERalpha or ERbeta were treated with E(2 or the ERbeta-selective compounds for 6 h. Microarray data demonstrated that ERB-041, MF101 and liquiritigenin were the most ERbeta-selective agonists compared to estradiol, followed by nyasol and then diarylpropionitrile. FRET analysis showed that all compounds induced a similar conformation of ERbeta, which is consistent with the finding that most genes regulated by the ERbeta-selective compounds were similar to each other and E(2. However, there were some classes of genes differentially regulated by the ERbeta agonists and E(2. Two ERbeta-selective compounds, MF101 and liquiritigenin had cell type-specific effects as they regulated different genes in HeLa, Caco-2 and Ishikawa cell lines expressing ERbeta. Our gene profiling studies

Gene selection for the reconstruction of stem cell differentiation trees: a linear programming approach.

Science.gov (United States)

Ghadie, Mohamed A; Japkowicz, Nathalie; Perkins, Theodore J

2015-08-15

Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. tperkins@ohri.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An efficient parallel stochastic simulation method for analysis of nonviral gene delivery systems

KAUST Repository

Kuwahara, Hiroyuki

2011-01-01

Gene therapy has a great potential to become an effective treatment for a wide variety of diseases. One of the main challenges to make gene therapy practical in clinical settings is the development of efficient and safe mechanisms to deliver foreign DNA molecules into the nucleus of target cells. Several computational and experimental studies have shown that the design process of synthetic gene transfer vectors can be greatly enhanced by computational modeling and simulation. This paper proposes a novel, effective parallelization of the stochastic simulation algorithm (SSA) for pharmacokinetic models that characterize the rate-limiting, multi-step processes of intracellular gene delivery. While efficient parallelizations of the SSA are still an open problem in a general setting, the proposed parallel simulation method is able to substantially accelerate the next reaction selection scheme and the reaction update scheme in the SSA by exploiting and decomposing the structures of stochastic gene delivery models. This, thus, makes computationally intensive analysis such as parameter optimizations and gene dosage control for specific cell types, gene vectors, and transgene expression stability substantially more practical than that could otherwise be with the standard SSA. Here, we translated the nonviral gene delivery model based on mass-action kinetics by Varga et al. [Molecular Therapy, 4(5), 2001] into a more realistic model that captures intracellular fluctuations based on stochastic chemical kinetics, and as a case study we applied our parallel simulation to this stochastic model. Our results show that our simulation method is able to increase the efficiency of statistical analysis by at least 50% in various settings. © 2011 ACM.

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

2012-05-01

The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy; Bachkirova, Elena; Rey, Michael

2013-10-01

The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

Selection of Reference Genes for Expression Studies in Diaphorina citri (Hemiptera: Liviidae).

Science.gov (United States)

Bassan, Meire Menezes; Angelotti-Mendonc A, Je Ssika; Alves, Gustavo Rodrigues; Yamamoto, Pedro Takao; Moura O Filho, Francisco de Assis Alves

2017-12-05

The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae), is considered the main vector of the bacteria associated with huanglongbing, a very serious disease that has threatened the world citrus industry. The absence of efficient control management protocols, including a lack of resistant cultivars, has led to the development of different approaches to study this pathosystem. The production of resistant genotypes relies on D. citri gene expression analyses by RT-qPCR to assess control of the vector population. High-quality, reliable RT-qPCR analyses depend upon proper reference gene selection and validation. However, adequate D. citri reference genes have not yet been identified. In the present study, we evaluated the genes EF 1-α, ACT, GAPDH, RPL7, RPL17, and TUB as candidate reference genes for this insect. Gene expression stability was evaluated using the mathematical algorithms deltaCt, NormFinder, BestKeeper, and geNorm, at five insect developmental stages, grown on two different plant hosts [Citrus sinensis (L.) Osbeck (Sapindales: Rutaceae) and Murraya paniculata (L.) Jack (Sapindales: Rutaceae)]. The final gene ranking was calculated using RefFinder software, and the V-ATPase-A gene was selected for validation. According to our results, two reference genes are recommended when different plant hosts and developmental stages are considered. Considering gene expression studies in D. citri grown on M. paniculata, regardless of the insect developmental stage, GAPDH and RPL7 have the best fit as reference genes in RT-qPCR analyses, whereas GAPDH and EF 1-α are recommended as reference genes in insect studies using C. sinensis. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effective selection of transgenic papaya plants with the PMI/Man selection system.

Science.gov (United States)

Zhu, Yun J; Agbayani, Ricelle; McCafferty, Heather; Albert, Henrik H; Moore, Paul H

2005-09-01

The selectable marker gene phospho-mannose isomerase (pmi), which encodes the enzyme phospho-mannose isomerase (PMI) to enable selection of transformed cell lines on media containing mannose (Man), was evaluated for genetic transformation of papaya (Carica papaya L.). We found that papaya embryogenic calli have little or no PMI activity and cannot utilize Man as a carbon source; however, when calli were transformed with a pmi gene, the PMI activity was greatly increased and they could utilize Man as efficiently as sucrose. Plants regenerated from selected callus lines also exhibited PMI activity but at a lower specific activity level. Our transformation efficiency with Man selection was higher than that reported using antibiotic selection or with a visual marker. For papaya, the PMI/Man selection system for producing transgenic plants is a highly efficient addition to previously published methods for selection and may facilitate the stacking of multiple transgenes of interest. Additionally, since the PMI/Man selection system does not involve antibiotic or herbicide resistance genes, its use might reduce environmental concerns about the potential flow of those genes into related plant populations.

A Screening Method for the ALK Fusion Gene in NSCLC

International Nuclear Information System (INIS)

Murakami, Yoshiko; Mitsudomi, Tetsuya; Yatabe, Yasushi

2012-01-01

Lung cancer research has recently made significant progress in understanding the molecular pathogenesis of lung cancer and in developing treatments for it. Such achievements are directly utilized in clinical practice. Indeed, the echinoderm microtubule-associated protein-like 4–anaplastic lymphoma kinase (ALK) fusion gene was first described in non-small cell lung cancer in 2007, and a molecularly targeted drug against the fusion was approved in 2011. However, lung cancer with the ALK fusion constitutes only a small fraction of lung cancers; therefore, efficient patient selection is crucial for successful treatment using the ALK inhibitor. Currently, RT-PCR, fluorescent in situ hybridization (FISH), and immunohistochemistry are commonly used to detect the ALK fusion. Although FISH is currently the gold standard technique, there are no perfect methods for detecting these genetic alterations. In this article, we discuss the advantages and disadvantages of each method and the possible criteria for selecting patients who are more likely to have the ALK fusion. If we can successfully screen patients, then ALK inhibitor treatment will be the best example of personalized therapy in terms of selecting patients with an uncommon genotype from a larger group with the same tumor phenotype. In other words, the personalized therapy may offer a new challenge for current clinical oncology.

Preclinical evaluation of gene delivery methods for the treatment of loco-regional disease in breast cancer.

LENUS (Irish Health Repository)

Rajendran, Simon

2011-04-01

Preclinical results with various gene therapy strategies indicate significant potential for new cancer treatments. However, many therapeutics fail at clinical trial, often due to differences in tissue physiology between animal models and humans, and tumor phenotype variation. Clinical data relevant to treatment strategies may be generated prior to clinical trial through experimentation using intact patient tissue ex vivo. We developed a novel tumor slice model culture system that is universally applicable to gene delivery methods, using a realtime luminescence detection method to assess gene delivery. Methods investigated include viruses (adenovirus [Ad] and adeno-associated virus), lipofection, ultrasound (US), electroporation and naked DNA. Viability and tumor populations within the slices were well maintained for seven days, and gene delivery was qualitatively and quantitatively examinable for all vectors. Ad was the most efficient gene delivery vector with transduction efficiency >50%. US proved the optimal non-viral gene delivery method in human tumor slices. The nature of the ex vivo culture system permitted examination of specific elements. Parameters shown to diminish Ad gene delivery included blood, regions of low viability and secondary disease. US gene delivery was significantly reduced by blood and skin, while tissue hyperthermia improved gene delivery. US achieved improved efficacy for secondary disease. The ex vivo model was also suitable for examination of tissue-specific effects on vector expression, with Ad expression mediated by the CXCR4 promoter shown to provide a tumor selective advantage over the ubiquitously active cytomegalovirus promoter. In conclusion, this is the first study incorporating patient tissue models in comparing gene delivery from various vectors, providing knowledge on cell-type specificity and examining the crucial biological factors determining successful gene delivery. The results highlight the importance of in

Preclinical evaluation of gene delivery methods for the treatment of loco-regional disease in breast cancer.

LENUS (Irish Health Repository)

Rajendran, Simon

2012-01-31

Preclinical results with various gene therapy strategies indicate significant potential for new cancer treatments. However, many therapeutics fail at clinical trial, often due to differences in tissue physiology between animal models and humans, and tumor phenotype variation. Clinical data relevant to treatment strategies may be generated prior to clinical trial through experimentation using intact patient tissue ex vivo. We developed a novel tumor slice model culture system that is universally applicable to gene delivery methods, using a realtime luminescence detection method to assess gene delivery. Methods investigated include viruses (adenovirus [Ad] and adeno-associated virus), lipofection, ultrasound (US), electroporation and naked DNA. Viability and tumor populations within the slices were well maintained for seven days, and gene delivery was qualitatively and quantitatively examinable for all vectors. Ad was the most efficient gene delivery vector with transduction efficiency >50%. US proved the optimal non-viral gene delivery method in human tumor slices. The nature of the ex vivo culture system permitted examination of specific elements. Parameters shown to diminish Ad gene delivery included blood, regions of low viability and secondary disease. US gene delivery was significantly reduced by blood and skin, while tissue hyperthermia improved gene delivery. US achieved improved efficacy for secondary disease. The ex vivo model was also suitable for examination of tissue-specific effects on vector expression, with Ad expression mediated by the CXCR4 promoter shown to provide a tumor selective advantage over the ubiquitously active cytomegalovirus promoter. In conclusion, this is the first study incorporating patient tissue models in comparing gene delivery from various vectors, providing knowledge on cell-type specificity and examining the crucial biological factors determining successful gene delivery. The results highlight the importance of in

A Bayesian variable selection procedure for ranking overlapping gene sets

DEFF Research Database (Denmark)

Skarman, Axel; Mahdi Shariati, Mohammad; Janss, Luc

2012-01-01

Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been de...

Use of the alr gene as a food-grade selection marker in lactic acid bacteria.

Science.gov (United States)

Bron, Peter A; Benchimol, Marcos G; Lambert, Jolanda; Palumbo, Emmanuelle; Deghorain, Marie; Delcour, Jean; De Vos, Willem M; Kleerebezem, Michiel; Hols, Pascal

2002-11-01

Both Lactococcus lactis and Lactobacillus plantarum contain a single alr gene, encoding an alanine racemase (EC 5.1.1.1), which catalyzes the interconversion of D-alanine and L-alanine. The alr genes of these lactic acid bacteria were investigated for their application as food-grade selection markers in a heterologous complementation approach. Since isogenic mutants of both species carrying an alr deletion (Deltaalr) showed auxotrophy for D-alanine, plasmids carrying a heterologous alr were constructed and could be selected, since they complemented D-alanine auxotrophy in the L. plantarum Deltaalr and L. lactis Deltaalr strains. Selection was found to be highly stringent, and plasmids were stably maintained over 200 generations of culturing. Moreover, the plasmids carrying the heterologous alr genes could be stably maintained in wild-type strains of L. plantarum and L. lactis by selection for resistance to D-cycloserine, a competitive inhibitor of Alr (600 and 200 micro g/ml, respectively). In addition, a plasmid carrying the L. plantarum alr gene under control of the regulated nisA promoter was constructed to demonstrate that D-cycloserine resistance of L. lactis is linearly correlated to the alr expression level. Finally, the L. lactis alr gene controlled by the nisA promoter, together with the nisin-regulatory genes nisRK, were integrated into the chromosome of L. plantarum Deltaalr. The resulting strain could grow in the absence of D-alanine only when expression of the alr gene was induced with nisin.

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

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Alok Arun

Full Text Available Real-time quantitative reverse transcription PCR (qRT-PCR is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae, two developmental stages (pupal and adult and two sexes (male and female, all of which were subjected to two food treatments (food stress and control feeding ad libitum. The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

Science.gov (United States)

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression

Selection shaped the evolution of mouse androgen-binding protein (ABP) function and promoted the duplication of Abp genes.

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Karn, Robert C; Laukaitis, Christina M

2014-08-01

In the present article, we summarize two aspects of our work on mouse ABP (androgen-binding protein): (i) the sexual selection function producing incipient reinforcement on the European house mouse hybrid zone, and (ii) the mechanism behind the dramatic expansion of the Abp gene region in the mouse genome. Selection unifies these two components, although the ways in which selection has acted differ. At the functional level, strong positive selection has acted on key sites on the surface of one face of the ABP dimer, possibly to influence binding to a receptor. A different kind of selection has apparently driven the recent and rapid expansion of the gene region, probably by increasing the amount of Abp transcript, in one or both of two ways. We have shown previously that groups of Abp genes behave as LCRs (low-copy repeats), duplicating as relatively large blocks of genes by NAHR (non-allelic homologous recombination). The second type of selection involves the close link between the accumulation of L1 elements and the expansion of the Abp gene family by NAHR. It is probably predicated on an initial selection for increased transcription of existing Abp genes and/or an increase in Abp gene number providing more transcriptional sites. Either or both could increase initial transcript production, a quantitative change similar to increasing the volume of a radio transmission. In closing, we also provide a note on Abp gene nomenclature.

Positive selection and ancient duplications in the evolution of class B floral homeotic genes of orchids and grasses

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Koch Marcus A

2009-04-01

Full Text Available Abstract Background Positive selection is recognized as the prevalence of nonsynonymous over synonymous substitutions in a gene. Models of the functional evolution of duplicated genes consider neofunctionalization as key to the retention of paralogues. For instance, duplicate transcription factors are specifically retained in plant and animal genomes and both positive selection and transcriptional divergence appear to have played a role in their diversification. However, the relative impact of these two factors has not been systematically evaluated. Class B MADS-box genes, comprising DEF-like and GLO-like genes, encode developmental transcription factors essential for establishment of perianth and male organ identity in the flowers of angiosperms. Here, we contrast the role of positive selection and the known divergence in expression patterns of genes encoding class B-like MADS-box transcription factors from monocots, with emphasis on the family Orchidaceae and the order Poales. Although in the monocots these two groups are highly diverse and have a strongly canalized floral morphology, there is no information on the role of positive selection in the evolution of their distinctive flower morphologies. Published research shows that in Poales, class B-like genes are expressed in stamens and in lodicules, the perianth organs whose identity might also be specified by class B-like genes, like the identity of the inner tepals of their lily-like relatives. In orchids, however, the number and pattern of expression of class B-like genes have greatly diverged. Results The DEF-like genes from Orchidaceae form four well-supported, ancient clades of orthologues. In contrast, orchid GLO-like genes form a single clade of ancient orthologues and recent paralogues. DEF-like genes from orchid clade 2 (OMADS3-like genes are under less stringent purifying selection than the other orchid DEF-like and GLO-like genes. In comparison with orchids, purifying selection

The relationship between PMI (manA) gene expression and optimal selection pressure in Indica rice transformation.

Science.gov (United States)

Gui, Huaping; Li, Xia; Liu, Yubo; Han, Kai; Li, Xianggan

2014-07-01

An efficient mannose selection system was established for transformation of Indica cultivar IR58025B . Different selection pressures were required to achieve optimum transformation frequency for different PMI selectable marker cassettes. This study was conducted to establish an efficient transformation system for Indica rice, cultivar IR58025B. Four combinations of two promoters, rice Actin 1 and maize Ubiquitin 1, and two manA genes, native gene from E. coli (PMI-01) and synthetic maize codon-optimized gene (PMI-09) were compared under various concentrations of mannose. Different selection pressures were required for different gene cassettes to achieve corresponding optimum transformation frequency (TF). Higher TFs as 54 and 53% were obtained when 5 g/L mannose was used for selection of prActin-PMI-01 cassette and 7.5 g/L mannose used for selection of prActin-PMI-09, respectively. TFs as 67 and 56% were obtained when 7.5 and 15 g/L mannose were used for selection of prUbi-PMI-01 and prUbi-PMI-09, respectively. We conclude that higher TFs can be achieved for different gene cassettes when an optimum selection pressure is applied. By investigating the PMI expression level in transgenic calli and leaves, we found there was a significant positive correlation between the protein expression level and the optimal selection pressure. Higher optimal selection pressure is required for those constructs which confer higher expression of PMI protein. The single copy rate of those transgenic events for prActin-PMI-01 cassette is lower than that for other three cassettes. We speculate some of low copy events with low protein expression levels might not have been able to survive in the mannose selection.

Selection of relatively exact reference genes for gene expression studies in goosegrass (Eleusine indica) under herbicide stress.

Science.gov (United States)

Chen, Jingchao; Huang, Zhaofeng; Huang, Hongjuan; Wei, Shouhui; Liu, Yan; Jiang, Cuilan; Zhang, Jie; Zhang, Chaoxian

2017-04-21

Goosegrass (Eleusine indica) is one of the most serious annual grassy weeds worldwide, and its evolved herbicide-resistant populations are more difficult to control. Quantitative real-time PCR (qPCR) is a common technique for investigating the resistance mechanism; however, there is as yet no report on the systematic selection of stable reference genes for goosegrass. This study proposed to test the expression stability of 9 candidate reference genes in goosegrass in different tissues and developmental stages and under stress from three types of herbicide. The results show that for different developmental stages and organs (control), eukaryotic initiation factor 4 A (eIF-4) is the most stable reference gene. Chloroplast acetolactate synthase (ALS) is the most stable reference gene under glyphosate stress. Under glufosinate stress, eIF-4 is the best reference gene. Ubiquitin-conjugating enzyme (UCE) is the most stable reference gene under quizalofop-p-ethyl stress. The gene eIF-4 is the recommended reference gene for goosegrass under the stress of all three herbicides. Moreover, pairwise analysis showed that seven reference genes were sufficient to normalize the gene expression data under three herbicides treatment. This study provides a list of reliable reference genes for transcript normalization in goosegrass, which will facilitate resistance mechanism studies in this weed species.

Selection of reliable reference genes for quantitative real-time PCR in human T cells and neutrophils

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Ledderose Carola

2011-10-01

Full Text Available Abstract Background The choice of reliable reference genes is a prerequisite for valid results when analyzing gene expression with real-time quantitative PCR (qPCR. This method is frequently applied to study gene expression patterns in immune cells, yet a thorough validation of potential reference genes is still lacking for most leukocyte subtypes and most models of their in vitro stimulation. In the current study, we evaluated the expression stability of common reference genes in two widely used cell culture models-anti-CD3/CD28 activated T cells and lipopolysaccharide stimulated neutrophils-as well as in unselected untreated leukocytes. Results The mRNA expression of 17 (T cells, 7 (neutrophils or 8 (unselected leukocytes potential reference genes was quantified by reverse transcription qPCR, and a ranking of the preselected candidate genes according to their expression stability was calculated using the programs NormFinder, geNorm and BestKeeper. IPO8, RPL13A, TBP and SDHA were identified as suitable reference genes in T cells. TBP, ACTB and SDHA were stably expressed in neutrophils. TBP and SDHA were also the most stable genes in untreated total blood leukocytes. The critical impact of reference gene selection on the estimated target gene expression is demonstrated for IL-2 and FIH expression in T cells. Conclusions The study provides a shortlist of suitable reference genes for normalization of gene expression data in unstimulated and stimulated T cells, unstimulated and stimulated neutrophils and in unselected leukocytes.

A copula method for modeling directional dependence of genes

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Park Changyi

2008-05-01

Full Text Available Abstract Background Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation. Results We analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex by adopting a measure of directional dependence based on a copula function. We have compared

Reranking candidate gene models with cross-species comparison for improved gene prediction

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Pereira Fernando CN

2008-10-01

Full Text Available Abstract Background Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patterns, etc. Competing models with similar state-based scores may be distinguishable with additional information. In particular, functional and comparative genomics datasets may help to select among competing models of comparable probability by exploiting features likely to be associated with the correct gene models, such as conserved exon/intron structure or protein sequence features. Results We have investigated the utility of a simple post-processing step for selecting among a set of alternative gene models, using global scoring rules to rerank competing models for more accurate prediction. For each gene locus, we first generate the K best candidate gene models using the gene finder Evigan, and then rerank these models using comparisons with putative orthologous genes from closely-related species. Candidate gene models with lower scores in the original gene finder may be selected if they exhibit strong similarity to probable orthologs in coding sequence, splice site location, or signal peptide occurrence. Experiments on Drosophila melanogaster demonstrate that reranking based on cross-species comparison outperforms the best gene models identified by Evigan alone, and also outperforms the comparative gene finders GeneWise and Augustus+. Conclusion Reranking gene models with cross-species comparison improves gene prediction accuracy. This straightforward method can be readily adapted to incorporate additional lines of evidence, as it requires only a ranked source of candidate gene models.

Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR

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Longjian Niu

2015-06-01

Full Text Available Real-time quantitative PCR (RT-qPCR is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis, a promising oilseed crop known for its polyunsaturated fatty acid (PUFA-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt, BestKeeper, geNorm, and NormFinder were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE, actin (ACT and phospholipase A22 (PLA were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13, cyclophilin (CYC and elongation factor-1alpha (EF1α were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi.

Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR

Science.gov (United States)

Niu, Longjian; Tao, Yan-Bin; Chen, Mao-Sheng; Fu, Qiantang; Li, Chaoqiong; Dong, Yuling; Wang, Xiulan; He, Huiying; Xu, Zeng-Fu

2015-01-01

Real-time quantitative PCR (RT-qPCR) is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis), a promising oilseed crop known for its polyunsaturated fatty acid (PUFA)-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt), BestKeeper, geNorm, and NormFinder) were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE), actin (ACT) and phospholipase A22 (PLA) were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13), cyclophilin (CYC) and elongation factor-1alpha (EF1α) were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII) were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi. PMID:26047338

Improvement Method of Gene Transfer in Kappaphycus Alvarezii

OpenAIRE

Triana, St. Hidayah; Alimuddin,; Widyastuti, Utut; Suharsono,; Suryati, Emma; Parenrengi, Andi

2016-01-01

Method of foreign gene transfer in red seaweed Kappaphycus alvarezii has been reported, however, li-mited number of transgenic F0 (broodstock) was obtained. This study was conducted to improve the method of gene transfer mediated by Agrobacterium tumefaciens in order to obtain high percentage of K. alvarezii transgenic. Superoxide dismutase gene from Melastoma malabatrichum (MmCu/Zn-SOD) was used as model towards increasing adaptability of K. alvarezii to environmental stress. The treat-ment...

Genealogy-based methods for inference of historical recombination and gene flow and their application in Saccharomyces cerevisiae.

Science.gov (United States)

Jenkins, Paul A; Song, Yun S; Brem, Rachel B

2012-01-01

Genetic exchange between isolated populations, or introgression between species, serves as a key source of novel genetic material on which natural selection can act. While detecting historical gene flow from DNA sequence data is of much interest, many existing methods can be limited by requirements for deep population genomic sampling. In this paper, we develop a scalable genealogy-based method to detect candidate signatures of gene flow into a given population when the source of the alleles is unknown. Our method does not require sequenced samples from the source population, provided that the alleles have not reached fixation in the sampled recipient population. The method utilizes recent advances in algorithms for the efficient reconstruction of ancestral recombination graphs, which encode genealogical histories of DNA sequence data at each site, and is capable of detecting the signatures of gene flow whose footprints are of length up to single genes. Further, we employ a theoretical framework based on coalescent theory to test for statistical significance of certain recombination patterns consistent with gene flow from divergent sources. Implementing these methods for application to whole-genome sequences of environmental yeast isolates, we illustrate the power of our approach to highlight loci with unusual recombination histories. By developing innovative theory and methods to analyze signatures of gene flow from population sequence data, our work establishes a foundation for the continued study of introgression and its evolutionary relevance.

Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions.

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Evans, Ciaran; Hardin, Johanna; Stoebel, Daniel M

2017-02-27

RNA-Seq is a widely used method for studying the behavior of genes under different biological conditions. An essential step in an RNA-Seq study is normalization, in which raw data are adjusted to account for factors that prevent direct comparison of expression measures. Errors in normalization can have a significant impact on downstream analysis, such as inflated false positives in differential expression analysis. An underemphasized feature of normalization is the assumptions on which the methods rely and how the validity of these assumptions can have a substantial impact on the performance of the methods. In this article, we explain how assumptions provide the link between raw RNA-Seq read counts and meaningful measures of gene expression. We examine normalization methods from the perspective of their assumptions, as an understanding of methodological assumptions is necessary for choosing methods appropriate for the data at hand. Furthermore, we discuss why normalization methods perform poorly when their assumptions are violated and how this causes problems in subsequent analysis. To analyze a biological experiment, researchers must select a normalization method with assumptions that are met and that produces a meaningful measure of expression for the given experiment. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparative study on gene set and pathway topology-based enrichment methods.

Science.gov (United States)

Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim

2015-10-22

Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both

A new electrospray method for targeted gene delivery.

Science.gov (United States)

Boehringer, Stephan; Ruzgys, Paulius; Tamò, Luca; Šatkauskas, Saulius; Geiser, Thomas; Gazdhar, Amiq; Hradetzky, David

2018-03-05

A challenge for gene therapy is absence of safe and efficient local delivery of therapeutic genetic material. An efficient and reproducible physical method of electrospray for localized and targeted gene delivery is presented. Electrospray works on the principle of coulombs repulsion, under influence of electric field the liquid carrying genetic material is dispersed into micro droplets and is accelerated towards the targeted tissue, acting as a counter electrode. The accelerated droplets penetrate the targeted cells thus facilitating the transfer of genetic material into the cell. The work described here presents the principle of electrospray for gene delivery, the basic instrument design, and the various optimized parameters to enhance gene transfer in vitro. We estimate a transfection efficiency of up to 60% was achieved. We describe an efficient gene transfer method and a potential electrospray-mediated gene transfer mechanism.

Selection of reliable reference genes in Caenorhabditis elegans for analysis of nanotoxicity.

Science.gov (United States)

Zhang, Yanqiong; Chen, Dongliang; Smith, Michael A; Zhang, Baohong; Pan, Xiaoping

2012-01-01

Despite rapid development and application of a wide range of manufactured metal oxide nanoparticles (NPs), the understanding of potential risks of using NPs is less completed, especially at the molecular level. The nematode Caenorhabditis elegans (C.elegans) has been emerging as an environmental model to study the molecular mechanism of environmental contaminations, using standard genetic tools such as the real-time quantitative PCR (RT-qPCR). The most important factor that may affect the accuracy of RT-qPCR is to choose appropriate genes for normalization. In this study, we selected 13 reference gene candidates (act-1, cdc-42, pmp-3, eif-3.C, actin, act-2, csq-1, Y45F10D.4, tba-1, mdh-1, ama-1, F35G12.2, and rbd-1) to test their expression stability under different doses of nano-copper oxide (CuO 0, 1, 10, and 50 µg/mL) using RT-qPCR. Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method, were employed to evaluate these 13 candidates expressions. As a result, tba-1, Y45F10D.4 and pmp-3 were the most reliable, which may be used as reference genes in future study of nanoparticle-induced genetic response using C.elegans.

Selection of Housekeeping Genes for Transgene Expression Analysis in Eucommia ulmoides Oliver Using Real-Time RT-PCR

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Ren Chen

2010-01-01

Full Text Available In order to select appropriate housekeeping genes for accurate calibration of experimental variations in real-time (RT- PCR results in transgene expression analysis, particularly with respect to the influence of transgene on stability of endogenous housekeeping gene expression in transgenic plants, we outline a reliable strategy to identify the optimal housekeeping genes from a set of candidates by combining statistical analyses of their (RT- PCR amplification efficiency, gene expression stability, and transgene influences. We used the strategy to select two genes, ACTα and EF1α, from 10 candidate housekeeping genes, as the optimal housekeeping genes to evaluate transgenic Eucommia ulmoides Oliver root lines overexpressing IPPI or FPPS1 genes, which are involved in isoprenoid biosynthesis.

Selection of reference genes for tissue/organ samples on day 3 fifth-instar larvae in silkworm, Bombyx mori.

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Wang, Genhong; Chen, Yanfei; Zhang, Xiaoying; Bai, Bingchuan; Yan, Hao; Qin, Daoyuan; Xia, Qingyou

2018-06-01

The silkworm, Bombyx mori, is one of the world's most economically important insect. Surveying variations in gene expression among multiple tissue/organ samples will provide clues for gene function assignments and will be helpful for identifying genes related to economic traits or specific cellular processes. To ensure their accuracy, commonly used gene expression quantification methods require a set of stable reference genes for data normalization. In this study, 24 candidate reference genes were assessed in 10 tissue/organ samples of day 3 fifth-instar B. mori larvae using geNorm and NormFinder. The results revealed that, using the combination of the expression of BGIBMGA003186 and BGIBMGA008209 was the optimum choice for normalizing the expression data of the B. mori tissue/organ samples. The most stable gene, BGIBMGA003186, is recommended if just one reference gene is used. Moreover, the commonly used reference gene encoding cytoplasmic actin was the least appropriate reference gene of the samples investigated. The reliability of the selected reference genes was further confirmed by evaluating the expression profiles of two cathepsin genes. Our results may be useful for future studies involving the quantification of relative gene expression levels of different tissue/organ samples in B. mori. © 2018 Wiley Periodicals, Inc.

The cld mutation: narrowing the critical chromosomal region and selecting candidate genes.

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Péterfy, Miklós; Mao, Hui Z; Doolittle, Mark H

2006-10-01

Combined lipase deficiency (cld) is a recessive, lethal mutation specific to the tw73 haplotype on mouse Chromosome 17. While the cld mutation results in lipase proteins that are inactive, aggregated, and retained in the endoplasmic reticulum (ER), it maps separately from the lipase structural genes. We have narrowed the gene critical region by about 50% using the tw18 haplotype for deletion mapping and a recombinant chromosome used originally to map cld with respect to the phenotypic marker tf. The region now extends from 22 to 25.6 Mbp on the wild-type chromosome, currently containing 149 genes and 50 expressed sequence tags (ESTs). To identify the affected gene, we have selected candidates based on their known role in associated biological processes, cellular components, and molecular functions that best fit with the predicted function of the cld gene. A secondary approach was based on differences in mRNA levels between mutant (cld/cld) and unaffected (+/cld) cells. Using both approaches, we have identified seven functional candidates with an ER localization and/or an involvement in protein maturation and folding that could explain the lipase deficiency, and six expression candidates that exhibit large differences in mRNA levels between mutant and unaffected cells. Significantly, two genes were found to be candidates with regard to both function and expression, thus emerging as the strongest candidates for cld. We discuss the implications of our mapping results and our selection of candidates with respect to other genes, deletions, and mutations occurring in the cld critical region.

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

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Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

2018-03-19

With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

Selection and validation of reference genes for gene expression analysis in switchgrass (Panicum virgatum using quantitative real-time RT-PCR.

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Jacinta Gimeno

Full Text Available Switchgrass (Panicum virgatum has received a lot of attention as a forage and bioenergy crop during the past few years. Gene expression studies are in progress to improve new traits and develop new cultivars. Quantitative real time PCR (qRT-PCR has emerged as an important technique to study gene expression analysis. For accurate and reliable results, normalization of data with reference genes is essential. In this work, we evaluate the stability of expression of genes to use as reference for qRT-PCR in the grass P. virgatum. Eleven candidate reference genes, including eEF-1α, UBQ6, ACT12, TUB6, eIF-4a, GAPDH, SAMDC, TUA6, CYP5, U2AF, and FTSH4, were validated for qRT-PCR normalization in different plant tissues and under different stress conditions. The expression stability of these genes was verified by the use of two distinct algorithms, geNorm and NormFinder. Differences were observed after comparison of the ranking of the candidate reference genes identified by both programs but eEF-1α, eIF-4a, CYP5 and U2AF are ranked as the most stable genes in the samples sets under study. Both programs discard the use of SAMDC and TUA6 for normalization. Validation of the reference genes proposed by geNorm and NormFinder were performed by normalization of transcript abundance of a group of target genes in different samples. Results show similar expression patterns when the best reference genes selected by both programs were used but differences were detected in the transcript abundance of the target genes. Based on the above research, we recommend the use of different statistical algorithms to identify the best reference genes for expression data normalization. The best genes selected in this study will help to improve the quality of gene expression data in a wide variety of samples in switchgrass.

Gene Ontology and KEGG Enrichment Analyses of Genes Related to Age-Related Macular Degeneration

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Jian Zhang

2014-01-01

Full Text Available Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-related macular degeneration (AMD is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes.

Nucleofection: A New Method for Cutaneous Gene Transfer?

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Frank Jacobsen

2006-01-01

Full Text Available Background. Transfection efficacy after nonviral gene transfer in primary epithelial cells is limited. The aim of this study was to compare transfection efficacy of the recently available method of nucleofection with the established transfection reagent FuGENE6. Methods. Primary human keratinocytes (HKC, primary human fibroblasts (HFB, and a human keratinocyte cell line (HaCaT were transfected with reporter gene construct by FuGENE6 or Amaxa Nucleofector device. At corresponding time points, β-galactosidase expression, cell proliferation (MTT-Test, transduction efficiency (X-gal staining, cell morphology, and cytotoxicity (CASY were determined. Results. Transgene expression after nucleofection was significantly higher in HKC and HFB and detected earlier (3 h vs. 24 h than in FuGENE6. After lipofection 80%–90% of the cells remained proliferative without any influence on cell morphology. In contrast, nucleofection led to a decrease in keratinocyte cell size, with only 20%–42% proliferative cells. Conclusion. Related to the method-dependent increase of cytotoxicity, transgene expression after nucleofection was earlier and higher than after lipofection.

Nucleofection: A New Method for Cutaneous Gene Transfer?

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Jacobsen, Frank; Mertens-Rill, Janine; Beller, Juergen; Hirsch, Tobias; Daigeler, Adrien; Langer, Stefan; Lehnhardt, Marcus; Steinau, Hans-Ulrich; Steinstraesser, Lars

2006-01-01

Background. Transfection efficacy after nonviral gene transfer in primary epithelial cells is limited. The aim of this study was to compare transfection efficacy of the recently available method of nucleofection with the established transfection reagent FuGENE6. Methods. Primary human keratinocytes (HKC), primary human fibroblasts (HFB), and a human keratinocyte cell line (HaCaT) were transfected with reporter gene construct by FuGENE6 or Amaxa Nucleofector device. At corresponding time points, β-galactosidase expression, cell proliferation (MTT-Test), transduction efficiency (X-gal staining), cell morphology, and cytotoxicity (CASY) were determined. Results. Transgene expression after nucleofection was significantly higher in HKC and HFB and detected earlier (3 h vs. 24 h) than in FuGENE6. After lipofection 80%–90% of the cells remained proliferative without any influence on cell morphology. In contrast, nucleofection led to a decrease in keratinocyte cell size, with only 20%–42% proliferative cells. Conclusion. Related to the method-dependent increase of cytotoxicity, transgene expression after nucleofection was earlier and higher than after lipofection. PMID:17489014

Selection and evaluation of potential reference genes for gene expression analysis in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae using reverse-transcription quantitative PCR.

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Miao Yuan

Full Text Available The brown planthopper (BPH, Nilaparvata lugens (Hemiptera, Delphacidae, is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR. Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT, muscle actin (MACT, ribosomal protein S11 (RPS11, ribosomal protein S15e (RPS15, alpha 2-tubulin (TUB, elongation factor 1 delta (EF, 18S ribosomal RNA (18S, and arginine kinase (AK and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for

YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

KAUST Repository

Kleftogiannis, Dimitrios A.; Theofilatos, Konstantinos; Likothanassis, Spiros; Mavroudi, Seferina

2015-01-01

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

KAUST Repository

Kleftogiannis, Dimitrios A.

2015-01-23

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

Biclustering methods: biological relevance and application in gene expression analysis.

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Ali Oghabian

Full Text Available DNA microarray technologies are used extensively to profile the expression levels of thousands of genes under various conditions, yielding extremely large data-matrices. Thus, analyzing this information and extracting biologically relevant knowledge becomes a considerable challenge. A classical approach for tackling this challenge is to use clustering (also known as one-way clustering methods where genes (or respectively samples are grouped together based on the similarity of their expression profiles across the set of all samples (or respectively genes. An alternative approach is to develop biclustering methods to identify local patterns in the data. These methods extract subgroups of genes that are co-expressed across only a subset of samples and may feature important biological or medical implications. In this study we evaluate 13 biclustering and 2 clustering (k-means and hierarchical methods. We use several approaches to compare their performance on two real gene expression data sets. For this purpose we apply four evaluation measures in our analysis: (1 we examine how well the considered (biclustering methods differentiate various sample types; (2 we evaluate how well the groups of genes discovered by the (biclustering methods are annotated with similar Gene Ontology categories; (3 we evaluate the capability of the methods to differentiate genes that are known to be specific to the particular sample types we study and (4 we compare the running time of the algorithms. In the end, we conclude that as long as the samples are well defined and annotated, the contamination of the samples is limited, and the samples are well replicated, biclustering methods such as Plaid and SAMBA are useful for discovering relevant subsets of genes and samples.

GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

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Chris Cheadle

2007-01-01

Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of gene expression simultaneously for multiple lists of genes (gene sets against entire distributions of gene expression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

Vancomycin gene selection in the microbiome of urban Rattus norvegicus from hospital environment

DEFF Research Database (Denmark)

Arn Hansen, Thomas; Joshi, Tejal; Larsen, Anders Rhod

2016-01-01

for the presence of antibiotic resistance genes. We show that despite the shared resistome within samples from the same geographic locations, samples from hospital area carry significantly abundant vancomycin resistance genes. The observed pattern is consistent with a selection for vancomycin genes in the R...

Selection on plant male function genes identifies candidates for reproductive isolation of yellow monkeyflowers.

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Jan E Aagaard

Full Text Available Understanding the genetic basis of reproductive isolation promises insight into speciation and the origins of biological diversity. While progress has been made in identifying genes underlying barriers to reproduction that function after fertilization (post-zygotic isolation, we know much less about earlier acting pre-zygotic barriers. Of particular interest are barriers involved in mating and fertilization that can evolve extremely rapidly under sexual selection, suggesting they may play a prominent role in the initial stages of reproductive isolation. A significant challenge to the field of speciation genetics is developing new approaches for identification of candidate genes underlying these barriers, particularly among non-traditional model systems. We employ powerful proteomic and genomic strategies to study the genetic basis of conspecific pollen precedence, an important component of pre-zygotic reproductive isolation among yellow monkeyflowers (Mimulus spp. resulting from male pollen competition. We use isotopic labeling in combination with shotgun proteomics to identify more than 2,000 male function (pollen tube proteins within maternal reproductive structures (styles of M. guttatus flowers where pollen competition occurs. We then sequence array-captured pollen tube exomes from a large outcrossing population of M. guttatus, and identify those genes with evidence of selective sweeps or balancing selection consistent with their role in pollen competition. We also test for evidence of positive selection on these genes more broadly across yellow monkeyflowers, because a signal of adaptive divergence is a common feature of genes causing reproductive isolation. Together the molecular evolution studies identify 159 pollen tube proteins that are candidate genes for conspecific pollen precedence. Our work demonstrates how powerful proteomic and genomic tools can be readily adapted to non-traditional model systems, allowing for genome-wide screens

A synbio approach for selection of highly expressed gene variants in Gram-positive bacteria

DEFF Research Database (Denmark)

Ferro, Roberto; Rennig, Maja; Hernández Rollán, Cristina

2018-01-01

with a long history in food fermentation. We have developed a synbio approach for increasing gene expression in two Gram-positive bacteria. First of all, the gene of interest was coupled to an antibiotic resistance gene to create a growth-based selection system. We then randomised the translation initiation...... region (TIR) preceding the gene of interest and selected clones that produced high protein titres, as judged by their ability to survive on high concentrations of antibiotic. Using this approach, we were able to significantly increase production of two industrially relevant proteins; sialidase in B....... subtilis and tyrosine ammonia lyase in L. lactis. Gram-positive bacteria are widely used to produce industrial enzymes. High titres are necessary to make the production economically feasible. The synbio approach presented here is a simple and inexpensive way to increase protein titres, which can be carried...

Systematic differences in the response of genetic variation to pedigree and genome-based selection methods.

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Heidaritabar, M; Vereijken, A; Muir, W M; Meuwissen, T; Cheng, H; Megens, H-J; Groenen, M A M; Bastiaansen, J W M

2014-12-01

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167-0.198) and BLUP (0.105-0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.

Natural selection in avian protein-coding genes expressed in brain.

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Axelsson, Erik; Hultin-Rosenberg, Lina; Brandström, Mikael; Zwahlén, Martin; Clayton, David F; Ellegren, Hans

2008-06-01

The evolution of birds from theropod dinosaurs took place approximately 150 million years ago, and was associated with a number of specific adaptations that are still evident among extant birds, including feathers, song and extravagant secondary sexual characteristics. Knowledge about the molecular evolutionary background to such adaptations is lacking. Here, we analyse the evolution of > 5000 protein-coding gene sequences expressed in zebra finch brain by comparison to orthologous sequences in chicken. Mean d(N)/d(S) is 0.085 and genes with their maximal expression in the eye and central nervous system have the lowest mean d(N)/d(S) value, while those expressed in digestive and reproductive tissues exhibit the highest. We find that fast-evolving genes (those which have higher than expected rate of nonsynonymous substitution, indicative of adaptive evolution) are enriched for biological functions such as fertilization, muscle contraction, defence response, response to stress, wounding and endogenous stimulus, and cell death. After alignment to mammalian orthologues, we identify a catalogue of 228 genes that show a significantly higher rate of protein evolution in the two bird lineages than in mammals. These accelerated bird genes, representing candidates for avian-specific adaptations, include genes implicated in vocal learning and other cognitive processes. Moreover, colouration genes evolve faster in birds than in mammals, which may have been driven by sexual selection for extravagant plumage characteristics.

[Construction of plant expression vectors with PMI gene as selection marker and their utilization in transformation of Salvia miltiorrhiza f. alba].

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Tao, Ru; Zhang, You-Can; Fang, Qian; Shi, Ren-Jiu; Li, Yan-Ling; Huang, Lu-Qi; Hao, Gang-Ping

2014-04-01

To construct plant expression pCAMBIA1301-PMI by substituting PMI for hygromycin resistance gene in pCAMBIA1301 and obtain transgenic Salvia miltiorrhiza f. alba using PMI-mannose selection system. The 6-phosphomannose isomerase gene (PMI) of Escherichia coli was amplified by PCR. Sequence analysis showed that it shared 100% amino acids identities with the sequences of PMI genes isolates reported in the NCBI. Based on pCAMBIA1305, the plant expression pCAMBIA1305-PMI was constructed successfully by substituting PMI for hygromycin resistance gene in pCAMBIA1305. pCAMBIA1305-PMI was transformed into Agrobacterium tumefaciens LBA4404, and then the leaves of S. miltiorrhiza f. alba were inoculated in LBA4404 with pCAMBIA1305-PMI. Plant expression pCAMBIA1301-PMI was successfully constructed and the leaves of S. miltiorrhiza f. alba inoculated in LBA4404 with pCAMBIA1305-PMI were selected on medium supplemented with a combination of 20 g x L(-1) mannose and 10 g x L(-1) sucrose as a carbon source. The transformation efficiency rate was 23.7%. Genetic transformation was confirmed by PCR, indicating that a new method for obtaining transgenic S. miltiorrhiza f. alba plants was developed using PMI-mannose selection system.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

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Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E.; Re, Matteo

2014-01-01

Objective In the context of “network medicine”, gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. Materials and methods We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. Results The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different “informativeness” embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Conclusions Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further

A simple method for analyzing exome sequencing data shows distinct levels of nonsynonymous variation for human immune and nervous system genes.

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Jan Freudenberg

Full Text Available To measure the strength of natural selection that acts upon single nucleotide variants (SNVs in a set of human genes, we calculate the ratio between nonsynonymous SNVs (nsSNVs per nonsynonymous site and synonymous SNVs (sSNVs per synonymous site. We transform this ratio with a respective factor f that corrects for the bias of synonymous sites towards transitions in the genetic code and different mutation rates for transitions and transversions. This method approximates the relative density of nsSNVs (rdnsv in comparison with the neutral expectation as inferred from the density of sSNVs. Using SNVs from a diploid genome and 200 exomes, we apply our method to immune system genes (ISGs, nervous system genes (NSGs, randomly sampled genes (RSGs, and gene ontology annotated genes. The estimate of rdnsv in an individual exome is around 20% for NSGs and 30-40% for ISGs and RSGs. This smaller rdnsv of NSGs indicates overall stronger purifying selection. To quantify the relative shift of nsSNVs towards rare variants, we next fit a linear regression model to the estimates of rdnsv over different SNV allele frequency bins. The obtained regression models show a negative slope for NSGs, ISGs and RSGs, supporting an influence of purifying selection on the frequency spectrum of segregating nsSNVs. The y-intercept of the model predicts rdnsv for an allele frequency close to 0. This parameter can be interpreted as the proportion of nonsynonymous sites where mutations are tolerated to segregate with an allele frequency notably greater than 0 in the population, given the performed normalization of the observed nsSNV to sSNV ratio. A smaller y-intercept is displayed by NSGs, indicating more nonsynonymous sites under strong negative selection. This predicts more monogenically inherited or de-novo mutation diseases that affect the nervous system.

Detecting loci under recent positive selection in dairy and beef cattle by combining different genome-wide scan methods.

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Yuri Tani Utsunomiya

Full Text Available As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP data generated from dairy and beef cattle (taurine and indicine. The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10(-7 population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3 in Brown Swiss (P = 3.82×10(-12, and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.

EEG feature selection method based on decision tree.

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Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Selection of reliable reference genes in Caenorhabditis elegans for analysis of nanotoxicity.

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Yanqiong Zhang

Full Text Available Despite rapid development and application of a wide range of manufactured metal oxide nanoparticles (NPs, the understanding of potential risks of using NPs is less completed, especially at the molecular level. The nematode Caenorhabditis elegans (C.elegans has been emerging as an environmental model to study the molecular mechanism of environmental contaminations, using standard genetic tools such as the real-time quantitative PCR (RT-qPCR. The most important factor that may affect the accuracy of RT-qPCR is to choose appropriate genes for normalization. In this study, we selected 13 reference gene candidates (act-1, cdc-42, pmp-3, eif-3.C, actin, act-2, csq-1, Y45F10D.4, tba-1, mdh-1, ama-1, F35G12.2, and rbd-1 to test their expression stability under different doses of nano-copper oxide (CuO 0, 1, 10, and 50 µg/mL using RT-qPCR. Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method, were employed to evaluate these 13 candidates expressions. As a result, tba-1, Y45F10D.4 and pmp-3 were the most reliable, which may be used as reference genes in future study of nanoparticle-induced genetic response using C.elegans.

PSP: rapid identification of orthologous coding genes under positive selection across multiple closely related prokaryotic genomes.

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Su, Fei; Ou, Hong-Yu; Tao, Fei; Tang, Hongzhi; Xu, Ping

2013-12-27

With genomic sequences of many closely related bacterial strains made available by deep sequencing, it is now possible to investigate trends in prokaryotic microevolution. Positive selection is a sub-process of microevolution, in which a particular mutation is favored, causing the allele frequency to continuously shift in one direction. Wide scanning of prokaryotic genomes has shown that positive selection at the molecular level is much more frequent than expected. Genes with significant positive selection may play key roles in bacterial adaption to different environmental pressures. However, selection pressure analyses are computationally intensive and awkward to configure. Here we describe an open access web server, which is designated as PSP (Positive Selection analysis for Prokaryotic genomes) for performing evolutionary analysis on orthologous coding genes, specially designed for rapid comparison of dozens of closely related prokaryotic genomes. Remarkably, PSP facilitates functional exploration at the multiple levels by assignments and enrichments of KO, GO or COG terms. To illustrate this user-friendly tool, we analyzed Escherichia coli and Bacillus cereus genomes and found that several genes, which play key roles in human infection and antibiotic resistance, show significant evidence of positive selection. PSP is freely available to all users without any login requirement at: http://db-mml.sjtu.edu.cn/PSP/. PSP ultimately allows researchers to do genome-scale analysis for evolutionary selection across multiple prokaryotic genomes rapidly and easily, and identify the genes undergoing positive selection, which may play key roles in the interactions of host-pathogen and/or environmental adaptation.

Selection signature in domesticated animals.

Science.gov (United States)

Pan, Zhang-yuan; He, Xiao-yun; Wang, Xiang-yu; Guo, Xiao-fei; Cao, Xiao-han; Hu, Wen-ping; Di, Ran; Liu, Qiu-yue; Chu, Ming-xing

2016-12-20

Domesticated animals play an important role in the life of humanity. All these domesticated animals undergo same process, first domesticated from wild animals, then after long time natural and artificial selection, formed various breeds that adapted to the local environment and human needs. In this process, domestication, natural and artificial selection will leave the selection signal in the genome. The research on these selection signals can find functional genes directly, is one of the most important strategies in screening functional genes. The current studies of selection signal have been performed in pigs, chickens, cattle, sheep, goats, dogs and other domestic animals, and found a great deal of functional genes. This paper provided an overview of the types and the detected methods of selection signal, and outlined researches of selection signal in domestic animals, and discussed the key issues in selection signal analysis and its prospects.

A Robust and Versatile Method of Combinatorial Chemical Synthesis of Gene Libraries via Hierarchical Assembly of Partially Randomized Modules

Science.gov (United States)

Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried

2015-01-01

A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis. PMID:26355961

Shifts in Selective Pressures on Snake Phototransduction Genes Associated with Photoreceptor Transmutation and Dim-Light Ancestry.

Science.gov (United States)

Schott, Ryan K; Van Nynatten, Alexander; Card, Daren C; Castoe, Todd A; S W Chang, Belinda

2018-06-01

The visual systems of snakes are heavily modified relative to other squamates, a condition often thought to reflect their fossorial origins. Further modifications are seen in caenophidian snakes, where evolutionary transitions between rod and cone photoreceptors, termed photoreceptor transmutations, have occurred in many lineages. Little previous work, however, has focused on the molecular evolutionary underpinnings of these morphological changes. To address this, we sequenced seven snake eye transcriptomes and utilized new whole-genome and targeted capture sequencing data. We used these data to analyze gene loss and shifts in selection pressures in phototransduction genes that may be associated with snake evolutionary origins and photoreceptor transmutation. We identified the surprising loss of rhodopsin kinase (GRK1), despite a low degree of gene loss overall and a lack of relaxed selection early during snake evolution. These results provide some of the first evolutionary genomic corroboration for a dim-light ancestor that lacks strong fossorial adaptations. Our results also indicate that snakes with photoreceptor transmutation experienced significantly different selection pressures from other reptiles. Significant positive selection was found primarily in cone-specific genes, but not rod-specific genes, contrary to our expectations. These results reveal potential molecular adaptations associated with photoreceptor transmutation and also highlight unappreciated functional differences between rod- and cone-specific phototransduction proteins. This intriguing example of snake visual system evolution illustrates how the underlying molecular components of a complex system can be reshaped in response to changing selection pressures.

Identification of landscape features influencing gene flow: How useful are habitat selection models?

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Gretchen H. Roffler; Michael K. Schwartz; Kristine Pilgrim; Sandra L. Talbot; George K. Sage; Layne G. Adams; Gordon Luikart

2016-01-01

Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is...

Likelihood analysis of the chalcone synthase genes suggests the role of positive selection in morning glories (Ipomoea).

Science.gov (United States)

Yang, Ji; Gu, Hongya; Yang, Ziheng

2004-01-01

Chalcone synthase (CHS) is a key enzyme in the biosynthesis of flavonoides, which are important for the pigmentation of flowers and act as attractants to pollinators. Genes encoding CHS constitute a multigene family in which the copy number varies among plant species and functional divergence appears to have occurred repeatedly. In morning glories (Ipomoea), five functional CHS genes (A-E) have been described. Phylogenetic analysis of the Ipomoea CHS gene family revealed that CHS A, B, and C experienced accelerated rates of amino acid substitution relative to CHS D and E. To examine whether the CHS genes of the morning glories underwent adaptive evolution, maximum-likelihood models of codon substitution were used to analyze the functional sequences in the Ipomoea CHS gene family. These models used the nonsynonymous/synonymous rate ratio (omega = d(N)/ d(S)) as an indicator of selective pressure and allowed the ratio to vary among lineages or sites. Likelihood ratio test suggested significant variation in selection pressure among amino acid sites, with a small proportion of them detected to be under positive selection along the branches ancestral to CHS A, B, and C. Positive Darwinian selection appears to have promoted the divergence of subfamily ABC and subfamily DE and is at least partially responsible for a rate increase following gene duplication.

Assessment of ptxD gene as an alternative selectable marker for Agrobacterium-mediated maize transformation.

Science.gov (United States)

Nahampun, Hartinio N; López-Arredondo, Damar; Xu, Xing; Herrera-Estrella, Luis; Wang, Kan

2016-05-01

Bacterial phosphite oxidoreductase gene and chemical phosphite can be used as a selection system for Agrobacterium -mediated maize transformation. Application of phosphite (Phi) on plants can interfere the plant metabolic system leading to stunted growth and lethality. On the other hand, ectopic expression of the ptxD gene in tobacco and Arabidopsis allowed plants to grow in media with Phi as the sole phosphorous source. The phosphite oxidoreductase (PTXD) enzyme catalyzes the conversion of Phi into phosphate (Pi) that can then be metabolized by plants and utilized as their essential phosphorous source. Here we assess an alternative selectable marker based on a bacterial ptxD gene for Agrobacterium-mediated maize transformation. We compared the transformation frequencies of maize using either the ptxD/Phi selection system or a standard herbicide bar/bialaphos selection system. Two maize genotypes, a transformation amenable hybrid Hi II and an inbred B104, were tested. Transgene presence, insertion copy numbers, and ptxD transcript levels were analyzed and compared. This work demonstrates that the ptxD/Phi selection system can be used for Agrobacterium-mediated maize transformation of both type I and type II callus culture and achieve a comparable frequency as that of the herbicide bar/bialaphos selection system.

IMPROVEMENT METHOD OF GENE TRANSFER IN Kappaphycus alvarezii

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St. Hidayah Triana

2016-11-01

Full Text Available Method of foreign gene transfer in red seaweed Kappaphycus alvarezii has been reported, however, li-mited number of transgenic F0 (broodstock was obtained. This study was conducted to improve the method of gene transfer mediated by Agrobacterium tumefaciens in order to obtain high percentage of K. alvarezii transgenic. Superoxide dismutase gene from Melastoma malabatrichum (MmCu/Zn-SOD was used as model towards increasing adaptability of K. alvarezii to environmental stress. The treat-ments were the culture media and recovery duration, and each treatment consisted of three replica-tions. The best method was co-cultivation using liquid media, then recovery was conducted in liquid media for 10 days. That treatment allowed higher transformation percentage (90%, regeneration effi-ciency (90%, putative bud efficiency (100%, number of buds and explants sprouted (100% and transgenic explants (100%. The transgenic explants showed an amplification PCR product of Mm-Cu/Zn-SOD gene fragment, whereas the non-transgenic explants showed no amplification product.  All results revealed that suitable method of transgenesis for K. alvarezii has been developed. Keywords:       Agrobacterium tumefaciens, culture media, Kappaphycus alvarezii, recovery duration, transformation

Selection and Verification of Candidate Reference Genes for Mature MicroRNA Expression by Quantitative RT-PCR in the Tea Plant (Camellia sinensis

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Hui Song

2016-05-01

Full Text Available Quantitative reverse transcription-polymerase chain reaction (qRT-PCR is a rapid and sensitive method for analyzing microRNA (miRNA expression. However, accurate qRT-PCR results depend on the selection of reliable reference genes as internal positive controls. To date, few studies have identified reliable reference genes for differential expression analysis of miRNAs among tissues, and among experimental conditions in plants. In this study, three miRNAs and four non-coding small RNAs (ncRNA were selected as reference candidates, and the stability of their expression was evaluated among different tissues and under different experimental conditions in the tea plant (Camellia sinensis using the geNorm and NormFinder programs. It was shown that miR159a was the best single reference gene in the bud to the fifth leaf, 5S rRNA was the most suitable gene in different organs, miR6149 was the most stable gene when the leaves were attacked by Ectropis oblique and U4, miR5368n and miR159a were the best genes when the leaves were treated by methyl jasmonate (MeJA, salicylic acid (SA and abscisic acid (ABA, respectively. Our results provide suitable reference genes for future investigations on miRNA functions in tea plants.

The joint effects of background selection and genetic recombination on local gene genealogies.

Science.gov (United States)

Zeng, Kai; Charlesworth, Brian

2011-09-01

Background selection, the effects of the continual removal of deleterious mutations by natural selection on variability at linked sites, is potentially a major determinant of DNA sequence variability. However, the joint effects of background selection and genetic recombination on the shape of the neutral gene genealogy have proved hard to study analytically. The only existing formula concerns the mean coalescent time for a pair of alleles, making it difficult to assess the importance of background selection from genome-wide data on sequence polymorphism. Here we develop a structured coalescent model of background selection with recombination and implement it in a computer program that efficiently generates neutral gene genealogies for an arbitrary sample size. We check the validity of the structured coalescent model against forward-in-time simulations and show that it accurately captures the effects of background selection. The model produces more accurate predictions of the mean coalescent time than the existing formula and supports the conclusion that the effect of background selection is greater in the interior of a deleterious region than at its boundaries. The level of linkage disequilibrium between sites is elevated by background selection, to an extent that is well summarized by a change in effective population size. The structured coalescent model is readily extendable to more realistic situations and should prove useful for analyzing genome-wide polymorphism data.

Efficacious and safe tissue-selective controlled gene therapy approaches for the cornea.

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Rajiv R Mohan

2011-04-01

Full Text Available Untargeted and uncontrolled gene delivery is a major cause of gene therapy failure. This study aimed to define efficient and safe tissue-selective targeted gene therapy approaches for delivering genes into keratocytes of the cornea in vivo using a normal or diseased rabbit model. New Zealand White rabbits, adeno-associated virus serotype 5 (AAV5, and a minimally invasive hair-dryer based vector-delivery technique were used. Fifty microliters of AAV5 titer (6.5×10(12 vg/ml expressing green fluorescent protein gene (GFP was topically applied onto normal or diseased (fibrotic or neovascularized rabbit corneas for 2-minutes with a custom vector-delivery technique. Corneal fibrosis and neovascularization in rabbit eyes were induced with photorefractive keratectomy using excimer laser and VEGF (630 ng using micropocket assay, respectively. Slit-lamp biomicroscopy and immunocytochemistry were used to confirm fibrosis and neovascularization in rabbit corneas. The levels, location and duration of delivered-GFP gene expression in the rabbit stroma were measured with immunocytochemistry and/or western blotting. Slot-blot measured delivered-GFP gene copy number. Confocal microscopy performed in whole-mounts of cornea and thick corneal sections determined geometric and spatial localization of delivered-GFP in three-dimensional arrangement. AAV5 toxicity and safety were evaluated with clinical eye exam, stereomicroscopy, slit-lamp biomicroscopy, and H&E staining. A single 2-minute AAV5 topical application via custom delivery-technique efficiently and selectively transduced keratocytes in the anterior stroma of normal and diseased rabbit corneas as evident from immunocytochemistry and confocal microscopy. Transgene expression was first detected at day 3, peaked at day 7, and was maintained up to 16 weeks (longest tested time point. Clinical and slit-lamp eye examination in live rabbits and H&E staining did not reveal any significant changes between AAV5

Disentangling the effects of selection and loss bias on gene dynamics

NARCIS (Netherlands)

Iranzo, J.; Cuesta, J.A.; Manrubia, S.; Katsnelson, M.I.; Koonin, E.V.

2017-01-01

We combine mathematical modeling of genome evolution with comparative analysis of prokaryotic genomes to estimate the relative contributions of selection and intrinsic loss bias to the evolution of different functional classes of genes and mobile genetic elements (MGE). An exact solution for the

AMES: Towards an Agile Method for ERP Selection

OpenAIRE

Juell-Skielse, Gustaf; Nilsson, Anders G.; Nordqvist, Andreas; Westergren, Mattias

2012-01-01

Conventional on-premise installations of ERP are now rapidly being replaced by ERP as service. Although ERP becomes more accessible and no longer requires local infrastructure, current selection methods do not take full advantage of the provided agility. In this paper we present AMES (Agile Method for ERP Selection), a novel method for ERP selection which better utilizes the strengths of service oriented ERP. AMES is designed to shorten lead time for selection, support identification of essen...

MAINTENANCE OF ECOLOGICALLY SIGNIFICANT GENETIC VARIATION IN THE TIGER SWALLOWTAIL BUTTERFLY THROUGH DIFFERENTIAL SELECTION AND GENE FLOW.

Science.gov (United States)

Bossart, J L; Scriber, J M

1995-12-01

Differential selection in a heterogeneous environment is thought to promote the maintenance of ecologically significant genetic variation. Variation is maintained when selection is counterbalanced by the homogenizing effects of gene flow and random mating. In this study, we examine the relative importance of differential selection and gene flow in maintaining genetic variation in Papilio glaucus. Differential selection on traits contributing to successful use of host plants (oviposition preference and larval performance) was assessed by comparing the responses of southern Ohio, north central Georgia, and southern Florida populations of P. glaucus to three hosts: Liriodendron tulipifera, Magnolia virginiana, and Prunus serotina. Gene flow among populations was estimated using allozyme frequencies from nine polymorphic loci. Significant genetic differentiation was observed among populations for both oviposition preference and larval performance. This differentiation was interpreted to be the result of selection acting on Florida P. glaucus for enhanced use of Magnolia, the prevalent host in Florida. In contrast, no evidence of population differentiation was revealed by allozyme frequencies. F ST -values were very small and Nm, an estimate of the relative strengths of gene flow and genetic drift, was large, indicating that genetic exchange among P. glaucus populations is relatively unrestricted. The contrasting patterns of spatial differentiation for host-use traits and lack of differentiation for electrophoretically detectable variation implies that differential selection among populations will be counterbalanced by gene flow, thereby maintaining genetic variation for host-use traits. © 1995 The Society for the Study of Evolution.

Lack of direct evidence for natural selection at the candidate thrifty gene locus, PPARGC1A.

Science.gov (United States)

Cadzow, Murray; Merriman, Tony R; Boocock, James; Dalbeth, Nicola; Stamp, Lisa K; Black, Michael A; Visscher, Peter M; Wilcox, Phillip L

2016-11-15

The gene PPARGC1A, in particular the Gly482Ser variant (rs8192678), had been proposed to be subject to natural selection, particularly in recent progenitors of extant Polynesian populations. Reasons include high levels of population differentiation and increased frequencies of the derived type 2 diabetes (T2D) risk 482Ser allele, and association with body mass index (BMI) in a small Tongan population. However, no direct statistical tests for selection have been applied. Using a range of Polynesian populations (Tongan, Māori, Samoan) we re-examined evidence for association between Gly482Ser with T2D and BMI as well as gout. Using also Asian, European, and African 1000 Genome Project samples a range of statistical tests for selection (F ST , integrated haplotype score (iHS), cross population extended haplotype homozygosity (XP-EHH), Tajima's D and Fay and Wu's H) were conducted on the PPARGC1A locus. No statistically significant evidence for association between Gly482Ser and any of BMI, T2D or gout was found. Population differentiation (F ST ) was smallest between Asian and Pacific populations (New Zealand Māori ≤ 0.35, Samoan ≤ 0.20). When compared to European (New Zealand Māori ≤ 0.40, Samoan ≤ 0.25) or African populations (New Zealand Māori ≤ 0.80, Samoan ≤ 0.66) this differentiation was larger. We did not find any strong evidence for departure from neutral evolution at this locus when applying any of the other statistical tests for selection. However, using the same analytical methods, we found evidence for selection in specific populations at previously identified loci, indicating that lack of selection was the most likely explanation for the lack of evidence of selection in PPARGC1A. We conclude that there is no compelling evidence for selection at this locus, and that this gene should not be considered a candidate thrifty gene locus in Pacific populations. High levels of population differentiation at this locus and the

Sex linkage, sex-specific selection, and the role of recombination in the evolution of sexually dimorphic gene expression.

Science.gov (United States)

Connallon, Tim; Clark, Andrew G

2010-12-01

Sex-biased genes--genes that are differentially expressed within males and females--are nonrandomly distributed across animal genomes, with sex chromosomes and autosomes often carrying markedly different concentrations of male- and female-biased genes. These linkage patterns are often gene- and lineage-dependent, differing between functional genetic categories and between species. Although sex-specific selection is often hypothesized to shape the evolution of sex-linked and autosomal gene content, population genetics theory has yet to account for many of the gene- and lineage-specific idiosyncrasies emerging from the empirical literature. With the goal of improving the connection between evolutionary theory and a rapidly growing body of genome-wide empirical studies, we extend previous population genetics theory of sex-specific selection by developing and analyzing a biologically informed model that incorporates sex linkage, pleiotropy, recombination, and epistasis, factors that are likely to vary between genes and between species. Our results demonstrate that sex-specific selection and sex-specific recombination rates can generate, and are compatible with, the gene- and species-specific linkage patterns reported in the genomics literature. The theory suggests that sexual selection may strongly influence the architectures of animal genomes, as well as the chromosomal distribution of fixed substitutions underlying sexually dimorphic traits. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

Dominant negative selection of vaccinia virus using a thymidine kinase/thymidylate kinase fusion gene and the prodrug azidothymidine

International Nuclear Information System (INIS)

Holzer, Georg W.; Mayrhofer, Josef; Gritschenberger, Werner; Falkner, Falko G.

2005-01-01

The Escherichia coli thymidine kinase/thymidylate kinase (tk/tmk) fusion gene encodes an enzyme that efficiently converts the prodrug 3'-azido-2',3'-dideoxythymidine (AZT) into its toxic triphosphate derivative, a substance which stops DNA chain elongation. Integration of this marker gene into vaccinia virus that normally is not inhibited by AZT allowed the establishment of a powerful selection procedure for recombinant viruses. In contrast to the conventional vaccinia thymidine kinase (tk) selection that is performed in tk-negative cell lines, AZT selection can be performed in normal (tk-positive) cell lines. The technique is especially useful for the generation of replication-deficient vaccinia viruses and may also be used for gene knock-out studies of essential vaccinia genes

Selection of housekeeping genes and demonstration of RNAi in cotton leafhopper, Amrasca biguttula biguttula (Ishida)

Science.gov (United States)

Gupta, Mridula; Pandher, Suneet; Kaur, Gurmeet; Rathore, Pankaj; Palli, Subba Reddy

2018-01-01

Amrasca biguttula biguttula (Ishida) commonly known as cotton leafhopper is a severe pest of cotton and okra. Not much is known on this insect at molecular level due to lack of genomic and transcriptomic data. To prepare for functional genomic studies in this insect, we evaluated 15 common housekeeping genes (Tub, B-Tub, EF alpha, GADPH, UbiCF, RP13, Ubiq, G3PD, VATPase, Actin, 18s, 28s, TATA, ETF, SOD and Cytolytic actin) during different developmental stages and under starvation stress. We selected early (1st and 2nd), late (3rd and 4th) stage nymphs and adults for identification of stable housekeeping genes using geNorm, NormFinder, BestKeeper and RefFinder software. Based on the different algorithms, RP13 and VATPase are identified as the most suitable reference genes for quantification of gene expression by reverse transcriptase quantitative PCR (RT-qPCR). Based on RefFinder which comprehended the results of three algorithms, RP13 in adults, Tubulin (Tub) in late nymphs, 28S in early nymph and UbiCF under starvation stress were identified as the most stable genes. We also developed methods for feeding double-stranded RNA (dsRNA) incorporated in the diet. Feeding dsRNA targeting Snf7, IAP, AQP1, and VATPase caused 56.17–77.12% knockdown of targeted genes compared to control and 16 to 48% mortality of treated insects when compared to control. PMID:29329327

Selection of housekeeping genes and demonstration of RNAi in cotton leafhopper, Amrasca biguttula biguttula (Ishida.

Directory of Open Access Journals (Sweden)

Satnam Singh

Full Text Available Amrasca biguttula biguttula (Ishida commonly known as cotton leafhopper is a severe pest of cotton and okra. Not much is known on this insect at molecular level due to lack of genomic and transcriptomic data. To prepare for functional genomic studies in this insect, we evaluated 15 common housekeeping genes (Tub, B-Tub, EF alpha, GADPH, UbiCF, RP13, Ubiq, G3PD, VATPase, Actin, 18s, 28s, TATA, ETF, SOD and Cytolytic actin during different developmental stages and under starvation stress. We selected early (1st and 2nd, late (3rd and 4th stage nymphs and adults for identification of stable housekeeping genes using geNorm, NormFinder, BestKeeper and RefFinder software. Based on the different algorithms, RP13 and VATPase are identified as the most suitable reference genes for quantification of gene expression by reverse transcriptase quantitative PCR (RT-qPCR. Based on RefFinder which comprehended the results of three algorithms, RP13 in adults, Tubulin (Tub in late nymphs, 28S in early nymph and UbiCF under starvation stress were identified as the most stable genes. We also developed methods for feeding double-stranded RNA (dsRNA incorporated in the diet. Feeding dsRNA targeting Snf7, IAP, AQP1, and VATPase caused 56.17-77.12% knockdown of targeted genes compared to control and 16 to 48% mortality of treated insects when compared to control.

Purifying Selection Maintains Dosage-Sensitive Genes during Degeneration of the Threespine Stickleback Y Chromosome

Science.gov (United States)

White, Michael A.; Kitano, Jun; Peichel, Catherine L.

2015-01-01

Sex chromosomes are subject to unique evolutionary forces that cause suppression of recombination, leading to sequence degeneration and the formation of heteromorphic chromosome pairs (i.e., XY or ZW). Although progress has been made in characterizing the outcomes of these evolutionary processes on vertebrate sex chromosomes, it is still unclear how recombination suppression and sequence divergence typically occur and how gene dosage imbalances are resolved in the heterogametic sex. The threespine stickleback fish (Gasterosteus aculeatus) is a powerful model system to explore vertebrate sex chromosome evolution, as it possesses an XY sex chromosome pair at relatively early stages of differentiation. Using a combination of whole-genome and transcriptome sequencing, we characterized sequence evolution and gene expression across the sex chromosomes. We uncovered two distinct evolutionary strata that correspond with known structural rearrangements on the Y chromosome. In the oldest stratum, only a handful of genes remain, and these genes are under strong purifying selection. By comparing sex-linked gene expression with expression of autosomal orthologs in an outgroup, we show that dosage compensation has not evolved in threespine sticklebacks through upregulation of the X chromosome in males. Instead, in the oldest stratum, the genes that still possess a Y chromosome allele are enriched for genes predicted to be dosage sensitive in mammals and yeast. Our results suggest that dosage imbalances may have been avoided at haploinsufficient genes by retaining function of the Y chromosome allele through strong purifying selection. PMID:25818858

[Gene method for inconsistent hydrological frequency calculation. 2: Diagnosis system of hydrological genes and method of hydrological moment genes with inconsistent characters].

Science.gov (United States)

Xie, Ping; Zhao, Jiang Yan; Wu, Zi Yi; Sang, Yan Fang; Chen, Jie; Li, Bin Bin; Gu, Hai Ting

2018-04-01

The analysis of inconsistent hydrological series is one of the major problems that should be solved for engineering hydrological calculation in changing environment. In this study, the diffe-rences of non-consistency and non-stationarity were analyzed from the perspective of composition of hydrological series. The inconsistent hydrological phenomena were generalized into hydrological processes with inheritance, variability and evolution characteristics or regulations. Furthermore, the hydrological genes were identified following the theory of biological genes, while their inheritance bases and variability bases were determined based on composition of hydrological series under diffe-rent time scales. To identify and test the components of hydrological genes, we constructed a diagnosis system of hydrological genes. With the P-3 distribution as an example, we described the process of construction and expression of the moment genes to illustrate the inheritance, variability and evolution principles of hydrological genes. With the annual minimum 1-month runoff series of Yunjinghong station in Lancangjiang River basin as an example, we verified the feasibility and practicability of hydrological gene theory for the calculation of inconsistent hydrological frequency. The results showed that the method could be used to reveal the evolution of inconsistent hydrological series. Therefore, it provided a new research pathway for engineering hydrological calculation in changing environment and an essential reference for the assessment of water security.

Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space

Science.gov (United States)

Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R.; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J.

2013-01-01

For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding. PMID:23592960

Combinatorial pooling enables selective sequencing of the barley gene space.

Directory of Open Access Journals (Sweden)

Stefano Lonardi

2013-04-01

Full Text Available For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

Combinatorial pooling enables selective sequencing of the barley gene space.

Science.gov (United States)

Lonardi, Stefano; Duma, Denisa; Alpert, Matthew; Cordero, Francesca; Beccuti, Marco; Bhat, Prasanna R; Wu, Yonghui; Ciardo, Gianfranco; Alsaihati, Burair; Ma, Yaqin; Wanamaker, Steve; Resnik, Josh; Bozdag, Serdar; Luo, Ming-Cheng; Close, Timothy J

2013-04-01

For the vast majority of species - including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

HisB as novel selection marker for gene targeting approaches in Aspergillus niger.

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Fiedler, Markus R M; Gensheimer, Tarek; Kubisch, Christin; Meyer, Vera

2017-03-08

For Aspergillus niger, a broad set of auxotrophic and dominant resistance markers is available. However, only few offer targeted modification of a gene of interest into or at a genomic locus of choice, which hampers functional genomics studies. We thus aimed to extend the available set by generating a histidine auxotrophic strain with a characterized hisB locus for targeted gene integration and deletion in A. niger. A histidine-auxotrophic strain was established via disruption of the A. niger hisB gene by using the counterselectable pyrG marker. After curing, a hisB - , pyrG - strain was obtained, which served as recipient strain for further studies. We show here that both hisB orthologs from A. nidulans and A. niger can be used to reestablish histidine prototrophy in this recipient strain. Whereas the hisB gene from A. nidulans was suitable for efficient gene targeting at different loci in A. niger, the hisB gene from A. niger allowed efficient integration of a Tet-on driven luciferase reporter construct at the endogenous non-functional hisB locus. Subsequent analysis of the luciferase activity revealed that the hisB locus is tight under non-inducing conditions and allows even higher luciferase expression levels compared to the pyrG integration locus. Taken together, we provide here an alternative selection marker for A. niger, hisB, which allows efficient homologous integration rates as well as high expression levels which compare favorably to the well-established pyrG selection marker.

Transcriptome-wide selection of a reliable set of reference genes for gene expression studies in potato cyst nematodes (Globodera spp.).

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Sabeh, Michael; Duceppe, Marc-Olivier; St-Arnaud, Marc; Mimee, Benjamin

2018-01-01

Relative gene expression analyses by qRT-PCR (quantitative reverse transcription PCR) require an internal control to normalize the expression data of genes of interest and eliminate the unwanted variation introduced by sample preparation. A perfect reference gene should have a constant expression level under all the experimental conditions. However, the same few housekeeping genes selected from the literature or successfully used in previous unrelated experiments are often routinely used in new conditions without proper validation of their stability across treatments. The advent of RNA-Seq and the availability of public datasets for numerous organisms are opening the way to finding better reference genes for expression studies. Globodera rostochiensis is a plant-parasitic nematode that is particularly yield-limiting for potato. The aim of our study was to identify a reliable set of reference genes to study G. rostochiensis gene expression. Gene expression levels from an RNA-Seq database were used to identify putative reference genes and were validated with qRT-PCR analysis. Three genes, GR, PMP-3, and aaRS, were found to be very stable within the experimental conditions of this study and are proposed as reference genes for future work.

Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.

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Fei Xiao

Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

Gene set analysis: limitations in popular existing methods and proposed improvements.

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Mishra, Pashupati; Törönen, Petri; Leino, Yrjö; Holm, Liisa

2014-10-01

Gene set analysis is the analysis of a set of genes that collectively contribute to a biological process. Most popular gene set analysis methods are based on empirical P-value that requires large number of permutations. Despite numerous gene set analysis methods developed in the past decade, the most popular methods still suffer from serious limitations. We present a gene set analysis method (mGSZ) based on Gene Set Z-scoring function (GSZ) and asymptotic P-values. Asymptotic P-value calculation requires fewer permutations, and thus speeds up the gene set analysis process. We compare the GSZ-scoring function with seven popular gene set scoring functions and show that GSZ stands out as the best scoring function. In addition, we show improved performance of the GSA method when the max-mean statistics is replaced by the GSZ scoring function. We demonstrate the importance of both gene and sample permutations by showing the consequences in the absence of one or the other. A comparison of asymptotic and empirical methods of P-value estimation demonstrates a clear advantage of asymptotic P-value over empirical P-value. We show that mGSZ outperforms the state-of-the-art methods based on two different evaluations. We compared mGSZ results with permutation and rotation tests and show that rotation does not improve our asymptotic P-values. We also propose well-known asymptotic distribution models for three of the compared methods. mGSZ is available as R package from cran.r-project.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Evidence of Positive Selection of Aquaporins Genes from Pontoporia blainvillei during the Evolutionary Process of Cetaceans.

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Simone Lima São Pedro

Full Text Available Marine mammals are well adapted to their hyperosmotic environment. Several morphological and physiological adaptations for water conservation and salt excretion are known to be present in cetaceans, being responsible for regulating salt balance. However, most previous studies have focused on the unique renal physiology of marine mammals, but the molecular bases of these mechanisms remain poorly explored. Many genes have been identified to be involved in osmotic regulation, including the aquaporins. Considering that aquaporin genes were potentially subject to strong selective pressure, the aim of this study was to analyze the molecular evolution of seven aquaporin genes (AQP1, AQP2, AQP3, AQP4, AQP6, AQP7, and AQP9 comparing the lineages of cetaceans and terrestrial mammals.Our results demonstrated strong positive selection in cetacean-specific lineages acting only in the gene for AQP2 (amino acids 23, 83, 107,179, 180, 181, 182, whereas no selection was observed in terrestrial mammalian lineages. We also analyzed the changes in the 3D structure of the aquaporin 2 protein. Signs of strong positive selection in AQP2 sites 179, 180, 181, and 182 were unexpectedly identified only in the baiji lineage, which was the only river dolphin examined in this study. Positive selection in aquaporins AQP1 (45, AQP4 (74, AQP7 (342, 343, 356 was detected in cetaceans and artiodactyls, suggesting that these events are not related to maintaining water and electrolyte homeostasis in seawater.Our results suggest that the AQP2 gene might reflect different selective pressures in maintaining water balance in cetaceans, contributing to the passage from the terrestrial environment to the aquatic. Further studies are necessary, especially those including other freshwater dolphins, who exhibit osmoregulatory mechanisms different from those of marine cetaceans for the same essential task of maintaining serum electrolyte balance.

Gene transfer preferentially selects MHC class I positive tumour cells and enhances tumour immunogenicity.

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Hacker, Ulrich T; Schildhauer, Ines; Barroso, Margarita Céspedes; Kofler, David M; Gerner, Franz M; Mysliwietz, Josef; Buening, Hildegard; Hallek, Michael; King, Susan B S

2006-05-01

The modulated expression of MHC class I on tumour tissue is well documented. Although the effect of MHC class I expression on the tumorigenicity and immunogenicity of MHC class I negative tumour cell lines has been rigorously studied, less is known about the validity of gene transfer and selection in cell lines with a mixed MHC class I phenotype. To address this issue we identified a C26 cell subline that consists of distinct populations of MHC class I (H-2D/K) positive and negative cells. Transient transfection experiments using liposome-based transfer showed a lower transgene expression in MHC class I negative cells. In addition, MHC class I negative cells were more sensitive to antibiotic selection. This led to the generation of fully MHC class I positive cell lines. In contrast to C26 cells, all transfectants were rejected in vivo and induced protection against the parental tumour cells in rechallenge experiments. Tumour cell specificity of the immune response was demonstrated in in vitro cytokine secretion and cytotoxicity assays. Transfectants expressing CD40 ligand and hygromycin phosphotransferase were not more immunogenic than cells expressing hygromycin resistance alone. We suggest that the MHC class I positive phenotype of the C26 transfectants had a bearing on their immunogenicity, because selected MHC class I positive cells were more immunogenic than parental C26 cells and could induce specific anti-tumour immune responses. These data demonstrate that the generation of tumour cell transfectants can lead to the selection of subpopulations that show an altered phenotype compared to the parental cell line and display altered immunogenicity independent of selection marker genes or other immune modulatory genes. Our results show the importance of monitoring gene transfer in the whole tumour cell population, especially for the evaluation of in vivo therapies targeted to heterogeneous tumour cell populations.

On theoretical models of gene expression evolution with random genetic drift and natural selection.

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Osamu Ogasawara

2009-11-01

Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

Alternative microbial methods: An overview and selection criteria.

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Jasson, Vicky; Jacxsens, Liesbeth; Luning, Pieternel; Rajkovic, Andreja; Uyttendaele, Mieke

2010-09-01

This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant bibliography. Perspectives on future development and the potential of the rapid method for routine application in food diagnostics are discussed. As various alternative "rapid" methods in different formats are available on the market, it can be very difficult for a food business operator or for a control authority to select the most appropriate method which fits its purpose. Validation of a method by a third party, according to international accepted protocol based upon ISO 16140, may increase the confidence in the performance of a method. A list of at the moment validated methods for enumeration of both utility indicators (aerobic plate count) and hygiene indicators (Enterobacteriaceae, Escherichia coli, coagulase positive Staphylococcus) as well as for detection of the four major pathogens (Salmonella spp., Listeria monocytogenes, E. coli O157 and Campylobacter spp.) is included with reference to relevant websites to check for updates. In a second part of this study, selection criteria are introduced to underpin the choice of the appropriate method(s) for a defined application. The selection criteria link the definition of the context in which the user of the method functions - and thus the prospective use of the microbial test results - with the technical information on the method and its operational requirements and sustainability. The selection criteria can help the end user of the method to obtain a systematic insight into all relevant factors to be taken into account for selection of a method for microbial analysis. Copyright 2010 Elsevier Ltd. All rights reserved.

Comparative genomic and transcriptomic analysis of selected fatty acid biosynthesis genes and CNL disease resistance genes in oil palm

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Rosli, Rozana; Amiruddin, Nadzirah; Ab Halim, Mohd Amin; Chan, Pek-Lan; Chan, Kuang-Lim; Azizi, Norazah; Morris, Priscilla E.; Leslie Low, Eng-Ti; Ong-Abdullah, Meilina; Sambanthamurthi, Ravigadevi; Singh, Rajinder

2018-01-01

Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops. PMID:29672525

Comparative genomic and transcriptomic analysis of selected fatty acid biosynthesis genes and CNL disease resistance genes in oil palm.

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Rosli, Rozana; Amiruddin, Nadzirah; Ab Halim, Mohd Amin; Chan, Pek-Lan; Chan, Kuang-Lim; Azizi, Norazah; Morris, Priscilla E; Leslie Low, Eng-Ti; Ong-Abdullah, Meilina; Sambanthamurthi, Ravigadevi; Singh, Rajinder; Murphy, Denis J

2018-01-01

Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops.

Differential gene expression and clonal selection during cellular transformation induced by adhesion deprivation

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Kumar Mahesh J

2010-12-01

Full Text Available Abstract Background Anchorage independent growth is an important hallmark of oncogenic transformation. Previous studies have shown that when adhesion dependent fibroblasts were prevented from adhering to a substrate they underwent anoikis. In the present study we have demonstrated how anoikis resistant cells gain the transformation related properties with sequential selection of genes. We have proposed this process as a model system for selection of transformed cells from normal cells. Results This report demonstrates that some fibroblasts can survive during late stages of anoikis, at which time they exhibit transformation-associated properties such as in vitro colony formation in soft agar and in vivo subcutaneous tumour formation in nude mice. Cytogenetic characterisation of these cells revealed that they contained a t (2; 2 derivative chromosome and they have a selective survival advantage in non adherent conditions. Gene expression profile indicated that these cells over expressed genes related to hypoxia, glycolysis and tumor suppression/metastasis which could be helpful in their retaining a transformed phenotype. Conclusion Our results reveal some new links between anoikis and cell transformation and they provide a reproducible model system which can potentially be useful to study multistage cancer and to identify new targets for drug development.

Gene duplication, loss and selection in the evolution of saxitoxin biosynthesis in alveolates.

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Murray, Shauna A; Diwan, Rutuja; Orr, Russell J S; Kohli, Gurjeet S; John, Uwe

2015-11-01

A group of marine dinoflagellates (Alveolata, Eukaryota), consisting of ∼10 species of the genus Alexandrium, Gymnodinium catenatum and Pyrodinium bahamense, produce the toxin saxitoxin and its analogues (STX), which can accumulate in shellfish, leading to ecosystem and human health impacts. The genes, sxt, putatively involved in STX biosynthesis, have recently been identified, however, the evolution of these genes within dinoflagellates is not clear. There are two reasons for this: uncertainty over the phylogeny of dinoflagellates; and that the sxt genes of many species of Alexandrium and other dinoflagellate genera are not known. Here, we determined the phylogeny of STX-producing and other dinoflagellates based on a concatenated eight-gene alignment. We determined the presence, diversity and phylogeny of sxtA, domains A1 and A4 and sxtG in 52 strains of Alexandrium, and a further 43 species of dinoflagellates and thirteen other alveolates. We confirmed the presence and high sequence conservation of sxtA, domain A4, in 40 strains (35 Alexandrium, 1 Pyrodinium, 4 Gymnodinium) of 8 species of STX-producing dinoflagellates, and absence from non-producing species. We found three paralogs of sxtA, domain A1, and a widespread distribution of sxtA1 in non-STX producing dinoflagellates, indicating duplication events in the evolution of this gene. One paralog, clade 2, of sxtA1 may be particularly related to STX biosynthesis. Similarly, sxtG appears to be generally restricted to STX-producing species, while three amidinotransferase gene paralogs were found in dinoflagellates. We investigated the role of positive (diversifying) selection following duplication in sxtA1 and sxtG, and found negative selection in clades of sxtG and sxtA1, clade 2, suggesting they were functionally constrained. Significant episodic diversifying selection was found in some strains in clade 3 of sxtA1, a clade that may not be involved in STX biosynthesis, indicating pressure for diversification

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

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Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

Candidate gene identification of ovulation-inducing genes by RNA sequencing with an in vivo assay in zebrafish.

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Wanlada Klangnurak

Full Text Available We previously reported the microarray-based selection of three ovulation-related genes in zebrafish. We used a different selection method in this study, RNA sequencing analysis. An additional eight up-regulated candidates were found as specifically up-regulated genes in ovulation-induced samples. Changes in gene expression were confirmed by qPCR analysis. Furthermore, up-regulation prior to ovulation during natural spawning was verified in samples from natural pairing. Gene knock-out zebrafish strains of one of the candidates, the starmaker gene (stm, were established by CRISPR genome editing techniques. Unexpectedly, homozygous mutants were fertile and could spawn eggs. However, a high percentage of unfertilized eggs and abnormal embryos were produced from these homozygous females. The results suggest that the stm gene is necessary for fertilization. In this study, we selected additional ovulation-inducing candidate genes, and a novel function of the stm gene was investigated.

Inventory of LCIA selection methods for assessing toxic releases. Methods and typology report part B

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Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

method(s) in Work package 8 (WP8) of the OMNIITOX project. The selection methods and the other CRS methods are described in detail, a set of evaluation criteria are developed and the methods are evaluated against these criteria. This report (Deliverable 11B (D11B)) gives the results from task 7.1d, 7.1e......This report describes an inventory of Life Cycle Impact Assessment (LCIA) selection methods for assessing toxic releases. It consists of an inventory of current selection methods and other Chemical Ranking and Scoring (CRS) methods assessed to be relevant for the development of (a) new selection...... and 7.1f of WP 7 for selection methods. The other part of D11 (D11A) is reported in another report and deals with characterisation methods. A selection method is a method for prioritising chemical emissions to be included in an LCIA characterisation of toxic releases, i.e. calculating indicator scores...

Positive selection within the Schizophrenia-associated GABA(A receptor beta(2 gene.

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Wing-Sze Lo

Full Text Available The gamma-aminobutyric acid type-A (GABA(A receptor plays a major role in inhibitory neurotransmissions. Intronic SNPs and haplotypes in GABRB2, the gene for GABA(A receptor beta(2 subunit, are associated with schizophrenia and correlated with the expression of two alternatively spliced beta(2 isoforms. In the present study, using chimpanzee as an ancestral reference, high frequencies were observed for the derived (D alleles of the four SNPs rs6556547, rs187269, rs1816071 and rs1816072 in GABRB2, suggesting the occurrence of positive selection for these derived alleles. Coalescence-based simulation showed that the population frequency spectra and the frequencies of H56, the haplotype having all four D alleles, significantly deviated from neutral-evolution expectation in various demographic models. Haplotypes containing the derived allele of rs1816072 displayed significantly less diversity compared to haplotypes containing its ancestral allele, further supporting positive selection. The variations in DD-genotype frequencies in five human populations provided a snapshot of the evolutionary history, which suggested that the positive selections of the D alleles are recent and likely ongoing. The divergence between the DD-genotype profiles of schizophrenic and control samples pointed to the schizophrenia-relevance of positive selections, with the schizophrenic samples showing weakened selections compared to the controls. These DD-genotypes were previously found to increase the expression of beta(2, especially its long isoform. Electrophysiological analysis showed that this long beta(2 isoform favored by the positive selections is more sensitive than the short isoform to the inhibition of GABA(A receptor function by energy depletion. These findings represent the first demonstration of positive selection in a schizophrenia-associated gene.

Selection of suitable reference genes for RT-qPCR analyses in cyanobacteria.

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Filipe Pinto

Full Text Available Cyanobacteria are a group of photosynthetic prokaryotes that have a diverse morphology, minimal nutritional requirements and metabolic plasticity that has made them attractive organisms to use in biotechnological applications. The use of these organisms as cell factories requires the knowledge of their physiology and metabolism at a systems level. For the quantification of gene transcripts real-time quantitative polymerase chain reaction (RT-qPCR is the standard technique. However, to obtain reliable RT-qPCR results the use and validation of reference genes is mandatory. Towards this goal we have selected and analyzed twelve candidate reference genes from three morphologically distinct cyanobacteria grown under routinely used laboratory conditions. The six genes exhibiting less variation in each organism were evaluated in terms of their expression stability using geNorm, NormFinder and BestKeeper. In addition, the minimum number of reference genes required for normalization was determined. Based on the three algorithms, we provide a list of genes for cyanobacterial RT-qPCR data normalization. To our knowledge, this is the first work on the validation of reference genes for cyanobacteria constituting a valuable starting point for future works.

Inspection methods and their selection

International Nuclear Information System (INIS)

Maier, H.J.

1980-01-01

First those nondestructive testing methods, which are used in quality assurance, are to be treated, e.g. - ultrasonics - radiography - magnetic particle testing - dye penetrant testing - eddy currents, and their capabilities and limitations are shown. Second the selection of optimal testing methods under the aspect of defect recognition in different materials and components are shown. (orig./RW)

A relative variation-based method to unraveling gene regulatory networks.

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Yali Wang

Full Text Available Gene regulatory network (GRN reconstruction is essential in understanding the functioning and pathology of a biological system. Extensive models and algorithms have been developed to unravel a GRN. The DREAM project aims to clarify both advantages and disadvantages of these methods from an application viewpoint. An interesting yet surprising observation is that compared with complicated methods like those based on nonlinear differential equations, etc., methods based on a simple statistics, such as the so-called Z-score, usually perform better. A fundamental problem with the Z-score, however, is that direct and indirect regulations can not be easily distinguished. To overcome this drawback, a relative expression level variation (RELV based GRN inference algorithm is suggested in this paper, which consists of three major steps. Firstly, on the basis of wild type and single gene knockout/knockdown experimental data, the magnitude of RELV of a gene is estimated. Secondly, probability for the existence of a direct regulation from a perturbed gene to a measured gene is estimated, which is further utilized to estimate whether a gene can be regulated by other genes. Finally, the normalized RELVs are modified to make genes with an estimated zero in-degree have smaller RELVs in magnitude than the other genes, which is used afterwards in queuing possibilities of the existence of direct regulations among genes and therefore leads to an estimate on the GRN topology. This method can in principle avoid the so-called cascade errors under certain situations. Computational results with the Size 100 sub-challenges of DREAM3 and DREAM4 show that, compared with the Z-score based method, prediction performances can be substantially improved, especially the AUPR specification. Moreover, it can even outperform the best team of both DREAM3 and DREAM4. Furthermore, the high precision of the obtained most reliable predictions shows that the suggested algorithm may be

EasyClone: method for iterative chromosomal integration of multiple genes in Saccharomyces cerevisiae

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Jensen, Niels Bjerg; Strucko, Tomas; Kildegaard, Kanchana Rueksomtawin

2014-01-01

of multiple genes with an option of recycling selection markers. The vectors combine the advantage of efficient uracil excision reaction-based cloning and Cre-LoxP-mediated marker recycling system. The episomal and integrative vector sets were tested by inserting genes encoding cyan, yellow, and red...... fluorescent proteins into separate vectors and analyzing for co-expression of proteins by flow cytometry. Cells expressing genes encoding for the three fluorescent proteins from three integrations exhibited a much higher level of simultaneous expression than cells producing fluorescent proteins encoded...... on episomal plasmids, where correspondingly 95% and 6% of the cells were within a fluorescence interval of Log10 mean ± 15% for all three colors. We demonstrate that selective markers can be simultaneously removed using Cre-mediated recombination and all the integrated heterologous genes remain...

High amino acid diversity and positive selection at a putative coral immunity gene (tachylectin-2

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Hellberg Michael E

2010-05-01

Full Text Available Abstract Background Genes involved in immune functions, including pathogen recognition and the activation of innate defense pathways, are among the most genetically variable known, and the proteins that they encode are often characterized by high rates of amino acid substitutions, a hallmark of positive selection. The high levels of variation characteristic of immunity genes make them useful tools for conservation genetics. To date, highly variable immunity genes have yet to be found in corals, keystone organisms of the world's most diverse marine ecosystem, the coral reef. Here, we examine variation in and selection on a putative innate immunity gene from Oculina, a coral genus previously used as a model for studies of coral disease and bleaching. Results In a survey of 244 Oculina alleles, we find high nonsynonymous variation and a signature of positive selection, consistent with a putative role in immunity. Using computational protein structure prediction, we generate a structural model of the Oculina protein that closely matches the known structure of tachylectin-2 from the Japanese horseshoe crab (Tachypleus tridentatus, a protein with demonstrated function in microbial recognition and agglutination. We also demonstrate that at least three other genera of anthozoan cnidarians (Acropora, Montastrea and Nematostella possess proteins structurally similar to tachylectin-2. Conclusions Taken together, the evidence of high amino acid diversity, positive selection and structural correspondence to the horseshoe crab tachylectin-2 suggests that this protein is 1 part of Oculina's innate immunity repertoire, and 2 evolving adaptively, possibly under selective pressure from coral-associated microorganisms. Tachylectin-2 may serve as a candidate locus to screen coral populations for their capacity to respond adaptively to future environmental change.

A method for selecting cis-acting regulatory sequences that respond to small molecule effectors

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Allas Ülar

2010-08-01

Full Text Available Abstract Background Several cis-acting regulatory sequences functioning at the level of mRNA or nascent peptide and specifically influencing transcription or translation have been described. These regulatory elements often respond to specific chemicals. Results We have developed a method that allows us to select cis-acting regulatory sequences that respond to diverse chemicals. The method is based on the β-lactamase gene containing a random sequence inserted into the beginning of the ORF. Several rounds of selection are used to isolate sequences that suppress β-lactamase expression in response to the compound under study. We have isolated sequences that respond to erythromycin, troleandomycin, chloramphenicol, meta-toluate and homoserine lactone. By introducing synonymous and non-synonymous mutations we have shown that at least in the case of erythromycin the sequences act at the peptide level. We have also tested the cross-activities of the constructs and found that in most cases the sequences respond most strongly to the compound on which they were isolated. Conclusions Several selected peptides showed ligand-specific changes in amino acid frequencies, but no consensus motif could be identified. This is consistent with previous observations on natural cis-acting peptides, showing that it is often impossible to demonstrate a consensus. Applying the currently developed method on a larger scale, by selecting and comparing an extended set of sequences, might allow the sequence rules underlying the activity of cis-acting regulatory peptides to be identified.

Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

Science.gov (United States)

Malmendal, Anders; Sørensen, Jesper Givskov; Overgaard, Johannes; Holmstrup, Martin; Nielsen, Niels Chr.; Loeschcke, Volker

2013-05-01

We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic 1H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.

Use of the alr gene as a food-grade selection marker in lactic acid bacteria

NARCIS (Netherlands)

Bron, P.A.; Benchimol, M.G.; Lambert, J.; Palumbo, E.; Deghorain, M.; Delcour, J.; Vos, de W.M.; Kleerebezem, M.; Hols, P.

2002-01-01

Both Lactococcus lactis and Lactobacillus plantarum contain a single alr gene, encoding an alanine racemase (EC 5.1.1.1), which catalyzes the interconversion of D-alanine and L-alanine. The alr genes of these lactic acid bacteria were investigated for their application as food-grade selection

Transcriptome profile and unique genetic evolution of positively selected genes in yak lungs.

Science.gov (United States)

Lan, DaoLiang; Xiong, XianRong; Ji, WenHui; Li, Jian; Mipam, Tserang-Donko; Ai, Yi; Chai, ZhiXin

2018-04-01

The yak (Bos grunniens), which is a unique bovine breed that is distributed mainly in the Qinghai-Tibetan Plateau, is considered a good model for studying plateau adaptability in mammals. The lungs are important functional organs that enable animals to adapt to their external environment. However, the genetic mechanism underlying the adaptability of yak lungs to harsh plateau environments remains unknown. To explore the unique evolutionary process and genetic mechanism of yak adaptation to plateau environments, we performed transcriptome sequencing of yak and cattle (Bos taurus) lungs using RNA-Seq technology and a subsequent comparison analysis to identify the positively selected genes in the yak. After deep sequencing, a normal transcriptome profile of yak lung that containing a total of 16,815 expressed genes was obtained, and the characteristics of yak lungs transcriptome was described by functional analysis. Furthermore, Ka/Ks comparison statistics result showed that 39 strong positively selected genes are identified from yak lungs. Further GO and KEGG analysis was conducted for the functional annotation of these genes. The results of this study provide valuable data for further explorations of the unique evolutionary process of high-altitude hypoxia adaptation in yaks in the Tibetan Plateau and the genetic mechanism at the molecular level.

AST: an automated sequence-sampling method for improving the taxonomic diversity of gene phylogenetic trees.

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Zhou, Chan; Mao, Fenglou; Yin, Yanbin; Huang, Jinling; Gogarten, Johann Peter; Xu, Ying

2014-01-01

A challenge in phylogenetic inference of gene trees is how to properly sample a large pool of homologous sequences to derive a good representative subset of sequences. Such a need arises in various applications, e.g. when (1) accuracy-oriented phylogenetic reconstruction methods may not be able to deal with a large pool of sequences due to their high demand in computing resources; (2) applications analyzing a collection of gene trees may prefer to use trees with fewer operational taxonomic units (OTUs), for instance for the detection of horizontal gene transfer events by identifying phylogenetic conflicts; and (3) the pool of available sequences is biased towards extensively studied species. In the past, the creation of subsamples often relied on manual selection. Here we present an Automated sequence-Sampling method for improving the Taxonomic diversity of gene phylogenetic trees, AST, to obtain representative sequences that maximize the taxonomic diversity of the sampled sequences. To demonstrate the effectiveness of AST, we have tested it to solve four problems, namely, inference of the evolutionary histories of the small ribosomal subunit protein S5 of E. coli, 16 S ribosomal RNAs and glycosyl-transferase gene family 8, and a study of ancient horizontal gene transfers from bacteria to plants. Our results show that the resolution of our computational results is almost as good as that of manual inference by domain experts, hence making the tool generally useful to phylogenetic studies by non-phylogeny specialists. The program is available at http://csbl.bmb.uga.edu/~zhouchan/AST.php.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

Science.gov (United States)

Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

2016-01-01

The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis

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Chun Chen

2016-03-01

Full Text Available Abstract The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host–pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S, 28S rRNA(28S and elongation factor 1 alpha-like protein (EF1, were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae, and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189, 28S (1.414 and EF1 (3. The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis.

Reference gene selection for real-time quantitative PCR analysis of the mouse uterus in the peri-implantation period.

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Pengfei Lin

Full Text Available The study of uterine gene expression patterns is valuable for understanding the biological and molecular mechanisms that occur during embryo implantation. Real-time quantitative RT-PCR (qRT-PCR is an extremely sensitive technique that allows for the precise quantification of mRNA abundance; however, selecting stable reference genes suitable for the normalization of qRT-PCR data is required to avoid the misinterpretation of experimental results and erroneous analyses. This study employs several mouse models, including an early pregnancy, a pseudopregnancy, a delayed implantation and activation, an artificial decidualization and a hormonal treatment model; ten candidate reference genes (PPIA, RPLP0, HPRT1, GAPDH, ACTB, TBP, B2M, 18S, UBC and TUBA that are found in uterine tissues were assessed for their suitability as internal controls for relative qRT-PCR quantification. GeNorm(PLUS, NormFinder, and BestKeeper were used to evaluate these candidate reference genes, and all of these methods identified RPLP0 and GAPDH as the most stable candidates and B2M and 18S as the least stable candidates. However, when the different models were analyzed separately, the reference genes exhibited some variation in their expression levels.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

Science.gov (United States)

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Predator-induced defences in Daphnia pulex: Selection and evaluation of internal reference genes for gene expression studies with real-time PCR

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Gilbert Don

2010-06-01

Full Text Available Abstract Background The planktonic microcrustacean Daphnia pulex is among the best-studied animals in ecological, toxicological and evolutionary research. One aspect that has sustained interest in the study system is the ability of D. pulex to develop inducible defence structures when exposed to predators, such as the phantom midge larvae Chaoborus. The available draft genome sequence for D. pulex is accelerating research to identify genes that confer plastic phenotypes that are regularly cued by environmental stimuli. Yet for quantifying gene expression levels, no experimentally validated set of internal control genes exists for the accurate normalization of qRT-PCR data. Results In this study, we tested six candidate reference genes for normalizing transcription levels of D. pulex genes; alpha tubulin (aTub, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, TATA box binding protein (Tbp syntaxin 16 (Stx16, X-box binding protein 1 (Xbp1 and CAPON, a protein associated with the neuronal nitric oxide synthase, were selected on the basis of an earlier study and from microarray studies. One additional gene, a matrix metalloproteinase (MMP, was tested to validate its transcriptional response to Chaoborus, which was earlier observed in a microarray study. The transcription profiles of these seven genes were assessed by qRT-PCR from RNA of juvenile D. pulex that showed induced defences in comparison to untreated control animals. We tested the individual suitability of genes for expression normalization using the programs geNorm, NormFinder and BestKeeper. Intriguingly, Xbp1, Tbp, CAPON and Stx16 were selected as ideal reference genes. Analyses on the relative expression level using the software REST showed that both classical housekeeping candidate genes (aTub and GAPDH were significantly downregulated, whereas the MMP gene was shown to be significantly upregulated, as predicted. aTub is a particularly ill suited reference gene because five copies are

Tracking microorganisms and gene in the environment

International Nuclear Information System (INIS)

Atlas, R.M.; Sayler, G.S.

1988-01-01

Studies have been conducted to determine the sensitivities and limitations of various methods for determining the fate of genetically engineered microorganisms (GEMs) and their genes in the environment. Selective viable plate count procedures can be designed to detect the introduced organisms with high sensitivity; but they are restricted by potential mutations affecting the expression of the selective characteristic in the introduced organism, the occurrence of the particular selective characteristic in the indigenous organisms, and the need to culture the organism. The accuracy of this approach is greatly improved by colony hybridization procedures that use a specific gene probe to detect the introduced genes, but this approach is still only as sensitive as the plating procedure. Direct extraction of DNA from environmental samples, coupled with dot blot hybridization with radiolabeled probe DNA or solution hybridization, gives a high degree of both sensitivity and precision. This approach does not require culturing of the organism; and even if an introduced gene moves into a new organism or if the introduced organism is viable but nonculturable, the gene probe methods will detect the persistence of the introduced genes in the environment. Efficient direct DNA extraction methods have been developed and tested following in vitro experimental additions of GEMs to sediment and water samples

Using MACBETH method for supplier selection in manufacturing environment

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Prasad Karande

2013-04-01

Full Text Available Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.

The importance of the selection of appropriate reference genes for gene expression profiling in adrenal medulla or sympathetic ganglia of spontaneously hypertensive rat

Czech Academy of Sciences Publication Activity Database

Vavřínová, Anna; Behuliak, Michal; Zicha, Josef

2016-01-01

Roč. 65, č. 3 (2016), s. 401-411 ISSN 0862-8408 R&D Projects: GA ČR(CZ) GP14-16225P Institutional support: RVO:67985823 Keywords : adrenal medulla * gene expression profiling * reference gene selection * sympathetic nervous system Subject RIV: FA - Cardiovascular Diseases incl. Cardiotharic Surgery Impact factor: 1.461, year: 2016

Adiponectin gene polymorphism is selectively associated with the concomitant presence of metabolic syndrome and essential hypertension.

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Hsin-Bang Leu

Full Text Available OBJECTIVE: Cardiovascular risk increases with the presence of both metabolic syndrome (MetS and hypertension (HTN. Although the adiponectin (ADIPOQ gene has been reported to be involved in MetS, its association with HTN remained undetermined. This study aimed to investigate the association of ADIPOQ gene with the phenotypes of HTN and MetS. METHODS: A total of 962 participants from 302 families from the Taiwan young-onset hypertension genetic study were enrolled. Plasma adiponectin were measured, and association analysis was conducted by using GEE regression-based method. Another study, of 1448 unrelated participants, was conducted to replicate the association between ADIPOQ gene and variable phenotypes of MetS with or without HTN. RESULTS: Among 962 subjects from family samples, the lowest plasma adiponectin value was observed in MetS with HTN component (9.3±0.47 µg/ml compared with hypertensives (13.4±0.74 µg /ml or MetS without HTN (11.9±0.60 µg/ml, P<0.05. The SNP rs1501299 (G276T in ADIPOQ gene was found associated with the presence of HTN in MetS (odds ratio for GG+GT vs. TT = 2.46; 95% CI: 1.14-5.3, p = 0.02, but not rs2241766 (T45G. No association of ADIPOQ gene with HTN alone or MetS without HTN was observed. The significant association of the SNP rs1501299 (G276T with the phenotype of presence of HTN in MetS was confirmed (odds ratio for GG+GT vs. TT = 2.15; 95% CI: 1.1-4.3 in the replication study. CONCLUSIONS: ADIPOQ genetic variants were selectively and specifically associated with the concomitant presence of MetS and HTN, suggesting potential genetic linkage between MetS and HTN.

Selectable antibiotic resistance marker gene-free transgenic rice harbouring the garlic leaf lectin gene exhibits resistance to sap-sucking planthoppers.