Development of a RNA extraction method from milk for gene expression study in the mammary gland of sheep

The aim of the study was to develop a reliable method for the RNA extraction from milk of Sarda sheep breed and to highlight if the extracted RNA can be used for expression study on mammary genes involved in milk fat synthesis using RT-qPCR. The main result is that a sample of 150 ml of milk provides an optimal amount of RNA (73.5 μg/ml). The highest RNA concentration has been found in the samples analysed within 4 h after collection. The RNA extracted was positively correlated to the number of somatic cells (P < 0.001). The efficiency of the extraction method was confirmed by the results obtained from qPCR which showed a Ct value, for SREBPF1 gene of 26.8 ± 0.15. This research demonstrated that the high-quality of the RNA obtained is suited to use for studies of mammary genes expression in sheep, avoiding any damage caused by mammary gland biopsy.     

A phylogenetic method for detecting positive epistasis in gene sequences and its application to RNA virus evolution

RNA virus genomes are compact, often containing multiple overlapping reading frames and functional secondary structure. Consequently, it is thought that evolutionary interactions between nucleotide sites are commonplace in the genomes of these infectious agents. However, the role of epistasis in natural populations of RNA viruses remains unclear. To investigate the pervasiveness of epistasis in RNA viruses, we used a parsimony-based computational method to identify pairs of co-occurring mutations along phylogenies of 177 RNA virus genes. This analysis revealed widespread evidence for positive epistatic interactions at both synonymous and nonsynonymous nucleotide sites and in both clonal and recombining viruses, with the majority of these interactions spanning very short sequence regions. These findings have important implications for understanding the key aspects of RNA virus evolution, including the dynamics of adaptation. Additionally, many comparative analyses that utilize the phylogenetic relationships among gene sequences assume that mutations represent independent, uncorrelated events. Our results show that this assumption may often be invalid.     

A method for aligning RNA secondary structures and its application to RNA motif detection

Background  

Alignment of RNA secondary structures is important in studying functional RNA motifs. In recent years, much progress has been made in RNA motif finding and structure alignment. However, existing tools either require a large number of prealigned structures or suffer from high time complexities. This makes it difficult for the tools to process RNAs whose prealigned structures are unavailable or process very large RNA structure databases.     

Gene suture--a novel method for intramuscular gene transfer and its application in hypertension therapy

In this report, reporter gene beta-galactosidase (LacZ) was chosen to compare two different intramuscular gene transfer methods, direct injection and gene suture. Evidence showed that gene suture can produce a higher foreign gene express efficiency in skeletal muscle compared with the direct injection method. The highly efficient eukaryotic expressing vectors of human atrial natriuretic factor (ANF) were constructed (pcD2/pAdVAntage/hANF and pcDNA3/hANF), and in vivo ANF gene delivery was performed by intramuscular gene suture. The effects of ANF gene transfer on blood pressure and renal sodium and water excretion were studied in three models of hypertensive animals. Results showed that a marked decrease of mean arterial pressure (MAP) and a significant increase of urine volume and urinary sodium excretion was produced in rats receiving the hANF construct due to the local expression of ANF and its secretion into plasma. Taken together, these results indicate that gene suture may represent a novel gene delivery modality in gene therapy.     

A method for discovering common patterns from two RNA secondary structures and its application to structural repeat detection

We propose an ab initio method, named DiscoverR, for finding common patterns from two RNA secondary structures. The method works by representing RNA secondary structures as ordered labeled trees and performs tree pattern discovery using an efficient dynamic programming algorithm. DiscoverR is able to identify and extract the largest common substructures from two RNA molecules having different sizes without prior knowledge of the locations and topologies of these substructures. We also extend DiscoverR to find repeated regions in an RNA secondary structure, and apply this extended method to detect structural repeats in the 3'-untranslated region of a protein kinase gene. We describe the biological significance of a repeated hairpin found by our method, demonstrating the usefulness of the method. DiscoverR is implemented in Java; a jar file including the source code of the program is available for download at http://bioinformatics.njit.edu/DiscoverR.     

Validation of extraction methods for total RNA and miRNA from bovine blood prior to quantitative gene expression analyses

The benefit and precision of blood diagnosis by quantitative real-time PCR (qPCR) is limited by sampling procedures and RNA extraction methods. We have compared five different RNA extraction protocols from bovine blood regarding RNA and miRNA yield, quality, and most reproducible data in the qRT-PCR with the lowest point of quantification. Convincing results in terms of highest quantity, quality, and best performance for mRNA qPCR were obtained by leukocyte extraction following blood lysis as well as extraction of PAXgene stabilized blood. The best microRNA qPCR results were obtained for samples extracted by the leukocyte extraction method.     

PathAct: a novel method for pathway analysis using gene expression profiles

We developed PathAct, a novel method for pathway analysis to investigate the biological and clinical implications of the gene expression profiles. The advantage of PathAct in comparison with the conventional pathway analysis methods is that it can estimate pathway activity levels for individual patient quantitatively in the form of a pathway-by-sample matrix. This matrix can be used for further analysis such as hierarchical clustering and other analysis methods. To evaluate the feasibility of PathAct, comparison with frequently used gene-enrichment analysis methods was conducted using two public microarray datasets. The dataset #1 was that of breast cancer patients, and we investigated pathways associated with triple-negative breast cancer by PathAct, compared with those obtained by gene set enrichment analysis (GSEA). The dataset #2 was another breast cancer dataset with disease-free survival (DFS) of each patient. Contribution by each pathway to prognosis was investigated by our method as well as the Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis. In the dataset #1, four out of the six pathways that satisfied p < 0.05 and FDR < 0.30 by GSEA were also included in those obtained by the PathAct method. For the dataset #2, two pathways (“Cell Cycle” and “DNA replication”) out of four pathways by PathAct were commonly identified by DAVID analysis. Thus, we confirmed a good degree of agreement among PathAct and conventional methods. Moreover, several applications of further statistical analyses such as hierarchical cluster analysis by pathway activity, correlation analysis and survival analysis between pathways were conducted.     

A novel magnetic resonance-based method to measure gene expression in living cells

In unicellular and multicellular eukaryotes, elaborate gene regulatory mechanisms facilitate a broad range of biological processes from cell division to morphological differentiation. In order to fully understand the gene regulatory networks involved in these biological processes, the spatial and temporal patterns of expression of many thousands of genes will need to be determined in real time in living organisms. Currently available techniques are not sufficient to achieve this goal; however, novel methods based on magnetic resonance (MR) imaging may be particularly useful for sensitive detection of gene expression in opaque tissues. This report describes a novel reporter gene system that monitors gene expression dynamically and quantitatively, in yeast cells, by measuring the accumulation of inorganic polyphosphate (polyP) using MR spectroscopy (MRS) or MR spectroscopic imaging (MRI). Because this system is completely non-invasive and does not require exogenous substrates, it is a powerful tool for studying gene expression in multicellular organisms, as well.     

A novel method for quantifying overdispersion in count data and its application to farmland birds

The statistical modelling of count data permeates the discipline of ecology. Such data often exhibit overdispersion compared with a standard Poisson distribution, so that the variance of the counts is greater than that of the mean. Whereas modelling to reveal the effects of explanatory variables on the mean is commonplace, overdispersion is generally regarded as a nuisance parameter to be accounted for and subsequently ignored. Instead, we propose a method that models the overdispersion as a biologically interesting property of a data set and show how novel inference is provided as a result. We adapted the double hierarchical generalized linear model approach to create an easily extendible model structure that quantifies the influence of explanatory variables on the overdispersion of count data, and apply it to farmland birds. These data were from a study within Irish agricultural ecosystems, in which total bird species abundance and the abundance of farmland indicator species were compared on dairy and non‐dairy farms in the winter and breeding seasons. In general, overdispersion in bird counts was greater on dairy farms than on non‐dairy farms, and for total bird numbers, overdispersion was greatest on dairy farms in winter. Our code is fitted using the Bayesian package Rstan, and we make all code and data available in a GitHub repository. Within a Bayesian framework, this approach facilitates a meaningful quantification of the effects of categorical explanatory variables on any response variable with a tendency to overdispersion that has a meaningful biological or ecological explanation.     

A reliable method for extraction of RNA from various conifer tissues

Summary A simple and efficient procedure suitable for extraction of high-quality RNA from cultured conifer tissues, somatic embryos, zygotic embryos, needles, stem and root tissues was developed. It produced from 100 g up to 700 g total RNA per gram tissue dependent on the types of tissues used. RNA quality was estimated by spectrophotometry, agarose gel electrophoresis, in vitro translation of mRNA, cDNA synthesis and Northern blot analysis. The method also worked well with Arabidopsis thaliana and tobacco tissues.Abbreviations CTAB cetyltrimethylammonium bromide - DEPC diethylpyrocarbonate - PVP polyvinylpyrrolidone - SDS-PAGE sodium dodecyl sulphate-polyacrylamide gel electrophoresis     

A moment-based method for estimating the proportion of true null hypotheses and its application to microarray gene expression data

Due to advances in experimental technologies, it is feasible to collect measurements for a large number of variables. When these variables are simultaneously screened by a statistical test, it is necessary to consider the adjustment for multiple hypothesis testing. The false discovery rate has been proposed and widely used to address this issue. A related problem is the estimation of the proportion of true null hypotheses. The long-standing difficulty to this problem is the identifiability of the nonparametric model. In this study, we propose a moment-based method coupled with sample splitting for estimating this proportion. If the p values from the alternative hypothesis are homogeneously distributed, then the proposed method will solve the identifiability and give its optimal performances. When the p values from the alternative hypothesis are heterogeneously distributed, we propose to approximate this mixture distribution so that the identifiability can be achieved. Theoretical aspects of the approximation error are discussed. The proposed estimation method is completely nonparametric and simple with an explicit formula. Simulation studies show the favorable performances of the proposed method when it is compared to the other existing methods. Two microarray gene expression data sets are considered for applications.     

A novel method to isolate cells with conditional gene expression using fluorescence activated cell sorting.

An inducible expression system using control elements of the tetracycline resistance operon has recently shown promise for conditional gene expression of any gene of interest. However, intensive screening of multiple independent clones is often required to find cell lines with optimal induction characteristics. By coupling expression of the gene of interest with a fluorescent marker, we have developed a novel fluorescence activated cell sorting (FACS) based strategy to isolate cells with desirable expression characteristics, thus alleviating the laborious isolation and analysis of multiple independent clones.