Selection of reliable reference genes for gene expression studies in peach using real-time PCR

Background  

RT-qPCR is a preferred method for rapid and reliable quantification of gene expression studies. Appropriate application of RT-qPCR in such studies requires the use of reference gene(s) as an internal control to normalize mRNA levels between different samples for an exact comparison of gene expression level. However, recent studies have shown that no single reference gene is universal for all experiments. Thus, the identification of high quality reference gene(s) is of paramount importance for the interpretation of data generated by RT-qPCR. Only a few studies on reference genes have been done in plants and none in peach (Prunus persica L. Batsch). Therefore, the present study was conducted to identify suitable reference gene(s) for normalization of gene expression in peach.     

Chromosome-specific spatial periodicities in gene expression revealed by spectral analysis

Recent years have seen an unprecedented surge of research activity in studies of gene expression. This extensive work, however, has been almost uniformly focused on genome-wide gene expression and has largely ignored the fundamental fact that every gene has a specific chromosome location. We propose a novel method of spectral analysis for detecting hidden periodicities in gene expression signals ordered along the length of each chromosome. Using this method, we have discovered that each chromosome in rodents and humans has a unique periodic pattern of gene expression. The uncovered spatial periodicities in gene expression are tissue-specific in the sense that the largest differences in humans were observed between two normal tissues (brain and mammary gland) as well as between their tumor counterparts (glioma and breast cancer). The smallest differences resulted from the comparison of tumors (glioma and breast cancer) with their normal counterparts. All such effects do not extend to all chromosomes but are limited to only some of them. The estimated periods and amplitudes are identical for the genes located on the positive and negative DNA strands. While precise molecular mechanisms of chromosome-specific periodicities in gene expression have yet to be unraveled, their universal presence in different tissues adds another dimension to the current understanding of the genome organization.     

Identifying consensus disease pathways in Parkinson's disease using an integrative systems biology approach

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p<0.01) from a joint analysis of three existing PD GWAS were identified and each assigned to a gene. For gene expression, rather than the traditional comparison of one anatomical region between sets of patients and controls, we identified differentially expressed genes between adjacent Braak regions in each individual and adjusted using average control expression profiles. Over-represented pathways were calculated using a hyper-geometric statistical comparison. An integrated, systems meta-analysis of the over-represented pathways combined the expression and GWAS results using a Fisher's combined probability test. Four of the top seven pathways from each approach were identical. The top three pathways in the meta-analysis, with their corrected p-values, were axonal guidance (p = 2.8E-07), focal adhesion (p = 7.7E-06) and calcium signaling (p = 2.9E-05). These results support that a systems biology (pathway) approach will provide additional insight into the genetic etiology of PD and that these pathways have both biological and statistical support to be important in PD.     

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n 相似文献   

A new method to transfect the hypoblast of the chick embryo reveals conservation of the regulation of an Otx2 enhancer between mouse and chick extraembryonic endoderm

Background

The mouse anterior visceral endoderm (AVE) and the chick hypoblast are thought to have homologous roles in the early stages of neural induction and primitive streak formation. In mouse, many regulatory elements directing gene expression to the AVE have been identified. However, there is no technique to introduce DNA into the chick hypoblast that would enable a comparison of their activity and this has hampered a direct comparison of the regulation of gene expression in the mouse and chick extraembryonic endoderm.

Results

Here we describe a new method to introduce DNA into the chick hypoblast, using lipofectamine-mediated transfection. We show that the hypoblast can be easily transfected and that it starts to express a luciferase reporter within 2 hours of transfection. The validity of technique is tested by following the movement and fate of hypoblast cells, which reveals their translocation to the anterior germinal crescent. We then introduce a vector containing GFP driven by the mouse VEcis-Otx2 enhancer (which directs gene expression to the mouse AVE) and we detect activity in the hypoblast.

Conclusion

The new technique for delivering expression constructs to the chick hypoblast will enable studies on gene activity and regulation to be performed in this tissue, which has proved difficult to transfect by electroporation. Our findings also reveal that regulatory elements that direct gene expression to the mouse AVE are active in chick hypoblast, supporting the idea that these two tissues have homologous functions.     

非编码长链RNA与基因表达调控

近年来,在小鼠全长cDNA文库大规模测序中发现一类新的转录物——非编码长链RNA(long noncoding RNA,lncRNA),引起了科学界的关注.lncRNA长度大于200个核苷酸,无蛋白质编码功能,在真核细胞基因组中被普遍转录.lncRNA种类繁多,数量庞大,占哺乳动物基因组转录物的绝大部分.相对于研究较多的非编码小RNA,lncRNA的功能目前尚不完全清楚.但越来越多的研究发现,lncRNA在多个水平调控基因的表达,在胚胎发育、物种进化、细胞分化和某些疾病如神经退行性疾病及肿瘤的发生过程中起着重要作用.本文在简要介绍lncRNA基本概念的基础上,结合当前研究成果,就lncRNA在转录水平、转录后水平和表观遗传水平调控基因表达的机制作一综述.     

Microarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

Background  

Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods.     

Transcriptional signatures of normal human mammary epithelial cells in response to benzo[a]pyrene exposure: a comparison of three microarray platforms

Microarrays are used to study gene expression in a variety of biological systems. A number of different platforms have been developed, but few studies exist that have directly compared the performance of one platform with another. The goal of this study was to determine array variation by analyzing the same RNA samples with three different array platforms. Using gene expression responses to benzo[a]pyrene exposure in normal human mammary epithelial cells (NHMECs), we compared the results of gene expression profiling using three microarray platforms: photolithographic oligonucleotide arrays (Affymetrix), spotted oligonucleotide arrays (Amersham), and spotted cDNA arrays (NCI). While most previous reports comparing microarrays have analyzed pre-existing data from different platforms, this comparison study used the same sample assayed on all three platforms, allowing for analysis of variation from each array platform. In general, poor correlation was found with corresponding measurements from each platform. Each platform yielded different gene expression profiles, suggesting that while microarray analysis is a useful discovery tool, further validation is needed to extrapolate results for broad use of the data. Also, microarray variability needs to be taken into consideration, not only in the data analysis but also in specific probe selection for each array type.     

Identification and embryonic expression of Wnt2, Wnt4, Wnt5 and Wnt9 in the millipede Glomeris marginata (Myriapoda: Diplopoda)

The Wnt genes encode secreted glycoprotein ligands that are key players during animal development. Previous studies revealed the presence of 12 classes of Wnt genes in protostomes, although lineage specific losses of Wnt genes are common. So far, the gene expression profile of only two complete sets of arthropod Wnt genes has been studied; these are the Wnt genes of the fly Drosophila melanogaster and the beetle Tribolium castaneum. Insects, however, do not represent good models for the understanding of Wnt gene evolution because several Wnt genes have been lost in the lineage leading to the insects, or within the different orders of insects. Comparative gene expression data from non-insect arthropods are rare and restricted to a subset of Wnt genes.This study aims to fill this gap and describes four newly detected Wnt genes from the millipede Glomeris marginata (Myriapoda: Diplopoda). Together with previous studies, now 11 Glomeris Wnt genes have been isolated and their expression has been studied. The only predicted but hitherto undetected Wnt gene is Wnt10. The new data provide a platform for the comparison of Wnt gene expression patterns in arthropods and reveal conserved as well as diverged aspects of Wnt gene expression in Arthropoda. Prominent expression of Wnt4 in dorsal tissue implies a role in dorsal segmentation and suggests that Wnt4 may be the predicted substitute for the previously reported missing expression of wg/Wnt1 in dorsal tissue.     

Regression approaches for microarray data analysis.

A variety of new procedures have been devised to handle the two-sample comparison (e.g., tumor versus normal tissue) of gene expression values as measured with microarrays. Such new methods are required in part because of some defining characteristics of microarray-based studies: (i) the very large number of genes contributing expression measures which far exceeds the number of samples (observations) available and (ii) the fact that by virtue of pathway/network relationships, the gene expression measures tend to be highly correlated. These concerns are exacerbated in the regression setting, where the objective is to relate gene expression, simultaneously for multiple genes, to some external outcome or phenotype. Correspondingly, several methods have been recently proposed for addressing these issues. We briefly critique some of these methods prior to a detailed evaluation of gene harvesting. This reveals that gene harvesting, without additional constraints, can yield artifactual solutions. Results obtained employing such constraints motivate the use of regularized regression procedures such as the lasso, least angle regression, and support vector machines. Model selection and solution multiplicity issues are also discussed. The methods are evaluated using a microarray-based study of cardiomyopathy in transgenic mice.