DNA array profiling of gene expression changes during maize embryo development

We are using DNA microarray-based gene expression profiling to classify temporal patterns of gene expression during the development of maize embryos, to understand mRNA-level control of embryogenesis and to dissect metabolic pathways and their interactions in the maize embryo. Genes involved in carbohydrate, fatty acid, and amino acid metabolism, the tricarboxylic acid (TCA) cycle, glycolysis, the pentose phosphate pathway, embryogenesis, membrane transport, signal transduction, cofactor biosynthesis, photosynthesis, oxidative phosphorylation and electron transfer, as well as 600 random complementary DNA (cDNA) clones from maize embryos, were arrayed on glass slides. DNA arrays were hybridized with fluorescent dye-labeled cDNA probes synthesized from kernel and embryo poly(A)⁺RNA from different stages of maize seed development. Several characteristic developmental patterns of expression were identified and correlated with gene function. Patterns of coordinated gene expression in the TCA cycle and glycolysis were analyzed in detail. The steady state level of poly(A)⁺ RNA for many genes varies dramatically during maize embryo development. Expression patterns of genes coding for enzymes of fatty acid biosynthesis and glycolysis are coordinately regulated during development. Genes of unknown function may by assigned a hypothetical role based on their patterns of expression resembling well characterized genes. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s10142-002-0046-6. Electronic Publication     

Gene Expression of Tyrosine Hydroxylase in the Developing Fetal Brain

Tyrosine hydroxylase, aromatic L-amino-acid decarboxylase, and dopamine beta-hydroxylase activities were studied in the developing fetal rat brain. A delay of 2-3 days between the detection of the tyrosine hydroxylase and the aromatic L-amino-acid decarboxylase and dopamine beta-hydroxylase activities was observed. For this reason, the expression of tyrosine hydroxylase mRNA was studied. Tyrosine hydroxylase mRNA was visualized in the whole brain from 13 days of gestation, but the largest increase of the expression was observed in the hypothalamus. These results are discussed in terms of the relative gene expressions of the three enzymes involved in the biosynthesis of catecholamines and phenolamines in nervous tissues.     

Comparative expression analysis of four breast cancer subtypes versus matched normal tissue from the same patients

Gene expression studies have been widely used in an effort to identify signatures that can predict clinical progression of cancer. In this study we focused instead on identifying gene expression differences between breast tumors and adjacent normal tissue, and between different subtypes of tumor classified by clinical marker status. We have collected a set of 20 breast cancer tissues, matched with the adjacent pathologically normal tissue from the same patient. The cancer samples representing each subtype of breast cancer identified by estrogen receptor ER(+/-) and Her2(+/-) status and divided into four subgroups (ER+/Her2+, ER+/Her2-, ER-/Her2+, and ER-/Her2-) were hybridized on Affymetrix HG-133 Plus 2.0 microarrays. By comparing cancer samples with their matched normal controls we have identified 3537 overall differentially expressed genes using data analysis methods from Bioconductor. When we looked at the genes in common of the four subgroups, we found 151 regulated genes, some of them encoding known targets for breast cancer treatment. Unique genes in the four subgroups instead suggested gene regulation dependent on the ER/Her2 markers selection. In conclusion, the results indicate that microarray studies using robust analysis of matched tumor and normal samples from the same patients can be used to identify genes differentially expressed in breast cancer tumor subtypes even when small numbers of samples are considered and can further elucidate molecular features of breast cancer.     

基因芯片在衣原体研究中的应用

基因芯片又称为DNA微阵列,是指将大量核酸片段以预先设计的方式固定在载体上组成密集分子阵列,与荧光素或其他方式标记的样品进行杂交,通过检测杂交信号的强弱来判断样品中有无靶分子以及对靶分子进行定量,是一种研究生物大分子功能的新技术。在衣原体研究方面,基因芯片主要应用于衣原体的检测与分型、感染机制的研究、特定基因作用分析、毒力及耐药基因的筛选等。     

cRNA target preparation for microarrays: comparison of gene expression profiles generated with different amplification procedures

Microarray technology has become a standard tool for generation of gene expression profiles to explore human disease processes. Being able to start from minute amounts of RNA extends the fields of application to core needle biopsies, laser capture microdissected cells, and flow-sorted cells. Several RNA amplification methods have been developed, but no extensive comparability and concordance studies of gene expression profiles are available. Different amplification methods may produce differences in gene expression patterns. Therefore, we compared profiles processed by a standard microarray protocol with three different types of RNA amplification: (i) two rounds of linear target amplification, (ii) random amplification, and (iii) amplification based on a template switching mechanism. The latter two methods accomplish target amplification in a nonlinear way using PCR technology. Starting from as little as 50 ng of total RNA, the yield of labeled cRNA was sufficient for hybridization to Affymetrix HG-U133A GeneChip array using the respective methods. Replicate experiments were highly reproducible for each method. In comparison with the standard protocol, all three approaches are less sensitive and introduced a minor but clearly detectable bias of the detection call. In conclusion, the three amplification protocols used are applicable for GeneChip analysis of small tissue samples.     

对与小鼠胚胎发育相关的印记基因Mcts2的研究

目的：对与小鼠胚胎发育相关的印记基因Mcts2表达模式及生物学功能做初步的分析。方法：采用切片原位杂交,全胚胎原位杂交,Northern blot和real-time PCR对该基因进行了表达谱的分析。结果：切片原位杂交结果显示Mcts2基因在E13.5和E15.5胚胎中的脑、舌、心脏、肺脏、肝脏、肾脏等重要脏器中都有普遍表达。全胚胎原位杂交结果显示Mcts2基因在E10.5胚胎中的前脑、前肢、尾芽中出现较强的信号,其他部位信号较弱。Northern和Real-time PCR实验分析了Mcts2基因在E12.5,E15.5,E18.5胚胎和新生小鼠的脑、心脏、肺脏、肝脏和肾脏中的表达谱,发现Mcts2基因在这几个主要发育时期都有普遍表达,在E15.5胚胎中表达信号最为强烈。结论：Mcts2基因在小鼠胚胎的发育的各主要时期的重要脏器中都有普遍的表达,提示该基因在小鼠胚胎发育过程中起到了重要的作用。     

Male rats with the testicular feminization mutation of the androgen receptor display elevated anxiety-related behavior and corticosterone response to mild stress

Testosterone influences the hypothalamic–pituitary–adrenal axis, anxiety-related behavior, and sensorimotor gating in rodents, but little is known about the role of the androgen receptor (AR) in mediating these influences. We compared levels of the stress hormone corticosterone at baseline and following exposure to a novel object in an open field in wild type (wt) male and female rats, and male rats with the testicular feminization mutation (Tfm) of the AR, which disables its function. Basal corticosterone was equivalent in all groups, but exposure to a novel object in an open field elicited a greater increase in corticosterone in Tfm males and wt females than in wt males. Tfm males also showed increased behavioral indices of anxiety compared to wt males and females in the test. Analysis of the immediate early gene c-Fos expression after exposure to a novel object revealed greater activation in Tfm males than wt males in some regions (medial preoptic area) and lesser activation in others (dentate gyrus, posterodorsal medial amygdala). No differences were found in a measure of sensorimotor gating (prepulse inhibition of the acoustic startle response), although Tfm males had an increased acoustic startle response compared to wt males and females. These findings demonstrate that ARs play a role in regulating anxiety-related behaviors, as well as corticosterone responses and neural activation following exposure to a mild stressor in rats.     

Global analysis of G-protein-coupled receptor signaling in human tissues

The G-protein-coupled receptor (GPCR) family mediates a host of cell–cell communications upon activation by diverse ligands. Numerous GPCRs have been shown to display anatomically selective patterns of gene expression, however, our understanding of the complexity of GPCR signaling within human tissues remains unclear. In an effort to characterize global patterns of GPCR signaling in the human body, microarray analysis was performed on a large panel of tissues to monitor the gene expression levels of the receptors as well as related signaling and regulatory molecules. Analysis of the data revealed complex signaling networks in many tissue types, with tissue-specific patterns of gene expression observed for the majority of the receptors and a number of components and regulators of GPCR signaling.     

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation

Background

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study.

Results

Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this “gold-standard” comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues.

Conclusions

Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-649) contains supplementary material, which is available to authorized users.