Comparison of normalization methods with microRNA microarray

MicroRNAs (miRNAs) are a group of RNAs that play important roles in regulating gene expression and protein translation. In a previous study, we established an oligonucleotide microarray platform to detect miRNA expression. Because it contained only hundreds of probes, data normalization was difficult. In this study, the microarray data for eight miRNAs extracted from inflamed rat dorsal root ganglion (DRG) tissue were normalized using 15 methods and compared with the results of real-time polymerase chain reaction. It was found that the miRNA microarray data normalized by the print-tip loess method were the most consistent with results from real-time polymerase chain reaction. Moreover, the same pattern was also observed in 14 different types of rat tissue. This study compares a variety of normalization methods and will be helpful in the preprocessing of miRNA microarray data.     

Rapid divergence in expression between duplicate genes inferred from microarray data

For more than 30 years, expression divergence has been considered as a major reason for retaining duplicated genes in a genome, but how often and how fast duplicate genes diverge in expression has not been studied at the genomic level. Using yeast microarray data, we show that expression divergence between duplicate genes is significantly correlated with their synonymous divergence (K_S) and also with their nonsynonymous divergence (K_A) if K_A ≤ 0.3. Thus, expression divergence increases with evolutionary time, and K_A is initially coupled with expression divergence. More interestingly, a large proportion of duplicate genes have diverged quickly in expression and the vast majority of gene pairs eventually become divergent in expression. Indeed, more than 40% of gene pairs show expression divergence even when K_S is ≤ 0.10, and this proportion becomes >80% for K_S > 1.5. Only a small fraction of ancient gene pairs do not show expression divergence.     

Comprehensive DNA microarray expression profiles of tumors in tenascin-C-knockout mice

Tenascin-C (TNC), an extracellular matrix glycoprotein, plays a pivotal role in tumor growth. However, the mechanism whereby TNC affects tumor biology remains unclear. To investigate the exact role of TNC in primary tumor growth, a mouse mammary tumor cell line, GLMT1, was first developed. Subsequently, global gene expression in GLMT1-derived tumors was compared between wild-type (WT) and TNC-knockout (TNKO) mice. Tumors in WT mice were significantly larger than those in TNKO mice. DNA microarray analysis revealed 447 up and 667 downregulated in the tumors inoculated into TNKO mice as compared to tumors in WT mice. Validation by quantitative gene expression analysis showed that Tnc, Cxcl1, Cxcl2, and Cxcr2 were significantly upregulated in WT mice. We hypothesize that TNC stimulates the CXCL1/2-CXCR2 pathway involved in cancer cell proliferation.     

The microarray analysis for gene expression in haploids and diploids derived from twin-seedling rice

In this study, microarray technique was employed to analyze the gene expression at the RNA level between haploids and corresponding diploids derived from a rice twin-seedling line SARII-628. Differ- ent degrees of expression variations were observed in the plant after haploidization. The main results are as follows: (1) after haploidization, the ratio of the sensitive loci was 2.47% of the total loci designed on chip. Those loci were randomly distributed on the 12 pairs of rice chromosomes and the activated loci were more than the silenced ones. (2) Gene clusters on chromosome were observed for 33 se- quences. (3) GoPipe function classification for 575 sensitive loci revealed an involvement in the bio- logical process, cell component and molecular function. (4) RT-PCR generally validated the result from microarray with a coincidence rate of 83.78%. And for the randomly-selected activated or silenced loci in chip analysis, the coincidence rate was up to 91.86%.     

Enhanced quantile normalization of microarray data to reduce loss of information in gene expression profiles

In microarray experiments, removal of systematic variations resulting from array preparation or sample hybridization conditions is crucial to ensure sensible results from the ensuing data analysis. For example, quantile normalization is routinely used in the treatment of both oligonucleotide and cDNA microarray data, even though there might be some loss of information in the normalization process. We recognize that the ideal normalization, if it ever exists, would aim to keep the maximal amount of gene profile information with the lowest possible noise. With this objective in mind, we propose a valuable enhancement to quantile normalization, and demonstrate through three Affymetrix experiments that the enhanced normalization can result in better performance in detecting and ranking differentially expressed genes across experimental conditions.     

微阵列数据揭示基因在癌样本中广泛表达

癌的发生与发展过程涉及大量基因的异常表达。在目前基因表达谱分析中采用的标准化方法通常假设在疾病中差异表达的基因的比例很小并且差异上、下调的比例大致相等。这个被研究者所广泛采用的标准化的前提假设尚未被充分地论证过。通过分析胰腺癌的两套表达谱数据,我们发现在胰腺癌样本中基因表达的中值显著高于正常样本,提示传统的标准化假设并不适用于胰腺癌表达谱数据。采用标准化数据会导致错误地判断大量的差异下调的基因并失查许多差异上调的基因。采用原始数据分析发现在胰腺癌中的基因表达有广泛上调的特征,为深入研究胰腺癌的发生和发展机制提供了新线索。     

Differential expression profiles of miRNA in the serum of sarcopenic rats

As the geriatric population and life expectancy increase, the interest in preventing geriatric diseases, such as sarcopenia, is increasing. However, the causes of sarcopenia are unclear, and current diagnostic methods for sarcopenia are unreliable. We hypothesized that the changes in the expression of certain miRNAs may be associated with the pathophysiology of sarcopenia. Herein, we analyzed the miRNA expression profiles in the blood of young (3-months-old) healthy rats, old sarcopenic (17-months-old) rats, and age-matched (17-months-old) control rats. The changes in miRNA expression levels were analyzed using Bowtie 2 software. A total of 523 miRNAs were detected in the rat serum. Using scatter plots and clustering heatmap data, we found 130 miRNAs that were differentially expressed in sarcopenic rats (>2-fold change) compared to the expression in young healthy and age-matched control rats. With a threshold of >5-fold change, we identified 14 upregulated miRNAs, including rno-miR-133b-3p, rno-miR-133a-3p, rno-miR-133c, rno-miR-208a-3p, and rno-miR434-5p among others in the serum of sarcopenic rats. A protein network map based on these 14 miRNAs identified the genes involved in skeletal muscle differentiation, among which Notch1, Egr2, and Myocd represented major nodes. The data obtained in this study are potentially useful for the early diagnosis of sarcopenia and for the identification of novel therapeutic targets for the treatment and/or prevention of sarcopenia.     

cDNA芯片阳性对照的制备及在芯片敏感性分析中的应用

cDNA芯片是一种高通量基因表达谱分析技术,在生理病理条件下细胞基因表达谱分析,新基因发现和功能研究等方面具有广阔应用前景。CDNA芯片阳性对照的选取以及CDNA芯片检测敏感性是芯片成功应用的关键问题之一。以在系统发育上与人类基因同源性小的荧火虫荧光素酶基因材料,制备了用于人类和其他动物基因表达谱CDNA芯片的通用型阳性对照探针和相应的mRNA参照物,经反转录对mRNA参照物进行Cy3荧光标记并与DNA芯片杂交后发现,mRNA参照物能特异性地与荧光酶基因cDNA片断杂交,而与人β-肌动蛋白基因,人G3PDH基因以及λDNA/HINDⅢ无杂交反应。把mRNA参照物以不同比例加入HepG2总RNA中,以反转录荧光标记后与CDNA芯片杂交,结果发现当总RNA中的MRNA含量为1/10^4稀释（即mRNA分子个数约为10^8个）时,CDNA芯片基本检测不出mRNA标记产物的杂交信号。而且,cDNA芯片检测的信号强度与芯片上固定的探针浓度密切相关,当探针浓度为2g/L时,杂交信号最强,随着探针浓度下降芯片的杂交信号趋于减弱。CDNA芯片通用型阳性参照物的制备以及应用于CDNA芯片检测敏感性研究为CDNA芯片应用于人和其他动物基因表达谱高通量分析和新基因功能研究提供了技术基础和理论依据。     

The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease

Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether miRNA microarrays are suited or not to accurately detecting global miRNA decreases seen in cancers. In this work, we analyzed the miRNA profiles of samples with global miRNA decreases using Affymetrix miRNA microarrays following the inducible genetic deletion of Dicer1. Surprisingly, up to a third of deregulated miRNAs identified upon Dicer1 depletion were found to be up-regulated following standard robust multichip average (RMA) background correction and quantile normalization, indicative of normalization bias. Our comparisons of five preprocess steps performed at the probe level demonstrated that the use of cyclic loess relying on non-miRNA small RNAs present on the Affymetrix platform significantly improved specificity and sensitivity of detection of decreased miRNAs. These findings were validated in samples from patients with prostate cancer, where conjugation of robust normal-exponential background correction with cyclic loess normalization and array weights correctly identified the greatest number of decreased miRNAs, and the lowest amount of false-positive up-regulated miRNAs. These findings highlight the importance of miRNA microarray normalization for the detection of miRNAs that are truly differentially expressed and suggest that the use of cyclic loess based on non-miRNA small RNAs can help to improve the sensitivity and specificity of miRNA profiling in cancer samples with global miRNA decrease.     

基因表达数据聚类分析技术及其软件工具

随着DNA芯片技术的广泛应用,基因表达数据分析已成为生命科学的研究热点之一。概述基因表达聚类技术类型、算法分类与特点、结果可视化与注释;阐述一些流行的和新型的算法;介绍17个最新相关软件包和在线web服务工具;并说明软件工具的研究趋向。     

Analysis of extracellular vesicle miRNA profiles in heart failure

Extracellular vesicles (EVs) have recently emerged as an important carrier for various genetic materials including microRNAs (miRs). Growing evidences suggested that several miRs transported by EVs were particularly involved in modulating cardiac function. However, it has remained unclear what miRs are enriched in EVs and play an important role in the pathological condition. Therefore, we established the miR expression profiles in EVs from murine normal and failing hearts and consecutively identified substantially altered miRs. In addition, we have performed bioinformatics approach to predict potential cardiac outcomes through the identification of miR targets. Conclusively, we observed approximately 63% of predicted targets were validated with previous reports. Notably, the predicted targets by this approach were often involved in both beneficial and malicious signalling pathways, which may reflect heterogeneous cellular origins of EVs in tissues. Lastly, there has been an active debate on U6 whether it is a proper control. Through further analysis of EV miR profiles, miR‐676 was identified as a superior reference control due to its consistent and abundant expressions. In summary, our results contribute to identifying specific EV miRs for the potential therapeutic targets in heart failure and suggest that miR‐676 as a new reference control for the EV miR studies.     

Effective feature selection framework for cluster analysis of microarray data

The microarray technique has become a standard means in simultaneously examining expression of all genes measured in different circumstances. As microarray data are typically characterized by high dimensional features with a small number of samples, feature selection needs to be incorporated to identify a subset of genes that are meaningful for biological interpretation and accountable for the sample variation. In this article, we present a simple, yet effective feature selection framework suitable for two-dimensional microarray data. Our correlation-based, nonparametric approach allows compact representation of class-specific properties with a small number of genes. We evaluated our method using publicly available experimental data and obtained favorable results.