两种微量RNA扩增方法的比较研究

本研究通过比较体外转录和单引物扩增这两种扩增微量RNA的不同方法,以寻找一种高效的扩增方法。我们用两种不同方法分别扩增小鼠大脑全皮层及第五皮层细胞的RNA,扩增的RNA合成cDNA后进行荧光定量PCR实验,根据PCR结果比较两种不同扩增方法的效率。WT-ovation扩增RNA的效率约为IVT效率的2.8倍;IVT方法扩增后,基因D-C值与引物距离mRNA 3'端的长度及mRNA的长度均存在正线性相关(P<0.05),即引物距离mRNA的3'端越近、mRNA越短,基因D-Ct值越低。而WT-ovation方法扩增后,基因D-Ct值与引物距离mRNA 3'端的长度及mRNA的长度均不存在统计学相关性。与IVT方法相比,WT-ovation方法效率更高,扩增时受影响因素较少、更稳定。     

Assessing the Quality of Hybridized RNA in Affymetrix GeneChips Using Linear Regression

The quality of data from microarray analysis is highly dependent on the quality of RNA. Because of the lability of RNA, steps involved in tissue sampling, RNA purification, and RNA storage are known to potentially lead to the degradation of RNAs; therefore, assessment of RNA quality and integrity is essential. Existing methods for estimating the quality of RNA hybridized to a GeneChip either suffer from subjectivity or are inefficient in performance. To overcome these drawbacks, we propose a linear regression method for assessing RNA quality for a hybridized Genechip. In particular, our approach used the probe intensities from the .cel files that the Affymetrix software associates with each microarray. The effectiveness and the improvements of the proposed method over the existing methods are illustrated by the application of the method to the previously published 19 human Affymetrix microarray data sets for which external verification of RNA quality is available.     

Assessing quality of hybridized RNA in Affymetrix GeneChip experiments using mixed-effects models

The technology for hybridizing archived tissue specimens and the use of laser-capture microdissection for selecting cell populations for RNA extraction have increased over the past few years. Both these methods contribute to RNA degradation. Therefore, quality assessments of RNA hybridized to microarrays are becoming increasingly more important. Existing methods for estimating the quality of RNA hybridized to a GeneChip, from resulting microarray data, suffer from subjectivity and lack of estimates of variability. In this article, a method for assessing RNA quality for a hybridized array which overcomes these drawbacks is proposed. The effectiveness of the proposed method is demonstrated by the application of the method to two microarray data sets for which external verification of RNA quality is known.     

Optimized procedures for microarray analysis of histological specimens processed by laser capture microdissection

Analysis of cell-specific gene expression patterns using microarrays can reveal genes that are differentially expressed in diseased and normal tissue, as well as identify genes associated with specialized cellular functions. However, the cellular heterogeneity of the tissues precludes the resolution of expression profiles of specific cell types. While laser capture microdissection (LCM) can be used to obtain purified cell populations, the limited quantity of RNA isolated makes it necessary to perform an RNA amplification step prior to microarray analysis. The linearity and reproducibility of two RNA amplification protocols--the Baugh protocol (Baugh et al., 2001, Nucleic Acids Res 29:E29) and an in-house protocol have been assessed by conducting microarray analyses. Cy3-labeled total RNA from the colorectal cell line Colo-205 was compared to Cy5-labeled Colo-205 amplified RNA (aRNA) generated with each of the two protocols, using a human 10K cDNA array. The correlation of the gene intensities between amplified and total RNA measured in the two channels of each microarray was 0.72 and 0.61 for the Baugh protocol and the in-house protocol, respectively. The two protocols were further evaluated using aRNA obtained from normal colonic crypt cross-sections isolated via LCM. In both cases a microarray profile representative of colonic mucosa was obtained; statistically, the Baugh protocol was superior. Furthermore, a substantial overlap between highly expressed genes in the Colo-205 cells and colonic crypts underscores the reliability of the microarray analysis of LCM-derived material. Taken together, these results demonstrate that LCM-derived tissue from histological specimens can generate abundant amounts of high-quality aRNA for subsequent microarray analysis.     

Linear amplification of catalyzed reporter deposition technology on nylon membrane microarray

The application of microarray analysis to gene expression from limited tissue samples has not been very successful because of the poor signal qualityfrom the genes expressed at low levels. Here we discussed the use of catalyzed reporter deposition (CARD) technology to amplify signals from limited RNA samples on nylon membrane cDNA microarray. When the input RNA level was greater than 10 microg, the genes expressed at high levels did not amplify in proportion to those expressed at low levels. Compared to conventional colorimetric detection, the CARD method requires less than 10% of the total RNA used for amplification of signal displayed onto a nylon membrane cDNA microarray. Total RNA (5-10 microg), as one can extract from a limited amount of specimen, was determined to produce a linear correlation between the colorimetric detection and CARD methods. Beyond this range, it can cause a nonlinear amplification of highly expressed and low-abundance genes. These results suggest that when amplification is needed for any applications using the CARD method, including DNA microarray experiments, precaution has to be taken in the amount of RNA used to avoid skew amplification and thus misleading conclusions.     

An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis

Archival formalin-fixed, paraffin-embedded and ethanol-fixed tissues represent a potentially invaluable resource for gene expression analysis, as they are the most widely available material for studies of human disease. Little data are available evaluating whether RNA obtained from fixed (archival) tissues could produce reliable and reproducible microarray expression data. Here we compare the use of RNA isolated from human archival tissues fixed in ethanol and formalin to frozen tissue in cDNA microarray experiments. Since an additional factor that can limit the utility of archival tissue is the often small quantities available, we also evaluate the use of the tyramide signal amplification method (TSA), which allows the use of small amounts of RNA. Detailed analysis indicates that TSA provides a consistent and reproducible signal amplification method for cDNA microarray analysis, across both arrays and the genes tested. Analysis of this method also highlights the importance of performing non-linear channel normalization and dye switching. Furthermore, archived, fixed specimens can perform well, but not surprisingly, produce more variable results than frozen tissues. Consistent results are more easily obtainable using ethanol-fixed tissues, whereas formalin-fixed tissue does not typically provide a useful substrate for cDNA synthesis and labeling.     

How the RNA isolation method can affect microRNA microarray results

The quality of RNA is crucial in gene expression experiments. RNA degradation interferes in the measurement of gene expression, and in this context, microRNA quantification can lead to an incorrect estimation. In the present study, two different RNA isolation methods were used to perform microRNA microarray analysis on porcine brain tissue. One method is a phenol-guanidine isothiocyanate-based procedure that permits isolation of total RNA. The second method, miRVana? microRNA isolation, is column based and recovers the small RNA fraction alone. We found that microarray analyses give different results that depend on the RNA fraction used, in particular because some microRNAs appear very sensitive to the RNA isolation method. We conclude that precautions need to be taken when comparing microarray studies based on RNA isolated with different methods.     

Characterization of the effect of sample quality on high density oligonucleotide microarray data using progressively degraded rat liver RNA

Background  

The interpretability of microarray data can be affected by sample quality. To systematically explore how RNA quality affects microarray assay performance, a set of rat liver RNA samples with a progressive change in RNA integrity was generated by thawing frozen tissue or by ex vivo incubation of fresh tissue over a time course.     

Genomic DNA as a cohybridization standard for mammalian microarray measurements

A persistent design problem for ratiometric microarray studies is selecting the ‘denominator’ RNA cohybridization standard. The ideal standard should be readily available, inexpensive, invariant over time and from laboratory to laboratory, and should represent all genes with a uniform signal. RNA references (both commercial ‘universal’ and experiment- specific types), fall short of these goals. We show here that mouse genomic DNA is a reliable microarray cohybridization standard which can meet these criteria. Genomic DNA was superior in universality of coverage (>98% of genes from a 16 000 feature mouse 70mer microarray) to the Stratagene Universal Mouse Reference RNA standard. Ratios for genes in very low abundance in the Stratagene standard were more unstable with the Stratagene standard than with genomic DNA. Genes with mid-range, and therefore presumably optimal RNA denominator values, showed comparable reproducibility with both standards. Inferred ratios made between two different experimental RNAs using a genomic DNA standard were found to correlate well with companion, directly measured ratios (Spearman correlation coefficient = 0.98). The advantage in array feature coverage of genomic DNA will likely increase as newer generation microarrays include genes which are expressed exclusively in minor tissue or developmental domains that are not represented in mixed tissue RNA standards.     

Methods for the identification of differentially expressed genes in human post-mortem brain

Microarrays can be used to monitor the expression of thousands of genes simultaneously. This technique requires high-quality RNA which can be extracted from a variety of tissues and cells including post-mortem human brain. Given the vast amount of information obtained from microarray studies, it is critical to establish valid analysis techniques to identify differentially expressed genes. This technical report describes the basic methodology and analyses used to identify such genes in human post-mortem brain tissue.     

Assessing the Reliability of Amplified RNA Used in Microarrays

A certain minimal amount of RNA from biological samples is necessary to perform a microarray experiment with suitable replication. In some cases, the amount of RNA available is insufficient, necessitating RNA amplification prior to target synthesis. However, there is some uncertainty about the reliability of targets that have been generated from amplified RNA, because of nonlinearity and preferential amplification. This current work develops a straightforward strategy to assess the reliability of microarray data obtained from amplified RNA. The tabular method we developed, which utilises a Down-Up-Missing-Below (DUMB) classification scheme, shows that microarrays generated with amplified RNA targets are reliable within constraints. There was an increase in false negatives because of the need for increased filtering. Furthermore, this analysis method is generic and can be broadly applied to evaluate all microarray data. A copy of the Microsoft Excel spreadsheet is available upon request from Edward Bearden.     

Extraction of high-quality RNA from pancreatic tissues for gene expression studies

Extracting RNA from pancreatic tissue is notoriously challenging because of the organ's high RNase content. Standard methods using TriPure or TRIzol classically yield RNA of sufficient quality for routine gene expression analysis but not for microarray or deep sequencing analysis. Here we developed a simple method to extract high-quality RNA from mouse pancreas. Our method uses an RNase inhibitor and combines different protocols using guanidium thiocyanate–phenol extraction. It enables reproducible isolation of RNA with an RNA integrity number around 9.