Cross-species hybridisation of pig RNA to human nylon microarrays

Background

The objective of this research was to investigate the reproducibility of cross-species microarray hybridisation. Comparisons between same- and cross-species hybridisations were also made. Nine hybridisations between a single pig skeletal muscle RNA sample and three human cDNA nylon microarrays were completed. Three replicate hybridisations of two different amounts of pig RNA, and of human skeletal muscle RNA were completed on three additional microarrays.

Results

Reproducibility of microarray hybridisations of pig cDNA to human microarrays was high, as determined by Spearman and Pearson correlation coefficients and a Kappa statistic. Variability among replicate hybridisations was similar for human and pig data, indicating the reproducibility of results were not compromised in cross-species hybridisations. The concordance between data generated from hybridisations using pig and human skeletal muscle RNA was high, further supporting the use of human microarrays for the analysis of gene expression in the pig. No systematic effect of stripping and re-using nylon microarrays was found, and variability across microarrays was minimal.

Conclusion

The majority of genes generated highly reproducible data in cross-species microarray hybridisations, although approximately 6% were identified as highly variable. Experimental designs that include at least three replicate hybridisations for each experimental treatment will enable the variability of individual genes to be considered appropriately. The use of cross-species microarray analysis looks promising. However, additional validation is needed to determine the specifiCity of cross-species hybridisations, and the validity of results.     

A simple and effective method for the isolation of inner cell mass samples from human blastocysts for gene expression analysis

The isolation of pure inner cell mass (ICM) and trophectoderm (TE) cells from a single human blastocyst is necessary to obtain accurate gene expression patterns of these cells, which will aid in the understanding of the primary steps of embryo differentiation. However, previously developed pure ICM isolation methods are either time-consuming or alter the normal gene expression patterns of these cells. Here, we demonstrate a simple and effective method of ICM samples isolation from human blastocysts. In total, 35 human blastocysts of all stages with expanded and good morphology were incubated in calcium/magnesium-free HEPES medium for 5 min before micromanipulation. With the aid of a laser, a biopsy pipette was inserted directly into the blastocoel for the suction-based removal of ICM samples. The ICM samples were obtained through simple mechanical pulling force or laser assistance, and each isolation process required 3–4 min. The isolated ICM and TE fractions were subjected to single-cell real-time quantitative RT-PCR to evaluate keratin 18 (KRT18) expression. Finally, 33 paired ICM and TE samples were verified using gene expression analysis. KRT18 was readily detectable in all TE cells but absent in 30 ICM counterparts, indicating a pure ICM isolation rate of 90.9% (30/33). The relative KRT18 expression of three TE samples compared with their three contaminated ICM counterparts was 19-fold (P?<?0.001), indicating that the contamination was very weak. These results demonstrate that our ICM isolation method is simple and effective.     

Gene expression in the normal adult human kidney assessed by complementary DNA microarray

The kidney is a highly specialized organ with a complex, stereotyped architecture and a great diversity of functions and cell types. Because the microscopic organization of the nephron, the functional unit of the kidney, has a consistent relationship to the macroscopic anatomy of the kidney, knowledge of the characteristic patterns of gene expression in different compartments of the kidney could provide insight into the functions and functional organization of the normal nephron. We studied gene expression in dissected renal lobes of five adult human kidneys using cDNA microarrays representing approximately 30,000 different human genes. Total RNA was isolated from sections of the inner and outer cortex, inner and outer medulla, papillary tips, and renal pelvis and from glomeruli isolated by sieving. The results revealed unique and highly distinctive patterns of gene expression for glomeruli, cortex, medulla, papillary tips, and pelvic samples. Immunohistochemical staining using selected antisera confirmed differential expression of several cognate proteins and provided histological localization of expression within the nephron. The distinctive patterns of gene expression in discrete portions of the kidney may serve as a resource for further understanding of renal physiology and the molecular and cellular organization of the nephron.     

Application of microarray technology in primate behavioral neuroscience research

Gene expression profiling of brain tissue samples applied to DNA microarrays promises to provide novel insights into the neurobiological bases of primate behavior. The strength of the microarray technology lies in the ability to simultaneously measure the expression levels of all genes in defined brain regions that are known to mediate behavior. The application of microarrays presents, however, various limitations and challenges for primate neuroscience research. Low RNA abundance, modest changes in gene expression, heterogeneous distribution of mRNA among cell subpopulations, and individual differences in behavior all mandate great care in the collection, processing, and analysis of brain tissue. A unique problem for nonhuman primate research is the limited availability of species-specific arrays. Arrays designed for humans are often used, but expression level differences are inevitably confounded by gene sequence differences in all cross-species array applications. Tools to deal with this problem are currently being developed. Here we review these methodological issues, and provide examples from our experiences using human arrays to examine brain tissue samples from squirrel monkeys. Until species-specific microarrays become more widely available, great caution must be taken in the assessment and interpretation of microarray data from nonhuman primates. Nevertheless, the application of human microarrays in nonhuman primate neuroscience research recovers useful information from thousands of genes, and represents an important new strategy for understanding the molecular complexity of behavior and mental health.     

Genome-wide expression analysis of plant cell cycle modulated genes

Genome-wide expression analysis is rapidly becoming an essential tool for identifying and analysing genes involved in, or controlling, various biological processes ranging from development to responses to environmental cues. The control of cell division involves the temporal expression of different sets of genes, allowing the dividing cell to progress through the different phases of the cell cycle. A landmark study using DNA microarrays to follow the patterns of gene expression in synchronously dividing yeast cells has allowed the identification of several hundreds of genes that are involved in the cell cycle. Although DNA microarrays provide a convenient tool for genome-wide expression analysis, their use is limited to organisms for which the complete genome sequence or a large cDNA collection is available. For other organisms, including most plant species, DNA fragment analysis based methods, such as cDNA-AFLP, provide a more appropriate tool for genome-wide expression analysis. Furthermore, cDNA-AFLP exhibits properties that complement DNA microarrays and, hence, constitutes a useful tool for gene discovery.     

Variation in gene expression patterns in human gastric cancers

Gastric cancer is the world's second most common cause of cancer death. We analyzed gene expression patterns in 90 primary gastric cancers, 14 metastatic gastric cancers, and 22 nonneoplastic gastric tissues, using cDNA microarrays representing approximately 30,300 genes. Gastric cancers were distinguished from nonneoplastic gastric tissues by characteristic differences in their gene expression patterns. We found a diversity of gene expression patterns in gastric cancer, reflecting variation in intrinsic properties of tumor and normal cells and variation in the cellular composition of these complex tissues. We identified several genes whose expression levels were significantly correlated with patient survival. The variations in gene expression patterns among cancers in different patients suggest differences in pathogenetic pathways and potential therapeutic strategies.     

Towards Arabidopsis genome analysis: monitoring expression profiles of 1400 genes using cDNA microarrays

cDNA microarrays containing 1443 Arabidopsis thaliana genes were analyzed for expression profiles in major organs of Arabidopsis plants. Novel expression profiles were identified for many coding sequences with putative gene identifications. Expression patterns of novel sequences provided clues to their possible functions. The results demonstrate how microarrays containing a large number of Arabidopsis genes can provide a powerful tool for plant gene discovery, functional analysis and elucidation of genetic regulatory networks.     

Bayesian robust inference for differential gene expression in microarrays with multiple samples

We consider the problem of identifying differentially expressed genes under different conditions using gene expression microarrays. Because of the many steps involved in the experimental process, from hybridization to image analysis, cDNA microarray data often contain outliers. For example, an outlying data value could occur because of scratches or dust on the surface, imperfections in the glass, or imperfections in the array production. We develop a robust Bayesian hierarchical model for testing for differential expression. Errors are modeled explicitly using a t-distribution, which accounts for outliers. The model includes an exchangeable prior for the variances, which allows different variances for the genes but still shrinks extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and it can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space. The method is illustrated using two publicly available gene expression data sets. We compare our method to six other baseline and commonly used techniques, namely the t-test, the Bonferroni-adjusted t-test, significance analysis of microarrays (SAM), Efron's empirical Bayes, and EBarrays in both its lognormal-normal and gamma-gamma forms. In an experiment with HIV data, our method performed better than these alternatives, on the basis of between-replicate agreement and disagreement.     

Gene expression analysis on small numbers of invasive cells collected by chemotaxis from primary mammary tumors of the mouse

Background  

cDNA microarrays have the potential to identify the genes involved in invasion and metastasis. However, when used with whole tumor tissue, the results average the expression patterns of different cell types. We have combined chemotaxis-based cell collection of the invasive subpopulation of cells within the primary tumor with array-based gene expression analysis to identify the genes necessary for the process of carcinoma cell invasion.     

Comparative Gene Expression Analyses Identify Luminal and Basal Subtypes of Canine Invasive Urothelial Carcinoma That Mimic Patterns in Human Invasive Bladder Cancer

More than 160,000 people are expected to die from invasive urothelial carcinoma (iUC) this year worldwide. Research in relevant animal models is essential to improving iUC management. Naturally-occurring canine iUC closely resembles human iUC in histopathology, metastatic behavior, and treatment response, and could provide a relevant model for human iUC. The molecular characterization of canine iUC, however, has been limited. Work was conducted to compare gene expression array results between tissue samples from iUC and normal bladder in dogs, with comparison to similar expression array data from human iUC and normal bladder in the literature. Considerable similarities between enrichment patterns of genes in canine and human iUC were observed. These included patterns mirroring basal and luminal subtypes initially observed in human breast cancer and more recently noted in human iUC. Canine iUC samples also exhibited enrichment for genes involved in P53 pathways, as has been reported in human iUC. This is particularly relevant as drugs targeting these genes/pathways in other cancers could be repurposed to treat iUC, with dogs providing a model to optimize therapy. As part of the validation of the results and proof of principal for evaluating individualized targeted therapy, the overexpression of EGFR in canine bladder iUC was confirmed. The similarities in gene expression patterns between dogs and humans add considerably to the value of naturally-occurring canine iUC as a relevant and much needed animal model for human iUC. Furthermore, the finding of expression patterns that cross different pathologically-defined cancers could allow studies of dogs with iUC to help optimize cancer management across multiple cancer types. The work is also expected to lead to a better understanding of the biological importance of the gene expression patterns, and the potential application of the cross-species comparisons approach to other cancer types as well.     

Genes that code for T cell signaling proteins establish transcriptional regulatory networks during thymus ontogeny

Gene expression profiling by cDNA microarrays during murine thymus ontogeny has contributed to dissecting the large-scale molecular genetics of T cell maturation. Gene profiling, although useful for characterizing the thymus developmental phases and identifying the differentially expressed genes, does not permit the determination of possible interactions between genes. In order to reconstruct genetic interactions, on RNA level, within thymocyte differentiation, a pair of microarrays containing a total of 1,576 cDNA sequences derived from the IMAGE MTB library was applied on samples of developing thymuses (14-17 days of gestation). The data were analyzed using the GeneNetwork program. Genes that were previously identified as differentially expressed during thymus ontogeny showed their relationships with several other genes. The present method provided the detection of gene nodes coding for proteins implicated in the calcium signaling pathway, such as Prrg2 and Stxbp3, and in protein transport toward the cell membrane, such as Gosr2. The results demonstrate the feasibility of reconstructing networks based on cDNA microarray gene expression determinations, contributing to a clearer understanding of the complex interactions between genes involved in thymus/thymocyte development.     

A method for cross-species gene expression analysis with high-density oligonucleotide arrays

DNA microarrays have been widely used in gene expression analysis of biological processes. Due to a lack of sequence information, the applications have been largely restricted to humans and a few model organisms. Presented within this study are results of the cross-species hybridization with Affymetrix human high-density oligonucleotide arrays or GeneChip® using distantly related mammalian species; cattle, pig and dog. Based on the unique feature of the Affymetrix GeneChip® where every gene is represented by multiple probes, we hypothesized that sequence conservation within mammals is high enough to generate sufficient signals from some of the probes for expression analysis. We demonstrated that while overall hybridization signals are low for cross-species hybridization, a few probes of most genes still generated signals equivalent to the same-species hybridization. By masking the poorly hybridized probes electronically, the remaining probes provided reliable data for gene expression analysis. We developed an algorithm to select the reliable probes for analysis utilizing the match/mismatch feature of GeneChip®. When comparing gene expression between two tissues using the selected probes, we found a linear correlation between the cross-species and same-species hybridization. In addition, we validated cross-species hybridization results by quantitative PCR using randomly selected genes. The method shown herein could be applied to both plant and animal research.     

NOR1基因转染对肝癌细胞HepG2基因表达谱的影响

NOR1基因是一在正常组织中广泛表达且在肿瘤组织中表达下调的新基因.为进一步研究NOR1基因的功能和寻找其下游基因,利用脂质体技术将NOR1基因转染进HepG2细胞,采用cDNA微阵列技术分析其基因表达谱的改变.试验表明NOR1基因的转染能使Grb2,HBP17,TNFRSF11B等59个基因上调,同时也下调Bik,MAp2K6,ZFP95等103个基因.随后用实时荧光定量PCR对cDNA 微阵列结果中上述3个上调表达基因进行验证,结果表明,基因表达差异具有统计学意义(P<0.05),荧光定量PCR结果与微阵列结果相符.这些结果提示,NOR1基因对肝癌HepG2细胞的生物学行为的影响可能与它对细胞信号转导,细胞周期调控,转录、翻译调控相关基因的表达影响有关.