Identification of genes differentially expressed in extraradical mycelium and ectomycorrhizal roots during Paxillus involutus-Betula pendula ectomycorrhizal symbiosis

The development of ectomycorrhizal symbiosis leads to drastic changes in gene expression in both partners. However, little is known about the spatial regulation of symbiosis-regulated genes. Using cDNA array profiling, we compared the levels of expression of fungal genes corresponding to approximately 1,200 expressed sequenced tags in the ectomycorrhizal root tips (ECM) and the connected extraradical mycelium (EM) for the Paxillus involutus-Betula pendula ectomycorrhizal association grown on peat in a microcosm system. Sixty-five unique genes were found to be differentially expressed in these two fungal compartments. In ECM, a gene coding for a putative phosphatidylserine decarboxylase (Psd) was up-regulated by 24-fold, while genes coding for urea (Dur3) and spermine (Tpo3) transporters were up-regulated 4.1- and 6.2-fold in EM. Moreover, urea was the major nitrogen compound found in EM by gas chromatography-mass spectrometry analysis. These results suggest that (i) there is a spatial difference in the patterns of fungal gene expression between ECM and EM, (ii) urea and polyamine transporters could facilitate the translocation of nitrogen compounds within the EM network, and (iii) fungal Psd may contribute to membrane remodeling during ectomycorrhiza formation.     

Identification of differentially expressed genes in mouse kidney after irradiation using microarray analysis

Irradiation of the kidney induces dose-dependent, progressive renal functional impairment, which is partly mediated by vascular damage. The molecular mechanisms underlying the development of radiation-induced nephropathy are unclear. Given the complexity of radiation-induced responses, microarrays may offer new opportunities to identify a wider range of genes involved in the development of radiation injury. The aim of the present study was to determine whether microarrays are a useful tool for identifying time-related changes in gene expression and potential mechanisms of radiation-induced nephropathy. Microarray experiments were performed using amplified RNA from irradiated mouse kidneys (1 x 16 Gy) and from sham-irradiated control tissue at different intervals (1-30 weeks) after irradiation. After normalization procedures (using information from straight-color, color-reverse and self-self experiments), the differentially expressed genes were identified. Control and repeat experiments were done to confirm that the observations were not artifacts of the array procedure (RNA amplification, probe synthesis, hybridizations and data analysis). To provide independent confirmation of microarray data, semi-quantitative PCR was performed on a selection of genes. At 1 week after irradiation (before the onset of vascular and functional damage), 16 genes were significantly up-regulated and 9 genes were down-regulated. During the period of developing nephropathy (10 to 20 weeks), 31 and 42 genes were up-regulated and 9 and 4 genes were down-regulated. At the later time of 30 weeks, the vast majority of differentially expressed genes (191 out of 203) were down-regulated. Potential genes of interest included TSA-1 (also known as Ly6e) and Jagged 1 (Jag1). Increased expression of TSA-1, a member of the Ly-6 family, has previously been reported in response to proteinuria. Jagged 1, a ligand for the Notch receptor, is known to play a role in angiogenesis, and is particularly interesting in the context of radiation-induced vascular injury. The present study demonstrates the potential of microarrays to identify changing patterns of gene expression in irradiated kidney. Further studies will be required to evaluate functional involvement of these genes in vascular-mediated normal tissue injury.     

Identification of differentially expressed genes from adult cockroach females exhibiting maternal care behavior

Recent challenges in the study of animal behavior are to detect genes related to behavior and how the genes exert their influence on morphological and behavioral plasticity, particularly as related to the mechanism of insect sociability. In this study, we discovered genes related to parental care behavior in social insects. Woodroaches of the genus Cryptocercus provide nutritious materials and symbiotic protists via proctodeal feeding to their young during early developmental stages. Thus, they are a good model species for discovering genes related to parental care behavior. We screened eight differentially expressed genes (DEG1–DEG8) from adult Cryptocercus females exhibiting maternal care behavior. Of the proteins translated from the screened genes, DEG7 showed high homology to apolipophorin-III-like proteins. Analysis of diverse molecular features revealed that DEG7 was a partial clone encoding apoLp-III, which plays essential roles in hemolymph-lipid transport processes in insects. Isolation of full-length cDNAs for the DEGs identified in this study would be very helpful for a functional annotation of the individual genes and further understanding of maternal care behavior at the molecular level in the future.     

Selecting differentially expressed genes from microarray experiments

High throughput technologies, such as gene expression arrays and protein mass spectrometry, allow one to simultaneously evaluate thousands of potential biomarkers that could distinguish different tissue types. Of particular interest here is distinguishing between cancerous and normal organ tissues. We consider statistical methods to rank genes (or proteins) in regards to differential expression between tissues. Various statistical measures are considered, and we argue that two measures related to the Receiver Operating Characteristic Curve are particularly suitable for this purpose. We also propose that sampling variability in the gene rankings be quantified, and suggest using the "selection probability function," the probability distribution of rankings for each gene. This is estimated via the bootstrap. A real dataset, derived from gene expression arrays of 23 normal and 30 ovarian cancer tissues, is analyzed. Simulation studies are also used to assess the relative performance of different statistical gene ranking measures and our quantification of sampling variability. Our approach leads naturally to a procedure for sample-size calculations, appropriate for exploratory studies that seek to identify differentially expressed genes.     

Identification of genes differentially expressed in benign prostatic hyperplasia.

Differences between benign prostatic hyperplasia (BPH) and normal prostate tissue at the level of mRNA expression provide an opportunity to identify candidate genes for this disease. A cDNA subtraction procedure was used to isolate differentially expressed genes in BPH. The subtraction was done by solution hybridization of BPH cDNA against excess normal prostate cDNA. We identified known, EST, and novel genes by sequence and database analysis of the subtracted cDNAs. Several of these cDNAs were used as probes in Northern blotting analysis to confirm over-expression of their corresponding mRNAs in BPH tissues. One highly upregulated sequence of interest shared identity with a known mRNA encoding human NELL2, a protein containing epidermal growth factor-like domains. NELL2 was not previously reported to be expressed in prostate and may code for a novel prostatic growth factor. In situ hybridization analysis of hyperplastic prostate specimens demonstrated that NELL2 mRNA expression is predominantly localized in basal cells of the epithelium. Disease-related changes in the levels of NELL2 may contribute to alterations in epithelial-stromal homeostasis in BPH. (J Histochem Cytochem 49:669-670, 2001)     

Identification of drought-inducible genes and differentially expressed sequence tags in barley

Drought limits cereal yields in several regions of the world and plant water status plays an important role in tolerance to drought. To investigate and understand the genetic and physiological basis of drought tolerance in barley, differentially expressed sequence tags (dESTs) and candidate genes for the drought response were mapped in a population of 167 F₈ recombinant inbred lines derived from a cross between Tadmor (drought tolerant) and Er/Apm (adapted only to specific dry environments). One hundred sequenced probes from two cDNA libraries previously constructed from drought-stressed barley (Hordeum vulgare L., var. Tokak) plants and 12 candidate genes were surveyed for polymorphism, and 33 loci were added to a previously published map. Composite interval mapping was used to identify quantitative trait loci (QTL) associated with drought tolerance including leaf relative water content, leaf osmotic potential, osmotic potential at full turgor, water-soluble carbohydrate concentration, osmotic adjustment, and carbon isotope discrimination. A total of 68 QTLs with a limit of detection score 2.5 were detected for the traits evaluated under two water treatments and the two traits calculated from both treatments. The number of QTLs identified for each trait varied from one to 12, indicating that the genome contains multiple genes affecting different traits. Two candidate genes and ten differentially expressed sequences were associated with QTLs for drought tolerance traits.     

Identification of differentially expressed genes by mutually subtracted RNA fingerprinting

A mutually subtracted RNA fingerprinting (SuRF) method has been developed that allows efficient identification of differentially expressed sequence tags between two samples. Mutual subtractions of two RNA samples are achieved by first synthesizing cDNAs using oligo(dT) coupled with magnetic beads which are then reciprocally hybridized to starting RNA samples to remove common mRNAs between them. The second step involves differential fingerprinting of the subtracted RNA samples by polymerase chain reaction with specially designed degenerate primers. SuRF was applied to identify alteration in gene expression pertinent to osteogenic sarcoma which was achieved by employing the method between FOB (an immortalized fetal osteoblast) and MG63 (an osteosarcoma) cell lines. An estimated 10% of the total expressed genes in these two cell types were screened by the method. This analysis identified 96 differentially expressed sequences, none of which was identified repeatedly. A subset of these sequences was subsequently confirmed to have differential expression between the two cell types. Removal of common mRNAs prior to differential display should diminish redundant identification of abundant genes and increase the chance of identifying rare differentially expressed genes.     

Identification of differentially expressed genes from ovarian cancer cells by MICROMAX cDNA microarray system

Using the MICROMAX cDNA microarray system, we were able to identify genes that are differentially overexpressed in ovarian cancer. A total of 30 putative genes, which are differentially overexpressed in ovarian cancer cell lines, were identified. The differential expression of some of these genes was further confirmed by real-time RT-PCR. Using this strategy, we have identified genes that either overexpress in all cancer cell lines or in only some cancer cell lines. Further characterization of these genes will allow them to be exploited in diagnosis, prognosis, anticancer therapy, and molecular classification of ovarian cancer.     

基于熵信息处理和PCA的肿瘤基因表达谱分类识别

通过对基因表达谱数据的分析从而促进肿瘤诊断与治疗技术的发展,其研究正成为生物医学领域的一个热点。因此,提出了一种熵信息处理和主成分分析（principal component analysis,PCA）相结合的方法。首先运用熵信息对超高维基因表达谱数据进行粗选取,得到特征基因子集;由于基因子集仍存在相关性,进而利用PCA对其进一步冗余剔除;最后对得到的无冗余且具有正交性信息的基因特征进行真实数据实验。实验结果显示所采用的方法能有效去除肿瘤样本中的不相关和冗余信息,同时最大程度的保留肿瘤分类信息。与其他肿瘤分类方法相比,在精度上具有比较明显的优势,从而验证了该方法是有效的、可行的。     

Identification of differentially expressed genes and false discovery rate in microarray studies

PURPOSE OF REVIEW: To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. RECENT FINDINGS: The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. SUMMARY: There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.     

Identification of differentially expressed genes in normal and tumor human gastric tissue

The search for differentially expressed genes in gastric cancer may help define molecular alterations and molecular diagnosis of gastric cancer. Using the differential display PCR technique, we identified 18 genes that are differentially expressed between normal and tumor human gastric tissues. Their expressions were verified with reverse Northern blot analysis and Northern blot analysis. Oxidative phosphorylation-related genes, antizyme inhibitor of ornithine decarboxylase, protein phosphatase-1beta, 35-kDa peroxisomal membrane protein, and cystic fibrosis transmembrane conductance receptor were highly expressed in tumor tissue, whereas pepsinogen A, Na-K ATPase alpha subunit, nerve growth factor receptor, and alpha-tropomyosin were highly expressed in normal tissue. In addition, 3 unknown genes were found to be differentially expressed in paired gastric tissues. These differentially expressed genes may provide significant opportunities for further understanding of gastric carcinogenesis and the molecular diagnosis of gastric cancer.     

Detecting multivariate differentially expressed genes

Background  

Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariate in nature. Yet, current statistical methods for detecting differential expression merely consider the univariate difference in expression level of each gene in isolation, thus potentially neglecting many genes of biological importance.