Functional classes of bronchial mucosa genes that are differentially expressed in asthma

Background  

Asthma pathogenesis and susceptibility involves a complex interplay between genetic and environmental factors. Their interaction modulates the airway inflammation and remodelling processes that are present even in mild asthma and governs the appearance and severity of symptoms of airway hyperresponsiveness. While asthma is felt to develop as the result of interaction among many different genes and signalling pathways, only a few genes have been linked to an increased risk of developing this condition.     

The small genome of Arabidopsis contains at least six expressed alpha-tubulin genes.

The goal of our investigations is to define the genetic control of microtubule-based processes in a higher plant. The available evidence suggests that we have achieved our first objective: the characterization of the complete alpha-tubulin and beta-tubulin gene families of Arabidopsis. Four additional alpha-tubulin genes (TUA2, TUA4, TUA5, and TUA6) of Arabidopsis have been cloned and sequenced to complete the analysis of the gene structure for all six alpha-tubulin genes detectable on DNA gel blots of Arabidopsis genomic DNA hybridized with alpha-tubulin coding sequences. TUA1 and TUA3 were characterized earlier in our laboratory. Noncoding gene-specific hybridization probes have been constructed for all six alpha-tubulin genes and used in RNA gel blot analyses to demonstrate that all six genes are transcribed. The six genes encode four different alpha-tubulin isoforms; TUA2 and TUA4 encode a single isoform, as do TUA3 and TUA5. Two-dimensional protein gel immunoblot analyses have resolved at least four alpha-tubulin isoforms from plant tissues, suggesting that all of the predicted TUA gene products are synthesized in vivo.     

基因芯片技术筛选转SlNAC1基因拟南芥差异表达基因

研究已表明植物特有的一些NAC(NAM,ATAF1/2,CUC2)转录因子可提高植物抗逆性,利用基因芯片技术筛选转SlNAC1基因拟南芥与野生型拟南芥间差异表达基因,能够为研究转基因拟南芥非生物胁迫抗性相关基因提供依据。结果显示,在转SlNAC1基因拟南芥43 604个基因中有3 046个差异表达2倍以上的基因。对差异表达5倍以上基因经过GO富集度统计学分析表明,细胞组分相关基因占33.05%;分子功能相关基因占33.95%;生物学过程相关基因占33.00%。对差异表达2倍以上基因进行KEGG信号通路分析,结果表明有2 431个基因涉及到88个不同的信号通路。通过筛选获得转基因拟南芥非生物胁迫抗性相关候选基因,为后续研究NAC转录因子的下游基因及其调控网络的构建提供方向和理论支撑。     

Tomato contains two differentially expressed genes encoding B-type phytochromes,neither of which can be considered an ortholog of Arabidopsis phytochrome B

Tomato (Solanum lycopersicon L.) contains two B-type phytochrome genes (PHYB1 and PHYB2). Fragments of these two PHYB were cloned following amplification by the polymerase chain reaction of a portion of their relatively well conserved 5 coding regions. Polypeptides encoded by these gene fragments exhibit 90% sequence identity. These two PHYB are independently expressed in organ-specific fashion. In mature plants, PHYB2 mRNA is most abundant in fruit and PHYB1 mRNA in expanded leaves. A phylogenetic analysis fails to establish which tomato PHYB is orthologous to either Arabidopsis PHYB or PHYD, the latter being a second B-type phytochrome. Instead, this analysis indicates that following the divergence of the Solanaceae and Brassicaceae from one another, a PHYB gene duplicated independently in each lineage. Consequently, Arabidopsis PHYB mutants cannot be considered strictly equivalent to the tomato tri mutants, which appear to be mutated at the PHYB1 locus. Similarly, other putative PHYB mutants might not be equivalent to those described for Arabidopsis and tomato. This situation complicates efforts to determine PHYB function because there might be no one answer to this question.Abbreviations PCR polymerase chain reaction - PHY undesignated phytochrome gene - PHYA, PHYB, etc phytochrome gene(s) of the A, B, etc. type This research was supported by USDA NRICGP grant 93-00939 and by NATO travel grant CRG 931183. It was initiated when two of us (L.H.P., M.-M.C.-P.) spent a sabbatical year at the Institut National de la Recherche Agronomique in Versailles, France. L.H.P. gratefully acknowledges support provided by a senior guest fellowship from the Ministère de l'enseignement superieur et de la recherche during his stay in Versailles. L.H.P. and M.-M.C.-P thank all of their colleagues in Versailles for their warm hospitality and their willingness to share their expertise with us. We also thank Russell Malmberg, Richard Meagher and Robert Price for helpful discussions concerning the interpretation of molecular phylogenies.     

The three typical aspartic proteinase genes of Arabidopsis thaliana are differentially expressed.

Genomic sequencing has identified three different typical plant aspartic proteinases in the genome of Arabidopsis thaliana, named Pasp-A1, A2 and A3. A1 is identical to a cDNA we had previously isolated and the two others produce proteins 81 and 63% identical to that predicted protein. Sequencing of the aspartic proteinase protein purified from Arabidopsis seeds showed that the peptides are derived from two of these genes, A1 and A2. Using gene specific probes, we have analyzed RNA from different tissues and found these three genes are differentially expressed. A1 mRNA is detected in all tissues analyzed and more abundant in leaves during the light phase of growth. The other two genes are expressed either primarily in flowers (A3) or in seeds (A2). Insitu hybridization demonstrated that all three genes are expressed in many cells of the seeds and developing seed pods. The A1 and A3 genes are expressed in the sepals and petals of flowers as well as the outer layer of the style, but are not expressed in the transmitting tract or on the stigmatal surface. The A2 gene is weakly expressed only in the transmitting tissue of the style. All three genes are also expressed in the guard cells of sepals. These data suggest multiple roles for aspartic proteinases besides those proposed in seeds.     

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.     

Chlorophyll a/b-binding protein genes are differentially expressed during soybean development

The levels of chlorophyll a/b-binding protein (Cab) gene polysomal poly(A)⁺ mRNA were quantitated throughout the development of Glycine max L. Cab mRNAs were abundant in young expanding leaves, representing 6.1% of the leaf mRNA population. Lower Cab mRNA levels were present in embryos, stems, and cotyledons of developing seedlings; the lowest levels were found in roots where they accounted for 0.04% of the polysomal poly(A)⁺ mRNA of this organ. To determine the contribution of different members of the Cab gene family to the Cab mRNA populations, a quantitative S1 nuclease reconstruction assay was developed. Cab3, Cab4, and Cab5 mRNAs were detected in all stages examined during soybean development but their levels underwent differential changes. Cab3 encodes the most abundant Cab mRNA in young leaves, developing embryos, and in Stage VII cotyledons from the developing soybean seedling. The levels of Cab mRNAs were compared to the levels of ribulose-1,5-bisphosphate carboxylase small subunit gene mRNA and differences in their patterns of accumulation were noted. Collectively these data indicate that during soybean embryogenesis developmental control mechanisms supersede light-regulatory signals.     

差异表达基因的分离策略

生命活动的各个进程伴随着不同基因的选择性开启和关闭。如何有效地分离克隆各种差异表达的基因,成为分子生物学研究的一个努力方向,大量差异基因分离策略因之问世。本文扼要介绍了近年来发展的几种主要分离策略,并详细介绍一种新的差异基因分离方法--抑制差减杂交。     

Two differentially expressed MATE factor genes from apple complement the Arabidopsis transparent testa12 mutant

Proanthocyanidins (PAs) are a class of flavonoids with numerous functions in plant ecology and development, including protection against microbial infection, animal foraging and damage by UV light. PAs are also beneficial in the human diet and livestock farming, preventing diseases of the cardiovascular system and lowering the risk of cancer, asthma and diabetes. Apples (Malus x domestica Borkh.) are naturally rich in flavonoids, but the flavonoid content and composition varies significantly between cultivars. In this work, we applied knowledge from the model plant Arabidopsis thaliana, for which the main features of flavonoid biosynthesis have been elucidated, to investigate PA accumulation in apple. We identified functional homologues of the Multidrug And Toxic compound Extrusion (MATE) gene TRANSPARENT TESTA12 from A. thaliana using a comparative genomics approach. MdMATE1 and MdMATE2 were differentially expressed, and the function of the encoded proteins was verified by complementation of the respective A. thaliana mutant. In addition, MdMATE genes have a different gene structure in comparison to homologues from other species. Based on our findings, we propose that MdMATE1 and MdMATE2 are vacuolar flavonoid/H(+) -antiporters, active in PA accumulating cells of apple fruit. The identification of these flavonoid transporter genes expands our understanding of secondary metabolite biosynthesis and transport in apple, and is a prerequisite to improve the nutritional value of apples and apple-derived beverages.     

Two alpha-L-arabinofuranosidase genes in Arabidopsis thaliana are differentially expressed during vegetative growth and flower development

Glycosyl hydrolases are important mediators of plant cell wall modification during plant development. These enzymes catalyse the hydrolytic release of specific sugars, such as L-arabinose, from the polysaccharide-rich cell wall matrix. The cloning and expression analysis of two genes, AtASD1 and AtASD2, encoding putative alpha-L-arabinofuranosidases in Arabidopsis thaliana are reported here. AtASD1 and AtASD2 identities were assigned on the basis of homology to plant and microbial family 51 glycoside hydrolases. Using RT-PCR, RNA gel blot analysis and reporter gene expression analysis, AtASD1 and AtASD2 were shown to have different developmental expression profiles. High levels of AtASD1 promoter activity are present in multiple tissues during vegetative and reproductive growth. AtASD1 expression is particularly intense in zones of cell proliferation, the vascular system, developing and regressing floral tissues, and floral abscission zones. By comparison, AtASD2 expression is limited to the vasculature of older root tissue and to some floral organs and floral abscission zones.     

Ranking analysis for identifying differentially expressed genes

Microarrays allow researchers to examine the expression of thousands of genes simultaneously. However, identification of genes differentially expressed in microarray experiments is challenging. With an optimal test statistic, we rank genes and estimate a threshold above which genes are considered to be differentially expressed genes (DE). This overcomes the embarrassing shortcoming of many statistical methods to determine the cut-off values in ranking analysis. Experiments demonstrate that our method is a good performance and avoids the problems with graphical examination and multiple hypotheses testing that affect alternative approaches. Comparing to those well known methods, our method is more sensitive to data sets with small differentially expressed values and not biased in favor of data sets based on certain distribution models.     

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.     

Statistical methods for ranking differentially expressed genes

In the analysis of microarray data the identification of differential expression is paramount. Here I outline a method for finding an optimal test statistic with which to rank genes with respect to differential expression. Tests of the method show that it allows generation of top gene lists that give few false positives and few false negatives. Estimation of the false-negative as well as the false-positive rate lies at the heart of the method.     

Finding differentially expressed genes for pattern generation

MOTIVATION: It is important to consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation. RESULTS: We developed two methods which are mainly based on the q-values approach; the first is a direct extension of the q-values approach, while the second uses two approaches: q-values and maximum-likelihood. We present two algorithms for the second method, one for error minimization and the other for confidence bounding. Also, we show how the method called Patterns from Gene Expression (PaGE) (Grant et al., 2000) can benefit from q-values. Finally, we conducted some experiments to demonstrate the effectiveness of the proposed methods; experimental results on a selected dataset (BRCA1 vs BRCA2 tumor types) are provided. CONTACT: alhajj@cpsc.ucalgary.ca.     

Detecting differentially expressed genes by relative entropy

DNA microarray experiments have generated large amount of gene expression measurements across different conditions. One crucial step in the analysis of these data is to detect differentially expressed genes. Some parametric methods, including the two-sample t-test (T-test) and variations of it, have been used. Alternatively, a class of non-parametric algorithms, such as the Wilcoxon rank sum test (WRST), significance analysis of microarrays (SAM) of Tusher et al. (2001), the empirical Bayesian (EB) method of Efron et al. (2001), etc., have been proposed. Most available popular methods are based on t-statistic. Due to the quality of the statistic that they used to describe the difference between groups of data, there are situations when these methods are inefficient, especially when the data follows multi-modal distributions. For example, some genes may display different expression patterns in the same cell type, say, tumor or normal, to form some subtypes. Most available methods are likely to miss these genes. We developed a new non-parametric method for selecting differentially expressed genes by relative entropy, called SDEGRE, to detect differentially expressed genes by combining relative entropy and kernel density estimation, which can detect all types of differences between two groups of samples. The significance of whether a gene is differentially expressed or not can be estimated by resampling-based permutations. We illustrate our method on two data sets from Golub et al. (1999) and Alon et al. (1999). Comparing the results with those of the T-test, the WRST and the SAM, we identified novel differentially expressed genes which are of biological significance through previous biological studies while they were not detected by the other three methods. The results also show that the genes selected by SDEGRE have a better capability to distinguish the two cell types.