Additional file 1 of LncRNA regulates tomato fruit cracking by coordinating gene expression via a hormone-redox-cell wall network
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Additional file 1: Table S1. LncRNAs in 12 tomato fruit libraries.Objective: To screen the differential expression genes of Kanglaite Injection in treating cancer cachexia. Methods: mRNA was extracted from the blood cells of T739 animal model of C.C., hybridizated respectively on 20S gene chip. Analysis discuss on differential expression genes was carried out. Results: 5 differential expression genes were obtained. Among these genes, 4 genes were up-regulated and 1 gene was down-regulated. Most of these genes were related with immunity and metabolism of tumor. Conclusion: cDNA microarray for analysis of gene expression patterns is a powerful method to identify associated genes of Kanglaite.
Cancer Cachexia
Gene chip analysis
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ABSTRACT It is not understood what evolutionary factors drive some genes to be expressed at a higher level than others. Here, we hypothesized that a gene’s function plays an important role in setting expression level. First, we established that each S. cerevisiae gene is maintained at a specific expression level by analyzing RNA-seq data from multiple studies. Next, we found that mRNA and protein levels were maintained for the orthologous genes in S. pombe , showing that gene function, conserved in orthologs, is important in setting expression level. To further explore the role of gene function in setting expression level, we analyzed mRNA and protein levels of S. cerevisiae genes within gene ontology (GO) categories. The GO framework systematically defines gene function based on experimental evidence. We found that several GO categories contain genes with statistically significant expression extremes; for example, genes involved in translation or energy production are highly expressed while genes involved in chromosomal activities, such as replication and transcription, are weakly expressed. Finally, we were able to predict expression levels using GO information alone. We created and optimized a linear equation that predicted a gene’s expression based on the gene’s membership in 161 GO categories. The greater number of GO categories with which a gene is associated, the more accurately expression could be predicted. Taken together, our analysis systematically demonstrates that gene function is an important determinant of expression level.
Pair-rule gene
Transcription
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Yeast cells are surrounded by the cell wall, a rigid but dynamic structure that is essential for their viability. The complexity and functionality of this structure suggest that a high number of proteins must be involved in the biogenesis of the cell wall architecture and, as a consequence, in the maintenance of cell integrity. Among them, a high percentage is assumed to be located at the cell surface, mostly as structural or enzymatic components of the cell wall. Therefore, the presence of a protein in the cell wall is suggestive of its cell wall-related function. Different techniques can be used to specifically detect the cell wall localisation of a given protein or to identify cell wall proteins in large-scale analyses. These include the detection of proteins in whole cells or specific cell wall fractions by immunological, biochemical, microscopic, or genetic approaches, as well as the emerging proteomic technology. The advantages, limitations, and usefulness of these techniques are discussed and illustrated with some examples. Microsc. Res. Tech. 51:601–612, 2000. © 2000 Wiley-Liss, Inc.
Cell function
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Plasmodesma
Secondary cell wall
Cell plate
Plant cell
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Evolutionary rates provide important information about the pattern and mechanism of evolution. Although the rate of gene sequence evolution has been well studied, the rate of gene expression evolution is poorly understood. In particular, it is unclear whether the gene expression level and tissue specificity influence the divergence of expression profiles between orthologous genes. Here we address this question using a microarray data set comprising the expression signals of 10,607 pairs of orthologous human and mouse genes from over 60 tissues per species. We show that the level of gene expression and the degree of tissue specificity are generally conserved between the human and mouse orthologs. The rate of gene expression profile change during evolution is negatively correlated with the level of gene expression, measured by either the average or the highest level among all tissues examined. This is analogous to the observation that the rate of gene (or protein) sequence evolution is negatively correlated with the gene expression level. The impacts of the degree of tissue specificity on the evolutionary rate of gene sequence and that of expression profile, however, are opposite. Highly tissue-specific genes tend to evolve rapidly at the gene sequence level but slowly at the expression profile level. Thus, different forces and selective constraints must underlie the evolution of gene sequence and that of gene expression.
Molecular evolution
Sequence (biology)
Rate of evolution
Divergence (linguistics)
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Phthalonitrile
Half-reaction
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To study the genes differentially expressed in the liver of Kkay diabetic and normal mice by genomic-scale gene expression analysis.cDNA microarray chips containing 8,192 cDNAs were used to explore the gene expression pattern of Kkay mouse liver.One hundred and fifty-four genes were screened out, including 68 complete cDNAs and expressed sequence tags, and among them 40 genes were up-regulated and 114 genes were down-regulated respectively.Most of the gene expression analysis results were consistent with previous study, and the gene expression pattern of Kkay mouse based on cDNA microarray could be used for high-throughout screening out the genes associated with type 2 diabetes.
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Objective To analyze the differential gene expression profiling of liver in rats subjected to hemorrhagic shock(HS) and sham hemorrhage shock(SHAM) by gene chip technology, thus to evaluate the possible molecular pathogenesis of HS. Method 20 male Wistar rats were randomly divided into a SHAM group and a HS group, with 10 rats in each group. Hepatic gene expression profiles were detected by oligonucleotide microarrays of 5705 mouse genes in two groups for three times. Genes with ratio(R) > 2 were identified as up-regulated and R < 0.5 were identified as down-regulated. Biological function of differentially expressed genes was analyzed and 9 genes were selected to undergo semi-quantitative RT-PCR. Results Among the total 5705 probes detected,86 genes showed differential expression in HS group comparison with SHAM group. The expression levels of 72 genes were up-regulated while those of 14 genes were down-regulated significantly. Differentially expressed genes were classified according to their biological function: transport genes, transcription regulator genes, signaling genes, response to stress genes, metabolic genes, development genes and cell adhesion genes. Conclusions cDNA microarray is an efficient and high-throughout method to survey gene expression profiles in HS.The variation of those gene expressions might be a potential pathogenic mechanism for HS that may offer a novel target for further study of therapeutic strategies of HS.
Key words:
Hemorrhagic shock; DNA chip; Gene expression; liver
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Phthalonitrile
Half-reaction
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Secondary cell wall
Hemicellulose
Pectin
Plant cell
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