葡萄Actin基因家族的鉴定及进化和表达分析

采用生物信息学方法从葡萄(Vitis vinifera Linn.)全基因组中鉴定Actin基因家族,并对各基因的染色体定位和结构特征,编码蛋白质的理化性质、亚细胞定位、二级结构、三级结构和系统进化,以及不同组织的基因表达进行研究.结果表明:葡萄Actin基因家族16个基因分布在12条染色体上.16个基因的结构特征及其编码蛋白质的理化性质差异较大.16个基因的长度及其内含子总长度的变化范围较大,编码序列(CDS)和外显子总长度的变化范围较小.除登录号GSVIVG01008254001和GSVIVG01014035001的基因外,其他14个基因的GC含量均低于其CDS的GC含量.除登录号GSVIVG01008254001的基因外,其他15个基因编码的蛋白质的理论相对分子质量为12534.54~82612.33,理论等电点为pI 4.92~pI 9.13.16个基因编码蛋白质的消光系数为14105~73645,脂肪族氨基酸指数为65.54~92.06,其中9个为稳定蛋白,7个为不稳定蛋白.除登录号GSVIVG01014035001的基因外,其他15个基因编码的蛋白质均为亲水性蛋白.登录号GSVIVG01016517001的基因编码的蛋白质定位于细胞质和细胞核,其他15个基因编码的蛋白质定位于细胞质.二级结构和三级结构显示:葡萄Actin基因家族16个基因编码的蛋白质均由α螺旋、无规则卷曲和延伸链构成,且总体以无规则卷曲为主.系统进化分析和不同组织的基因表达分析结果显示:与拟南芥〔Arabidopsis thaliana(Linn.)Heynh.〕相似,葡萄Actin基因家族16个基因编码的蛋白质分为3个亚家族,ClassⅡ亚家族(营养型)包括登录号GSVIVG01003099001和GSVIVG01026580001的基因编码的蛋白质,这2个基因在所有组织中的表达均较高;ClassⅢ亚家族(生殖型)包括登录号GSVIVG01033494001、GSVIVG01024980001和GSVIVG01016550001的基因编码的蛋白质,这3个基因在花粉、雄蕊和花中的表达均较高;ClassⅠ亚家族包括其他11个基因编码的蛋白质,这11个基因在各组织中的表达总体上较低.研究结果显示:葡萄Actin基因家族的表达具有组织特异性.     

Genetic algorithms applied to multi-class clustering for gene expression data

A hybrid GA (genetic algorithm)-based clustering (HGACLUS) schema, combining merits of the Simulated Annealing, was described for finding an optimal or near-optimal set of medoids. This schema maximized the clustering success by achieving internal cluster cohesion and external cluster isolation. The performance     

真核基因的快速克隆及表达

以细胞间隙连接蛋白基因Cx26作为目的基因,通过T-A载体介导,构建真核表达重组载体pcDNA3.1( ) /Cx26,重组表达载体转染人鼻咽癌细胞株HNE1,表达Cx26间隙连接蛋白。     

Genetic basis of differential opsin gene expression in cichlid fishes

Visual sensitivity can be tuned by differential expression of opsin genes. Among African cichlid fishes, seven cone opsin genes are expressed in different combinations to produce diverse visual sensitivities. To determine the genetic architecture controlling these adaptive differences, we analysed genetic crosses between species expressing different complements of opsin genes. Quantitative genetic analyses suggest that expression is controlled by only a few loci with correlations among some genes. Genetic mapping identifies clear evidence of trans‐acting factors in two chromosomal regions that contribute to differences in opsin expression as well as one cis‐regulatory region. Therefore, both cis and trans regulation are important. The simple genetic architecture suggested by these results may explain why opsin gene expression is evolutionarily labile, and why similar patterns of expression have evolved repeatedly in different lineages.     

Genetic and functional properties of uncultivated thermophilic crenarchaeotes from a subsurface gold mine as revealed by analysis of genome fragments

Within a phylum Crenarchaeota, only some members of the hyperthermophilic class Thermoprotei, have been cultivated and characterized. In this study, we have constructed a metagenomic library from a microbial mat formation in a subsurface hot water stream of the Hishikari gold mine, Japan, and sequenced genome fragments of two different phylogroups of uncultivated thermophilic Crenarchaeota: (i) hot water crenarchaeotic group (HWCG) I (41.2 kb), and (ii) HWCG III (49.3 kb). The genome fragment of HWCG I contained a 16S rRNA gene, two tRNA genes and 35 genes encoding proteins but no 23S rRNA gene. Among the genes encoding proteins, several genes for putative aerobic-type carbon monoxide dehydrogenase represented a potential clue with regard to the yet unknown metabolism of HWCG I Archaea. The genome fragment of HWCG III contained a 16S/23S rRNA operon and 44 genes encoding proteins. In the 23S rRNA gene, we detected a homing-endonuclease encoding a group I intron similar to those detected in hyperthermophilic Crenarchaeota and Bacteria, as well as eukaryotic organelles. The reconstructed phylogenetic tree based on the 23S rRNA gene sequence reinforced the intermediate phylogenetic affiliation of HWCG III bridging the hyperthermophilic and non-thermophilic uncultivated Crenarchaeota.     

Gene expression profiling of human diseases by serial analysis of gene expression

Until recently, the approach to understanding the molecular basis of complex syndromes such as cancer, coronary artery disease, and diabetes was to study the behavior of individual genes. However, it is generally recognized that expression of a number of genes is coordinated both spatially and temporally and that this coordination changes during the development and progression of diseases. Newly developed functional genomic approaches, such as serial analysis of gene expression (SAGE) and DNA microarrays have enabled researchers to determine the expression pattern of thousands of genes simultaneously. One attractive feature of SAGE compared to microarrays is its ability to quantify gene expression without prior sequence information or information about genes that are thought to be expressed. SAGE has been successfully applied to the gene expression profiling of a number of human diseases. In this review, we will first discuss SAGE technique and contrast it to microarray. We will then highlight new biological insights that have emerged from its application to the study of human diseases.     

Biochemical and gene expression analyses of conotoxins in Conus textile venom ducts

Each Conus snail species produces 50-200 unique peptide-based conotoxins, derived from a number of different gene superfamilies. Conotoxins are synthesized and secreted in a long venom duct, but biochemical and molecular aspects of their biosynthesis remain poorly understood. Here, we analyzed expression patterns of conotoxin genes belonging to different superfamilies in Conus textile venom ducts. The results demonstrate that specific gene families are expressed in particular regions of the venom duct. Biochemical analysis using liquid chromatography and mass spectrometry revealed an even more localized accumulation of individual conotoxins. This study demonstrates for the first time that specialization of gene expression, processing, and secretion of conotoxins occurs in different regions of the venom duct.     

Unveiling network-based functional features through integration of gene expression into protein networks

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype–phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers.     

Evaluation of light regulatory potential of Calvin cycle steps based on large-scale gene expression profiling data

Although large-scale gene expression data have been studied from many perspectives, they have not been systematically integrated to infer the regulatory potentials of individual genes in specific pathways. Here we report the analysis of expression patterns of genes in the Calvin cycle from 95 Arabidopsis microarray experiments, which revealed a consistent gene regulation pattern in most experiments. This identified pattern, likely due to gene regulation by light rather than feedback regulations of the metabolite fluxes in the Calvin cycle, is remarkably consistent with the rate-limiting roles of the enzymes encoded by these genes reported from both experimental and modeling approaches. Therefore, the regulatory potential of the genes in a pathway may be inferred from their expression patterns. Furthermore, gene expression analysis in the context of a known pathway helps to categorize various biological perturbations that would not be recognized with the prevailing methods.     

Global analysis of gene expression by differential display

Differential display (DD) is one of the most commonly used approaches for identifying differentially expressed genes. However, there has been lack of an accurate guidance on how many DD polymerase chain reaction (PCR) primer combinations are needed to display most of the genes expressed in a eukaryotic cell. This study critically evaluated the gene coverage by DD as a function of the number of arbitrary primers, the number of 3′ bases of an arbitrary primer required to completely match an mRNA target sequence, the additional 5′ base match(s) of arbitrary primers in first-strand cDNA recognition, and the length of mRNA tails being analyzed. The resulting new DD mathematical model predicts that 80 to 160 arbitrary 13mers, when used in combinations with 3 one-base anchored oligo-dT primers, would allow any given mRNA within a eukaryotic cell to be detected with a 74% to 93% probability, respectively. The prediction was supported by both computer simulation of the DD process and experimental data from a comprehensive fluorescent DD screening for target genes of tumor-suppressor p53. Thus, this work provides a theoretical foundation upon which global analysis of gene expression by DD can be pursued.     

The role of the cell cycle in determining gene expression and productivity in CHO cells

Understanding the relationships between cell cycle and protein expression is critical to the optimisation of media and environmental conditions for successful commercial operation of animal cell culture processes. Using flow cytometry for the analysis of the early phases of synchronised batch cultures, the dependency of product expression on cell cycle related events has been evaluated in a recombinant CHO cell line. Although the production of recombinant protein is initially found to be cell cycle related, the maximum specific protein productivity is only achieved at a later stage of the exponential phase which also sees a maximum in the intracellular protein concentration. Subsequent work suggests that it is the batch phase/medium composition of cultures which is the major determinant of maximum specific productivity in this cell line. Furthermore the effect of the positive association between S phase and specific productivity is subordinate to the effect of batch phase/medium composition on the specific productivity of batch cultures. This revised version was published online in July 2006 with corrections to the Cover Date.     

Structure and expression of a root-specific rice gene

Two rice cDNA clones (COS6 and COS9) were isolated, corresponding to genes that were highly expressed in roots from seedlings and mature plants. A genomic clone (GOS9) corresponding to cDNA clone COS9 was isolated and the intron/exon structure was determined by comparing the nucleotide sequences of the mRNA and the genomic clone. 5 ends and 3 ends of the mRNA were determined by primer extension and S1-nuclease mapping respectively. The open reading frame present in GOS9 potentially encodes a protein (14kDa) that does not show any significant homology to other proteins in databases.     

Biological and functional analysis of statistically significant pathways deregulated in colon cancer by using gene expression profiles

Gene expression profiling offers a great opportunity for studying multi-factor diseases and for understanding the key role of genes in mechanisms which drive a normal cell to a cancer state. Single gene analysis is insufficient to describe the complex perturbations responsible for cancer onset, progression and invasion. A deeper understanding of the mechanisms of tumorigenesis can be reached focusing on deregulation of gene sets or pathways rather than on individual genes. We apply two known and statistically well founded methods for finding pathways and biological processes deregulated in pathological conditions by analyzing gene expression profiles. In particular, we measure the amount of deregulation and assess the statistical significance of predefined pathways belonging to a curated collection (Molecular Signature Database) in a colon cancer data set. We find that pathways strongly involved in different tumors are strictly connected with colon cancer. Moreover, our experimental results show that the study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. Our study shows the importance of using gene sets rather than single genes for understanding the main biological processes and pathways involved in colorectal cancer. Our analysis evidences that many of the genes involved in these pathways are strongly associated to colorectal tumorigenesis. In this new perspective, the focus shifts from finding differentially expressed genes to identifying biological processes, cellular functions and pathways perturbed in the phenotypic conditions by analyzing genes co-expressed in a given pathway as a whole, taking into account the possible interactions among them and, more importantly, the correlation of their expression with the phenotypical conditions.     

Regulation of gene expression by endogenous ABA in tomato plants

In response to water deficit, endogenous abscisic acid (ABA) accumulates in plants. This ABA serves as a signal for a multitude of processes, including regulation of gene expression. ABA accumulated in response to water deficit signals cellular as well as whole plant responses playing a role in the pattern of gene expression throughout the plant. Although the function of genes regulated by ABA during stress are currently poorly understood, a number of these genes may permit the plant to adapt to environmental stress.