基因捕捉及其在植物基因分离和功能基因组学上的应用

基因捕捉是一种报告基因的随机整合技术。基因捕捉系统已成为分离基因、鉴定基因功能的重要手段。基因捕捉(gene traps)包括增强子捕捉(enhancer trap)、启动子捕捉(promoter trap)和基因捕捉(gene trap),通称为基因捕捉(gcne traps)。在增强子捕捉中,报告基因与一个基本启动子融合,这个启动子不能使报告基因表达,但可被临近的增强子激活。在启动子捕捉和基因捕捉中,报告基因的启动子被去除,融合基因只有以正确的方向插入到转录单元内才能表达。对基因捕捉系统的结构特征、构建方法、应用范围、研究现状和应用前景等作了系统论述,并对有关问题进行了讨论。     

Identifying Gene Interaction Enrichment for Gene Expression Data

Gene set analysis allows the inclusion of knowledge from established gene sets, such as gene pathways, and potentially improves the power of detecting differentially expressed genes. However, conventional methods of gene set analysis focus on gene marginal effects in a gene set, and ignore gene interactions which may contribute to complex human diseases. In this study, we propose a method of gene interaction enrichment analysis, which incorporates knowledge of predefined gene sets (e.g. gene pathways) to identify enriched gene interaction effects on a phenotype of interest. In our proposed method, we also discuss the reduction of irrelevant genes and the extraction of a core set of gene interactions for an identified gene set, which contribute to the statistical variation of a phenotype of interest. The utility of our method is demonstrated through analyses on two publicly available microarray datasets. The results show that our method can identify gene sets that show strong gene interaction enrichments. The enriched gene interactions identified by our method may provide clues to new gene regulation mechanisms related to the studied phenotypes. In summary, our method offers a powerful tool for researchers to exhaustively examine the large numbers of gene interactions associated with complex human diseases, and can be a useful complement to classical gene set analyses which only considers single genes in a gene set.     

利用套叠PCR技术进行基因突变和拼接

利用套叠PCR技术（又称重叠区扩增基因拼接法）对hGM-CSF基因内第28位氨基酸处的糖基化位点进行突变和进行人促性腺激素基因,腺苷酸激酶短肽与胰岛素样生长因子－基因三者之间的拼接,结果表明采用该技术能在体外实行有效的基因重组和定点突变,其成功率为100％,这一技术不需要内切酶消化和连接酶处理,技术操作员简单易行,在基因拼接,基因内部突变方面具有良好的应用价值。     

转基因海带的研究现状

海带是海洋中一种极其重要的经济海藻。转基因技术在海带科研中的应用,将使海带的附加值得到进一步的提高。就海带遗传转化方法,以及转GUS基因、转lacZ基因、转CAT基因、转bar基因等报告基因和转HBsAg基因、转r-PA基因等功能基因海带的研究现状进行了综述。     

Pinaceae show elevated rates of gene turnover that are robust to incomplete gene annotation

Gene duplications and gene losses are major determinants of genome evolution and phenotypic diversity. The frequency of gene turnover (gene gains and gene losses combined) is known to vary between organisms. Comparative genomic analyses of gene families can highlight such variation; however, estimates of gene turnover may be biased when using highly fragmented genome assemblies resulting in poor gene annotations. Here, we address potential biases introduced by gene annotation errors in estimates of gene turnover frequencies in a dataset including both well‐annotated angiosperm genomes and the incomplete gene sets of four Pinaceae, including two pine species, Norway spruce and Douglas‐fir. We show that Pinaceae experienced higher gene turnover rates than angiosperm lineages lacking recent whole‐genome duplications. This finding is robust to both known major issues in Pinaceae gene sets: missing gene models and erroneous annotation of pseudogenes. A separate analysis limited to the four Pinaceae gene sets pointed to an accelerated gene turnover rate in pines compared with Norway spruce and Douglas‐fir. Our results indicate that gene turnover significantly contributes to genome variation and possibly to speciation in Pinaceae, particularly in pines. Moreover, these findings indicate that reliable estimates of gene turnover frequencies can be discerned in incomplete and potentially inaccurate gene sets. Because gymnosperms are known to exhibit low overall substitution rates compared with angiosperms, our results suggest that the rate of single‐base pair mutations is uncoupled from the rate of large DNA duplications and deletions associated with gene turnover in Pinaceae.     

In vitro binding of the bacteriophage f1 gene V protein to the gene II RNA-operator and its DNA analog.

We have investigated the binding of the f1 single-stranded DNA-binding protein (gene V protein) to DNA oligonucleotides and RNA synthesized in vitro. The first 16 nucleotides of the f1 gene II mRNA leader sequence were previously identified as the gene II RNA-operator; the target to which the gene V protein binds to repress gene II translation. Using a gel retardation assay, we find that the preferential binding of gene V protein to an RNA carrying the gene II RNA-operator sequence is affected by mutations which abolish gene II translational repression in vivo. In vitro, gene V protein also binds preferentially to a DNA oligonucleotide whose sequence is the DNA analog of the wild-type gene II RNA-operator. Therefore, the gene V protein recognizes the gene II mRNA operator sequence when present in either an RNA or DNA context.     

The problem of the gene

During the early 20th century the diverse practices of genetics were unified by the concept of the gene. This classical gene was simultaneously a unit of structure, function, mutation, and recombination. Starting in the 1940s, however, the classical gene began to fragment. Today when we speak of a gene for some malady, a regulatory gene, a structural gene, or a gene frequency, it is entirely possible that we are deploying different gene concepts even though we are using the same term. The problem of the gene addresses the fragmentation of the classical gene concept by asking to what extent a comprehensive and unifying gene concept is possible or desirable. Fully comprehensive gene concepts seem untenable today, but, within different disciplinary domains, unifying, but non-comprehensive, gene concepts can be epistemically worthwhile. The problem of the gene persists, however, not because of its epistemic value, but because of its political value. Using both the arguments for newly proposed gene concepts and the historical dispute over the classical gene, I argue that the desirability of gene concepts rests in part on the political ramifications of their deployment and contestation.     

Evolutionary significance of gene expression divergence

Recent large-scale studies of evolutionary changes in gene expression among mammalian species have led to the proposal that gene expression divergence may be neutral with respect to organismic fitness. Here, we employ a comparative analysis of mammalian gene sequence divergence and gene expression divergence to test the hypothesis that the evolution of gene expression is predominantly neutral. Two models of neutral gene expression evolution are considered: 1-purely neutral evolution (i.e., no selective constraint) of gene expression levels and patterns and 2-neutral evolution accompanied by selective constraint. With respect to purely neutral evolution, levels of change in gene expression between human-mouse orthologs are correlated with levels of gene sequence divergence that are determined largely by purifying selection. In contrast, evolutionary changes of tissue-specific gene expression profiles do not show such a correlation with sequence divergence. However, divergence of both gene expression levels and profiles are significantly lower for orthologous human-mouse gene pairs than for pairs of randomly chosen human and mouse genes. These data clearly point to the action of selective constraint on gene expression divergence and are inconsistent with the purely neutral model; however, there is likely to be a neutral component in evolution of gene expression, particularly, in tissues where the expression of a given gene is low and functionally irrelevant. The model of neutral evolution with selective constraint predicts a regular, clock-like accumulation of gene expression divergence. However, relative rate tests of the divergence among human-mouse-rat orthologous gene sets reveal clock-like evolution for gene sequence divergence, and to a lesser extent for gene expression level divergence, but not for the divergence of tissue-specific gene expression profiles. Taken together, these results indicate that gene expression divergence is subject to the effects of purifying selective constraint and suggest that it might also be substantially influenced by positive Darwinian selection.     

肿瘤基因治疗的研究进展

肿瘤是严重影响人类身体健康的重大疾病之一,肿瘤的发生发展是一个复杂的涉及到众多基因的过程,肿瘤的基因治疗也已经成为肿瘤治疗的研究热点之一。目前,肿瘤基因治疗的策略主要包括以下几个方面:基因沉默治疗、抑癌基因治疗、免疫基因治疗、自杀基因疗法、抑制肿瘤血管生成基因治疗、肿瘤多药耐药基因治疗、抗端粒酶疗法和多基因联合疗法等。我们简要地对上述策略及相关研究进展进行综述。     

当前肿瘤基因治疗中存在的主要问题及其解决途径

本文概述了当前肿瘤基因治疗研究中存在的一些主要问题,如绝大多数治疗方案中目的基因只有一个,肿瘤基因治疗缺乏靶向性,基因转移载体的效率、安全性及容量等问题。讨论了解决这些问题的主要途径,即肿瘤多基因联合治疗、直接体内途径基因治疗与靶向基因治疗、基因转移载体的改造。     

转基因植物中外源基因的沉默及应对策略

随着转基因技术在作物育种领域的应用,转基因植物中外源基因表达量低的现象较为普遍。导致外源基因表达量低的主要原因是基因沉默。外源基因沉默可分为转录水平的基因沉默和转录后水平的基因沉默。如何应对基因沉默,提高外源基因的表达量,是转基因技术发展亟待解决的问题。     

大绿蛙Sox基因和Dmrt基因的序列分析

Sox基因家族与Dmrt基因家族在胚胎发育及性别分化中起着重要作用。采用PCR方法,扩增了大绿蛙Sox基因和Dmrt基因的保守区,分别获得长约220 bp和140 bp的片段。序列分析表明,大绿蛙雌雄个体之间Sox基因、Dmrt基因序列没有差异,与人和其它动物的Sox基因、Dmrt基因有非常高的相似性,显示了Sox基因及Dmrt基因在系统进化上的高度保守性。本研究为探讨大绿蛙的性别决定机制及Sox基因与Dmrt基因的进化提供了分子资料。     

Evolution of mercuric reductase (<Emphasis Type="Italic">merA</Emphasis>) gene: A case of horizontal gene transfer

In the present study the role of horizontal gene transfer events in providing the mercury resistance is depicted. merA gene is key gene in mer operon and has been used for this swtudy. Phylogenetic analysis of aligned merA gene sequences shows broad similarities to the established 16S rRNA gene phylogeny. But there is no separation of bacterial merA gene from archael merA gene which suggests that merA gene in both these groups share considerable sequence homology. However, inconsistencies between merA gene and 16S rRNA gene phylogenetic trees are apparent for some taxa. These discrepancies in the phylogenetic trees for merA gene and 16S rRNA gene have lead to the suggestion that horizontal gene transfer (HGT) is a major contributor for its evolution. The close association among members of different groups in merA gene tree, as supported by high bootstrap values, deviations in GC content and codon usage pattern indicate the possibility that horizontal gene transfer events might have taken place during the evolution of this gene.     

Effect of FAK, DLC-1 gene expression on OVCAR-3 proliferation

The study investigates the effect of FAK, DLC-1 on OVCAR-3 proliferation. FAK gene siRNA vector recombinant plasmid was constructed using RNA interference technique. FAK gene-transfected OVCAR-3 cells, OVCAR-3 cells with DLC-1 gene expression, and OVCAR-3 cells with simultaneous expression of DLC-1 and FAK genes were obtained using gene transfection technology. In addition, siRNA control group and blank control were also given. Effect of FAK, DLC-1 gene expression on OVCAR-3 proliferation was examined by FCM and Cell Counting Kit-8 (CCK-8) methods. Results showed that DLC-1 gene high expression and FAK gene silencing, single silencing FAK gene, and single DLC-1 gene high expression in OVCAR-3 cells may decrease S and G2/M phase proportion of the cell cycle. Moreover, DLC-1 gene high expression and FAK gene silencing in OVCAR-3 cells can display the most significant effect. This confirmed that DLC-1 gene high expression and FAK gene silencing may significantly inhibit the OVCAR-3 cells proliferation. CCK-8 analysis showed that silence FAK gene exprssion or/and increasing DLC-1 gene expression may decrease OVCAR-3 growth rate. Moreover, simultaneous silence the exprssion of FAK gene and high expression of DLC-1 gene can display the most significant effect on OVCAR-3 growth. It can be concluded that downregulation of FAK gene expression or/and upregulation of DLC-1 gene expression can all inhibit the OVCAR-3 growth. Moreover, DLC-1 gene expression and FAK gene silencing can display the most marked inhibitory effect on the OVCAR-3 growth.     

From gene trees to species trees II: species tree inference by minimizing deep coalescence events

When gene copies are sampled from various species, the resulting gene tree might disagree with the containing species tree. The primary causes of gene tree and species tree discord include incomplete lineage sorting, horizontal gene transfer, and gene duplication and loss. Each of these events yields a different parsimony criterion for inferring the (containing) species tree from gene trees. With incomplete lineage sorting, species tree inference is to find the tree minimizing extra gene lineages that had to coexist along species lineages; with gene duplication, it becomes to find the tree minimizing gene duplications and/or losses. In this paper, we present the following results: 1) The deep coalescence cost is equal to the number of gene losses minus two times the gene duplication cost in the reconciliation of a uniquely leaf labeled gene tree and a species tree. The deep coalescence cost can be computed in linear time for any arbitrary gene tree and species tree. 2) The deep coalescence cost is always not less than the gene duplication cost in the reconciliation of an arbitrary gene tree and a species tree. 3) Species tree inference by minimizing deep coalescence events is NP-hard.     

基因治疗心肌缺血的载体应用新进展

近年来,随着基因治疗技术的不断进步,为心肌缺血的治疗开辟了一条全新的途径,并取得了一些令人鼓舞的进展。基因治疗主要包括治疗基因、基因转移载体以及基因导入途径三个方面。基因转移载体又在治疗基因和基因表达之间起着桥梁作用,因此,发展安全、高效的基因转移系统是基因治疗的关键之一。目前用于基因治疗心肌缺血基因转移的载体主要有病毒载体和非病毒载体。下面将就不同载体在心肌缺血的基因治疗中的应用进展进行简要的总结。     

Use of gene networks for identifying and validating drug targets

We propose a new method for identifying and validating drug targets by using gene networks, which are estimated from cDNA microarray gene expression profile data. We created novel gene disruption and drug response microarray gene expression profile data libraries for the purpose of drug target elucidation. We use two types of microarray gene expression profile data for estimating gene networks and then identifying drug targets. The estimated gene networks play an essential role in understanding drug response data and this information is unattainable from clustering methods, which are the standard for gene expression analysis. In the construction of gene networks, we use the Bayesian network model. We use an actual example from analysis of the Saccharomyces cerevisiae gene expression profile data to express a concrete strategy for the application of gene network information to drug discovery.     

Multi-Edge Gene Set Networks Reveal Novel Insights into Global Relationships between Biological Themes

Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstalk, is often underutilized. A gene set network, where nodes representing individual gene sets such as KEGG pathways are connected to indicate a functional dependency, is well suited to visualize and analyze global gene set relationships. Here we introduce a novel gene set network construction algorithm that integrates gene lists derived from high-throughput experiments with curated gene sets to construct co-enrichment gene set networks. Along with previously described co-membership and linkage algorithms, we apply the co-enrichment algorithm to eight gene set collections to construct integrated multi-evidence gene set networks with multiple edge types connecting gene sets. We demonstrate the utility of approach through examples of novel gene set networks such as the chromosome map co-differential expression gene set network. A total of twenty-four gene set networks are exposed via a web tool called MetaNet, where context-specific multi-edge gene set networks are constructed from enriched gene sets within user-defined gene lists. MetaNet is freely available at http://blaispathways.dfci.harvard.edu/metanet/.