基于PCR的基因差异表达分析技术

基因差异表达分析是研究许多生物学过程的分子基础的一条直接、有效的途径。自DDRT-PCR技术建立以来,一系列基于PCR的基因差异表达分析技术,如SAGE、SSH、RDA和DNA微阵列等相继发展起来,为分析和克隆差异表达的基因提供了更为快速、灵敏的工具。本对这几种方法进行了简要综述,比较了不同方法的优缺点,并展望了今后基因差异表达研究技术的发展方向。     

基因表达差异显示分析技术在创伤研究中的应用

基因是细胞增殖,分化,成熟等各项生命活动的调控中心,也是许多痢疾发生,发展和转归的决定性因素。基因表达的变化必然导致细胞,组织,器官乃至整个机体的各种异常。包括创伤在内的各种内外刺激,都可不同程度地引起基因表达的变化,最终妨碍机体健康。随着生物信息学的逐渐兴起和分子生物学的不断发展并向其他学科的逐渐渗透,业已建立起一系列研究基因表达变化的切实可行的技术手段（即“基因表达差异分析技术”,如DNA微阵列）,对捕获基因表达的种种变化具有重要价值。这些技术已经在肿瘤及其他疾病的研究中得到广泛应用,近几年也逐渐进入创伤研究领域,在一定程度上推动了创伤研究的发展。     

Phytochrome regulation of nuclear gene expression in plants

The photoregulation of gene expression in higher plants was extensively studied during the 1980s, in particular the light-responsive cis -acting elements and trans -acting factors of the Lhcb and rbcS genes. However, little has been discovered about: (1) which plant genes are regulated by light, and (2) which photoreceptors control the expression of these genes. In the 1990s, the functional analysis of the various photoreceptors has progressed rapidly using photoreceptor-deficient mutants, including those of the phytochrome gene family. More recently however, advanced techniques for gene expression analysis, such as fluorescent differential display and DNA microarray technology, have become available enabling the global identification of genes that are regulated by particular photoreceptors. In this paper we describe distinct and overlapping effects of individual phytochromes on gene expression in Arabidopsis thaliana.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, “RFE_Relief algorithm” was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

苹果绵蚜在苹果树上空间分布型的研究

采用6种空间分布型聚集度指标,测楚了苹果绵蚜在苹果树新梢、侧枝、树干(环剥处)和根部的空间分布型。结果表明均呈聚集分布,据此提出了适宜的调查取样技术。     

Differential gene expression in liver of inbred chickens and their hybrid offspring

Differential display of mRNA was used to analyse the differences of gene expression in liver between chicken hybrids and their parents in a 4 x 4 diallel crosses in order to study the molecular basis of heterosis in chickens. The results indicated that patterns of gene expression in hybrids differ significantly from their parents. Four patterns of differential gene expression were revealed, which included: (i) bands only detected in the hybrid F1s (UNF1); (ii) bands only absent in the hybrid F1s (ABF1); (iii) bands only detected in the parental P1 or P2 lines (UNP1 and UNP2) and (iv) bands absent in the parental P1 or P2 lines (ABP1 and ABP2). In addition, correlations between patterns of gene expression and heterosis percentages of nine carcass traits of 8-week-old chickens were evaluated. Statistical results showed that negative correlations between heterosis percentages and the percentage of F1-specific bands (UNF1) were significant at P < 0.01 for breast muscle yield, leg muscle yield, wing weight, eviscerated weight and eviscerated weight with giblet of 8-week-old chickens, and at P < 0.05 for intermuscular fat width. Heterosis percentage was negatively correlated with ABP (bands present in the hybrid F1s and one parental line but absent in the other parental line, ABP1 and ABP2) for breast muscle yield, leg muscle yield, wing weight, eviscerated weight and eviscerated weight with giblet of 8-week-old chickens (P < 0.01). Bands detected only in the hybrid F1s but not in either of the parental lines (UNF1) and bands absent in parental P1 or P2 lines (which includes ABP1 and ABP2) may play important roles in chicken heterosis.     

基因差异表达与杂种优势形成机制探讨

对杂种优势这一普遍而重要的生物学现象研究虽有百余年的历史, 但其根本机理尚未阐述清楚。继基因组组成差异及基因效应研究之后, 基因表达差异成为探寻杂种优势分子机理新的切入点。旨在通过揭示杂种中等位基因差异表达、杂种与亲本间基因差异表达的调控机制, 来认识杂种优势形成的分子机理, 从而达到指导育种实践的目的。文章概述了杂种等位基因差异表达现象及其产生机理, 总结了杂种与亲本相比所呈现出的加性、显性和超显性等多种差异基因表达模式, 归纳了表达谱研究筛选出的与杂种优势形成有关的基因, 以及某些关键生化代谢途径对杂种优势形成的贡献。但由于杂种优势机理的复杂性, 基因表达研究并没有得出统一的表达模式, 大多数杂种优势基因也不能被归属为同一类别。尽管如此, 基因表达谱研究毕竟迈出了解析杂种优势形成复杂基因表达网络的第一步, 随着表达谱技术和生物信息学的不断更新和发展, 杂种优势形成的分子机理有望在基因表达层面上取得突破。     

金针菇单、双核菌丝差异表达基因分析

对金针菇Flammulina velutipes单核菌丝W23的菌丝体以及与L11质配后的双核菌丝H1123菌丝体进行了转录组测序,以本实验室已获得的W23基因组为参考基因组研究两样本间差异基因,并对这些差异基因进行了GO功能和Pathway显著性富集分析。差异基因分析显示,两个样本中共有显著性差异表达的基因3 504个,其中在双核菌丝中上调、下调的基因数分别为2 151和1 353个。研究发现差异表达基因含有很多的转录因子基因、蛋白激酶以及WD40 repeat-like蛋白。Gene Ontology（GO）功能分析结果表明,extracellular region和membrane-enclosed lumen条目下的差异基因全部为上调表达,而envelope下的差异基因全部为下调表达,以利于双核菌丝分裂时锁状联合的形成而便于核的迁移。Pathway 功能富集分析结果表明,脂肪酸、氨基酸以及大部分糖类合成相关基因具有比较活跃的上调表达。说明双核菌丝主要进行营养物质的富集,为下一步在合适条件下分化成原基,进入生殖生长阶段储备物质基础。     

苹果柠檬酸合酶3基因家族成员鉴定及表达分析

柠檬酸合酶(citrate synthase 3, CS3)是细胞代谢途径中的关键酶之一,其活性调节着生物体的物质和能量代谢过程。本研究旨在从苹果全基因组中鉴定CS3基因家族成员,并进行生物信息学和表达模式分析,为研究苹果CS3基因的潜在功能提供理论基础。利用BLASTp基于GDR数据库鉴定苹果CS3家族成员,通过Pfam、SMART、MEGA5.0、clustalx.exe、ExPASy Proteomics Server、MEGAX、SOPMA、MEME和WoLF PSORT等软件分析CS3蛋白序列基本信息、亚细胞定位情况、结构域组成、系统进化关系以及染色体定位情况。利用酸含量的测定和实时荧光定量PCR (real-time fluorescence quantitative polymerase chain reaction, qRT-PCR)技术检测苹果6个CS3的组织表达和诱导表达特性。苹果CS3基因家族包含6个成员,这些CS3蛋白包括473−608个不等的氨基酸残基,等电点分布在7.21−8.82。亚细胞定位结果显示CS3蛋白分别定位在线粒体和叶绿体。系统进化分析可将其分为3类,各亚家族基因数量分别为2个。染色体定位结果显示,CS3基因分布在苹果不同的染色体上。蛋白二级结构以a-螺旋为主,其次是无规则卷曲,b-转角所占比例最小。筛选的6个家族成员在不同苹果组织中均有表达,整体表达趋势从高到低依次为MdCS3.4相对表达含量最高,MdCS3.6次之,其他家族成员相对表达量依次为MdCS3.3>MdCS3.2>MdCS3.1>MdCS3.5。qRT-PCR结果显示,MdCS3.1和MdCS3.3基因在酸含量较低的‘成纪1号’果肉中相对表达量最高,酸含量较高的‘艾斯达’果肉中MdCS3.2和MdCS3.3基因相对表达量最高。因此,本研究对不同苹果品种中CS3基因相对表达量进行了检测,并分析了其在苹果果实酸合成过程中的作用。结果表明,CS3基因在不同苹果品种中的相对表达量存在差异,为后续研究苹果品质形成机制提供了参考。     

Normalization and quantification of differential expression in gene expression microarrays

Array-based gene expression studies frequently serve to identify genes that are expressed differently under two or more conditions. The actual analysis of the data, however, may be hampered by a number of technical and statistical problems. Possible remedies on the level of computational analysis lie in appropriate preprocessing steps, proper normalization of the data and application of statistical testing procedures in the derivation of differentially expressed genes. This review summarizes methods that are available for these purposes and provides a brief overview of the available software tools.     

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.     

Relationships of differential gene expression in leaves with heterosis and heterozygosity in a rice diallel cross

Using differential display analysis, we assessed the patterns of differential gene expression in hybrids relative to their parents in a diallel cross involving 8 elite rice lines. The analysis revealed several patterns of differential expression including: (1) bands present in one parent and F₁ but absent in the other parent, (2) bands observed in both parents but not in the F₁, (3) bands occurring in only one parent but not in the F₁ or the other parent, and, (4) bands detected only in the F₁ but in neither of the parents. Relationships between differential gene expression and heterosis and marker heterozygosity were evaluated using data for RFLPs, SSRs and a number of agronomic characters. The analysis showed that there was very little correlation between patterns of differential expression and the F₁ means for all six agronomic traits. Differentially expressed fragments that occurred only in one parent but not in the other parent or in F₁ in each of the respective crosses were positively correlated with heterosis and heterozygosity. And conversely, fragments that were detected in F₁s but in neither of the respective parents were negatively correlated with heterosis and heterozygosity. The remaining patterns of differential expression were not correlated with heterosis or heterozygosity. The relationships between the patterns of differential expression and heterosis observed in this study were not consistent with expectations based on dominance or overdominance hypotheses.     

Differential gene expression during somatic embryogenesis in Coffea arabica L., revealed by RT-PCR differential display

Molecular and biochemical studies of somatic embryogenesis may help to shed light on the mechanisms governing this phenomenon. In this article, a differential display analysis approach was employed to investigate the changes taking place during the induction of somatic embryogenesis in leaf explants and suspension cultures of coffee. Cloned fragments show homologies to several proteins reported in databases, but only one has previously been described as regulated during somatic embryogenesis. By a reverse dot blot modification, the expression pattern of such fragments was evaluated.