Visualization of Differential Gene Expression – Using Fluorescence‐Based cDNA‐AFLP

cDNA‐AFLP is one of the techniques developed to study differentially expressed genes. This recent technique is advantageous because it does not need prior sequence knowledge and is reliable due to highly stringent PCR conditions. The traditional cDNA‐AFLP method uses radioactively labelled products and is characterised by high sensitivity and resolution. Here, the use of Cy5‐labelled primers to detect products on polyacrylamide gels is reported. This non‐radioactive method, based on fluorescence, is shown to be faster and the recovery of interesting bands is easier. The study of the differential gene expression of the interaction between potato and Phytophthora infestans was used for the valuation of this method. Different gene expression profiles – such as up‐regulation, down‐regulation or point expression – were obtained. Moreover, this technique was shown to be highly reproducible.     

Rotation gene set testing for longitudinal expression data

Gene set analysis methods are popular tools for identifying differentially expressed gene sets in microarray data. Most existing methods use a permutation test to assess significance for each gene set. The permutation test's assumption of exchangeable samples is often not satisfied for time‐series data and complex experimental designs, and in addition it requires a certain number of samples to compute p‐values accurately. The method presented here uses a rotation test rather than a permutation test to assess significance. The rotation test can compute accurate p‐values also for very small sample sizes. The method can handle complex designs and is particularly suited for longitudinal microarray data where the samples may have complex correlation structures. Dependencies between genes, modeled with the use of gene networks, are incorporated in the estimation of correlations between samples. In addition, the method can test for both gene sets that are differentially expressed and gene sets that show strong time trends. We show on simulated longitudinal data that the ability to identify important gene sets may be improved by taking the correlation structure between samples into account. Applied to real data, the method identifies both gene sets with constant expression and gene sets with strong time trends.     

结合基因功能分类体系Gene Ontology筛选聚类特征基因

使用两套基因表达谱数据,按各基因的表达值方差,选择表达变异基因对样本聚类,发现一般使用方差较大的前10％的基因作为特征基因,就可以较好地对疾病样本聚类。对不同的疾病,包含聚类信息的特征基因有不同的分布特点。在此基础上,结合基因功能分类体系(Gene Ontology,GO),进一步筛选聚类的特征基因。通过检验在Gene Ontology中的每个功能类中的表达变异基因是否非随机地聚集,寻找疾病相关功能类,再根据相关功能类中的表达变异基因进行聚类分析。实验结果显示：结合基因功能体系进一步筛选表达变异基因作为聚类特征基因,可以保持或提高聚类准确性,并使得聚类结果具有明确的生物学意义。另外,发现了一些可能和淋巴瘤和白血病相关的基因。     

Characterization of genes with tissue-specific differential expression patterns in Populus

Like many plants, Populus has an evolutionary history in which several, both recent and more ancient, genome duplication events have occurred and, therefore, constitutes an excellent model system for studying the functional evolution of genes. In the present study, we have focused on the properties of genes with tissue-specific differential expression patterns in poplar. We identified the genes by analyzing digital expression profiles derived by mapping 90,000+ expressed sequence tags (ESTs) from 18 sources to the predicted genes of Populus. Our sequence analysis suggests that tissue-specific differentially expressed genes have less diverged paralogs than average, indicating that gene duplication events is an important event in the pathway leading to this type of expression pattern. The functional analysis showed that genes coding for proteins involved in processes of functional importance for the specific tissue(s) in which they are expressed and genes coding for regulatory or responsive proteins are most common among the differentially expressed genes, demonstrating that the expression differentiation process is under strong selective pressure. Thus, our data supports a model where gene duplication followed by gene specialization or expansion of the regulatory and responsive networks leads to tissue-specific differential expression patterns. We have also searched for clustering of genes with similar expression pattern into gene-expression neighborhoods within the Populus genome. However, we could not detect any major clustering among the analyzed genes with highly specific expression patterns. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

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.     

A novel porcine gene, POT1, differentially expressed in the longissimus muscle tissues from Wujin and Large White pigs

The mRNA differential display technique was performed to investigate the differences of gene expression in the longissimus muscle tissues from Wujin and Large White pigs. One novel gene differentially expressed was identified through quantitative real time PCR and the cDNA complete sequence was then obtained using the rapid amplification of cDNA ends (RACE) method. The nucleotide sequence of the gene is not homologous to any of the known porcine genes. The sequence prediction analysis revealed that the open reading frame of this gene encodes a protein of 507 amino acids that shares high homology with the protection of telomeres 1 isoform 4 (POT1) of human (86%)-so that this gene can be defined as swine POT1 gene. This gene is structured in 12 exons and 11 introns as revealed by computer-assisted analysis. The tissue expression analysis indicated that the swine POT1 gene is differentially expressed in tissues including muscle, heart, liver, fat, kidney, lung, pancreas and spleen. Our experiment is the first to establish the primary foundation for further research on the swine POT1 gene.     

红莲优6号杂交水稻与亲本三系不同发育时期幼苗叶片基因表达差异分析

运用DDRT-PCR对红莲型杂交稻组合红莲优6号及其亲本、保持系（粤泰A、粤泰B、9311）的一叶期、三叶期叶片基因表达状况进行分析。结果表明：杂种与亲本之间在同一发育时期基因表达既有质量上又有数量上的差异,但差异表达基因所占比较较小;而对于同一材料,一叶期、三叶期的叶片cDNA扩增带型相似,没有发现基因质上的差异表达,说明一叶期与三叶期幼苗叶片基因表达差异很小。实验也证明DDRT-PCR技术结合银染方法是一种简单快速分析差异表达基因的有效方法。     

枯草芽孢杆菌寡聚—1，6—葡萄糖苷酶基因的克隆及其在大肠杆菌中的表达

本研究用鸟枪法构建了枯草芽孢杆菌（Bacillus subtilis)HB002的基因组文库,经平板法筛选得到了六株能水解合成底物对－硝基苯－α-D－葡萄糖吡喃糖苷的阳性克隆,经鉴定均含克隆了寡聚－1,6－葡萄糖苷酶基因的重组质粒（命名为pHBM001-pHBM006)。选择pHBM003,对其插入片段测序分析,此片段内有一编码561个氨基酸的开放阅读框,该 蛋白质的计算分子量为65.985kD。HB002的寡聚－1,6－葡萄糖苷酶的氨基酸序列与Bacillus sp.和凝结芽孢杆菌（Bacillus coagulans)的寡聚－1,6－葡萄糖苷酶的氨基酸序列一致性分别为81％、67％,相似性分别为89％、79％。从pHBM003中扩增出寡聚－1,6－葡萄糖苷酶基因,克隆到pBV220上,转化大肠杆菌（Escherichia coli)DH5α,得到三个能水解对－硝基苯－α－D－葡萄糖吡喃糖苷的阳性克隆HBM003－1～HBM003－3,将此三个菌株热诱导表达,SDS－PAGE电泳可检测到特异表达的蛋白质,其中HBM003－1、HBM003－2表达的蛋白约66kD,为完整的寡聚－1,6－葡萄糖苷酶,而HBM003－3表达的蛋白质偏小;表达的蛋白质均有寡聚－1,6－葡萄糖苷酶活性。     

利用生物信息学研究肥胖与2型糖尿病患者肝组织基因表达变化

目的:利用芯片数据分析工具对GEO基因芯片数据进行数据挖掘,系统分析肥胖与2型糖尿病患者肝组织相关基因表达的变化,探讨肥胖与2型糖尿病的联系及糖尿病早期预防和诊断的新靶点。方法:首先在公共芯片数据库中选择肥胖与2型糖尿病相关芯片数据(GSE15653),利用R等芯片数据分析工具分析肥胖与2型糖尿病患者肝组织基因的表达变化,并预测相关差异表达基因在血中蛋白表达。结果:肥胖患者与正常人肝组织比较发现412个差异表达基因,其中上调表达基因212个,下调表达基因200个,2型糖尿病患者中控制良好者与正常人肝组织比较发现486个差异表达基因,其中上调表达基因253个,下调表达基因233个,而2型糖尿病患者中控制不良者与正常人肝组织比较发现1051个差异表达基因,其中上调表达基因560个,下调表达基因491个;2型糖尿病控制良好者与肥胖患者肝组织有263个相同的表达变化基因,而2型糖尿病控制不良者与肥胖患者肝组织有131个相同的表达变化基因;结合蛋白质组学结果分析肥胖与2型糖尿病相关的差异表达基因中有30个蛋白表达产物是分泌型蛋白。结论:肥胖及2型糖尿病患者肝组织与正常肝组织比较基因表达均发生明显变化,其基因表达变化数目随疾病的严重性增加而增多,而且2型糖尿病的控制情况与肝组织基因表达变化有密切关系。肥胖与2型糖尿病相关的差异表达基因中表达分泌型蛋白的可进一步用于研发监测疾病发生发展的候选靶分子。     

Bayesian Hierarchical Modeling and Selection of Differentially Expressed Genes for the EST Data

Summary Expressed sequence tag (EST) sequencing is a one‐pass sequencing reading of cloned cDNAs derived from a certain tissue. The frequency of unique tags among different unbiased cDNA libraries is used to infer the relative expression level of each tag. In this article, we propose a hierarchical multinomial model with a nonlinear Dirichlet prior for the EST data with multiple libraries and multiple types of tissues. A novel hierarchical prior is developed and the properties of the proposed prior are examined. An efficient Markov chain Monte Carlo algorithm is developed for carrying out the posterior computation. We also propose a new selection criterion for detecting which genes are differentially expressed between two tissue types. Our new method with the new gene selection criterion is demonstrated via several simulations to have low false negative and false positive rates. A real EST data set is used to motivate and illustrate the proposed method.     

Analysis of gene expression in granulosa cells of ovine antral growing follicles using suppressive subtractive hybridization

Follicular growth, development and ovulation are highly ordered processes that involve the expression of many genes under precise temporal and spatial regulation. However, information on stage-specific gene expression during the antral follicle phase in sheep is not well understood. In the present study, suppressive subtractive hybridization (SSH) was performed to screen genes that were differentially expressed in the granulosa cells between large follicles (LF, >5 mm) and small follicles (SF, 3–5 mm), and subtractive cDNA library was constructed. Furthermore, with dot-blot analysis, a total of 90 clones randomly selected from the library were proven to be differentially expressed in the granulosa cells. Among these, 38 exhibited high homology to known genes, 14 sequences were corresponding to novel expressed sequence tags (ESTs). Four ESTs, LAPTM4A, SERPINE2, GSTA1, and INHBA, were further examined the reproducibility of the SSH data by the real-time quantitative PCR. Results confirmed an increase expression of respective mRNA in granulosa cells of large follicles compared with that of small follicles. It is concluded that we have identified several genes (known or unknown) that may effect follicular growth, dominance or ovulation in ewes.     

应用基因芯片筛选慢性乙型肝炎相关差异性基因

目的：应用基因芯片技术筛选不同病毒载量的慢乙肝病人及健康人差异性表达的基因。方法：选用含有48000位点的人类表达谱cDNA基因芯片,筛选4例慢乙肝病人与2例健康人外周血差异性表达的基因。结果：与健康人相比,慢乙肝患者有838个差异表达的基因,其中高表达的基因有150个,低表达的基因有688个。结论：用表达谱基因芯片可有效地研究高、低病毒载量的慢乙肝患者间,以及它们与健康人之间基因表达的差异,通过进一步分析有望筛选出与慢性乙型肝炎相关的新基因靶点。     

Affymetrix基因表达谱芯片在新疆维吾尔族与汉族胰腺癌组织样本间差异表达基因筛选中的运用

目的:运用基因表达谱芯片筛选并分析新疆维吾尔族与汉族胰腺癌组织样本间的差异表达基因。方法:收集我院2014年1月至2016年6月间行手术切除的维吾尔族与汉族胰腺导管细胞癌组织并提取总RNA,选取经Nanodrop 2000与Agilent 2100仪器质检合格的样本总RNA采用Affymetrix基因表达谱芯片筛选出差异表达基因并绘制统计图,运用基因本体(GO)分析及信号通路(Pathway)分析对这些差异表达基因的生物信息进行汇总分析。结果:通过基因表达谱芯片分析,新疆维吾尔族与汉族胰腺癌组织样本间共检测到1063个基因存在差异表达,在维吾尔族胰腺癌标本中显著上调表达的基因共281个,差异表达倍数最高的为IGLV1-44基因(差异倍数:9.99)下调表达的基因共782个,差异表达倍数最高的为CPB1基因(差异倍数:33.76);在Gene Ontology数据库中共检索到815个上述差异表达基因具有明确的GO分类,差异表达倍数最高的为CPB1基因(差异倍数:33.76);Pathway分析中共检测到30条信号通路包含有上述差异表达基因,共涉及196个基因,其中以FAK信号通路差异表达基因富集程度最高,差异表达倍数最高的基因为COL11A1基因(差异倍数:5.02)。结论:基因表达谱芯片分析结果显示,在新疆维吾尔族与汉族胰腺癌组织样本间存在大量的差异表达基因,这些基因与胰腺癌的增殖分化、侵袭转移及多药耐药等特性密切相关,且参与了多条生物体内重要信号转导通路的调控。     

应用基因表达谱芯片研究黄药子对小鼠肝脏的毒性机制(简报)

黄药子为薯蓣科植物黄独(Dioscorea bulbifera L．)的块茎,临床常用于治疗甲状腺肿、抗肿瘤、抗炎、抗病毒等。近年来临床上关于黄药子的毒副作用,尤其是对肝、肾的不良反应屡有报道。当黄药子或其代谢物在肝细胞内累积时会直接干扰肝细     

应用代表性差异分析法筛选人癌候选抑癌基因

运用cDNA代表性差异分析法(cDNA representational difference analysis,cDNA RDA),以正常人鼻咽上皮细胞及鼻咽癌HNE1细胞作为比较的样品来源,分离了四个在鼻咽癌中缺失的cDNA片段.以此四个片段作探针,分别进行DNA杂交、RNA杂交,结果显示,这些差异性的cDNA序列确实来自正常人鼻咽上皮且只在其中表达和/或在鼻咽癌HNE1中表达降低,并在鼻咽癌病人中存在不同程度的缺失.序列分析结果表明这些差异性表达的基因为具有相当抑癌基因功能的已知基因和可能与鼻咽癌相关的抑癌基因的新基因.从而说明cDNA RDA是一种高效、敏感、假阳性低的克隆抑癌基因的有效方法.     

Characterization of a human sphingosine-1-phosphate receptor gene (S1P5) and its differential expression in LGL leukemia

Large granular lymphocyte (LGL) leukemia is a lymphoproliferative disorder often associated with autoimmune disease. A central feature of this disease is dysregulation of apoptosis. In order to identify differentially expressed genes in LGL leukemia, microarray analysis was performed. We found many differentially expressed genes including several expression sequence tags (ESTs). As a systematic study, we selected one up-regulated EST (GenBank Accession number N47089) and further investigated. An LGL leukemia library was screened using this EST as a probe and a full-length sequence for a novel gene was identified. The deduced amino acid sequence revealed that the novel gene encodes a G-protein-coupled receptor gene that exhibits 86% identity with rat sphingosine-1-phosphate receptor (edg-8/nrg-1). This gene is present in brain, spleen, and peripheral blood mononuclear cells (PBMC) and is overexpressed in leukemic LGL.     

生长素介导OsRGP1和0sSuS参与水稻地上部基部向重性弯曲生长

在水稻幼苗被放平后,地上部重力响应部位（地上部基部）的上半部生长比下半部生长慢,从而导致地上部基部发生向上弯曲．发生不对称生长的向重性反应。通过抑制差减杂交（SSH）实验发现．水稻地上部基部向重性弯曲生长过程中,反复糖基化多肽OsRGP1和蔗糖合成酶OsSuS在基部上下部有不对称表达。我们还采用Realtime PCR开展进一步研究。实验结果显示OsRGP1和0sSMS的表达受到IAA的调控。通过生物信息学分析也发现OsRGPl和OsSuS的启动子上存在着生长素的调控元件．生长素极性运输抑制剂TIBA处理能够消除OsRGP1和OsSuS在向重性过程中的不对称表达．这进一步说明向重性过程中不对称分布的生长素介导了OsRGP1和OsSuS基因的不对称表达。另外．向重性反应过程中,检测到基部下半部的己糖浓度增加。因此,OsRGP1的不对称表达可能有助于下半部细胞壁多糖的积累,进而促进了下半部细胞壁的扩张。OsSuS不对称表达也有可能会引起己糖在上下半部的不对称分布。己糖和细胞壁多糖在下半部的积累可能在下部细胞扩张从而导致向重性弯曲生长中起一定的作用。