筛选差异表达基因方法的新进展

了解不同细胞或同类细胞在不同发育阶段、不同生理状态下的基因表达状况,可以为研究生命活动过程提供重要信息。以差别筛选、削减杂交等基本方法为出发点,研究基因表达差异的方法不断完善,先后出现了DDRT—PCR、RDA、SSH、cDNA微阵列(基因芯片)、基因表达的系统分析(SAGE)等技术。本着重对这些方法的优缺点及改进进行论述和评介,并对技术的发展趋势进行了分析。     

Identification of differentially expressed genes using multi-resolution wavelet transformation analysis combined with SAM

Although many statistical methods have been proposed for identifying differentially expressed genes, the optimal approach has still not been resolved. Therefore, it is necessary to develop more efficient methods of finding differentially expressed genes while accounting for noise and false discovery rate (FDR). We propose a method based on multi-resolution wavelet transformation analysis combined with SAM for identifying differentially expressed genes by adjusting the Δ and computing the FDR. This method was applied to a microarray expression dataset from adenoma patients and normal subjects. The number of differentially expressed genes gradually reduced with an increasing Δ value, and the FDR was reduced after wavelet transformation. At a given Δ value, the FDR was also reduced before and after wavelet transformation. In conclusion, a greater number and quality of differentially expressed genes were detected using the method when compared to non-transformed data, and the FDRs were notably more controlled and reduced.     

从microarray时序表达数据识别周期表达基因

根据周期表达基因的周期性和峰值特点,提出了一种将microarray时序表达数据划分为若干个基因表达周期,并对周期内的峰值特点进行评估以识别周期表达基因的方法,能有效减小microarray实验时的噪声干扰。选取了三组广泛使用的时序表达数据和一组可靠的周期表达基因集合对该方法的效果进行了测试,并与三种典型的周期表达基因识别方法的效果进行了比较。该方法能有效地从各种microarray时序表达数据中识别周期表达基因。     

Identification of differentially expressed genes related to metabolic syndrome induced with high-fat diet in E3 rats

Understanding the genes differentially expressing in aberrant organs of metabolic syndrome (MetS) facilitates the uncovering of molecular mechanisms and the identification of novel therapeutic targets for the disease. This study aimed to identify differentially expressed genes related to MetS in livers of E3 rats with high-fat-diet-induced metabolic syndrome (HFD-MetS). E3 rats were fed with high-fat diet for 24 weeks to induce MetS. Then, suppression subtractive hybridization (SSH) technology was used to identify the genes differentially expressed between HFD-MetS and control E3 rat livers. Twenty positive recombinant clones were chosen randomly from forward subtractive library and sent to sequence. BLAST analysis in GenBank database was used to determine the property of each cDNA fragment. In total, 11 annotated genes, 3 ESTs, and 2 novel gene fragments were identified by SSH technology. The expression of four genes (Alb, Pip4k2a, Scd1, and Tf) known to be associated with MetS and other five genes (Eif1, Rnase4, Rps12, Rup2, and Tmsb4) unknown to be relevant to MetS was significantly up-regulated in the livers of HFD-MetS E3 rats compared with control rats using real-time quantitative PCR (RT-qPCR). By analyzing the correlations between the expression of these nine genes and serum concentrations of TG, Tch, HDL-C, and LDL-C, we found that there were significant positive correlations between TG and the expression of five genes (Alb, Eif1, Pip4k2a, Rps12, and Tmsb4x), Tch and three genes (Rnase4, Scd1, and Tmsb4x), and LDL-C and two genes (Rnase4 and Scd1), as well there were significant negative correlations between HDL-C and the expression of three genes (Rup2, Scd1, and Tf). This study provides important clues for unraveling the molecular mechanisms of MetS.     

基于RNA-Seq技术分析在金属矿上部生长的芒萁的差异表达基因

以生长于广西大厂锡多金属矿上部(重金属胁迫区)和未受矿化或污染影响的矿区外围(对照区)的芒萁〔Dicranopteris pedata(Houtt.)Nakaike〕为实验材料,对芒萁叶片进行转录组高通量测序,并对组装得到的unigenes经NCBI官方非冗余蛋白质序列数据库(Nr)、NCBI官方非冗余核苷酸序列数据库(Nt)、KEGG直系同源数据库(KO)、Swiss-Prot数据库(Swiss-Prot)、蛋白质家族数据库(Pfam)、基因功能分类体系数据库(GO)和真核生物直系同源序列数据库(KOG)进行注释,同时分析重金属胁迫区和对照区芒萁叶片间的差异表达unigenes.结果显示:测序获得19.56 Gb clean data,其中,重金属胁迫区和对照区芒萁叶片分别含10.14和9.42 Gb clean data.组装得到的250582个unigenes中有120097个unigenes得到注释,占unigenes总数的47.93%.与对照区相比较,重金属胁迫区芒萁叶片中上调和下调差异表达unigenes分别有208和620个,其中120个上调差异表达unigenes注释为代谢过程,占所有上调差异表达unigenes的57.69%;285个下调差异表达unigenes注释为催化活性,占所有下调差异表达unigenes的45.97%.重金属胁迫区芒萁叶片中15个unigenes与重金属转运和耐受相关,其中c44988 g1和c84121 g1的相对表达量分别极显著和显著高于对照区.研究结果显示:芒萁响应自然金属矿化或矿山重金属污染的基因可以用于生物地球化学找矿和土壤重金属污染检测.     

Probing differentially expressed genes against a microarray database for in silico suppressor/enhancer and inhibitor/activator screens

High-density oligonucleotide arrays are widely used for analysis of gene expression on a genomic scale, but the generated data remain largely inaccessible for comparative analysis purposes. Similarity searches in databases with differentially expressed gene (DEG) lists may be used to assign potential functions to new genes and to identify potential chemical inhibitors/activators and genetic suppressors/enhancers. Although this is a very promising concept, it requires the compatibility and validity of the DEG lists to be significantly improved. Using Arabidopsis and human datasets, we have developed guidelines for the performance of similarity searches against databases that collect microarray data. We found that, in comparison with many other methods, a rank-product analysis achieves a higher degree of inter- and intra-laboratory consistency of DEG lists, and is advantageous for assessing similarities and differences between them. To support this concept, we developed a tool called MASTA (microarray overlap search tool and analysis), and re-analyzed over 600 Arabidopsis microarray expression datasets. This revealed that large-scale searches produce reliable intersections between DEG lists that prove to be useful for genetic analysis, thus aiding in the characterization of cellular and molecular mechanisms. We show that this approach can be used to discover unexpected connections and to illuminate unanticipated interactions between individual genes.     

Identifying differentially expressed genes in human acute leukemia and mouse brain microarray datasets utilizing QTModel

One of the essential issues in microarray data analysis is to identify differentially expressed genes (DEGs) under different experimental treatments. In this article, a statistical procedure was proposed to identify the DEGs for gene expression data with or without missing observations from microarray experiment with one- or two-treatment factors. An F statistic based on Henderson method III was constructed to test the significance of differential expression for each gene under different treatment(s) levels. The cutoff P value was adjusted to control the experimental-wise false discovery rate. A human acute leukemia dataset corrected from 38 leukemia patients was reanalyzed by the proposed method. In comparison to the results from significant analysis of microarray (SAM) and microarray analysis of variance (MAANOVA), it was indicated that the proposed method has similar performance with MAANOVA for data with one-treatment factor, but MAANOVA cannot directly handle missing data. In addition, a mouse brain dataset collected from six brain regions of two inbred strains (two-treatment factors) was reanalyzed to identify genes with distinct regional-specific expression patterns. The results showed that the proposed method could identify more distinct regional-specific expression patterns than the previous analysis of the same dataset. Moreover, a computer program was developed and incorporated in the software QTModel, which is freely available at .     

Ranking analysis of microarray data: a powerful method for identifying differentially expressed genes

Microarray technology provides a powerful tool for the expression profile of thousands of genes simultaneously, which makes it possible to explore the molecular and metabolic etiology of the development of a complex disease under study. However, classical statistical methods and technologies fail to be applicable to microarray data. Therefore, it is necessary and motivating to develop powerful methods for large-scale statistical analyses. In this paper, we described a novel method, called Ranking Analysis of Microarray Data (RAM). RAM, which is a large-scale two-sample t-test method, is based on comparisons between a set of ranked T statistics and a set of ranked Z values (a set of ranked estimated null scores) yielded by a "randomly splitting" approach instead of a "permutation" approach and a two-simulation strategy for estimating the proportion of genes identified by chance, i.e., the false discovery rate (FDR). The results obtained from the simulated and observed microarray data show that RAM is more efficient in identification of genes differentially expressed and estimation of FDR under undesirable conditions such as a large fudge factor, small sample size, or mixture distribution of noises than Significance Analysis of Microarrays.     

转化的大鼠胚胎成纤维细胞系差异表达基因的筛选研究

来源于转化的大鼠胚胎成纤维细胞系的两株细胞,A1－5细胞与B4细胞相比表现出非常强的抗辐射性并伴随不同寻常强的G2延迟效应;用PCR选择性抑制消减杂交方法对这两株细胞进行差减,希望找到对A1－5细胞表现出的不同寻常的表型起关键作用的某一个或某一些基因。结果得到了160个差减转化子,逐个进行序列测定,并进行Dot blot杂交,共得到35个差异表达基因片段（EST）。通过对美国国家生物技术信息中心（NCBI）的非冗余序列库（NT）、鼠EST库及人EST库的BLAST进行同源检索,发现其中21个代表了尚未登录的新基因,另外14个分别与已知基因高度同源。     

Bootstrapping of gene-expression data improves and controls the false discovery rate of differentially expressed genes

The ordinary-, penalized-, and bootstrap t-test, least squares and best linear unbiased prediction were compared for their false discovery rates (FDR), i.e. the fraction of falsely discovered genes, which was empirically estimated in a duplicate of the data set. The bootstrap-t-test yielded up to 80% lower FDRs than the alternative statistics, and its FDR was always as good as or better than any of the alternatives. Generally, the predicted FDR from the bootstrapped P-values agreed well with their empirical estimates, except when the number of mRNA samples is smaller than 16. In a cancer data set, the bootstrap-t-test discovered 200 differentially regulated genes at a FDR of 2.6%, and in a knock-out gene expression experiment 10 genes were discovered at a FDR of 3.2%. It is argued that, in the case of microarray data, control of the FDR takes sufficient account of the multiple testing, whilst being less stringent than Bonferoni-type multiple testing corrections. Extensions of the bootstrap simulations to more complicated test-statistics are discussed.     

不同浓度外源IAA处理对杉木茎部基因表达的影响

为了揭示吲哚-3-乙酸(Indole-3-acetic acid,IAA)参与杉木木材发育调控的遗传机制,文章分别以0、3mg.IAA/g.lanolin处理不同阶段的杉木截顶茎秆作为驱动方(Driver)和测试方(Tester),利用抑制消减杂交技术(Suppression substractive hybridization,SSH),对其中差异表达的目的基因进行了分离和克隆。共获得332个Unigenes,其潜在的功能分别涉及到细胞组织和生物合成、发育进程调控、电子传递、逆境应答以及信号传导等方面;进一步地表达鉴定发现ClHIRA、ClPGY1和ClARF4等集中于茎部近轴区域表达的基因,能够积极地响应外源IAA刺激的维管形成层分裂和管胞分化活动;而ClSMP1、ClTCTP1和ClTRN2等集中于茎部远轴区域表达的基因,则在转录水平上对外源IAA的处理水平及近轴次生维管的发育变化表现出负相关的关系。这一结果表明特异性定位的发育基因对木材形成组织中内源IAA水平变化的差异性识别和响应很可能是生长素参与林木维管形成层次生发育调节的重要分子机制。     

Multiple hypothesis testing to detect lineages under positive selection that affects only a few sites

Detection of positive Darwinian selection has become ever more important with the rapid growth of genomic data sets. Recent branch-site models of codon substitution account for variation of selective pressure over branches on the tree and across sites in the sequence and provide a means to detect short episodes of molecular adaptation affecting just a few sites. In likelihood ratio tests based on such models, the branches to be tested for positive selection have to be specified a priori. In the absence of a biological hypothesis to designate so-called foreground branches, one may test many branches, but a correction for multiple testing becomes necessary. In this paper, we employ computer simulation to evaluate the performance of 6 multiple test correction procedures when the branch-site models are used to test every branch on the phylogeny for positive selection. Four of the methods control the familywise error rates (FWERs), whereas the other 2 control the false discovery rate (FDR). We found that all correction procedures achieved acceptable FWER except for extremely divergent sequences and serious model violations, when the test may become unreliable. The power of the test to detect positive selection is influenced by the strength of selection and the sequence divergence, with the highest power observed at intermediate divergences. The 4 correction procedures that control the FWER had similar power. We recommend Rom's procedure for its slightly higher power, but the simple Bonferroni correction is useable as well. The 2 correction procedures that control the FDR had slightly more power and also higher FWER. We demonstrate the multiple test procedures by analyzing gene sequences from the extracellular domain of the cluster of differentiation 2 (CD2) gene from 10 mammalian species. Both our simulation and real data analysis suggest that the multiple test procedures are useful when multiple branches have to be tested on the same data set.     

A mixture model approach to detecting differentially expressed genes with microarray data

An exciting biological advancement over the past few years is the use of microarray technologies to measure simultaneously the expression levels of thousands of genes. The bottleneck now is how to extract useful information from the resulting large amounts of data. An important and common task in analyzing microarray data is to identify genes with altered expression under two experimental conditions. We propose a nonparametric statistical approach, called the mixture model method (MMM), to handle the problem when there are a small number of replicates under each experimental condition. Specifically, we propose estimating the distributions of a t -type test statistic and its null statistic using finite normal mixture models. A comparison of these two distributions by means of a likelihood ratio test, or simply using the tail distribution of the null statistic, can identify genes with significantly changed expression. Several methods are proposed to effectively control the false positives. The methodology is applied to a data set containing expression levels of 1,176 genes of rats with and without pneumococcal middle ear infection.     

Identification of differentially expressed genes in human uterine leiomyomas using differential display

INTRODUCTIONUterine leiomyomas (ULs) have been consideredto be of uniceIIular origin[l1. It is one of the mostcommon benign tumors, occurring in 20% to 30% ofwomen[2], accounting for significant morbidity andusually need major surgery[3] which might causesome side effects afterwards[4]. Therefore, to de-velop certain drug treatments instead has been thehope of these patients for a long time. Using alter-native approaches fOr studying patients sufferingfrom leiomyoma in various ethnic gr…     

Construction of the seed-coat cDNA microarray and screening of differentially expressed genes in barley

Proanthocyanidins are dimeric or polymeric conden-sation products of the flavonoids, including catechin,epicatechin or gallocatechin with leucocyanidin, leuco-pelargonidin or leucodelphinidin [1]. They are prominentcolorless compounds, and are found widely existed inthe bark of trees, leaves, fruits, flowers and seed coats.They have many natural functions, such as antioxidantproperties [2] and insect resistance [3]. In forage, theycan bind and precipitate dietary proteins, thus protectthe anim…