Analyzing Kernel Matrices for the Identification of Differentially Expressed Genes

One of the most important applications of microarray data is the class prediction of biological samples. For this purpose, statistical tests have often been applied to identify the differentially expressed genes (DEGs), followed by the employment of the state-of-the-art learning machines including the Support Vector Machines (SVM) in particular. The SVM is a typical sample-based classifier whose performance comes down to how discriminant samples are. However, DEGs identified by statistical tests are not guaranteed to result in a training dataset composed of discriminant samples. To tackle this problem, a novel gene ranking method namely the Kernel Matrix Gene Selection (KMGS) is proposed. The rationale of the method, which roots in the fundamental ideas of the SVM algorithm, is described. The notion of ''''the separability of a sample'''' which is estimated by performing -like statistics on each column of the kernel matrix, is first introduced. The separability of a classification problem is then measured, from which the significance of a specific gene is deduced. Also described is a method of Kernel Matrix Sequential Forward Selection (KMSFS) which shares the KMGS method''s essential ideas but proceeds in a greedy manner. On three public microarray datasets, our proposed algorithms achieved noticeably competitive performance in terms of the B.632+ error rate.     

Identification of Genes Differentially Expressed Between Ochratoxin-Producing and Non-Producing Strains of Aspergillus westerdijkiae

Approximately 70 % of Aspergillus westerdijkiae strains are able to produce ochratoxin A (OTA), a nephrotoxic and carcinogenic mycotoxin which have been found in cereal and food commodities. Despite of its importance there is, up to now, no information available about which genes are differentially expressed between A. westerdijkiae ochratoxin-producing and non-producing strains. Using cDNA RDA approach we successfully sequenced 231 raw ESTs expected to be enriched in the ochratoxin-producing strain. BLASTX searches against the public databases showed that of these, 205 ESTs (79 %) exhibited significant similarities with proteins of known functions, 28 ESTs (11 %) had matches to hypothetical proteins, and the remaining 27 ESTs (10 %) had no significant hits. EST alignment resulted in a total of 14 non-redundant consensus sequences. Three putative genes encoding oxidoreductases were validated as up-expressed in the OTA producer strain using RT-qPCR approach. The expression of the putative genes encoding a cytochrome P450 family protein, 3-hydroxyphenylacetate-6-hydroxylase, and endoplasmic reticulum oxidoreductin were higher (32-, 2.8- and 20-fold respectively) in the OTA producer strain compared to the non-producer strain.     

A Robust Statistical Method for Detecting Differentially Expressed Genes

DNA microarray technology allows researchers to monitor the expressions of thousands of genes under different conditions, and to measure the levels of thousands of different DNA molecules at a given point in the life of an organism, tissue or cell. A wide variety of different diseases that are characterised by unregulated gene expression, DNA replication, cell division and cell death, can be detected early using microarrays. One of the major objectives of microarray experiments is to identify differentially expressed genes under various conditions. The detection of differential gene expression under two different conditions is very important in biological studies, and allows us to identify experimental variables that affect different biological processes. Most of the tests available in the literature are based on the assumption of normal distribution. However, the assumption of normality may not be true in real-life data, particularly with respect to microarray data.A test is proposed for the identification of differentially expressed genes in replicated microarray experiments conducted under two different conditions. The proposed test does not assume the distribution of the parent population; thus, the proposed test is strictly nonparametric in nature. We calculate the p-value and the asymptotic power function of the proposed test statistic. The proposed test statistic is compared with some of its competitors under normal, gamma and exponential population setup using the Monte Carlo simulation technique. The application of the proposed test statistic is presented using microarray data. The proposed test is robust and highly efficient when populations are non-normal.     

Differentially Expressed Genes in EEC and LMS Syndromes

Objectives

Ectrodactyly ectodermal dysplasia cleft lip/palate (EEC) syndrome and limb-mammary syndrome (LMS) share a similar phenotype and the same pathogenic gene, which complicates the ability to distinguish between these diagnoses. The current study aims to identify a potential and practical clinical biomarker to distinguish EEC from LMS.

Methods

Two EEC pedigrees and one LMS pedigree that have been previously reported were reanalyzed. After confirmation of the causative mutations for these new patients, whole-genome expression microarray analysis was performed to assess the molecular genetic changes in these families.

Results

Five new patients with classic symptoms were reported, and these individuals exhibited the same mutation as their relatives (c.812 G>C; c.611G>A; and c.680G>A). According to the whole genome expression results, the EEC patients exhibited different gene expression characteristics compared with the LMS patients. More than 5,000 genes were differentially expressed (changes >2 or <0.5-fold) among the EEC patients, LMS patients and healthy individuals. The top three altered pathways have been implicated in apoptosis, the hematopoietic cell lineage and the Toll-like receptor signaling pathway.

Conclusion

Our results provide additional clinical and molecular information regarding EEC and LMS and suggest that peripheral blood cytokines may represent a promising clinical biomarker for the diagnosis of these syndromes.     

克隆差异表达基因的新策略

基因表达的变化有两种,即新出现的基因表达与表达量差异的基因表达.表达量差异的基因克隆技术主要有mRNA差异展示,此技术是目前筛选差异表达基因最有效的方法之一,但主要存在假阳性率高的不足,针对此缺点,近几年提出了新的策略与方法,如差异消减展示、基于PCR和减法杂交基础上的差异表达基因克隆技术,这些技术具有显著优势.     

差异表达基因克隆技术的进展

分离并克隆差异表达基因,不仅有助于揭示生命的奥秘,而且还能为基因诊断与治疗提供重要的理论依据。基因差异表达的变化有两种,即新出现的基因表达与表达量差异的基因表达。以前,过多强调克隆新出现的表达基因,忽略表达量差异的基因。目前研究认为,表达量差异的基因...     

Powers of Multiple-Testing Procedures for Identification of Genes Significantly Differentially Expressed in Microarray Experiments

Because of the high operation costs involved in microarray experiments, the determination of the number of replicates required to detect a gene significantly differentially expressed in a given multiple-testing procedure is of considerable significance. Calculation of power/replicate numbers required in multiple-testing procedures provides design guidance for microarray experiments. Based on this model and by choice of a multiple-testing procedure, expression noises based on permutation resampling can be considerably minimized. The method for mixture distribution model is suitable to various microarray data types obtained from single noise sources, or from multiple noise sources. By using the biological replicate number required in microarray experiments for a given power or by determining the power required to detect a gene significantly differentially expressed, given the sample size, or the best multiple-testing method can be chosen. As an example, a single-distribution model of t-statistic was fitted to an observed microarray dataset of 3 000 genes responsive to stroke in rat, and then used to calculate powers of four popular multiple-testing procedures to detect a gene of an expression change D. The results show that the B-procedure had the lowest power to detect a gene of small change among the multiple-testing procedures, whereas the BH-procedure had the highest power. However, all multiple-testing procedures had the same power to identify a gene having the largest change. Similar to a single test, the power of the BH-procedure to detect a small change does not vary as the number of genes increases, but powers of the other three multiple-testing procedures decline as the number of genes increases.     

北京油鸡与AA肉鸡脂肪组织差异表达基因的研究

运用mRNA差异显示技术对AA肉鸡和北京油鸡脂肪组织基因的差异表达进行研究,从分子遗传学角度分析导致两品种脂肪组织差异表达的原因,对了解性状形成的遗传基础和调控机理是十分必要的。通过反Northern杂交验证共筛选出脂肪组织差异表达基因10条,经与GenBank数据库进行相似性比对,XF1 与已知基因有较高同源性,该基因是人类cDNA全长开放阅读框（ORF）的一段; XF2、YF1、YF2及YF4经与nr数据库进行同源性比对,均可找到同源性较高的基因,但功能未知;XF4 与克隆人类胎盘CL0BA010ZF08基因的一段cDNA序列同源性为83%;YF3与预测原鸡MLL5 (LOC417712)基因有一定的同源性,目前尚无功能报道;XF5和YF5 与原鸡高迁移率族蛋白（HMGN3）有较高同源性;XF3 在nr库中未找到同源序列,确定为新发现的EST,提交数据库获得GenBank登录号(Accession number: EU594549)。为进一步研究北京油鸡与AA肉鸡脂肪组织差异基因的功能与脂肪发育的关系奠定基础。     

Identification of Differentially Expressed Genes in Breast Muscle and Skin Fat of Postnatal Pekin Duck

Lean-type Pekin duck is a commercial breed that has been obtained through long-term selection. Investigation of the differentially expressed genes in breast muscle and skin fat at different developmental stages will contribute to a comprehensive understanding of the potential mechanisms underlying the lean-type Pekin duck phenotype. In the present study, RNA-seq was performed on breast muscle and skin fat at 2-, 4- and 6-weeks of age. More than 89% of the annotated duck genes were covered by our RNA-seq dataset. Thousands of differentially expressed genes, including many important genes involved in the regulation of muscle development and fat deposition, were detected through comparison of the expression levels in the muscle and skin fat of the same time point, or the same tissue at different time points. KEGG pathway analysis showed that the differentially expressed genes clustered significantly in many muscle development and fat deposition related pathways such as MAPK signaling pathway, PPAR signaling pathway, Calcium signaling pathway, Fat digestion and absorption, and TGF-beta signaling pathway. The results presented here could provide a basis for further investigation of the mechanisms involved in muscle development and fat deposition in Pekin duck.     

多重检验法在基因芯片研究中鉴定差异表达基因的统计功效

鉴于基因芯片实验的造价,在基因芯片实验设计中,首要考虑的因素是需要多少重复才能检测出一个具有显著差异表达的基因。计算多重检验法要求的重复数（样本大小）或功效可为基因芯片实验设计提供重要的参考。为此,本文基于置换重抽样法构建了一种基因表达噪声混合分布模型。该方法适用各类基因表达数据,即无论是基因表达单噪声源或是多噪声源都可行。应用混合模型和多重检验法并给定统计功效。研究者能在基因芯片实验中获得所需要的最少生物学重复数：或者根据样本大小来确定测定一个显著差异表达的基因所具有的检验功效;或者根据样本大小和统计检验功效,选择最好的统计测验方法。本文以一组在老鼠中与中风有关的3000个基因的基因芯片实验所获得的数据为例,应用该方法拟和后组建了一个单分布模型（即表达单噪声源的分布模型）。根据该模型,我们计算了4种多重检验法在鉴定一个具有表达差异（D）值的基因中所需要的统计功效。结果表明。检测一个小的差异D值,4种多重检验法中B方法的统计功效最低,而BH方法最高。但是,对于鉴定一个具有最大表达差异的基因时,4种方法有相同的鉴定功效。与传统的单个检验法一样,BH方法检测一个小的变化所需要的效率不会随基因数目增加而改变,其他3种多重检验法的检测功效则随基因数目增加而降低。     

Identification of Differentially Expressed Genes in Distinct Skeletal Muscles in Cattle using cDNA Microarray

The 788-gene microarray was manufactured using selected elements from three different cDNA libraries in order to identify molecular processes that determine phenotypic characteristics between loin (M. longissimus thoracis) and round (M. semimembranosus) muscles. Microarray analyses identified 24 differentially expressed genes between the two muscles investigated. Five of the genes were verified by quantitative RT-PCR and three of them were mapped on bovine chromosomes using 5,000 rad bovine radiation hybrid (RH) panel. The map locations indicated that they were mapped in the same chromosomal regions where IMF and growth QTLs were located, suggesting that they are most possible positional candidate genes for the traits.     

Microarray-Based Identification of Differentially Expressed Genes in Intracellular Brucella abortus within RAW264.7 Cells

Brucella spp. is a species of facultative intracellular Gram-negative bacteria that induces abortion and causes sterility in domesticated mammals and chronic undulant fever in humans. Important determinants of Brucella’s virulence and potential for chronic infection include the ability to circumvent the host cell’s internal surveillance system and the capability to proliferate within dedicated and non-dedicated phagocytes. Hence, identifying genes necessary for intracellular survival may hold the key to understanding Brucella infection. In the present study, microarray analysis reveals that 7.82% (244/3334) of all Brucella abortus genes were up-regulated and 5.4% (180/3334) were down-regulated in RAW264.7 cells, compared to free-living cells in TSB. qRT-PCR verification further confirmed a >5-fold up-regulation for fourteen genes. Functional analysis classified araC, ddp, and eryD as to partake in information storage and processing, alp, flgF and virB9 to be involved in cellular processes, hpcd and aldh to play a role in metabolism, mfs and nikC to be involved in both cellular processes and metabolism, and four hypothetical genes (bruAb1_1814, bruAb1_0475, bruAb1_1926, and bruAb1_0292) had unknown functions. Furthermore, we constructed a B. abortus 2308 mutant Δddp where the ddp gene is deleted in order to evaluate the role of ddp in intracellular survival. Infection assay indicated significantly higher adherence and invasion abilities of the Δddp mutant, however it does not survive well in RAW264.7 cells. Brucella may survive in hostile intracellular environment by modulating gene expression.     

鼻咽癌上皮细胞株HNE1差异表达基因的分离与鉴定

为了分离鼻咽癌差异表达基因 ,应用抑制性扣除杂交技术 ,在正向抑制性扣除杂交中 ,以鼻咽癌上皮细胞株HNE1cDNA作为检测子 ,以人胚鼻咽上皮细胞cDNA作为驱赶子 ;在反向抑制性扣除杂交中 ,以人胚鼻咽上皮细胞cDNA作为检测子 ,以鼻咽癌上皮细胞株HNE1cDNA作为驱赶子 ,分别通过抑制性扣除杂交 ,构建了鼻咽癌上皮细胞株HNE1表达下调和表达上调的两个扣除cDNA文库 .从鼻咽癌相关的扣除cDNA文库中随机挑取 1 2 0 0个克隆 ,采用菌落PCR扩增其插入cDNA片段 ,自动点膜制备成cDNA微阵列膜 ,分别用鼻咽癌上皮细胞株HNE1、人胚鼻咽上皮mRNA经逆转录标记cDNA探针 ,分别与cDNA微阵列膜杂交 ,通过杂交信号的自动扫描分析 ,对杂交信号存在 5倍差异的克隆进行测序 ,获得了 1 0个鼻咽癌差异表达基因的cDNA片段 ,其中 3个为新基因序列 ,其GenBank登录号为 :AF5 1 0 1 88、AF5 1 0 1 89和AF5 1 0 1 90 ,7个代表已知基因序列 .采用RT PCR证实S1 0 0A8,CK1 9和RBP1基因在人胚鼻咽上皮中高表达而在鼻咽癌细胞株HNE1中低表达 .这些结果显示上述基因可能是鼻咽癌发生的重要因素     

Identification of Novel Genes Differentially Expressed in PMA-induced HL-60 Cells Using cDNA Microarrays

Identification of normal growth and differentiation-inducing proteins and their interaction in normal development have made it possible to elucidate the molecular basis of normal development and the mechanisms uncoupling growth and differentiation during tumor development. The development of cancer and the experimental reversal of tumorigenicity are accompanied by complex changes in patterns of gene expression. cDNA microarrays provide a powerful tool for studying these phenomena. In the present study, a high-density microarray of human cDNA elements was used to search for differences in gene expression associated with differentiation of human promyelic leukemia HL-60 cells. Microarrays containing 3,063 human cDNAs were printed on glass slides with high-speed robotics. These DNA 'chips' were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. The identification of known and novel phorbol ester-regulated genes in hematopoietic progenitor cells demonstrates the sensitivity of the assay.     

Identification of Novel Genes Differentially Expressed in PMA-induced HL-60 Cells Using cDNA Microarrays

Identification of normal growth and differentiation-inducing proteins and their interaction in normal development have made it possible to elucidate the molecular basis of normal development and the mechanisms uncoupling growth and differentiation during tumor development. The development of cancer and the experimental reversal of tumorigenicity are accompanied by complex changes in patterns of gene expression. cDNA microarrays provide a powerful tool for studying these phenomena. In the present study, a high-density microarray of human cDNA elements was used to search for differences in gene expression associated with differentiation of human promyelic leukemia HL-60 cells. Microarrays containing 3,063 human cDNAs were printed on glass slides with high-speed robotics. These DNA chips were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. The identification of known and novel phorbol ester-regulated genes in hematopoietic progenitor cells demonstrates the sensitivity of the assay.     

cDNA芯片差异表达基因检测的非转换方法

cDNA微阵列数据中包含许多变异因素,用于检测差异表达基因和其它统计分析前,必须将这些“噪音”剔除。对数比法（背景校正、对数比转换和数据标准化）已经被广泛应用于cDNA微阵列数据分析中,然而这种方法却存在着一些亟待解决的缺陷。对此,该文提出一种非转换方法,它可免去对数比的转化过程,直接在背景校正后进行数据标准化,可以有效剔除实验“噪音”。研究结果表明：在检测差异表达基因的效率方面,非转换方法比常规的对数比法具有更好的稳健性和更高的检测功效,基因检出率和准确性大大提高。