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.     

Function and Chromosome Location of Differentially Expressed Genes in Gastric Cancer

Using Affymetrix U133A oligonucleotide microarrays, screening was done for genes that were differentially expressed in gastric cancer (T) and normal gastric mucosa (C), and their chromosome location was characterized by bioinformatics. A total of 270 genes were found to have a difference in expression levels of more than eight times. Of them 157 were up-regulated (Signal Log Ratio [SLR]≥3), and 113 were down-regulated (SLR≤-3). Except for, four genes with unknown localization, a vast majority of the genes were sporadically distributed over every chromosome. However, chromosome 1 contained the most differentially expressed genes (26 genes, or 9.8%), followed by chromosomes 11 and 19 (both 24 genes, or 9.1%). These genes were also more likely to be on the short-arm of the chromosome (q), which had 173 (65%). When these genes were classified according to their functions, it was found that most (67 genes, 24.8%) belonged to the enzymes and their regulators groups. The next group was the signal transduction genes group (43 genes, 15.9%). The rest of the top three groups were nucleic acid binding genes (17, 6.3%), transporter genes (15, 5.5%), and protein binding genes (12, 4.4%). These made up 56.9% of all the differentially expressed genes. There were also 50 genes of unknown function (18.5%). Therefore it was concluded that differentially expressed genes in gastric cancer seemed to be sporadically distributed across the genome, but most were found on chromosomes 1, 11 and 19. The five groups associated genes abnormality were important genes for further study on gastric cancer.     

胃癌差异表达基因在染色体上的定位及其功能分析

利用标准化的Affymetrix公司生产的U133A基因芯片检测胃癌（T）与切缘正常胃黏膜（C）基因表达谱差异,并利用生物信息学方法对检测结果进行差异基因在染色体定位和功能分析。结果表明：胃癌与正常胃黏膜比较差异8倍以上共有270个基因,其中表达上调[信号比的对数值（SLR）≥3]有157个,表达下调（SLR≤-3）有113个。从表达差异的基因在染色体定位分析,发现除4个基因未知其定位外,其余所有差异表达基因散在分布和各条染色体上,但以1号染色体为最多,有26个（占9．8％）,其次是11和19号染色体上分别有24个（各占9．1％）。而差异表达的基因发生在染色体短臂（q）上有173个（占65％）。从表达差异的基因功能分类看,属于酶和酶调控子基因最多（67个,24．8占％）,其次是信号传导基因（43个,占15．9％）,第3类是核酸结合基因（17个,占6．3％）,第4类是转运子基因（15个,占5．5％）,第5类是蛋白结合基因（12个,占4．4％）,还有功能未知的基因有50个,占18．5％。以上5大类共占基因总数56．9％。胃癌差异表达基因散在分布在各条染色体上,但以1、11、19号染色体差异表达基因居多。这5大类（酶和酶调控子、信号传导、核酸结合、转运子、蛋白结合）相关基因异常是今后研究胃癌的重要基因。     

雄激素非依赖性前列腺癌细胞中差异甲基化基因的初步筛选

应用全基因组DNA甲基化芯片(Illumina Infinium HumanMethylation27 BeadChip)杂交技术以及转录组RNA测序技术,检测了雄激素依赖性前列腺癌(androgen-dependent prostate cancer,ADPC)细胞株LNCaP和雄激素非依赖性前列腺癌(androgen-independent prostate cancer,AIPC)细胞株LNCaP-AI(androgen independent)中的差异甲基化基因。发现与LNCaP细胞株相比,LNCaP-AI细胞株有990个CpG位点表现为高甲基化,涉及855个基因;2 305个CpG位点表现为低甲基化,涉及1 970个基因。结合转录组mRNA表达结果,筛选出6个超甲基化基因:FAM111B、RAB36、PCDH7、COL6A2、IGF1R、GULP1;8个低甲基化基因:EPHA3、TM4SF1、IGFBP5、FAM105A、RASD1、ITPR2、CYP27B1、UBE2E3。这些差异甲基化基因涉及钙离子信号通路、Wnt信号通路等多个信号通路,参与了细胞的基因表达、信号传导、细胞通讯、细胞运动、细胞黏附以及血管生成等功能,为探讨这些差异甲基化基因在前列腺癌雄激素非依赖性转化过程中发挥的作用奠定了基础。     

Differentially Expressed MicroRNAs in Postpartum Breast Cancer in Hispanic Women

The risk of breast cancer transiently increases immediately following pregnancy; peaking between 3-7 years. The biology that underlies this risk window and the effect on the natural history of the disease is unknown. MicroRNAs (miRNAs) are small non-coding RNAs that have been shown to be dysregulated in breast cancer. We conducted miRNA profiling of 56 tumors from a case series of multiparous Hispanic women and assessed the pattern of expression by time since last full-term pregnancy. A data-driven splitting analysis on the pattern of 355 miRNAs separated the case series into two groups: a) an early group representing women diagnosed with breast cancer ≤ 5.2 years postpartum (n = 12), and b) a late group representing women diagnosed with breast cancer ≥ 5.3 years postpartum (n = 44). We identified 15 miRNAs with significant differential expression between the early and late postpartum groups; 60% of these miRNAs are encoded on the X chromosome. Ten miRNAs had a two-fold or higher difference in expression with miR-138, miR-660, miR-31, miR-135b, miR-17, miR-454, and miR-934 overexpressed in the early versus the late group; while miR-892a, miR-199a-5p, and miR-542-5p were underexpressed in the early versus the late postpartum group. The DNA methylation of three out of five tested miRNAs (miR-31, miR-135b, and miR-138) was lower in the early versus late postpartum group, and negatively correlated with miRNA expression. Here we show that miRNAs are differentially expressed and differentially methylated between tumors of the early versus late postpartum, suggesting that potential differences in epigenetic dysfunction may be operative in postpartum breast cancers.     

Identification of New Differentially Methylated Genes That Have Potential Functional Consequences in Prostate Cancer

Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P<0.05), defined as a mean methylation difference of at least 20% between PCa and normal samples. Furthermore, a total of 122 genes had more than one differentially methylated CpG site in their promoter region and a gene expression pattern that was inverse to the direction of change in DNA methylation (e.g. decreased expression with increased methylation, and vice-versa). Aberrant DNA methylation of two genes, AOX1 and SPON2, were confirmed via bisulfate sequencing, with most of the respective CpG sites showing significant differences between tumor samples and normal tissues. The AOX1 promoter region showed hypermethylation in 92.6% of 54 tested PCa samples in contrast to only three out of 53 tested normal tissues. This study used a new BeadChip combined with gene expression data in PCa to identify novel differentially methylated CpG sites located within genes. The newly identified differentially methylated genes may be used as biomarkers for PCa diagnosis.     

Characterization of Differentially Expressed Genes Involved in Pathways Associated with Gastric Cancer

To explore the patterns of gene expression in gastric cancer, a total of 26 paired gastric cancer and noncancerous tissues from patients were enrolled for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR) value was < 0.01, P-value was <0.01 and the fold change (FC) was >2. Subsequently, Gene Ontology (GO) categories were used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we found pathways significantly associated with the differential genes. Gene-Act network and co-expression network were built respectively based on the relationships among the genes, proteins and compounds in the database. 2371 mRNAs and 350 lncRNAs considered as significantly differentially expressed genes were selected for the further analysis. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were responsible for tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. These results of this study provide some novel findings on coding RNAs, lncRNAs, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease.     

mRNA差异展示研究胃癌差异表达基因

以胃癌细胞株GC7901与胃粘膜细胞株GES-1为对比材料,利用mRNA差异展示技术,研究胃粘膜至胃癌过程的差异表达基因,为建立胃癌预警系统打下基础.获得8个未知的与胃癌相关的cDNA,命名为GCYS-1,2,3,4,5,6,7,20,完成其克隆及序列分析,RNA印迹证实GCYS-1至7片段与GCYS-20基因在GC7901细胞株中呈高表达,在GES-1细胞株中呈低表达.此8个序列在GenBank数据库中登录,接受号为AF054162～AF056168及AF219140.     

胃癌组织中肿瘤相关成纤维细胞与正常成纤维细胞之间转录组学研究及验证

胃癌组织中肿瘤相关成纤维细胞(carcinoma associated fibroblasts, CAFs)是胃癌微环境的重要成分,主要来源于正常成纤维细胞(normal fibroblasts, NFs)的活化,对胃癌的发生发展有重要作用,但是两者之间的基因表达差异并不完全清楚。本研究选取从人胃癌组织中分离获得的CAFs及NFs 各3组,进行转录组学研究,筛选出3组细胞中交集且差异倍数较大的基因12个,用Omicsbean在线工具对差异基因进行Gene Ontology (GO)功能及KEGG通路富集,构建蛋白质相互作用调控网络;最后用RT-qPCR验证CAFs和NFs中差异基因的表达。结果显示,筛选出的12个差异表达基因主要参与NF-κB信号、炎症、细胞黏附、细胞表面受体和细胞因子等功能,上述功能均与肿瘤的发生发展密切相关。RT-qPCR检测发现,与NFs相比,CAFs中BCL2A1、NKX3-2、CXCL12、TNFAIP3、FOS、CDH4及CLDN1表达上调;ATF3、CYFIP2、CCL11、KLF2及GDF15基因表达下调,差异均具有统计学意义(P＜0.05)。结果提示,胃癌CAFs与NFs中存在肿瘤相关的差异表达基因,这些差异基因可能在胃癌微环境中发挥重要作用。     

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.     

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.     

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates.     

Identification of Imprinted Genes and Their Differentially Methylated Regions in Porcine

Russian Journal of Genetics - Genomic imprinting is an epigenetic mechanism that leads to parent-specific gene expression. A&nbsp;number of imprinted genes have been identified in humans and...     

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...     

Oligonucleotide Microarray Identifies Genes Differentially Expressed during Tumorigenesis of DMBA-Induced Pancreatic Cancer in Rats

The extremely dismal prognosis of pancreatic cancer (PC) is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA)-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes) were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.     

Differentially Expressed Androgen-Regulated Genes in Androgen-Sensitive Tissues Reveal Potential Biomarkers of Early Prostate Cancer

Background

Several data favor androgen receptor implication in prostate cancer initiation through the induction of several gene activation programs. The aim of the study is to identify potential biomarkers for early diagnosis of prostate cancer (PCa) among androgen-regulated genes (ARG) and to evaluate comparative expression of these genes in normal prostate and normal prostate-related androgen-sensitive tissues that do not (or rarely) give rise to cancer.

Methods

ARG were selected in non-neoplastic adult human prostatic epithelial RWPE-1 cells stably expressing an exogenous human androgen receptor, using RNA-microarrays and validation by qRT-PCR. Expression of 48 preselected genes was quantified in tissue samples (seminal vesicles, prostate transitional zones and prostate cancers, benign prostatic hypertrophy obtained from surgical specimens) using TaqMan® low-density arrays. The diagnostic performances of these potential biomarkers were compared to that of genes known to be associated with PCa (i.e. PCA3 and DLX1).

Results and Discussion

By crossing expression studies in 26 matched PCa and normal prostate transitional zone samples, and 35 matched seminal vesicle and PCa samples, 14 genes were identified. Similarly, 9 genes were overexpressed in 15 benign prostatic hypertrophy samples, as compared to PCa samples. Overall, we selected 8 genes of interest to evaluate their diagnostic performances in comparison with that of PCA3 and DLX1. Among them, 3 genes: CRYAB, KCNMA1 and SDPR, were overexpressed in all 3 reference non-cancerous tissues. The areas under ROC curves of these genes reached those of PCA3 (0.91) and DLX1 (0.94).

Conclusions

We identified ARG with reduced expression in PCa and with significant diagnostic values for discriminating between cancerous and non-cancerous prostatic tissues, similar that of PCA3. Given their expression pattern, they could be considered as potentially protective against prostate cancer. Moreover, they could be complementary to known genes overexpressed in PCa and included along with them in multiplex diagnostic tools.     

鼠精子发生时期差异表达基因的克隆(英文)

为了分离鼠精子发生时期表达的基因,本文采用mRNA差异显示法,以鼠的粗线期卵母细胞为对照,检测了出生后60天和16天鼠的睾丸。得到12个有差异的片段(Fig.1&Table 1)。克隆测序结果表明,其中5个与已知基因非常吻合,另外6个与一些未知功能的cDNA、ESTs有较高的同源性,只有1个与已知序列没有同源性。Northern杂交分析显示sp1和sp8主要在成年鼠睾丸表达(Fig.4B)。采用5RACE对sp1的cDNA进行了全长分析,该基因编码一个推测是高度磷酸化蛋白的541个氨基酸(Fig.2),其中包括一个核定位信号,无论在核苷酸水平上,还是在氨基酸水平上均没有明显的同源性,仅在2个蛋白区有少量同源氨基酸(Fig.3)。该基因在20-60天龄鼠的睾丸均有表达,并且具有很高的组织特异性只在睾丸里表达(Fig.4A)。因而,这个基因有可能参与减数分裂及其以后的整个过程。可以认为这是一个新基因。我们把它命名为peat (predominantly expressed in adult testis)。