【作者】 方明笛；

【导师】 李奎； 赵书红；

【作者基本信息】 华中农业大学 ， 动物遗传育种与繁殖， 2008， 硕士

【摘要】 后基因组时代,表达谱基因芯片技术被广泛应用。表达谱基因芯片的实验技术的研究已经成熟,而寻找差异表达基因的统计学方法和表达谱芯片数据的生物信息学分析方法虽然有一定的发展,但是还存在很多的不足。本研究以猪胎盘发育后期表达谱基因芯片数据为研究对象,采用了方差分析法和贝叶斯法两种方法进行了差异表达基因的筛选,并利用芯片数据进行了基因注释,聚类分析,Pathway分析。本研究的主要结果如下:1.运用方差分析法对猪胎盘发育后期差异表达基因进行了筛选。其中,胎盘发育75天的二花脸猪(E75)和大白猪(L75)中筛选到胎盘差异表达基因90个,二花脸猪相对大白猪上调表达的有35个,下调表达的有55个;胎盘发育90天的二花脸(E90)和大白猪(L90)中筛选到差异表达基因319个,二花脸猪相对大白猪上调表达的有135个,下调表达的有184个。2.运用贝叶斯方法对猪胎盘发育后期差异表达基因进行了筛选。E75和L75中筛选到差异表达基因271个,二花脸猪相对大白猪上调表达的有108个,下调表达的有163个;E90和L90中筛选到差异表达基因538个,其中二花脸猪相对大白猪上调表达的有256个,下调表达的有282个。3.对两种统计方法进行了比较研究。将E75和L75组中使用方差分析法筛选到的90个差异表达基因和使用贝叶斯方法筛选到的271个基因进行比较发现,两种方法都包含的基因有61个。将E90和L90组中使用方差分析法筛选到的3 19个差异表达基因和使用贝叶斯方法筛选到的538个基因比较发现,两种方法都包含的基因有247个。4.差异表达的基因按照分子功能进行分类的结果显示,E75和L75组中,主要的类别有细胞生理过程(58.6%),细胞通信(22.5%),信号转导(20%),发育(16.7%),以及器官生理过程(16.7%)。E90 and L90组中,主要的类别有细胞通信(21.6%),信号转导(19.2%),发育16.1%),器官生理过程(14.1%),以及生物多聚体修饰(10.2%)。5.聚类分析结果显示不同的发育时期先聚,然后不同的品种再聚。而基因则分成6个具有相似表达模式的类别。6.挑选了9个基因对两种分析方法(方差法和贝叶斯法)进行了Q-PCR验证。其中,方差分析法分析结果中有8个基因(ALDH1A1,DIO3,DIRAS3,PON2,ASCL2,WIF1,VEGF,DCN)具有显著性,SLC38a4没有显著性;贝叶斯方法分析结果中有6个基因(ALDH1A1,DIO3,DIRAS3,ASCL2,WIF1,,VEGF)有显著性,SLC38a4、DCN和PON2这3个基因没有显著性。Q-PCR的实验结果为8个基因(ALDH1A1,DIO3,DIRAS3,PON2,ASCL2,WIF1,,VEGF,SLC38a4)具有显著性(p＜0.05),1个基因(DCN)不具有显著性(p＞0.05)。两种方法与Q-PCR的检测结果基本一致,验汪率都是78%。更多还原

【Abstract】 Gene expression microarray techonology is widely used in post genome studies. Experimental techniques of gene expression microarray were well developed,but the statistical methods and bioinformatics analysis on gene expression microarray data has lagged behind.In this study,two statistical methods(ANOVA and bayesian methods) were used to find differentially expressed genes in porcine placenta of mid-later gestation, and some bioinformatics methods such as gene annotation,clustering and the maping of pathway were also used to understand the gene expression patterns.The main results are as follows:1.By variance analysis,a total of 90 and 319 differentially expressed transcripts were detected between E75 and L75 and between E90 and L90(P＜0.05;FDR＜0.2; FC＞2 or FC＜0.5).Among the 90 genes,35 genes were up-regulated at E75,55 genes were down-regulated at E75.Among the 319 genes,135 genes were up-regulated at E90, 184 genes were down-regulated at E90.2.By Bayesian analysis,a total of 271 and 538 differentially expressed genes were detected between E75 and L75 and between E90 and L90(p＜0.05;FC＞2 or FC＜0.5). Among the 271 genes,108 genes were up-regulated at E75,163 genes were down-regulated at E75.Among the 538 genes,256 genes were up-regulated at E90,282 genes were down-regulated at E90.3.Results of the two methods(variance methods and bayesian methods) were compared.We found 61 common genes were identified as differential expression between E75 and L75 by both methods.247 common genes were identified as differential expression between E90 and L90 by both methods.4.Functional annotations were pursued for differentially expressed genes selected. The TC accession numbers were first updated from TIGR 5.0 to TIGR 11.0 and the corresponding Human Gene IDs were pulled out so that the DAVID analysis software could be interrogated.The data were then analyzed using DAVID 2.0 and 2.1 beta.Gene Ontology(GO) biological process classification of 472 differentially expressed genes between E75 and L75 indicated that encoding proteins of these genes were associated with cellular physiological process(58.6%),cell communication(22.5%),signal transduction(20%),development(16.7%) and organismal physiological process(16.7%). In E90 and L90,biological process classification of 657 differentially expressed genes indicated that encoding proteins of these genes were associated with cell communication (21.6%),signal transduction(19.2%),development(16.1%),organismal physiological process(14.1%),and biopolymer modification(10.2%).5.Hierarchical cluster analysis of differentially expressed genes was conducted using the Gene Cluster 3.0 and treeview 1.6 software(Stanford University,2002).To gain insight into transcriptome-scale similarities among all four placenta types,all the differentially expressed genes were used to do systematic cluster analysis.The result showed that L75 and L90 were initially clustered together because their expression profiles were most similar.E75 and E90 were clustered to form another class.The result also showed the genes were classified to 6 functional parts.6.Real-time quantitative PCR was used to verify the differential expression of 9 genes detected by the Affymetrix GeneChip.We selected nine genes(ALDH1A1,DIO3, DIRAS3,PLAGL1,PON2,DCN,ASCL2,WIF1,SLC38A4) to confirm microarray data by Q-PCR.Expression patterns of 8 genes were in consistent with the microarray data.In these genes,SLC38A4 showed no significant change on the microarray by ANOVA method.It also was confirmed by Q-PCR.One gene,DCN,showing differentially expressed on the microarray,did not show significant differential expression in Q-PCR result.The results of the study showed that the variance analysis of differentially expressed genes have a certain credibility.The new Bayesian method for the study of the chip provides a new way of analyzing microarray data.This work laid a good foundation for functional research of genes in further study.更多还原