中华口腔医学杂志
中華口腔醫學雜誌
중화구강의학잡지
Chinese Journal of Stomatology
2008年
3期
168-171
,共4页
胡延佳%翦新春%刘斌杰%彭解英
鬍延佳%翦新春%劉斌傑%彭解英
호연가%전신춘%류빈걸%팽해영
口腔黏膜下纤维化%计算生物学%基因
口腔黏膜下纖維化%計算生物學%基因
구강점막하섬유화%계산생물학%기인
Oral submucous fibrosis%Computation biology%Genes
目的 运用基因芯片数据分析软件对口腔黏膜下纤维化(oral submucosa fibrosis,OSF)差异表达基因进行分析,研究其隐含的生物学意义.方法 利用DAVID和Onto-express两种基因芯片数据分析软件对前期筛选的865个OSF差异表达基因进行染色体定位、GO分析(gene ontology)和遗传关联疾病分析.结果 差异表达基因主要定位于1、2、5、6、7、11和12号染色体上(P＜0.01);GO分析显示差异表达基因主要参与免疫反应、防御反应等生物过程,并主要与细胞外基质、细胞骨架、细胞膜的组成和蛋白结合,细胞外基质结构组成和信号转导激活等分子功能相关;而与这些基因有遗传关联的疾病主要有感染,免疫和心血管疾病等.结论 运用基因芯片数据分析软件可快速分析大量的基因芯片数据,实现对差异基因初步的功能归类,为OSF的发病机制和流行病学研究提供新的思路.
目的 運用基因芯片數據分析軟件對口腔黏膜下纖維化(oral submucosa fibrosis,OSF)差異錶達基因進行分析,研究其隱含的生物學意義.方法 利用DAVID和Onto-express兩種基因芯片數據分析軟件對前期篩選的865箇OSF差異錶達基因進行染色體定位、GO分析(gene ontology)和遺傳關聯疾病分析.結果 差異錶達基因主要定位于1、2、5、6、7、11和12號染色體上(P＜0.01);GO分析顯示差異錶達基因主要參與免疫反應、防禦反應等生物過程,併主要與細胞外基質、細胞骨架、細胞膜的組成和蛋白結閤,細胞外基質結構組成和信號轉導激活等分子功能相關;而與這些基因有遺傳關聯的疾病主要有感染,免疫和心血管疾病等.結論 運用基因芯片數據分析軟件可快速分析大量的基因芯片數據,實現對差異基因初步的功能歸類,為OSF的髮病機製和流行病學研究提供新的思路.
목적 운용기인심편수거분석연건대구강점막하섬유화(oral submucosa fibrosis,OSF)차이표체기인진행분석,연구기은함적생물학의의.방법 이용DAVID화Onto-express량충기인심편수거분석연건대전기사선적865개OSF차이표체기인진행염색체정위、GO분석(gene ontology)화유전관련질병분석.결과 차이표체기인주요정위우1、2、5、6、7、11화12호염색체상(P＜0.01);GO분석현시차이표체기인주요삼여면역반응、방어반응등생물과정,병주요여세포외기질、세포골가、세포막적조성화단백결합,세포외기질결구조성화신호전도격활등분자공능상관;이여저사기인유유전관련적질병주요유감염,면역화심혈관질병등.결론 운용기인심편수거분석연건가쾌속분석대량적기인심편수거,실현대차이기인초보적공능귀류,위OSF적발병궤제화류행병학연구제공신적사로.
Objective To apply the bioinformatics tools for analyzing the differentially expressed genes in oral submucous fibrosis(OSF)to obtain the implied biological significance.Methods By using DAVID and Onto-express bioinformatic tools.865 differentially expressed genes in OSF were analized and the analysis of chromosome location,gene ontology(GO)and genetic-association diseases were performed.Results A majority of the differentially expressed genes were located on chromosome 1,2,5,6,7,11,12(P＜0.01).GO classification of the differentially expressed genes identified the biological process subgroups,including genes involved in immune response,defense response and so on.The cellular component subgroups were associated with extracellular matrix,cytoskeleton and membrane,molecular function subgroups related to protein binding,extracellular matrix structural constituent and signal transducer activity.The diseases genetically associated with these genes included infection.immune and cardiovascular diseases.Conclusions Bioinformatics can provide the quick and parallel analysis of massive data got from gene microarrays and enable the function classification of the differentially expressed genes,which provides new ideas on the research of pathogenesis and epidemiology of OSF.
