An integrative approach to analyze microarray datasets for prioritization of genes relevant to lens biology and disease.
An integrative approach to analyze microarray datasets for prioritization of genes relevant to lens biology and disease.
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一种综合方法来分析微阵列数据集，以优先考虑与晶状体生物学和疾病相关的基因。
DOI：
10.1016/j.gdata.2015.06.017
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发表时间：
2015-08-01
期刊：
影响因子：
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通讯作者：
Lachke SA
中科院分区：
文献类型：
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作者：
Anand D;Agrawal S;Siddam A;Motohashi H;Yamamoto M;Lachke SA
基于微阵列的基因表达谱分析是在基因组水平上分析细胞或组织特异性基因表达的有效方法。然而，在对照和突变体样品之间的比较分析中，微阵列通常识别大量差异表达的基因，从而使得分离与观察到的突变体表型最相关的选择“高优先级候选者”具有挑战性。在这里，我们描述了一个综合的方法，小鼠突变透镜微阵列基因表达分析使用的是可访问的系统级信息，如野生型小鼠透镜的表达数据在iSyTE（集成系统工具眼基因发现），蛋白质-蛋白质相互作用的数据在公共数据库，基因本体富集数据，和转录因子结合谱数据。当Agrawal et al. 2015 [1]将该策略应用于小Maf Mafg −/−：Mafk +/−小鼠透镜微阵列数据集（保藏在NCBI Gene Expression Omnibus数据库中，登录号为GSE 65500）时，可有效优先排序与这些突变体中的透镜缺陷相关的候选基因。事实上，从Mafg −/−：Mafk +/−突变晶状体中差异表达为± 1.5倍且p < 0.05的基因的原始列表中，该分析导致鉴定出36个高优先级候选基因，从而将用于进一步研究的基因数量减少了约1/3。此外，在已发表的文献中，这些基因中有8个与哺乳动物白内障有关，验证了这种方法的有效性。此外，这些高优先级的候选人提供有价值的信息，为组装的基因调控网络中的透镜。总之，在本报告中概述的管道代表了一种有效的方法，为初始以及下游的微阵列表达数据分析，以确定基因的重要透镜生物学和白内障。我们预计，这种整合策略可以扩展到优先表型相关的候选基因在其他细胞和组织的微阵列数据。
Microarray-based profiling represents an effective method to analyze cellular or tissue-specific gene expression on the genome-level. However, in comparative analyses between control and mutant samples, microarrays often identify a large number of differentially expressed genes, in turn making it challenging to isolate the select “high-priority candidates” that are most relevant to an observed mutant phenotype. Here, we describe an integrative approach for mouse mutant lens microarray gene expression analysis using publically accessible systems-level information such as wild-type mouse lens expression data in iSyTE (integrated Systems Tool for Eye gene discovery), protein–protein interaction data in public databases, gene ontology enrichment data, and transcription factor binding profile data. This strategy, when applied to small Maf Mafg −/−:Mafk +/− mouse lens microarray datasets (deposited in NCBI Gene Expression Omnibus database with accession number GSE65500) in Agrawal et al. 2015 [1], led to the effective prioritization of candidate genes linked to lens defects in these mutants. Indeed, from the original list of genes that are differentially expressed at ± 1.5-fold and p < 0.05 in Mafg −/−:Mafk +/− mutant lenses, this analysis led to the identification of thirty-six high-priority candidates, in turn reducing the number of genes for further study by approximately 1/3 of the total. Moreover, eight of these genes are linked to mammalian cataract in the published literature, validating the efficacy of this approach. Additionally, these high-priority candidates contribute valuable information for the assembly of a gene regulatory network in the lens. In sum, the pipeline outlined in this report represents an effective approach for initial as well as downstream microarray expression data analysis to identify genes important for lens biology and cataracts. We anticipate that this integrative strategy can be extended to prioritize phenotypically relevant candidate genes from microarray data in other cells and tissues.