Ehler Martin, Rajapakse Vinodh N, Zeeberg Barry R, Brooks Brian P, Brown Jacob, Czaja Wojciech, Bonner Robert F
National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Section on Medical Biophysics, Bethesda MD 20892, USA.
BMC Proc. 2011 May 28;5 Suppl 2(Suppl 2):S3. doi: 10.1186/1753-6561-5-S2-S3.
The gene networks underlying closure of the optic fissure during vertebrate eye development are not well-understood. We use a novel clustering method based on nonlinear dimension reduction with data labeling to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure.
Our nonlinear methods created clusters of genes that mapped onto more specific biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates than conventional linear cluster algorithms. Our new methods build on the advantages of LCM to isolate pure phenotypic populations within complex tissues in order to identify systems biology relationships among critical gene products expressed at lower copy number.
The combination of LCM of embryonic organs, gene expression microarrays, and nonlinear dimension reduction with labeling is a potentially useful approach to extract subtle spatial and temporal co-variations within the gene regulatory networks that specify mammalian organogenesis and organ function. Our results motivate further analysis of nonlinear dimension reduction with labeling within other microarray data sets from LCM dissected tissues or other cell specific samples to determine the more general utility of our method for uncovering more specific biological functional relationships.
脊椎动物眼睛发育过程中视神经裂闭合的基因网络尚未得到充分理解。我们使用一种基于非线性降维和数据标记的新型聚类方法，来分析来自视神经裂闭合部位及发育阶段（第10.5至12.5天）的激光捕获显微切割（LCM）细胞的微阵列数据。
我们的非线性方法创建了基因簇，这些基因簇映射到与眼睛发育相关的更具体的生物学过程和功能上，与传统线性聚类算法相比，其错误发现率更低，这是由基因本体论定义的。我们的新方法基于LCM的优势，在复杂组织中分离出纯表型群体，以便识别低拷贝数表达的关键基因产物之间的系统生物学关系。
胚胎器官的LCM、基因表达微阵列以及带标记的非线性降维相结合，是一种潜在有用的方法，可用于提取基因调控网络中细微的时空协变，这些基因调控网络决定了哺乳动物的器官发生和器官功能。我们的结果促使对来自LCM切割组织或其他细胞特异性样本的其他微阵列数据集中带标记的非线性降维进行进一步分析，以确定我们的方法在揭示更具体的生物学功能关系方面的更普遍效用。
