Profiling expression patterns of 2,214 unigenes in mouse craniofacial development by cDNA microarray analysis
Profiling expression patterns of 2,214 unigenes in mouse craniofacial development by cDNA microarray analysis
复制标题
通过 cDNA 微阵列分析分析小鼠颅面发育中 2,214 个 unigene 的表达模式
作者:
Haochuan Li;Yidong Chen;Yuan Jiang;M. Bittner;P. Meltzer;J. Trent;Kenneth M. Yamada;Yoshihiko Yamada
The recent development of cDNA microarray technology enables parallel expression monitoring of thousands of genes simultaneously, which provides a powerful tool for characterizing transcriptional activities of genes in various developmental stages and pathological states. We initiated the Oral and Craniofacial Genome Anatomy Project (OC-GAP) to identify genes important for craniofacial development and disorders. As part of this genome project, we have examined gene expression patterns during mouse craniofacial development. Fluorescently labelled probes prepared using mRNA from mouse embryonic craniofacial tissues at embryonic day (E) 9.5, E13.5 and E16.5 were hybridized to microarray slides printed with 2,214 mouse unigenes. A microarray quantitative analysis revealed that 10% of these genes were expressed in different levels during craniofacial development, whereas the rest showed no significant differences in expression throughout the different developmental stages. We found that 41 genes, such as those encoding Wnt-1, retinoid receptor and Brca1, showed higher expression levels at E9.5; 54 genes, such as those encoding Bmp-1, IGF II and Sox3, were more highly expressed at E13.5; and another 126 genes, such as those encoding Mash 1, FHF-1 and fibulin-2, were expressed at higher levels at E16.5. The identification of these genes with highly stage-specific expression during craniofacial development is potentially important because they are likely to have key roles in the formation of craniofacial tissues. We are currently studying expression patterns of genes from an E8.5−9.5 mouse craniofacial cDNA library to identify novel craniofacial genes by microarray screening approaches.