Genomic-Functional Analyses-Conserved Noncoding Regions

基因组功能分析科的主要目标是通过比较分析确定脊椎动物基因组中顺式和反式作用的功能元件。该方法利用多物种全基因组序列比对来识别保守的非编码区，检查这些元件中序列突变的模式，并测试与通过物种形成事件获得的序列的变化相对应的表达水平的变化。正在考虑的功能元件包括任何组成转录因子结合位点集合的元件，如增强子、沉默因子、启动子和microRNA调节区，异常保守的元件，如超保守元件，或包含未表征的结构特征的元件，如复制起点。 我与宾夕法尼亚州立大学的合作努力导致了启动子的进化分析，这些启动子通过使用人/狗/鼠/鸡的多物种序列比对来研究Tata基序或CpG岛上的选择。第二项研究还利用序列比较来寻找可能的调控基序，控制非基因位置的microRNA的表达。与NHGRI的一项相关合作工作涉及建立一个数据库来存储来自ENCODE联盟的微阵列数据。这些重要数据包含通过芯片分析确定的转录因子结合位点的信息。这些数据被用作前述基因组调节区预测的阳性对照，并用于识别作为未来实验分析目标的区域。

The major aims of the Genomic Functional Analysis Section are to identify cis-and trans-acting functional elements in vertebrate genomes using comparative analyses. The approach utilizes multi-species, whole-genome sequence alignments to identify conserved noncoding regions, examine patterns of sequence mutation within those elements, and test for changes in expression levels that correspond to changes in the sequences acquired through speciation events. Functional elements under consideration include any elements that comprise collections of transcription factor binding sites such as enhancers, silencers, promoters, and microRNA regulatory regions, elements that are exceptionally conserved, such as ultra-conserved elements, or those that contain uncharacterized structural features such as origins of replication. Collaborative efforts of mine with Penn State University have resulted in evolutionary analyses of promoters that study selection on TATA motifs or CpG islands by using multispecies sequence alignments of human/dog/mouse/chicken. A second study also utilizes sequence comparison to find putative regulatory motifs that control the expression of microRNA from nongenic locations. A related collaborative effort, with NHGRI, involves building a database to house microarray data from the ENCODE consortium. These important data contain information on transcription factor binding sites identified through ChIP-chip assays. The data are used as positive controls for the aforementioned predictions of genomic regulatory regions and for the identification of regions that are targets for future experimental analyses.