Functional Genomics of Dictyostelium Development

利用携带5569个cdna以及数百个先前定义的盘基骨菌基因的微阵列，我们可以检查整个24小时周期中几乎所有发育基因的表达模式。基因将根据它们活跃的时间和细胞类型进行聚类，并用于定义发育阶段，以及对生理上重要的分化提供见解。在这个系统中发展的同步性是这样的，我们有统计上显著的2小时时间分辨率。通过对携带特定发育基因零突变的菌株进行微阵列分析，可以进一步确定发育过程中协调和调节细胞功能的遗传网络。内部cAMP和cAMP依赖性蛋白激酶PKA的相对发育作用将通过对缺乏一个或多个cAMP反应积累基因的菌株进行微阵列分析来确定。我们的总体目标有4个：1)利用携带全套靶基因的微阵列，建立NC44和AX4菌株基因表达的详细发育模式。基因将根据其细胞类型特异性和表达谱进行聚类。2)将对PKA调控改变的菌株进行微阵列表达分析，包括影响腺苷环化酶、cAMP磷酸二酯酶、cAMP受体、PKA和这些成分的调节剂的突变菌株。其中一些突变会影响发育速度。它们对表达概要的时间影响将为聚类增加另一个维度。3)转录因子MybB、GBF、STAT1和MybC的完整发育作用将通过比较缺乏这些因子的突变菌株与野生型菌株的集群特征来评估。4)各种特定发育基因的零突变对基因簇表达的影响将用于构建因果事件网络，该网络可能解释该系统中时间和细胞类型特异性分化。当微阵列分析扩展到包括进一步的发育突变时，从这些网络中得出的预测将得到检验。

Using microarrays carrying 5, 569 cDNAs as well as several hundred previously defined Dictyostelium genes, we can examine the expression patterns of almost all developmental genes throughout the 24 hour cycle. Genes will be clustered on the basis of the time and cell type in which they are active and used to define developmental stages as well as give insight into physiologically significant differentiations. The synchrony of development in this system is such we have statistically significant 2 hour temporal resolution. The genetic networks that coordinate and modulate cellular functions during development can be further defined by microarray analyses of strains carrying null mutations in specific developmental genes. The relative developmental roles of internal cAMP and the cAMP dependent protein kinase PKA will be determined by microarray analyses of strains lacking one or more of the genes responsible for accumulation of response to cAMP. We have 4 general aims: 1) Detailed developmental patterns of gene expression will be established for strains NC44 and AX4 with microarrays carrying the full set of targets. Genes will be clustered on the basis of their cell-type specificity and expression profiles. 2) Microarray expression analyses will be carried out on strains with altered PKA regulation including those with mutations affecting adenyly cyclases, cAMP phosphodiesterases, cAMP receptors, PKA and modulators of these components. Several of these mutations affect the rate of development. Their temporal consequences to expression profiles will add another dimension to clustering. 3) The full developmental roles of the transcription factors MybB, GBF, STAT1, and MybC will be assessed by comparing cluster profiles in mutant strains lacking these factors to those in wild type strains. 4)The effects of null mutations in various specific developmental genes on the expression of clusters of genes will be used to construct networks of causal events that may account for temporal and cell-type specific differentiations in this system. Predictions derived from such networks will be tested when microarray analyses are extended to include further developmental mutants.