基因调节网络包括转录调节(transcriptional regulation)、信号传导(signal transduction)和染色体重塑(chromatin modification)。序列多样性(Sequence polymorphisms)通过影响复杂的基因调节网络(regulatory network)影响基因表达。斯坦福大学研究人员Su-In Lee等利用一种叫做Geronemo的方法,直接寻找遗传改变影响调节网络的机制。文章刊登于2006年9月12日PNAS电子版。
Geronemo自发设计出一系列协同基因(coregulated genes 生物通编者译)或称modules(模数)。这些模数的改变能够引发基因改变和调节剂的表达。Geronemo通过利用基因序列调节系统的模块性,能够在一些一直被认为是无关的基因之间找到调节相关性(regulatory relationships),有助于发现复杂的基因调节网络机制。Geronemo将基因型调节物和表达调节物结合考虑,为一些没有直接作用于靶标的序列变异性(sequence variation)捕捉到了结果。
研究人员将实验室培养的BY4716 (BY)啤酒酵母(Saccharomyces cerevisiae.)菌株和野生型RM11-1a (RM) 啤酒酵母菌株杂交,得到杂交后代。利用Geronemo分析杂交后代的资料,推测出一系列从未描述过的有关酵母调节网络遗传机制变化的假说。包括转录调节(transcriptional regulation)、信号传导(signal transduction)和染色体重塑(chromatin modification)。研究人员发现,大量的模数具有染色体特征,而且能够被染色体重塑蛋白调节。事实上,表达中的许多发生变化的小片段可以用一小部分与染色体重塑有关的标记来解释。附加的分析显示,Swi/Snf染色体重塑复合体的序列进化(sequence evolution)是正向选择的结果。
研究人员总结认为,酵母进化过程中存在的个体表达差异,一部分原因是小数量染色体结构重塑。
部分英文原文:
Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification
Sequence polymorphisms affect gene expression by perturbing the complex network of regulatory interactions. We propose a probabilistic method, called Geronemo, which directly aims to identify the mechanism by which genetic changes perturb the regulatory network. Geronemo automatically constructs a set of coregulated genes (modules), whose regulation can involve both sequence variations and expression of regulators. By exploiting the modularity of genetic regulatory systems, Geronemo reveals regulatory relationships that are indiscernible when genes are considered in isolation, allowing the recovery of intricate combinatorial regulation. By incorporating both expression and genotype of regulators, Geronemo captures cases where the effect of sequence variation on its targets is indirect. We applied Geronemo to a data set from the progeny generated by a cross between laboratory BY4716 (BY) and wild RM11-1a (RM) isolates of Saccharomyces cerevisiae. Geronemo produced previously undescribed hypotheses regarding genetic perturbations in the yeast regulatory network, including transcriptional regulation, signal transduction, and chromatin modification. In particular, we find a large number of modules that have both chromosomal characteristics and are regulated by chromatin modification proteins. Indeed, a large fraction of the variance in the expression can be explained by a small number of markers associated with chromatin modifiers. Additional analysis reveals positive selection for sequence evolution of elements in the Swi/Snf chromatin remodeling complex. Overall, our results suggest that a significant part of individual expression variation in yeast arises from evolution of a small number of chromatin structure modifiers.