Large amounts of effort have been invested in trying to understand how a single genome is able to specify the identity of hundreds of cell types. Inspired by some aspects of Caenorhabditis elegans biology, we implemented an in silico evolutionary strategy to produce gene regulatory networks (GRNs) that drive cell-specific gene expression patterns, mimicking the process of terminal cell differentiation. Dynamics of the gene regulatory networks are governed by a thermodynamic model of gene expression, which uses DNA sequences and transcription factor degenerate position weight matrixes as input. In a version of the model, we included chromatin accessibility. Experimentally, it has been determined that cell-specific and broadly expressed genes are regulated differently. In our in silico evolved GRNs, broadly expressed genes are regulated very redundantly and the architecture of their cis-regulatory modules is different, in accordance to what has been found in C. elegans and also in other systems. Finally, we found differences in topological positions in GRNs between these two classes of genes, which help to explain why broadly expressed genes are so resilient to mutations. Overall, our results offer an explanatory hypothesis on why broadly expressed genes are regulated so redundantly compared to cell-specific genes, which can be extrapolated to phenomena such as ChIP-seq HOT regions.

人们投入了大量的精力来试图了解单个基因组如何能够指定数百种细胞类型的身份。受秀丽隐杆线虫生物学某些方面的启发，我们实施了一种计算机进化策略来产生驱动细胞特异性基因表达模式的基因调控网络（GRN），模仿终末细胞分化的过程。基因调控网络的动力学由基因表达的热力学模型控制，该模型使用 DNA 序列和转录因子简并位置权重矩阵作为输入。在该模型的一个版本中，我们包含了染色质可及性。实验表明，细胞特异性基因和广泛表达的基因受到不同的调控。在我们的计算机进化的GRN中，广泛表达的基因受到非常冗余的调节，并且它们的顺式调节模块的结构是不同的，这与在C中发现的一致。线虫以及其他系统。最后，我们发现这两类基因在 GRN 中的拓扑位置存在差异，这有助于解释为什么广泛表达的基因对突变具有如此大的弹性。总的来说，我们的结果提供了一个解释性假设，解释为什么与细胞特异性基因相比，广泛表达的基因受到如此冗余的调控，这可以推断到 ChIP-seq HOT 区域等现象。