Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

<strong>Understanding the genetic regulatory code that governs gene expression is a primary challenge in molecular biology that opens up possibilities to cure human diseases and solve biotechnology problems. However, the fundamental question of how each of the individual coding and non-coding regions of the gene regulatory structure interact and contribute to the mRNA expression levels remains unanswered. Considering that all the information for gene expression regulation is already present in living cells, here we applied deep learning on over 20,000 mRNA datasets to discover the genetic regulatory code controlling mRNA expression in 7 model organisms ranging from bacteria to Human. We show that in all organisms, mRNA abundance can be predicted directly from the DNA sequence with high accuracy, demonstrating that up to 82% of the variation of gene expression levels is encoded in the gene regulatory structure. Coding and non-coding regions carry both overlapping and orthogonal information and jointly contribute to gene expression levels. By searching for DNA regulatory motifs present across the whole gene regulatory structure, we discover that motif interactions can regulate gene expression levels in a range of over three orders of magnitude. The uncovered co-evolution of coding and non-coding regions challenges the current paradigm that single motifs or regions are solely responsible for gene expression levels. Instead, we demonstrate how the holistic system that spans the entire gene regulatory structure, and which contains the right combination of all regulatory elements, is required to understand, control, and design any future gene expression systems.</strong>解析调控基因表达的遗传调控密码，是分子生物学领域的核心挑战之一，可为人类疾病治疗与生物技术难题破解提供全新路径。然而，基因调控结构中各个编码区与非编码区如何相互作用、共同影响信使RNA（messenger RNA，mRNA）表达水平这一核心科学问题，至今仍未得到解答。鉴于基因表达调控的全部信息均已存在于活体细胞中，本研究基于超20000个mRNA数据集开展深度学习（deep learning）研究，在从细菌到人类的7种模式生物中发掘调控mRNA表达的遗传调控密码。研究表明，在所有受试生物中，均可直接从DNA序列高精度预测mRNA丰度，这证实了高达82%的基因表达水平变异可由基因调控结构编码得到。编码区与非编码区携带重叠且正交的调控信息，二者共同参与调控基因表达水平。通过扫描覆盖整个基因调控结构的DNA调控基序（DNA regulatory motif），本研究发现基序间的相互作用可在超过三个数量级的范围内调控基因表达水平。本研究揭示的编码区与非编码区协同进化现象，对当前"单一基序或区域单独决定基因表达水平"的主流范式提出了挑战。取而代之的是，本研究证实，要理解、调控并设计未来的基因表达系统，必须依托覆盖整个基因调控结构、包含所有调控元件正确组合的整体系统。