Data_Sheet_1_Using machine learning to link the influence of transferred Agrobacterium rhizogenes genes to the hormone profile and morphological traits in Centella asiatica hairy roots.PDF

Hairy roots are made after the integration of a small set of genes from Agrobacterium rhizogenes in the plant genome. Little is known about how this small set is linked to their hormone profile, which determines development, morphology, and levels of secondary metabolite production. We used C. asiatica hairy root line cultures to determine the putative links between the rol and aux gene expressions with morphological traits, a hormone profile, and centelloside production. The results obtained after 14 and 28 days of culture were processed via multivariate analysis and machine-learning processes such as random forest, supported vector machines, linear discriminant analysis, and neural networks. This allowed us to obtain models capable of discriminating highly productive root lines from their levels of genetic expression (rol and aux genes) or from their hormone profile. In total, 12 hormones were evaluated, resulting in 10 being satisfactorily detected. Within this set of hormones, abscisic acid (ABA) and cytokinin isopentenyl adenosine (IPA) were found to be critical in defining the morphological traits and centelloside content. The results showed that IPA brings more benefits to the biotechnological platform. Additionally, we determined the degree of influence of each of the evaluated genes on the individual hormone profile, finding that aux1 has a significant influence on the IPA profile, while the rol genes are closely linked to the ABA profile. Finally, we effectively verified the gene influence on these two specific hormones through feeding experiments that aimed to reverse the effect on root morphology and centelloside content.

发根（hairy roots）是通过将发根农杆菌（Agrobacterium rhizogenes）的一组小型基因整合至植物基因组后获得的。目前学界对于这组小型基因如何与发根的激素谱相关联尚不清楚，而激素谱正是决定植物发育、形态结构以及次生代谢产物生成量的核心因素。本研究采用积雪草（Centella asiatica）发根株系培养体系，探究rol基因与aux基因的表达量与形态性状、激素谱及积雪草苷（centelloside）生成量之间的潜在关联。本研究对培养14天与28天后获得的实验结果，采用多元统计分析及随机森林（random forest）、支持向量机（support vector machines）、线性判别分析（linear discriminant analysis）以及神经网络（neural networks）等机器学习方法进行处理。该分析流程帮助我们构建了可通过基因表达量（rol与aux基因）或激素谱，精准区分高产发根株系的预测模型。本研究共检测12种激素，最终成功定量检出10种。在检出的激素中，脱落酸（abscisic acid, ABA）与细胞分裂素异戊烯基腺苷（isopentenyl adenosine, IPA）被证实是调控形态性状与积雪草苷含量的关键因子。研究结果表明，IPA对该生物技术平台具有更积极的应用价值。此外，本研究明确了各待测基因对单种激素谱的影响程度，发现aux1基因对IPA谱具有显著调控作用，而rol基因则与ABA谱紧密相关。最后，本研究通过饲喂实验（旨在逆转其对发根形态及积雪草苷含量的影响），有效验证了上述两类基因对这两种特定激素的调控作用。