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利用机器学习将转移基因的影响与毛状根中的激素谱和形态特征联系起来。

Using machine learning to link the influence of transferred genes to the hormone profile and morphological traits in hairy roots.

作者信息

Alcalde Miguel Angel, Müller Maren, Munné-Bosch Sergi, Landín Mariana, Gallego Pedro Pablo, Bonfill Mercedes, Palazon Javier, Hidalgo-Martinez Diego

机构信息

Department of Biology, Healthcare and the Environment, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, Spain.

Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Barcelona, Spain.

出版信息

Front Plant Sci. 2022 Sep 2;13:1001023. doi: 10.3389/fpls.2022.1001023. eCollection 2022.

DOI:10.3389/fpls.2022.1001023
PMID:36119596
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9479193/
Abstract

Hairy roots are made after the integration of a small set of genes from 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 hairy root line cultures to determine the putative links between the and gene expressions with morphological traits, a hormone profile, and centelloside production. The results obtained after 14 and 28 days of culture were processed 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 ( and 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 has a significant influence on the IPA profile, while the 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.

摘要

毛状根是通过将一小部分基因整合到植物基因组中后形成的。关于这一小部分基因如何与它们的激素谱相关联,人们知之甚少,而激素谱决定了植物的发育、形态以及次生代谢产物的产生水平。我们使用毛状根系培养物来确定基因表达与形态特征、激素谱以及积雪草苷产量之间的假定联系。在培养14天和28天后获得的结果经过多变量分析以及随机森林、支持向量机、线性判别分析和神经网络等机器学习过程进行处理。这使我们能够获得能够根据基因表达水平(和基因)或激素谱来区分高产根系的模型。总共评估了12种激素,其中10种被成功检测到。在这组激素中,脱落酸(ABA)和细胞分裂素异戊烯基腺苷(IPA)被发现对定义形态特征和积雪草苷含量至关重要。结果表明,IPA对生物技术平台更有益。此外,我们确定了每个评估基因对个体激素谱的影响程度,发现对IPA谱有显著影响,而基因与ABA谱密切相关。最后,我们通过旨在逆转对根系形态和积雪草苷含量影响的饲喂实验有效地验证了基因对这两种特定激素的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/c57d60a443d9/fpls-13-1001023-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/ba20231ceefe/fpls-13-1001023-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/07f5b67cdf33/fpls-13-1001023-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/e1a8b48b9a6b/fpls-13-1001023-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/2c36a4e75599/fpls-13-1001023-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/fcfe277107d9/fpls-13-1001023-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/017315627116/fpls-13-1001023-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/c57d60a443d9/fpls-13-1001023-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/ba20231ceefe/fpls-13-1001023-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/07f5b67cdf33/fpls-13-1001023-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/e1a8b48b9a6b/fpls-13-1001023-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/2c36a4e75599/fpls-13-1001023-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/fcfe277107d9/fpls-13-1001023-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/017315627116/fpls-13-1001023-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c5/9479193/c57d60a443d9/fpls-13-1001023-g007.jpg

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