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Using machine learning to link the influence of transferred Agrobacterium rhizogenes genes to the hormone profile and morphological traits in Centella asiatica hairy roots
by
Palazon, Javier
, Landín, Mariana
, Hidalgo-Martinez, Diego
, Müller, Maren
, Gallego, Pedro Pablo
, Bonfill, Mercedes
, Alcalde, Miguel Angel
, Munné-Bosch, Sergi
in
Abscisic acid
/ Adenosine
/ Agrobacterium rhizogenes
/ Biotechnology
/ Centella asiatica
/ centellosides
/ Cytokinins
/ Discriminant analysis
/ Gene expression
/ Genes
/ Genomes
/ Hairy root
/ hairy root cultures
/ Hormones
/ Learning algorithms
/ Machine learning
/ Metabolism
/ Metabolites
/ Morphology
/ Multivariate analysis
/ Neural networks
/ Phytochemicals
/ plant hormones
/ Plant Science
/ Plasmids
/ Roots
2022
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Using machine learning to link the influence of transferred Agrobacterium rhizogenes genes to the hormone profile and morphological traits in Centella asiatica hairy roots
by
Palazon, Javier
, Landín, Mariana
, Hidalgo-Martinez, Diego
, Müller, Maren
, Gallego, Pedro Pablo
, Bonfill, Mercedes
, Alcalde, Miguel Angel
, Munné-Bosch, Sergi
in
Abscisic acid
/ Adenosine
/ Agrobacterium rhizogenes
/ Biotechnology
/ Centella asiatica
/ centellosides
/ Cytokinins
/ Discriminant analysis
/ Gene expression
/ Genes
/ Genomes
/ Hairy root
/ hairy root cultures
/ Hormones
/ Learning algorithms
/ Machine learning
/ Metabolism
/ Metabolites
/ Morphology
/ Multivariate analysis
/ Neural networks
/ Phytochemicals
/ plant hormones
/ Plant Science
/ Plasmids
/ Roots
2022
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Using machine learning to link the influence of transferred Agrobacterium rhizogenes genes to the hormone profile and morphological traits in Centella asiatica hairy roots
by
Palazon, Javier
, Landín, Mariana
, Hidalgo-Martinez, Diego
, Müller, Maren
, Gallego, Pedro Pablo
, Bonfill, Mercedes
, Alcalde, Miguel Angel
, Munné-Bosch, Sergi
in
Abscisic acid
/ Adenosine
/ Agrobacterium rhizogenes
/ Biotechnology
/ Centella asiatica
/ centellosides
/ Cytokinins
/ Discriminant analysis
/ Gene expression
/ Genes
/ Genomes
/ Hairy root
/ hairy root cultures
/ Hormones
/ Learning algorithms
/ Machine learning
/ Metabolism
/ Metabolites
/ Morphology
/ Multivariate analysis
/ Neural networks
/ Phytochemicals
/ plant hormones
/ Plant Science
/ Plasmids
/ Roots
2022
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Using machine learning to link the influence of transferred Agrobacterium rhizogenes genes to the hormone profile and morphological traits in Centella asiatica hairy roots
Journal Article
Using machine learning to link the influence of transferred Agrobacterium rhizogenes genes to the hormone profile and morphological traits in Centella asiatica hairy roots
2022
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Overview
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.
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