scholarly journals Modeling cross-regulatory influences on monolignol transcripts and proteins under single and combinatorial gene knockdowns in Populus trichocarpa

2019 ◽  
Author(s):  
Megan L. Matthews ◽  
Jack P. Wang ◽  
Ronald Sederoff ◽  
Vincent L. Chiang ◽  
Cranos M. Williams
Keyword(s):  
Computational Model ◽  
Biosynthetic Pathway ◽  
Computational Models ◽  
Lignin Content ◽  
Populus Trichocarpa ◽  
Lignin Biosynthesis ◽  
Wood Properties ◽  
Specific Gene ◽  
Driving Mechanisms ◽  
Wood Traits

AbstractAccurate manipulation of metabolites in the monolignol biosynthetic pathway is a key step for controlling lignin content, structure, and other wood properties important to the bioenergy and biomaterial industries. A crucial component of this strategy is predicting how single and combinatorial knockdowns of monolignol specific gene transcripts influence the abundance of monolignol proteins, which are the driving mechanisms of monolignol biosynthesis. Computational models have been developed to estimate protein abundances from transcript perturbations of monolignol specific genes. The accuracy of these models, however, is hindered by the inability to capture indirect regulatory influences on other pathway genes. Here, we examine the manifestation of these indirect influences collectively on transgenic transcript and protein abundances, identifying putative indirect regulatory influences that occur when one or more specific monolignol pathway genes are perturbed. We created a computational model using sparse maximum likelihood to estimate the resulting monolignol transcript and protein abundances in transgenic Populus trichocarpa based on desired single or combinatorial knockdowns of specific monolignol genes. Using in-silico simulations of this model and root mean square error, we show that our model more accurately estimates transcript and protein abundances in differentiating xylem tissue when individual and families of monolignol genes were perturbed. This approach provides a useful computational tool for exploring the cascaded impact of single and combinatorial modifications of monolignol specific genes on lignin and other wood properties. Additionally, these results can be used to guide future experiments to elucidate the mechanisms responsible for the indirect influences.Author summaryEngineering trees to have desirable lignin and wood traits is of significant interest to the bioenergy and biomaterial industries. Genetically modifying the expression of the genes that drive the monolignol biosynthetic pathway is a useful method for obtaining new traits. Modifying the expression of one gene affects not only the abundance of its encoded protein, but can also indirectly impact the amount of other transcripts and proteins. These proteins drive the monolignol biosynthetic pathway. Having an accurate representation of their abundances is key to understanding how lignin and wood traits are altered. We developed a computational model to estimate how the abundance of monolignol transcripts and proteins are changed when one or more monolignol genes are knocked down. Specifying only the abundances of the targeted genes as input, our model estimates how the levels of the other, untargeted, transcripts and proteins are altered. Our model captures indirect regulatory influences at the transcript and protein levels observed in experimental data. The model is an important addition to current models of lignin biosynthesis. By incorporating our approach into the existing models, we expect to improve our ability to explore how new combinations of gene knockdowns impact lignin and many other wood properties.

scholarly journals Characterization and functional analysis of the Hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase (HCT) gene family in poplar

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10741
Author(s):  
Nan Chao ◽  
Qi Qi ◽  
Shuang Li ◽  
Brent Ruan ◽  
Xiangning Jiang ◽  
...  
Keyword(s):  
Shikimic Acid ◽  
Lignin Content ◽  
Expression Profiles ◽  
Populus Trichocarpa ◽  
Functional Divergence ◽  
Lignin Biosynthesis ◽  
Populus Tomentosa ◽  
Motif Analysis ◽  
Monolignol Biosynthesis ◽  
Populus Tomentosa Carr

Hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase (HCT) divides the mass flux to H, G and S units in monolignol biosynthesis and affects lignin content. Ten HCT homologs were identified in the Populus trichocarpa (Torr. & Gray) genome. Both genome duplication and tandem duplication resulted in the expansion of HCT orthologs in Populus. Comprehensive analysis including motif analysis, phylogenetic analysis, expression profiles and co-expression analysis revealed the divergence and putative function of these candidate PoptrHCTs. PoptrHCT1 and 2 were identified as likely involved in lignin biosynthesis. PoptrHCT9 and 10- are likely to be involved in plant development and the response to cold stress. Similar functional divergence was also identified in Populus tomentosa Carr. Enzymatic assay of PtoHCT1 showed that PtoHCT1 was able to synthesize caffeoyl shikimate using caffeoyl-CoA and shikimic acid as substrates.

scholarly journals Growth under field conditions affects lignin content and productivity in transgenic Populus trichocarpa with altered lignin biosynthesis

2014 ◽  
Vol 68 ◽  
pp. 228-239 ◽  
Author(s):  
Anna T. Stout ◽  
Aletta A. Davis ◽  
Jean-Christophe Domec ◽  
Chenmin Yang ◽  
Rui Shi ◽  
...  
Keyword(s):  
Lignin Content ◽  
Populus Trichocarpa ◽  
Lignin Biosynthesis ◽  
Field Conditions

scholarly journals Inheritance and Correlation Analysis of Pulpwood Properties, Wood Density, and Growth Traits of Slash Pine

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 493 ◽  
Author(s):  
Yanjie Li ◽  
Xianyin Ding ◽  
Jingmin Jiang ◽  
Qifu Luan
Keyword(s):  
Wood Density ◽  
Growth Traits ◽  
Lignin Content ◽  
Pinus Elliottii ◽  
Wood Properties ◽  
Slash Pine ◽  
Wood Traits ◽  
Breeding Selection ◽  
The Relationship

Slash pine (Pinus elliottii) is the most important and a fast-growing material that is used for industrial timber and pulp production. A breeding program of slash pine that aims to improve wood properties has been employed for the past decade. This study analysed the genetics and correlation of growth traits and wood properties of a total of 1059 individual plants from 49 families of P. elliottii. Heritability, family ranking, genetic gain, and the relationship between these traits were estimated. The results showed that there was a significant negative genetic correlation between the holocellulose and lignin content. The heritabilities of these four traits were ranked from 0.18 to 0.32. The chemical wood traits did not show a strong correlation with diameter at breast height (DBH) and wood density. However, it is still possible to combine wood traits for selection. It was suggested that the genetic breeding selection could improve the growth and quality of P. elliottii.

CSBPI_Site：Multi-Information Sources of Features to RNA Binding Sites Prediction

2021 ◽  
Vol 15 ◽  
Author(s):  
Lichao Zhang ◽  
Zihong Huang ◽  
Liang Kong
Keyword(s):  
Computational Model ◽  
Binding Sites ◽  
Noncoding Rna ◽  
Computational Models ◽  
Information Sources ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Gradient Boosting ◽  
Position Information ◽  
Rna Binding Sites

Background: RNA-binding proteins establish posttranscriptional gene regulation by coordinating the maturation, editing, transport, stability, and translation of cellular RNAs. The immunoprecipitation experiments could identify interaction between RNA and proteins, but they are limited due to the experimental environment and material. Therefore, it is essential to construct computational models to identify the function sites. Objective: Although some computational methods have been proposed to predict RNA binding sites, the accuracy could be further improved. Moreover, it is necessary to construct a dataset with more samples to design a reliable model. Here we present a computational model based on multi-information sources to identify RNA binding sites. Method: We construct an accurate computational model named CSBPI_Site, based on xtreme gradient boosting. The specifically designed 15-dimensional feature vector captures four types of information (chemical shift, chemical bond, chemical properties and position information). Results: The satisfied accuracy of 0.86 and AUC of 0.89 were obtained by leave-one-out cross validation. Meanwhile, the accuracies were slightly different (range from 0.83 to 0.85) among three classifiers algorithm, which showed the novel features are stable and fit to multiple classifiers. These results showed that the proposed method is effective and robust for noncoding RNA binding sites identification. Conclusion: Our method based on multi-information sources is effective to represent the binding sites information among ncRNAs. The satisfied prediction results of Diels-Alder riboz-yme based on CSBPI_Site indicates that our model is valuable to identify the function site.

scholarly journals Numerical and Experimental Investigations on Vocal Fold Approximation in Healthy and Simulated Unilateral Vocal Fold Paralysis

2021 ◽  
Vol 11 (4) ◽  
pp. 1817
Author(s):  
Zheng Li ◽  
Azure Wilson ◽  
Lea Sayce ◽  
Amit Avhad ◽  
Bernard Rousseau ◽  
...  
Keyword(s):  
Computational Model ◽  
Vocal Fold ◽  
High Speed ◽  
Computational Models ◽  
Ex Vivo ◽  
Vocal Fold Paralysis ◽  
Future Application ◽  
Experimental Investigations ◽  
Type I ◽  
Mri Scans

We have developed a novel surgical/computational model for the investigation of unilat-eral vocal fold paralysis (UVFP) which will be used to inform future in silico approaches to improve surgical outcomes in type I thyroplasty. Healthy phonation (HP) was achieved using cricothyroid suture approximation on both sides of the larynx to generate symmetrical vocal fold closure. Following high-speed videoendoscopy (HSV) capture, sutures on the right side of the larynx were removed, partially releasing tension unilaterally and generating asymmetric vocal fold closure characteristic of UVFP (sUVFP condition). HSV revealed symmetric vibration in HP, while in sUVFP the sutured side demonstrated a higher frequency (10–11%). For the computational model, ex vivo magnetic resonance imaging (MRI) scans were captured at three configurations: non-approximated (NA), HP, and sUVFP. A finite-element method (FEM) model was built, in which cartilage displacements from the MRI images were used to prescribe the adduction, and the vocal fold deformation was simulated before the eigenmode calculation. The results showed that the frequency comparison between the two sides was consistent with observations from HSV. This alignment between the surgical and computational models supports the future application of these methods for the investigation of treatment for UVFP.

scholarly journals Targeting hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase for lignin modification in Brachypodium distachyon

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Juan Carlos Serrani-Yarce ◽  
Luis Escamilla-Trevino ◽  
Jaime Barros ◽  
Lina Gallego-Giraldo ◽  
Yunqiao Pu ◽  
...  
Keyword(s):  
Negative Impact ◽  
Lignin Content ◽  
Brachypodium Distachyon ◽  
Lignin Biosynthesis ◽  
Reverse Direction ◽  
Wall Structure ◽  
Kinetic Properties ◽  
Loss Of Function ◽  
Down Regulation ◽  
Lignin Modification

Abstract Background Hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT) is a central enzyme of the so-called “esters” pathway to monolignols. As originally envisioned, HCT functions twice in this pathway, to form coumaroyl shikimate and then, in the “reverse” direction, to convert caffeoyl shikimate to caffeoyl CoA. The discovery of a caffeoyl shikimate esterase (CSE) that forms caffeic acid directly from caffeoyl shikimate calls into question the need for the reverse HCT reaction in lignin biosynthesis. Loss of function of HCT gives severe growth phenotypes in several dicot plants, but less so in some monocots, questioning whether this enzyme, and therefore the shikimate shunt, plays the same role in both monocots and dicots. The model grass Brachypodium distachyon has two HCT genes, but lacks a classical CSE gene. This study was therefore conducted to evaluate the utility of HCT as a target for lignin modification in a species with an “incomplete” shikimate shunt. Results The kinetic properties of recombinant B. distachyon HCTs were compared with those from Arabidopsis thaliana, Medicago truncatula, and Panicum virgatum (switchgrass) for both the forward and reverse reactions. Along with two M. truncatula HCTs, B. distachyon HCT2 had the least kinetically unfavorable reverse HCT reaction, and this enzyme is induced when HCT1 is down-regulated. Down regulation of B. distachyon HCT1, or co-down-regulation of HCT1 and HCT2, by RNA interference led to reduced lignin levels, with only modest changes in lignin composition and molecular weight. Conclusions Down-regulation of HCT1, or co-down-regulation of both HCT genes, in B. distachyon results in less extensive changes in lignin content/composition and cell wall structure than observed following HCT down-regulation in dicots, with little negative impact on biomass yield. Nevertheless, HCT down-regulation leads to significant improvements in biomass saccharification efficiency, making this gene a preferred target for biotechnological improvement of grasses for bioprocessing.

scholarly journals Identification of genetic markers and wood properties that predict wood biorefinery potential in aspen bioenergy feedstock (Populus tremula).

2021 ◽  
Author(s):  
Sacha Escamez ◽  
Mikko Luomaranta ◽  
Niklas Mahler ◽  
Madhavi Latha Gandla ◽  
Kathryn M Robinson ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Genetic Markers ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Wood Properties ◽  
Yield Traits ◽  
Bioenergy Feedstock ◽  
European Aspen ◽  
Wood Traits ◽  
Wood Chemical Composition

Wood represents the majority of the biomass on lands, and it constitutes a renewable source of biofuels and other bioproducts. However, wood is recalcitrant to bioconversion, meaning that feedstocks must be improved. We investigated the properties of wood that affect bioconversion, as well as the underlying genetics, to help identify superior biorefinery tree feedstocks. We recorded as many as 65 wood-related and growth traits in a population of European aspen natural genotypes. These traits included three growth and field performance traits, 20 traits for wood chemical composition, 17 traits for wood anatomy and structure, and 25 wood saccharification traits as indicators of bioconversion potential. We used statistical modelling to determine which wood traits best predict bioconversion yield traits. This way, we identified a core set of wood properties that predict bioprocessing traits. Several of these predictor traits showed high broad-sense heritability, suggesting potential for genetic improvement of feedstocks. Finally, we performed genome-wide association study (GWAS) to identify genetic markers for yield traits or for wood traits that predict yield. GWAS revealed only a few genetic markers for saccharification yield traits, but many more SNPs were associated with wood chemical composition traits, including predictors traits for saccharification. Among them, 16 genetic markers associated specifically with lignin chemical composition were situated in and around two genes which had not previously been associated with lignin. Our approach allowed linking aspen wood bioprocessing yield to wood properties and the underlying genetics, including the discovery of two new potential regulator genes for wood chemical composition.

scholarly journals Distinct and overlapping functions of Miscanthus sinensis MYB transcription factors SCM1 and MYB103 in lignin biosynthesis

2019 ◽  
Author(s):  
Philippe Golfier ◽  
Faride Unda ◽  
Emily K. Murphy ◽  
Jianbo Xie ◽  
Feng He ◽  
...  
Keyword(s):  
Cell Wall ◽  
Transcriptional Regulation ◽  
Secondary Cell Wall ◽  
Lignin Content ◽  
Lignin Biosynthesis ◽  
Miscanthus Sinensis ◽  
Cell Wall Formation ◽  
Transcriptional Responses ◽  
Secondary Cell Wall Formation ◽  
Wall Formation

AbstractCell wall recalcitrance is a major constraint for the exploitation of lignocellulosic biomass as renewable resource for energy and bio-based products. Transcriptional regulators of the lignin biosynthetic pathway represent promising targets for tailoring lignin content and composition in plant secondary cell walls. A wealth of research in model organisms has revealed that transcriptional regulation of secondary cell wall formation is orchestrated by a hierarchical transcription factor (TF) network with NAC TFs as master regulators and MYB factors in the lower tier regulators. However, knowledge about the transcriptional regulation of lignin biosynthesis in lignocellulosic feedstocks, such as Miscanthus, is limited. Here, we characterized two Miscanthus MYB TFs, MsSCM1 and MsMYB103, and compared their transcriptional impact with that of the master regulator MsSND1. In Miscanthus leaves MsSCM1 and MsMYB103 are expressed at growth stages associated with lignification. Ectopic expression of MsSCM1 and MsMYB103 in tobacco leaves was sufficient to trigger secondary cell wall deposition with distinct sugar and lignin composition. Moreover, RNA-seq analysis revealed that the transcriptional responses to MsSCM1 and MsMYB103 overexpression showed extensive overlap with the response to MsSND1, but were distinct from each other, underscoring the inherent complexity of secondary cell wall formation. Together, MsSCM1 and MsMYB103 represent interesting targets for manipulations of lignin content and composition in Miscanthus towards tailored biomass.

scholarly journals The Exponential-Weight Mean-Variance Model: A novel computational model for the Balloon Analogue Risk Task

2019 ◽  
Author(s):  
Harhim Park ◽  
Jaeyeong Yang ◽  
Jasmin Vassileva ◽  
Woo-Young Ahn
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
Model Comparison ◽  
Exponential Weight ◽  
Multiple Model ◽  
Variance Model ◽  
Balloon Analogue Risk Task ◽  
Parameter Recovery ◽  
Post Hoc ◽  
Mean Variance

The Balloon Analogue Risk Task (BART) is a popular task used to measure risk-taking behavior. To identify cognitive processes associated with choice behavior on the BART, a few computational models have been proposed. However, the extant models are either too simplistic or fail to show good parameter recovery performance. Here, we propose a novel computational model, the exponential-weight mean-variance (EWMV) model, which addresses the limitations of existing models. By using multiple model comparison methods, including post hoc model fits criterion and parameter recovery, we showed that the EWMV model outperforms the existing models. In addition, we applied the EWMV model to BART data from healthy controls and substance-using populations (patients with past opiate and stimulant dependence). The results suggest that (1) the EWMV model addresses the limitations of existing models and (2) heroin-dependent individuals show reduced risk preference than other groups in the BART.

Sign in / Sign up

Export Citation Format

Share Document