RECONSTRUCT
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB45810 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR6394690_1.fastq.gz | Fastqsanger.gz | |||
| ERR6394690_2.fastq.gz | Fastqsanger.gz | |||
| ERR6394700_1.fastq.gz | Fastqsanger.gz | |||
| ERR6394700_2.fastq.gz | Fastqsanger.gz | |||
| ERR6394710_1.fastq.gz | Fastqsanger.gz |
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Project description:The proposed project aims to elucidate the gene-regulatory networks (GRNs) underlying terpenoid metabolism in three major bioenergy crops, switchgrass (Panicum virgatum), maize (Zea mays), and sorghum (Sorghum bicolor), to aid crop development for enhanced stress resilience and biofuel production from biomass feedstock. Prior studies identified more than 50 terpene synthases (TPS) and cytochrome P450 monooxygenases (P450), as key enzymes in generating bioactive terpenoids, in several bioenergy plants including switchgrass and maize. This knowledge now enables a precise investigation of the GRNs that govern common and species-specific terpenoid pathways. We will integrate transcription factor (TF) functional studies, TF binding site mapping, transcript and metabolite profiling, and terpenoid pathway engineering to identify the terpenoid-metabolic TF networks mediating stress responses in switchgrass, maize and sorghum.
The work (proposal:https://doi.org/10.46936/10.25585/60001378) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.
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2008-01-29 | GSE10308 | GEO
Project description:Modification of cis regulatory elements to produce differences in gene expression level, localization, and timing is an important mechanism by which organisms evolve divergent adaptations. To examine gene regulatory change during the domestication of maize from its wild progenitor, teosinte, we assessed allele-specific expression in a collection of maize and teosinte inbreds and their F1 hybrids using three tissues from different developmental stages. Our use of F1 hybrids represents the first study in a domesticated crop and wild progenitor that dissects cis and trans regulatory effects to examine characteristics of genes under various cis and trans regulatory regimes. We find evidence for consistent cis regulatory divergence that differentiates maize from teosinte in approximately 4% of genes. These genes are significantly correlated with genes under selection during domestication and crop improvement, suggesting an important role for cis regulatory elements in maize evolution.
2014-11-06 | GSE61810 | GEO
Project description:Modification of cis regulatory elements to produce differences in gene expression level, localization, and timing is an important mechanism by which organisms evolve divergent adaptations. To examine gene regulatory change during the domestication of maize from its wild progenitor, teosinte, we assessed allele-specific expression in a collection of maize and teosinte inbreds and their F1 hybrids using three tissues from different developmental stages. Our use of F1 hybrids represents the first study in a domesticated crop and wild progenitor that dissects cis and trans regulatory effects to examine characteristics of genes under various cis and trans regulatory regimes. We find evidence for consistent cis regulatory divergence that differentiates maize from teosinte in approximately 4% of genes. These genes are significantly correlated with genes under selection during domestication and crop improvement, suggesting an important role for cis regulatory elements in maize evolution. We assayed genome-wide cis and trans regulatory differences between maize and its wild progenitor, teosinte, using deep RNA sequencing in F1 hybrid and parent inbred lines for three tissue types (ear, leaf and stem) followed by assessment of allele-specific gene expression.
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Project description:The depiction of maize chromatin architecture using Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) provides great opportunities to investigate cis-regulatory elements, which is crucial for crop improvement. We demonstrate a streamlined ATAC-seq protocol for maize in which nuclei purification can be achieved without cell sorting, and using only a standard bench-top centrifuge. Our protocol, coupled with the bioinformatic analysis, provides a precise and efficient assessment of the maize chromatin landscape.
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Project description:Saha2011- Genome-scale metabolic network of
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This model is described in the article:
Zea mays iRS1563: a
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Saha R, Suthers PF, Maranas
CD.
PLoS ONE 2011; 6(7): e21784
Abstract:
The scope and breadth of genome-scale metabolic
reconstructions have continued to expand over the last decade.
Herein, we introduce a genome-scale model for a plant with
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rigorous standards on gene-protein-reaction (GPR) associations,
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secondary maize metabolism. For approximately 42% of the
reactions direct literature evidence for the participation of
the reaction in maize was found. As many as 445 reactions and
369 metabolites are unique to the maize model compared to the
AraGEM model for A. thaliana. 674 metabolites and 893 reactions
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and localized into six different compartments (i.e., cytoplasm,
mitochondrion, plastid, peroxisome, vacuole and extracellular).
GPR associations are also established based on the functional
annotation information and homology prediction accounting for
monofunctional, multifunctional and multimeric proteins,
isozymes and protein complexes. We describe results from
performing flux balance analysis under different physiological
conditions, (i.e., photosynthesis, photorespiration and
respiration) of a C4 plant and also explore model predictions
against experimental observations for two naturally occurring
mutants (i.e., bm1 and bm3). The developed model corresponds to
the largest and more complete to-date effort at cataloguing
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This model is hosted on
BioModels Database
and identified by:
MODEL1507180064.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
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Project description:Saha2011 - Genome-scale metabolic network of
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This model is described in the article:
Zea mays iRS1563: a
comprehensive genome-scale metabolic reconstruction of maize
metabolism.
Saha R, Suthers PF, Maranas
CD.
PLoS ONE 2011; 6(7): e21784
Abstract:
The scope and breadth of genome-scale metabolic
reconstructions have continued to expand over the last decade.
Herein, we introduce a genome-scale model for a plant with
direct applications to food and bioenergy production (i.e.,
maize). Maize annotation is still underway, which introduces
significant challenges in the association of metabolic
functions to genes. The developed model is designed to meet
rigorous standards on gene-protein-reaction (GPR) associations,
elementally and charged balanced reactions and a biomass
reaction abstracting the relative contribution of all biomass
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1,825 metabolites involved in 1,985 reactions from primary and
secondary maize metabolism. For approximately 42% of the
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369 metabolites are unique to the maize model compared to the
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are present in Zea mays iRS1563 that are not accounted for in
maize C4GEM. All reactions are elementally and charged balanced
and localized into six different compartments (i.e., cytoplasm,
mitochondrion, plastid, peroxisome, vacuole and extracellular).
GPR associations are also established based on the functional
annotation information and homology prediction accounting for
monofunctional, multifunctional and multimeric proteins,
isozymes and protein complexes. We describe results from
performing flux balance analysis under different physiological
conditions, (i.e., photosynthesis, photorespiration and
respiration) of a C4 plant and also explore model predictions
against experimental observations for two naturally occurring
mutants (i.e., bm1 and bm3). The developed model corresponds to
the largest and more complete to-date effort at cataloguing
metabolism for a plant species.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180011.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
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