Chlorops oryzae
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA712980 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| JAIPUU01.dat.gz | Other | |||
| JAIPUU01.fasta.gz | Fasta.gz | |||
| JAIPUU01.master.dat | Other | |||
| SRR14340331_subreads.fastq.gz | Fastqsanger.gz |
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Project description:Chlorops oryzae is a pest of rice that has caused severe damage to crops in major rice-growing areas in recent years. We generated a 447.60 Mb high-quality chromosome-level genome with contig and scaffold N50 values of 1.17 Mb and 117.57 Mb, respectively. Hi-C analysis anchored 93.22% scaffolds to 4 chromosomes. The relatively high expression level of Heat Shock Proteins (HSPs) and antioxidant genes in response to thermal stress suggests these genes may play a role in the environmental adaptability of C. oryzae. The identification of multiple pathways that regulate reproductive development (juvenile hormone, 20-hydroxyecdsone, and insulin signaling pathways) provides evidence that these pathways also play an important role in vitellogenesis and thus insect population maintenance. These findings identify possible reasons for the increased frequency of outbreaks of C. oryzae in recent years. Our chromosome-level genome assembly may provide a basis for further genetic studies of C. oryzae, and promote the development of novel, sustainable strategies to control this pest.
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Project description:Vongsangnak2008 - Genome-scale metabolic
network of Aspergillus oryzae (iWV1314)
This model is described in the article:
Improved annotation through
genome-scale metabolic modeling of Aspergillus oryzae.
Vongsangnak W, Olsen P, Hansen K,
Krogsgaard S, Nielsen J.
BMC Genomics 2008; 9: 245
Abstract:
BACKGROUND: Since ancient times the filamentous fungus
Aspergillus oryzae has been used in the fermentation industry
for the production of fermented sauces and the production of
industrial enzymes. Recently, the genome sequence of A. oryzae
with 12,074 annotated genes was released but the number of
hypothetical proteins accounted for more than 50% of the
annotated genes. Considering the industrial importance of this
fungus, it is therefore valuable to improve the annotation and
further integrate genomic information with biochemical and
physiological information available for this microorganism and
other related fungi. Here we proposed the gene prediction by
construction of an A. oryzae Expressed Sequence Tag (EST)
library, sequencing and assembly. We enhanced the function
assignment by our developed annotation strategy. The resulting
better annotation was used to reconstruct the metabolic network
leading to a genome scale metabolic model of A. oryzae.
RESULTS: Our assembled EST sequences we identified 1,046 newly
predicted genes in the A. oryzae genome. Furthermore, it was
possible to assign putative protein functions to 398 of the
newly predicted genes. Noteworthy, our annotation strategy
resulted in assignment of new putative functions to 1,469
hypothetical proteins already present in the A. oryzae genome
database. Using the substantially improved annotated genome we
reconstructed the metabolic network of A. oryzae. This network
contains 729 enzymes, 1,314 enzyme-encoding genes, 1,073
metabolites and 1,846 (1,053 unique) biochemical reactions. The
metabolic reactions are compartmentalized into the cytosol, the
mitochondria, the peroxisome and the extracellular space.
Transport steps between the compartments and the extracellular
space represent 281 reactions, of which 161 are unique. The
metabolic model was validated and shown to correctly describe
the phenotypic behavior of A. oryzae grown on different carbon
sources. CONCLUSION: A much enhanced annotation of the A.
oryzae genome was performed and a genome-scale metabolic model
of A. oryzae was reconstructed. The model accurately predicted
the growth and biomass yield on different carbon sources. The
model serves as an important resource for gaining further
insight into our understanding of A. oryzae physiology.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180056.
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.
2015-07-30 | MODEL1507180056 | BioModels
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