Project description:We applied the RNA-Seq approach to reconstruct the transcriptome of Vitis vinifera cv. Corvina, using RNA pooled from a comprehensive set of sampled tissues in different organs and development steps, and we were able to reconstruct some novel and putative private Corvina genes. We analyzed the expression of these genes in three berry developmental conditions, and posit that they may play some role in the formation of the mature organ. Background: Plants display a high genetic and phenotypic variability among different cultivars. Understanding the genetic components that contribute to phenotypic diversity is necessary to disentangle genetic factors from the environment. Given the high degree of genetic diversity among plant cultivars a whole-genome sequencing and re-annotation of each variety is required but a reliable genome assembly is hindered by the high heterozigosity and sequence divergence. Results: we show the feasibility of an approach based on sequencing of cDNA by RNA-Seq to analyze varietal diversity between a local grape cultivar Corvina and the PN40024 grape reference genome. We detected 15,260 known genes and we annotated alternative splicing isoforms for 9,463 genes. Our approach allowed to define 2,321 protein coding putative novel genes in unannotated or unassembled regions of the reference genome PN40024 and 180 putative private Corvina genes whose sequence is not shared with the reference genome. Conclusions: With a de novo assembly based approach we were able to reconstruct a substantial part of the Corvina transcriptome and we improved substantially known genes annotations by better defining the structure of known genes, annotating splicing isoforms and detecting unannotated genes. Moreover our results clearly define sets of private genes which are likely part of the âdispensableâ genome and potentially involved into influencing some cultivar-specific characteristics. In plant biology a transcriptome de novo assembly approach should not be limited to species where no reference genome is available as it can improve the annotation lead to the identification of genes peculiar of a cultivar.

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.

Project description:Proteogenomics, the combination of proteomics, genomics and transcriptomics, has considerably improved genome annotation in under-studied phylogenetic groups, where homology information is missing. Yet, it can also be advantageous when re-investigating well-annotated genomes. Here, we apply an advanced proteogenomics approach, combining standard proteogenomics with peptide de novo sequencing, to refine annotation of the well-studied model fungus Sordaria macrospora. We investigated samples from different developmental and physiological conditions, resulting in detection of 104 hidden proteins and annotation changes in 575 genes, including 389 splice site refinements. Significantly, our approach provides peptide-level evidence for 113 single amino acid variations and 15 C-terminal protein elongations originating from A-to-I RNA editing, a phenomenon recently detected in fungi. Co-expression and phylostratigraphic analysis of the refined proteome suggests new functions in evolutionary young genes correlated with distinct developmental stages. In conclusion, our advanced proteogenomics approach is highly supportive to promote functional studies of model systems. Proteogenomics, the combination of proteomics, genomics and transcriptomics, has considerably improved genome annotation in under-studied phylogenetic groups, where homology information is missing. Yet, it can also be advantageous when re-investigating well-annotated genomes. Here, we apply an advanced proteogenomics approach, combining standard proteogenomics with peptide de novo sequencing, to refine annotation of the well-studied model fungus Sordaria macrospora. We investigated samples from different developmental and physiological conditions, resulting in detection of 104 hidden proteins and annotation changes in 575 genes, including 389 splice site refinements. Significantly, our approach provides peptide-level evidence for 113 single amino acid variations and 15 C-terminal protein elongations originating from A-to-I RNA editing, a phenomenon recently detected in fungi. Co-expression and phylostratigraphic analysis of the refined proteome suggests new functions in evolutionary young genes correlated with distinct developmental stages. In conclusion, our advanced proteogenomics approach is highly supportive to promote functional studies of model systems.

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Onygena_corvinaGenome2025

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