학술논문
Re-annotation of the Saccharopolyspora erythraea genome using a systems biology approach
Document Type
Report
Author
Source
BMC Genomics. October 11, 2013, Vol. 14 Issue 1
Subject
Language
English
ISSN
1471-2164
Abstract
Author(s): Esteban Marcellin[sup.1] , Cuauhtemoc Licona-Cassani[sup.1] , Tim R Mercer[sup.1] , Robin W Palfreyman[sup.1] and Lars K Nielsen[sup.1] Background Genome annotations are essential to study and manipulate microorganisms. With advances [...]
Background Accurate bacterial genome annotations provide a framework to understanding cellular functions, behavior and pathogenicity and are essential for metabolic engineering. Annotations based only on in silico predictions are inaccurate, particularly for large, high G + C content genomes due to the lack of similarities in gene length and gene organization to model organisms. Results Here we describe a 2D systems biology driven re-annotation of the Saccharopolyspora erythraea genome using proteogenomics, a genome-scale metabolic reconstruction, RNA-sequencing and small-RNA-sequencing. We observed transcription of more than 300 intergenic regions, detected 59 peptides in intergenic regions, confirmed 164 open reading frames previously annotated as hypothetical proteins and reassigned function to open reading frames using the genome-scale metabolic reconstruction. Finally, we present a novel way of mapping ribosomal binding sites across the genome by sequencing small RNAs. Conclusions The work presented here describes a novel framework for annotation of the Saccharopolyspora erythraea genome. Based on experimental observations, the 2D annotation framework greatly reduces errors that are commonly made when annotating large-high G + C content genomes using computational prediction algorithms. Keywords: Proteogenomics, Saccharopolyspora erythraea, Systems biology, Genome annotation, High G + C content genomes
Background Accurate bacterial genome annotations provide a framework to understanding cellular functions, behavior and pathogenicity and are essential for metabolic engineering. Annotations based only on in silico predictions are inaccurate, particularly for large, high G + C content genomes due to the lack of similarities in gene length and gene organization to model organisms. Results Here we describe a 2D systems biology driven re-annotation of the Saccharopolyspora erythraea genome using proteogenomics, a genome-scale metabolic reconstruction, RNA-sequencing and small-RNA-sequencing. We observed transcription of more than 300 intergenic regions, detected 59 peptides in intergenic regions, confirmed 164 open reading frames previously annotated as hypothetical proteins and reassigned function to open reading frames using the genome-scale metabolic reconstruction. Finally, we present a novel way of mapping ribosomal binding sites across the genome by sequencing small RNAs. Conclusions The work presented here describes a novel framework for annotation of the Saccharopolyspora erythraea genome. Based on experimental observations, the 2D annotation framework greatly reduces errors that are commonly made when annotating large-high G + C content genomes using computational prediction algorithms. Keywords: Proteogenomics, Saccharopolyspora erythraea, Systems biology, Genome annotation, High G + C content genomes