OryzaPG-DB: Rice Proteome Database based on Shotgun Proteogenomics

Background  

Proteogenomics aims to utilize experimental proteome information for refinement of genome annotation. Since mass spectrometry-based shotgun proteomics approaches provide large-scale peptide sequencing data with high throughput, a data repository for shotgun proteogenomics would represent a valuable source of gene expression evidence at the translational level for genome re-annotation.     

Elemental formula annotation of polar and lipophilic metabolites using (13) C, (15) N and (34) S isotope labelling, in combination with high-resolution mass spectrometry

The unbiased and comprehensive analysis of metabolites in any organism presents a major challenge if proper peak annotation and unambiguous assignment of the biological origin of the peaks are required. Here we provide a comprehensive multi-isotope labelling-based strategy using fully labelled (13) C, (15) N and (34) S plant tissues, in combination with a fractionated metabolite extraction protocol. The extraction procedure allows for the simultaneous extraction of polar, semi-polar and hydrophobic metabolites, as well as for the extraction of proteins and starch. After labelling and extraction, the metabolites and lipids were analysed using a high-resolution mass spectrometer providing accurate MS and all-ion fragmentation data, providing an unambiguous readout for every detectable isotope-labelled peak. The isotope labelling assisted peak annotation process employed can be applied in either an automated database-dependent or a database-independent analysis of the plant polar metabolome and lipidome. As a proof of concept, the developed methods and technologies were applied and validated using Arabidopsis thaliana leaf and root extracts. Along with a large repository of assigned elemental compositions, which is provided, we show, using selected examples, the accuracy and reliability of the developed workflow.     

Whole genome sequence resource of Indian Zaprionus indianus

This article documents the whole genome sequence information of the Indian Zaprionus indianus, a member of the fruit fly family Drosophilidae. The sequences were generated on an Illumina platform and reads and whole genome sequence submitted to NCBI to the SRA and BioProject databases, respectively. This is the first Indian Z. indianus whole genome (draft) submitted to the sequence repository with SRA reads. The details of methodology, assembly statistics and functional annotation are presented in this work.     

The human proteomics initiative (HPI)

The availability of the human genome sequence has enabled the exploration and exploitation of the human genome and proteome to begin. Research has now focussed on the annotation of the genome and in particular of the proteome. With expert annotation extracted from the literature by biologists as the foundation, it has been possible to expand into the areas of data mining and automatic annotation. With further development and integration of pattern recognition methods and the application of alignments clustering, proteome analysis can now be provided in a meaningful way. These various approaches have been integrated to attach, extract and combine as much relevant information as possible to the proteome. This resource should be valuable to users from both research and industry.     

EMGLib: the enhanced microbial genomes library (update 2000)

As the number of complete microbial genomes publicly available is still growing, the problem of annotation quality in these very large sequences remains unsolved. Indeed, the number of annotations associated with complete genomes is usually lower than those of the shorter entries encountered in the repository collections. Moreover, classical sequence database management systems have difficulties in handling entries of such size. In this context, the Enhanced Microbial Genomes Library (EMGLib) was developed to try to alleviate these problems. This library contains all the complete genomes from prokaryotes (bacteria and archaea) already sequenced and the yeast genome in GenBank format. The annotations are improved by the introduction of data on codon usage, gene orientation on the chromosome and gene families. It is possible to access EMGLib through two database systems set up on WWW servers: the PBIL server at http://pbil.univ-lyon1.fr/emglib.html and the MICADO server at http://locus.jouy.inra.fr/micado     

利用全长转录本优化柞蚕基因组注释(英文)

【目的】优化柞蚕Antheraea pernyi基因组注释,更好地扩展其在比较基因组学及品种改良研究中的应用。【方法】对柞蚕进行全长转录组测序分析;经全长转录本与参考基因组比对,鉴定新基因及新转录本,并对这些新基因和新转录本进行功能注释及长链非编码RNAs (lncRNAs)预测。利用大量的蛋白质编码转录本和lncRNAs对柞蚕基因组中基因结构进行修订。最后创建矫正后的柞蚕基因组基因注释。【结果】新发现1 997个蛋白编码基因和3 399个lncRNA基因,分别由2 402个和3 574个全长转录本数据支持。发现柞蚕基因组含25 021个基因,其中19 825个基因是蛋白编码基因,包括7个保幼激素酸甲基转移酶基因。【结论】本研究促进了对柞蚕基因组基因注释信息的认识,为柞蚕及相关物种功能基因组及比较基因组学研究提供了很有用的数据资源。     

Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry

A crucial aim upon the completion of the human genome is the verification and functional annotation of all predicted genes and their protein products. Here we describe the mapping of peptides derived from accurate interpretations of protein tandem mass spectrometry (MS) data to eukaryotic genomes and the generation of an expandable resource for integration of data from many diverse proteomics experiments. Furthermore, we demonstrate that peptide identifications obtained from high-throughput proteomics can be integrated on a large scale with the human genome. This resource could serve as an expandable repository for MS-derived proteome information.     

面向大规模人群的基因组注释系统

基因组注释是识别出基因组序列中功能组件的过程,其可以直接对序列赋予生物学意义,由此方便研究者探究和分析基因组功能.基因组注释可以帮助研究从三个层次上理解基因组,一种是在核苷酸水平的注释,主要确定DNA序列中基因、RNA、重复序列等组件的物理位置,包括转录起始,翻译起始,外显子边界等具体位置信息.同时可以注释得到变异在不...     

The use of evolutionary biology concepts for genome annotation

The past decade has seen the completion of numerous whole-genome sequencing projects, began with bacterial genomes and continued with eukaryotic species from different phyla: fungi, plants and animals. Besides, more biological information are produced and are shared thanks to information exchange systems, and more biological concepts, as well as more bioinformatics tools, are available. In this article, we will describe how the evolutionary biology concepts, as well as computer science, are useful for a better understanding of biology in general and genome annotation in particular. The genome annotation process consists of taking the raw DNA produced, for example, by the genome sequencing projects, adding the layers of analysis and interpretation necessary to extract its biological significance and placing it in the context of our understanding of biological processes. Genome annotation is a multistep process falling into two broad categories: structural and functional annotation.     

Expressed peptide tags: an additional layer of data for genome annotation

While genome sequencing is becoming ever more routine, genome annotation remains a challenging process. Identification of the coding sequences within the genomic milieu presents a tremendous challenge, especially for eukaryotes with their complex gene architectures. Here, we present a method to assist the annotation process through the use of proteomic data and bioinformatics. Mass spectra of digested protein preparations of the organism of interest were acquired and searched against a protein database created by a six-frame translation of the genome. The identified peptides were mapped back to the genome, compared to the current annotation, and then categorized as supporting or extending the current genome annotation. We named the classified peptides Expressed Peptide Tags (EPTs). The well-annotated bacterium Rhodopseudomonas palustris was used as a control for the method and showed a high degree of correlation between EPT mapping and the current annotation, with 86% of the EPTs confirming existing gene calls and less than 1% of the EPTs expanding on the current annotation. The eukaryotic plant pathogens Phytophthora ramorum and Phytophthora sojae, whose genomes have been recently sequenced and are much less well-annotated, were also subjected to this method. A series of algorithmic steps were taken to increase the confidence of EPT identification for these organisms, including generation of smaller subdatabases to be searched against, and definition of EPT criteria that accommodates the more complex eukaryotic gene architecture. As expected, the analysis of the Phytophthora species showed less correlation between EPT mapping and their current annotation. While approximately 76% of Phytophthora EPTs supported the current annotation, a portion of them (7.7% and 12.9% for P. ramorum and P. sojae, respectively) suggested modification to current gene calls or identified novel genes that were missed by the current genome annotation of these organisms.     

ArrayExpress: a public database of gene expression data at EBI

ArrayExpress is a public repository for microarray-based gene expression data, resulting from the implementation of the MAGE object model to ensure accurate data structuring and the MIAME standard, which defines the annotation requirements. ArrayExpress accepts data as MAGE-ML files for direct submissions or data from MIAMExpress, the MIAME compliant web-based annotation and submission tool of EBI. A team of curators supports the submission process, providing assistance in data annotation. Data retrieval is performed through a dedicated web interface. Relevant results may be exported to ExpressionProfiler, the EBI based expression analysis tool available online (http://www.ebi.ac.uk/arrayexpress).     

MaGe: a microbial genome annotation system supported by synteny results

Magnifying Genomes (MaGe) is a microbial genome annotation system based on a relational database containing information on bacterial genomes, as well as a web interface to achieve genome annotation projects. Our system allows one to initiate the annotation of a genome at the early stage of the finishing phase. MaGe's main features are (i) integration of annotation data from bacterial genomes enhanced by a gene coding re-annotation process using accurate gene models, (ii) integration of results obtained with a wide range of bioinformatics methods, among which exploration of gene context by searching for conserved synteny and reconstruction of metabolic pathways, (iii) an advanced web interface allowing multiple users to refine the automatic assignment of gene product functions. MaGe is also linked to numerous well-known biological databases and systems. Our system has been thoroughly tested during the annotation of complete bacterial genomes (Acinetobacter baylyi ADP1, Pseudoalteromonas haloplanktis, Frankia alni) and is currently used in the context of several new microbial genome annotation projects. In addition, MaGe allows for annotation curation and exploration of already published genomes from various genera (e.g. Yersinia, Bacillus and Neisseria). MaGe can be accessed at http://www.genoscope.cns.fr/agc/mage.     

USDA Stakeholder Workshop on Animal Bioinformatics: Summary and Recommendations

An electronic workshop was conducted on 4 November-13 December 2002 to discuss current issues and needs in animal bioinformatics. The electronic (e-mail listserver) format was chosen to provide a relatively speedy process that is broad in scope, cost-efficient and easily accessible to all participants. Approximately 40 panelists with diverse species and discipline expertise communicated through the panel e-mail listserver. The panel included scientists from academia, industry and government, in the USA, Australia and the UK. A second 'stakeholder' e-mail listserver was used to obtain input from a broad audience with general interests in animal genomics. The objectives of the electronic workshop were: (a) to define priorities for animal genome database development; and (b) to recommend ways in which the USDA could provide leadership in the area of animal genome database development. E-mail messages from panelists and stakeholders are archived at http://genome.cvm.umn.edu/bioinfo/. Priorities defined for animal genome database development included: (a) data repository; (b) tools for genome analysis; (c) annotation; (d) practical application of genomic data; and (e) a biological framework for DNA sequence. A stable source of funding, such as the USDA Agricultural Research Service (ARS), was recommended to support maintenance of data repositories and data curation. Continued support for competitive grants programs within the USDA Cooperative State Research, Education and Extension Service (CSREES) was recommended for tool development and hypothesis-driven research projects in genome analysis. Additional stakeholder input will be required to continuously refine priorities and maximize the use of limited resources for animal bioinformatics within the USDA.     

A beginner's guide to eukaryotic genome annotation

The falling cost of genome sequencing is having a marked impact on the research community with respect to which genomes are sequenced and how and where they are annotated. Genome annotation projects have generally become small-scale affairs that are often carried out by an individual laboratory. Although annotating a eukaryotic genome assembly is now within the reach of non-experts, it remains a challenging task. Here we provide an overview of the genome annotation process and the available tools and describe some best-practice approaches.     

GPAC: benchmarking the sensitivity of genome informatics analysis to genome annotation completeness

In view of the recent explosion in genome sequence data, and the 200 or more complete genome sequences currently available, the importance of genome-scale bioinformatics analysis is increasing rapidly. However, computational genome informatics analyses often lack a statistical assessment of their sensitivity to the completeness of the functional annotation. Therefore, a pre-analysis method to automatically validate the sensitivity of computational genome analyses with regard to genome annotation completeness is useful for this purpose. In this report we developed the Gene Prediction Accuracy Classification (GPAC) test, which provides statistical evidence of sensitivity by repeating the same analysis for five different gene groups (classified according to annotation accuracy level), and for randomly sampled gene groups, with the same number of genes as each of the five classified groups. Variability in these results is then assessed, and if the results vary significantly with different data subsets, the analysis is considered "sensitive" to annotation completeness, and careful selection of data is advised prior to the actual in silico analysis. The GPAC test has been applied to the analyses of Sakai et al., 2001, and Ohno et al., 2001, and it revealed that the analysis of Ohno et al. was more sensitive to annotation completeness. It showed that GPAC could be employed to ascertain the sensitivity of an analysis. The GPAC bendhmarking software is freely available in the latest G-language Genome Analysis Environment package, at http://www.g-language.org/.     

Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary

MOTIVATION: High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has certain limitations such as the lack of direct association with pathways. RESULTS: We demonstrated the use of the KEGG Orthology (KO), part of the KEGG suite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available stand-alone Python program that can contribute significantly to genome annotation and microarray analysis.     

Assembly and RNA‐free annotation of highly heterozygous genomes: The case of the thick‐billed murre (Uria lomvia)

Thanks to a dramatic reduction in sequencing costs followed by a rapid development of bioinformatics tools, genome assembly and annotation have become accessible to many researchers in recent years. Among tetrapods, birds have genomes that display many features that facilitate their assembly and annotation, such as small genome size, low number of repeats and highly conserved genomic structure. However, we found that high genomic heterozygosity could have a great impact on the quality of the genome assembly of the thick‐billed murre (Uria lomvia), an arctic colonial seabird. In this study, we tested the performance of three genome assemblers, ray /sscape , soapdenovo 2 and platanus , in assembling the highly heterozygous genome of the thick‐billed murre. Our results show that platanus , an assembler specifically designed for heterozygous genomes, outperforms the other two approaches and produces a highly contiguous (N50 = 15.8 Mb) and complete genome assembly (93% presence of genes from the Benchmarking Universal Single Copy Ortholog [BUSCO] gene set). Additionally, we annotated the thick‐billed murre genome using a homology‐based approach that takes advantage of the genomic resources available for birds and other taxa. Our study will be useful for those researchers who are approaching assembly and annotation of highly heterozygous genomes, or genomes of species of conservation concern, and/or who have limited financial resources.