BEACON: automated tool for Bacterial GEnome Annotation ComparisON
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer Science Program
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2015-08-18
Print Publication Date2015-12
Permanent link to this recordhttp://hdl.handle.net/10754/575255
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AbstractBackground Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). Results The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON’s utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27 %, while the number of genes without any function assignment is reduced. Conclusions We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/
CitationBEACON: automated tool for Bacterial GEnome Annotation ComparisON 2015, 16 (1) BMC Genomics
RelationsIs Supplemented By:
- ParsEval: parallel comparison and analysis of gene structure annotations.
- Authors: Standage DS, Brendel VP
- Issue date: 2012 Aug 1
- GASS: genome structural annotation for Eukaryotes based on species similarity.
- Authors: Wang Y, Chen L, Song N, Lei X
- Issue date: 2015 Mar 4
- PANNOTATOR: an automated tool for annotation of pan-genomes.
- Authors: Santos AR, Barbosa E, Fiaux K, Zurita-Turk M, Chaitankar V, Kamapantula B, Abdelzaher A, Ghosh P, Tiwari S, Barve N, Jain N, Barh D, Silva A, Miyoshi A, Azevedo V
- Issue date: 2013 Aug 16
- High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.
- Authors: Seaver SM, Gerdes S, Frelin O, Lerma-Ortiz C, Bradbury LM, Zallot R, Hasnain G, Niehaus TD, El Yacoubi B, Pasternak S, Olson R, Pusch G, Overbeek R, Stevens R, de Crécy-Lagard V, Ware D, Hanson AD, Henry CS
- Issue date: 2014 Jul 1
- Genome Annotation Transfer Utility (GATU): rapid annotation of viral genomes using a closely related reference genome.
- Authors: Tcherepanov V, Ehlers A, Upton C
- Issue date: 2006 Jun 13
Showing items related by title, author, creator and subject.
The NLR-Annotator tool enables annotation of the intracellular immune receptor repertoireSteuernagel, Burkhard; Witek, Kamil; Krattinger, Simon G.; Ramirez-Gonzalez, Ricardo H.; Schoonbeek, Henk-jan; Yu, Guotai; Baggs, Erin; Witek, Agnieszka; Yadav, Inderjit; Krasileva, Ksenia V; Jones, Jonathan D; Uauy, Cristobal; Keller, Beat; Ridout, Christopher James; Wulff, Brande B (Plant Physiology, American Society of Plant Biologists (ASPB), 2020-03-17) [Article]Disease resistance genes encoding nucleotide-binding and leucine-rich repeat (NLR) intracellular immune receptor proteins detect pathogens by the presence of pathogen effectors. Plant genomes typically contain hundreds of NLR-encoding genes. The availability of the hexaploid wheat (Triticum aestivum) cultivar Chinese Spring reference genome allows a detailed study of its NLR complement. However, low NLR expression and high intra-family sequence homology hinders their accurate annotation. Here we developed NLR-Annotator, a software tool for in silico NLR identification independent of transcript support. Although developed for wheat, we demonstrate the universal applicability of NLR-Annotator across diverse plant taxa. We applied our tool to wheat and combined it with a transcript-validated subset of genes from the reference gene annotation to characterize the structure, phylogeny and expression profile of the NLR gene family. We detected 3,400 full-length NLR loci of which 1,560 were confirmed as expressed genes with intact open reading frames. NLRs with integrated domains mostly group in specific subclades. Members of another subclade predominantly locate in close physical proximity to NLRs carrying integrated domains, suggesting a paired helper-function. Most NLRs (88%) display low basal expression (in the lower 10 percentile of transcripts). In young leaves subjected to biotic stress we found upregulation of 266 of the NLRs. To illustrate the utility of our tool for the positional cloning of resistance genes, we estimated the number of NLR genes within the intervals of mapped rust resistance genes. Our study will support the identification of functional resistance genes in wheat to accelerate the breeding and engineering of disease-resistant varieties.
Diversity Indices as Measures of Functional Annotation Methods in Metagenomics StudiesJankovic, Boris R. (2016-01-26) [Presentation]Applications of high-throughput techniques in metagenomics studies produce massive amounts of data. Fragments of genomic, transcriptomic and proteomic molecules are all found in metagenomics samples. Laborious and meticulous effort in sequencing and functional annotation are then required to, amongst other objectives, reconstruct a taxonomic map of the environment that metagenomics samples were taken from. In addition to computational challenges faced by metagenomics studies, the analysis is further complicated by the presence of contaminants in the samples, potentially resulting in skewed taxonomic analysis. The functional annotation in metagenomics can utilize all available omics data and therefore different methods that are associated with a particular type of data. For example, protein-coding DNA, non-coding RNA or ribosomal RNA data can be used in such an analysis. These methods would have their advantages and disadvantages and the question of comparison among them naturally arises. There are several criteria that can be used when performing such a comparison. Loosely speaking, methods can be evaluated in terms of computational complexity or in terms of the expected biological accuracy. We propose that the concept of diversity that is used in the ecosystems and species diversity studies can be successfully used in evaluating certain aspects of the methods employed in metagenomics studies. We show that when applying the concept of Hill’s diversity, the analysis of variations in the diversity order provides valuable clues into the robustness of methods used in the taxonomical analysis.
Single Amplified Genomes as Source for Novel Extremozymes: Annotation, Expression and Functional AssessmentGrötzinger, Stefan (2017-12) [Dissertation]
Advisor: Arold, Stefan T.
Committee members: Ladbury, John E.; Rueping, Magnus; Tester, Mark A.Enzymes, as nature’s catalysts, show remarkable abilities that can revolutionize the chemical, biotechnological, bioremediation, agricultural and pharmaceutical industries. However, the narrow range of stability of the majority of described biocatalysts limits their use for many applications. To overcome these restrictions, extremozymes derived from microorganisms thriving under harsh conditions can be used. Extremophiles living in high salinity are especially interesting as they operate at low water activity, which is similar to conditions used in standard chemical applications. Because only about 0.1 % of all microorganisms can be cultured, the traditional way of culture-based enzyme function determination needs to be overcome. The rise of high-throughput next-generation-sequencing technologies allows for deep insight into nature’s variety. Single amplified genomes (SAGs) specifically allow for whole genome assemblies from small sample volumes with low cell yields, as are typical for extreme environments. Although these technologies have been available for years, the expected boost in biotechnology has held off. One of the main reasons is the lack of reliable functional annotation of the genomic data, which is caused by the low amount (0.15 %) of experimentally described genes. Here, we present a novel annotation algorithm, designed to annotate the enzymatic function of genomes from microorganisms with low homologies to described microorganisms. The algorithm was established on SAGs from the extreme environment of selected hypersaline Red Sea brine pools with 4.3 M salinity and temperatures up to 68°C. Additionally, a novel consensus pattern for the identification of γ-carbonic anhydrases was created and applied in the algorithm. To verify the annotation, selected genes were expressed in the hypersaline expression system Halobacterium salinarum. This expression system was established and optimized in a continuously stirred tank reactor, leading to substantially increased cell amounts and protein yields. The resulting gene expression products were assessed for function in vivo and/or in vitro. Our functional evaluation of the tested genes confirmed our annotation algorithm. Our developed strategy offers a general guide for using SAGs as a source of scientific and industrial investigations into “microbial dark matter” and may help to develop new catalysts, applicable for novel reactions in green chemistry.