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Rakov AV, Shubin FN. Comparative Genomic Analysis of the Virulence Plasmid from Salmonella enterica Subspecies enterica Serovar Enteritidis. RUSS J GENET+ 2019. [DOI: 10.1134/s102279541902011x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Kim S, Jeong H, Kim EY, Kim JF, Lee SY, Yoon SH. Genomic and transcriptomic landscape of Escherichia coli BL21(DE3). Nucleic Acids Res 2017; 45:5285-5293. [PMID: 28379538 PMCID: PMC5435950 DOI: 10.1093/nar/gkx228] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 03/26/2017] [Indexed: 11/23/2022] Open
Abstract
Escherichia coli BL21(DE3) has long served as a model organism for scientific research, as well as a workhorse for biotechnology. Here we present the most current genome annotation of E. coli BL21(DE3) based on the transcriptome structure of the strain that was determined for the first time. The genome was annotated using multiple automated pipelines and compared to the current genome annotation of the closely related strain, E. coli K-12. High-resolution tiling array data of E. coli BL21(DE3) from several different stages of cell growth in rich and minimal media were analyzed to characterize the transcriptome structure and to provide supporting evidence for open reading frames. This new integrated analysis of the genomic and transcriptomic structure of E. coli BL21(DE3) has led to the correction of translation initiation sites for 88 coding DNA sequences and provided updated information for most genes. Additionally, 37 putative genes and 66 putative non-coding RNAs were also identified. The panoramic landscape of the genome and transcriptome of E. coli BL21(DE3) revealed here will allow us to better understand the fundamental biology of the strain and also advance biotechnological applications in industry.
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Affiliation(s)
- Sinyeon Kim
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Republic of Korea
| | - Haeyoung Jeong
- Infectious Disease Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Eun-Youn Kim
- School of Basic Sciences, Hanbat National University, Daejeon 34158, Republic of Korea
| | - Jihyun F Kim
- Department of Systems Biology and Division of Life Sciences, Yonsei University, Seoul 03722, Republic of Korea
| | - Sang Yup Lee
- Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Plus Program), BioProcess Engineering Research Center, Center for Systems and Synthetic Biotechnology, and Institute for the BioCentury, KAIST, Daejeon 34141, Republic of Korea
| | - Sung Ho Yoon
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Republic of Korea
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3
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Eckshtain-Levi N, Shkedy D, Gershovits M, Da Silva GM, Tamir-Ariel D, Walcott R, Pupko T, Burdman S. Insights from the Genome Sequence of Acidovorax citrulli M6, a Group I Strain of the Causal Agent of Bacterial Fruit Blotch of Cucurbits. Front Microbiol 2016; 7:430. [PMID: 27092114 PMCID: PMC4821854 DOI: 10.3389/fmicb.2016.00430] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Accepted: 03/17/2016] [Indexed: 11/13/2022] Open
Abstract
Acidovorax citrulli is a seedborne bacterium that causes bacterial fruit blotch of cucurbit plants including watermelon and melon. A. citrulli strains can be divided into two major groups based on DNA fingerprint analyses and biochemical properties. Group I strains have been generally isolated from non-watermelon cucurbits, while group II strains are closely associated with watermelon. In the present study, we report the genome sequence of M6, a group I model A. citrulli strain, isolated from melon. We used comparative genome analysis to investigate differences between the genome of strain M6 and the genome of the group II model strain AAC00-1. The draft genome sequence of A. citrulli M6 harbors 139 contigs, with an overall approximate size of 4.85 Mb. The genome of M6 is ∼500 Kb shorter than that of strain AAC00-1. Comparative analysis revealed that this size difference is mainly explained by eight fragments, ranging from ∼35-120 Kb and distributed throughout the AAC00-1 genome, which are absent in the M6 genome. In agreement with this finding, while AAC00-1 was found to possess 532 open reading frames (ORFs) that are absent in strain M6, only 123 ORFs in M6 were absent in AAC00-1. Most of these M6 ORFs are hypothetical proteins and most of them were also detected in two group I strains that were recently sequenced, tw6 and pslb65. Further analyses by PCR assays and coverage analyses with other A. citrulli strains support the notion that some of these fragments or significant portions of them are discriminative between groups I and II strains of A. citrulli. Moreover, GC content, effective number of codon values and cluster of orthologs' analyses indicate that these fragments were introduced into group II strains by horizontal gene transfer events. Our study reports the genome sequence of a model group I strain of A. citrulli, one of the most important pathogens of cucurbits. It also provides the first comprehensive comparison at the genomic level between the two major groups of strains of this pathogen.
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Affiliation(s)
- Noam Eckshtain-Levi
- Department of Plant Pathology and Microbiology and the Otto Warburg Center for Agricultural Biotechnology, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of JerusalemRehovot, Israel
| | - Dafna Shkedy
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv UniversityTel Aviv, Israel
| | - Michael Gershovits
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv UniversityTel Aviv, Israel
| | | | - Dafna Tamir-Ariel
- Department of Plant Pathology and Microbiology and the Otto Warburg Center for Agricultural Biotechnology, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of JerusalemRehovot, Israel
| | - Ron Walcott
- Department of Plant Pathology, The University of Georgia, AthensGA, USA
| | - Tal Pupko
- Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv UniversityTel Aviv, Israel
| | - Saul Burdman
- Department of Plant Pathology and Microbiology and the Otto Warburg Center for Agricultural Biotechnology, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of JerusalemRehovot, Israel
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Benjak A, Uplekar S, Zhang M, Piton J, Cole ST, Sala C. Genomic and transcriptomic analysis of the streptomycin-dependent Mycobacterium tuberculosis strain 18b. BMC Genomics 2016; 17:190. [PMID: 26944551 PMCID: PMC4779234 DOI: 10.1186/s12864-016-2528-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Accepted: 02/24/2016] [Indexed: 12/05/2022] Open
Abstract
Background The ability of Mycobacterium tuberculosis to establish a latent infection (LTBI) in humans confounds the treatment of tuberculosis. Consequently, there is a need to discover new therapeutic agents that can kill M. tuberculosis both during active disease and LTBI. The streptomycin-dependent strain of M. tuberculosis, 18b, provides a useful tool for this purpose since upon removal of streptomycin (STR) it enters a non-replicating state that mimics latency both in vitro and in animal models. Results The 4.41 Mb genome sequence of M. tuberculosis 18b was determined and this revealed the strain to belong to clade 3 of the ancient ancestral lineage of the Beijing family. STR-dependence was attributable to insertion of a single cytosine in the 530 loop of the 16S rRNA and to a single amino acid insertion in the N-terminal domain of initiation factor 3. RNA-seq was used to understand the genetic programme activated upon STR-withdrawal and hence to gain insight into LTBI. This revealed reconfiguration of gene expression and metabolic pathways showing strong similarities between non-replicating 18b and M. tuberculosis residing within macrophages, and with the core stationary phase and microaerophilic responses. Conclusion The findings of this investigation confirm the validity of 18b as a model for LTBI, and provide insight into both the evolution of tubercle bacilli and the functioning of the ribosome. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2528-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrej Benjak
- Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland.
| | - Swapna Uplekar
- Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland. .,Current addresses: Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.
| | - Ming Zhang
- Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland. .,Current addresses: Department of Biochemistry, University of Lausanne, Quartier UNIL-Epalinges, Ch. des Boveresses 155, CH-1066, Epalinges, Switzerland.
| | - Jérémie Piton
- Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland.
| | - Stewart T Cole
- Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland.
| | - Claudia Sala
- Global Health Institute, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland.
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Yagoub D, Tay AP, Chen Z, Hamey JJ, Cai C, Chia SZ, Hart-Smith G, Wilkins MR. Proteogenomic Discovery of a Small, Novel Protein in Yeast Reveals a Strategy for the Detection of Unannotated Short Open Reading Frames. J Proteome Res 2015; 14:5038-47. [DOI: 10.1021/acs.jproteome.5b00734] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Daniel Yagoub
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Aidan P. Tay
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Zhiliang Chen
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Joshua J. Hamey
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Curtis Cai
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Samantha Z. Chia
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Gene Hart-Smith
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Marc R. Wilkins
- Systems Biology Initiative,
School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia
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Abstract
The identification of translation initiation sites (TISs) constitutes an important aspect of sequence-based genome analysis. An erroneous TIS annotation can impair the identification of regulatory elements and N-terminal signal peptides, and also may flaw the determination of descent, for any particular gene. We have formulated a reference-free method to score the TIS annotation quality. The method is based on a comparison of the observed and expected distribution of all TISs in a particular genome given prior gene-calling. We have assessed the TIS annotations for all available NCBI RefSeq microbial genomes and found that approximately 87% is of appropriate quality, whereas 13% needs substantial improvement. We have analyzed a number of factors that could affect TIS annotation quality such as GC-content, taxonomy, the fraction of genes with a Shine-Dalgarno sequence and the year of publication. The analysis showed that only the first factor has a clear effect. We have then formulated a straightforward Principle Component Analysis-based TIS identification strategy to self-organize and score potential TISs. The strategy is independent of reference data and a priori calculations. A representative set of 277 genomes was subjected to the analysis and we found a clear increase in TIS annotation quality for the genomes with a low quality score. The PCA-based annotation was also compared with annotation with the current tool of reference, Prodigal. The comparison for the model genome of Escherichia coli K12 showed that both methods supplement each other and that prediction agreement can be used as an indicator of a correct TIS annotation. Importantly, the data suggest that the addition of a PCA-based strategy to a Prodigal prediction can be used to ‘flag’ TIS annotations for re-evaluation and in addition can be used to evaluate a given annotation in case a Prodigal annotation is lacking.
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Tay AP, Pang CNI, Twine NA, Hart-Smith G, Harkness L, Kassem M, Wilkins MR. Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data. J Proteome Res 2015; 14:3541-54. [PMID: 25961807 DOI: 10.1021/pr5011394] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analyzed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ∼450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of nonisoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We covisualize mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449).
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Affiliation(s)
- Aidan P Tay
- Systems Biology Initiative, The University of New South Wales , Sydney, New South Wales 2052, Australia.,School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Chi Nam Ignatius Pang
- Systems Biology Initiative, The University of New South Wales , Sydney, New South Wales 2052, Australia.,School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Natalie A Twine
- Systems Biology Initiative, The University of New South Wales , Sydney, New South Wales 2052, Australia.,School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Gene Hart-Smith
- Systems Biology Initiative, The University of New South Wales , Sydney, New South Wales 2052, Australia.,School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
| | - Linda Harkness
- Endocrine Research Laboratory (KMEB), Department of Endocrinology and Metabolism, Odense University Hospital & University of Southern Denmark , Odense 5230, Denmark
| | - Moustapha Kassem
- Endocrine Research Laboratory (KMEB), Department of Endocrinology and Metabolism, Odense University Hospital & University of Southern Denmark , Odense 5230, Denmark
| | - Marc R Wilkins
- Systems Biology Initiative, The University of New South Wales , Sydney, New South Wales 2052, Australia.,School of Biotechnology and Biomolecular Sciences, The University of New South Wales , Sydney, New South Wales 2052, Australia
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Zickmann F, Renard BY. IPred - integrating ab initio and evidence based gene predictions to improve prediction accuracy. BMC Genomics 2015; 16:134. [PMID: 25766582 PMCID: PMC4345001 DOI: 10.1186/s12864-015-1315-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Accepted: 02/03/2015] [Indexed: 11/21/2022] Open
Abstract
Background Gene prediction is a challenging but crucial part in most genome analysis pipelines. Various methods have evolved that predict genes ab initio on reference sequences or evidence based with the help of additional information, such as RNA-Seq reads or EST libraries. However, none of these strategies is bias-free and one method alone does not necessarily provide a complete set of accurate predictions. Results We present IPred (Integrative gene Prediction), a method to integrate ab initio and evidence based gene identifications to complement the advantages of different prediction strategies. IPred builds on the output of gene finders and generates a new combined set of gene identifications, representing the integrated evidence of the single method predictions. Conclusion We evaluate IPred in simulations and real data experiments on Escherichia Coli and human data. We show that IPred improves the prediction accuracy in comparison to single method predictions and to existing methods for prediction combination. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1315-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Franziska Zickmann
- Research Group Bioinformatics (NG4), Robert Koch-Institute, Berlin, Germany.
| | - Bernhard Y Renard
- Research Group Bioinformatics (NG4), Robert Koch-Institute, Berlin, Germany.
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Wozniak M, Wong L, Tiuryn J. eCAMBer: efficient support for large-scale comparative analysis of multiple bacterial strains. BMC Bioinformatics 2014; 15:65. [PMID: 24597904 PMCID: PMC4023553 DOI: 10.1186/1471-2105-15-65] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2013] [Accepted: 02/24/2014] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Inconsistencies are often observed in the genome annotations of bacterial strains. Moreover, these inconsistencies are often not reflected by sequence discrepancies, but are caused by wrongly annotated gene starts as well as mis-identified gene presence. Thus, tools are needed for improving annotation consistency and accuracy among sets of bacterial strain genomes. RESULTS We have developed eCAMBer, a tool for efficiently supporting comparative analysis of multiple bacterial strains within the same species. eCAMBer is a highly optimized revision of our earlier tool, CAMBer, scaling it up for significantly larger datasets comprising hundreds of bacterial strains. eCAMBer works in two phases. First, it transfers gene annotations among all considered bacterial strains. In this phase, it also identifies homologous gene families and annotation inconsistencies. Second, eCAMBer, tries to improve the quality of annotations by resolving the gene start inconsistencies and filtering out gene families arising from annotation errors propagated in the previous phase. CONCLUSIONS [corrected] eCAMBer efficiently identifies and resolves annotation inconsistencies among closely related bacterial genomes. It outperforms other competing tools both in terms of running time and accuracy of produced annotations. Software, user manual, and case study results are available at the project website: http://bioputer.mimuw.edu.pl/ecamber.
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Affiliation(s)
- Michal Wozniak
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.
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Pang CNI, Tay AP, Aya C, Twine NA, Harkness L, Hart-Smith G, Chia SZ, Chen Z, Deshpande NP, Kaakoush NO, Mitchell HM, Kassem M, Wilkins MR. Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing. J Proteome Res 2013; 13:84-98. [PMID: 24152167 DOI: 10.1021/pr400820p] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.
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Affiliation(s)
- Chi Nam Ignatius Pang
- Systems Biology Initiative, The University of New South Wales , Sydney, New South Wales 2052, Australia
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Zickmann F, Lindner MS, Renard BY. GIIRA--RNA-Seq driven gene finding incorporating ambiguous reads. ACTA ACUST UNITED AC 2013; 30:606-13. [PMID: 24123675 DOI: 10.1093/bioinformatics/btt577] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
MOTIVATION The reliable identification of genes is a major challenge in genome research, as further analysis depends on the correctness of this initial step. With high-throughput RNA-Seq data reflecting currently expressed genes, a particularly meaningful source of information has become commonly available for gene finding. However, practical application in automated gene identification is still not the standard case. A particular challenge in including RNA-Seq data is the difficult handling of ambiguously mapped reads. RESULTS We present GIIRA (Gene Identification Incorporating RNA-Seq data and Ambiguous reads), a novel prokaryotic and eukaryotic gene finder that is exclusively based on a RNA-Seq mapping and inherently includes ambiguously mapped reads. GIIRA extracts candidate regions supported by a sufficient number of mappings and reassigns ambiguous reads to their most likely origin using a maximum-flow approach. This avoids the exclusion of genes that are predominantly supported by ambiguous mappings. Evaluation on simulated and real data and comparison with existing methods incorporating RNA-Seq information highlight the accuracy of GIIRA in identifying the expressed genes. AVAILABILITY AND IMPLEMENTATION GIIRA is implemented in Java and is available from https://sourceforge.net/projects/giira/.
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Affiliation(s)
- Franziska Zickmann
- Research Group Bioinformatics (NG4), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany
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