Evaluating High-Throughput Ab Initio Gene Finders to Discover Proteins Encoded in Eukaryotic Pathogen Genomes Missed by Laboratory Techniques

PLoS ONE

Volumn 7, Issue 11, 2012, Pages

  Goodswen, Stephen J ^a   Kennedy, Paul J ^b   Ellis, John T ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

^b UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

PROTOZOAL PROTEIN;

AB INITIO CALCULATION; AB INITIO GENE FINDER; ANALYTICAL ERROR; ARTICLE; BIOINFORMATICS; DATA ANALYSIS SOFTWARE; EUKARYOTE; EVALUATION RESEARCH; EXON; GENE IDENTIFICATION; GENOME ANALYSIS; HIGH THROUGHPUT SEQUENCING; LABORATORY TEST; PREDICTION; PROTEIN DETERMINATION; QUALITY CONTROL; TOXOPLASMA GONDII;

BASE SEQUENCE; GENES, PROTOZOAN; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; LABORATORIES; PROTOZOAN PROTEINS; REPRODUCIBILITY OF RESULTS; TOXOPLASMA;

EUKARYOTA; TOXOPLASMA GONDII;

EID: 84870596055     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0050609     Document Type: Article

References (71)

1. Serruto D, Serino L, Masignani V, Pizza M, (2009) Genome-based approaches to develop vaccines against bacterial pathogens. Vaccine 27: 3245-3250.
2. Kassahn KS, Waddell N, Grimmond SM, (2011) Sequencing transcriptomes in toto. Integrative Biology 3: 522-528.
3. Wang Z, Gerstein M, Snyder M, (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10: 57-63.
4. Claverie J-M, Poirot O, Lopez F, (1997) The difficulty of identifying genes in anonymous vertebrate sequences. Computers & Chemistry 21: 203-214.
5. Fickett JW, (1996) The gene identification problem: An overview for developers. Computers and Chemistry 20: 103-118.
6. Fickett JW, (1996) Finding genes by computer: the state of the art. Trends in Genetics 12: 316-320.
7. Guigó R, (1997) Computational gene identification: an open problem. Computers & Chemistry 21: 215-222.
8. Guigó R, Agarwal P, Abril JF, Burset M, Fickett JW, (2000) An Assessment of Gene Prediction Accuracy in Large DNA Sequences. Genome Research 10: 1631-1642.
9. Korf I, (2004) Gene finding in novel genomes. BMC Bioinformatics 5: 59.
10. Mathé C, Sagot MF, Schiex T, Rouzé P, (2002) Current methods of gene prediction, their strengths and weaknesses. Nucleic Acids Research 30: 4103-4117.
11. Bork P, (2000) Powers and Pitfalls in Sequence Analysis: The 70% Hurdle. Genome Research 10: 398-400.
12. Ivanov IP, Firth AE, Michel AM, Atkins JF, Baranov PV, (2011) Identification of evolutionarily conserved non-AUG-initiated N-terminal extensions in human coding sequences. Nucleic Acids Research 39: 4220-4234.
13. Takahashi K, Maruyama M, Tokuzawa Y, Murakami M, Oda Y, et al. (2005) Evolutionarily conserved non-AUG translation initiation in NAT1/p97/DAP5 (EIF4G2). Genomics 85: 360-371.
14. Touriol C, Bornes S, Bonnal S, Audigier S, Prats H, et al. (2003) Generation of protein isoform diversity by alternative initiation of translation at non-AUG codons. Biology of the Cell 95: 169-178.
15. Chambers I, Harrison PR, (1987) A new puzzle in selenoprotein biosynthesis- selenocysteine seems to be encoded by the stop codon, UGA. Trends in Biochemical Sciences 12: 255-256.
16. Brent MR, (2007) How does eukaryotic gene prediction work? Nat Biotech 25: 883-885.
17. Burset M, Seledtsov IA, Solovyev VV, (2000) Analysis of canonical and non-canonical splice sites in mammalian genomes. Nucleic Acids Research 28: 4364-4375.
18. Patel AA, Steitz JA, (2003) Splicing double: Insights from the second spliceosome. Nature Reviews Molecular Cell Biology 4: 960-970.
19. Xu Y, Mural RJ, Einstein JR, Shah MB, Uberbacher EC, (1996) GRAIL: A multi-agent neural network system for gene identification. Proceedings of the Ieee 84: 1544-1552.
20. Parra G, Blanco E, Guigo R, (2000) GeneID in Drosophila. Genome Research 10: 511-515.
21. Snyder EE, Stormo GD, (1993) Identification of coding regions in genomic DNA-sequences- an application of dynamic-programming and neural networks. Nucleic Acids Research 21: 607-613.
22. Solovyev VV, Salamov AA, Lawrence CB, (1995) Identification of human gene structure using linear discriminant functions and dynamic programming. Proceedings/International Conference on Intelligent Systems for Molecular Biology; ISMB International Conference on Intelligent Systems for Molecular Biology 3: 367-375.
23. Kulp D, Haussler D, Reese MG, Eeckman FH, (1996) A generalized hidden Markov model for the recognition of human genes in DNA. Proceedings/International Conference on Intelligent Systems for Molecular Biology; ISMB International Conference on Intelligent Systems for Molecular Biology 4: 134-142.
24. Gelfand MS, Mironov AA, Pevzner PA, (1996) Gene recognition via spliced sequence alignment. Proceedings of the National Academy of Sciences of the United States of America 93: 9061-9066.
25. Salamov AA, Solovyev VV, (2000) Ab initio gene finding in Drosophila genomic DNA. Genome Research 10: 516-522.
26. Burge C, Karlin S, (1997) Prediction of complete gene structures in human genomic DNA. Journal of Molecular Biology 268: 78-94.
27. Krogh A (1997) Two methods for improving performance of an HMM and their application for gene finding; Gaasterland TKPKKOCSCVA, editor. 179-186 p.
28. Birney E, Durbin R, (1997) Dynamite: a flexible code generating language for dynamic programming methods used in sequence comparison. Proceedings/International Conference on Intelligent Systems for Molecular Biology; ISMB International Conference on Intelligent Systems for Molecular Biology 5: 56-64.
29. Lukashin AV, Borodovsky M, (1998) GeneMark.hmm: New solutions for gene finding. Nucleic Acids Research 26: 1107-1115.
30. Yeh RF, Lim LP, Burge CB, (2001) Computational inference of homologous gene structures in the human genome. Genome Research 11: 803-816.
31. van Baren MJ, Koebbe BC, Brent MR (2002) Using N-SCAN or TWINSCAN to Predict Gene Structures in Genomic DNA Sequences. Current Protocols in Bioinformatics: John Wiley & Sons, Inc.
32. Howe KL, Chothia T, Durbin R, (2002) GAZE: A Generic Framework for the Integration of Gene-Prediction Data by Dynamic Programming. Genome Research 12: 1418-1427.
33. Hubbard T, Barker D, Birney E, Cameron G, Chen Y, et al. (2002) The Ensembl genome database project. Nucleic Acids Research 30: 38-41.
34. Majoros WH, Pertea M, Salzberg SL, (2004) TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics 20: 2878-2879.
35. Stanke M, Steinkamp R, Waack S, Morgenstern B, (2004) AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Research 32: W309-W312.
36. Gross S, Brent M, (2006) Using Multiple Alignments to Improve Gene Prediction. Journal of Computational Biology 13: 379-393.
37. Wei CC, Brent MR (2006) Using ESTs to improve the accuracy of de novo gene prediction. BMC Bioinformatics 7.
38. DeCaprio D, Vinson JP, Pearson MD, Montgomery P, Doherty M, et al. (2007) Conrad: Gene prediction using conditional random fields. Genome Research 17: 1389-1398.
39. Gross SS, Do CB, Sirota M, Batzoglou S (2007) CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction. Genome Biology 8.
40. Schweikert G, Behr J, Zien A, Zeller G, Ong CS, et al. (2009) mGene.web: a web service for accurate computational gene finding. Nucleic Acids Research 37: W312-W316.
41. Baxevanis AD (2002) Predictive Methods Using DNA Sequences. Bioinformatics: John Wiley & Sons, Inc. 233-252.
42. Borodovsky M, Rudd KE, Koonin EV, (1994) Intrinsic and extrinsic approaches for detecting genes in a bacterial genome. Nucleic Acids Research 22: 4756-4767.
43. Parra Gs, Agarwal P, Abril JF, Wiehe T, Fickett JW, et al. (2003) Comparative Gene Prediction in Human and Mouse. Genome Research 13: 108-117.
44. Margulies EH, Birney E, (2008) Approaches to comparative sequence analysis: towards a functional view of vertebrate genomes. Nature Reviews Genetics 9: 303-313.
45. Montoya JG, Liesenfeld O, (2004) Toxoplasmosis. The Lancet 363: 1965-1976.
46. Che F-Y, Madrid-Aliste C, Burd B, Zhang H, Nieves E, et al. (2010) Comprehensive proteomic analysis of membrane proteins in toxoplasma gondii. Molecular & Cellular Proteomics.
47. Kim K, Weiss LM, (2004) Toxoplasma gondii: the model apicomplexan. International Journal for Parasitology 34: 423-432.
48. Roos DS, Crawford MJ, Donald RG, Fohl LM, Hager KM, et al. (1999) Transport and trafficking: Toxoplasma as a model for Plasmodium. Novartis Foundation symposium 226: 176.
49. Roos DS, (2005) Themes and variations in apicomplexan parasite biology. Science 309: 72-73.
50. Stanke M, Tzvetkova A, Morgenstern B, (2006) AUGUSTUS at EGASP: using EST, protein and genomic alignments for improved gene prediction in the human genome. Genome Biology 7: S11.
51. Pertea M, Salzberg SL (2002) Using GlimmerM to Find Genes in Eukaryotic Genomes: John Wiley & Sons, Inc.
52. Sleator RD, (2010) An overview of the current status of eukaryote gene prediction strategies. Gene 461: 1-4.
53. Kissinger JC, Gajria B, Li L, Paulsen IT, Roos DS, (2003) ToxoDB: accessing the Toxoplasma gondii genome. Nucleic Acids Research 31: 234-236.
54. Burset M, Guigo R, (1996) Evaluation of gene structure prediction programs. Genomics 34: 353-367.
55. Guigo R, Flicek P, Abril JF, Reymond A, Lagarde J, et al. (2006) EGASP: the human ENCODE genome annotation assessment project. Genome Biology 7.
56. Dybas JM, Madrid-Aliste CJ, Che F-Y, Nieves E, Rykunov D, et al. (2008) Computational Analysis and Experimental Validation of Gene Predictions in Toxoplasma gondii. PLoS ONE 3: e3899.
57. Liu Q, Crammer K, Pereira FCN, Roos DS (2008) Reranking candidate gene models with cross-species comparison for improved gene prediction. BMC Bioinformatics 9.
58. Knapp K, Chen Y-PP, (2007) An evaluation of contemporary hidden Markov model genefinders with a predicted exon taxonomy. Nucleic Acids Research 35: 317-324.
59. Allen JE, Pertea M, Salzberg SL, (2004) Computational Gene Prediction Using Multiple Sources of Evidence. Genome Research 14: 142-148.
60. Haas B, Salzberg S, Zhu W, Pertea M, Allen J, et al. (2008) Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biology 9: R7.
61. Allen JE, Salzberg SL, (2005) JIGSAW: integration of multiple sources of evidence for gene prediction. Bioinformatics 21: 3596-3603.
62. Liu Q, Mackey AJ, Roos DS, Pereira FCN, (2008) Evigan: a hidden variable model for integrating gene evidence for eukaryotic gene prediction. Bioinformatics 24: 597-605.
63. Lomsadze A, Ter-Hovhannisyan V, Chernoff YO, Borodovsky M, (2005) Gene identification in novel eukaryotic genomes by self-training algorithm. Nucleic Acids Research 33: 6494-6506.
64. Li L, Brunk BP, Kissinger JC, Pape D, Tang KL, et al. (2003) Gene discovery in the Apicomplexa as revealed by EST sequencing and assembly of a comparative gene database. Genome Research 13: 443-454.
65. Wakaguri H, Suzuki Y, Sasaki M, Sugano S, Watanabe J (2009) Inconsistencies of genome annotations in apicomplexan parasites revealed by 5′-end-one-pass and full-length sequences of oligo-capped cDNAs. BMC Genomics 10.
66. Wastling JM, Xia D, Sohal A, Chaussepied M, Pain A, et al. (2009) Proteomes and transcriptomes of the Apicomplexa- Where's the message? International Journal for Parasitology 39: 135-143.
67. Harrow J, Nagy A, Reymond A, Alioto T, Patthy L, et al. (2009) Identifying protein-coding genes in genomic sequences. Genome Biology 10.
68. Flower DR, Macdonald IK, Ramakrishnan K, Davies MN, Doytchinova IA, (2010) Computer aided selection of candidate vaccine antigens. Immunome Research 6Suppl 2: S1.
69. Ninaber A, Goodfellow JM, (1999) DNA conformation and dynamics. Radiation and Environmental Biophysics 38: 23-29.
70. Service RF (2000) DNA imaging- Getting a feel for genetic variations. Science 289: 27-28.
71. Mora M, Donati C, Medini D, Covacci A, Rappuoli R (2006) Microbial genomes and vaccine design: refinements to the classical reverse vaccinology approach. Curr Opin Microbiol 9.