Using protein complexes to predict phenotypic effects of gene mutation
Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Fraser, Hunter B [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Anmerkung: |
© Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
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| Übergeordnetes Werk: |
Enthalten in: Genome biology - London : BioMed Central, 2000, 8(2007), 11 vom: 27. Nov. |
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| Übergeordnetes Werk: |
volume:8 ; year:2007 ; number:11 ; day:27 ; month:11 |
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| DOI / URN: |
10.1186/gb-2007-8-11-r252 |
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| 520 | |a Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. | ||
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10.1186/gb-2007-8-11-r252 doi (DE-627)SPR029997976 (SPR)gb-2007-8-11-r252-e DE-627 ger DE-627 rakwb eng Fraser, Hunter B verfasserin aut Using protein complexes to predict phenotypic effects of gene mutation 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. Gene Pair (dpeaa)DE-He213 Disease Gene (dpeaa)DE-He213 Additional Data File (dpeaa)DE-He213 Human Protein Reference Database (dpeaa)DE-He213 Human Disease Gene (dpeaa)DE-He213 Plotkin, Joshua B aut Enthalten in Genome biology London : BioMed Central, 2000 8(2007), 11 vom: 27. Nov. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:8 year:2007 number:11 day:27 month:11 https://dx.doi.org/10.1186/gb-2007-8-11-r252 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2007 11 27 11 |
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10.1186/gb-2007-8-11-r252 doi (DE-627)SPR029997976 (SPR)gb-2007-8-11-r252-e DE-627 ger DE-627 rakwb eng Fraser, Hunter B verfasserin aut Using protein complexes to predict phenotypic effects of gene mutation 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. Gene Pair (dpeaa)DE-He213 Disease Gene (dpeaa)DE-He213 Additional Data File (dpeaa)DE-He213 Human Protein Reference Database (dpeaa)DE-He213 Human Disease Gene (dpeaa)DE-He213 Plotkin, Joshua B aut Enthalten in Genome biology London : BioMed Central, 2000 8(2007), 11 vom: 27. Nov. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:8 year:2007 number:11 day:27 month:11 https://dx.doi.org/10.1186/gb-2007-8-11-r252 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2007 11 27 11 |
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10.1186/gb-2007-8-11-r252 doi (DE-627)SPR029997976 (SPR)gb-2007-8-11-r252-e DE-627 ger DE-627 rakwb eng Fraser, Hunter B verfasserin aut Using protein complexes to predict phenotypic effects of gene mutation 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. Gene Pair (dpeaa)DE-He213 Disease Gene (dpeaa)DE-He213 Additional Data File (dpeaa)DE-He213 Human Protein Reference Database (dpeaa)DE-He213 Human Disease Gene (dpeaa)DE-He213 Plotkin, Joshua B aut Enthalten in Genome biology London : BioMed Central, 2000 8(2007), 11 vom: 27. Nov. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:8 year:2007 number:11 day:27 month:11 https://dx.doi.org/10.1186/gb-2007-8-11-r252 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2007 11 27 11 |
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10.1186/gb-2007-8-11-r252 doi (DE-627)SPR029997976 (SPR)gb-2007-8-11-r252-e DE-627 ger DE-627 rakwb eng Fraser, Hunter B verfasserin aut Using protein complexes to predict phenotypic effects of gene mutation 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. Gene Pair (dpeaa)DE-He213 Disease Gene (dpeaa)DE-He213 Additional Data File (dpeaa)DE-He213 Human Protein Reference Database (dpeaa)DE-He213 Human Disease Gene (dpeaa)DE-He213 Plotkin, Joshua B aut Enthalten in Genome biology London : BioMed Central, 2000 8(2007), 11 vom: 27. Nov. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:8 year:2007 number:11 day:27 month:11 https://dx.doi.org/10.1186/gb-2007-8-11-r252 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2007 11 27 11 |
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10.1186/gb-2007-8-11-r252 doi (DE-627)SPR029997976 (SPR)gb-2007-8-11-r252-e DE-627 ger DE-627 rakwb eng Fraser, Hunter B verfasserin aut Using protein complexes to predict phenotypic effects of gene mutation 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. Gene Pair (dpeaa)DE-He213 Disease Gene (dpeaa)DE-He213 Additional Data File (dpeaa)DE-He213 Human Protein Reference Database (dpeaa)DE-He213 Human Disease Gene (dpeaa)DE-He213 Plotkin, Joshua B aut Enthalten in Genome biology London : BioMed Central, 2000 8(2007), 11 vom: 27. Nov. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:8 year:2007 number:11 day:27 month:11 https://dx.doi.org/10.1186/gb-2007-8-11-r252 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2007 11 27 11 |
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Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
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Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
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Background Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. Results Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. Conclusion We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. © Fraser and Plotkin; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
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| score |
7.398857 |