Divergence of Noncoding Regulatory Elements Explains Gene–Phenotype Differences between Human and Mouse Orthologous Genes
Mice have been widely used as a model organism to investigate human gene-phenotype relationships based on a conjecture that orthologous genes generally perform similar functions and are associated with similar phenotypes. However, phenotypes associated with orthologous genes often turn out to be qui...
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| Published in | Molecular biology and evolution Vol. 35; no. 7; pp. 1653 - 1667 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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United States
Oxford University Press
01.07.2018
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| Abstract | Mice have been widely used as a model organism to investigate human gene-phenotype relationships based on a conjecture that orthologous genes generally perform similar functions and are associated with similar phenotypes. However, phenotypes associated with orthologous genes often turn out to be quite different between human and mouse. Herein, we devised a method to quantitatively compare phenotypes annotations associated with mouse models and human. Using semantic similarity comparisons, we identified orthologous genes with different phenotype annotations, of which the similarity score is on a par with that of random gene pairs. Analysis of sequence evolution and transcriptomic changes revealed that orthologous genes with phenotypic differences are correlated with changes in noncoding regulatory elements and tissue-specific expression profiles rather than changes in protein-coding sequences. To map accurate gene-phenotype relationships using model organisms, we propose that careful consideration of the evolutionary divergence of noncoding regulatory elements and transcriptomic profiles is essential. |
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| AbstractList | Mice have been widely used as a model organism to investigate human gene-phenotype relationships based on a conjecture that orthologous genes generally perform similar functions and are associated with similar phenotypes. However, phenotypes associated with orthologous genes often turn out to be quite different between human and mouse. Herein, we devised a method to quantitatively compare phenotypes annotations associated with mouse models and human. Using semantic similarity comparisons, we identified orthologous genes with different phenotype annotations, of which the similarity score is on a par with that of random gene pairs. Analysis of sequence evolution and transcriptomic changes revealed that orthologous genes with phenotypic differences are correlated with changes in noncoding regulatory elements and tissue-specific expression profiles rather than changes in protein-coding sequences. To map accurate gene-phenotype relationships using model organisms, we propose that careful consideration of the evolutionary divergence of noncoding regulatory elements and transcriptomic profiles is essential.Mice have been widely used as a model organism to investigate human gene-phenotype relationships based on a conjecture that orthologous genes generally perform similar functions and are associated with similar phenotypes. However, phenotypes associated with orthologous genes often turn out to be quite different between human and mouse. Herein, we devised a method to quantitatively compare phenotypes annotations associated with mouse models and human. Using semantic similarity comparisons, we identified orthologous genes with different phenotype annotations, of which the similarity score is on a par with that of random gene pairs. Analysis of sequence evolution and transcriptomic changes revealed that orthologous genes with phenotypic differences are correlated with changes in noncoding regulatory elements and tissue-specific expression profiles rather than changes in protein-coding sequences. To map accurate gene-phenotype relationships using model organisms, we propose that careful consideration of the evolutionary divergence of noncoding regulatory elements and transcriptomic profiles is essential. Mice have been widely used as a model organism to investigate human gene–phenotype relationships based on a conjecture that orthologous genes generally perform similar functions and are associated with similar phenotypes. However, phenotypes associated with orthologous genes often turn out to be quite different between human and mouse. Herein, we devised a method to quantitatively compare phenotypes annotations associated with mouse models and human. Using semantic similarity comparisons, we identified orthologous genes with different phenotype annotations, of which the similarity score is on a par with that of random gene pairs. Analysis of sequence evolution and transcriptomic changes revealed that orthologous genes with phenotypic differences are correlated with changes in noncoding regulatory elements and tissue-specific expression profiles rather than changes in protein-coding sequences. To map accurate gene–phenotype relationships using model organisms, we propose that careful consideration of the evolutionary divergence of noncoding regulatory elements and transcriptomic profiles is essential. |
| Author | Kim, Donghyo Kim, Sanguk Lee, Heetak Han, Seong Kyu Kim, Inhae |
| Author_xml | – sequence: 1 givenname: Seong Kyu surname: Han fullname: Han, Seong Kyu organization: Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea – sequence: 2 givenname: Donghyo surname: Kim fullname: Kim, Donghyo organization: Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea – sequence: 3 givenname: Heetak surname: Lee fullname: Lee, Heetak organization: Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea – sequence: 4 givenname: Inhae surname: Kim fullname: Kim, Inhae organization: Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea – sequence: 5 givenname: Sanguk surname: Kim fullname: Kim, Sanguk organization: Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29697819$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Animal models Annotations Disease Divergence Evolutionary genetics Genes Genetic engineering Genomes Genotype & phenotype Human subjects Ontology Organisms Phenotypes Regulatory sequences Semantics Similarity Transcriptomics |
| Title | Divergence of Noncoding Regulatory Elements Explains Gene–Phenotype Differences between Human and Mouse Orthologous Genes |
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