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iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases
Disease modeling with induced pluripotent stem cells (iPSCs) is creating an abundance of phenotypic information that has become difficult to follow and interpret. Here, we report a systematic analysis of research practices and reporting bias in neurological disease models from 93 published articles....
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5731211/ https://www.ncbi.nlm.nih.gov/pubmed/29051230 http://dx.doi.org/10.15252/emmm.201708191 |
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author | Hollingsworth, Ethan W Vaughn, Jacob E Orack, Josh C Skinner, Chelsea Khouri, Jamil Lizarraga, Sofia B Hester, Mark E Watanabe, Fumihiro Kosik, Kenneth S Imitola, Jaime |
author_facet | Hollingsworth, Ethan W Vaughn, Jacob E Orack, Josh C Skinner, Chelsea Khouri, Jamil Lizarraga, Sofia B Hester, Mark E Watanabe, Fumihiro Kosik, Kenneth S Imitola, Jaime |
author_sort | Hollingsworth, Ethan W |
collection | PubMed |
description | Disease modeling with induced pluripotent stem cells (iPSCs) is creating an abundance of phenotypic information that has become difficult to follow and interpret. Here, we report a systematic analysis of research practices and reporting bias in neurological disease models from 93 published articles. We find heterogeneity in current research practices and a reporting bias toward certain diseases. Moreover, we identified 663 CNS cell‐derived phenotypes from 243 patients and 214 controls, which varied by mutation type and developmental stage in vitro. We clustered these phenotypes into a taxonomy and characterized these phenotype–genotype relationships to generate a phenogenetic map that revealed novel correlations among previously unrelated genes. We also find that alterations in patient‐derived molecular profiles associated with cellular phenotypes, and dysregulated genes show predominant expression in brain regions with pathology. Last, we developed the iPS cell phenogenetic map project atlas (iPhemap), an open submission, online database to continually catalog disease phenotypes. Overall, our findings offer new insights into the phenogenetics of iPSC‐derived models while our web tool provides a platform for researchers to query and deposit phenotypic information of neurological diseases. |
format | Online Article Text |
id | pubmed-5731211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57312112017-12-18 iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases Hollingsworth, Ethan W Vaughn, Jacob E Orack, Josh C Skinner, Chelsea Khouri, Jamil Lizarraga, Sofia B Hester, Mark E Watanabe, Fumihiro Kosik, Kenneth S Imitola, Jaime EMBO Mol Med Research Articles Disease modeling with induced pluripotent stem cells (iPSCs) is creating an abundance of phenotypic information that has become difficult to follow and interpret. Here, we report a systematic analysis of research practices and reporting bias in neurological disease models from 93 published articles. We find heterogeneity in current research practices and a reporting bias toward certain diseases. Moreover, we identified 663 CNS cell‐derived phenotypes from 243 patients and 214 controls, which varied by mutation type and developmental stage in vitro. We clustered these phenotypes into a taxonomy and characterized these phenotype–genotype relationships to generate a phenogenetic map that revealed novel correlations among previously unrelated genes. We also find that alterations in patient‐derived molecular profiles associated with cellular phenotypes, and dysregulated genes show predominant expression in brain regions with pathology. Last, we developed the iPS cell phenogenetic map project atlas (iPhemap), an open submission, online database to continually catalog disease phenotypes. Overall, our findings offer new insights into the phenogenetics of iPSC‐derived models while our web tool provides a platform for researchers to query and deposit phenotypic information of neurological diseases. John Wiley and Sons Inc. 2017-10-19 2017-12 /pmc/articles/PMC5731211/ /pubmed/29051230 http://dx.doi.org/10.15252/emmm.201708191 Text en © 2017 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the Creative Commons Attribution 4.0 (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Hollingsworth, Ethan W Vaughn, Jacob E Orack, Josh C Skinner, Chelsea Khouri, Jamil Lizarraga, Sofia B Hester, Mark E Watanabe, Fumihiro Kosik, Kenneth S Imitola, Jaime iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases |
title | iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases |
title_full | iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases |
title_fullStr | iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases |
title_full_unstemmed | iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases |
title_short | iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases |
title_sort | iphemap: an atlas of phenotype to genotype relationships of human ipsc models of neurological diseases |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5731211/ https://www.ncbi.nlm.nih.gov/pubmed/29051230 http://dx.doi.org/10.15252/emmm.201708191 |
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