Genetic dissection of complex traits using hierarchical biological knowledge.

Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act through poorly understood mechanisms. Recent machine learning (ML) systems have used hierarchical biological knowledge to associate genetic mutations w...

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Autores principales:	Hidenori Tanaka, Jason F Kreisberg, Trey Ideker
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/c7e9fe0d5e554f64bd4c986c5d19c70b
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spelling	oai:doaj.org-article:c7e9fe0d5e554f64bd4c986c5d19c70b2021-12-02T19:57:46ZGenetic dissection of complex traits using hierarchical biological knowledge.1553-734X1553-735810.1371/journal.pcbi.1009373https://doaj.org/article/c7e9fe0d5e554f64bd4c986c5d19c70b2021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009373https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act through poorly understood mechanisms. Recent machine learning (ML) systems have used hierarchical biological knowledge to associate genetic mutations with phenotypic outcomes, yielding substantial predictive power and mechanistic insight. Here, we use an ontology-guided ML system to map single nucleotide variants (SNVs) focusing on 6 classic phenotypic traits in natural yeast populations. The 29 identified loci are largely novel and account for ~17% of the phenotypic variance, versus <3% for standard genetic analysis. Representative results show that sensitivity to hydroxyurea is linked to SNVs in two alternative purine biosynthesis pathways, and that sensitivity to copper arises through failure to detoxify reactive oxygen species in fatty acid metabolism. This work demonstrates a knowledge-based approach to amplifying and interpreting signals in population genetic studies.Hidenori TanakaJason F KreisbergTrey IdekerPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009373 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Hidenori Tanaka Jason F Kreisberg Trey Ideker Genetic dissection of complex traits using hierarchical biological knowledge.
description	Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act through poorly understood mechanisms. Recent machine learning (ML) systems have used hierarchical biological knowledge to associate genetic mutations with phenotypic outcomes, yielding substantial predictive power and mechanistic insight. Here, we use an ontology-guided ML system to map single nucleotide variants (SNVs) focusing on 6 classic phenotypic traits in natural yeast populations. The 29 identified loci are largely novel and account for ~17% of the phenotypic variance, versus <3% for standard genetic analysis. Representative results show that sensitivity to hydroxyurea is linked to SNVs in two alternative purine biosynthesis pathways, and that sensitivity to copper arises through failure to detoxify reactive oxygen species in fatty acid metabolism. This work demonstrates a knowledge-based approach to amplifying and interpreting signals in population genetic studies.
format	article
author	Hidenori Tanaka Jason F Kreisberg Trey Ideker
author_facet	Hidenori Tanaka Jason F Kreisberg Trey Ideker
author_sort	Hidenori Tanaka
title	Genetic dissection of complex traits using hierarchical biological knowledge.
title_short	Genetic dissection of complex traits using hierarchical biological knowledge.
title_full	Genetic dissection of complex traits using hierarchical biological knowledge.
title_fullStr	Genetic dissection of complex traits using hierarchical biological knowledge.
title_full_unstemmed	Genetic dissection of complex traits using hierarchical biological knowledge.
title_sort	genetic dissection of complex traits using hierarchical biological knowledge.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/c7e9fe0d5e554f64bd4c986c5d19c70b
work_keys_str_mv	AT hidenoritanaka geneticdissectionofcomplextraitsusinghierarchicalbiologicalknowledge AT jasonfkreisberg geneticdissectionofcomplextraitsusinghierarchicalbiologicalknowledge AT treyideker geneticdissectionofcomplextraitsusinghierarchicalbiologicalknowledge
_version_	1718375803528413184

Genetic dissection of complex traits using hierarchical biological knowledge.

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