Cargando…

Understanding Disease Susceptibility through Population Genomics

Genetic epidemiology studies have established that the natural variation of gene expression profiles is heritable and has genetic bases. A number of proximal and remote DNA variations, known as expression quantitative trait loci (eQTLs), that are associated with the expression phenotypes have been i...

Descripción completa

Detalles Bibliográficos
Autores principales: Han, Seonggyun, Lee, Junnam, Kim, Sangsoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543923/
https://www.ncbi.nlm.nih.gov/pubmed/23346035
http://dx.doi.org/10.5808/GI.2012.10.4.234
_version_ 1782255720254668800
author Han, Seonggyun
Lee, Junnam
Kim, Sangsoo
author_facet Han, Seonggyun
Lee, Junnam
Kim, Sangsoo
author_sort Han, Seonggyun
collection PubMed
description Genetic epidemiology studies have established that the natural variation of gene expression profiles is heritable and has genetic bases. A number of proximal and remote DNA variations, known as expression quantitative trait loci (eQTLs), that are associated with the expression phenotypes have been identified, first in Epstein-Barr virus-transformed lymphoblastoid cell lines and later expanded to other cell and tissue types. Integration of the eQTL information and the network analysis of transcription modules may lead to a better understanding of gene expression regulation. As these network modules have relevance to biological or disease pathways, these findings may be useful in predicting disease susceptibility.
format Online
Article
Text
id pubmed-3543923
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Korea Genome Organization
record_format MEDLINE/PubMed
spelling pubmed-35439232013-01-23 Understanding Disease Susceptibility through Population Genomics Han, Seonggyun Lee, Junnam Kim, Sangsoo Genomics Inform Review Article Genetic epidemiology studies have established that the natural variation of gene expression profiles is heritable and has genetic bases. A number of proximal and remote DNA variations, known as expression quantitative trait loci (eQTLs), that are associated with the expression phenotypes have been identified, first in Epstein-Barr virus-transformed lymphoblastoid cell lines and later expanded to other cell and tissue types. Integration of the eQTL information and the network analysis of transcription modules may lead to a better understanding of gene expression regulation. As these network modules have relevance to biological or disease pathways, these findings may be useful in predicting disease susceptibility. Korea Genome Organization 2012-12 2012-12-31 /pmc/articles/PMC3543923/ /pubmed/23346035 http://dx.doi.org/10.5808/GI.2012.10.4.234 Text en Copyright © 2012 by The Korea Genome Organization http://creativecommons.org/licenses/by-nc/3.0/ It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/).
spellingShingle Review Article
Han, Seonggyun
Lee, Junnam
Kim, Sangsoo
Understanding Disease Susceptibility through Population Genomics
title Understanding Disease Susceptibility through Population Genomics
title_full Understanding Disease Susceptibility through Population Genomics
title_fullStr Understanding Disease Susceptibility through Population Genomics
title_full_unstemmed Understanding Disease Susceptibility through Population Genomics
title_short Understanding Disease Susceptibility through Population Genomics
title_sort understanding disease susceptibility through population genomics
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3543923/
https://www.ncbi.nlm.nih.gov/pubmed/23346035
http://dx.doi.org/10.5808/GI.2012.10.4.234
work_keys_str_mv AT hanseonggyun understandingdiseasesusceptibilitythroughpopulationgenomics
AT leejunnam understandingdiseasesusceptibilitythroughpopulationgenomics
AT kimsangsoo understandingdiseasesusceptibilitythroughpopulationgenomics