Dissecting cis regulation of gene expression in human metabolic tissues.
Complex diseases such as obesity and type II diabetes can result from a failure in multiple organ systems including the central nervous system and tissues involved in partitioning and disposal of nutrients. Studying the genetics of gene expression in tissues that are involved in the development of t...
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doaj-bc094830d70a4dd7a6051d4817b31f452020-11-25T01:17:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-0168e2348010.1371/journal.pone.0023480Dissecting cis regulation of gene expression in human metabolic tissues.Radu DobrinDanielle M GreenawaltGuanghui HuDaniel M KempLee M KaplanEric E SchadtValur EmilssonComplex diseases such as obesity and type II diabetes can result from a failure in multiple organ systems including the central nervous system and tissues involved in partitioning and disposal of nutrients. Studying the genetics of gene expression in tissues that are involved in the development of these diseases can provide insights into how these tissues interact within the context of disease. Expression quantitative trait locus (eQTL) studies identify mRNA expression changes linked to proximal genetic signals (cis eQTLs) that have been shown to affect disease. Given the high impact of recent eQTL studies, it is important to understand what role sample size and environment plays in identification of cis eQTLs. Here we show in a genotyped obese human population that the number of cis eQTLs obey precise scaling laws as a function of sample size in three profiled tissues, i.e. omental adipose, subcutaneous adipose and liver. Also, we show that genes (or transcripts) with cis eQTL associations detected in a small population are detected at approximately 90% rate in the largest population available for our study, indicating that genes with strong cis acting regulatory elements can be identified with relatively high confidence in smaller populations. However, by increasing the sample size we allow for better detection of weaker and more distantly located cis-regulatory elements. Yet, we determined that the number of tissue specific cis eQTLs saturates in a modestly sized cohort while the number of cis eQTLs common to all tissues fails to reach a maximum value. Understanding the power laws that govern the number and specificity of eQTLs detected in different tissues, will allow a better utilization of genetics of gene expression to inform the molecular mechanism underlying complex disease traits.http://europepmc.org/articles/PMC3166146?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Radu Dobrin Danielle M Greenawalt Guanghui Hu Daniel M Kemp Lee M Kaplan Eric E Schadt Valur Emilsson |
spellingShingle |
Radu Dobrin Danielle M Greenawalt Guanghui Hu Daniel M Kemp Lee M Kaplan Eric E Schadt Valur Emilsson Dissecting cis regulation of gene expression in human metabolic tissues. PLoS ONE |
author_facet |
Radu Dobrin Danielle M Greenawalt Guanghui Hu Daniel M Kemp Lee M Kaplan Eric E Schadt Valur Emilsson |
author_sort |
Radu Dobrin |
title |
Dissecting cis regulation of gene expression in human metabolic tissues. |
title_short |
Dissecting cis regulation of gene expression in human metabolic tissues. |
title_full |
Dissecting cis regulation of gene expression in human metabolic tissues. |
title_fullStr |
Dissecting cis regulation of gene expression in human metabolic tissues. |
title_full_unstemmed |
Dissecting cis regulation of gene expression in human metabolic tissues. |
title_sort |
dissecting cis regulation of gene expression in human metabolic tissues. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2011-01-01 |
description |
Complex diseases such as obesity and type II diabetes can result from a failure in multiple organ systems including the central nervous system and tissues involved in partitioning and disposal of nutrients. Studying the genetics of gene expression in tissues that are involved in the development of these diseases can provide insights into how these tissues interact within the context of disease. Expression quantitative trait locus (eQTL) studies identify mRNA expression changes linked to proximal genetic signals (cis eQTLs) that have been shown to affect disease. Given the high impact of recent eQTL studies, it is important to understand what role sample size and environment plays in identification of cis eQTLs. Here we show in a genotyped obese human population that the number of cis eQTLs obey precise scaling laws as a function of sample size in three profiled tissues, i.e. omental adipose, subcutaneous adipose and liver. Also, we show that genes (or transcripts) with cis eQTL associations detected in a small population are detected at approximately 90% rate in the largest population available for our study, indicating that genes with strong cis acting regulatory elements can be identified with relatively high confidence in smaller populations. However, by increasing the sample size we allow for better detection of weaker and more distantly located cis-regulatory elements. Yet, we determined that the number of tissue specific cis eQTLs saturates in a modestly sized cohort while the number of cis eQTLs common to all tissues fails to reach a maximum value. Understanding the power laws that govern the number and specificity of eQTLs detected in different tissues, will allow a better utilization of genetics of gene expression to inform the molecular mechanism underlying complex disease traits. |
url |
http://europepmc.org/articles/PMC3166146?pdf=render |
work_keys_str_mv |
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