An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.
BACKGROUND
Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach.


METHODS
Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data.


RESULTS
Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B.


CONCLUSIONS
To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.
Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark. lkog@sund.ku.dk.
Lisette J A
LJ
Kogelman
Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. dashazhernakova@gmail.com.
Daria V
DV
Zhernakova
Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. westra.harmjan@outlook.com.|Partners Center for Personalized Genetic Medicine, Boston, MA, USA. westra.harmjan@outlook.com.|Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. westra.harmjan@outlook.com.
Harm-Jan
HJ
Westra
Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark. scs@sund.ku.dk.
Susanna
S
Cirera
Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark. mf@sund.ku.dk.
Merete
M
Fredholm
Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. lude@ludesign.nl.
Lude
L
Franke
Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark. hajak@sund.ku.dk.
Haja N
HN
Kadarmideen
D000273:Adipose Tissue / Q000378:metabolism; D000818:Animals; D005260:Female; D020869:Gene Expression Profiling; D020022:Genetic Predisposition to Disease; D023281:Genomics; D008297:Male; D009765:Obesity / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D017423:Sequence Analysis, RNA; D013552:Swine