Transcriptional Regulatory Mechanisms in Adipose and Muscle Tissue Associated with Composite Glucometabolic Phenotypes

Langefeld, Carl D.; Comeau, Mary E.; Sharma, Neeraj Kumar; Bowden, Donald W.; Freedman, Barry I.; Das, Swapan K.

doi:10.1002/oby.22113

Cited by 5 publications

(7 citation statements)

References 34 publications

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“…Our previous transcriptome-wide association study (TWAS) analyses identified 7,464 glucometabolic trait-associated transcripts significantly associated with at least 1 of the 23 individual traits and six composite glucometabolic phenotypes tested at Benjamini-Hochberg false discovery rate (FDR)-corrected P value ,0.01 in AT of AAGMEx participants (5,6,28,33). The eQTM analysis used linear regression, as implemented in MatrixEQTL to test whether DNAm levels were associated with transcript expression levels of these glucometabolic trait-associated transcripts.…”

Section: Discussionmentioning

confidence: 99%

“…Subcutaneous AT biopsy samples collected from 230 individuals without diabetes from the AAGMEx cohort (5,6) were used for epigenome-wide DNAm profiling. The clinical and anthropometric characteristics of the AAGMEx cohort have been previously described (5,6,28). Briefly, cohort participants were healthy, self-reported AA men and women residing in North Carolina, aged 18-60 years, with a BMI between 18 and 42 kg/m 2 (Supplementary Table 1).…”

Section: Human Subjectsmentioning

confidence: 99%

“…Details of clinical laboratory measures have been previously described (5,6,28). Among the participants in the AAGMEx cohort, AT transcript profiling data were available for 256 individuals.…”

Section: Laboratory Measures and Physiological Phenotypesmentioning

confidence: 99%

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Integrative Analysis of Glucometabolic Traits, Adipose Tissue DNA Methylation, and Gene Expression Identifies Epigenetic Regulatory Mechanisms of Insulin Resistance and Obesity in African Americans

et al. 2020

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Decline in insulin sensitivity due to dysfunction of adipose tissue (AT) is one of the earliest pathogenic events in type 2 diabetes. We hypothesize that differential DNA methylation (DNAm) controls insulin sensitivity and obesity by modulating transcript expression in AT. Integrating AT DNAm profiles with transcript profile data measured in a cohort of 230 African Americans (AAs) from the African American Genetics of Metabolism and Expression cohort, we performed cis-expression quantitative trait methylation (cis-eQTM) analysis to identify epigenetic regulatory loci for glucometabolic trait–associated transcripts. We identified significantly associated cytosine-guanine dinucleotide regions for 82 transcripts (false discovery rate [FDR]-P < 0.05). The strongest eQTM locus was observed for the proopiomelanocortin (POMC; ρ = −0.632, P = 4.70 × 10−27) gene. Epigenome-wide association studies (EWAS) further identified 155, 46, and 168 cytosine-guanine dinucleotide regions associated (FDR-P < 0.05) with the Matsuda index, SI, and BMI, respectively. Intersection of EWAS, transcript level to trait association, and eQTM results, followed by causal inference test identified significant eQTM loci for 23 genes that were also associated with Matsuda index, SI, and/or BMI in EWAS. These associated genes include FERMT3, ITGAM, ITGAX, and POMC. In summary, applying an integrative multiomics approach, our study provides evidence for DNAm-mediated regulation of gene expression at both previously identified and novel loci for many key AT transcripts influencing insulin resistance and obesity.

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Section: Discussionmentioning

confidence: 99%

Section: Human Subjectsmentioning

confidence: 99%

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Integrative Analysis of Glucometabolic Traits, Adipose Tissue DNA Methylation, and Gene Expression Identifies Epigenetic Regulatory Mechanisms of Insulin Resistance and Obesity in African Americans

et al. 2020

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“…We have for the first time systematically catalogued eQTL in equine skeletal muscle, both at rest and post-exercise. Previous investigations of eQTL in skeletal muscle have focussed primarily on human T2D (Sharma et al, 2011; Keildson et al, 2014a; Sajuthi et al, 2016; Langefeld et al, 2018) and meat quality traits in production animals (Ponsuksili et al, 2015; Gonzalez-Prendes et al, 2017; Pampouille et al, 2018; Gonzalez-Prendes et al, 2019; Velez-Irizarry et al, 2019). Our investigation of eQTL in the context of skeletal muscle and exercise present some of the only work to-date in this area (Kelly et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome

et al. 2019

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While over ten thousand genetic loci have been associated with phenotypic traits and inherited diseases in genome-wide association studies, in most cases only a relatively small proportion of the trait heritability is explained and biological mechanisms underpinning these traits have not been clearly identified. Expression quantitative trait loci (eQTL) are subsets of genomic loci shown experimentally to influence gene expression. Since gene expression is one of the primary determinants of phenotype, the identification of eQTL may reveal biologically relevant loci and provide functional links between genomic variants, gene expression and ultimately phenotype. Skeletal muscle (gluteus medius) gene expression was quantified by RNA-seq for 111 Thoroughbreds (47 male, 64 female) in race training at a single training establishment sampled at two time-points: at rest (n = 92) and four hours after high-intensity exercise (n = 77); n = 60 were sampled at both time points. Genotypes were generated from the Illumina Equine SNP70 BeadChip. Applying a False Discovery Rate (FDR) corrected P-value threshold (P FDR < 0.05), association tests identified 3,583 cis-eQTL associated with expression of 1,456 genes at rest; 4,992 cis-eQTL associated with the expression of 1,922 genes post-exercise; 1,703 trans-eQTL associated with 563 genes at rest; and 1,219 trans-eQTL associated with 425 genes post-exercise. The gene with the highest cis-eQTL association at both time-points was the endosome-associated-trafficking regulator 1 gene (ENTR1; Rest: P FDR = 3.81 × 10-27, Post-exercise: P FDR = 1.66 × 10-24), which has a potential role in the transcriptional regulation of the solute carrier family 2 member 1 glucose transporter protein (SLC2A1). Functional analysis of genes with significant eQTL revealed significant enrichment for cofactor metabolic processes. These results suggest heritable variation in genomic elements such as regulatory sequences (e.g. gene promoters, enhancers, silencers), microRNA and transcription factor genes, which are associated with metabolic function and may have roles in determining end-point muscle and athletic performance phenotypes in Thoroughbred horses. The incorporation of the eQTL identified with genome and transcriptome-wide association may reveal useful biological links between genetic variants and their impact on traits of interest, such as elite racing performance and adaptation to training.

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“…We have for the first time systematically catalogued eQTL in equine skeletal muscle, both at rest and post-exercise. Previous investigations of eQTL in skeletal muscle have focussed primarily on human T2D (Sharma et al, 2011; Keildson et al, 2014a; Sajuthi et al, 2016a; Langefeld et al, 2018)and meat quality traits in production animals (Ponsuksili et al, 2015; Gonzalez-Prendes et al, 2017; Pampouille et al, 2018; Gonzalez-Prendes et al, 2019; Velez-Irizarry et al, 2019). Our investigation of eQTL in the context of skeletal muscle and exercise present some of the only work to-date in this area (Kelly et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Identification of expression quantitative trait loci in the skeletal muscle of Thoroughbreds reveals heritable variation in expression of genes relevant to cofactor metabolism

Farries

Bryan

McGivney

et al. 2019

Preprint

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Summary While over ten thousand genetic loci have been associated with phenotypic traits and inherited diseases in genome-wide association studies, in most cases only a relatively small proportion of the trait heritability is explained and biological mechanisms underpinning these traits have not been clearly identified. Expression quantitative trait loci (eQTL) are subsets of genomic loci shown experimentally to influence gene expression. Since gene expression is one of the primary determinants of phenotype, the identification of eQTL may reveal biologically relevant loci and provide functional links between genomic variants, gene expression and ultimately phenotype. Skeletal muscle (gluteus medius) gene expression was quantified by RNA-seq for 111 Thoroughbreds (47 male, 64 female) in race training at a single training establishment sampled at two time-points: at rest (n = 92) and four hours after high-intensity exercise (n = 77); n = 60 were sampled at both time points. Genotypes were generated from the Illumina Equine SNP70 BeadChip. Applying a Benjamini-Hochberg corrected P-value threshold (PFDR < 0.05), association tests identified 3,583 cis-eQTL associated with expression of 1,456 genes at rest; 4,992 cis-eQTL associated with the expression of 1,922 genes post-exercise; 1,703 trans-eQTL associated with 563 genes at rest; and 1,219 trans-eQTL associated with 425 genes post-exercise. The gene with the highest cis-eQTL association at both time-points was the endosome-associated-trafficking regulator 1 gene (ENTR1; Rest: PFDR = 3.81 × 10−27, Post-exercise: PFDR = 1.66 × 10−24), which has a potential role in the transcriptional regulation of the solute carrier family 2 member 1 glucose transporter protein (SLC2A1). Functional analysis of genes with significant eQTL revealed significant enrichment for cofactor metabolic processes. These results suggest heritable variation in genomic elements such as regulatory sequences (e.g. gene promoters, enhancers, silencers), microRNA and transcription factor genes, which are associated with metabolic function and may have roles in determining end-point muscle and athletic performance phenotypes in Thoroughbred horses.

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Transcriptional Regulatory Mechanisms in Adipose and Muscle Tissue Associated with Composite Glucometabolic Phenotypes

Cited by 5 publications

References 34 publications

Integrative Analysis of Glucometabolic Traits, Adipose Tissue DNA Methylation, and Gene Expression Identifies Epigenetic Regulatory Mechanisms of Insulin Resistance and Obesity in African Americans

Integrative Analysis of Glucometabolic Traits, Adipose Tissue DNA Methylation, and Gene Expression Identifies Epigenetic Regulatory Mechanisms of Insulin Resistance and Obesity in African Americans

Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome

Identification of expression quantitative trait loci in the skeletal muscle of Thoroughbreds reveals heritable variation in expression of genes relevant to cofactor metabolism

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