Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

Short-term step reduction reduces citrate synthase activity without altering skeletal muscle markers of oxidative metabolism or insulin-mediated signaling in young males

Mitochondria are critical to skeletal muscle contractile function and metabolic health. Short-term periods of step reduction (SR) are associated with alterations in muscle protein turnover and mass. However, the effects of SR on mitochondrial metabolism/muscle oxidative metabolism and insulin-mediated signaling are unclear. We tested the hypothesis that the total and/or phosphorylated protein content of key skeletal muscle markers of mitochondrial/oxidative metabolism, and insulin-mediated signaling would be altered over 7 days of SR in young healthy males. Eleven, healthy, recreationally active males (means ± SE, age: 22 ± 1 yr, BMI: 23.4 ± 0.7 kg·m(2)) underwent a 7-day period of SR. Immediately before and following SR, fasted-state muscle biopsy samples were acquired and analyzed for the assessment of total and phosphorylated protein content of key markers of mitochondrial/oxidative metabolism and insulin-mediated signaling. Daily step count was significantly reduced during the SR intervention (13,054 ± 833 to 1,192 ± 99 steps·day(−1), P 0.05). These results suggest that short-term SR reduces the maximal activity of citrate synthase, a marker of mitochondrial content, without altering the total or phosphorylated protein content of key markers of skeletal muscle mitochondrial metabolism and insulin signaling in young healthy males. NEW & NOTEWORTHY Short-term (7 day) step reduction reduces the activity of citrate synthase without altering the total or phosphorylated protein content of key markers of skeletal muscle mitochondrial metabolism and insulin signaling in young healthy males

Oxidation of independent and combined ingested galactose and glucose during exercise

Coingestion of glucose and galactose has been shown to enhance splanchnic extraction and metabolism of ingested galactose at rest; effects during exercise are unknown. This study examined whether combined ingestion of galactose and glucose during exercise enhances exogenous galactose oxidation. Fourteen endurance-trained male and female participants [age, 27 (5) yr; V̇o(2peak), 58.1 (7.0) mL·kg(−1)·min(−1)] performed cycle ergometry for 150 min at 50% peak power on four occasions, in a randomized counterbalanced manner. During exercise, they ingested beverages providing carbohydrates at rates of 0.4 g.min(−1) galactose (GAL), 0.8 g.min(−1) glucose (GLU), and on two occasions 0.8 g.min(−1) total galactose-glucose (GAL + GLU; 1:1 ratio). Single-monosaccharide (13)C-labeling (*) was used to calculate independent (GAL, GLU, GAL* + GLU, and GAL + GLU*) and combined (GAL* + GLU*, COMBINE) exogenous-monosaccharide oxidation between exercise. Plasma galactose concentrations with GAL + GLU [0.4 mmol.L; 95% confidence limits (CL): 0.1, 0.6] were lower (contrast: 0.5 mmol.L; 95% CL: 0.2, 0.8; P < 0.0001) than when GAL alone (0.9 mmol.L; 95% CL: 0.7, 1.2) was ingested. Exogenous carbohydrate oxidation with GAL alone (0.31 g·min(−1); 95% CL: 0.28, 0.35) was marginally reduced (contrast: 0.05 g·min(−1); 95% CL: −0.09, 0.00007; P = 0.01) when combined with glucose (GAL* + GLU 0.27 g·min(−1); 0.24, 0.30). Total combined exogenous-carbohydrate oxidation (COMBINE: 0.57 g·min(−1); 95% CL: 0.49, 0.64) was similar (contrast: 0.02 g·min(−1); 95% CL: −0.05, 0.09; P = 0.63) when compared with isoenergetic GLU (0.55 g·min(−1); 95% CL: 0.52, 0.58). In conclusion, coingestion of glucose and galactose did not enhance exogenous galactose oxidation during exercise. When combined, isoenergetic galactose-glucose ingestion elicited similar exogenous-carbohydrate oxidation to glucose suggesting galactose-glucose blends are a valid alternative for glucose as an exogenous-carbohydrate source during exercise. NEW & NOTEWORTHY Glucose and galactose coingestion blunted the galactosemia seen with galactose-only ingestion during exercise. Glucose and galactose coingestion did not enhance the oxidation of ingested galactose during exercise. Combined galactose-glucose (1:1 ratio) ingestion was oxidized to a similar extent as isoenergetic glucose-only ingestion during exercise. Galactose-glucose blends are a viable exogenous carbohydrate energy source for ingestion during exercise

Post-exercise muscle glycogen synthesis with glucose, galactose and combined galactose-glucose ingestion

Ingested galactose can enhance post-exercise liver glycogen repletion when combined with glucose but effects on muscle glycogen synthesis are unknown. In this double-blind randomised study participants (7 men, 2 women; VO2max: 51.1 (8.7) ml·kg-1·min-1) completed 3 trials of exhaustive cycling exercise followed by a 4-h recovery period, during which carbohydrates were ingested at the rate of 1.2 g·kg-1·h-1 comprising glucose (GLU), galactose (GAL) or galactose+glucose (GAL+GLU; 1:2 ratio). The increase in vastus lateralis skeletal-muscle glycogen concentration during recovery was higher with GLU relative to GAL+GLU (contrast: +50 mmol∙(kg DM)-1; 95%CL 10, 89; p=0.021) and GAL (+46 mmol∙(kg DM)-1; 95%CL 8, 84; p=0.024) with no difference between GAL+GLU and GAL (-3 mmol∙(kg DM)-1; 95%CL -44, 37; p=0.843). Plasma glucose concentration with GLU was not significantly different vs GAL+GLU (+0.41 mmol∙L-1; 95%CL -0.13, 0.94) but was significantly lower in GAL (-1.16 mmol∙L-1; 95%CL -0.53, -1.80) and lower in GAL vs GLU (-0.75 mmol∙L-1; 95%CL -1.34, 0.17). Plasma insulin was higher in GLU+GAL and GLU compared to GAL but not different between GLU+GAL and GLU. Plasma galactose concentration was higher in GAL compared to GLU (3.35 mmol∙L-1; 95%CL 3.07, 3.63) and GAL+GLU (3.22 mmol∙L-1; 95%CL 3.54, 2.90) with no difference between GLU+GAL (0.13 mmol∙L-1; 95%CL -0.11, 0.37) and GLU. Compared to galactose or a galactose+glucose blend, glucose feeding was more effective in post-exercise muscle glycogen synthesis. Comparable muscle glycogen synthesis was observed with galactose-glucose co-ingestion and exclusive galactose-only ingestion

Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease

Academi

Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.[Display omitted]•29% of lncRNA genes with eQTLs show tissue-specific genetic regulation•Co-expression networks and single-cell data provide annotations for 94% of lncRNAs•Rare variants near lncRNA expression outliers impact complex traits, like BMI•We identify 800 lncRNA-trait relationships not explained by protein-coding genesA systematic analysis of NIH Genotype Tissue Expression (GTEx) project data provides insights into lncRNA expression patterns and functions, explores the impact of genetic variation on lncRNAs, and connects lncRNAs to complex traits and human disease

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.Y