Dataset Information

Systems biology with high-throughput sequencing reveals genetic mechanisms underlying the metabolic syndrome in the Lyon hypertensive rat.

ABSTRACT:

Background

The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon hypertensive and Lyon normotensive rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, an F2 intercross between Lyon hypertensive and Lyon normotensive was comprehensively studied.

Methods and results

Multidimensional data were obtained including genotypes of 1536 single-nucleotide polymorphisms, 23 physiological traits, and >150 billion nucleotides of RNA-seq reads from the livers of F2 intercross offspring and parental rats. Phenotypic and expression quantitative trait loci (eQTL) were mapped. Application of systems biology methods identified 17 candidate MetS genes. Several putative causal cis-eQTL were identified corresponding with phenotypic QTL loci. We found an eQTL hotspot on rat chromosome 17 that is causally associated with multiple MetS-related traits and found RGD1562963, a gene regulated in cis by this eQTL hotspot, as the most likely eQTL driver gene directly affected by genetic variation between Lyon hypertensive and Lyon normotensive rats.

Conclusions

Our study sheds light on the intricate pathogenesis of MetS and demonstrates that systems biology with high-throughput sequencing is a powerful method to study the pathogenesis of complex genetic diseases.

SUBMITTER: Wang J

PROVIDER: S-EPMC4406788 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Publications

Systems biology with high-throughput sequencing reveals genetic mechanisms underlying the metabolic syndrome in the Lyon hypertensive rat.

Wang Jinkai J Ma Man Chun John MC Mennie Amanda K AK Pettus Janette M JM Xu Yang Y Lin Lan L Traxler Matthew G MG Jakoubek Jessica J Atanur Santosh S SS Aitman Timothy J TJ Xing Yi Y Kwitek Anne E AE

Circulation. Cardiovascular genetics 20150108 2

<h4>Background</h4>The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon hypertensive and Lyon normotensive rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, an F2 intercross between Lyon hypertensive and Lyon normotensive was comprehensively studied.<h4>Methods and results</h4>Multidimensional data were obtaine ...[more]

PMID: 25573024

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Project description:BackgroundThe metabolic syndrome (MetS), a complex disorder involving hypertension, obesity, dyslipidemia and insulin resistance, is a major risk factor for heart disease, stroke, and diabetes. The Lyon Hypertensive (LH), Lyon Normotensive (LN) and Lyon Low-pressure (LL) rats are inbred strains simultaneously derived from a common outbred Sprague Dawley colony by selection for high, normal, and low blood pressure, respectively. Further studies found that LH is a MetS susceptible strain, while LN is resistant and LL has an intermediate phenotype. Whole genome sequencing determined that, while the strains are phenotypically divergent, they are nearly 98% similar at the nucleotide level. Using the sequence of the three strains, we applied an approach that harnesses the distribution of Observed Strain Differences (OSD), or nucleotide diversity, to distinguish genomic regions of identity-by-descent (IBD) from those with divergent ancestry between the three strains. This information was then used to fine-map QTL identified in a cross between LH and LN rats in order to identify candidate genes causing the phenotypes.ResultsWe identified haplotypes that, in total, contain at least 95% of the identifiable polymorphisms between the Lyon strains that are likely of differing ancestral origin. By intersecting the identified haplotype blocks with Quantitative Trait Loci (QTL) previously identified in a cross between LH and LN strains, the candidate QTL regions have been narrowed by 78%. Because the genome sequence has been determined, we were further able to identify putative functional variants in genes that are candidates for causing the QTL.ConclusionsWhole genome sequence analysis between the LH, LN, and LL strains identified the haplotype structure of these three strains and identified candidate genes with sequence variants predicted to affect gene function. This approach, merged with additional integrative genetics approaches, will likely lead to novel mechanisms underlying complex disease and provide new drug targets and therapies.

Project description:BackgroundThe coronavirus disease 2019 (COVID-19), a pandemic contributing to more than 105 million cases and more than 2.3 million deaths worldwide, was described to be frequently accompanied by extrapulmonary manifestations, including liver dysfunction. Liver dysfunction and elevated liver enzymes were observed in about 53% of COVID-19 patients.AimTo gain insight into transcriptional abnormalities in liver tissue of severe COVID-19 patients that may result in liver dysfunction.MethodsThe transcriptome of liver autopsy samples from severe COVID-19 patients against those of non-COVID donors was analyzed. Differentially expressed genes were identified from normalized RNA-seq data and analyzed for the enrichment of functional clusters and pathways. The differentially expressed genes were then compared against the genetic signatures of liver diseases including cirrhosis, fibrosis, non-alcoholic fatty liver disease (NAFLD), and hepatitis A/B/C. Gene expression of some differentially expressed genes was assessed in the blood samples of severe COVID-19 patients with liver dysfunction using qRT-PCR.ResultsAnalysis of the differential transcriptome of the liver tissue of severe COVID-19 patients revealed a significant upregulation of transcripts implicated in tissue remodeling including G-coupled protein receptors family genes, DNAJB1, IGF2, EGFR, and HDGF. Concordantly, the differential transcriptome of severe COVID-19 liver tissues substantially overlapped with the disease signature of liver diseases characterized with pathological tissue remodeling (liver cirrhosis, Fibrosis, NAFLD, and hepatitis A/B/C). Moreover, we observed a significant suppression of transcripts implicated in metabolic pathways as well as mitochondrial function, including cytochrome P450 family members, ACAD11, CIDEB, GNMT, and GPAM. Consequently, drug and xenobiotics metabolism pathways are significantly suppressed suggesting a decrease in liver detoxification capacity. In correspondence with the RNA-seq data analysis, we observed a significant upregulation of DNAJB1 and HSP90AB1 as well as significant downregulation of CYP39A1 in the blood plasma of severe COVID-19 patients with liver dysfunction.ConclusionSevere COVID-19 patients appear to experience significant transcriptional shift that may ensue tissue remodeling, mitochondrial dysfunction and lower hepatic detoxification resulting in the clinically observed liver dysfunction.

Dataset Information

Systems biology with high-throughput sequencing reveals genetic mechanisms underlying the metabolic syndrome in the Lyon hypertensive rat.

Background

Methods and results

Conclusions

Publications

Systems biology with high-throughput sequencing reveals genetic mechanisms underlying the metabolic syndrome in the Lyon hypertensive rat.

Similar Datasets

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