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524 results on '"Pravenec, M."'

4. Conplastic strains for identification of retrograde effects of mitochondrial dna variation on cardiometabolic traits in the spontaneously hypertensive rat

Author

Pravenec, M, primary, Šilhavý, J, additional, Mlejnek, P, additional, Šimáková, M, additional, Mráček, T, additional, Pecinová, A, additional, Tauchmannová, K, additional, Hütl, M, additional, Malínská, H, additional, Kazdová, L, additional, Neckář, J, additional, Kolář, F, additional, Žurmanová, J, additional, Novotný, J, additional, and Houštěk, J, additional

Published
2021
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6. High Cysteine Diet Reduces Insulin Resistance in SHR-CRP Rats

Author

KRIJT, J, primary, SOKOLOVÁ, J, additional, ŠILHAVÝ, J, additional, MLEJNEK, P, additional, KUBOVČIAK, J, additional, LIŠKA, F, additional, MALÍNSKÁ, H, additional, HÜTTL, M, additional, MARKOVÁ, I, additional, KŘÍŽKOVÁ, M, additional, STIPANUK, M, additional, KŘÍŽEK, T, additional, DITROI, T, additional, NAGY, P, additional, KOŽICH, V, additional, and PRAVENEC, M, additional

Published
2021
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28. Dissecting the Role of Folr1 and Folh1 Genes in the Pathogenesis of Metabolic Syndrome in Spontaneously Hypertensive Rats

Author

ŠILHAVÝ, J., primary, KRIJT, J., additional, SOKOLOVÁ, J., additional, ZÍDEK, V., additional, MLEJNEK, P., additional, ŠIMÁKOVÁ, M., additional, ŠKOP, V., additional, TRNOVSKÁ, J., additional, OLIYARNYK, O., additional, MARKOVÁ, I., additional, HÜTTL, M., additional, MALÍNSKÁ, H., additional, KAZDOVÁ, L., additional, LIŠKA, F., additional, KOŽICH, V., additional, and PRAVENEC, M., additional

Published
2018
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33. Mutant Wars2 Gene in Spontaneously Hypertensive Rats Impairs Brown Adipose Tissue Function and Predisposes to Visceral Obesity

Author

PRAVENEC, M., primary, ZÍDEK, V., additional, LANDA, V., additional, MLEJNEK, P., additional, ŠILHAVÝ, J., additional, ŠIMÁKOVÁ, M., additional, TRNOVSKÁ, J., additional, ŠKOP, V., additional, MARKOVÁ, I., additional, MALÍNSKÁ, H., additional, HÜTTL, M., additional, KAZDOVÁ, L., additional, BARDOVÁ, K., additional, TAUCHMANNOVÁ, K., additional, VRBACKÝ, M., additional, NŮSKOVÁ, H., additional, MRÁČEK, T., additional, KOPECKÝ, J., additional, and HOUŠTĚK, J., additional

Published
2017
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39. histoneHMM: Differential analysis of histone modifications with broad genomic footprints

Author

Heinig, M., Colomé-Tatché, M., Taudt, A., Rintisch, C., Schafer, S., Pravenec, M., Hubner, N., Vingron, M., Johannes, F., Stem Cell Aging Leukemia and Lymphoma (SALL), and Bioinformatics

Subjects
Cardiovascular and Metabolic Diseases, Biochemistry, Molecular Biology, Computer Science Applications
Abstract

Background: ChIP-seq has become a routine method for interrogating the genome-wide distribution of various histone modifications. An important experimental goal is to compare the ChIP-seq profiles between an experimental sample and a reference sample, and to identify regions that show differential enrichment. However, comparative analysis of samples remains challenging for histone modifications with broad domains, such as heterochromatin-associated H3K27me3, as most ChIP-seq algorithms are designed to detect well defined peak-like features. Results: To address this limitation we introduce histoneHMM, a powerful bivariate Hidden Markov Model for the differential analysis of histone modifications with broad genomic footprints. histoneHMM aggregates short-reads over larger regions and takes the resulting bivariate read counts as inputs for an unsupervised classification procedure, requiring no further tuning parameters. histoneHMM outputs probabilistic classifications of genomic regions as being either modified in both samples, unmodified in both samples or differentially modified between samples. We extensively tested histoneHMM in the context of two broad repressive marks, H3K27me3 and H3K9me3, and evaluated region calls with follow up qPCR as well as RNA-seq data. Our results show that histoneHMM outperforms competing methods in detecting functionally relevant differentially modified regions. Conclusion: histoneHMM is a fast algorithm written in C++ and compiled as an R package. It runs in the popular R computing environment and thus seamlessly integrates with the extensive bioinformatic tool sets available through Bioconductor. This makes histoneHMM an attractive choice for the differential analysis of ChIP-seq data. Software is available from http://histonehmm.molgen.mpg.de webcite.

Published
2015

44. Gender-Related Effects on Substrate Utilization and Metabolic Adaptation in Hairless Spontaneously Hypertensive Rat

Author

TRNOVSKÁ, J., primary, ŠILHAVÝ, J., additional, ZÍDEK, V., additional, ŠIMÁKOVÁ, M., additional, MLEJNEK, P., additional, LANDA, V., additional, EIGNER, S., additional, EIGNER HENKE, K., additional, ŠKOP, V., additional, OLIYARNYK, O., additional, KAZDOVÁ, L., additional, MRÁČEK, T., additional, HOUŠTĚK, J., additional, and PRAVENEC, M., additional

Published
2015
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45. Genetical genomic determinants of alcohol consumption in rats and humans

Author

Tabakoff, B., Saba, L., Printz, M., Flodman, P., Hodgkinson, C., Goldman, D., Koob, G., Richardson, H.N., Kechris, K., Bell, R.L., Huebner, N., Heinig, M., Pravenec, M., Mangion, J., Legault, L., Dongier, M., Conigrave, K.M., Whitfield, J.B., Saunders, J., Grant, B., and Hoffman, P.L.

Subjects
Cardiovascular and Metabolic Diseases
Abstract

BACKGROUND: We have used a genetical genomic approach, in conjunction with phenotypic analysis of alcohol consumption, to identify candidate genes that predispose to varying levels of alcohol intake by HXB/BXH recombinant inbred rat strains. In addition, in two populations of humans, we assessed genetic polymorphisms associated with alcohol consumption using a custom genotyping array for 1,350 single nucleotide polymorphisms (SNPs). Our goal was to ascertain whether our approach, which relies on statistical and informatics techniques, and non-human animal models of alcohol drinking behavior, could inform interpretation of genetic association studies with human populations. RESULTS: In the HXB/BXH recombinant inbred (RI) rats, correlation analysis of brain gene expression levels with alcohol consumption in a two-bottle choice paradigm, and filtering based on behavioral and gene expression quantitative trait locus (QTL) analyses, generated a list of candidate genes. A literature-based, functional analysis of the interactions of the products of these candidate genes defined pathways linked to presynaptic GABA release, activation of dopamine neurons, and postsynaptic GABA receptor trafficking, in brain regions including the hypothalamus, ventral tegmentum and amygdala. The analysis also implicated energy metabolism and caloric intake control as potential influences on alcohol consumption by the recombinant inbred rats. In the human populations, polymorphisms in genes associated with GABA synthesis and GABA receptors, as well as genes related to dopaminergic transmission, were associated with alcohol consumption. CONCLUSIONS: Our results emphasize the importance of the signaling pathways identified using the non-human animal models, rather than single gene products, in identifying factors responsible for complex traits such as alcohol consumption. The results suggest cross-species similarities in pathways that influence predisposition to consume alcohol by rats and humans. The importance of a well-defined phenotype is also illustrated. Our results also suggest that different genetic factors predispose alcohol dependence versus the phenotype of alcohol consumption.

Published
2009

50. Genetic basis of transcriptome differences between the founder strains of the rat HXB/BXH recombinant inbred panel

Author

Simonis, M., Atanur, S.S., Linsen, S., Guryev, V., Ruzius, F.P., Game, L., Lansu, N., de Bruijn, E., van Heesch, S., Jones, S.J., Pravenec, M., Aitman, T.J., Cuppen, E., Simonis, M., Atanur, S.S., Linsen, S., Guryev, V., Ruzius, F.P., Game, L., Lansu, N., de Bruijn, E., van Heesch, S., Jones, S.J., Pravenec, M., Aitman, T.J., and Cuppen, E.

Abstract

BACKGROUND: With the advent of next generation sequencing it has become possible to detect genomic variation on a large scale. However, predicting which genomic variants are damaging to gene function remains a challenge, as knowledge of the effects of genomic variation on gene expression is still limited. Recombinant inbred panels are powerful tools to study the cis and trans effects of genetic variation on molecular phenotypes such as gene expression. RESULTS: We generated a comprehensive inventory of genomic differences between the two founder strains of the rat HXB/BXH recombinant inbred panel: SHR/OlaIpcv and BN-Lx/Cub. We identified 3.2 million single nucleotide variants, 425,924 small insertions and deletions, 907 copy number changes and 1,094 large structural genetic variants. RNA-sequencing analyses on liver tissue of the two strains identified 532 differentially expressed genes and 40 alterations in transcript structure. We identified both coding and non-coding variants that correlate with differential expression and alternative splicing. Furthermore, structural variants, in particular gene duplications, show a strong correlation with transcriptome alterations. CONCLUSIONS: We show that the panel is a good model for assessing the genetic basis of phenotypic heterogeneity and for providing insights into possible underlying molecular mechanisms. Our results reveal a high diversity and complexity underlying quantitative and qualitative transcriptional differences., BACKGROUND: With the advent of next generation sequencing it has become possible to detect genomic variation on a large scale. However, predicting which genomic variants are damaging to gene function remains a challenge, as knowledge of the effects of genomic variation on gene expression is still limited. Recombinant inbred panels are powerful tools to study the cis and trans effects of genetic variation on molecular phenotypes such as gene expression. RESULTS: We generated a comprehensive inventory of genomic differences between the two founder strains of the rat HXB/BXH recombinant inbred panel: SHR/OlaIpcv and BN-Lx/Cub. We identified 3.2 million single nucleotide variants, 425,924 small insertions and deletions, 907 copy number changes and 1,094 large structural genetic variants. RNA-sequencing analyses on liver tissue of the two strains identified 532 differentially expressed genes and 40 alterations in transcript structure. We identified both coding and non-coding variants that correlate with differential expression and alternative splicing. Furthermore, structural variants, in particular gene duplications, show a strong correlation with transcriptome alterations. CONCLUSIONS: We show that the panel is a good model for assessing the genetic basis of phenotypic heterogeneity and for providing insights into possible underlying molecular mechanisms. Our results reveal a high diversity and complexity underlying quantitative and qualitative transcriptional differences.

Published
2012

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