qgg: an R package for large-scale quantitative genetic analyses

Rohde, Palle Duun; Sørensen, Izel Fourie; Sørensen, Peter

doi:10.1093/bioinformatics/btz955

Cited by 41 publications

(53 citation statements)

References 11 publications

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“…We predicted the consequences of alternative alleles within the full-length transcript for PTPRG (ENST00000474889.6) using the Ensembl Variant Effect Predictor (VEP) ( McLaren et al, 2016 ); and included in our analyses, the 334 missense variants localized outside exon-intron boundary regions and 75 variants with predicted loss-of-function. Carriers of the identified variants were extracted using the R-package qgg ( Rohde et al, 2020 ). The identified loss-of-function variants included 36 with low (intronic splice region variants, synonymous splice region variants), 17 with moderate (in-frame insertions, in-frame deletions, missense splice region variants), and 22 with high (splice acceptor variants, splice donor variants, stop-gain variants, frameshift variants) predicted impact.…”

Section: Methodsmentioning

confidence: 99%

PTPRG is an ischemia risk locus essential for HCO3–-dependent regulation of endothelial function and tissue perfusion

Hansen

Staehr

Rohde

et al. 2020

eLife

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Acid-base conditions modify artery tone and tissue perfusion but the involved vascular sensing mechanisms and disease consequences remain unclear. We experimentally investigated transgenic mice and performed genetic studies in a UK-based human cohort. We show that endothelial cells express the putative HCO3–-sensor receptor-type tyrosine-protein phosphatase RPTPg, which enhances endothelial intracellular Ca2+-responses in resistance arteries and facilitates endothelium-dependent vasorelaxation only when CO2/HCO3– is present. Consistent with waning RPTPg-dependent vasorelaxation at low [HCO3–], RPTPg limits increases in cerebral perfusion during neuronal activity and augments decreases in cerebral perfusion during hyperventilation. RPTPg does not influence resting blood pressure but amplifies hyperventilation-induced blood pressure elevations. Loss-of-function variants in PTPRG, encoding RPTPg, are associated with increased risk of cerebral infarction, heart attack, and reduced cardiac ejection fraction. We conclude that PTPRG is an ischemia susceptibility locus; and RPTPg-dependent sensing of HCO3– adjusts endothelium-mediated vasorelaxation, microvascular perfusion, and blood pressure during acid-base disturbances and altered tissue metabolism.

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Section: Methodsmentioning

confidence: 99%

PTPRG is an ischemia risk locus essential for HCO3–-dependent regulation of endothelial function and tissue perfusion

Hansen

Staehr

Rohde

et al. 2020

eLife

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“…Detailed procedures were presented in [26]. We applied a sum-based marker-set test approach, implemented in the QGG package [78], to determine whether GWAS signals were enriched in tissue-specific histone marks. This approach employed a 10,000-time circular genotype permutation procedure and showed a better or at least equal performance compared to most of commonly used marker-set test methods in livestock [79][80][81][82], fruit fly [83], and human [84].…”

Section: Gwas Enrichment Analysis Based On Tissue-specific Histone Marksmentioning

confidence: 99%

Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Liu

Zhang

et al. 2020

BMC Biol

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Background: Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle. Results: We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cellspecific gene, was significantly associated with both allergic diseases in human and metritis in cattle.

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“…mQTLs for mean NMR intensity was identified using linear regression, 30 using the function for single marker association analysis implemented in the qgg package. 29 The estimated genetic effects (N, from equation 1) was used as line means, since these values represents the within DGRP line mean intensity of a single NMR feature adjusted for Wolbachia, chromosomal inversions, and polygenicity, which then was regressed on marker genotypes.…”

Section: Mapping Of Metabolome Qtlmentioning

confidence: 99%

Prediction of complex phenotypes using theDrosophilametabolome

Rohde

Kristensen

Sarup

et al. 2020

Preprint

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Understanding the genotype -phenotype map and how variation at different levels of biological organization are associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins, metabolites. This facilitates our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We do this by performing NMR metabolomics on four replicate pools of male flies from each of 170 isogenic lines. We show first that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, we show that for four of five traits related to behaviour and stress resistance the metabolome predicts phenotypes more accurately than genomic data, and that the metabolites driving the increased accuracy was trait specific. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding has strong applied importance e.g. in human medicine and animal and plant breeding.1 is a design matrix linking the genomic ( 1 ) and metabolomic ( 1 ) effects to the phenotypes. The random genomic effects are 1~( , [1,1] ! " ), and the metabolomic effects are 1~( , [1,1] 5 " ), where is the additive genomic relationship matrix as specified previously, and is the metabolomic relationship matrix.The metabolomic relationship matrix was computed as = ′ NMR ⁄ , where is a × NMR matrix of *77 18* T 6 , N 6 ), and was compared (using paired t-test corrected for multiple testing by a false discovery rate (FDR) of <0.05) within and across 9/ clusters to identify the NMR features resulting in the largest prediction accuracy. We only considered Drosophila melanogaster Genetic Reference Panel lines.

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qgg: an R package for large-scale quantitative genetic analyses

Cited by 41 publications

References 11 publications

PTPRG is an ischemia risk locus essential for HCO3–-dependent regulation of endothelial function and tissue perfusion

PTPRG is an ischemia risk locus essential for HCO3–-dependent regulation of endothelial function and tissue perfusion

Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Prediction of complex phenotypes using theDrosophilametabolome

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