Biology subjects

Arends, D.

Publications and source records attributed to Arends, D..

6 recordsLinked to original sources

bioRxiv2025

Genetic Modulation of Lifespan: Dynamic Effects, Sex Differences, and Body Weight Trade-offs

The dynamics of lifespan are shaped by DNA variants that exert effects at different ages. We have mapped genetic loci that modulate age-specific mortality using an actuarial approach. We started with an initial population of 6,438 pubescent siblings and ended with a survivorship of 559 mice that lived to at least 1100 days. Twenty-nine Vita loci dynamically modulate the mean lifespan of survivorships with strong age- and sex-specific effects. Fourteen have relatively steady effects on mortality while other loci act forcefully only early or late in life and with polarities of effects that invert. A distinct set of 19 Soma loci shape the negative correlation between weights of young adults with their life expectancies--much more strongly so in males than females. Another set of 11 Soma loci shape the positive correlation between weights at older ages with life expectancies. The Vita and Soma loci share 289 age-dependent epistatic interactions (LODs [≥]3.8) but fewer than 4% are common to both sexes. We provide two examples of how to move from maps toward potential mechanisms. Our findings provide an empirical bridge between evolutionary theories on aging and genetic and molecular causes. These loci and their interactions are key to begin to understand the impact of interventions that may extend healthy lifespan in mice and even in humans.

genetics↗

bioRxiv2022

LMM-MQM time series mapping - An application in a murine advanced intercross line identifies novel growth QTLs

The Berlin Fat Mouse Inbred line 860 (BFMI860) is a mouse model for juvenile obesity. Previously, a recessive major effect locus (jObes1) was identified on chromosome 3 explaining around 26% of the body weight variance in an BFMI860xC57BL/6NCrl advanced intercross line. The aim of this study was to discover additional QTL. Time series body weight data were modeled using linear mixed models (LMM), while a multiple QTL mapping (MQM) approach compensated for the jObes1 locus effect. LMM-MQM identified five additional loci significantly associated with body weight. Variance explained by the jObes1 locus increased to 38.1% when using LMM-MQM mapping, while the additional loci explained between 2.0% and 3.9% of the body weight variance. Several positional candidate genes within the novel QTL regions were found in KEGG pathways for insulin signaling and insulin resistance. Strong distortion with preference for the BFMI allele was observed within a newly identified QTL containing the well-known Foxo1 regulator of adipocyte differentiation. Here, we present a novel method for QTL detection in time series data: LMM-MQM time series mapping. We show that our method is more powerful in detecting QTLs compared to single timepoint mapping approaches. Thus, the time series structure should be considered for optimal detection of small effect QTLs. LMM-MQM time series mapping can be used to find genetic determinants of all kind of "phenotypes over time" be it lactation curves in cattle, plant biomass, drug clearance in human clinical trials, or cognitive decline during disease.

genetics↗

bioRxiv2021

Transmission distortion and genetic incompatibilities between alleles in a multigenerational mouse advanced intercross line

Background/ObjectivesWhile direct additive and dominance effects on complex traits have been mapped repeatedly, additional genetic factors contributing to the heterogeneity of complex traits have been scarcely investigated. To assess genetic background effects, we investigated transmission ratio distortions (TRDs) of alleles from parent to offspring using an advanced intercross line (AIL) of an initial cross between the mouse inbred strains C57BL/6NCrl (B6N) and BFMI860-12 (BFMI). Subjects/Methods341 males of generation 28 and their respective 61 parents and 66 grandparents were genotyped using Mega Mouse Universal Genotyping Arrays (MegaMUGA). TRDs were investigated using allele transmission asymmetry tests, and pathway overrepresentation analysis was performed. Sequencing data was used to test for overrepresentation of non-synonymous SNPs in TRD regions. Genetic incompatibilities were tested using the Bateson-Dobzhansky-Muller two-locus model. Results62 TRD regions were detected, many in close proximity to the telocentric centromere. TRD regions contained 44.5% more non-synonymous SNPs than randomly selected regions (182 vs. 125.9 {+/-} 17.0, P < 1x10-4). Testing for genetic incompatibilities between TRD regions identified 29 genome-wide significant incompatibilities between TRD regions (P(BF) < 0.05). Pathway overrepresentation analysis of genes in TRD regions showed that DNA methylation, epigenetic regulation of RNA, and meiotic/meiosis regulation pathways were affected independent of the parental origin of the TRD. Paternal BFMI TRD regions showed overrepresentation in the small interfering RNA (siRNA) biogenesis and in the metabolism of lipids and lipoproteins. Maternal B6N TRD regions harbored genes involved in meiotic recombination, cell death, and apoptosis pathways. The analysis of genes in TRD regions suggests the potential distortion of protein-protein interactions influencing obesity and diabetic retinopathy as a result of disadvantageous combinations of allelic variants in Aass, Pgx6 and Nme8. ConclusionsUsing an AIL significantly improves the resolution at which we can investigate TRD. Our analysis implicates distortion of protein-protein interactions as well as meiotic drive as the underlying mechanisms leading to the observed TRD in our AIL. Furthermore, genes with large amounts of non-synonymous SNPs located in TRD regions are more likely to be involved in pathways that are related to the phenotypic differences between the parental strains. Genes in these TRD regions provide new targets for investigating genetic adaptation, protein-protein interactions, and determinants of complex traits such as obesity.

genetics↗

bioRxiv2019

Molecular Basis for G-protein-Coupled Receptor (GPCR) Activation and Biased Signalling at the Platelet Thrombin Receptor Proteinase Activated Receptor-4 (PAR4)

Proteinase Activated Receptor-4 (PAR4) is a member of the proteolytically-activated PAR family of G-Protein-coupled Receptors (GPCRs). PARs are activated following proteolytic cleavage of the receptor N-terminus by enzymes such as thrombin, trypsin, and cathepsin-G to reveal the receptor-activating motif termed the tethered ligand. The tethered ligand binds intramolecularly to the receptor and triggers receptor signalling and cellular responses. In spite of this unusual mechanism of activation, PARs are fundamentally peptide receptors and can also be activated by exogenous application of short synthetic peptides derived from the tethered ligand sequence. In order to gain a better understanding of the molecular basis for PAR4-dependent signalling, we examined signalling responses to a library of peptides derived from the canonical PAR4 activating peptide (PAR4-AP), AYPGKF-NH2. We examined peptide residues involved in activation of the Gq/11-coupled calcium signalling pathway, {beta}-arrestin recruitment, and mitogen-activated protein kinase pathway activation. The peptide N-methyl-alanine-YPGKF-NH2 was identified as a compound that is a poor activator of PAR4-dependent calcium signalling but was fully competent in recruiting {beta}-arrestin-1 and -2. In order to gain a better understanding of the ligand-binding pocket, we used in silico docking to identify key residues involved in PAR4 interaction with AYPGKF-NH2. The predicted interactions were verified by site-directed mutagenesis and analysis of calcium signalling and {beta}-arrestin-1/-2 recruitment following proteolytic activation (with thrombin) or activation with the synthetic agonist peptide (AYPGKF-NH2). We determined that a key extracellular loop-2 aspartic acid residue (Asp230) is critical for signalling following both proteolytic and peptide activation of PAR4. Finally, we investigated platelet aggregation in response to AyPGKF-NH2 (a peptide with D-tyrosine in position two) which is unable to activate calcium signalling, and AYPGRF-NH2 a peptide that is equipotent to the parental peptide AYPGKF-NH2 for calcium signalling but is more potent at recruiting {beta}-arrestins. We found that AyPGKF-NH2 fails to activate platelets while AYPGRF-NH2 causes a platelet aggregation response that is greater than that seen with the parental peptide and is comparable to that seen with thrombin stimulation. Overall, these studies uncover molecular determinants for agonist binding and signalling through a non-canonically activated GPCR and provide a template for development of small molecule modulators of PAR4.

pharmacology and toxicology↗

bioRxiv2019

The expanded BXD family of mice: A cohort for experimental systems genetics and precision medicine

The challenge of precision medicine is to model complex interactions among DNA variants, sets of phenotypes, and complex environmental factors and confounders. We have expanded the BXD family, creating a powerful and extensible test bed for experimental precision medicine and an ideal cohort to study gene-by-environmental interactions.\n\nThese BXD segregate for over 6 million variants, with a mean minor allele frequency close to 0.5. We have increased the family two-fold to 150 inbred strains, all derived from C57BL/6J and DBA/2J. We have also generated updated and comprehensive genotypes and an unrivaled deep phenome.\n\nApproximately 10,000 recombinations have been located, allowing precision of quantitative trait loci mapping of {+/-}2.0 Mb over much of the genome and {+/-}0.5 Mb for Mendelian loci. The BXD phenome includes more than 100 omics data sets and >7000 quantitative and clinical phenotypes, all of which is publicly available.\n\nThe BXD family is an enduring, collaborative, and replicable resource to test causal and mechanistic links between genomes and phenomes at many stages and under a wide variety of treatments and interventions.

genomics↗

bioRxiv2019

Genetic dissection of femoral and tibial microarchitecture

Our understanding of the genetic control of bone has relied almost exclusively on estimates of bone mineral density. In contrast, here we have used high-resolution x-ray tomography (8 m isotropic voxels) to measure femoral and tibial components across a set of ~600 mice belonging to 60 diverse BXD strains of mice. We computed heritabilities of 25 cortical and trabecular compartments. Males and females have well matched trait heritabilities, ranging from 0.25 to 0.75. We mapped 16 QTLs that collectively cover ~8% of all protein-coding genes in mouse. A majority of loci are detected only in females, and there is also a bias in favor of QTLs for cortical traits. To efficiently evaluate candidate genes we developed a method that couples gene ontologies with expression data to compute bone-enrichment scores for almost all protein-coding genes. We carefully collated and aligned murine candidates with recent human BMD genome-wide association results. We highlight a subset of 50 strong candidates that fall into three categories: 1. those linked to bone function that have already been experimentally validated (Adamts4, Ddr2, Darc, Adam12, Fkbp10, E2f6, Adam17, Grem2, Ifi204); 2. candidates with putative bone function but not yet tested (e.g., Greb1, Ifi202b) but several of which have been linked to phenotypes in humans; and 3. candidates that have high bone-enrichment scores but for which there is not yet any specific link to bone biology or skeletal disease, including Ifi202b, Ly9, Ifi205, Mgmt, F2rl1, Iqgap2. Our results highlight contrasting genetic architecture between the sexes and among major bone compartments. The joint use and alignment of murine and human data should greatly facilitate function analysis and preclinical testing.\n\nDisclosureThe authors declare that no competing interests exist.

genetics↗