In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although ...external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genomewide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.
Abstract
Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene ...identification and a strict focus on bone mineral density (BMD). Here, we use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes
SERTAD4
and
GLT8D2
. We also perform GWAS in the DO for a wide-range of bone traits and identify
Qsox1
as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.
Genetic mapping studies in the mouse and other model organisms are used to search for genes underlying complex phenotypes. Traditional genetic mapping studies that employ single-generation crosses ...have poor mapping resolution and limit discovery to loci that are polymorphic between the two parental strains. Multiparent outbreeding populations address these shortcomings by increasing the density of recombination events and introducing allelic variants from multiple founder strains. However, multiparent crosses present new analytical challenges and require specialized software to take full advantage of these benefits. Each animal in an outbreeding population is genetically unique and must be genotyped using a high-density marker set; regression models for mapping must accommodate multiple founder alleles, and complex breeding designs give rise to polygenic covariance among related animals that must be accounted for in mapping analysis. The Diversity Outbred (DO) mice combine the genetic diversity of eight founder strains in a multigenerational breeding design that has been maintained for >16 generations. The large population size and randomized mating ensure the long-term genetic stability of this population. We present a complete analytical pipeline for genetic mapping in DO mice, including algorithms for probabilistic reconstruction of founder haplotypes from genotyping array intensity data, and mapping methods that accommodate multiple founder haplotypes and account for relatedness among animals. Power analysis suggests that studies with as few as 200 DO mice can detect loci with large effects, but loci that account for <5% of trait variance may require a sample size of up to 1000 animals. The methods described here are implemented in the freely available R package DOQTL.
Dysregulation of the dopamine system is linked to various aberrant behaviors, including addiction, compulsive exercise, and hyperphagia leading to obesity. The goal of the present experiments was to ...determine how dopamine contributes to the expression of opposing phenotypes, excessive exercise and obesity. We hypothesized that similar alterations in dopamine and dopamine-related gene expression may underly obesity and excessive exercise, as competing traits for central reward pathways. Moreover, we hypothesized that selective breeding for high levels of exercise or obesity may have influenced genetic variation controlling these pathways, manifesting as opposing complex traits. Dopamine, dopamine-related peptide concentrations, and gene expression were evaluated in dorsal striatum (DS) and nucleus accumbens (NA) of mice from lines selectively bred for high rates of wheel running (HR) or obesity (M16), and the non-selected ICR strain from which these lines were derived. HPLC analysis showed significantly greater neurotransmitter concentrations in DS and NA of HR mice compared to M16 and ICR. Microarray analysis showed significant gene expression differences between HR and M16 compared to ICR in both brain areas, with changes revealed throughout the dopamine pathway including D1 and D2 receptors, associated G-proteins (e.g.,
Golf), and adenylate cyclase (e.g.,
Adcy5). The results suggest that similar modifications within the dopamine system may contribute to the expression of opposite phenotypes in mice, demonstrating that alterations within central reward pathways can contribute to both obesity and excessive exercise.
The biology of how faces are built and come to differ from one another is complex. Discovering normal variants that contribute to differences in facial morphology is one key to untangling this ...complexity, with important implications for medicine and evolutionary biology. This study maps quantitative trait loci (QTL) for skeletal facial shape using Diversity Outbred (DO) mice. The DO is a randomly outcrossed population with high heterozygosity that captures the allelic diversity of eight inbred mouse lines from three subspecies. The study uses a sample of 1147 DO animals (the largest sample yet employed for a shape QTL study in mouse), each characterized by 22 three-dimensional landmarks, 56,885 autosomal and X-chromosome markers, and sex and age classifiers. We identified 37 facial shape QTL across 20 shape principal components (PCs) using a mixed effects regression that accounts for kinship among observations. The QTL include some previously identified intervals as well as new regions that expand the list of potential targets for future experimental study. Three QTL characterized shape associations with size (allometry). Median support interval size was 3.5 Mb. Narrowing additional analysis to QTL for the five largest magnitude shape PCs, we found significant overrepresentation of genes with known roles in growth, skeletal and facial development, and sensory organ development. For most intervals, one or more of these genes lies within 0.25 Mb of the QTL's peak. QTL effect sizes were small, with none explaining more than 0.5% of facial shape variation. Thus, our results are consistent with a model of facial diversity that is influenced by key genes in skeletal and facial development and, simultaneously, is highly polygenic.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Department of Cell and Molecular Physiology, University of North Carolina, Chapel Hill, North Carolina
Substantial variability exists in collateral density and ischemia-induced collateral growth ...among species. To begin to probe the underlying mechanisms, which are unknown, we characterized two mouse strains with marked differences in both parameters. Immediately after femoral artery ligation, collateral and foot perfusion were lower in BALB/c than C57BL/6 ( P < 0.05 here and below), suggesting fewer pre-existing collaterals. This was confirmed with angiography and immunohistochemistry ( 35% fewer collaterals in the BALB/c's thigh). Recovery of hindlimb perfusion was attenuated in BALB/c, in association with 54% less collateral remodeling, reduced angiogenesis, greater ischemia, and more impaired hindlimb use. Densities of CD45 + and CD4 + leukocytes around collaterals increased similarly, but TNF- expression was 50% lower in BALB/c, which may contribute to reduced collateral remodeling. In normal tissues, compared with C57BL/6, BALB/c exhibit an altered arterial branching pattern and, like skeletal muscle above, have 30% fewer collaterals in intestine and, remarkably, almost none in pial circulation, resulting in greatly impaired perfusion after cerebral artery occlusion. Ischemic induction of VEGF-A was attenuated in BALB/c. Analysis of a C57BL/6 x BALB/c recombinant inbred strain dataset identified a quantitative trait locus for VEGF-A mRNA abundance at or near the Vegfa locus that associates with lower expression in BALB/c. This suggests a cis -acting polymorphism in the Vegfa gene in BALB/c could contribute to reduced VEGF-A expression and, in turn, the above deficiencies in this strain. These findings suggest these strains offer a model to investigate genetic determinants of collateral formation and growth in ischemia.
pre-existing collateral network; collateral development and arteriogenesis; cerebral circulation; vascular endothelial growth factor and mouse strains; expression quantitative trait loci
Previous genetic association studies of physical activity, in both animal and human models, have been limited in number of subjects and genetically homozygous strains used as well as number of ...genomic markers available for analysis. Expansion of the available mouse physical activity strain screens and the recently published dense single-nucleotide polymorphism (SNP) map of the mouse genome (approximately 8.3 million SNPs) and associated statistical methods allowed us to construct a more generalizable map of the quantitative trait loci (QTL) associated with physical activity. Specifically, we measured wheel running activity in male and female mice (average age 9 wk) in 41 inbred strains and used activity data from 38 of these strains in a haplotype association mapping analysis to determine QTL associated with activity. As seen previously, there was a large range of activity patterns among the strains, with the highest and lowest strains differing significantly in daily distance run (27.4-fold), duration of activity (23.6-fold), and speed (2.9-fold). On a daily basis, female mice ran further (24%), longer (13%), and faster (11%). Twelve QTL were identified, with three (on Chr. 12, 18, and 19) in both male and female mice, five specific to males, and four specific to females. Eight of the 12 QTL, including the 3 general QTL found for both sexes, fell into intergenic areas. The results of this study further support the findings of a moderate to high heritability of physical activity and add general genomic areas applicable to a large number of mouse strains that can be further mined for candidate genes associated with regulation of physical activity. Additionally, results suggest that potential genetic mechanisms arising from traditional noncoding regions of the genome may be involved in regulation of physical activity.
To understand the genetic architecture of complex traits and bridge the genotype-phenotype gap, it is useful to study intermediate -omics data, e.g. the transcriptome. The present study introduces a ...method for simultaneous quantification of the contributions from single nucleotide polymorphisms (SNPs) and transcript abundances in explaining phenotypic variance, using Bayesian whole-omics models. Bayesian mixed models and variable selection models were used and, based on parameter samples from the model posterior distributions, explained variances were further partitioned at the level of chromosomes and genome segments.
We analyzed three growth-related traits: Body Weight (BW), Feed Intake (FI), and Feed Efficiency (FE), in an F2 population of 440 mice. The genomic variation was covered by 1806 tag SNPs, and transcript abundances were available from 23,698 probes measured in the liver. Explained variances were computed for models using pedigree, SNPs, transcripts, and combinations of these. Comparison of these models showed that for BW, a large part of the variation explained by SNPs could be covered by the liver transcript abundances; this was less true for FI and FE. For BW, the main quantitative trait loci (QTLs) are found on chromosomes 1, 2, 9, 10, and 11, and the QTLs on 1, 9, and 10 appear to be expression Quantitative Trait Locus (eQTLs) affecting gene expression in the liver. Chromosome 9 is the case of an apparent eQTL, showing that genomic variance disappears, and that a tri-modal distribution of genomic values collapses, when gene expressions are added to the model.
With increased availability of various -omics data, integrative approaches are promising tools for understanding the genetic architecture of complex traits. Partitioning of explained variances at the chromosome and genome-segment level clearly separated regulatory and structural genomic variation as the areas where SNP effects disappeared/remained after adding transcripts to the model. The models that include transcripts explained more phenotypic variance and were better at predicting phenotypes than a model using SNPs alone. The predictions from these Bayesian models are generally unbiased, validating the estimates of explained variances.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aging is associated with declining exercise and unhealthy changes in body composition. Exercise ameliorates certain adverse age‐related physiological changes and protects against many chronic ...diseases. Despite these benefits, willingness to exercise and physiological responses to exercise vary widely, and long‐term exercise and its benefits are difficult and costly to measure in humans. Furthermore, physiological effects of aging in humans are confounded with changes in lifestyle and environment. We used C57BL/6J mice to examine long‐term patterns of exercise during aging and its physiological effects in a well‐controlled environment. One‐year‐old male (n = 30) and female (n = 30) mice were divided into equal size cohorts and aged for an additional year. One cohort was given access to voluntary running wheels while another was denied exercise other than home cage movement. Body mass, composition, and metabolic traits were measured before, throughout, and after 1 year of treatment. Long‐term exercise significantly prevented gains in body mass and body fat, while preventing loss of lean mass. We observed sex‐dependent differences in body mass and composition trajectories during aging. Wheel running (distance, speed, duration) was greater in females than males and declined with age. We conclude that long‐term exercise may serve as a preventive measure against age‐related weight gain and body composition changes, and that mouse inbred strains can be used to characterize effects of long‐term exercise and factors (e.g. sex, age) modulating these effects. These findings will facilitate studies on relationships between exercise and health in aging populations, including genetic predisposition and genotype‐by‐environment interactions.
This study demonstrates that exercise prevents doubling of body fat, significant gains in body mass, and loss of lean mass during aging. It also provides evidence of the effect of sex on exercise, body mass, and body composition trajectories during aging. Thus, this study demonstrates that long‐term exercise (starting in midlife) may be used as a preventive measure against age‐related weight gain and changes in body composition.
The problem of identifying complex epistatic quantitative trait loci (QTL) across the entire genome continues to be a formidable challenge for geneticists. The complexity of genome-wide epistatic ...analysis results mainly from the number of QTL being unknown and the number of possible epistatic effects being huge. In this article, we use a composite model space approach to develop a Bayesian model selection framework for identifying epistatic QTL for complex traits in experimental crosses from two inbred lines. By placing a liberal constraint on the upper bound of the number of detectable QTL we restrict attention to models of fixed dimension, greatly simplifying calculations. Indicators specify which main and epistatic effects of putative QTL are included. We detail how to use prior knowledge to bound the number of detectable QTL and to specify prior distributions for indicators of genetic effects. We develop a computationally efficient Markov chain Monte Carlo (MCMC) algorithm using the Gibbs sampler and Metropolis-Hastings algorithm to explore the posterior distribution. We illustrate the proposed method by detecting new epistatic QTL for obesity in a backcross of CAST/Ei mice onto M16i.
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