Evidence of maternal QTL affecting growth and obesity in adult mice

Innovative approach to identify multigenomic and environmental interactions associated with birth defects in family-based hybrid designs

Genes, including those with transgenerational effects, work in concert with behavioral, environmental, and social factors via complex biological networks to determine human health. Understanding complex relationships between causal factors underlying human health is an essential step towards deciphering biological mechanisms. We propose a new analytical framework to investigate the interactions between maternal and offspring genetic variants or their surrogate single nucleotide polymorphisms (SNPs) and environmental factors using family-based hybrid study design. The proposed approach can analyze diverse genetic and environmental factors and accommodate samples from a variety of family units, including case/control-parental triads, and case/control-parental dyads, while minimizing potential bias introduced by population admixture. Comprehensive simulations demonstrated that our innovative approach outperformed the log-linear approach, the best available method for case-control family data. The proposed approach had greater statistical power and was capable to unbiasedly estimate the maternal and child genetic effects and the effects of environmental factors, while controlling the Type I error rate against population stratification. Using our newly developed approach, we analyzed the associations between maternal and fetal SNPs and obstructive and conotruncal heart defects, with adjustment for demographic and lifestyle factors and dietary supplements. Fourteen and 11 fetal SNPs were associated with obstructive and conotruncal heart defects, respectively. Twenty-seven and 17 maternal SNPs were associated with obstructive and conotruncal heart defects, respectively. In addition, maternal body mass index was a significant risk factor for obstructive defects. The proposed approach is a powerful tool for interrogating the etiological mechanism underlying complex traits.

Density-dependent offspring interactions do not explain macroevolutionary scaling of adult size and offspring size

Most life forms exhibit a correlated evolution of adult size (AS) and size at independence (SI), giving rise to AS-SI scaling relationships. Theory suggests that scaling arises because relatively large adults have relatively high reproductive output, resulting in strong density-dependent competition in early life, where large size at independence provides a competitive advantage to juveniles. The primary goal of our study is to test this density hypothesis, using large datasets that span the vertebrate tree of life (fishes, amphibians, reptiles, birds, and mammals). Our secondary goal is to motivate new hypotheses for AS-SI scaling by exploring how subtle variation in life-histories among closely related species is associated with variation in scaling. Our phylogenetically informed comparisons do not support the density hypothesis. Instead, exploration of AS-SI scaling among life-history variants suggests that steeper AS-SI scaling slopes are associated with evolutionary increases in size at independence. We suggest that a positive association between size at independence and juvenile growth rate may represent an important mechanism underlying AS-SI scaling, a mechanism that has been underappreciated by theorists. If faster juvenile growth is a consequence of evolutionary increases in size at independence, this may help offset the cost of delayed maturation, leading to steeper AS-SI scaling slopes.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www.

RESEARCH

va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

Genetics of metabolic syndrome: potential clues from wild-derived inbred mouse strains

The metabolic syndrome (MetS) is a complex constellation of metabolic abnormalities including obesity, abnormal glucose metabolism, dyslipidemia, and elevated blood pressure that together substantially increase risk for cardiovascular disease and Type 2 diabetes. Both genetic and environmental factors contribute to the development of MetS, but this process is still far from understood. Human studies have revealed only part of the underlying basis. Studies in mice offer many strengths that can complement human studies to help elucidate the etiology and pathophysiology of MetS. Here we review the ways mice can contribute to MetS research. In particular, we focus on the information that can be obtained from studies of the inbred strains, with specific focus on the phenotypes of the wild-derived inbred strains. These are newly derived inbred strains that were created from wild-caught mice. They contain substantial genetic variation that is not present in the classical inbred strains, have phenotypes of relevance for MetS, and various mouse strain resources have been created to facilitate the mining of this new genetic variation. Thus studies using wild-derived inbred strains hold great promise for increasing our understanding of MetS.

Social Interactions and Indirect Genetic Effects on Complex Juvenile and Adult Traits

Most animal species are social in one form or another, yet many studies in rodent model systems use either individually housed animals or ignore potential confounds caused by group housing. While such social interaction effects on developmental and behavioral traits are well established, the genetic basis of social interactions has not been researched in as much detail. Specifically, the effects of genetic variation in social partners on the phenotype of a focal individual have mostly been studied at the phenotypic level. Such indirect genetic effects (IGEs), where the genotype of one individual influences the phenotype of a second individual, can have important evolutionary and medically relevant consequences. In this chapter, we give a brief outline of social interaction effects, and how systems genetics approaches using recombinant inbred populations can be used to investigate indirect genetic effects specifically, including maternal genetic effects. We discuss experimental designs for the study of IGEs and show how indirect genetic loci can be identified that underlie social interaction effects, their mechanisms, and consequences for trait variation in focal individuals.

Evolutionary genetics of maternal effects

Maternal genetic effects (MGEs), where genes expressed by mothers affect the phenotype of their offspring, are important sources of phenotypic diversity in a myriad of organisms. We use a single‐locus model to examine how MGEs contribute patterns of heritable and nonheritable variation and influence evolutionary dynamics in randomly mating and inbreeding populations. We elucidate the influence of MGEs by examining the offspring genotype‐phenotype relationship, which determines how MGEs affect evolutionary dynamics in response to selection on offspring phenotypes. This approach reveals important results that are not apparent from classic quantitative genetic treatments of MGEs. We show that additive and dominance MGEs make different contributions to evolutionary dynamics and patterns of variation, which are differentially affected by inbreeding. Dominance MGEs make the offspring genotype‐phenotype relationship frequency dependent, resulting in the appearance of negative frequency‐dependent selection, while additive MGEs contribute a component of parent‐of‐origin dependent variation. Inbreeding amplifies the contribution of MGEs to the additive genetic variance and, therefore enhances their evolutionary response. Considering evolutionary dynamics of allele frequency change on an adaptive landscape, we show that this landscape differs from the mean fitness surface, and therefore, under some condition, fitness peaks can exist but not be “available” to the evolving population.

Body Composition QTLs Identified in Intercross Populations Are Reproducible in Consomic Mouse Strains

Genetic variation contributes to individual differences in obesity, but defining the exact relationships between naturally occurring genotypes and their effects on fatness remains elusive. As a step toward positional cloning of previously identified body composition quantitative trait loci (QTLs) from F2 crosses of mice from the C57BL/6ByJ and 129P3/J inbred strains, we sought to recapture them on a homogenous genetic background of consomic (chromosome substitution) strains. Male and female mice from reciprocal consomic strains originating from the C57BL/6ByJ and 129P3/J strains were bred and measured for body weight, length, and adiposity. Chromosomes 2, 7, and 9 were selected for substitution because previous F2 intercross studies revealed body composition QTLs on these chromosomes. We considered a QTL confirmed if one or both sexes of one or both reciprocal consomic strains differed significantly from the host strain in the expected direction after correction for multiple testing. Using these criteria, we confirmed two of two QTLs for body weight (Bwq5-6), three of three QTLs for body length (Bdln3-5), and three of three QTLs for adiposity (Adip20, Adip26 and Adip27). Overall, this study shows that despite the biological complexity of body size and composition, most QTLs for these traits are preserved when transferred to consomic strains; in addition, studying reciprocal consomic strains of both sexes is useful in assessing the robustness of a particular QTL.

Epigenetic marks: regulators of livestock phenotypes and conceivable sources of missing variation in livestock improvement programs

Improvement in animal productivity has been achieved over the years through careful breeding and selection programs. Today, variations in the genome are gaining increasing importance in livestock improvement strategies. Genomic information alone, however, explains only a part of the phenotypic variance in traits. It is likely that a portion of the unaccounted variance is embedded in the epigenome. The epigenome encompasses epigenetic marks such as DNA methylation, histone tail modifications, chromatin remodeling, and other molecules that can transmit epigenetic information such as non-coding RNA species. Epigenetic factors respond to external or internal environmental cues such as nutrition, pathogens, and climate, and have the ability to change gene expression leading to emergence of specific phenotypes. Accumulating evidence shows that epigenetic marks influence gene expression and phenotypic outcome in livestock species. This review examines available evidence of the influence of epigenetic marks on livestock (cattle, sheep, goat, and pig) traits and discusses the potential for consideration of epigenetic markers in livestock improvement programs. However, epigenetic research activities on farm animal species are currently limited partly due to lack of recognition, funding and a global network of researchers. Therefore, considerable less attention has been given to epigenetic research in livestock species in comparison to extensive work in humans and model organisms. Elucidating therefore the epigenetic determinants of animal diseases and complex traits may represent one of the principal challenges to use epigenetic markers for further improvement of animal productivity.

Genetics of Rapid and Extreme Size Evolution in Island Mice

Organisms on islands provide a revealing window into the process of adaptation. Populations that colonize islands often evolve substantial differences in body size from their mainland relatives. Although the ecological drivers of this phenomenon have received considerable attention, its genetic basis remains poorly understood. We use house mice (subspecies: Mus musculus domesticus) from remote Gough Island to provide a genetic portrait of rapid and extreme size evolution. In just a few hundred generations, Gough Island mice evolved the largest body size among wild house mice from around the world. Through comparisons with a smaller-bodied wild-derived strain from the same subspecies (WSB/EiJ), we demonstrate that Gough Island mice achieve their exceptional body weight primarily by growing faster during the 6 weeks after birth. We use genetic mapping in large F(2) intercrosses between Gough Island mice and WSB/EiJ to identify 19 quantitative trait loci (QTL) responsible for the evolution of 16-week weight trajectories: 8 QTL for body weight and 11 QTL for growth rate. QTL exhibit modest effects that are mostly additive. We conclude that body size evolution on islands can be genetically complex, even when substantial size changes occur rapidly. In comparisons to published studies of laboratory strains of mice that were artificially selected for divergent body sizes, we discover that the overall genetic profile of size evolution in nature and in the laboratory is similar, but many contributing loci are distinct. Our results underscore the power of genetically characterizing the entire growth trajectory in wild populations and lay the foundation necessary for identifying the mutations responsible for extreme body size evolution in nature.

Body composition and gene expression QTL mapping in mice reveals imprinting and interaction effects

BACKGROUND

Shifts in body composition, such as accumulation of body fat, can be a symptom of many chronic human diseases; hence, efforts have been made to investigate the genetic mechanisms that underlie body composition. For example, a few quantitative trait loci (QTL) have been discovered using genome-wide association studies, which will eventually lead to the discovery of causal mutations that are associated with tissue traits. Although some body composition QTL have been identified in mice, limited research has been focused on the imprinting and interaction effects that are involved in these traits. Previously, we found that Myostatin genotype, reciprocal cross, and sex interacted with numerous chromosomal regions to affect growth traits.

RESULTS

Here, we report on the identification of muscle, adipose, and morphometric phenotypic QTL (pQTL), translation and transcription QTL (tQTL) and expression QTL (eQTL) by applying a QTL model with additive, dominance, imprinting, and interaction effects. Using an F2 population of 1000 mice derived from the Myostatin-null C57BL/6 and M16i mouse lines, six imprinted pQTL were discovered on chromosomes 6, 9, 10, 11, and 18. We also identified two IGF1 and two Atp2a2 eQTL, which could be important trans-regulatory elements. pQTL, tQTL and eQTL that interacted with Myostatin, reciprocal cross, and sex were detected as well. Combining with the additive and dominance effect, these variants accounted for a large amount of phenotypic variation in this study.

CONCLUSIONS

Our study indicates that both imprinting and interaction effects are important components of the genetic model of body composition traits. Furthermore, the integration of eQTL and traditional QTL mapping may help to explain more phenotypic variation than either alone, thereby uncovering more molecular details of how tissue traits are regulated.

Detecting maternal-effect loci by statistical cross-fostering

Great progress has been made in understanding the genetic architecture of phenotypic variation, but it is almost entirely focused on how the genotype of an individual affects the phenotype of that same individual. However, in many species the genotype of the mother is a major determinant of the phenotype of her offspring. Therefore, a complete picture of genetic architecture must include these maternal genetic effects, but they can be difficult to identify because maternal and offspring genotypes are correlated and therefore, partially confounded. We present a conceptual framework that overcomes this challenge to separate direct and maternal effects in intact families through an analysis that we call "statistical cross-fostering." Our approach combines genotype data from mothers and their offspring to remove the confounding effects of the offspring's own genotype on measures of maternal genetic effects. We formalize our approach in an orthogonal model and apply this model to an experimental population of mice. We identify a set of six maternal genetic effect loci that explain a substantial portion of variation in body size at all ages. This variation would be missed in an approach focused solely on direct genetic effects, but is clearly a major component of genetic architecture. Our approach can easily be adapted to examine maternal effects in different systems, and because it does not require experimental manipulation, it provides a framework that can be used to understand the contribution of maternal genetic effects in both natural and experimental populations.

Disentangling prenatal and postnatal maternal genetic effects reveals persistent prenatal effects on offspring growth in mice

Mothers are often the most important determinant of traits expressed by their offspring. These "maternal effects" (MEs) are especially crucial in early development, but can also persist into adulthood. They have been shown to play a role in a diversity of evolutionary and ecological processes, especially when genetically based. Although the importance of MEs is becoming widely appreciated, we know little about their underlying genetic basis. We address the dearth of genetic data by providing a simple approach, using combined genotype information from parents and offspring, to identify "maternal genetic effects" (MGEs) contributing to natural variation in complex traits. Combined with experimental cross-fostering, our approach also allows for the separation of pre- and postnatal MGEs, providing rare insights into prenatal effects. Applying this approach to an experimental mouse population, we identified 13 ME loci affecting body weight, most of which (12/13) exhibited prenatal effects, and nearly half (6/13) exhibiting postnatal effects. MGEs contributed more to variation in body weight than the direct effects of the offsprings' own genotypes until mice reached adulthood, but continued to represent a major component of variation through adulthood. Prenatal effects always contributed more variation than postnatal effects, especially for those effects that persisted into adulthood. These results suggest that MGEs may be an important component of genetic architecture that is generally overlooked in studies focused on direct mapping from genotype to phenotype. Our approach can be used in both experimental and natural populations, providing a widely practicable means of expanding our understanding of MGEs.

Genome Scan for Parent-of-Origin QTL Effects on Bovine Growth and Carcass Traits

Parent-of-origin effects (POE) such as genomic imprinting influence growth and body composition in livestock, rodents, and humans. Here, we report the results of a genome scan to detect quantitative trait loci (QTL) with POE on growth and carcass traits in Angus × Brahman cattle crossbreds. We identified 24 POE–QTL on 15 Bos taurus autosomes (BTAs) of which six were significant at 5% genome-wide (GW) level and 18 at the 5% chromosome-wide (CW) significance level. Six QTL were paternally expressed while 15 were maternally expressed. Three QTL influencing post-weaning growth map to the proximal end of BTA2 (linkage region of 0–9 cM; genomic region of 5.0–10.8 Mb), for which only one imprinted ortholog is known so far in the human and mouse genomes, and therefore may potentially represent a novel imprinted region. The detected QTL individually explained 1.4 ∼ 5.1% of each trait’s phenotypic variance. Comparative in silico analysis of bovine genomic locations show that 32 out of 1,442 known mammalian imprinted genes from human and mouse homologs map to the identified QTL regions. Although several of the 32 genes have been associated with quantitative traits in cattle, only two (GNAS and PEG3) have experimental proof of being imprinted in cattle. These results lend additional support to recent reports that POE on quantitative traits in mammals may be more common than previously thought, and strengthen the need to identify and experimentally validate cattle orthologs of imprinted genes so as to investigate their effects on quantitative traits.

Four out of eight genes in a mouse chromosome 7 congenic donor region are candidate obesity genes

We previously identified a region of mouse chromosome 7 that influences body fat mass in F2 littermates of congenic × background intercrosses. Current analyses revealed that alleles in the donor region of the subcongenic B6.C-D7Mit318 (318) promoted a twofold increase in adiposity in homozygous lines of 318 compared with background C57BL/6ByJ (B6By) mice. Parent-of-origin effects were discounted through cross-fostering studies and an F1 reciprocal cross. Mapping of the donor region revealed that it has a maximal size of 2.8 Mb (minimum 1.8 Mb) and contains a maximum of eight protein coding genes. Quantitative PCR in whole brain, liver, and gonadal white adipose tissue (GWAT) revealed differential expression between genotypes for three genes in females and two genes in males. Alpha-2,8-sialyltransferase 8B (St8sia2) showed reduced 318 mRNA levels in brain for females and males and in GWAT for females only. Both sexes of 318 mice had reduced Repulsive guidance molecule-a (Rgma) expression in GWAT. In brain, Family with sequence similarity 174 member b (Fam174b) had increased expression in 318 females, whereas Chromodomain helicase DNA binding protein 2 (Chd2-2) had reduced expression in 318 males. No donor region genes were differentially expressed in liver. Sequence analysis of coding exons for all genes in the 318 donor region revealed only one single nucleotide polymorphism that produced a nonsynonymous missense mutation, Gln7Pro, in Fam174b. Our findings highlight the difficulty of using expression and sequence to identify quantitative trait genes underlying obesity even in small genomic regions.

Early postnatal BMI adaptation is regulated during a fixed time period and mainly depends on maternal BMI

In the present study, we investigated whether there are critical time periods which influence the course of BMI during the first 6 years of life. From 5,433 children who participated in preschool examinations those 212 children were selected who crossed the BMI percentiles as a result of an extreme postnatal BMI rise (from <10th to 90th percentile) or fall (from >90th to <10th percentile) or who have persistently low or high BMI both at birth and at the age of 6 years. Forty children with a BMI close to the 50th percentile both at birth and age 6 years were selected to serve as controls. The courses of weight and height during the first 6 years of age were assessed and BMI was calculated. To identify influences connected with BMI development, we investigated genetic, social, nutritional, and other factors proceeding from the mother during pregnancy. Finally completed data sets of 57 children were available. Our study shows that during two critical time periods a significant move toward low or high BMI takes place among the groups: in early infancy from ~0.5 to 1.5 years and again from 5 to 6 years. At the age of 1.5 years the final state of BMI is already fixed in all study groups. Mothers of overweight 6-year-old children are overweight, whereas mothers of underweight 6-year-old children have a below-normal BMI. All other investigated factors only had a minor influence on postnatal BMI development. We conclude that postnatal BMI development follows a fixed genetic program and is mainly programmed by maternal metabolism.