Single QTL Effects, Epistasis, and Pleiotropy Account for Two-thirds of the Phenotypic F2 Variance of Growth and Obesity in DU6i x DBA/2 Mice

Discovery of genomic loci for liver health and steatosis reveals overlap with glutathione redox genetics

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver condition in the United States, encompassing a wide spectrum of liver pathologies including steatosis, steatohepatitis, fibrosis, and cirrhosis. Despite its high prevalence, there are no medications currently approved by the Food and Drug Administration for the treatment of NAFLD. Recent work has suggested that NAFLD has a strong genetic component and identifying causative genes will improve our understanding of the molecular mechanisms contributing to NAFLD and yield targets for future therapeutic investigations. Oxidative stress is known to play an important role in NAFLD pathogenesis, yet the underlying mechanisms accounting for disturbances in redox status are not entirely understood. To better understand the relationship between the glutathione redox system and signs of NAFLD in a genetically-diverse population, we measured liver weight, serum biomarkers aspartate aminotransferase (AST) and alanine aminotransferase (ALT), and graded liver pathology in a large cohort of Diversity Outbred mice. We compared hepatic endpoints to those of the glutathione redox system previously measured in the livers and kidneys of the same mice, and we screened for statistical and genetic associations using the R/qtl2 software. We discovered several novel genetic loci associated with markers of liver health, including loci that were associated with both liver steatosis and glutathione redox status. Candidate genes within each locus point to possible new mechanisms underlying the complex relationship between NAFLD and the glutathione redox system, which could have translational implications for future studies targeting NAFLD pathology.

Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity

Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables to better inform dietary strategies and interventions for optimizing health, including managing obesity and metabolic disorders. Here, we review the evidence on potential mechanisms-including ones to identify individuals most likely to respond-that can be leveraged in the development of PN interventions addressing obesity. We conducted a review of the literature and included laboratory, animal, and human studies evaluating biochemical and genetic data, completed and ongoing clinical trials, and public programs in this review. Our analysis describes the potential mechanisms related to 6 domains including genetic predisposition, circadian rhythms, physical activity and sedentary behavior, metabolomics, the gut microbiome, and behavioral and socioeconomic characteristics, i.e., the factors that can be leveraged to design PN-based interventions to prevent and treat obesity-related outcomes such as weight loss or metabolic health as laid out by the NIH 2030 Strategic Plan for Nutrition Research. For example, single nucleotide polymorphisms can modify responses to certain dietary interventions, and epigenetic modulation of obesity risk via physical activity patterns and macronutrient intake have also been demonstrated. Additionally, we identified limitations including questions of equitable implementation across a limited number of clinical trials. These include the limited ability of current PN interventions to address systemic influences such as supply chains and food distribution, healthcare systems, racial or cultural inequities, and economic disparities, particularly when designing and implementing PN interventions in low- and middle-income communities. PN has the potential to help manage obesity by addressing intra- and inter-individual variation as well as context, as opposed to "one-size fits all" approaches though there is limited clinical trial evidence to date.

High-density genotyping reveals candidate genomic regions for chicken body size in breeds of Asian origin

Body size is one of the main selection indices in chicken breeding. Although often investigated, knowledge of the underlying genetic mechanisms is incomplete. The aim of the current study was to identify genomic regions associated with body size differences between Asian Game and Asian Bantam type chickens. In this study, 94 and 107 chickens from 4 Asian Game and 5 Asian Bantam type breeds, respectively, were genotyped using the chicken 580K single nucleotide polymorphism (SNP) array. A genome-wide association study (GWAS) and principal component analyses (PCA) were performed to identify genomic regions associated with body size related-traits such as wing length, shank length, shank thickness, keel length, and body weight. Hierarchical clustering of genotype data showed a clear genetic difference between the investigated Asian Game and Asian Bantam chicken types. GWAS identified 16 genomic regions associated with wing length (2, FDR ≤ 0.018), shank thickness (6, FDR ≤ 0.008), keel length (5, FDR ≤ 0.023), and body weight (3, FDR ≤ 0.041). PCA showed that the first principal component (PC1) separated the 2 chicken types and significantly correlated with the measured body size related-traits (P ≤ 2.24e-40). SNPs contributing significantly to PC1 were subjected to a more detailed investigation. This analysis identified 11 regions potentially associated with differences in body size related-traits. A region on chromosome 4 (GGA4) (17.3-21.3 Mb) was detected in both analyses GWAS and PCA. This region harbors 60 genes. Among them are myotubularin 1 (MTM1) and secreted frizzled-related protein 2 (SFPR2) which can be considered as potential candidate genes for body size related-traits. Our results clearly show that the investigated Asian Game type chicken breeds are genetically different from the Asian Bantam breeds. A region on GGA4 between 17.3 and 21.3 Mb was identified which contributes to the phenotypic difference, though further validation of candidate genes is necessary.

Genetics of murine type 2 diabetes and comorbidities

ABSTRAC

Type 2 diabetes (T2D) is a polygenic and multifactorial complex disease, defined as chronic metabolic disorder. It's a major global health concern with an estimated 463 million adults aged 20-79 years with diabetes and projected to increase up to 700 million by 2045. T2D was reported to be one of the four leading causes of non-communicable disease (NCD) deaths in 2012. Environmental factors play a part in the development of polygenic forms of diabetes. Polygenic forms of diabetes often run-in families. Fortunately, T2D, which accounts for 90-95% of the entire four types of diabetes including, Type 1 diabetes (T1D), T2D, monogenic diabetes syndromes (MGDS), and Gestational diabetes mellitus, can be prevented or delayed through nutrition and lifestyle changes as well as through pharmacologic interventions. Typical symptom of the T2D is high blood glucose levels and comprehensive insulin resistance of the body, producing an impaired glucose tolerance. Impaired glucose tolerance of T2D is accompanied by extensive health complications, including cardiovascular diseases (CVD) that vary in morbidity and mortality among populations. The pathogenesis of T2D varies between populations and/or ethnic groupings and is known to be attributed extremely by genetic components and environmental factors. It is evident that genetic background plays a critical role in determining the host response toward certain environmental conditions, whether or not of developing T2D (susceptibility versus resistant). T2D is considered as a silent disease that can progress for years before its diagnosis. Once T2D is diagnosed, many metabolic malfunctions are observed whether as side effects or as independent comorbidity. Mouse models have been proven to be a powerful tool for mapping genetic factors that underline the susceptibility to T2D development as well its comorbidities. Here, we have conducted a comprehensive search throughout the published data covering the time span from early 1990s till the time of writing this review, for already reported quantitative trait locus (QTL) associated with murine T2D and comorbidities in different mouse models, which contain different genetic backgrounds. Our search has resulted in finding 54 QTLs associated with T2D in addition to 72 QTLs associated with comorbidities associated with the disease. We summarized the genomic locations of these mapped QTLs in graphical formats, so as to show the overlapping positions between of these mapped QTLs, which may suggest that some of these QTLs could be underlined by sharing gene/s. Finally, we reviewed and addressed published reports that show the success of translation of the identified mouse QTLs/genes associated with the disease in humans.

Mapping the epistatic network underlying murine reproductive fatpad variation

Genome-wide mapping analyses are now commonplace in many species and several networks of interacting loci have been reported. However, relatively few details regarding epistatic interactions and their contribution to complex trait variation in multicellular organisms are available and the identification of positional candidate loci for epistatic QTL (epiQTL) is hampered, especially in mammals, by the limited genetic resolution inherent in most study designs. Here we further investigate the genetic architecture of reproductive fatpad weight in mice using the F(10) generation of the LG,SM advanced intercross (AI) line. We apply multiple mapping techniques including a single-locus model, locus-specific composite interval mapping (CIM), and tests for multiple QTL per chromosome to the 12 chromosomes known to harbor single-locus QTL (slQTL) affecting obesity in this cross. We also perform a genome-wide scan for pairwise epistasis. Using this combination of approaches we detect 199 peaks spread over all 19 autosomes, which potentially contribute to trait variation including all eight original F(2) loci (Adip1-8), novel slQTL peaks on chromosomes 7 and 9, and several novel epistatic loci. Extensive epistasis is confirmed involving both slQTL confidence intervals (C.I.) as well as regions that show no significant additive or dominance effects. These results provide important new insights into mapping complex genetic architectures and the role of epistasis in complex trait variation.

Genetic analysis of craniofacial traits in the medaka

Family and twin studies suggest that a substantial genetic component underlies individual differences in craniofacial morphology. In the current study, we quantified 444 craniofacial traits in 100 individuals from two inbred medaka (Oryzias latipes) strains, HNI and Hd-rR. Relative distances between defined landmarks were measured in digital images of the medaka head region. A total of 379 traits differed significantly between the two strains, indicating that many craniofacial traits are controlled by genetic factors. Of these, 89 traits were analyzed via interval mapping of 184 F(2) progeny from an intercross between HNI and Hd-rR. We identified quantitative trait loci for 66 craniofacial traits. The highest logarithm of the odds score was 6.2 for linkage group (LG) 9 and 11. Trait L33, which corresponds to the ratio of head length to head height at eye level, mapped to LG9; trait V15, which corresponds to the ratio of snout length to head width measured behind the eyes, mapped to LG11. Our initial results confirm the potential of the medaka as a model system for the genetic analysis of complex traits such as craniofacial morphology.

Mapping genetic loci that regulate lipid levels in a NZB/B1NJxRF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZBxRF/J (RF) intercross and in a combined data set that included NZBxRF and MRL/MpJxSJL/J intercrosses. In the NZBxRF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZBxRF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.

Genetic determinants of weight of fast- and slow-twitch skeletal muscles in old mice

The main goal of the study was to explore the genetic architecture underlying muscle weight in old mice. Weight of soleus, tibialis anterior (TA), extensor digitorum longus (EDL), and gastrocnemius muscles was measured in the C57BL/6J (B6) and DBA/2J (D2) strains and derivative generations: a panel of the BXD recombinant inbred (RI) strains and a B6D2 F(2) intercross at the age of 800 days. The between-strain difference in muscle weight (B6 > D2) ranged between 16% and 38%. Linkage analysis identified suggestive quantitative trait loci (QTL) on Chromosomes (Chr) 2, 6, 7, 8, 19, and X that influenced muscle weight in the 800-day-old group. Comparison of weights at 200, 500, and 800 days revealed a variable effect of age among the four muscles. Linkage analysis in the B6D2 F(2) population combined across the three different age groups identified muscle-, sex-, and age-specific QTL on Chr 1, 2, 3, 5, 6, 8, 9, 11, 13, 17, X, and Y. Genetic factors that influence the rate of weight change (within-strain weight difference at two ages) over the lifespan of BXD RIs were mapped to the markers D2Mit369 and D3Mit130 at the genome-wide p < 0.05 for TA muscle in males (between 200 and 800 days) and females (between 500 and 800 days), respectively. Analysis of all age groups supported previous findings that the genetic effects may be muscle-, age-, and sex-specific.

Quantitative trait locus analysis of atherosclerosis in an intercross between C57BL/6 and C3H mice carrying the mutant apolipoprotein E gene

Inbred mouse strains C57BL/6J (B6) and C3H/HeJ (C3H) differ significantly in atherosclerosis susceptibility and plasma lipid levels on the apolipoprotein E-deficient (apoE-/-) background when fed a Western diet. To determine genetic factors contributing to the variations in these phenotypes, we performed quantitative trait locus (QTL) analysis using an intercross between the two strains carrying the apoE-/- gene. Atherosclerotic lesions at the aortic root and plasma lipid levels of 234 female F2 mice were analyzed after being fed a Western diet for 12 weeks. QTL analysis revealed one significant QTL, named Ath22 (42 cM, LOD 4.1), on chromosome 9 and a suggestive QTL near D11mit236 (20 cM, LOD 2.4) on chromosome 11 that influenced atherosclerotic lesion size. One significant QTL on distal chromosome 1, which accounted for major variations in plasma LDL/VLDL cholesterol and triglyceride levels, coincided with a QTL having strong effects on body weight. Plasma LDL/VLDL cholesterol or triglyceride levels of F2 mice were significantly correlated with body weight, but they were not correlated with atherosclerotic lesion sizes. These data indicate that atherosclerosis susceptibility and plasma cholesterol levels are controlled by separate genetic factors in the B6 and C3H mouse model and that genetic linkages exist between body weight and lipoprotein metabolism.

Identification of quantitative trait loci that regulate obesity and serum lipid levels in MRL/MpJ x SJL/J inbred mice

The total body fat mass and serum concentration of total cholesterol, HDL cholesterol, and triglyceride (TG) differ between standard diet-fed female inbred mouse strains MRL/MpJ (MRL) and SJL/J (SJL) by 38-120% (P < 0.01). To investigate genetic regulation of obesity and serum lipid levels, we performed a genome-wide linkage analysis in 621 MRLx SJL F2 female mice. Fat mass was affected by two significant loci, D11Mit36 [43.7 cM, logarithm of the odds ratio (LOD) 11.2] and D16Mit51 (50.3 cM, LOD 3.9), and one suggestive locus at D7Mit44 (50 cM, LOD 2.4). TG levels were affected by two novel loci at D1Mit43 (76 cM, LOD 3.8) and D12Mit201 (26 cM, LOD 4.1), and two suggestive loci on chromosomes 5 and 17. HDL and cholesterol concentrations were influenced by significant loci on chromosomes 1, 3, 5, 7, and 17 that were in the regions identified earlier for other strains of mice, except for a suggestive locus on chromosome 14 that was specific to the MRL x SJL cross. In summary, linkage analysis in MRL x SJL F2 mice disclosed novel loci affecting TG, HDL, and fat mass, a measure of obesity. Knowledge of the genes in these quantitative trait loci will enhance our understanding of obesity and lipid metabolism.

Chromosome-wise dissection of the genome of the extremely big mouse line DU6i

The extreme high-body-weight-selected mouse line DU6i is a polygenic model for growth research, harboring many small-effect QTL. We dissected the genome of this line into 19 autosomes and the Y chromosome by the construction of a new panel of chromosome substitution strains (CSS). The DU6i chromosomes were transferred to a DBA/2 mice genetic background by marker-assisted recurrent backcrossing. Mitochondria and the X chromosome were of DBA/2 origin in the backcross. During the construction of these novel strains, >4000 animals were generated, phenotyped, and genotyped. Using these data, we studied the genetic control of variation in body weight and weight gain at 21, 42, and 63 days. The unique data set facilitated the analysis of chromosomal interaction with sex and parent-of-origin effects. All analyzed chromosomes affected body weight and weight gain either directly or in interaction with sex or parent of origin. The effects were age specific, with some chromosomes showing opposite effects at different stages of development.

Strategies for mapping and cloning quantitative trait genes in rodents

Over the past 15 years, more than 2,000 quantitative trait loci (QTLs) have been identified in crosses between inbred strains of mice and rats, but less than 1% have been characterized at a molecular level. However, new resources, such as chromosome substitution strains and the proposed Collaborative Cross, together with new analytical tools, including probabilistic ancestral haplotype reconstruction in outbred mice, Yin-Yang crosses and in silico analysis of sequence variants in many inbred strains, could make QTL cloning tractable. We review the potential of these strategies to identify genes that underlie QTLs in rodents.

Characterization of epistasis influencing complex spontaneous obesity in the BSB model

There is growing awareness that complex interactions among multiple genes and environmental factors play an important role in controlling obesity traits. The BSB mouse, which is produced by the backcross of (lean C57BL/6J x lean Mus spretus) x C57BL/6J, provides an excellent model of epistatic obesity. To evaluate potential epistatic interactions among six chromosomal regions previously determined to influence obesity phenotypes, we performed novel Bayesian analyses on the basis of both epistatic and nonepistatic models for four obesity traits: percentage of body fat, adiposity index, total fat mass, and body weight, and also for plasma total cholesterol. The epistatic analysis detected at least one more QTL than the nonepistatic analysis did for all obesity traits. These obesity traits were variously influenced by QTL on chromosomes 2, 7, 12, 15, and 16. Interaction between genes on chromosomes 2 and 12 was present for all obesity traits, accounting for 3-4.8% of the phenotypic variation. Chromosome 12 was found to have weak main effects on all obesity traits. Several different epistatic interactions were also detected for percentage of body fat, adiposity index, and total fat mass. Chromosomes 6 and 12 have not only main effects but also strong epistatic effects on plasma total cholesterol. Our results emphasize the importance of modeling epistasis for discovery of obesity genes.

Epistatic interaction between two nonstructural loci on chromosomes 7 and 3 influences hepatic lipase activity in BSB mice

BSB mice exhibit a wide range of obesity despite being produced by a backcross of lean C57BL/6J (B) x lean Mus spretus (SPRET/Pt) F1 animals x B. Previous linkage studies identified a quantitative trait locus (QTL) on mouse chromosome 7 with coincident peaks for hepatic lipase activity, obesity, and plasma cholesterol. However, these mice were not analyzed for gene x gene epistasis. Hepatic lipase activity is correlated with obesity and plasma cholesterol levels. In this study, we identified QTLs for plasma hepatic lipase activity with three statistical mapping methods: maximum likelihood interval mapping, Bayesian nonepistatic mapping, and Bayesian epistatic mapping. Bayesian epistatic mapping detected not only the QTL on chromosome 7 but also an additional QTL on chromosome 3, which has a weak main effect but a strong interaction with chromosome 7. SPRET/Pt alleles of the QTL on each chromosome promote hepatic lipase activity. The proportion of phenotypic variance explained by the epistatic effect is higher than that explained by the main effect of the QTL on chromosome 7.