Major quantitative trait locus on chromosome 2 for glucose tolerance in diabetic SMXA-5 mouse established from non-diabetic SM/J and A/J strains

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.

Identification and analysis of circulating long non-coding RNAs with high significance in diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM) lacks diagnostic biomarkers. Circulating long non-coding RNAs (lncRNAs) can serve as valuable diagnostic biomarkers in cardiovascular disease. To seek potential lncRNAs as a diagnostic biomarker for DCM, we investigated the genome-wide expression profiling of circulating lncRNAs and mRNAs in type 2 diabetic db/db mice with and without DCM and performed bioinformatic analyses of the deregulated lncRNA-mRNA co-expression network. Db/db mice had obesity and hyperglycemia with normal cardiac function at 6 weeks of age (diabetes without DCM) but with an impaired cardiac function at 20 weeks of age (DCM) on an isolated Langendorff apparatus. Compared with the age-matched controls, 152 circulating lncRNAs, 127 mRNAs and 3355 lncRNAs, 2580 mRNAs were deregulated in db/db mice without and with DCM, respectively. The lncRNA-mRNA co-expression network analysis showed that five deregulated lncRNAs, XLOC015617, AK035192, Gm10435, TCR-α chain, and MouselincRNA0135, have the maximum connections with differentially expressed mRNAs. Bioinformatic analysis revealed that these five lncRNAs were highly associated with the development and motion of myofilaments, regulation of inflammatory and immune responses, and apoptosis. This finding was validated by the ultrastructural examination of myocardial samples from the db/db mice with DCM using electron microscopy and changes in the expression of myocardial tumor necrosis factor-α and phosphorylated p38 mitogen-activated protein kinase in db/db mice with DCM. These results indicate that XLOC015617, AK035192, Gm10435, TCR-α chain, and MouselincRNA0135 are crucial circulating lncRNAs in the pathogenesis of DCM. These five circulating lncRNAs may have high potential as a diagnostic biomarker for DCM.

The JAX Synteny Browser for mouse-human comparative genomics

Visualizing regions of conserved synteny between two genomes is supported by numerous software applications. However, none of the current applications allow researchers to select genome features to display or highlight in blocks of synteny based on the annotated biological properties of the features (e.g., type, function, and/or phenotype association). To address this usability gap, we developed an interactive web-based conserved synteny browser, The Jackson Laboratory (JAX) Synteny Browser. The browser allows researchers to highlight or selectively display genome features in the reference and/or the comparison genome according to the biological attributes of the features. Although the current implementation for the browser is limited to the reference genomes for the laboratory mouse and human, the software platform is intentionally genome agnostic. The JAX Synteny Browser software can be deployed for any two genomes where genome coordinates for syntenic blocks are defined and for which biological attributes of the features in one or both genomes are available in widely used standard bioinformatics file formats. The JAX Synteny Browser is available at: http://syntenybrowser.jax.org/. The code base is available from GitHub: https://github.com/TheJacksonLaboratory/syntenybrowser and is distributed under the Creative Commons Attribution license (CC BY).

Detection of differentially expressed candidate genes for a fatty liver QTL on mouse chromosome 12

Background

The SMXA-5 mouse is an animal model of high-fat diet-induced fatty liver. The major QTL for fatty liver, Fl1sa on chromosome 12, was identified in a SM/J × SMXA-5 intercross. The SMXA-5 genome consists of the SM/J and A/J genomes, and the A/J allele of Fl1sa is a fatty liver-susceptibility allele. The existence of the responsible genes for fatty liver within Fl1sa was confirmed in A/J-12^SM consomic mice. The aim of this study was to identify candidate genes for Fl1sa, and to investigate whether the identified genes affect the lipid metabolism.

Results

A/J-12^SM mice showed a significantly lower liver triglyceride content compared to A/J mice when fed the high-fat diet for 7 weeks. We detected differences in the accumulation of liver lipids in response to the high-fat diet between A/J and A/J-12^SM consomic mice. To identify candidate genes for Fl1sa, we performed DNA microarray analysis using the livers of A/J-12^SM and A/J mice fed the high-fat diet. The mRNA levels of three genes (Iah1, Rrm2, Prkd1) in the chromosomal region of Fl1sa were significantly different between the strains. Iah1 mRNA levels in the liver, kidney, and lung were significantly higher in A/J-12^SM mice than in A/J mice. The hepatic Iah1 mRNA level in A/J-12^SM mice was 3.2-fold higher than that in A/J mice. To examine the effect of Iah1 on hepatic lipid metabolism, we constructed a stable cell line expressing the mouse Iah1 protein in mouse hepatoma Hepa1-6 cells. Overexpression of Iah1 in Hepa1-6 cells suppressed the mRNA levels of Cd36 and Dgat2, which play important roles in triglyceride synthesis and lipid metabolism.

Conclusions

These results demonstrated that Fl1sa on the proximal region of chromosome 12 affected fatty liver in mice on a high-fat diet. Iah1 (isoamyl acetate-hydrolyzing esterase 1 homolog) was identified as one of the candidate genes for Fl1sa. This study revealed that the mouse Iah1 gene regulated the expression of genes related to lipid metabolism in the liver.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0385-2) contains supplementary material, which is available to authorized users.

A GWAS assessment of the contribution of genomic imprinting to the variation of body mass index in mice

Background

Genomic imprinting is an epigenetic mechanism that can lead to differential gene expression depending on the parent-of-origin of a received allele. While most studies on imprinting address its underlying molecular mechanisms or attempt at discovering genomic regions that might be subject to imprinting, few have focused on the amount of phenotypic variation contributed by such epigenetic process. In this report, we give a brief review of a one-locus imprinting model in a quantitative genetics framework, and provide a decomposition of the genetic variance according to this model. Analytical deductions from the proposed imprinting model indicated a non-negligible contribution of imprinting to genetic variation of complex traits. Also, we performed a whole-genome scan analysis on mouse body mass index (BMI) aiming at revealing potential consequences when existing imprinting effects are ignored in genetic analysis.

Results

10,021 SNP markers were used to perform a whole-genome single marker regression on mouse BMI using an additive and an imprinting model. Markers significant for imprinting indicated that BMI is subject to imprinting. Marked variance changed from 1.218 ×10⁻⁴ to 1.842 ×10⁻⁴ when imprinting was considered in the analysis, implying that one third of marked variance would be lost if existing imprinting effects were not accounted for. When both marker and pedigree information were used, estimated heritability increased from 0.176 to 0.195 when imprinting was considered.

Conclusions

When a complex trait is subject to imprinting, using an additive model that ignores this phenomenon may result in an underestimate of additive variability, potentially leading to wrong inferences about the underlying genetic architecture of that trait. This could be a possible factor explaining part of the missing heritability commonly observed in genome-wide association studies (GWAS).

Genetic dissection of susceptibility genes for diabetes and related phenotypes on mouse chromosome 14 by means of congenic strains

Background

A susceptibility locus, Nidd2n, for type 2 diabetes has been mapped to mouse chromosome 14 (Chr 14) and confirmed using the consomic strain (C3H-Chr 14^NSY) of the Nagoya-Shibata-Yasuda (NSY) mouse, an animal model of spontaneous type 2 diabetes. The aim of this study was to localize and characterize Nidd2n.

Results

We constructed two novel congenic strains homozygous for different segments of NSY-Chr 14 on the control C3H/HeNcrj (C3H) background: R1 (C3H.NSY-(D14Mit206-D14Mit5)) possesses the proximal and middle segment, and R2 (C3H.NSY-(D14Mit206-D14Mit186)) possesses the most proximal segment of NSY-Chr 14. Diabetes-related phenotypes were studied in comparison with those of consomic C3H-Chr 14^NSY (R0) and parental NSY and C3H strains. Congenic R1 and R2 showed significantly higher post-challenge glucose than that in C3H mice. Fasting glucose, in contrast, was significantly lower in R1 and R2 than in C3H mice. Insulin sensitivity was significantly impaired in R1 and R2 compared to C3H mice. R2 showed significantly higher body weight and fat-pad weight than those in C3H and R1. Leptin level was significantly higher in R0, R1 and R2 than in C3H mice, with R2 showing the highest level, similar to that in NSY mice. Serum adiponectin level was significantly lower in R0, R1 and R2 than in C3H mice, while it was significantly higher in NSY than in C3H mice.

Conclusions

These data indicate that Chr 14 harbors multiple genes for diabetes-related phenotypes. The original Nidd2n, which is located in the middle region of Chr 14, was divided into two segments; Nidd2.1n in proximal Chr 14 and Nidd2.2n in distal Chr 14. Nidd2.1n contributes to post-challenge hyperglycemia, insulin resistance and adiposity. Nidd2.2n contributes to fasting as well as post-challenge hyperglycemia and insulin resistance. Adp1n, which contributes to decreased adiposity and increased insulin sensitivity, rather than a diabetogenic gene, was mapped in the middle segment.

Searching for genomic region of high-fat diet-induced type 2 diabetes in mouse chromosome 2 by analysis of congenic strains

SMXA-5 mice are a high-fat diet-induced type 2 diabetes animal model established from non-diabetic SM/J and A/J mice. By using F2 intercross mice between SMXA-5 and SM/J mice under feeding with a high-fat diet, we previously mapped a major diabetogenic QTL (T2dm2sa) on chromosome 2. We then produced the congenic strain (SM.A-T2dm2sa (R0), 20.8–163.0 Mb) and demonstrated that the A/J allele of T2dm2sa impaired glucose tolerance and increased body weight and body mass index in the congenic strain compared to SM/J mice. We also showed that the combination of T2dm2sa and other diabetogenic loci was needed to develop the high-fat diet-induced type 2 diabetes. In this study, to narrow the potential genomic region containing the gene(s) responsible for T2dm2sa, we constructed R1 and R2 congenic strains. Both R1 (69.6–163.0 Mb) and R2 (20.8–128.2 Mb) congenic mice exhibited increases in body weight and abdominal fat weight and impaired glucose tolerance compared to SM/J mice. The R1 and R2 congenic analyses strongly suggested that the responsible genes existed in the overlapping genomic interval (69.6–128.2 Mb) between R1 and R2. In addition, studies using the newly established R1A congenic strain showed that the narrowed genomic region (69.6–75.4 Mb) affected not only obesity but also glucose tolerance. To search for candidate genes within the R1A genomic region, we performed exome sequencing analysis between SM/J and A/J mice and extracted 4 genes (Itga6, Zak, Gpr155, and Mtx2) with non-synonymous coding SNPs. These four genes might be candidate genes for type 2 diabetes caused by gene-gene interactions. This study indicated that one of the genes responsible for high-fat diet-induced diabetes exists in the 5.8 Mb genomic interval on mouse chromosome 2.

Mapping behavioural evolution onto brain evolution: the strategic roles of conserved organization in individuals and species

The pattern of individual variation in brain component structure in pigs, minks and laboratory mice is very similar to variation across species in the same components, at a reduced scale. This conserved pattern of allometric scaling resembles robotic architectures designed to be robust to changes in computing power and task demands, and may reflect the mechanism by which both growing and evolving brains defend basic sensory, motor and homeostatic functions at multiple scales. Conserved scaling rules also have implications for species-specific sensory and social communication systems, motor competencies and cognitive abilities. The role of relative changes in neuron number in the central nervous system in producing species-specific behaviour is thus highly constrained, while changes in the sensory and motor periphery, and in motivational and attentional systems increase in probability as the principal loci producing important changes in functional neuroanatomy between species. By their nature, these loci require renewed attention to development and life history in the initial organization and production of species-specific behavioural abilities.

Genetic analysis of abdominal fat distribution in SM/J and A/J mice

Each abdominal fat depot, such as mesenteric or epididymal, differently contributes to the development of insulin resistance. The aim of this study was to identify the genetic regions that contribute to fat accumulation in epididymal/mesenteric fat and to examine whether or not the genetic regions that affect glucose metabolism and body fat distribution are coincident. We previously mapped a major quantitative trait locus (QTL) (T2dm2sa) for impaired glucose tolerance on chromosome 2 and revealed that SM.A-T2dm2sa congenic mice showed not only glucose tolerance but also fat accumulation. In the present study, to identify the loci/genes that control the accumulation of abdominal fat, we performed QTL analyses of epididymal/mesenteric fat weight by using (A/J x SM.A-T2dm2sa)F2 mice in which the effect of T2dm2sa was excluded. As a result, two highly significant QTLs for mesenteric fat, as well as three significant QTLs for epididymal/mesenteric fat, were mapped on the different chromosomal regions. This suggests that the fat accumulations in individual fat depots are controlled by distinct genomic regions. Our comparison of these QTLs for abdominal fat distribution with those for glucose metabolism revealed that the major genetic factors affecting body fat distribution do not coincide with genetic factors affecting glucose metabolism in (A/J x SM.A-T2dm2sa)F2.

Confirmation of diabetes-related quantitative trait loci derived from SM/J and A/J mice by using congenic strains fed a high-carbohydrate or high-fat diet

The interaction between causative genes and diet is known to influence the onset of obesity and diabetes in humans, although it has remained difficult to identify diabetogenic gene(s) because humans are genetically and environmentally heterogeneous. Mouse SMXA recombinant inbred (RI) strains are established from parental inbred strains (SM/J and A/J) and have been shown to be beneficial tools for analyzing polygenic traits. We previously mapped a significant quantitative trait locus (QTL, T2dm1sa) on Chromosome (Chr.) 10 and suggestive QTLs on Chr. 2, 6, and 18 for diabetes-related traits by using SMXA RI strains fed a high-carbohydrate diet. As a first step in identifying the responsible gene among QTLs for glucose tolerance mapped on Chr. 10 and 18, we established new strains of A.SM-T2dm1sa and SM.A-D18Mit19-D18Mit7 congenic mice. Each congenic strain bears the diabetogenic allele of an introgressed chromosomal region on a genetic background strain carrying the non-diabetogenic allele. The diabetogenic effect of T2dm1sa mapped on Chr. 10 was not supported by studies of A.SM-T2dm1sa congenic mice when the mice were fed a high-carbohydrate or high-fat diet. SM.A-D18Mit19-D18Mit7 congenic mice showed impaired glucose tolerance not only when they were fed a high-carbohydrate diet, but also when they were fed a high-fat diet. Thus, it appears that gene(s) affecting diabetes-related traits under either dietary condition may be present on Chr. 18.

Quantitative trait loci for impaired glucose tolerance in nondiabetic SM/J and A/J mice

The SMXA-5 recombinant inbred strain, which was established from nondiabetic parental SM/J and A/J mice, develops diabetic phenotypes such as impaired glucose tolerance. The combination of diabetogenic genes in the SM/J and A/J genomes impairs glucose tolerance in SMXA-5 mice. Using (SM/J x SMXA-5)F2 mice fed a high-fat diet, we previously detected a diabetogenic locus, T2dm2sa, on chromosome (Chr) 2. The A/J allele at this locus is diabetogenic. The SM.A-T2dm2sa congenic mouse, in which the Chr 2 region of A/J including T2dm2sa was introgressed into SM/J, showed obviously impaired glucose tolerance. These results indicate that SM.A-T2dm2sa mice develop diabetogenic traits due to T2dm2sa with the A/J allele and unknown diabetogenic loci with the SM/J allele. The aim of this study was to dissect these unknown loci, using quantitative trait locus (QTL) analysis in the (A/J x SM.A-T2dm2sa) F2 intercross fed a high-fat diet. The results revealed a highly significant QTL, T2dm4sa, for glucose tolerance on Chr 6 and a significant QTL, T2dm5sa, for glucose tolerance on Chr 11. These loci with the SM/J allele were diabetogenic. The diabetogenic effect of T2dm4sa or T2dm5sa was verified by the impairment of glucose tolerance in the A/J-6(SM) or A/J-11(SM) consomic strain, in which Chr 6 or Chr 11 of SM/J is introgressed into A/J, respectively. These results demonstrate that diabetogenic loci exist in the genomes of nondiabetic A/J and SM/J mice and suggest that T2dm2sa with the A/J allele and T2dm4sa and/or T2dm5sa with the SM/J allele elicit impaired glucose tolerance in SM.A-T2dm2sa mice.

A meta-analysis of QTL for diabetes-related traits in rodents

Crossbreeding studies in rodents have identified numerous quantitative trait loci (QTL) that are linked to diabetes-related component traits. To identify genetic consensus regions implicated in insulin action and glucose homeostasis, we have performed a meta-analysis of genomewide linkage scans for diabetes-related traits. From a total of 43 published genomewide scans we assembled a nonredundant collection of 153 QTL for glucose levels, insulin levels, and glucose tolerance. Collectively, these studies include data from 48 different parental strains and >11,000 individual animals. The results of the studies were analyzed by the truncated product method (TPM). The analysis revealed significant evidence for linkage of glucose levels, insulin levels, and glucose tolerance to 27 different segments of the mouse genome. The most prominent consensus regions [localized to chromosomes 2, 4, 7, 9, 11, 13, and 19; logarithm of odds (LOD) scores 10.5-17.4] cover approximately 11% of the mouse genome and collectively contain the peak markers for 47 QTL. Approximately half of these genomic segments also show significant linkage to body weight and adiposity, indicating the presence of multiple obesity-dependent and -independent consensus regions for diabetes-related traits. At least 84 human genetic markers from genomewide scans and >80 candidate genes from human and rodent studies map into the mouse consensus regions for diabetes-related traits, indicating a substantial overlap between the species. Our results provide guidance for the identification of novel candidate genes and demonstrate the presence of numerous distinct consensus QTL regions with highly significant LOD scores that control glucose homeostasis. An interactive physical map of the QTL is available online at http://www.diabesitygenes.org.

Linkage disequilibrium in wild mice

Crosses between laboratory strains of mice provide a powerful way of detecting quantitative trait loci for complex traits related to human disease. Hundreds of these loci have been detected, but only a small number of the underlying causative genes have been identified. The main difficulty is the extensive linkage disequilibrium (LD) in intercross progeny and the slow process of fine-scale mapping by traditional methods. Recently, new approaches have been introduced, such as association studies with inbred lines and multigenerational crosses. These approaches are very useful for interval reduction, but generally do not provide single-gene resolution because of strong LD extending over one to several megabases. Here, we investigate the genetic structure of a natural population of mice in Arizona to determine its suitability for fine-scale LD mapping and association studies. There are three main findings: (1) Arizona mice have a high level of genetic variation, which includes a large fraction of the sequence variation present in classical strains of laboratory mice; (2) they show clear evidence of local inbreeding but appear to lack stable population structure across the study area; and (3) LD decays with distance at a rate similar to human populations, which is considerably more rapid than in laboratory populations of mice. Strong associations in Arizona mice are limited primarily to markers less than 100 kb apart, which provides the possibility of fine-scale association mapping at the level of one or a few genes. Although other considerations, such as sample size requirements and marker discovery, are serious issues in the implementation of association studies, the genetic variation and LD results indicate that wild mice could provide a useful tool for identifying genes that cause variation in complex traits.

Searching for genetic factors of fatty liver in SMXA-5 mice by quantitative trait loci analysis under a high-fat diet

Fatty liver is strongly associated with the metabolic syndrome characterized by obesity, insulin resistance, and type 2 diabetes, but the genetic basis and functional mechanisms linking fatty liver with the metabolic syndrome are largely unknown. The SMXA-5 mouse is one of the SMXA recombinant inbred substrains established from SM/J and A/J strains and is a model for polygenic type 2 diabetes, characterized by moderately impaired glucose tolerance, hyperinsulinemia, and mild obesity. SMXA-5 mice also developed fatty liver, and a high-fat diet markedly worsened this trait, although SM/J and A/J mice are resistant to fatty liver development under a high-fat diet. To dissect loci for fatty liver in the A/J regions of the SMXA-5 genome, we attempted quantitative trait loci (QTLs) analysis in (SM/JxSMXA-5)F2 intercross mice fed a high-fat diet. We mapped a major QTL for relative liver weight and liver lipid content near D12Mit270 on chromosome 12 and designated this QTL Fl1sa. The A/J allele at this locus contributes to the increase in these traits. We confirmed the effect of Fl1sa on lipid accumulation in liver using the A/J-Chr12(SM) consomic strain, which showed significantly less accumulation than A/J mice. This suggests that the SM/J and A/J strains, neither of which develops fatty liver, possess loci causing fatty liver and that the coexistence of these loci causes fatty liver in SMXA-5 mice.

The genetic landscape of type 2 diabetes in mice

Inbred mouse strains provide genetic diversity comparable to that of the human population. Like humans, mice have a wide range of diabetes-related phenotypes. The inbred mouse strains differ in the response of their critical physiological functions, such as insulin sensitivity, insulin secretion, beta-cell proliferation and survival, and fuel partitioning, to diet and obesity. Most of the critical genes underlying these differences have not been identified, although many loci have been mapped. The dramatic improvements in genomic and bioinformatics resources are accelerating the pace of gene discovery. This review describes how mouse genetics can be used to discover diabetes-related genes, summarizes how the mouse strains differ in their diabetes-related phenotypes, and describes several examples of how loci identified in the mouse may directly relate to human diabetes.