Candidate genes for plasma triglyceride, FFA, and glucose revealed from an intercross between inbred mouse strains NZB/B1NJ and NZW/LacJ

Whole-Genome Resequencing Analysis of the Camelus bactrianus (Bactrian Camel) Genome Identifies Mutations and Genes Affecting Milk Production Traits

Milk production is an important trait that influences the economic value of camels. However, the genetic regulatory mechanisms underlying milk production in camels have not yet been elucidated. We aimed to identify candidate molecular markers that affect camel milk production. We classified Junggar Bactrian camels (9-10-year-old) as low-yield (<1.96 kg/d) or high-yield (>2.75 kg/d) based on milk production performance. Milk fat (5.16 ± 0.51 g/100 g) and milk protein (3.59 ± 0.22 g/100 g) concentrations were significantly lower in high-yielding camels than those in low-yielding camels (6.21 ± 0.59 g/100 g, and 3.93 ± 0.27 g/100 g, respectively) (p < 0.01). There were no apparent differences in gland tissue morphology between the low- and high-production groups. Whole-genome resequencing of 12 low- and 12 high-yield camels was performed. The results of selection mapping methods, performed using two methods (FST and θπ), showed that 264 single nucleotide polymorphism sites (SNPs) overlapped between the two methods, identifying 181 genes. These genes were mainly associated with the regulation of oxytocin, estrogen, ErbB, Wnt, mTOR, PI3K-Akt, growth hormone synthesis/secretion/action, and MAPK signaling pathways. A total of 123 SNPs were selected, based on significantly associated genomic regions and important pathways for SNP genotyping, for verification in 521 additional Bactrian camels. This analysis showed that 13 SNPs were significantly associated with camel milk production yield and 18 SNPs were significantly associated with camel milk composition percentages. Most of these SNPs were located in coding regions of the genome. However, five and two important mutation sites were found in the introns of CSN2 (β-casein) and CSN3 (κ-casein), respectively. Among the candidate genes, NR4A1, ADCY8, PPARG, CSN2, and CSN3 have previously been well studied in dairy livestock. These observations provide a basis for understanding the molecular mechanisms underlying milk production in camels as well as genetic markers for breeding programs aimed at improving milk production.

Copy number variants selected during pig domestication inferred from whole genome resequencing

Over extended periods of natural and artificial selection, China has developed numerous exceptional pig breeds. Deciphering the germplasm characteristics of these breeds is crucial for their preservation and utilization. While many studies have employed single nucleotide polymorphism (SNP) analysis to investigate the local pig germplasm characteristics, copy number variation (CNV), another significant type of genetic variation, has been less explored in understanding pig resources. In this study, we examined the CNVs of 18 Wanbei pigs (WBP) using whole genome resequencing data with an average depth of 12.61. We identified a total of 8,783 CNVs (~30.07 Mb, 1.20% of the pig genome) in WBP, including 8,427 deletions and 356 duplications. Utilizing fixation index (Fst), we determined that 164 CNVs were within the top 1% of the Fst value and defined as under selection. Functional enrichment analyses of the genes associated with these selected CNVs revealed genes linked to reproduction (SPATA6, CFAP43, CFTR, BPTF), growth and development (NR6A1, SMYD3, VIPR2), and immunity (PARD3, FYB2). This study enhances our understanding of the genomic characteristics of the Wanbei pig and offers a theoretical foundation for the future breeding of this breed.

Assessing Population Structure and Signatures of Selection in Wanbei Pigs Using Whole Genome Resequencing Data

Wanbei pig (WBP) is one of the indigenous pig resources in China and has many germplasm characteristics. However, research on its genome is lacking. To assess the genomic variation, population structure, and selection signatures, we resequenced 18 WBP for the first time and performed a comprehensive analysis with resequenced data of 10 Asian wild boars. In total, 590.03 Gb of data and approximately 41 million variants were obtained. Polymorphism level (θπ) ratio and genetic differentiation (fixation index)-based cross approaches were applied, and 539 regions, which harbored 176 genes, were selected. Functional analysis of the selected genes revealed that they were associated with lipid metabolism (SCP2, APOA1, APOA4, APOC3, CD36, BCL6, ADCY8), backfat thickness (PLAG1, CACNA2D1), muscle (MYOG), and reproduction (CABS1). Overall, our results provide a valuable resource for characterizing the uniqueness of WBP and a basis for future breeding.

Genetic Connection between Hyperglycemia and Carotid Atherosclerosis in Hyperlipidemic Mice

Type 2 diabetes (T2D) is a major risk for atherosclerosis and its complications. Apoe-null (Apoe^−/−) mouse strains exhibit a wide range of variations in susceptibility to T2D and carotid atherosclerosis, with the latter being a major cause of ischemic stroke. To identify genetic connections between T2D and carotid atherosclerosis, 145 male F2 mice were generated from LP/J and BALB/cJ Apoe^−/− mice and fed 12 weeks of a Western diet. Atherosclerotic lesions in the carotid arteries, fasting, and non-fasting plasma glucose levels were measured, and genotyping was performed using miniMUGA arrays. Two significant QTL (quantitative trait loci) on chromosomes (Chr) 6 and 15 were identified for carotid lesions. The Chr15 QTL coincided precisely with QTL Bglu20 for fasting and non-fasting glucose levels. Carotid lesion sizes showed a trend toward correlation with fasting and non-fasting glucose levels in F2 mice. The Chr15 QTL for carotid lesions was suppressed after excluding the influence from fasting or non-fasting glucose. Likely candidate genes for the causal association were Tnfrsf11b, Deptor, and Gsdmc2. These results demonstrate a causative role for hyperglycemia in the development of carotid atherosclerosis in hyperlipidemic mice.

Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study

Selective serotonin reuptake inhibitors (SSRIs) are prescribed both to patients with schizophrenia and bipolar disorder. Previous studies have shown associations between SSRI treatment and cardiometabolic alterations. The aim of the present study was to investigate genetic variants associated with cardiometabolic adverse effects in patients treated with SSRIs in a naturalistic setting, using a genome-wide cross-sectional approach in a genetically homogeneous sample. We included and genotyped 1981 individuals with schizophrenia or bipolar disorder, of whom 1180 had information available on the outcomes low-density lipoprotein cholesterol (LDL-cholesterol), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, and body mass index (BMI) and investigated interactions between SNPs and SSRI use (N = 246) by conducting a genome-wide GxE analysis. We report 13 genome-wide significant interaction effects of SNPs and SSRI serum concentrations on LDL-cholesterol, HDL-cholesterol, and BMI, located in four distinct genomic loci. This study provides new insight into the pharmacogenetics of SSRI but warrants replication in independent populations.

Mapping and Congenic Dissection of Genetic Loci Contributing to Hyperglycemia and Dyslipidemia in Mice

Background

Patients with dyslipidemia have an increased risk of developing type 2 diabetes, and diabetic patients often have dyslipidemia. Potential genetic connections of fasting plasma glucose with plasma lipid profile were evaluated using hyperlipidemic mice.

Methods

225 male F₂ mice were generated from BALB/cJ (BALB) and SM/J(SM) Apoe-deficient (Apoe^−/−) mice and fed a Western diet for 5 weeks. Fasting plasma glucose and lipid levels of F₂ mice were measured before and after 5 weeks of Western diet and quantitative trait locus (QTL) analysis was performed using data collected from these two time points. 144 SNP(single nucleotide polymorphism) markers across the entire genome were typed.

Results

One major QTL (logarithm of odds ratio (LOD): 6.46) peaked at 12.7 cM on chromosome 9,Bglu16, and 3 suggestive QTLs on chromosomes 15, 18 and X were identified for fasting glucose, and over 10 loci identified for lipid traits. Bglu16 was adjacent to a major QTL, Hdlq17, for high-density lipoprotein (HDL) cholesterol (LOD: 6.31, peak: 19.1 cM). A congenic strain with a donor chromosomal region harboring Bglu16 and Hdlq17 on the Apoe^−/− background showed elevations in plasma glucose and HDL levels. Fasting glucose levels were significantly correlated with non-HDL cholesterol and triglyceride levels, especially on the Western diet, but only marginally correlated with HDL levels in F₂ mice.

Conclusions

We have demonstrated a correlative relationship between fasting glucose and plasma lipids in a segregating F₂ population under hyperlipidemic conditions, and this correlation is partially due to genetic linkage between the two disorders.

Multilevel control of glucose homeostasis by adenylyl cyclase 8

AIMS/HYPOTHESIS

Nutrient homeostasis requires integration of signals generated by glucose metabolism and hormones. Expression of the calcium-stimulated adenylyl cyclase ADCY8 is regulated by glucose and the enzyme is capable of integrating signals from multiple pathways. It may thus have an important role in glucose-induced signalling and glucose homeostasis.

METHODS

We used pharmacological and genetic approaches in beta cells to determine secretion and calcium metabolism. Furthermore, Adcy8 knockout mice were characterised.

RESULTS

In clonal beta cells, inhibitors of adenylyl cyclases or their downstream targets reduced the glucose-induced increase in cytosolic calcium and insulin secretion. This was reproduced by knock-down of ADCY8, but not of ADCY1. These agents also inhibited glucose-induced increase in cytosolic calcium and electrical activity in primary beta cells and similar effects were observed after ADCY8 knock-down. Moreover, insulin secretion was diminished in islets from Adcy8 knockout mice. These mice were glucose intolerant after oral or intraperitoneal administration of glucose whereas their levels of glucagon-like peptide-1 remained unaltered. Finally, we knocked down ADCY8 in the ventromedial hypothalamus to evaluate the need for ADCY8 in the central regulation of glucose homeostasis. Whereas mice fed a standard diet had normal glucose levels, high-fat diet exacerbated glucose intolerance and knock-down mice were incapable of raising their plasma insulin levels. Finally we confirmed that ADCY8 is expressed in human islets.

CONCLUSIONS/INTERPRETATIONS

Collectively, our findings demonstrate that ADCY8 is required for the physiological activation of glucose-induced signalling pathways in beta cells, for glucose tolerance and for hypothalamic adaptation to a high-fat diet via regulation of islet insulin secretion.

The role of ADAM17 in metabolic inflammation

The TNF-alpha Converting Enzyme (TACE), also called ADAM17 (A Disintegrin and A Metalloproteinase 17) is a type I transmembrane metalloproteinase involved in the shedding of the extracellular domain of several transmembrane proteins such as cytokines, growth factors, receptors and adhesion molecules. Some of these proteolytic events are part of cleavage cascades known as Regulated Intramembrane Proteolysis and lead to intracellular signaling. Evidence is provided that ADAM17 plays a role in atherosclerosis, in adipose tissue metabolism, insulin resistance and diabetes. The multitude of substrates cleaved by ADAM17 makes this enzyme an attractive candidate to study its role in inflammatory disorders. This review is focused on effects of ADAM17 in major metabolic tissues.

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a "toolbox" of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits.

Untangling HDL quantitative trait loci on mouse chromosome 5 and identifying Scarb1 and Acads as the underlying genes

Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identified on mouse distal chromosome 5. Our objective was to identify the underlying genes. We first used bioinformatics to narrow the Hdlq1 locus to 56 genes. The most likely candidate, Scarb1 (scavenger receptor B1), was supported by gene expression data consistent with knockout and transgenic mouse models. Then we confirmed Hdlq8 as an independent QTL by detecting it in an intercross between NZB and NZW (LOD = 12.7), two mouse strains that have identical genotypes for Scarb1. Haplotyping narrowed this QTL to 9 genes; the most likely candidate was Acads (acyl-coenzymeA dehydrogenase, short chain). Sequencing showed that Acads had an amino acid polymorphism, Gly94Asp, in a conserved region; Western blotting showed that protein levels were significantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL levels were significantly elevated in BALB/cBy compared with BALB/c mice and that this HDL difference cosegregated with the Acads mutation. We confirmed that Hdlq1 and Hdlq8 are independent QTL on mouse chromosome 5 and demonstrated that Scarb1 and Acads are the underlying genes.

TIMP3 is reduced in atherosclerotic plaques from subjects with type 2 diabetes and increased by SirT1

OBJECTIVE

Atherosclerosis is accelerated in subjects with type 2 diabetes by unknown mechanisms. We identified tissue inhibitor of metalloproteinase 3 (TIMP3), the endogenous inhibitor of A disintegrin and metalloprotease domain 17 (ADAM17) and other matrix metalloproteinases (MMPs), as a gene modifier for insulin resistance and vascular inflammation in mice. We tested its association with atherosclerosis in subjects with type 2 diabetes and identified Sirtuin 1 (SirT1) as a major regulator of TIMP3 expression.

RESEARCH DESIGN AND METHODS

We investigated ADAM10, ADAM17, MMP9, TIMP1, TIMP2, TIMP3, and TIMP4 expression levels in human carotid atherosclerotic plaques (n = 60) from subjects with and without diabetes. Human vascular smooth muscle cells exposed to several metabolic stimuli were used to identify regulators of TIMP3 expression. SirT1 small interference RNA, cDNA, and TIMP3 promoter gene reporter were used to study SirT1-dependent regulation of TIMP3.

RESULTS

Here, we show that in human carotid atherosclerotic plaques, TIMP3 was significantly reduced in subjects with type 2 diabetes, leading to ADAM17 and MMP9 overactivity. Reduced expression of TIMP3 was associated in vivo with SirT1 levels. In smooth muscle cells, inhibition of SirT1 activity and levels reduced TIMP3 expression, whereas SirT1 overexpression increased TIMP3 promoter activity.

CONCLUSIONS

In atherosclerotic plaques from subjects with type 2 diabetes, the deregulation of ADAM17 and MMP9 activities is related to inadequate expression of TIMP3 via SirT1. Studies in vascular cells confirmed the role of SirT1 in tuning TIMP3 expression.

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.

Four additional mouse crosses improve the lipid QTL landscape and identify Lipg as a QTL gene

To identify genes controlling plasma HDL and triglyceride levels, quantitative trait locus (QTL) analysis was performed in one backcross, (NZO/H1Lt x NON/LtJ) x NON/LtJ, and three intercrosses, C57BL/6J x DBA/2J, C57BL/6J x C3H/HeJ, and NZB/B1NJ x NZW/LacJ. HDL concentrations were affected by 25 QTL distributed on most chromosomes (Chrs); those on Chrs 1, 8, 12, and 16 were newly identified, and the remainder were replications of previously identified QTL. Triglyceride concentrations were controlled by nine loci; those on Chrs 1, 2, 3, 7, 16, and 18 were newly identified QTL, and the remainder were replications. Combining mouse crosses with haplotype analysis for the HDL QTL on Chr 18 reduced the list of candidates to six genes. Further expression analysis, sequencing, and quantitative complementation testing of these six genes identified Lipg as the HDL QTL gene on distal Chr 18. The data from these crosses further increase the ability to perform haplotype analyses that can lead to the identification of causal lipid genes.

Farp2 and Stk25 are candidate genes for the HDL cholesterol locus on mouse chromosome 1

OBJECTIVE

To identify the gene responsible for the quantitative trait locus (QTL) Hdlq14, a high-density lipoprotein cholesterol (HDL) QTL previously identified in a C57BL/6Jx129S1/SvImJ cross.

METHODS AND RESULTS

Hdlq14 was first confirmed as an independent QTL by detecting it in an intercross between NZB/B1NJ and NZW/LacJ, 2 strains that had identical genotypes at nearby QTL genes on chromosome 1. Using the bioinformatics tools of combined cross data and haplotype analysis, we narrowed this QTL from a 45-Mb 225-gene region to 2 genes, Farp2 and Stk25. Sequencing and expression studies showed that Farp2 had an amino acid polymorphism in an important plekstrin domain and that Stk25 had a significant expression difference between the parental strains. These 2 genes are immediately adjacent to each other and share the same haplotype over 45 inbred strains. The haplotype was associated with a significant difference in HDL levels among these strains.

CONCLUSIONS

We confirmed Hdlq14 as a separate independent QTL for HDL and narrowed the region to 2 genes, Farp2 and Stk25, with considerable evidence for both. Additional studies are needed to choose between these 2 genes or to show that both are important in determining HDL levels.

Genetic basis of HDL variation in 129/SvImJ and C57BL/6J mice: importance of testing candidate genes in targeted mutant mice

To evaluate the effect of genetic background on high-density lipoprotein cholesterol (HDL) levels in Soat1(-/-) mice, we backcrossed sterol O-acyltransferase 1 (Soat1)(-/-) mice, originally reported to have elevated HDL levels, to C57BL/6 mice and constructed a congenic strain with only a small region (3.3Mb) of 129 alleles, specifically excluding the nearby apolipoprotein A-II (Apoa2) gene from 129. HDL levels in these Soat1(-/-) mice were no different from C57BL/6, indicating that the passenger gene Apoa2 caused the previously reported elevation of HDL in these Soat1(-/-) mice. Because many knockouts are made in strain 129 and then subsequently backcrossed into C57BL/6, it is important to identify quantitative trait loci (QTL) that differ between 129 and C57BL/6 so that one can guard against effects ascribed to a knockout but really caused by a passenger gene from 129. To provide such data, we generated 528 F(2) progeny from an intercross of 129S1/SvImJ and C57BL/6 and measured HDL concentrations in F(2) animals first fed chow and then atherogenic diet. A genome wide scan using 508 single-nucleotide polymorphisms (SNPs) identified 19 QTL, 2 of which were male specific and 2 were female specific. Using comparative genomics and haplotype analysis, we narrowed QTL on chromosomes 3, 5, 8, 17, and 18 to 0.5, 6.3, 2.6, 1.1, and 0.6 Mb, respectively. These data will serve as a reference for any effort to test the impact of candidate genes on HDL using a knockout strategy.

Differential sensitivity of mouse strains to an N-alkylated imino sugar: glycosphingolipid metabolism and acrosome formation

This review deals with the pharmacological properties of an alkylated monosaccharide mimetic, N-butyldeoxynojirimycin (NB-DNJ). This compound is of pharmacogenetic interest because one of its biological effects in mice - impairment of spermatogenesis, leading to male infertility - depends greatly on the genetic background of the animal. In susceptible mice, administration of NB-DNJ perturbs the formation of an organelle, the acrosome, in early post-meiotic male germ cells. In all recipient mice, irrespective of reproductive phenotype, NB-DNJ has a similar biochemical effect: inhibition of the glucosylceramidase beta-glucosidase 2 and subsequent elevation of glucosylceramide, a glycosphingolipid. The questions that we now need to address are: how can glucosylceramide specifically affect early acrosome formation, and why is this contingent on genetic factors? Here we discuss relevant aspects of reproductive biology, the metabolism and cell biology of sphingolipids, and complex trait analysis; we also present a speculative model that takes our observations into account.

Differences in DBA/1J and DBA/2J reveal lipid QTL genes

Recent advances in mouse genomics have revealed considerable variation in the form of single-nucleotide polymorphisms (SNPs) among common inbred strains. This has made it possible to characterize closely related strains and to identify genes that differ; such genes may be causal for quantitative phenotypes. The mouse strains DBA/1J and DBA/2J differ by just 5.6% at the SNP level. These strains exhibit differences in a number of metabolic and lipid phenotypes, such as plasma levels of triglycerides (TGs) and HDL. A cross between these strains revealed multiple quantitative trait loci (QTLs) in 294 progeny. We identified significant TG QTLs on chromosomes (Chrs) 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 16, and 19, and significant HDL QTLs on Chrs 3, 9, and 16. Some QTLs mapped to chromosomes with limited variability between the two strains, thus facilitating the identification of candidate genes. We suggest that Tshr is the QTL gene for Chr 12 TG and HDL levels and that Ihh may account for the TG QTL on Chr 1. This cross highlights the advantage of crossing closely related strains for subsequent identification of QTL genes.