Contrasting genetic architectures in different mouse reference populations used for studying complex traits

A complete chromosome substitution mapping panel reveals genome-wide epistasis in Arabidopsis

Chromosome substitution lines (CSLs) are tentatively supreme resources to investigate non-allelic genetic interactions. However, the difficulty of generating such lines in most species largely yielded imperfect CSL panels, prohibiting a systematic dissection of epistasis. Here, we present the development and use of a unique and complete panel of CSLs in Arabidopsis thaliana, allowing the full factorial analysis of epistatic interactions. A first comparison of reciprocal single chromosome substitutions revealed a dependency of QTL detection on different genetic backgrounds. The subsequent analysis of the complete panel of CSLs enabled the mapping of the genetic interactors and identified multiple two- and three-way interactions for different traits. Some of the detected epistatic effects were as large as any observed main effect, illustrating the impact of epistasis on quantitative trait variation. We, therefore, have demonstrated the high power of detection and mapping of genome-wide epistasis, confirming the assumed supremacy of comprehensive CSL sets.

A Missense Pathogenic Variant in a Conserved Region of CNTNAP2 Is Associated with Obesity, Seizures, and Language Impairment in a Pakistani Family

Introduction

In a consanguineous family, seven siblings born in three sibships showed a syndromic disorder characterized by obesity, seizures, and language impairment phenotypes, which appeared at early age or developed during early childhood.

Methods

By whole-exome sequencing and subsequent Sanger sequencing, a novel homozygous missense variant (c.3371 T>A [p.Ile1124Asn]) in exon 20 of the CNTNAP2 gene was identified.

Results

The pathogenic variant in this family is located within one of the laminin G-like 4 domains of CASPR2 and may cause loss of hydrophobic interactions of CASPR2 with its partner proteins. Single nucleotide and copy number variants in this gene have previously been related to Gilles de la Tourette syndrome, cortical dysplasia-focal epilepsy syndrome, schizophrenia, Pitt-Hopkins syndrome, and autism spectrum, attention deficit hyperactivity, and obsessive compulsive disorders. Yet, few studies described patients with CNTNAP2 variants showing diet-induced obesity.

Conclusion

This report expands the phenotypic spectrum of this rare syndrome and provides deeper insights by documenting the clinical features and genetic findings of the patients.

Intermediate Molecular Phenotypes to Identify Genetic Markers of Anthracycline-Induced Cardiotoxicity Risk

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex trait with a polygenic component that is mainly unidentified. We propose that levels of intermediate molecular phenotypes (IMPs) in the myocardium associated with histopathological damage could explain CDA susceptibility, so variants of genes encoding these IMPs could identify patients susceptible to this complication. Thus, a genetically heterogeneous cohort of mice (n = 165) generated by backcrossing were treated with doxorubicin and docetaxel. We quantified heart fibrosis using an Ariol slide scanner and intramyocardial levels of IMPs using multiplex bead arrays and QPCR. We identified quantitative trait loci linked to IMPs (ipQTLs) and cdaQTLs via linkage analysis. In three cancer patient cohorts, CDA was quantified using echocardiography or Cardiac Magnetic Resonance. CDA behaves as a complex trait in the mouse cohort. IMP levels in the myocardium were associated with CDA. ipQTLs integrated into genetic models with cdaQTLs account for more CDA phenotypic variation than that explained by cda-QTLs alone. Allelic forms of genes encoding IMPs associated with CDA in mice, including AKT1, MAPK14, MAPK8, STAT3, CAS3, and TP53, are genetic determinants of CDA in patients. Two genetic risk scores for pediatric patients (n = 71) and women with breast cancer (n = 420) were generated using machine-learning Least Absolute Shrinkage and Selection Operator (LASSO) regression. Thus, IMPs associated with heart damage identify genetic markers of CDA risk, thereby allowing more personalized patient management.

Intermediate molecular phenotypes to identify genetic markers of anthracycline-induced cardiotoxicity risk

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex disease whose polygenic component is mainly unidentified. We propose that levels of intermediate molecular phenotypes in the myocardium associated with histopathological damage could explain CDA susceptibility; so that variants of genes encoding these intermediate molecular phenotypes could identify patients susceptible to this complication. A genetically heterogeneous cohort of mice generated by backcrossing (N = 165) was treated with doxorubicin and docetaxel. Cardiac histopathological damage was measured by fibrosis and cardiomyocyte size by an Ariol slide scanner. We determine intramyocardial levels of intermediate molecular phenotypes of CDA associated with histopathological damage and quantitative trait loci (ipQTLs) linked to them. These ipQTLs seem to contribute to the missing heritability of CDA because they improve the heritability explained by QTL directly linked to CDA (cda-QTLs) through genetic models. Genes encoding these molecular subphenotypes were evaluated as genetic markers of CDA in three cancer patient cohorts (N = 517) whose cardiac damage was quantified by echocardiography or Cardiac Magnetic Resonance. Many SNPs associated with CDA were found using genetic models. LASSO multivariate regression identified two risk score models, one for pediatric cancer patients and the other for women with breast cancer. Molecular intermediate phenotypes associated with heart damage can identify genetic markers of CDA risk, thereby allowing a more personalized patient management. A similar strategy could be applied to identify genetic markers of other complex trait diseases.

Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene

To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue (gWAT), defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3 T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with BMI and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will shine light on the mechanism by which Sgcg may protect from the development of obesity.

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.

Genetic Modifiers of Oral Nicotine Consumption in Chrna5 Null Mutant Mice

The gene CHRNA5 is strongly associated with the level of nicotine consumption in humans and manipulation of the expression or function of Chrna5 similarly alters nicotine consumption in rodents. In both humans and rodents, reduced or complete loss of function of Chrna5 leads to increased nicotine consumption. However, the mechanism through which decreased function of Chrna5 increases nicotine intake is not well-understood. Toward a better understanding of how loss of function of Chrna5 increases nicotine consumption, we have initiated efforts to identify genetic modifiers of Chrna5 deletion-dependent oral nicotine consumption in mice. For this, we introgressed the Chrna5 knockout (KO) mutation onto a panel of C57BL/6J-Chr#A/J/NAJ chromosome substitution strains (CSS) and measured oral nicotine consumption in 18 CSS and C57BL/6 (B6) mice homozygous for the Chrna5 KO allele as well as their Chrna5 wild type littermates. As expected, nicotine consumption was significantly increased in Chrna5 KO mice relative to Chrna5 wildtype mice on a B6 background. Among the CSS homozygous for the Chrna5 KO allele, several exhibited altered nicotine consumption relative to B6 Chrna5 KO mice. Sex-independent modifiers were detected in CSS possessing A/J chromosomes 5 and 11 and a male-specific modifier was found on chromosome 15. In all cases nicotine consumption was reduced in the CSS Chrna5 KO mice relative to B6 Chrna5 KO mice and consumption in the CSS KO mice was indistinguishable from their wild type littermates. Nicotine consumption was also reduced in both Chrna5 KO and wildtype CSS mice possessing A/J chromosome 1 and increased in both KO and wild type chromosome 17 CSS relative to KO and wild type B6 mice. These results demonstrate the presence of several genetic modifiers of nicotine consumption in Chrna5 KO mice as well as identify loci that may affect nicotine consumption independent of Chrna5 genotype. Identification of the genes that underlie the altered nicotine consumption may provide novel insight into the mechanism through which Chrna5 deletion increases nicotine consumption and, more generally, a better appreciation of the neurobiology of nicotine intake.

A Novel Mapping Strategy Utilizing Mouse Chromosome Substitution Strains Identifies Multiple Epistatic Interactions That Regulate Complex Traits

The genetic contribution of additive vs. non-additive (epistatic) effects in the regulation of complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate approach for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTL) were identified using a CSS-based backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. In the liver transcriptomes of offspring from this cross, we identified and mapped additive QTL regulating the hepatic expression of 768 genes, and epistatic QTL pairs for 519 genes. Similarly, we identified additive QTL for fat pad weight, platelets, and the percentage of granulocytes in blood, as well as epistatic QTL pairs controlling the percentage of lymphocytes in blood and red cell distribution width. The variance attributed to the epistatic QTL pairs was approximately equal to that of the additive QTL; however, the SNPs in the epistatic QTL pairs that accounted for the largest variances were undetected in our single locus association analyses. These findings highlight the need to account for epistasis in association studies, and more broadly demonstrate the importance of identifying genetic interactions to understand the complete genetic architecture of complex traits.

Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for "polygenic epistasis"

Background

The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors.

Results

We applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection.

Conclusions

Unlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.

Many statistical tests which link genetic markers in the genome to differences in traits rely on the assumption that the same polymorphism will have identical effects in different individuals. However, there is substantial evidence indicating that this is not the case. Epistasis is the phenomenon in which multiple polymorphisms interact with one another to amplify or negate each other’s effects on a trait. We hypothesized that individual SNP effects could be changed in a polygenic manner, such that the proportion of as genetic ancestry, rather than specific markers, might be used to capture epistatic interactions. Motivated by this possibility, we develop a new statistical test that allowed us to examine the genome to identify polymorphisms which have different effects depending on the ancestral makeup of each individual. We use our test in two different populations of inbred mice and a yeast panel and demonstrate that these sorts of variable effect polymorphisms exist in 14 different physical traits in mice and 38 phenotypes in yeast as well as in murine gene expression. We use the term “polygenic epistasis” to distinguish these interactions from the more conventional two- or multi-locus interactions.

The Genetics of Variation of the Wave 1 Amplitude of the Mouse Auditory Brainstem Response

This is the first genome-wide association study with the Hybrid Mouse Diversity Panel (HDMP) to define the genetic landscape of the variation in the suprathreshold wave 1 amplitude of the auditory brainstem response (ABR) both pre- and post-noise exposure. This measure is correlated with the density of the auditory neurons (AN) and/or the compliment of synaptic ribbons within the inner hair cells of the mouse cochlea. We analyzed suprathreshold ABR for 635 mice from 102 HMDP strains pre- and post-noise exposure (108 dB 10 kHz octave band noise exposure for 2 h) using auditory brainstem response (ABR) wave 1 suprathreshold amplitudes as part of a large survey (Myint et al., Hear Res 332:113-120, 2016). Genome-wide significance levels for pre- and post-exposure wave 1 amplitude across the HMDP were performed using FaST-LMM. Synaptic ribbon counts (Ctbp2 and mGluR2) were analyzed for the extreme strains within the HMDP. ABR wave 1 amplitude varied across all strains of the HMDP with differences ranging between 2.42 and 3.82-fold pre-exposure and between 2.43 and 7.5-fold post-exposure with several tone burst stimuli (4 kHz, 8 kHz, 12 kHz, 16 kHz, 24 kHz, and 32 kHz). Immunolabeling of paired synaptic ribbons and glutamate receptors of strains with the highest and lowest wave 1 values pre- and post-exposure revealed significant differences in functional synaptic ribbon counts. Genome-wide association analysis identified genome-wide significant threshold associations on chromosome 3 (24 kHz; JAX00105429; p < 1.12E-06) and chromosome 16 (16 kHz; JAX00424604; p < 9.02E-07) prior to noise exposure and significant associations on chromosomes 2 (32 kHz; JAX00497967; p < 3.68E-08) and 13 (8 kHz; JAX00049416; 1.07E-06) after noise exposure. In order to prioritize candidate genes, we generated cis-eQTLs from microarray profiling of RNA isolated from whole cochleae in 64 of the tested strains.This is the first report of a genome-wide association analysis, controlled for population structure, to explore the genetic landscape of suprathreshold wave 1 amplitude measurements of the mouse ABR. We have defined two genomic regions associated with wave 1 amplitude variation prior to noise exposure and an additional two associated with variation after noise exposure.

Mouse Systems Genetics as a Prelude to Precision Medicine

Mouse models have been instrumental in understanding human disease biology and proposing possible new treatments. The precise control of the environment and genetic composition of mice allows more rigorous observations, but limits the generalizability and translatability of the results into human applications. In the era of precision medicine, strategies using mouse models have to be revisited to effectively emulate human populations. Systems genetics is one promising paradigm that may promote the transition to novel precision medicine strategies. Here, we review the state-of-the-art resources and discuss how mouse systems genetics helps to understand human diseases and to advance the development of precision medicine, with an emphasis on the existing resources and strategies.

Candidate Regulators of Dyslipidemia in Chromosome 1 Substitution Lines Using Liver Co-Expression Profiling Analysis

Dyslipidemia is a major risk factor for cardiovascular disease. Although many genetic factors have been unveiled, a large fraction of the phenotypic variance still needs further investigation. Chromosome 1 (Chr 1) harbors multiple gene loci that regulate blood lipid levels, and identifying functional genes in these loci has proved challenging. We constructed a mouse population, Chr 1 substitution lines (C1SLs), where only Chr 1 differs from the recipient strain C57BL/6J (B6), while the remaining chromosomes are unchanged. Therefore, any phenotypic variance between C1SLs and B6 can be attributed to the differences in Chr 1. In this study, we assayed plasma lipid and glucose levels in 13 C1SLs and their recipient strain B6. Through weighted gene co-expression network analysis of liver transcriptome and “guilty-by-association” study, eight associated modules of plasma lipid and glucose were identified. Further joint analysis of human genome wide association studies revealed 48 candidate genes. In addition, 38 genes located on Chr 1 were also uncovered, and 13 of which have been functionally validated in mouse models. These results suggest that C1SLs are ideal mouse models to identify functional genes on Chr 1 associated with complex traits, like dyslipidemia, by using gene co-expression network analysis.

Benefits and limitations of genome-wide association studies

Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS.

Systems genetics applications in metabolism research

The common forms of metabolic diseases are highly complex, involving hundreds of genes, environmental and lifestyle factors, age-related changes, sex differences and gut-microbiome interactions. Systems genetics is a population-based approach to address this complexity. In contrast to commonly used 'reductionist' approaches, such as gain or loss of function, that examine one element at a time, systems genetics uses high-throughput 'omics' technologies to quantitatively assess the many molecular differences among individuals in a population and then to relate these to physiologic functions or disease states. Unlike genome-wide association studies, systems genetics seeks to go beyond the identification of disease-causing genes to understand higher-order interactions at the molecular level. The purpose of this review is to introduce the systems genetics applications in the areas of metabolic and cardiovascular disease. Here, we explain how large clinical and omics-level data and databases from both human and animal populations are available to help researchers place genes in the context of pathways and networks and formulate hypotheses that can then be experimentally examined. We provide lists of such databases and examples of the integration of reductionist and systems genetics data. Among the important applications emerging is the development of improved nutritional and pharmacological strategies to address the rise of metabolic diseases.

Untangling the genomics of noise-induced hearing loss and tinnitus: Contributions of Mus musculus and Homo sapiens

Acoustic trauma is a feature of the industrial age, in general, and mechanized warfare, in particular. Noise-induced hearing loss (NIHL) and tinnitus have been the number 1 and number 2 disabilities at U.S. Veterans hospitals since 2006. In a reversal of original protocols to identify candidate genes associated with monogenic deafness disorders, unbiased genome-wide association studies now direct animal experiments in order to explore genetic variants common in Homo sapiens. However, even these approaches must utilize animal studies for validation of function and understanding of mechanisms. Animal research currently focuses on genetic expression profiles since the majority of variants occur in non-coding regions, implying regulatory divergences. Moving forward, it will be important in both human and animal research to define the phenotypes of hearing loss and tinnitus, as well as exposure parameters, in order to extricate genes related to acoustic trauma versus those related to aging. It has become clear that common disorders like acoustic trauma are influenced by large numbers of genes, each with small effects, which cumulatively lead to susceptibility to a disorder. A polygenic risk score, which aggregates these small effect sizes of multiple genes, may offer a more accurate description of risk for NIHL and/or tinnitus.

Whole Genome Sequencing of the Mutamouse Model Reveals Strain- and Colony-Level Variation, and Genomic Features of the Transgene Integration Site

The MutaMouse transgenic rodent model is widely used for assessing in vivo mutagenicity. Here, we report the characterization of MutaMouse's whole genome sequence and its genetic variants compared to the C57BL/6 reference genome. High coverage (>50X) next-generation sequencing (NGS) of whole genomes from multiple MutaMouse animals from the Health Canada (HC) colony showed ~5 million SNVs per genome, ~20% of which are putatively novel. Sequencing of two animals from a geographically separated colony at Covance indicated that, over the course of 23 years, each colony accumulated 47,847 (HC) and 17,677 (Covance) non-parental homozygous single nucleotide variants. We found no novel nonsense or missense mutations that impair the MutaMouse response to genotoxic agents. Pairing sequencing data with array comparative genomic hybridization (aCGH) improved the accuracy and resolution of copy number variants (CNVs) calls and identified 300 genomic regions with CNVs. We also used long-read sequence technology (PacBio) to show that the transgene integration site involved a large deletion event with multiple inversions and rearrangements near a retrotransposon. The MutaMouse genome gives important genetic context to studies using this model, offers insight on the mechanisms of structural variant formation, and contributes a framework to analyze aCGH results alongside NGS data.

Taar1 gene variants have a causal role in methamphetamine intake and response and interact with Oprm1

We identified a locus on mouse chromosome 10 that accounts for 60% of the genetic variance in methamphetamine intake in mice selectively bred for high versus low methamphetamine consumption. We nominated the trace amine-associated receptor 1 gene, Taar1, as the strongest candidate and identified regulation of the mu-opioid receptor 1 gene, Oprm1, as another contributor. This study exploited CRISPR-Cas9 to test the causal role of Taar1 in methamphetamine intake and a genetically-associated thermal response to methamphetamine. The methamphetamine-related traits were rescued, converting them to levels found in methamphetamine-avoiding animals. We used a family of recombinant inbred mouse strains for interval mapping and to examine independent and epistatic effects of Taar1 and Oprm1. Both methamphetamine intake and the thermal response mapped to Taar1 and the independent effect of Taar1 was dependent on genotype at Oprm1. Our findings encourage investigation of the contribution of Taar1 and Oprm1 variants to human methamphetamine addiction.

Analysis of the genomic architecture of a complex trait locus in hypertensive rat models links Tmem63c to kidney damage

Unraveling the genetic susceptibility of complex diseases such as chronic kidney disease remains challenging. Here, we used inbred rat models of kidney damage associated with elevated blood pressure for the comprehensive analysis of a major albuminuria susceptibility locus detected in these models. We characterized its genomic architecture by congenic substitution mapping, targeted next-generation sequencing, and compartment-specific RNA sequencing analysis in isolated glomeruli. This led to prioritization of transmembrane protein Tmem63c as a novel potential target. Tmem63c is differentially expressed in glomeruli of allele-specific rat models during onset of albuminuria. Patients with focal segmental glomerulosclerosis exhibited specific TMEM63C loss in podocytes. Functional analysis in zebrafish revealed a role for tmem63c in mediating the glomerular filtration barrier function. Our data demonstrate that integrative analysis of the genomic architecture of a complex trait locus is a powerful tool for identification of new targets such as Tmem63c for further translational investigation.

The human kidneys filter the entire volume of the blood about 300 times each day. This ability depends on specialized cells, known as podocytes, which wrap around some of the blood vessels in the kidney. These cells control which molecules leave the blood based on their size. Normally large molecules like proteins are blocked, while smaller molecules including waste products, toxins, excess water and salts pass through into the urine.

If this filtration system is damaged, by high blood pressure, for example, it can lead to chronic kidney disease. A hallmark of this disease, often called CKD for short, is high levels of the protein albumin in the urine. Previous studies involving rats with high blood pressure have found several regions of the genome that contribute to high levels of albumin in the urine, including one on chromosome 6. However, this region contains several genes and it was unclear which genes affected the condition.

Schulz et al. set out to narrow down the list and find specific genes that might contribute to elevated albumin in the urine of rats with high blood pressure. This search identified the gene for a protein called TMEM63c as a likely candidate. This protein spans the outer membrane of podocyte cells. Analysis of kidney biopsies showed that patients with chronic kidney disease also had low levels of this protein in their podocytes. Further experiments, this time in zebrafish, showed that reducing the activity of the gene for tmem63c led to damaged podocytes and a leakier filter in the kidneys.

The results suggest that this gene plays an important role in the integrity of the kidneys filtration barrier. It is possible that faulty versions of this gene are behind some cases of chronic kidney disease. If this proves to be the case, a better understanding of the role of this gene may lead to new treatments for the condition.

Genetic variation in thyroid folliculogenesis influences susceptibility to hypothyroidism-induced hearing impairment

Maternal and fetal sources of thyroid hormone are important for the development of many organ systems. Thyroid hormone deficiency causes variable intellectual disability and hearing impairment in mouse and man, but the basis for this variation is not clear. To explore this variation, we studied two thyroid hormone-deficient mouse mutants with mutations in pituitary-specific transcription factors, POU1F1 and PROP1, that render them unable to produce thyroid stimulating hormone. DW/J-Pou1f1^dw/dw mice have profound deafness and both neurosensory and conductive hearing impairment, while DF/B-Prop1^df/df mice have modest elevations in hearing thresholds consistent with developmental delay, eventually achieving normal hearing ability. The thyroid glands of Pou1f1 mutants are more severely affected than those of Prop1^df/df mice, and they produce less thyroglobulin during the neonatal period critical for establishing hearing. We previously crossed DW/J-Pou1f1^dw/+ and Cast/Ei mice and mapped a major locus on Chromosome 2 that protects against hypothyroidism-induced hearing impairment in Pou1f1^dw/dw mice: modifier of dw hearing (Mdwh). Here we refine the location of Mdwh by genotyping 196 animals with 876 informative SNPs, and we conduct novel mapping with a DW/J-Pou1f1^dw/+ and 129/P2 cross that reveals 129/P2 mice also have a protective Mdwh locus. Using DNA sequencing of DW/J and DF/B strains, we determined that the genes important for thyroid gland function within Mdwh vary in amino acid sequence between strains that are susceptible or resistant to hypothyroidism-induced hearing impairment. These results suggest that the variable effects of congenital hypothyroidism on the development of hearing ability are attributable to genetic variation in postnatal thyroid gland folliculogenesis and function.

Two Novel Candidate Genes for Insulin Secretion Identified by Comparative Genomics of Multiple Backcross Mouse Populations

To identify novel disease genes for type 2 diabetes (T2D) we generated two backcross populations of obese and diabetes-susceptible New Zealand Obese (NZO/HI) mice with the two lean mouse strains 129P2/OlaHsd and C3HeB/FeJ. Subsequent whole-genome linkage scans revealed 30 novel quantitative trait loci (QTL) for T2D-associated traits. The strongest association with blood glucose [12 cM, logarithm of the odds (LOD) 13.3] and plasma insulin (17 cM, LOD 4.8) was detected on proximal chromosome 7 (designated Nbg7p, NZO blood glucose on proximal chromosome 7) exclusively in the NZOxC3H crossbreeding, suggesting that the causal gene is contributed by the C3H genome. Introgression of the critical C3H fragment into the genetic NZO background by generating recombinant congenic strains and metabolic phenotyping validated the phenotype. For the detection of candidate genes in the critical region (30-46 Mb), we used a combined approach of haplotype and gene expression analysis to search for C3H-specific gene variants in the pancreatic islets, which appeared to be the most likely target tissue for the QTL. Two genes, Atp4a and Pop4, fulfilled the criteria from our candidate gene approaches. The knockdown of both genes in MIN6 cells led to decreased glucose-stimulated insulin secretion, indicating a regulatory role of both genes in insulin secretion, thereby possibly contributing to the phenotype linked to Nbg7p In conclusion, our combined- and comparative-cross analysis approach has successfully led to the identification of two novel diabetes susceptibility candidate genes, and thus has been proven to be a valuable tool for the discovery of novel disease genes.

Genetic contribution to waist-to-hip ratio in Mexican children and adolescents based on 12 loci validated in European adults

BACKGROUND/OBJECTIVES

The prevalence of abdominal obesity in Mexican children has risen dramatically in the past decade. Genome-wide association studies (GWAS) for waist-to-hip ratio (WHR) performed predominantly in European descent adult  populations have identified multiple single-nucleotide polymorphisms (SNPs) with larger effects in women. The contribution of these SNPs to WHR in non-European children is unknown.

SUBJECTS/METHODS

Mexican children and adolescents (N = 1421, 5-17 years) were recruited in Mexico City. Twelve GWAS SNPs were genotyped using TaqMan Open Array and analyzed individually and as a gene score (GS).

RESULTS

Mexican boys and girls displayed 2.81 ± 0.29 and 3.10 ± 0.31 WHR standard deviations higher than children and adolescents from the United States. WHR was positively associated with TG (β = 0.733 ± 0.190, P = 1.1 × 10^-4) and LDL-C (β = 0.491 ± 0.203, P = 1.6 × 10^-2), and negatively associated with HDL-C (β = -0.652 ± 0.195, P = 8.0 × 10^-4), independently of body mass index. The effect allele frequency (EAF) of 8 of 12 (67%) SNPs differed significantly (P < 4.17 × 10^-3) in Mexican children and European adults, with no evidence of effect allele enrichment in both populations (4 depleted and 4 enriched; binomial test, P = 1). Ten out of 12 SNPs (83.3%) had effects that were directionally consistent with those reported in GWAS (P = 0.04). HOXC13 rs1443512 displayed the best fit when modeled recessively, and was significantly associated with WHR under a recessive mode of inheritance (β = 0.140 ± 0.06, P = 2.3 × 10^-2). Significant interactions with sex were also observed for HOXC13 rs1443512 and the GS on WHR (P = 2.2 × 10^-2 and 1.2 × 10^-2, respectively). HOXC13 rs1443512 (β = 0.022 ± 0.012, P = 4.7 × 10^-2) and the GS (β = 0.007 ± 0.003, P = 7.0 × 10^-3) were significantly associated with WHR in girls only.

CONCLUSIONS

This study demonstrates that Mexican children are at high risk for abdominal obesity and detrimental lipid profiles. Our data support a partial transferability of sex-specific European GWAS WHR association signals in children and adolescents from the admixed Mexican population.

Fine-mapping of 98 obesity loci in Mexican children

BACKGROUND/OBJECTIVES

Mexico has one of the highest prevalence of childhood obesity in the world. Genome-wide association studies (GWAS) for obesity have identified multiple single-nucleotide polymorphisms (SNPs) in populations of European, East Asian, and African descent. The contribution of these loci to obesity in Mexican children is unclear. We assessed the transferability of 98 obesity loci in Mexican children and fine-mapped the association signals.

SUBJECTS/METHODS

The study included 405 and 390 Mexican children with normal weight and obesity. Participants were genotyped with a genome-wide dense SNP array designed for Latino populations, allowing for the analysis of GWAS index SNPs as well as fine-mapping SNPs, totaling 750 SNPs covering 98 loci. Two genetic risk scores (GRS) were constructed: a "discovery GRS" and a "best-associated GRS", representing the number of effect alleles at the GWAS index SNPs and at the best-associated SNPs after fine-mapping for each subject.

RESULTS

Seventeen obesity loci were significantly associated with obesity, and five had fine-mapping SNPs significantly better associated with obesity than their corresponding GWAS index SNPs in Mexican children. Six obesity-associated SNPs significantly departed from additive to dominant (N = 5) or recessive (N = 1) models, and a significant interaction was found between rs274609 (TNNI3K) and rs1010553 (ITIH4) on childhood obesity risk. The best-associated GRS was significantly more associated with childhood obesity (OR = 1.21 per additional risk allele [95%CI:1.17-1.25], P = 4.8 × 10^-25) than the discovery GRS (OR = 1.05 per additional risk allele [95%CI:1.02-1.08], P = 8.0 × 10^-4), and was also associated with waist-to-hip ratio, fasting glucose, fasting insulin and triglyceride levels, the association being mediated by obesity. An overall depletion of obesity risk alleles was observed in Mexican children with normal weight when compared to GWAS discovery populations.

CONCLUSIONS

Our study indicates a partial transferability of GWAS obesity loci in Mexican children, and supports the pertinence of post-GWAS fine-mapping experiments in the admixed Mexican population.

High-Resolution Maps of Mouse Reference Populations

Genetic reference panels are widely used to map complex, quantitative traits in model organisms. We have generated new high-resolution genetic maps of 259 mouse inbred strains from recombinant inbred strain panels (C57BL/6J × DBA/2J, ILS/IbgTejJ × ISS/IbgTejJ, and C57BL/6J × A/J) and chromosome substitution strain panels (C57BL/6J-Chr#<A/J>, C57BL/6J-Chr#<PWD/Ph>, and C57BL/6J-Chr#<MSM/Ms>). We genotyped all samples using the Affymetrix Mouse Diversity Array with an average intermarker spacing of 4.3 kb. The new genetic maps provide increased precision in the localization of recombination breakpoints compared to the previous maps. Although the strains were presumed to be fully inbred, we found residual heterozygosity in 40% of individual mice from five of the six panels. We also identified de novo deletions and duplications, in homozygous or heterozygous state, ranging in size from 21 kb to 8.4 Mb. Almost two-thirds (46 out of 76) of these deletions overlap exons of protein coding genes and may have phenotypic consequences. Twenty-nine putative gene conversions were identified in the chromosome substitution strains. We find that gene conversions are more likely to occur in regions where the homologous chromosomes are more similar. The raw genotyping data and genetic maps of these strain panels are available at http://churchill-lab.jax.org/website/MDA.

Why do Individuals Differ in Viral Susceptibility? A Story Told by Model Organisms

Viral susceptibility and disease progression is determined by host genetic variation that underlies individual differences. Genetic polymorphisms that affect the phenotype upon infection have been well-studied for only a few viruses, such as HIV-1 and Hepatitis C virus. However, even for well-studied viruses the genetic basis of individual susceptibility differences remains elusive. Investigating the effect of causal polymorphisms in humans is complicated, because genetic methods to detect rare or small-effect polymorphisms are limited and genetic manipulation is not possible in human populations. Model organisms have proven a powerful experimental platform to identify and characterize polymorphisms that underlie natural variations in viral susceptibility using quantitative genetic tools. We summarize and compare the genetic tools available in three main model organisms, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans, and illustrate how these tools can be applied to detect polymorphisms that determine the viral susceptibility. Finally, we analyse how candidate polymorphisms from model organisms can be used to shed light on the underlying mechanism of individual variation. Insights in causal polymorphisms and mechanisms underlying individual differences in viral susceptibility in model organisms likely provide a better understanding in humans.

Widespread epistasis regulates glucose homeostasis and gene expression

The relative contributions of additive versus non-additive interactions in the regulation of complex traits remains controversial. This may be in part because large-scale epistasis has traditionally been difficult to detect in complex, multi-cellular organisms. We hypothesized that it would be easier to detect interactions using mouse chromosome substitution strains that simultaneously incorporate allelic variation in many genes on a controlled genetic background. Analyzing metabolic traits and gene expression levels in the offspring of a series of crosses between mouse chromosome substitution strains demonstrated that inter-chromosomal epistasis was a dominant feature of these complex traits. Epistasis typically accounted for a larger proportion of the heritable effects than those due solely to additive effects. These epistatic interactions typically resulted in trait values returning to the levels of the parental CSS host strain. Due to the large epistatic effects, analyses that did not account for interactions consistently underestimated the true effect sizes due to allelic variation or failed to detect the loci controlling trait variation. These studies demonstrate that epistatic interactions are a common feature of complex traits and thus identifying these interactions is key to understanding their genetic regulation.

Most complex traits and diseases are regulated by the combined influence of multiple genetic variants. However, it remains controversial whether these genetic variants independently influence complex traits, and therefore the impact of each variant could be simply added together (additivity), or whether the variants work together to influence trait variation, in which case the combined impact of multiple variants would differ from the summed impact of each individual variant (epistasis). In this study in mice, we discovered that the genetic regulation of blood sugar levels and gene expression in the liver were predominantly controlled by non-additive interactions, whereas body weight was predominantly controlled by additive interactions. Remarkably, the expression level of nearly 25% of all genes in the liver was controlled by non-additive interactions. The non-additive interactions typically acted to return trait values to the levels detected in control mice, thus contributing to a reduction in trait variation. We also demonstrated that not accounting for non-additive interactions significantly underestimated the phenotypic effect of a genetic variant on a particular genetic background, suggesting that many previously identified risk loci may have significantly larger effects on disease susceptibility in a subset of individuals. These studies highlight the importance of understanding interactions between genetic variants to better understand disease risk and personalize clinical care.

How mice are indispensable for understanding obesity and diabetes genetics

PURPOSE OF REVIEW

The task of cataloging human genetic variation and its relation to disease is rapidly approaching completion. The new challenge is to discover the function of disease-associated genes and to understand the pathways that lead to human disease. We propose that achieving this new level of understanding will increasingly rely on the use of model organisms. We discuss the advantages of the mouse as a model organism to our understanding of human disease.

RECENT FINDINGS

The collection of available mouse strains represents as much genetic and phenotypic variation as is found in the human population. However, unlike humans, mice can be subjected to experimental breeding protocols and the availability of tissues allows for a far greater and deeper level of phenotyping. New methods for gene editing make it relatively easy to create mouse models of known human mutations. The distinction between genetic and epigenetic inheritance can be studied in great detail. Various experimental protocols enable the exploration of the role of the microbiome in physiology and disease.

SUMMARY

We propose that there will be an interdependence between human and model organism research. Technological advances and new genetic screening platforms in the mouse have greatly improved the path to gene discovery and mechanistic studies of gene function.

Resources for Systems Genetics

A key characteristic of systems genetics is its reliance on populations that vary to a greater or lesser degree in genetic complexity-from highly admixed populations such as the Collaborative Cross and Diversity Outcross to relatively simple crosses such as sets of consomic strains and reduced complexity crosses. This protocol is intended to help investigators make more informed decisions about choices of resources given different types of questions. We consider factors such as costs, availability, and ease of breeding for common scenarios. In general, we recommend using complementary resources and minimizing depth of resampling of any given genome or strain.

Regulatory changes in two chemoreceptor genes contribute to a Caenorhabditis elegans QTL for foraging behavior

Natural isolates of C. elegans differ in their sensitivity to pheromones that inhibit exploratory behavior. Previous studies identified a QTL for pheromone sensitivity that includes alternative alleles of srx-43, a chemoreceptor that inhibits exploration through its activity in ASI sensory neurons. Here we show that the QTL is multigenic and includes alternative alleles of srx-44, a second chemoreceptor gene that modifies pheromone sensitivity. srx-44 either promotes or inhibits exploration depending on its expression in the ASJ or ADL sensory neurons, respectively. Naturally occurring pheromone insensitivity results in part from previously described changes in srx-43 expression levels, and in part from increased srx-44 expression in ASJ, which antagonizes ASI and ADL. Antagonism between the sensory neurons results in cellular epistasis that is reflected in their transcription of insulin genes that regulate exploration. These results and genome-wide evidence suggest that chemoreceptor genes may be preferred sites of adaptive variation in C. elegans.

DOI:http://dx.doi.org/10.7554/eLife.21454.001

Transcriptome Profiling in Rat Inbred Strains and Experimental Cross Reveals Discrepant Genetic Architecture of Genome-Wide Gene Expression

To test the impact of genetic heterogeneity on cis- and trans-mediated mechanisms of gene expression regulation, we profiled the transcriptome of adipose tissue in 20 inbred congenic strains derived from diabetic Goto-Kakizaki (GK) rats and Brown-Norway (BN) controls, which contain well-defined blocks (1-183 Mb) of genetic polymorphisms, and in 123 genetically heterogeneous rats of an (GK × BN)F2 offspring. Within each congenic we identified 73-1351 differentially expressed genes (DEGs), only 7.7% of which mapped within the congenic blocks, and which may be regulated in cis The remainder localized outside the blocks, and therefore must be regulated in trans Most trans-regulated genes exhibited approximately twofold expression changes, consistent with monoallelic expression. Altered biological pathways were replicated between congenic strains sharing blocks of genetic polymorphisms, but polymorphisms at different loci also had redundant effects on transcription of common distant genes and pathways. We mapped 2735 expression quantitative trait loci (eQTL) in the F2 cross, including 26% predominantly cis-regulated genes, which validated DEGs in congenic strains. A hotspot of >300 eQTL in a 10 cM region of chromosome 1 was enriched in DEGs in a congenic strain. However, many DEGs among GK, BN and congenic strains did not replicate as eQTL in F2 hybrids, demonstrating distinct mechanisms of gene expression when alleles segregate in an outbred population or are fixed homozygous across the entire genome or in short genomic regions. Our analysis provides conceptual advances in our understanding of the complex architecture of genome expression and pathway regulation, and suggests a prominent impact of epistasis and monoallelic expression on gene transcription.

Genome Sequencing of Chromosome 1 Substitution Lines Derived from Chinese Wild Mice Revealed a Unique Resource for Genetic Studies of Complex Traits

Mouse resources such as Collaborative Cross, outbred stocks, Hybrid Mouse Diversity Panel, and chromosome substitution strains have been instrumental to many progresses in the studies of complex traits genetics. We have established a population of chromosome 1 (Chr 1) substitution lines (C1SLs) in which donor chromosomes were derived from Chinese wild mice. Genome sequencing of 18 lines of this population showed that Chr 1 had been replaced by the donor chromosome. About 4.5 million unique single nucleotide polymorphisms and indels were discovered on Chr 1, of which 1.3 million were novel. Compared with sequenced classical inbred strains, Chr 1 of each C1SL had fivefold more variants, and more loss of function and potentially regulatory variants. Further haplotype analysis showed that the donor chromosome accumulated more historical recombination events, with the largest haplotype block being only 100 kb, and about 57% of the blocks were <1 kb. Subspecies origin analysis showed that these chromosomes had a mosaic genome structure that dominantly originated from Mus musculus musculus and M. m. castaneus subspecies, except for the C57BL/6J-Chr1^KM line from M. m. domesticus. In addition, phenotyping four of these lines on blood biochemistry suggested that there were substantial phenotypic variations among our lines, especially line C57BL/6J-Chr1^HZ and donor strain C57BL/6J. Further gene ontology enrichment revealed that the differentially expressed genes among liver-expressed genes between C57BL/6J and C57BL/6J-Chr1^HZ were enriched in lipid metabolism biological processes. All these characteristics enable C1SLs to be a unique resource for identifying and fine mapping quantitative trait loci on mouse Chr 1, and carrying out systems genetics studies of complex traits.

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series

Background

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits.

Methods

We used systematic metabotyping by ¹H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block.

Results

Despite strong genomic similarities (95–99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing.

Conclusions

These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0352-6) contains supplementary material, which is available to authorized users.

Consomic mouse strain selection based on effect size measurement, statistical significance testing and integrated behavioral z-scoring: focus on anxiety-related behavior and locomotion

Background

Selecting chromosome substitution strains (CSSs, also called consomic strains/lines) used in the search for quantitative trait loci (QTLs) consistently requires the identification of the respective phenotypic trait of interest and is simply based on a significant difference between a consomic and host strain. However, statistical significance as represented by P values does not necessarily predicate practical importance. We therefore propose a method that pays attention to both the statistical significance and the actual size of the observed effect. The present paper extends on this approach and describes in more detail the use of effect size measures (Cohen’s d, partial eta squared - η_p²) together with the P value as statistical selection parameters for the chromosomal assignment of QTLs influencing anxiety-related behavior and locomotion in laboratory mice.

Results

The effect size measures were based on integrated behavioral z-scoring and were calculated in three experiments: (A) a complete consomic male mouse panel with A/J as the donor strain and C57BL/6J as the host strain. This panel, including host and donor strains, was analyzed in the modified Hole Board (mHB). The consomic line with chromosome 19 from A/J (CSS-19A) was selected since it showed increased anxiety-related behavior, but similar locomotion compared to its host. (B) Following experiment A, female CSS-19A mice were compared with their C57BL/6J counterparts; however no significant differences and effect sizes close to zero were found. (C) A different consomic mouse strain (CSS-19PWD), with chromosome 19 from PWD/PhJ transferred on the genetic background of C57BL/6J, was compared with its host strain. Here, in contrast with CSS-19A, there was a decreased overall anxiety in CSS-19PWD compared to C57BL/6J males, but not locomotion.

Conclusions

This new method shows an improved way to identify CSSs for QTL analysis for anxiety-related behavior using a combination of statistical significance testing and effect sizes. In addition, an intercross between CSS-19A and CSS-19PWD may be of interest for future studies on the genetic background of anxiety-related behavior.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0411-4) contains supplementary material, which is available to authorized users.

The Hybrid Mouse Diversity Panel: a resource for systems genetics analyses of metabolic and cardiovascular traits

The Hybrid Mouse Diversity Panel (HMDP) is a collection of approximately 100 well-characterized inbred strains of mice that can be used to analyze the genetic and environmental factors underlying complex traits. While not nearly as powerful for mapping genetic loci contributing to the traits as human genome-wide association studies, it has some important advantages. First, environmental factors can be controlled. Second, relevant tissues are accessible for global molecular phenotyping. Finally, because inbred strains are renewable, results from separate studies can be integrated. Thus far, the HMDP has been studied for traits relevant to obesity, diabetes, atherosclerosis, osteoporosis, heart failure, immune regulation, fatty liver disease, and host-gut microbiota interactions. High-throughput technologies have been used to examine the genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes of the mice under various environmental conditions. All of the published data are available and can be readily used to formulate hypotheses about genes, pathways and interactions.

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.

Influenza H3N2 infection of the collaborative cross founder strains reveals highly divergent host responses and identifies a unique phenotype in CAST/EiJ mice

BACKGROUND

Influenza A virus is a zoonotic pathogen that poses a major threat to human and animal health. The severe course of influenza infection is not only influenced by viral virulence factors but also by individual differences in the host response. To determine the extent to which the genetic background can modulate severity of an infection, we studied the host responses to influenza infections in the eight genetically highly diverse Collaborative Cross (CC) founder mouse strains.

RESULTS

We observed highly divergent host responses between the CC founder strains with respect to survival, body weight loss, hematological parameters in the blood, relative lung weight and viral load. Mouse strain was the main factor with highest effect size on body weight loss after infection, demonstrating that this phenotype was highly heritable. Sex represented another significant main effect, although it was less strong. Analysis of survival rates and mean time to death suggested three groups of susceptibility phenotypes: highly susceptible (A/J, CAST/EiJ, WSB/EiJ), intermediate susceptible (C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ) and highly resistant strains (NZO/HlLtJ, PWK/PhJ). These three susceptibility groups were significantly different with respect to death/survival counts. Viral load was significantly different between susceptible and resistant strains but not between intermediate and highly susceptible strains. CAST/EiJ mice showed a unique phenotype. Despite high viral loads in their lungs, CAST/EiJ mice exhibited low counts of infiltrating granulocytes and showed increased numbers of macrophages in the lung. Histological studies of infected lungs and transcriptome analyses of peripheral blood cells and lungs confirmed an abnormal response in the leukocyte recruitment in CAST/EiJ mice.

CONCLUSIONS

The eight CC founder strains exhibited a large diversity in their response to influenza infections. Therefore, the CC will represent an ideal mouse genetic reference population to study the influence of genetic variation on the susceptibility and resistance to influenza infections which will be important to understand individual variations of disease severity in humans. The unique phenotype combination in the CAST/EiJ strain resembles human leukocyte adhesion deficiency and may thus represent a new mouse model to understand this and related abnormal immune responses to infections in humans.

Genetic control of obesity, glucose homeostasis, dyslipidemia and fatty liver in a mouse model of diet-induced metabolic syndrome

BACKGROUND/OBJECTIVES

Both genetic and dietary factors contribute to the metabolic syndrome (MetS) in humans and animal models. Characterizing their individual roles as well as relationships among these factors is critical for understanding MetS pathogenesis and developing effective therapies. By studying phenotypic responsiveness to high-risk versus control diet in two inbred mouse strains and their derivatives, we estimated the relative contributions of diet and genetic background to MetS, characterized strain-specific combinations of MetS conditions, and tested genetic and phenotypic complexity on a single substituted chromosome.

METHODS

Ten measures of metabolic health were assessed in susceptible C57BL/6 J and resistant A/J male mice fed either a control or a high-fat, high-sucrose (HFHS) diet, permitting estimates of the relative influences of strain, diet and strain-diet interactions for each trait. The same traits were measured in a panel of C57BL/6 J (B6)-Chr(A/J) chromosome substitution strains (CSSs) fed the HFHS diet, followed by characterization of interstrain relationships, covariation among metabolic traits and quantitative trait loci (QTLs) on Chromosome 10.

RESULTS

We identified significant genetic contributions to nine of ten metabolic traits and significant dietary influence on eight. Significant strain-diet interaction effects were detected for four traits. Although a range of HFHS-induced phenotypes were observed among the CSSs, significant associations were detected among all traits but one. Strains were grouped into three clusters based on overall phenotype and specific CSSs were identified with distinct and reproducible trait combinations. Finally, several Chr10 regions were shown to control the severity of MetS conditions.

CONCLUSIONS

Generally strong genetic and dietary effects validate these CSSs as a multifactorial model of MetS. Although traits tended to segregate together, considerable phenotypic heterogeneity suggests that underlying genetic factors influence their co-occurrence and severity. Identification of multiple QTLs within and among strains highlights both the complexity of genetically regulated, diet-induced MetS and the ability of CSSs to prioritize candidate loci for mechanistic studies.