The Collaborative Cross, a community resource for the genetic analysis of complex traits

53BP1 Repair Kinetics for Prediction of In Vivo Radiation Susceptibility in 15 Mouse Strains

We present a novel mathematical formalism to predict the kinetics of DNA damage repair after exposure to both low- and high-LET radiation (X rays; 350 MeV/n 40Ar; 600 MeV/n 56Fe). Our method is based on monitoring DNA damage repair protein 53BP1 that forms radiation-induced foci (RIF) at locations of DNA double-strand breaks (DSB) in the nucleus and comparing its expression in primary skin fibroblasts isolated from 15 mice strains. We previously reported strong evidence for clustering of nearby DSB into single repair units as opposed to the classic "contact-first" model where DSB are considered immobile. Here we apply this clustering model to evaluate the number of remaining RIF over time. We also show that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the characteristic time constant of RIF repair measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated not only with radiation-induced cellular survival in vivo, but also with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk.

Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning

BACKGROUND

Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational approaches that effectively address its heterogeneity. To meet these shortcomings, we show that Diversity Outbred (DO) mice reflect human-like genetic diversity and develop human-like lung granulomas when infected with Mycobacterium tuberculosis (M.tb) .

METHODS

Following M.tb infection, a "supersusceptible" phenotype develops in approximately one-third of DO mice characterized by rapid morbidity and mortality within 8 weeks. These supersusceptible DO mice develop lung granulomas patterns akin to humans. This led us to utilize deep learning to identify supersusceptibility from hematoxylin & eosin (H&E) lung tissue sections utilizing only clinical outcomes (supersusceptible or not-supersusceptible) as labels.

FINDINGS

The proposed machine learning model diagnosed supersusceptibility with high accuracy (91.50 ± 4.68%) compared to two expert pathologists using H&E stained lung sections (94.95% and 94.58%). Two non-experts used the imaging biomarker to diagnose supersusceptibility with high accuracy (88.25% and 87.95%) and agreement (96.00%). A board-certified veterinary pathologist (GB) examined the imaging biomarker and determined the model was making diagnostic decisions using a form of granuloma necrosis (karyorrhectic and pyknotic nuclear debris). This was corroborated by one other board-certified veterinary pathologist. Finally, the imaging biomarker was quantified, providing a novel means to convert visual patterns within granulomas to data suitable for statistical analyses.

IMPLICATIONS

Overall, our results have translatable implication to improve our understanding of TB and also to the broader field of computational pathology in which clinical outcomes alone can drive automatic identification of interpretable imaging biomarkers, knowledge discovery, and validation of existing clinical biomarkers.

FUNDING

National Institutes of Health and American Lung Association.

Inferring the Allelic Series at QTL in Multiparental Populations

Multiparental populations (MPPs) are experimental populations in which the genome of every individual is a mosaic of known founder haplotypes. These populations are useful for detecting quantitative trait loci (QTL) because tests of association can leverage inferred founder haplotype descent. It is difficult, however, to determine how haplotypes at a locus group into distinct functional alleles, termed the allelic series. The allelic series is important because it provides information about the number of causal variants at a QTL and their combined effects. In this study, we introduce a fully Bayesian model selection framework for inferring the allelic series. This framework accounts for sources of uncertainty found in typical MPPs, including the number and composition of functional alleles. Our prior distribution for the allelic series is based on the Chinese restaurant process, a relative of the Dirichlet process, and we leverage its connection to the coalescent to introduce additional prior information about haplotype relatedness via a phylogenetic tree. We evaluate our approach via simulation and apply it to QTL from two MPPs: the Collaborative Cross (CC) and the Drosophila Synthetic Population Resource (DSPR). We find that, although posterior inference of the exact allelic series is often uncertain, we are able to distinguish biallelic QTL from more complex multiallelic cases. Additionally, our allele-based approach improves haplotype effect estimation when the true number of functional alleles is small. Our method, Tree-Based Inference of Multiallelism via Bayesian Regression (TIMBR), provides new insight into the genetic architecture of QTL in MPPs.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions

BACKGROUND

Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans.

RESULTS

A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation.

CONCLUSIONS

This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Container-aided integrative QTL and RNA-seq analysis of Collaborative Cross mice supports distinct sex-oriented molecular modes of response in obesity

BACKGROUND

The Collaborative Cross (CC) mouse population is a valuable resource to study the genetic basis of complex traits, such as obesity. Although the development of obesity is influenced by environmental factors, underlying genetic mechanisms play a crucial role in the response to these factors. The interplay between the genetic background and the gene expression pattern can provide further insight into this response, but we lack robust and easily reproducible workflows to integrate genomic and transcriptomic information in the CC mouse population.

RESULTS

We established an automated and reproducible integrative workflow to analyse complex traits in the CC mouse genetic reference panel at the genomic and transcriptomic levels. We implemented the analytical workflow to assess the underlying genetic mechanisms of host susceptibility to diet induced obesity and integrated these results with diet induced changes in the hepatic gene expression of susceptible and resistant mice. Hepatic gene expression differs significantly between obese and non-obese mice, with a significant sex effect, where male and female mice exhibit different responses and coping mechanisms.

CONCLUSION

Integration of the data showed that different genes but similar pathways are involved in the genetic susceptibility and disturbed in diet induced obesity. Genetic mechanisms underlying susceptibility to high-fat diet induced obesity are different in female and male mice. The clear distinction we observed in the systemic response to the high-fat diet challenge and to obesity between male and female mice points to the need for further research into distinct sex-related mechanisms in metabolic disease.

Development of a Model of the Acute and Delayed Effects of High Dose Radiation Exposure in Jackson Diversity Outbred Mice; Comparison to Inbred C57BL/6 Mice

Development of medical countermeasures against radiation relies on robust animal models for efficacy testing. Mouse models have advantages over larger species due to economics, ease of conducting aging studies, existence of historical databases, and research tools allowing for sophisticated mechanistic studies. However, the radiation dose-response relationship of inbred strains is inherently steep and sensitive to experimental variables, and inbred models have been criticized for lacking genetic diversity. Jackson Diversity Outbred (JDO) mice are the most genetically diverse strain available, developed by the Collaborative Cross Consortium using eight founder strains, and may represent a more accurate model of humans than inbred strains. Herein, models of the Hematopoietic-Acute Radiation Syndrome and the Delayed Effects of Acute Radiation Exposure were developed in JDO mice and compared to inbred C57BL/6. The dose response relationship curve in JDO mice mirrored the more shallow curves of primates and humans, characteristic of genetic diversity. JDO mice were more radioresistant than C57BL/6 and differed in sensitivity to antibiotic countermeasures. The model was validated with pegylated-G-CSF, which provided significantly enhanced 30-d survival and accelerated blood recovery. Long-term JDO survivors exhibited increased recovery of blood cells and functional bone marrow hematopoietic progenitors compared to C57BL/6. While JDO hematopoietic stem cells declined more in number, they maintained a greater degree of quiescence compared to C57BL/6, which is essential for maintaining function. These JDO radiation models offer many of the advantages of small animals with the genetic diversity of large animals, providing an attractive alternative to currently available radiation animal models.

Identification of novel loci controlling inflammatory bowel disease susceptibility utilizing the genetic diversity of wild-derived mice

Inflammatory bowel disease (IBD) is a complex disorder that imposes a growing health burden. Multiple genetic associations have been identified in IBD, but the mechanisms underlying many of these associations are poorly understood. Animal models are needed to bridge this gap, but conventional laboratory mouse strains lack the genetic diversity of human populations. To more accurately model human genetic diversity, we utilized a panel of chromosome (Chr) substitution strains, carrying chromosomes from the wild-derived and genetically divergent PWD/PhJ (PWD) strain on the commonly used C57BL/6J (B6) background, as well as their parental B6 and PWD strains. Two models of IBD were used, TNBS- and DSS-induced colitis. Compared with B6 mice, PWD mice were highly susceptible to TNBS-induced colitis, but resistant to DSS-induced colitis. Using consomic mice, we identified several PWD-derived loci that exhibited profound effects on IBD susceptibility. The most pronounced of these were loci on Chr1 and Chr2, which yielded high susceptibility in both IBD models, each acting at distinct phases of the disease. Leveraging transcriptomic data from B6 and PWD immune cells, together with a machine learning approach incorporating human IBD genetic associations, we identified lead candidate genes, including Itga4, Pip4k2a, Lcn10, Lgmn, and Gpr65.

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.

A Thalamic Orphan Receptor Drives Variability in Short-Term Memory

Working memory is a form of short-term memory that involves maintaining and updating task-relevant information toward goal-directed pursuits. Classical models posit persistent activity in prefrontal cortex (PFC) as a primary neural correlate, but emerging views suggest additional mechanisms may exist. We screened ∼200 genetically diverse mice on a working memory task and identified a genetic locus on chromosome 5 that contributes to a substantial proportion (17%) of the phenotypic variance. Within the locus, we identified a gene encoding an orphan G-protein-coupled receptor, Gpr12, which is sufficient to drive substantial and bidirectional changes in working memory. Molecular, cellular, and imaging studies revealed that Gpr12 enables high thalamus-PFC synchrony to support memory maintenance and choice accuracy. These findings identify an orphan receptor as a potent modifier of short-term memory and supplement classical PFC-based models with an emerging thalamus-centric framework for the mechanistic understanding of working memory.

Alcohol Sensitivity as an Endophenotype of Alcohol Use Disorder: Exploring Its Translational Utility between Rodents and Humans

Alcohol use disorder (AUD) is a complex, chronic, relapsing disorder with multiple interacting genetic and environmental influences. Numerous studies have verified the influence of genetics on AUD, yet the underlying biological pathways remain unknown. One strategy to interrogate complex diseases is the use of endophenotypes, which deconstruct current diagnostic categories into component traits that may be more amenable to genetic research. In this review, we explore how an endophenotype such as sensitivity to alcohol can be used in conjunction with rodent models to provide mechanistic insights into AUD. We evaluate three alcohol sensitivity endophenotypes (stimulation, intoxication, and aversion) for their translatability across human and rodent research by examining the underlying neurobiology and its relationship to consumption and AUD. We show examples in which results gleaned from rodents are successfully integrated with information from human studies to gain insight in the genetic underpinnings of AUD and AUD-related endophenotypes. Finally, we identify areas for future translational research that could greatly expand our knowledge of the biological and molecular aspects of the transition to AUD with the broad hope of finding better ways to treat this devastating disorder.

Age and Genetic Background Modify Hybrid Male Sterility in House Mice

Hybrid male sterility (HMS) contributes to reproductive isolation commonly observed among house mouse (Mus musculus) subspecies, both in the wild and in laboratory crosses. Incompatibilities involving specific Prdm9 alleles and certain Chromosome (Chr) X genotypes are known determinants of fertility and HMS, and previous work in the field has demonstrated that genetic background modifies these two major loci. We constructed hybrids that have identical genotypes at Prdm9 and identical X chromosomes, but differ widely across the rest of the genome. In each case, we crossed female PWK/PhJ mice representative of the M. m. musculus subspecies to males from a classical inbred strain representative of M. m. domesticus: 129S1/SvImJ, A/J, C57BL/6J, or DBA/2J. We detected three distinct trajectories of fertility among the hybrids using breeding experiments. The PWK129S1 males were always infertile. PWKDBA2 males were fertile, despite their genotypes at the major HMS loci. We also observed age-dependent changes in fertility parameters across multiple genetic backgrounds. The PWKB6 and PWKAJ males were always infertile before 12 weeks and after 35 weeks. However, some PWKB6 and PWKAJ males were transiently fertile between 12 and 35 weeks. This observation could resolve previous contradictory reports about the fertility of PWKB6. Taken together, these results point to multiple segregating HMS modifier alleles, some of which have age-related modes of action. The ultimate identification of these alleles and their age-related mechanisms will advance understanding both of the genetic architecture of HMS and of how reproductive barriers are maintained between house mouse subspecies.

Baseline T cell immune phenotypes predict virologic and disease control upon SARS-CoV infection

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans, from asymptomatic or mild disease to severe disease that can require mechanical ventilation. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from indiviuals that go on to become infected with SARS-CoV-2. Here, we utilized data from a screen of genetically diverse mice from the Collaborative Cross (CC) infected with SARS-CoV to determine whether circulating baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Further, early control of virus in the lung correlates with an increased abundance of activated CD4 and CD8 T cells and regulatory T cells prior to infections across strains. A basal propensity of T cells to express IFNg and IL17 over TNFa also correlated with early viral control. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. While future studies of human samples prior to infection with SARS-CoV-2 are required, our studies in mice with SARS-CoV serve as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease.

SUMMARY

We used a screen of genetically diverse mice from the Collaborative Cross infected with mouse-adapted SARS-CoV in combination with comprehensive pre-infection immunophenotyping to identify baseline circulating immune correlates of severe virologic and clinical outcomes upon SARS-CoV infection.

Naive Pluripotent Stem Cells Exhibit Phenotypic Variability that Is Driven by Genetic Variation

Variability among pluripotent stem cell (PSC) lines is a prevailing issue that hampers not only experimental reproducibility but also large-scale applications and personalized cell-based therapy. This variability could result from epigenetic and genetic factors that influence stem cell behavior. Naive culture conditions minimize epigenetic fluctuation, potentially overcoming differences in PSC line differentiation potential. Here we derived PSCs from distinct mouse strains under naive conditions and show that lines from distinct genetic backgrounds have divergent differentiation capacity, confirming a major role for genetics in PSC phenotypic variability. This is explained in part through inconsistent activity of extra-cellular signaling, including the Wnt pathway, which is modulated by specific genetic variants. Overall, this study shows that genetic background plays a dominant role in driving phenotypic variability of PSCs.

Antipsychotic Behavioral Phenotypes in the Mouse Collaborative Cross Recombinant Inbred Inter-Crosses (RIX)

Schizophrenia is an idiopathic disorder that affects approximately 1% of the human population, and presents with persistent delusions, hallucinations, and disorganized behaviors. Antipsychotics are the standard pharmacological treatment for schizophrenia, but are frequently discontinued by patients due to inefficacy and/or side effects. Chronic treatment with the typical antipsychotic haloperidol causes tardive dyskinesia (TD), which manifests as involuntary and often irreversible orofacial movements in around 30% of patients. Mice treated with haloperidol develop many of the features of TD, including jaw tremors, tongue protrusions, and vacuous chewing movements (VCMs). In this study, we used genetically diverse Collaborative Cross (CC) recombinant inbred inter-cross (RIX) mice to elucidate the genetic basis of antipsychotic-induced adverse drug reactions (ADRs). We performed a battery of behavioral tests in 840 mice from 73 RIX lines (derived from 62 CC strains) treated with haloperidol or placebo in order to monitor the development of ADRs. We used linear mixed models to test for strain and treatment effects. We observed highly significant strain effects for almost all behavioral measurements investigated (P < 0.001). Further, we observed strong strain-by-treatment interactions for most phenotypes, particularly for changes in distance traveled, vertical activity, and extrapyramidal symptoms (EPS). Estimates of overall heritability ranged from 0.21 (change in body weight) to 0.4 (VCMs and change in distance traveled) while the portion attributable to the interactions of treatment and strain ranged from 0.01 (for change in body weight) to 0.15 (for change in EPS). Interestingly, close to 30% of RIX mice exhibited VCMs, a sensitivity to haloperidol exposure, approximately similar to the rate of TD in humans chronically exposed to haloperidol. Understanding the genetic basis for the susceptibility to antipsychotic ADRs may be possible in mouse, and extrapolation to humans could lead to safer therapeutic approaches for schizophrenia.

Integrating fish models in tuberculosis vaccine development

Tuberculosis is a chronic infection by Mycobacterium tuberculosis that results in over 1.5 million deaths worldwide each year. Currently, there is only one vaccine against tuberculosis, the Bacillus Calmette–Guérin (BCG) vaccine. Despite widespread vaccination programmes, over 10 million new M. tuberculosis infections are diagnosed yearly, with almost half a million cases caused by antibiotic-resistant strains. Novel vaccination strategies concentrate mainly on replacing BCG or boosting its efficacy and depend on animal models that accurately recapitulate the human disease. However, efforts to produce new vaccines against an M. tuberculosis infection have encountered several challenges, including the complexity of M. tuberculosis pathogenesis and limited knowledge of the protective immune responses. The preclinical evaluation of novel tuberculosis vaccine candidates is also hampered by the lack of an appropriate animal model that could accurately predict the protective effect of vaccines in humans. Here, we review the role of zebrafish (Danio rerio) and other fish models in the development of novel vaccines against tuberculosis and discuss how these models complement the more traditional mammalian models of tuberculosis.

Summary: In this Review, we discuss how zebrafish (Danio rerio) and other fish models can complement the more traditional mammalian models in the development of novel vaccines against tuberculosis.

Micro-CT scan with virtual dissection of left ventricle is a non-destructive, reproducible alternative to dissection and weighing for left ventricular size

Micro-CT scan images enhanced by iodine staining provide high-resolution visualisation of soft tissues in laboratory mice. We have compared Micro-CT scan-derived left ventricular (LV) mass with dissection and weighing. Ex-vivo micro-CT scan images of the mouse hearts were obtained following staining by iodine. The LV was segmented and its volume was assessed using a semi-automated method by Drishti software. The left ventricle was then dissected in the laboratory and its actual weight was measured and compared against the estimated results. LV mass was calculated multiplying its estimated volume and myocardial specific gravity. Thirty-five iodine-stained post-natal mouse hearts were studied. Mice were of either sex and 68 to 352 days old (median age 202 days with interquartile range 103 to 245 days) at the time of sacrifice. Samples were from 20 genetically diverse strains. Median mouse body weight was 29 g with interquartile range 24 to 34 g. Left Ventricular weights ranged from 40.0 to 116.7 mg. The segmented LV mass estimated from micro-CT scan and directly measured dissected LV mass were strongly correlated (R² = 0. 97). Segmented LV mass derived from Micro-CT images was very similar to the physically dissected LV mass (mean difference = 0.09 mg; 95% confidence interval − 3.29 mg to 3.1 mg). Micro-CT scanning provides a non-destructive, efficient and accurate visualisation tool for anatomical analysis of animal heart models of human cardiovascular conditions. Iodine-stained soft tissue imaging empowers researchers to perform qualitative and quantitative assessment of the cardiac structures with preservation of the samples for future histological analysis.

Mapping the Effects of Genetic Variation on Chromatin State and Gene Expression Reveals Loci That Control Ground State Pluripotency

Mouse embryonic stem cells (mESCs) cultured in the presence of LIF occupy a ground state with highly active pluripotency-associated transcriptional and epigenetic circuitry. However, ground state pluripotency in some inbred strain backgrounds is unstable in the absence of ERK1/2 and GSK3 inhibition. Using an unbiased genetic approach, we dissect the basis of this divergent response to extracellular cues by profiling gene expression and chromatin accessibility in 170 genetically heterogeneous mESCs. We map thousands of loci affecting chromatin accessibility and/or transcript abundance, including 10 QTL hotspots where genetic variation at a single locus coordinates the regulation of genes throughout the genome. For one hotspot, we identify a single enhancer variant ∼10 kb upstream of Lifr associated with chromatin accessibility and mediating a cascade of molecular events affecting pluripotency. We validate causation through reciprocal allele swaps, demonstrating the functional consequences of noncoding variation in gene regulatory networks that stabilize pluripotent states in vitro.

Genetic Mapping with Background Control for Quantitative Trait Locus (QTL) in 8-Parental Pure-Line Populations

Multiparental advanced generation intercross (MAGIC) populations provide abundant genetic variation for use in plant genetics and breeding. In this study, we developed a method for quantitative trait locus (QTL) detection in pure-line populations derived from 8-way crosses, based on the principles of inclusive composite interval mapping (ICIM). We considered 8 parents carrying different alleles with different effects. To estimate the 8 genotypic effects, 1-locus genetic model was first built. Then, an orthogonal linear model of phenotypes against marker variables was established to explain genetic effects of the locus. The linear model was estimated by stepwise regression and finally used for phenotype adjustment and background genetic variation control in QTL mapping. Simulation studies using 3 genetic models demonstrated that the proposed method had higher detection power, lower false discovery rate (FDR), and unbiased estimation of QTL locations compared with other methods. Marginal bias was observed in the estimation of QTL effects. An 8-parental recombinant inbred line (RIL) population previously reported in cowpea and analyzed by interval mapping (IM) was reanalyzed by ICIM and genome-wide association mapping implemented in software FarmCPU. The results indicated that ICIM identified more QTLs explaining more phenotypic variation than did IM; ICIM provided more information on the detected QTL than did FarmCPU; and most QTLs identified by IM and FarmCPU were also detected by ICIM.

Mapping Viral Susceptibility Loci in Mice

Genetic alleles that contribute to enhanced susceptibility or resistance to viral infections and virally induced diseases have often been first identified in mice before humans due to the significant advantages of the murine system for genetic studies. Herein we review multiple discoveries that have revealed significant insights into virus-host interactions, all made using genetic mapping tools in mice. Factors that have been identified include innate and adaptive immunity genes that contribute to host defense against pathogenic viruses such as herpes viruses, flaviviruses, retroviruses, and coronaviruses. Understanding the genetic mechanisms that affect infectious disease outcomes will aid the development of personalized treatment and preventive strategies for pathogenic infections.

Creating outbred and inbred populations in haplodiploids to measure adaptive responses in the laboratory

Laboratory studies are often criticized for not being representative of processes occurring in natural populations. One reason for this is the fact that laboratory populations generally do not capture enough of the genetic variation of natural populations. This can be mitigated by mixing the genetic background of several field populations when creating laboratory populations. From these outbred populations, it is possible to generate inbred lines, thereby freezing and partitioning part of their variability, allowing each genotype to be characterized independently. Many studies addressing adaptation of organisms to their environment, such as those involving quantitative genetics or experimental evolution, rely on inbred or outbred populations, but the methodology underlying the generation of such biological resources is usually not explicitly documented. Here, we developed different procedures to circumvent common pitfalls of laboratory studies, and illustrate their application using two haplodiploid species, the spider mites Tetranychus urticae and Tetranychus evansi. First, we present a method that increases the chance of capturing high amounts of variability when creating outbred populations, by performing controlled crosses between individuals from different field-collected populations. Second, we depict the creation of inbred lines derived from such outbred populations, by performing several generations of sib-mating. Third, we outline an experimental evolution protocol that allows the maintenance of a constant population size at the beginning of each generation, thereby preventing bottlenecks and diminishing extinction risks. Finally, we discuss the advantages of these procedures and emphasize that sharing such biological resources and combining them with available genetic tools will allow consistent and comparable studies that greatly contribute to our understanding of ecological and evolutionary processes.

E2f8 and Dlg2 genes have independent effects on impaired insulin secretion associated with hyperglycaemia

AIMS/HYPOTHESIS

Reduced insulin secretion results in hyperglycaemia and diabetes involving a complex aetiology that is yet to be fully elucidated. Genetic susceptibility is a key factor in beta cell dysfunction and hyperglycaemia but the responsible genes have not been defined. The Collaborative Cross (CC) is a recombinant inbred mouse panel with diverse genetic backgrounds allowing the identification of complex trait genes that are relevant to human diseases. The aim of this study was to identify and characterise genes associated with hyperglycaemia.

METHODS

Using an unbiased genome-wide association study, we examined random blood glucose and insulin sensitivity in 53 genetically unique mouse strains from the CC population. The influences of hyperglycaemia susceptibility quantitative trait loci (QTLs) were investigated by examining glucose tolerance, insulin secretion, pancreatic histology and gene expression in the susceptible mice. Expression of candidate genes and their association with insulin secretion were examined in human islets. Mechanisms underlying reduced insulin secretion were studied in MIN6 cells using RNA interference.

RESULTS

Wide variations in blood glucose levels and the related metabolic traits (insulin sensitivity and body weight) were observed in the CC population. We showed that elevated blood glucose in the CC strains was not due to insulin resistance nor obesity but resulted from reduced insulin secretion. This insulin secretory defect was demonstrated to be independent of abnormalities in islet morphology, beta cell mass and pancreatic insulin content. Gene mapping identified the E2f8 (p = 2.19 × 10^-15) and Dlg2 loci (p = 3.83 × 10^-8) on chromosome 7 to be significantly associated with hyperglycaemia susceptibility. Fine mapping the implicated regions using congenic mice demonstrated that these two loci have independent effects on insulin secretion in vivo. Significantly, our results revealed that increased E2F8 and DLG2 gene expression are correlated with enhanced insulin secretory function in human islets. Furthermore, loss-of-function studies in MIN6 cells demonstrated that E2f8 is involved in insulin secretion through an ATP-sensitive K⁺ channel-dependent pathway, which leads to a 30% reduction in Abcc8 expression. Similarly, knockdown of Dlg2 gene expression resulted in impaired insulin secretion in response to glucose and non-glucose stimuli.

CONCLUSIONS/INTERPRETATION

Collectively, these findings suggest that E2F transcription factor 8 (E2F8) and discs large homologue 2 (DLG2) regulate insulin secretion. The CC resource enables the identification of E2f8 and Dlg2 as novel genes associated with hyperglycaemia due to reduced insulin secretion in pancreatic beta cells. Taken together, our results provide better understanding of the molecular control of insulin secretion and further support the use of the CC resource to identify novel genes relevant to human diseases.

Immune Predictors of Mortality After Ribonucleic Acid Virus Infection

BACKGROUND

Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines as well as the early identification of individuals with the highest risk that may require supportive treatment.

METHODS

We completed a screen of mice from the Collaborative Cross (CC) that we infected with influenza, severe acute respiratory syndrome-coronavirus, and West Nile virus.

RESULTS

The CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality after infection and strains exhibiting no mortality. We then used comprehensive preinfection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection.

CONCLUSIONS

These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design.

Beyond the looking glass: recent advances in understanding the impact of environmental exposures on neuropsychiatric disease

The etiologic pathways leading to neuropsychiatric diseases remain poorly defined. As genomic technologies have advanced over the past several decades, considerable progress has been made linking neuropsychiatric disorders to genetic underpinnings. Interest and consideration of nongenetic risk factors (e.g., lead exposure and schizophrenia) have, in contrast, lagged behind heritable frameworks of explanation. Thus, the association of neuropsychiatric illness to environmental chemical exposure, and their potential interactions with genetic susceptibility, are largely unexplored. In this review, we describe emerging approaches for considering the impact of chemical risk factors acting alone and in concert with genetic risk, and point to the potential role of epigenetics in mediating exposure effects on transcription of genes implicated in mental disorders. We highlight recent examples of research in nongenetic risk factors in psychiatric disorders that point to potential shared biological mechanisms-synaptic dysfunction, immune alterations, and gut-brain interactions. We outline new tools and resources that can be harnessed for the study of environmental factors in psychiatric disorders. These tools, combined with emerging experimental evidence, suggest that there is a need to broadly incorporate environmental exposures in psychiatric research, with the ultimate goal of identifying modifiable risk factors and informing new treatment strategies for neuropsychiatric disease.

Assessing the host genetic background effects on type 2 diabetes and obesity development in response to mixed-oral bacteria and high-fat diet using the collaborative cross mouse model

BACKGROUND

Host genetic background and sex, play central roles in defining the pathogenesis of type 2 diabetes (T2D), obesity and infectious diseases. Our previous studies demonstrated the utilization of genetically highly diverse inbred mouse lines, namely collaborative cross (CC), for dissecting host susceptibility for the development of T2D and obesity, showing significant variations following high-fat (42% fat) diet (HFD). Here, we aimed to assessing the host genetic background and sex effects on T2D and obesity development in response to oral-mixed bacterial infection and HFD using the CC lines.

MATERIALS AND METHODS

Study cohort consists of 97 mice from 2 CC lines (both sexes), maintained on either HFD or Standard diet (CHD) for 12 weeks. At week 5 a group of mice from each diet were infected with Porphyromonas gingivalis (Pg) and Fusobacterium nucleatum (Fn) bacteria (control groups without infection). Body weight (BW) and glucose tolerance ability were assessed at the end time point of the experiment.

RESULTS

The CC lines varied (P < .05) at their BW gain and glucose tolerance ability (with sex effect) in response to diets and/or infection, showing opposite responses despite sharing the same environmental conditions. The combination of diet and infection enhances BW accumulation for IL1912, while restraints it for IL72. As for glucose tolerance ability, only females (both lines) were deteriorated in response to infection.

CONCLUSIONS

This study emphasizes the power of the CC mouse population for the characterization of host genetic makeup for defining the susceptibility of the individual to development of obesity and/or impaired glucose tolerance.

Two Synthetic 18-Way Outcrossed Populations of Diploid Budding Yeast with Utility for Complex Trait Dissection

Advanced-generation multiparent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than genome-wide association studies to detect rare variants and higher resolution than F2 linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from 18 genetically diverse founding strains. We carried out de novo assemblies of the genomes of the 18 founder strains, such that virtually all variation segregating between these strains is known, and represented those assemblies as Santa Cruz Genome Browser tracks. We discovered complex patterns of structural variation segregating among the founders, including a large deletion within the vacuolar ATPase VMA1, several different deletions within the osmosensor MSB2, a series of deletions and insertions at PRM7 and the adjacent BSC1, as well as copy number variation at the dehydrogenase ALD2 Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66 kb, demonstrating that the population is highly recombined. We pool-sequenced the two MPPs to 3270× and 2226× coverage and demonstrated that we can accurately estimate local haplotype frequencies using pooled data. We further downsampled the pool-sequenced data to ∼20-40× and showed that local haplotype frequency estimates remained accurate, with median error rates 0.8 and 0.6% at 20× and 40×, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that 10 or more founders are present at a detectable frequency for > 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

Mouse Phenome Database: a data repository and analysis suite for curated primary mouse phenotype data

The Mouse Phenome Database (MPD; https://phenome.jax.org) is a widely accessed and highly functional data repository housing primary phenotype data for the laboratory mouse accessible via APIs and providing tools to analyze and visualize those data. Data come from investigators around the world and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD houses rigorously curated per-animal data with detailed protocols. Public ontologies and controlled vocabularies are used for annotation. In addition to phenotype tools, genetic analysis tools enable users to integrate and interpret genome–phenome relations across the database. Strain types and populations include inbred, recombinant inbred, F1 hybrid, transgenic, targeted mutants, chromosome substitution, Collaborative Cross, Diversity Outbred and other mapping populations. Our new analysis tools allow users to apply selected data in an integrated fashion to address problems in trait associations, reproducibility, polygenic syndrome model selection and multi-trait modeling. As we refine these tools and approaches, we will continue to provide users a means to identify consistent, quality studies that have high translational relevance.

Antecedent presentation of neurological phenotypes in the Collaborative Cross reveals four classes with complex sex-dependencies

Antecedent viral infection may contribute to increased susceptibility to several neurological diseases, such as multiple sclerosis and Parkinson’s disease. Variation in clinical presentations of these diseases is often associated with gender, genetic background, or a combination of these and other factors. The complicated etiologies of these virally influenced diseases are difficult to study in conventional laboratory mouse models, which display a very limited number of phenotypes. We have used the genetically and phenotypically diverse Collaborative Cross mouse panel to examine complex neurological phenotypes after viral infection. Female and male mice from 18 CC strains were evaluated using a multifaceted phenotyping pipeline to define their unique disease profiles following infection with Theiler’s Murine Encephalomyelitis Virus, a neurotropic virus. We identified 4 distinct disease progression profiles based on limb-specific paresis and paralysis, tremors and seizures, and other clinical signs, along with separate gait profiles. We found that mice of the same strain had more similar profiles compared to those of different strains, and also identified strains and phenotypic parameters in which sex played a significant role in profile differences. These results demonstrate the value of using CC mice for studying complex disease subtypes influenced by sex and genetic background. Our findings will be useful for developing novel mouse models of virally induced neurological diseases with heterogenous presentation, an important step for designing personalized, precise treatments.

Improved mouse models and advanced genetic and genomic technologies for the study of neutrophils

Mice have been excellent surrogates for studying neutrophil biology and, furthermore, murine models of human disease have provided fundamental insights into the roles of human neutrophils in innate immunity. The emergence of novel humanized mice and high-diversity mouse populations offers the research community innovative and powerful platforms for better understanding, respectively, the mechanisms by which human neutrophils drive pathogenicity, and how genetic differences underpin the variation in neutrophil biology observed among humans. Here, we review key examples of these new resources. Additionally, we provide an overview of advanced genetic engineering tools available to further improve such murine model systems, of sophisticated neutrophil-profiling technologies, and of multifunctional nanoparticle (NP)-based neutrophil-targeting strategies.

Complex Genetic Architecture Underlies Regulation of Influenza-A-Virus-Specific Antibody Responses in the Collaborative Cross

Host genetic factors play a fundamental role in regulating humoral immunity to viral infection, including influenza A virus (IAV). Here, we utilize the Collaborative Cross (CC), a mouse genetic reference population, to study genetic regulation of variation in antibody response following IAV infection. CC mice show significant heritable variation in the magnitude, kinetics, and composition of IAV-specific antibody response. We map 23 genetic loci associated with this variation. Analysis of a subset of these loci finds that they broadly affect the antibody response to IAV as well as other viruses. Candidate genes are identified based on predicted variant consequences and haplotype-specific expression patterns, and several show overlap with genes identified in human mapping studies. These findings demonstrate that the host antibody response to IAV infection is under complex genetic control and highlight the utility of the CC in modeling and identifying genetic factors with translational relevance to human health and disease.

Natural killer cells expanded in vivo or ex vivo with IL-15 overcomes the inherent susceptibility of CAST mice to lethal infection with orthopoxviruses

The wild-derived inbred CAST/EiJ mouse, one of eight founder strains in the Collaborative Cross panel, is an exceptional model for studying monkeypox virus (MPXV), an emerging human pathogen, and other orthopoxviruses including vaccinia virus (VACV). Previous studies suggested that the extreme susceptibility of the CAST mouse to orthopoxviruses is due to an insufficient innate immune response. Here, we focused on the low number of natural killer (NK) cells in the naïve CAST mouse as a contributing factor to this condition. Administration of IL-15 to CAST mice transiently increased NK and CD8⁺ T cells that could express IFN-γ, indicating that the progenitor cells were capable of responding to cytokines. However, the number of NK cells rapidly declined indicating a defect in their homeostasis. Furthermore, IL-15-treated mice were protected from an otherwise lethal challenge with VACV or MPXV. IL-15 decreased virus spread and delayed death even when CD4⁺/CD8⁺ T cells were depleted with antibody, supporting an early protective role of the expanded NK cells. Purified splenic NK cells from CAST mice proliferated in vitro in response to IL-15 and could be activated with IL-12/IL-18 to secrete interferon-γ. Passive transfer of non-activated or activated CAST NK cells reduced VACV spread but only the latter completely prevented death at the virus dose used. Moreover, antibodies to interferon-γ abrogated the protection by activated NK cells. Thus, the inherent susceptibility of CAST mice to orthopoxviruses can be explained by a low level of NK cells and this vulnerability can be overcome either by expanding their NK cells in vivo with IL-15 or by passive transfer of purified NK cells that were expanded and activated in vitro.

With the eradication of smallpox, monkeypox virus (MPXV) remains the only poxvirus causing significant mortality in humans. Although endemic in parts of Africa, human infections have occurred in the United States, the United Kingdom and Israel due to travelers or imported animals. Contrary to its name, MPXV primarily infects rodents and secondarily infects humans and other primates. The wild-derived CAST mouse is an excellent small animal model for studying the pathogenicity of MPXV and related orthopoxviruses including vaccinia virus (VACV) and for evaluating therapeutics. We previously found that the susceptibility of CAST mice is correlated with low numbers of natural killer (NK) cells and a delayed interferon-γ response. Here we showed that in vivo administration of the cytokine IL-15 transiently raised NK cell numbers and protected CAST mice from systemic infections with VACV and MPXV. CAST mouse NK cells that were purified and expanded in vitro with IL-15 also provided protection, further demonstrating the important role of NK cells. The rapid decline in NK cell numbers following cessation of IL-15 administration or NK cell transfer suggests that a low level of NK cell homeostasis contributes to the susceptibility of CAST mice to virus infection.

Genetic and metabolic links between the murine microbiome and memory

BACKGROUND

Recent evidence has linked the gut microbiome to host behavior via the gut-brain axis [1-3]; however, the underlying mechanisms remain unexplored. Here, we determined the links between host genetics, the gut microbiome and memory using the genetically defined Collaborative Cross (CC) mouse cohort, complemented with microbiome and metabolomic analyses in conventional and germ-free (GF) mice.

RESULTS

A genome-wide association analysis (GWAS) identified 715 of 76,080 single-nucleotide polymorphisms (SNPs) that were significantly associated with short-term memory using the passive avoidance model. The identified SNPs were enriched in genes known to be involved in learning and memory functions. By 16S rRNA gene sequencing of the gut microbial community in the same CC cohort, we identified specific microorganisms that were significantly correlated with longer latencies in our retention test, including a positive correlation with Lactobacillus. Inoculation of GF mice with individual species of Lactobacillus (L. reuteri F275, L. plantarum BDGP2 or L. brevis BDGP6) resulted in significantly improved memory compared to uninoculated or E. coli DH10B inoculated controls. Untargeted metabolomics analysis revealed significantly higher levels of several metabolites, including lactate, in the stools of Lactobacillus-colonized mice, when compared to GF control mice. Moreover, we demonstrate that dietary lactate treatment alone boosted memory in conventional mice. Mechanistically, we show that both inoculation with Lactobacillus or lactate treatment significantly increased the levels of the neurotransmitter, gamma-aminobutyric acid (GABA), in the hippocampus of the mice.

CONCLUSION

Together, this study provides new evidence for a link between Lactobacillus and memory and our results open possible new avenues for treating memory impairment disorders using specific gut microbial inoculants and/or metabolites. Video Abstract.

Characterization of genetically complex Collaborative Cross mouse strains that model divergent locomotor activating and reinforcing properties of cocaine

RATIONALE

Few effective treatments exist for cocaine use disorders due to gaps in knowledge about its complex etiology. Genetically defined animal models provide a useful tool for advancing our understanding of the biological and genetic underpinnings of addiction-related behavior and evaluating potential treatments. However, many attempts at developing mouse models of behavioral disorders were based on overly simplified single gene perturbations, often leading to inconsistent and misleading results in pre-clinical pharmacology studies. A genetically complex mouse model may better reflect disease-related behaviors.

OBJECTIVES

Screening defined, yet genetically complex, intercrosses of the Collaborative Cross (CC) mice revealed two lines, RIX04/17 and RIX41/51, with extreme high and low behavioral responses to cocaine. We characterized these lines as well as their CC parents, CC004/TauUnc and CC041/TauUnc, to evaluate their utility as novel model systems for studying the biological and genetic mechanisms underlying behavioral responses to cocaine.

METHODS

Behavioral responses to acute (initial locomotor sensitivity) and repeated (behavioral sensitization, conditioned place preference, intravenous self-administration) exposures to cocaine were assessed. We also examined the monoaminergic system (striatal tissue content and in vivo fast scan cyclic voltammetry), HPA axis reactivity, and circadian rhythms as potential mechanisms for the divergent phenotypic behaviors observed in the two strains, as these systems have a previously known role in mediating addiction-related behaviors.

RESULTS

RIX04/17 and 41/51 show strikingly divergent initial locomotor sensitivity to cocaine with RIX04/17 exhibiting very high and RIX41/51 almost no response. The lines also differ in the emergence of behavioral sensitization with RIX41/51 requiring more exposures to exhibit a sensitized response. Both lines show conditioned place preference for cocaine. We determined that the cocaine sensitivity phenotype in each RIX line was largely driven by the genetic influence of one CC parental strain, CC004/TauUnc and CC041/TauUnc. CC004 demonstrates active operant cocaine self-administration and CC041 is unable to acquire under the same testing conditions, a deficit which is specific to cocaine as both strains show operant response for a natural food reward. Examination of potential mechanisms driving differential responses to cocaine show strain differences in molecular and behavioral circadian rhythms. Additionally, while there is no difference in striatal dopamine tissue content or dynamics, there are selective differences in striatal norepinephrine and serotonergic tissue content.

CONCLUSIONS

These CC strains offer a complex polygenic model system to study underlying mechanisms of cocaine response. We propose that CC041/TauUnc and CC004/TauUnc will be useful for studying genetic and biological mechanisms underlying resistance or vulnerability to the stimulatory and reinforcing effects of cocaine.

Translation of mouse model to human gives insights into periodontitis etiology

To suggest candidate genes involved in periodontitis, we combined gene expression data of periodontal biopsies from Collaborative Cross (CC) mouse lines, with previous reported quantitative trait loci (QTL) in mouse and with human genome-wide association studies (GWAS) associated with periodontitis. Periodontal samples from two susceptible, two resistant and two lines that showed bone formation after periodontal infection were collected during infection and naïve status. Differential expressed genes (DEGs) were analyzed in a case-control and case-only design. After infection, eleven protein-coding genes were significantly stronger expressed in resistant CC lines compared to susceptible ones. Of these, the most upregulated genes were MMP20 (P = 0.001), RSPO4 (P = 0.032), CALB1 (P = 1.06×10-4), and AMTN (P = 0.05). In addition, human orthologous of candidate genes were tested for their association in a case-controls samples of aggressive (AgP) and chronic (CP) periodontitis (5,095 cases, 9,908 controls). In this analysis, variants at two loci, TTLL11/PTGS1 (rs9695213, P = 5.77×10-5) and RNASE2 (rs2771342, P = 2.84×10-5) suggested association with both AgP and CP. In the association analysis with AgP only, the most significant associations were located at the HLA loci HLA-DQH1 (rs9271850, P = 2.52×10-14) and HLA-DPA1 (rs17214512, P = 5.14×10-5). This study demonstrates the utility of the CC RIL populations as a suitable model to investigate the mechanism of periodontal disease.

Workshop report: Optimization of animal models to better predict influenza vaccine efficacy

Animal models that can recapitulate the human immune system are essential for the preclinical development of safe and efficacious vaccines. Development and optimization of representative animal models are key components of the NIAID strategic plan for the development of a universal influenza vaccine. To gain insight into the current landscape of animal model usage in influenza vaccine development, NIAID convened a workshop in Rockville, Maryland that brought together experts from academia, industry and government. Panelists discussed the benefits and limitations of the field's most widely-used animal models, identified currently available and critically needed resources and reagents, and suggested areas for improvement based on inadequacies of existing models. Although appropriately-selected animal models can be useful for evaluating safety, mechanism-of-action, and superiority over existing vaccines, workshop participants concluded that multiple animal models will likely be required to sufficiently test all aspects of a novel vaccine candidate. Refinements are necessary for all current model systems, for example, to better represent special human populations, and will be facilitated by the development and broader availability of new reagents. NIAID continues to support progress towards increasing the predictive value of animal models.

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population

The Collaborative Cross (CC) mouse resource is a next-generation mouse genetic reference population (GRP) designed for high-resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild-derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions. These traits are observed at multiple levels of the animals' systems, including metabolism, body weight, immune profile, and susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present general guidelines for design of QTL mapping experiments using the CC resource-along with full step-by-step protocols and methods that were implemented in our lab for the phenotypic and genotypic characterization of the different CC lines-for mapping the genes underlying host response to infectious and chronic diseases. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: CC lines for whole body mass index (BMI) Basic Protocol 2: A detailed assessment of the power to detect effect sizes based on the number of lines used, and the number of replicates per line Basic Protocol 3: Obtaining power for QTL with given target effect by interpolating in Table 1 of Keele et al. (2019).

A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice

The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice (Mus musculus) enables data-driven discovery of biological network components and mechanisms of host-microbial interactions underlying disease phenotypes. To examine the interplay among the whole host genome, transcriptome, and microbiome, we mapped QTL and correlated the abundance of cecal messenger RNA, luminal microflora, physiology, and behavior in a highly diverse Collaborative Cross breeding population. One such relationship, regulated by a variant on chromosome 7, was the association of Odoribacter (Bacteroidales) abundance and sleep phenotypes. In a test of this association in the BKS.Cg-Dock7m +/+ Leprdb/J mouse model of obesity and diabetes, known to have abnormal sleep and colonization by Odoribacter, treatment with antibiotics altered sleep in a genotype-dependent fashion. The many other relationships extracted from this study can be used to interrogate other diseases, microbes, and mechanisms.

The Many Hosts of Mycobacteria 8 (MHM8): A conference report

Mycobacteria are important causes of disease in human and animal hosts. Diseases caused by mycobacteria include leprosy, tuberculosis (TB), nontuberculous mycobacteria (NTM) infections and Buruli Ulcer. To better understand and treat mycobacterial disease, clinicians, veterinarians and scientists use a range of discipline-specific approaches to conduct basic and applied research, including conducting epidemiological surveys, patient studies, wildlife sampling, animal models, genetic studies and computational simulations. To foster the exchange of knowledge and collaboration across disciplines, the Many Hosts of Mycobacteria (MHM) conference series brings together clinical, veterinary and basic scientists who are dedicated to advancing mycobacterial disease research. Started in 2007, the MHM series recently held its 8th conference at the Albert Einstein College of Medicine (Bronx, NY). Here, we review the diseases discussed at MHM8 and summarize the presentations on research advances in leprosy, NTM and Buruli Ulcer, human and animal TB, mycobacterial disease comorbidities, mycobacterial genetics and 'omics, and animal models. A mouse models workshop, which was held immediately after MHM8, is also summarized. In addition to being a resource for those who were unable to attend MHM8, we anticipate this review will provide a benchmark to gauge the progress of future research concerning mycobacteria and their many hosts.

A genome-wide association study in mice reveals a role for Rhbdf2 in skeletal homeostasis

Low bone mass and an increased risk of fracture are predictors of osteoporosis. Individuals who share the same bone-mineral density (BMD) vary in their fracture risk, suggesting that microstructural architecture is an important determinant of skeletal strength. Here, we utilized the rich diversity of the Collaborative Cross mice to identify putative causal genes that contribute to the risk of fractures. Using microcomputed tomography, we examined key structural features that pertain to bone quality in the femoral cortical and trabecular compartments of male and female mice. We estimated the broad-sense heritability to be 50–60% for all examined traits, and we identified five quantitative trait loci (QTL) significantly associated with six traits. We refined each QTL by combining information inferred from the ancestry of the mice, ranging from RNA-Seq data and published literature to shortlist candidate genes. We found strong evidence for new candidate genes, particularly Rhbdf2, whose close association with the trabecular bone volume fraction and number was strongly suggested by our analyses. We confirmed our findings with mRNA expression assays of Rhbdf2 in extreme-phenotype mice, and by phenotyping bones of Rhbdf2 knockout mice. Our results indicate that Rhbdf2 plays a decisive role in bone mass accrual and microarchitecture.

A whole-tissue RNA-seq toolkit for organism-wide studies of gene expression with PME-seq

The immune system operates at the scale of the whole organism in mammals. We currently lack experimental approaches to systematically track and study organism-wide molecular processes in mice. Here we describe an integrated toolkit for measuring gene expression in whole tissues, 3-prime mRNA extension sequencing, that is applicable to most mouse organs and any mouse model of interest. Further, the methods of RNA-seq described in this protocol are broadly applicable to other sample types beyond whole organs, such as tissue samples or isolated cell populations. We report procedures to collect, store and lyse a dozen organ types using conditions compatible with the extraction of high-quality RNA. In addition, we detail protocols to perform high-throughput and low-cost RNA extraction and sequencing, as well as downstream data analysis. The protocol takes 5 d to process 384 mouse organs from collecting tissues to obtaining raw sequencing data, with additional time required for data analysis and mining. The protocol is accessible to individuals with basic skills in (i) mouse perfusion and dissection for sample collection and (ii) computation using Unix and R for data analysis. Overall, the methods presented here fill a gap in our toolbox for studying organism-wide processes in immunology and physiology.

Mathematical methods for visualization and anomaly detection in telemetry datasets

Recent developments in both biological data acquisition and analysis provide new opportunities for data-driven modelling of the health state of an organism. In this paper, we explore the evolution of temperature patterns generated by telemetry data collected from healthy and infected mice. We investigate several techniques to visualize and identify anomalies in temperature time series as temperature relates to the onset of infectious disease. Visualization tools such as Laplacian Eigenmaps and Multidimensional Scaling allow one to gain an understanding of a dataset as a whole. Anomaly detection tools for nonlinear time series modelling, such as Radial Basis Functions and Multivariate State Estimation Technique, allow one to build models representing a healthy state in individuals. We illustrate these methods on an experimental dataset of 306 Collaborative Cross mice challenged with Salmonella typhimurium and show how interruption in circadian patterns and severity of infection can be revealed directly from these time series within 3 days of the infection event.

Genetic Diversity of Collaborative Cross Mice Controls Viral Replication, Clinical Severity, and Brain Pathology Induced by Zika Virus Infection, Independently of Oas1b

The explosive spread of Zika virus (ZIKV) has been associated with major variations in severe disease and congenital afflictions among infected populations, suggesting an influence of host genes. We investigated how genome-wide variants could impact susceptibility to ZIKV infection in mice. We first describe that the susceptibility of Ifnar1-knockout mice is largely influenced by their genetic background. We then show that Collaborative Cross (CC) mice, which exhibit a broad genetic diversity, in which the type I interferon receptor (IFNAR) was blocked by an anti-IFNAR antibody expressed phenotypes ranging from complete resistance to severe symptoms and death, with large variations in the peak and the rate of decrease in the plasma viral load, in the brain viral load, in brain histopathology, and in the viral replication rate in infected cells. The differences in susceptibility to ZIKV between CC strains correlated with the differences in susceptibility to dengue and West Nile viruses between the strains. We identified highly susceptible and resistant mouse strains as new models to investigate the mechanisms of human ZIKV disease and other flavivirus infections. Genetic analyses revealed that phenotypic variations are driven by multiple genes with small effects, reflecting the complexity of ZIKV disease susceptibility in the human population. Notably, our results rule out the possibility of a role of the Oas1b gene in the susceptibility to ZIKV. Altogether, the findings of this study emphasize the role of host genes in the pathogeny of ZIKV infection and lay the foundation for further genetic and mechanistic studies.IMPORTANCE In recent outbreaks, ZIKV has infected millions of people and induced rare but potentially severe complications, including Guillain-Barré syndrome and encephalitis in adults. While several viral sequence variants were proposed to enhance the pathogenicity of ZIKV, the influence of host genetic variants in mediating the clinical heterogeneity remains mostly unexplored. We addressed this question using a mouse panel which models the genetic diversity of the human population and a ZIKV strain from a recent clinical isolate. Through a combination of in vitro and in vivo approaches, we demonstrate that multiple host genetic variants determine viral replication in infected cells and the clinical severity, the kinetics of blood viral load, and brain pathology in mice. We describe new mouse models expressing high degrees of susceptibility or resistance to ZIKV and to other flaviviruses. These models will facilitate the identification and mechanistic characterization of host genes that influence ZIKV pathogenesis.

Immune Correlates of Protection From West Nile Virus Neuroinvasion and Disease

BACKGROUND

A challenge to the design of improved therapeutic agents and prevention strategies for neuroinvasive infection and associated disease is the lack of known natural immune correlates of protection. A relevant model to study such correlates is offered by the Collaborative Cross (CC), a panel of recombinant inbred mouse strains that exhibit a range of disease manifestations upon infection.

METHODS

We performed an extensive screen of CC-F1 lines infected with West Nile virus (WNV), including comprehensive immunophenotyping, to identify groups of lines that exhibited viral neuroinvasion or neuroinvasion with disease and lines that remained free of WNV neuroinvasion and disease.

RESULTS

Our data reveal that protection from neuroinvasion and disease is multifactorial and that several immune outcomes can contribute. Immune correlates identified include decreased suppressive activity of regulatory T cells at steady state, which correlates with peripheral restriction of the virus. Further, a rapid contraction of WNV-specific CD8+ T cells in the brain correlated with protection from disease.

CONCLUSIONS

These immune correlates of protection illustrate additional networks and pathways of the WNV immune response that cannot be observed in the C57BL/6 mouse model. Additionally, correlates of protection exhibited before infection, at baseline, provide insight into phenotypic differences in the human population that may predict clinical outcomes upon infection.

Genetic Background and Sex: Impact on Generalizability of Research Findings in Pharmacology Studies

Animal models consisting of inbred laboratory rodent strains have been a powerful tool for decades, helping to unravel the underpinnings of biological problems and employed to evaluate potential therapeutic treatments in drug discovery. While inbred strains demonstrate relatively reliable and predictable responses, using a single inbred strain alone or as a background to a mutation is analogous to running a clinical trial in a single individual and their identical twins. Indeed, complex etiologies drive the most common human diseases, and a single inbred strain that is a surrogate of a single genome, or data generated from a single sex, is not representative of the genetically diverse patient populations. Further, pharmacological and toxicology data generated in otherwise healthy animals may not translate to disease states where physiology, metabolism, and general health are compromised. The purpose of this chapter is to provide guidance for improving generalizability of preclinical studies by providing insight into necessary considerations for introducing systematic variation within the study design, such as genetic diversity, the use of both sexes, and selection of appropriate age and disease model. The outcome of implementing these considerations should be that reproducibility and generalizability of significant results are significantly enhanced leading to improved clinical translation.

Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation

Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. Here we characterize expression and chromatin state dynamics across three tissues-liver, lung, and kidney-in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues, including local-eQTL for Pik3c2g detected in all three tissues but with distinct allelic effects. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. Based on QTL and mediation analyses over multiple tissues, we propose a causal model for the distal genetic regulation of Akr1e1, a gene involved in glycogen metabolism, through the zinc finger transcription factor Zfp985 and chromatin intermediates. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues.

Nature-Inspired Multiobjective Epistasis Elucidation from Genome-Wide Association Studies

In recent years, the detection of epistatic interactions of multiple genetic variants on the causes of complex diseases brings a significant challenge in genome-wide association studies (GWAS). However, most of the existing methods still suffer from algorithmic limitations such as single-objective optimization, intensive computational requirement, and premature convergence. In this paper, we propose and formulate an epistatic interaction multi-objective artificial bee colony algorithm based on decomposition (EIMOABC/D) to address those problems for genetic interaction detection in genome-wide association studies. First, to direct the genetic interaction detection, two objective functions are formulated to characterize various epistatic models; rank probability model is proposed to sort each population into different nondomination levels based on the fast nondominated sorting approach. After that, the mutual information based local search algorithm is proposed to guide the population search for disease model evaluations in an unbiased manner. To validate the effectiveness of EIMOABC/D, we compare EIMOABC/D against seven state-of-the-art methods on 77 epistatic models including eight small-scale epistatic models with marginal effects, eight large-scale epistatic models with marginal effects, 60 large-scale epistatic models without any marginal effect, and one case study. The experimental results indicate that our proposed algorithm EIMOABC/D outperforms seven state-of-the-art methods on those epistatic models. Furthermore, time complexity analysis and parameter analysis are conducted to demonstrate various properties of our proposed algorithm.

Population Genomics of the House Mouse and the Brown Rat

Mice (Mus musculus) and rats (Rattus norvegicus) have long served as model systems for biomedical research. However, they are also excellent models for studying the evolution of populations, subspecies, and species. Within the past million years, they have spread in various waves across large parts of the globe, with the most recent spread in the wake of human civilization. They have developed into commensal species, but have also been able to colonize extreme environments on islands free of human civilization. Given that ample genomic and genetic resources are available for these species, they have thus also become ideal mammalian systems for evolutionary studies on adaptation and speciation, particularly in the combination with the rapid developments in population genomics. The chapter provides an overview of the systems and their history, as well as of available resources.

Exploring genetic architecture of grain yield and quality traits in a 16-way indica by japonica rice MAGIC global population

Identification of Quantitative Trait Loci (QTL) has been a challenge for complex traits due to the use of populations with narrow genetic base. Most of QTL mapping studies were carried out from crosses made within the subspecies, either indica × indica or japonica × japonica. In this study we report advantages of using Multi-parent Advanced Generation Inter-Crosses global population, derived from a combination of eight indica and eight japonica elite parents, in QTL discovery for yield and grain quality traits. Genome-wide association study and interval mapping identified 38 and 34 QTLs whereas Bayesian networking detected 60 QTLs with 22 marker-marker associations, 32 trait-trait associations and 65 marker-trait associations. Notably, nine known QTLs/genes qPH₁/OsGA20ox2, qDF₃/OsMADS50, PL, QDg1, qGW-5b, grb7-2, qGL₃/GS3, Amy6/Wx gene and OsNAS3 were consistently identified by all approaches for nine traits whereas qDF₃/OsMADS50 was co-located for both yield and days-to-flowering traits on chromosome 3. Moreover, we identified a number of candidate QTLs in either one or two analyses but further validations will be needed. The results indicate that this new population has enabled identifications of significant QTLs and interactions for 16 traits through multiple approaches. Pyramided recombinant inbred lines provide a valuable source for integration into future breeding programs.

A Loss-of-Function Mutation in the Integrin Alpha L (Itgal) Gene Contributes to Susceptibility to Salmonella enterica Serovar Typhimurium Infection in Collaborative Cross Strain CC042

Salmonella is an intracellular bacterium found in the gastrointestinal tract of mammalian, avian, and reptilian hosts. Mouse models have been extensively used to model in vivo distinct aspects of human Salmonella infections and have led to the identification of several host susceptibility genes. We have investigated the susceptibility of Collaborative Cross strains to intravenous infection with Salmonella enterica serovar Typhimurium as a model of human systemic invasive infection. In this model, strain CC042/GeniUnc (CC042) mice displayed extreme susceptibility with very high bacterial loads and mortality. CC042 mice showed lower spleen weights and decreased splenocyte numbers before and after infection, affecting mostly CD8⁺ T cells, B cells, and all myeloid cell populations, compared with control C57BL/6J mice. CC042 mice also had lower thymus weights with a reduced total number of thymocytes and double-negative and double-positive (CD4⁺, CD8⁺) thymocytes compared to C57BL/6J mice. Analysis of bone marrow-resident hematopoietic progenitors showed a strong bias against lymphoid-primed multipotent progenitors. An F2 cross between CC042 and C57BL/6N mice identified two loci on chromosome 7 (Stsl6 and Stsl7) associated with differences in bacterial loads. In the Stsl7 region, CC042 carried a loss-of-function variant, unique to this strain, in the integrin alpha L (Itgal) gene, the causative role of which was confirmed by a quantitative complementation test. Notably, Itgal loss of function increased the susceptibility to S. Typhimurium in a (C57BL/6J × CC042)F1 mouse background but not in a C57BL/6J mouse inbred background. These results further emphasize the utility of the Collaborative Cross to identify new host genetic variants controlling susceptibility to infections and improve our understanding of the function of the Itgal gene.

Analyzing whole genome bisulfite sequencing data from highly divergent genotypes

In the study of DNA methylation, genetic variation between species, strains or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here, we use whole-genome bisulfite sequencing data on two highly divergent mouse strains to study this problem. We show that alignment to personal genomes is necessary for valid methylation quantification. We introduce a method for including strain-specific CpGs in differential analysis, and show that this increases power. We apply our method to a human normal-cancer dataset, and show this improves accuracy and power, illustrating the broad applicability of our approach. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, while accounting for differences in the spatial occurrences of CpGs. Our results have implications for joint analysis of genetic variation and DNA methylation using bisulfite-converted DNA, and unlocks the use of personal genomes for addressing this question.