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We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 μm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 μm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 μm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a hi gh- d imensional i ntegrated v olum e with r egistration ( HiDiver ) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.

Pangenome graphs can represent all variation between multiple genomes, but existing methods for constructing them are biased due to reference-guided approaches. In response, we have developed PanGenome Graph Builder (PGGB), a reference-free pipeline for constructing unbi-ased pangenome graphs. PGGB uses all-to-all whole-genome alignments and learned graph embeddings to build and iteratively refine a model in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

Genetic differences among mammalian hosts andMycobacterium tuberculosis(Mtb) strains determine diverse tuberculosis (TB) patient outcomes. The advent of recombinant inbred mouse panels and next-generation transposon mutagenesis and sequencing approaches has enabled dissection of complex host- pathogen interactions. To identify host and pathogen genetic determinants ofMtbpathogenesis, we infected members of the BXD family of mouse strains with a comprehensive library ofMtbtransposon mutants (TnSeq). Members of the BXD family segregate forMtb-resistant C57BL/6J (B6 orB) andMtb-susceptible DBA/2J (D2 orD) haplotypes. The survival of each bacterial mutant was quantified within each BXD host, and we identified those bacterial genes that were differentially required forMtbfitness across BXD genotypes. Mutants that varied in survival among the host family of strains were leveraged as reporters for “endophenotypes”, each bacterial fitness profile directly probing specific components of the infection microenvironment. We conducted QTL mapping of these bacterial fitness endophenotypes and identified 140host-pathogenquantitative trait loci (hpQTL). We identified a QTL hotspot on chromosome 6 (75.97–88.58 Mb) associated with the genetic requirement of multipleMtbgenes;Rv0127(mak),Rv0359(rip2),Rv0955(perM), andRv3849(espR). Together, this screen reinforces the utility of bacterial mutant libraries as precise reporters of the host immunological microenvironment during infection and highlights specific host-pathogen genetic interactions for further investigation. To enable downstream follow-up for both bacterial and mammalian genetic research communities, all bacterial fitness profiles have been deposited into GeneNetwork.org and added into the comprehensive collection of TnSeq libraries in MtbTnDB.

Summary ParagraphAlthough germline mutation rates and spectra can vary within and between species, genetic modifiers of these traits have long eluded detection. In this study, we searched for loci that influence germline mutagenesis using a uniquely powerful resource: a panel of recombinant inbred mouse lines known as the BXD, descended from the laboratory mouse strains C57BL/6J (B) and DBA/2J (D). Each BXD lineage has been maintained by brother-sister mating in the near absence of natural selection, accumulating de novo mutations for up to 50 years on a known genetic background that is a unique linear mosaic of B and D haplotypes. We show that mice inheriting D haplotypes at a quantitative trait locus (QTL) on chromosome 4 accumulate C>A germline mutations at a 50% higher rate than those inheriting B haplotypes, primarily due to the activity of a C>A-dominated mutational signature known as SBS18. The B and D QTL haplotypes encode different alleles of the DNA repair gene Mutyh, which underlies the heritable colorectal cancer syndrome in which SBS18 was first identified. The B and D Mutyh alleles are present in wild populations of Mus musculus domesticus, providing evidence that common genetic variation modulates germline mutagenesis in a model mammalian species.

The fundamental skills for motor coordination and motor control emerge through development, from infancy to late childhood years. Neurodevelopmental disorders such as Developmental Coordination Disorder (DCD) lead to impaired acquisition of motor skills. This study investigated motor behaviors that reflect the core symptoms of human DCD through the use of BXD recombinant inbred lines of mice that are known to have divergent phenotypes in many behavioral traits, including motor activity. We sought to correlate behavior in basic motor control tasks with the known genotypes of these reference populations of mice using quantitative trait locus (QTL) mapping. We used twelve BXD lines with an average of 16 mice per group to assess the onset of reflexes during the early neonatal stage of life and differences in motor coordination using the open field, rotarod, and gait analyses during the adolescent/young adulthood period. Results indicated significant variability between lines in as to when neonatal reflexes appeared as well as significant line differences for all measures of motor coordination. Five lines (BXD15, BXD27, BXD28, BXD75, and BXD86) struggled with sensorimotor coordination as seen in gait analysis, rotarod, and open field, similar to human presentation of DCD. We identified three significant quantitative trait loci for gait on proximal Chr 3, Chr 4 and distal Chr 6. Based on expression, function, and polymorphism within the mapped QTL intervals, 7 candidate genes (Gpr63, Spata5, Trpc3, Cntn6, Chl1, Grm7 and Ogg1) emerged. This study offers new insights into mouse motor behavior which promises to be a first murine model to explore the genetics and neural correlates of DCD.

Short tandem repeats (STRs) are a class of rapidly mutating genetic elements typically characterized by repeated units of 1–6bp. We leveraged whole genome sequencing data for 152 recombinant inbred (RI) strains from the BXD family of mice to map loci that modulate genome-wide patterns of new mutations arising during parent-to-offspring transmission at STRs. We defined quantitative phenotypes describing the numbers and types of germline STR mutations in each strain and performed quantitative trait locus (QTL) analyses for each of these phenotypes. We identified a locus on Chromosome 13 at which strains inheriting the C57BL/6J (B) haplotype have a higher rate of STR expansions than those inheriting the DBA/2J (D) haplotype. The strongest candidate gene in this locus isMsh3, a known modifier of STR stability in cancer and at pathogenic repeat expansions in mice and humans, and a current drug target against Huntington's disease. The D haplotype at this locus harbors a cluster of variants near the 5’ end ofMsh3including multiple missense variants near the DNA mismatch recognition domain. In contrast, the B haplotype contains a unique retrotransposon insertion. The rate of expansion covaries positively withMsh3expression—with higher expression from the B haplotype. Finally, detailed analysis of mutation patterns showed that strains carrying the B allele have higher expansion rates, but slightly lower overall total mutation rates, compared to those with the D allele, particularly at tetranucleotide repeats. Our results suggest an important role for inherited variants inMsh3in modulating genome-wide patterns of germline mutations at STRs.

We mapped high-precision time-series data (15 min bins for 3 hours) generated for ~ 700 adult BXD mice across 105 morphine- and naloxone-related traits using new sequence-derived marker maps and a linear-mixed model. We confirm a previously mapped sex-independent effect of initial locomotor responses to morphine (50 mg/kg ip) that maps precisely toOprm1on chromosome (Chr) 10, with the linkage score reaching −log10P of ~12.4 (with a high B allele) at 75 min and exhausted by 160 min. We detected a new modulator of opiate locomotor activation in both sexes on Chr 16, with a peak linkage that climbs from 105 through to 180 min after injection. This locus includes one compelling candidate—fibroblast growth factor 12 (Fgf12). We also detected a strong, but transient epistatic interaction between these two loci. Single nuclei transcriptomic analyses in rats demonstrates that expression ofOprm1andFgf12mRNA covary in one specific subtype ofDrd1medium spiny neurons. Our Bayesian network analysis identified that a cascade of MAP kinases—Mapk8ip2, Map3k11, andMap3k12—are part of theOprm1–Fgf12network. This is the first demonstration of a time-dependent epistatic interaction modulating drug response in mammals with interesting mechanistic implications. Analysis ofOPRM1andFGF12gene networks in human GWAS data highlights enrichment of signals associated with substance use disorder.

Gulf War Illness (GWI) is thought to be a chronic neuroimmune disorder caused by in-theater exposure during the 1990–1991 Gulf War. There is a consensus that the illness is caused by exposure to insecticides and nerve agent toxicants. However, the heterogeneity in both development of disease and clinical outcomes strongly suggests a genetic contribution. Here, we modeled GWI in 30 BXD recombinant inbred mouse strains with a combined treatment of corticosterone (CORT) and diisopropyl fluorophosphate (DFP). We quantified transcriptomes from 409 prefrontal cortex samples. Compared to the untreated and DFP treated controls, the combined treatment significantly activated pathways such as cytokine-cytokine receptor interaction and TNF signaling pathway. Protein-protein interaction analysis defined 6 subnetworks for CORT + DFP, with the key regulators being Cxcl1, Il6, Ccnb1, Tnf, Agt, and Itgam. We also identified 21 differentially expressed genes having significant QTLs related to CORT + DFP, but without evidence for untreated and DFP treated controls, suggesting regions of the genome specifically involved in the response to CORT + DFP. We identified Adamts9 as a potential contributor to response to CORT + DFP and found links to symptoms of GWI. Furthermore, we observed a significant effect of CORT + DFP treatment on the relative proportion of myelinating oligodendrocytes, with a QTL on Chromosome 5. We highlight three candidates, Magi2, Sema3c, and Gnai1, based on their high expression in the brain and oligodendrocyte. In summary, our results show significant genetic effects of the CORT + DFP treatment, which mirrors gene and protein expression changes seen in GWI sufferers, providing insight into the disease and a testbed for future interventions.

Linked-read whole genome sequencing methods, such as the 10x Chromium, attach a unique molecular barcode to each high molecular weight DNA molecule. The samples are then sequenced using short-read technology. During analysis, sequence reads sharing the same barcode are aligned to adjacent genomic locations. The pattern of barcode sharing between genomic regions allows the discovery of large structural variants (SVs) in the range of 1 Kb to a few Mb. Most SV calling methods for these data, such as LongRanger, analyze one sample at a time and often produces inconsistent results for the same genomic location across multiple samples. We developed a method, SVJAM, for joint calling of SVs, using data from 152 members of the BXD family of recombinant inbred strains of mice. Our method first collects candidate SV regions from single sample analysis, such as those produced by LongRanger. We then retrieve barcode overlapping data from all samples for each region. These data are organized as a high dimensional matrix. The dimension of this matrix is then reduced using principal component analysis. Samples projected onto a two dimensional space formed by the first two principal components forms two or three clusters based on their genotype, representing the reference, alternative, or heterozygotic alleles. We developed a novel distance measure for hierarchical clustering and rotating the axes to find the optimal clustering results. We also developed an algorithm to decide whether the pattern of sample distribution is best fitted with one, two, or three genotypes. For each sample, we calculate its membership score for each genotype. We compared results produced by SVJAM with LongRanger and few methods that rely on PacBio or Oxford Nanopore data. In a comparison of SVJAM with SV detected using long-read sequencing data for the DBA/2J strain, we found that our results recovered many SVs missed by LongRanger. We also found many SVs called by LongRanger were assigned with an incorrect SV type. Our algorithm also consistently identified heterozygotic regions.

Recombinant inbred rodents form immortal genome-types that can be resampled deeply at many stages, in both sexes, and under multiple experimental conditions to model genome-environment interactions and to test genome-phenome predictions. This allows for experimental precision medicine, for which sophisticated causal models of complex interactions among DNA variants, phenotype variants at many levels, and innumerable environmental factors are required. Large families and populations of isogenic lines of mice and rats are now available and have been used across fields of biology. We will use the BXD recombinant inbred family and their derived diallel cross population as an example for predictive, experimental precision medicine and biology.

Introduction Rat mothers exhibit natural variations in care that propagate between generations of female offspring. However, there is limited information on genetic variation that could influence this propagation. Methods We assessed early‐life maternal care received by individual female rat offspring, later‐life maternal care provisioning, and dopaminergic activity in the maternal brain in relation to naturally occurring genetic polymorphisms linked to the dopaminergic system. We also conducted a systematic analysis of other genetic variants potentially related to maternal behavior in our Long‐Evans rat population. Results While we did not find a direct relationship between early‐life licking received and later‐life licking provisioning, this relationship was indirectly affected by dopamine levels in the nucleus accumbens and dependent on variation in the dopamine receptor 2 gene (rs107017253). More specifically, female rat offspring with the A/G genotype showed a positive relationship between average licking received and dopamine levels in the nucleus accumbens of the maternal brain; there was no relationship with female rat offspring with the A/A genotype. The higher dopamine levels in the nucleus accumbens corresponded with higher maternal licking provisioning from postnatal days 2–9. We also discovered and validated several new variants that were predicted by our systematic analysis. Conclusion Our findings suggest that genetic variation influences the relationship between early‐life maternal care received and the dopaminergic system of the maternal brain, which can indirectly influence later‐life maternal care provisioning., Rat mothers exhibit natural variations in care that propagate between generations of female offspring, but there is limited information on genetic variation that influences this propagation. We assessed early‐life maternal care received by individual female rat offspring in relation to genetic polymorphisms linked to dopaminergic activity, maternal care provisioning, and dopaminergic activity in the maternal brain. We found that dopamine receptor 2 (rs107017253) variation interacted with the relationship between early‐life maternal care received and dopamine levels in the nucleus accumbens which, in turn, were associated with later‐life maternal care provisioning.

GeneNetwork and its earlier iteration, WebQTL, have now been an important database and toolkit for quantitative trait genetics research for two decades. Recent improvements to GeneNetwork have reinvigorated it, including the addition of data from 10 species, multi-omics analysis, updated code, and new tools. The new GeneNetwork is now an exciting resource for predictive medicine and systems genetics, which is constantly being maintained and improved. Here, we give a brief overview of the process for carrying out some of the most common functions on GeneNetwork, as a gateway to deeper analyses, demonstrating how a small number of plausible candidate genes can be found for a typical immune phenotype.

Genome-wide association studies have demonstrated significant links between human brain structure and common DNA variants. Similar studies with rodents have been challenging because of smaller brain volumes. Using high field MRI (9.4 T) and compressed sensing, we have achieved microscopic resolution and sufficiently high throughput for rodent population studies. We generated whole brain structural MRI and diffusion connectomes for four diverse isogenic lines of mice (C57BL/6J, DBA/2J, CAST/EiJ, and BTBR) at spatial resolution 20,000 times higher than human connectomes. We measured narrow sense heritability (h2) I.e. the fraction of variance explained by strains in a simple ANOVA model for volumes and scalar diffusion metrics, and estimates of residual technical error for 166 regions in each hemisphere and connectivity between the regions. Volumes of discrete brain regions had the highest mean heritability (0.71 ± 0.23 SD, n = 332), followed by fractional anisotropy (0.54 ± 0.26), radial diffusivity (0.34 ± 0.022), and axial diffusivity (0.28 ± 0.19). Connection profiles were statistically different in 280 of 322 nodes across all four strains. Nearly 150 of the connection profiles were statistically different between the C57BL/6J, DBA/2J, and CAST/EiJ lines. Microscopic whole brain MRI/DTI has allowed us to identify significant heritable phenotypes in brain volume, scalar DTI metrics, and quantitative connectomes.

Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV, MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virus-induced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.

Between 25 and 30% of the nearly one million military personnel who participated in the 1991 Persian Gulf War became ill with chronic symptoms ranging from gastrointestinal to nervous system dysfunction. This disorder is now referred to as Gulf War Illness (GWI) and the underlying pathophysiology has been linked to exposure-based neuroinflammation caused by organophosphorous (OP) compounds coupled with high circulating glucocorticoids. In a mouse model of GWI we developed, corticosterone was shown to act synergistically with an OP (diisopropylflurophosphate) to dramatically increase proinflammatory cytokine gene expression in the brain. Because not all Gulf War participants became sick, the question arises as to whether differential genetic constitution might underlie individual differences in susceptibility. To address this question of genetic liability, we tested the impact of OP and glucocorticoid exposure in a genetic reference population of 30 inbred mouse strains. We also studied both sexes. The results showed wide differences among strains and overall that females were less sensitive to the combined treatment than males. Furthermore, we identified one OP-glucocorticoid locus and nominated a candidate gene—Spon1—that may underlie the marked differences in response.

DNA methylation (DNAm) is shaped by genetic and environmental factors and modulated by aging. Here, we examine interrelations between epigenetic aging, body weight (BW), and life span in 12 isogenic strains from the BXD family of mice that exhibit over twofold variation in longevity. Genome‐wide DNAm was assayed in 70 liver specimens from predominantly female cases, 6–25 months old, that were maintained on normal chow or high‐fat diet (HFD). We defined subsets of CpG regions associated with age, BW at young adulthood, and strain‐by‐diet‐dependent life span. These age‐associated differentially methylated CpG regions (age‐DMRs) featured distinct genomic characteristics, with DNAm gains over time occurring in sites such as promoters and exons that have high CpG density and low average methylation. CpG regions associated with BW were enriched in introns, tended to have lower methylation in mice with higher BW, and were inversely correlated with gene expression (i.e., higher mRNA levels in mice with higher BW). CpG regions associated with life span were linked to genes involved in life span modulation, including the telomerase reverse transcriptase gene, Tert, which had both lower methylation and higher expression in long‐lived strains. An epigenetic clock defined from age‐DMRs revealed accelerated aging in mice belonging to strains with shorter life spans. Both higher BW and the HFD were associated with accelerated epigenetic aging. Our results highlight the age‐accelerating effect of heavier BW. Furthermore, we demonstrate that the measure of epigenetic aging derived from age‐DMRs can predict genotype and diet‐induced differences in life span among female BXD members., The epigenetic clock, also referred to as DNA methylation age, provides a measure of biological aging. This clock can predict life expectancy in genetically distinct mouse stains, and is accelerated by higher body weight and high‐fat diet.

In most mammals, mothers exhibit natural variations in care that propagate between generations of female offspring. However, there is limited information on genetic variation that influences this propagation. We assessed early-life maternal care received by individual female rat offspring in relation to genetic polymorphisms linked to dopaminergic activity, maternal care provisioning, and dopaminergic activity in the maternal brain. We also conducted a systematic analysis of other genetic variants potentially related to maternal behavior in our Long-Evans rat population. We found that dopamine receptor 2 (rs107017253) variation interacted with the relationship between early-life maternal care received and dopamine levels in the nucleus accumbens which, in turn, were associated with later-life maternal care provisioning. We also discovered and validated new variants that were predicted by our systematic analysis. Our findings suggest that genetic variation influences the relationship between maternal care received and maternal care provisioning, similar to findings in human populations.

Background Gulf War illness (GWI) is an archetypal, medically unexplained, chronic condition characterised by persistent sickness behaviour and neuroimmune and neuroinflammatory components. An estimated 25–32% of the over 900,000 veterans of the 1991 Gulf War fulfil the requirements of a GWI diagnosis. It has been hypothesised that the high physical and psychological stress of combat may have increased vulnerability to irreversible acetylcholinesterase (AChE) inhibitors leading to a priming of the neuroimmune system. A number of studies have linked high levels of psychophysiological stress and toxicant exposures to epigenetic modifications that regulate gene expression. Recent research in a mouse model of GWI has shown that pre-exposure with the stress hormone corticosterone (CORT) causes an increase in expression of specific chemokines and cytokines in response to diisopropyl fluorophosphate (DFP), a sarin surrogate and irreversible AChE inhibitor. Methods C57BL/6J mice were exposed to CORT for 4 days, and exposed to DFP on day 5, before sacrifice 6 h later. The transcriptome was examined using RNA-seq, and the epigenome was examined using reduced representation bisulfite sequencing and H3K27ac ChIP-seq. Results We show transcriptional, histone modification (H3K27ac) and DNA methylation changes in genes related to the immune and neuronal system, potentially relevant to neuroinflammatory and cognitive symptoms of GWI. Further evidence suggests altered proportions of myelinating oligodendrocytes in the frontal cortex, perhaps connected to white matter deficits seen in GWI sufferers. Conclusions Our findings may reflect the early changes which occurred in GWI veterans, and we observe alterations in several pathways altered in GWI sufferers. These close links to changes seen in veterans with GWI indicates that this model reflects the environmental exposures related to GWI and may provide a model for biomarker development and testing future treatments. Electronic supplementary material The online version of this article (10.1186/s12974-018-1113-9) contains supplementary material, which is available to authorized users.

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype with poor outcomes. This is a grave clinical challenge for the ~30,000 patients diagnosed with this disease every year. Discovering genetic modifiers of differential TNBC vulnerability and disease progression is critical to improving predictive and personalized treatments. We hypothesized that using a well-established recombinant inbred strain, novel genetic modifiers of TNBC risk and aggression will be identified. The C3(1)-T antigen (C3Tag) genetically engineered mouse model (GEMM) recapitulates many facets of human basal-like TNBC to demonstrate promoting effects of exposures on tumor phenotypes. However, GEMM are highly constrained by their inbred genotype and do not allow a robust interrogation of the manner in which individual genetic variation might impact tumor initiation, progression, and response to therapy. Therefore, we developed a novel murine model of TNBC in the background of the largest and best characterized genetic reference population. Systems genetics is used to identify gene candidates. Cross-species comparison of our findings with publicly available human GWAS and genomic databases is an effective approach to validate conserved biologically relevant and targetable pathways. To our knowledge, this is the first study to explore modifier genes for TNBC phenotypes using a systems genetics approach in a GEMM for TNBC. Our results will contribute to significant advances in understanding risk and improving outcomes for breast cancer. Citation Format: Laura M. Sipe, Emily B. Korba, Lu Lu, Robert W. Williams, David G. Ashbrook, Liza Makowski. Novel pre-clinical model to identify genetic modifiers of triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2919.

SUMMARYGenome-wide association studies have demonstrated significant links between human brain structure and common DNA variants. Similar studies with rodents have been challenging because of smaller brain volumes. Using high field MRI (9.4T) and compressed sensing, we have achieved microscopic resolution and sufficiently high throughput for rodent population studies. We generated whole brain structural MRI and diffusion connectomes for four diverse isogenic lines of mice (C57BL/6J, DBA/2J, CAST/EiJ, and BTBR) at spatial resolution 20,000 times higher than human connectomes. We derived volumes, scalar diffusion metrics, and estimates of residual technical error for 166 regions in each hemisphere and connectivity between the regions. Volumes of discrete brain regions had the highest mean heritability (0.71 ± 0.23 SD, n = 332), followed by fractional anisotropy (0.54 ± 0.26), radial diffusivity (0.34 ± 0.022), and axial diffusivity (0.28 ± 0.19). Connection profiles were statistically different in 280 of 322 nodes across all four strains. Nearly 150 of the connection profiles were statistically different between the C57BL/6J, DBA/2J, and CAST/EiJ lines.

The challenge of precision medicine is to model complex interactions among DNA variants, sets of phenotypes, and complex environmental factors and confounders. We have expanded the BXD family, creating a powerful and extensible test bed for experimental precision medicine and an ideal cohort to study gene-by-environmental interactions.These BXD segregate for over 6 million variants, with a mean minor allele frequency close to 0.5. We have increased the family two-fold to 150 inbred strains, all derived from C57BL/6J and DBA/2J. We have also generated updated and comprehensive genotypes and an unrivaled deep phenome.Approximately 10,000 recombinations have been located, allowing precision of quantitative trait loci mapping of ±2.0 Mb over much of the genome and ±0.5 Mb for Mendelian loci. The BXD phenome includes more than 100 ‘omics data sets and >7000 quantitative and clinical phenotypes, all of which is publicly available.The BXD family is an enduring, collaborative, and replicable resource to test causal and mechanistic links between genomes and phenomes at many stages and under a wide variety of treatments and interventions.

Parental care is found widely across animal taxa and is manifest in a range of behaviours from basic provisioning in cockroaches to highly complex behaviours seen in mammals. The evolution of parental care is viewed as the outcome of an evolutionary cost/benefit trade-off between investing in current and future offspring, leading to the selection of traits in offspring that influence parental behaviour. Thus, level and quality of parental care are affected by both parental and offspring genetic differences that directly and indirectly influence parental care behaviour. While significant research effort has gone into understanding how parental genomes affect parental, and mostly maternal, behaviour, few studies have investigated how offspring genomes affect parental care. In this review, we bring together recent findings across different fields focussing on the mechanism and genetics of offspring effects on maternal care in mammals.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is an example of a complex disease of unknown etiology. Multiple studies point to disruptions in immune functioning in ME/CFS patients as well as with specific genetic polymorphisms and alterations of the DNA methylome in lymphocytes. However, the association between DNA methylation and genetic background in relation to the ME/CFS is currently unknown. In this study we explored this association by characterizing the genomic (~4.3 million SNPs) and epigenomic (~480 thousand CpG loci) variability between populations of ME/CFS patients and healthy controls. We found significant associations of methylation states in T-lymphocytes at several CpG loci and regions with ME/CFS phenotype. These methylation anomalies are in close proximity to genes involved with immune function and cellular metabolism. Finally, we found significant correlations of genotypes with methylation phenotypes associated with ME/CFS. The findings from this study highlight the role of epigenetic and genetic interactions in complex diseases, and suggest several genetic and epigenetic elements potentially involved in the mechanisms of disease in ME/CFS.

What was once expensive and revolutionary—full genome sequence—is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women’s Health Initiative (www.whi.org), the Million Veterans Program (www.research.va.gov/MVP), the 100,000 Genomes Project (genomicsengland.co.uk), and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and samples sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequence of this new affordability of massive omics data sets: (1) It is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part—the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits, and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

Family members show behavioural strategies predicted to maximize individual fitness. These behaviours depend directly on genes expressed in focal individuals but also indirectly on genes expressed in other family members. However, how sibling and parental behavioural strategies are modified by genes expressed in family members, and to what degree, remains unclear. To answer this question, we have used a split litter design in an experimental population of genetically variable mouse families, and identified loci that indirectly affected sibling and maternal behaviour simultaneously. These loci map to genomic regions that also show a direct effect on offspring behaviour. Directly and indirectly affected traits were significantly correlated at the phenotypic level, illustrating how indirect effects are caused. Genetic variants in offspring that influence solicitation also impacted their siblings' and maternal behaviour. However, in contrast to predictions from sibling competition, unrelated litter mates benefited from increased solicitation. Overall, such indirect genetic effects explained a large proportion of variation seen in behaviours, with candidate genes involved in metabolism to neuronal development. These results reveal that we need to view behavioural strategies as the result of conjoint selection on genetic variation in all interacting family members.

Most animal species are social in one form or another, yet many studies in rodent model systems use either individually housed animals or ignore potential confounds caused by group housing. While such social interaction effects on developmental and behavioral traits are well established, the genetic basis of social interactions has not been researched in as much detail. Specifically, the effects of genetic variation in social partners on the phenotype of a focal individual have mostly been studied at the phenotypic level. Such indirect genetic effects (IGEs), where the genotype of one individual influences the phenotype of a second individual, can have important evolutionary and medically relevant consequences. In this chapter, we give a brief outline of social interaction effects, and how systems genetics approaches using recombinant inbred populations can be used to investigate indirect genetic effects specifically, including maternal genetic effects. We discuss experimental designs for the study of IGEs and show how indirect genetic loci can be identified that underlie social interaction effects, their mechanisms, and consequences for trait variation in focal individuals.

Most animal species are social in one form or another, yet many studies in rodent model systems use either individually housed animals or ignore potential confounds caused by group housing. While such social interaction effects on developmental and behavioral traits are well established, the genetic basis of social interactions has not been researched in as much detail. Specifically, the effects of genetic variation in social partners on the phenotype of a focal individual have mostly been studied at the phenotypic level. Such indirect genetic effects (IGEs), where the genotype of one individual influences the phenotype of a second individual, can have important evolutionary and medically relevant consequences. In this chapter, we give a brief outline of social interaction effects, and how systems genetics approaches using recombinant inbred populations can be used to investigate indirect genetic effects specifically, including maternal genetic effects. We discuss experimental designs for the study of IGEs and show how indirect genetic loci can be identified that underlie social interaction effects, their mechanisms, and consequences for trait variation in focal individuals.

Conflict over parental investment between parent and offspring is predicted to lead to selection on genes expressed in offspring for traits influencing maternal investment, and on parentally expressed genes affecting offspring behaviour. However, the specific genetic variants that indirectly modify maternal or offspring behaviour remain largely unknown. Using a cross-fostered population of mice, we map maternal behaviour in genetically uniform mothers as a function of genetic variation in offspring and identify loci on offspring chromosomes 5 and 7 that modify maternal behaviour. Conversely, we found that genetic variation among mothers influences offspring development, independent of offspring genotype. Offspring solicitation and maternal behaviour show signs of coadaptation as they are negatively correlated between mothers and their biological offspring, which may be linked to costs of increased solicitation on growth found in our study. Overall, our results show levels of parental provisioning and offspring solicitation are unique to specific genotypes. DOI: http://dx.doi.org/10.7554/eLife.11814.001, eLife digest Genes encode instructions that can influence the behaviour and physical traits of the individual that carries them. Individuals of the same species can carry different versions (or variants) of the same gene, leading to a variety of traits in the population. However, a gene expressed in one individual can also alter the traits of another individual. This is known as an indirect genetic effect. For example, a gene in a mother that affects her ability to provide care may influence how her offspring develop. Researchers have predicted that offspring should be able to manipulate their mothers to try and gain more care than the mothers are willing to give. Furthermore, the offspring born to mothers who respond to this begging are predicted to save energy and beg less. However, few gene variants that indirectly modify the behaviour of mothers or offspring have so far been identified. Ashbrook et al. used mice to test the idea that genetic variation in particular locations in the offspring’s genome can affect maternal behaviour, and vice versa. In the first experiment, mother mice with different gene variants fostered litters of mouse pups that were all genetically identical. In the other experiment, genetically identical mothers fostered litters of mouse pups with different gene variants. Ashbrook et al. identified several locations in the offspring’s genome that modified the behaviour of their foster mothers. Furthermore, the experiments also show that genetic variation among the mothers influenced the development of their offspring, independent of the genes carried by the offspring. The next steps are to identify the specific genes underlying the changes in behaviour, and the molecular and genetic pathways by which they impact indirectly on the traits of other individuals. DOI: http://dx.doi.org/10.7554/eLife.11814.002

Bipolar disorder (BD) is a significant neuropsychiatric disorder with a lifetime prevalence of ~1%. To identify genetic variants underlying BD genome-wide association studies (GWAS) have been carried out. While many variants of small effect associated with BD have been identified few have yet been confirmed, partly because of the low power of GWAS due to multiple comparisons being made. Complementary mapping studies using murine models have identified genetic variants for behavioral traits linked to BD, often with high power, but these identified regions often contain too many genes for clear identification of candidate genes. In the current study we have aligned human BD GWAS results and mouse linkage studies to help define and evaluate candidate genes linked to BD, seeking to use the power of the mouse mapping with the precision of GWAS. We use quantitative trait mapping for open field test and elevated zero maze data in the largest mammalian model system, the BXD recombinant inbred mouse population, to identify genomic regions associated with these BD-like phenotypes. We then investigate these regions in whole genome data from the Psychiatric Genomics Consortium’s bipolar disorder GWAS to identify candidate genes associated with BD. Finally we establish the biological relevance and pathways of these genes in a comprehensive systems genetics analysis. We identify four genes associated with both mouse anxiety and human BD. While TNR is a novel candidate for BD, we can confirm previously suggested associations with CMYA5, MCTP1 and RXRG. A cross49 species, systems genetics analysis shows that MCTP1, RXRG and TNR coexpress with genes linked to psychiatric disorders and identify the striatum as a potential site of action. CMYA5, MCTP1, RXRG and TNR are associated with mouse anxiety and human BD. We hypothesize that MCTP1, RXRG and TNR influence intercellular signaling in the striatum.

Adult neurogenesis, the lifelong production of new neurons in the adult brain, is under complex genetic control but many of the genes involved remain to be identified. In this study, we have integrated publicly available gene expression data from the BXD and CXB recombinant inbred mouse lines to discover genes co-expressed in the adult hippocampus with Nestin, a common marker of the neural precursor cell population. In addition, we incorporated spatial expression information to restrict candidates to genes with high differential gene expression in the hippocampal dentate gyrus. Incorporating data from curated protein-protein interaction databases revealed interactions between our candidate genes and those already known to be involved in adult neurogenesis. Enrichment analysis suggested a link to the Wnt/β-catenin pathway, known to be involved in adult neurogenesis. In particular, our candidates were enriched in targets of Lef1, a modulator of the Wnt pathway. In conclusion, our combination of bioinformatics approaches identified six novel candidate genes involved in adult neurogenesis; Amer3, Eya3, Mtdh, Nr4a3, Polr2a, and Tbkbp1. Further, we propose a role for Lef1 transcriptional control in the regulation of adult hippocampal precursor cell proliferation.

The close interaction between mother and offspring in mammals is thought to contribute to the evolution of genomic imprinting or parent-of-origin dependent gene expression. Empirical tests of theories about the evolution of imprinting have been scant for several reasons.Models make different assumptions about the traits affected by imprinted genes and the scenarios in which imprinting is predicted to have been selected for. Thus, competing hypotheses cannot readily be tested against each other. Further, it is far from clear how predictions about expression patterns of genes with specific phenotypic effects can be tested given current methodology of assaying gene expression levels, be it in the brain or in other tissues.We first set out a scenario for testing competing hypotheses and delineate the different assumptions and predictions of models.We then outline how predictions may be tested using mouse models such as intercrosses or recombinant inbred systems that can be phenotyped for traits relevant to imprinting theories. Further, we briefly discuss different molecular approaches that may be used in conjunction with experiments to ascertain expression patterns of imprinted genes and thus the testing of predictions. © 2013 Ashbrook and Hager.

Background Variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. To identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as ENIGMA have used large magnetic resonance imaging (MRI) data sets in human GWAS studies. In addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. A key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders. Results We combine the largest human GWAS of brain structure with the largest mammalian model system, the BXD recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. We first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, MGST3, associated with adult hippocampus size in both systems. We then establish the coregulation and function of this gene in a comprehensive systems-analysis. Conclusions We find that MGST3 is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as Alzheimer’s. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-850) contains supplementary material, which is available to authorized users.

How lifespan and body weight vary as a function of diet and genetic differences is not well understood. Here we quantify the impact of differences in diet on lifespan in a genetically diverse family of female mice, split into matched isogenic cohorts fed a low-fat chow diet (CD, n = 663) or a high-fat diet (HFD, n = 685). We further generate key metabolic data in a parallel cohort euthanized at four time points. HFD feeding shortens lifespan by 12%: equivalent to a decade in humans. Initial body weight and early weight gains account for longevity differences of roughly 4-6 days per gram. At 500 days, animals on a HFD typically gain four times as much weight as control, but variation in weight gain does not correlate with lifespan. Classic serum metabolites, often regarded as health biomarkers, are not necessarily strong predictors of longevity. Our data indicate that responses to a HFD are substantially modulated by gene-by-environment interactions, highlighting the importance of genetic variation in making accurate individualized dietary recommendations., Roy et al. quantify the impact of a high-fat diet across genetically diverse strains of mice, revealing a generally negative effect on lifespan but also a wide variability.

The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely powerful model for precision medicine. This family segregates for 6 million common DNA variants—a level that exceeds many human populations. Because each member can be replicated, heritable traits can be mapped with high power and precision. Current BXD phenomes are unsurpassed in coverage and include much omics data and thousands of quantitative traits. The BXDs can be extended by a single-generation cross to as many as 19,460 isogenic F1 progeny, and this extended BXD family is an effective platform for testing causal modeling and for predictive validation. The BXDs are a unique core resource for the field of experimental precision medicine.