Analyzing complex traits with congenic strains

Integrative analysis of hepatic transcriptional profiles reveals genetic regulation of atherosclerosis in hyperlipidemic Diversity Outbred-F1 mice

Atherogenesis is an insipidus but precipitating process leading to serious consequences of many cardiovascular diseases (CVD). Numerous genetic loci contributing to atherosclerosis have been identified in human genome-wide association studies, but these studies have limitations in the ability to control environmental factors and to decipher cause/effect relationships. To assess the power of hyperlipidemic Diversity Outbred (DO) mice in facilitating quantitative trait loci (QTL) analysis of complex traits, we generated a high-resolution genetic panel of atherosclerosis susceptible (DO-F1) mouse cohort by crossing 200 DO females with C57BL/6J males carrying two human genes: encoding apolipoprotein E3-Leiden and cholesterol ester transfer protein. We examined atherosclerotic traits including plasma lipids and glucose in the 235 female and 226 male progeny before and after 16 weeks of a high-fat/cholesterol diet, and aortic plaque size at 24 weeks. We also assessed the liver transcriptome using RNA-sequencing. Our QTL mapping for atherosclerotic traits identified one previously reported female-specific QTL on Chr10 with a narrower interval of 22.73 to 30.80 Mb, and one novel male-specific QTL at 31.89 to 40.25 Mb on Chr19. Liver transcription levels of several genes within each QTL were highly correlated with the atherogenic traits. A majority of these candidates have already known atherogenic potential in humans and/or mice, but integrative QTL, eQTL, and correlation analyses further pointed Ptprk as a major candidate of the Chr10 QTL, while Pten and Cyp2c67 of the Chr19 QTL in our DO-F1 cohort. Finally, through additional analyses of RNA-seq data we identified genetic regulation of hepatic transcription factors, including Nr1h3, contributes to atherogenesis in this cohort. Thus, an integrative approach using DO-F1 mice effectively validates the influence of genetic factors on atherosclerosis in DO mice and suggests an opportunity to discover therapeutics in the setting of hyperlipidemia.

Induced mammary cancer in rat models: pathogenesis, genetics, and relevance to female breast cancer

Mammary cancer, or breast cancer in women, is a polygenic disease with a complex etiopathogenesis. While much remains elusive regarding its origin, it is well established that chemical carcinogens and endogenous estrogens contribute significantly to the initiation and progression of this disease. Rats have been useful models to study induced mammary cancer. They develop mammary tumors with comparable histopathology to humans and exhibit differences in resistance or susceptibility to mammary cancer depending on strain. While some rat strains (e.g., Sprague-Dawley) readily form mammary tumors following treatment with the chemical carcinogen, 7,12-dimethylbenz[a]-anthracene (DMBA), other strains (e.g., Copenhagen) are resistant to DMBA-induced mammary carcinogenesis. Genetic linkage in inbred strains has identified strain-specific quantitative trait loci (QTLs) affecting mammary tumors, via mechanisms that act together to promote or attenuate, and include 24 QTLs controlling the outcome of chemical induction, 10 QTLs controlling the outcome of estrogen induction, and 4 QTLs controlling the outcome of irradiation induction. Moreover, and based on shared factors affecting mammary cancer etiopathogenesis between rats and humans, including orthologous risk regions between both species, rats have served as useful models for identifying methods for breast cancer prediction and treatment. These studies in rats, combined with alternative animal models that more closely mimic advanced stages of breast cancer and/or human lifestyles, will further improve our understanding of this complex disease.

Natural genetic variation as a tool for discovery in Caenorhabditis nematodes

Over the last 20 years, studies of Caenorhabditis elegans natural diversity have demonstrated the power of quantitative genetic approaches to reveal the evolutionary, ecological, and genetic factors that shape traits. These studies complement the use of the laboratory-adapted strain N2 and enable additional discoveries not possible using only one genetic background. In this chapter, we describe how to perform quantitative genetic studies in Caenorhabditis, with an emphasis on C. elegans. These approaches use correlations between genotype and phenotype across populations of genetically diverse individuals to discover the genetic causes of phenotypic variation. We present methods that use linkage, near-isogenic lines, association, and bulk-segregant mapping, and we describe the advantages and disadvantages of each approach. The power of C. elegans quantitative genetic mapping is best shown in the ability to connect phenotypic differences to specific genes and variants. We will present methods to narrow genomic regions to candidate genes and then tests to identify the gene or variant involved in a quantitative trait. The same features that make C. elegans a preeminent experimental model animal contribute to its exceptional value as a tool to understand natural phenotypic variation.

Integrative genomic analysis of blood pressure and related phenotypes in rats

Despite remarkable progress made in human genome-wide association studies, there remains a substantial gap between statistical evidence for genetic associations and functional comprehension of the underlying mechanisms governing these associations. As a means of bridging this gap, we performed genomic analysis of blood pressure (BP) and related phenotypes in spontaneously hypertensive rats (SHR) and their substrain, stroke-prone SHR (SHRSP), both of which are unique genetic models of severe hypertension and cardiovascular complications. By integrating whole-genome sequencing, transcriptome profiling, genome-wide linkage scans (maximum n=1415), fine congenic mapping (maximum n=8704), pharmacological intervention and comparative analysis with transcriptome-wide association study (TWAS) datasets, we searched causal genes and causal pathways for the tested traits. The overall results validated the polygenic architecture of elevated BP compared with a non-hypertensive control strain, Wistar Kyoto rats (WKY); e.g. inter-strain BP differences between SHRSP and WKY could be largely explained by an aggregate of BP changes in seven SHRSP-derived consomic strains. We identified 26 potential target genes, including rat homologs of human TWAS loci, for the tested traits. In this study, we re-discovered 18 genes that had previously been determined to contribute to hypertension or cardiovascular phenotypes. Notably, five of these genes belong to the kallikrein-kinin/renin-angiotensin systems (KKS/RAS), in which the most prominent differential expression between hypertensive and non-hypertensive alleles could be detected in rat Klk1 paralogs. In combination with a pharmacological intervention, we provide in vivo experimental evidence supporting the presence of key disease pathways, such as KKS/RAS, in a rat polygenic hypertension model.

Genetic controls of Tas1r3-independent sucrose consumption in mice

We have previously used crosses between C57BL/6ByJ (B6) and 129P3/J (129) inbred strains to map a quantitative trait locus (QTL) on mouse chromosome (Chr) 4 that affects behavioral and neural responses to sucrose. We have named it the sucrose consumption QTL 2 (Scon2), and shown that it corresponds to the Tas1r3 gene, which encodes a sweet taste receptor subunit TAS1R3. To discover other sucrose consumption QTLs, we have intercrossed B6 inbred and 129.B6-Tas1r3 congenic mice to produce F₂ hybrids, in which Scon2 (Tas1r3) does not segregate, and hence does not contribute to phenotypical variation. Chromosome mapping using this F₂ intercross identified two main-effect QTLs, Scon3 (Chr9) and Scon10 (Chr14), and an epistatically interacting QTL pair Scon3 (Chr9)-Scon4 (Chr1). Using serial backcrosses, congenic and consomic strains, we conducted high-resolution mapping of Scon3 and Scon4 and analyzed their epistatic interactions. We used mice with different Scon3 or Scon4 genotypes to understand whether these two QTLs influence sucrose intake via gustatory or postoral mechanisms. These studies found no evidence for involvement of the taste mechanisms, but suggested involvement of energy metabolism. Mice with the B6 Scon4 genotype drank less sucrose in two-bottle tests, and also had a higher respiratory exchange ratio and lower energy expenditure under basal conditions (when they had only chow and water available). Our results provide evidence that Scon3 and Scon4 influence mouse-to-mouse variation in sucrose intake and that both likely act through a common postoral mechanism.

Tightly linked antagonistic-effect loci underlie polygenic phenotypic variation in C. elegans

Recent work has provided strong empirical support for the classic polygenic model for trait variation. Population-based findings suggest that most regions of genome harbor variation affecting most traits. Here, we use the approach of experimental genetics to show that, indeed, most genomic regions carry variants with detectable effects on growth and reproduction in Caenorhabditis elegans populations sensitized by nickel stress. Nine of 15 adjacent intervals on the X chromosome, each encompassing ∼0.001 of the genome, have significant effects when tested individually in near-isogenic lines (NILs). These intervals have effects that are similar in magnitude to those of genome-wide significant loci that we mapped in a panel of recombinant inbred advanced intercross lines (RIAILs). If NIL-like effects were randomly distributed across the genome, the RIAILs would exhibit phenotypic variance that far exceeds the observed variance. However, the NIL intervals are arranged in a pattern that significantly reduces phenotypic variance relative to a random arrangement; adjacent intervals antagonize one another, cancelling each other's effects. Contrary to the expectation of small additive effects, our findings point to large-effect variants whose effects are masked by epistasis or linkage disequilibrium between alleles of opposing effect.

The genomic basis of environmental adaptation in house mice

House mice (Mus musculus) arrived in the Americas only recently in association with European colonization (~400-600 generations), but have spread rapidly and show evidence of local adaptation. Here, we take advantage of this genetic model system to investigate the genomic basis of environmental adaptation in house mice. First, we documented clinal patterns of phenotypic variation in 50 wild-caught mice from a latitudinal transect in Eastern North America. Next, we found that progeny of mice from different latitudes, raised in a common laboratory environment, displayed differences in a number of complex traits related to fitness. Consistent with Bergmann's rule, mice from higher latitudes were larger and fatter than mice from lower latitudes. They also built bigger nests and differed in aspects of blood chemistry related to metabolism. Then, combining exomic, genomic, and transcriptomic data, we identified specific candidate genes underlying adaptive variation. In particular, we defined a short list of genes with cis-eQTL that were identified as candidates in exomic and genomic analyses, all of which have known ties to phenotypes that vary among the studied populations. Thus, wild mice and the newly developed strains represent a valuable resource for future study of the links between genetic variation, phenotypic variation, and climate.

Fine mapping of the major bleomycin-induced pulmonary fibrosis susceptibility locus in mice

Susceptibility to fibrotic lung disease differs among people and among inbred strains of mice exposed to bleomycin where C57BL/6J mice are susceptible and C3H/HeJ mice are spared fibrotic disease. Genetic mapping studies completed in offspring derived from these inbred strains revealed the inheritance of C57BL/6J alleles at loci, including the major locus on chromosome 17, called Blmpf1 bleomycin-induced pulmonary fibrosis 1, to be linked to pulmonary fibrosis in treated mice. In the present study, to reduce the interval of Blmpf1, we bred and phenotyped a panel of subcongenic mice with C3H/HeJ alleles in a C57BL/6J background. Subcongenic mice received bleomycin via osmotic minipump and the fibrosis phenotype was measured histologically. Inheritance of C3H/HeJ alleles from 34.31 to 35.02 Mb was revealed to spare bleomycin-induced pulmonary fibrosis of C57BL/6J mice. From database analysis, 40 protein coding genes have been mapped to this reduced Blmpf1 interval, 18 of which contain C57BL/6J:C3H/HeJ sequence polymorphisms predicted to affect protein structure or to confer allele-dependent expression, and by RT-PCR analysis of lung tissue, we show 6 of these genes to differ in expression between C57BL/6J and C3H/HeJ mice. Genes known to regulate T cell numbers and activation (Btnl family, Notch4) are among the limited list of potential causal variants leading to lung disease in this model and the bronchoalveolar lavage of protected subcongenic mice had fewer lymphocytes, post bleomycin, than did C57BL/6J mice. We conclude that Blmpf1genes contributing to the susceptibility to bleomycin-induced pulmonary fibrosis could alter the adaptive immune response of C57BL/6J mice.

Burly1 is a mouse QTL for lean body mass that maps to a 0.8-Mb region of chromosome 2

To fine map a mouse QTL for lean body mass (Burly1), we used information from intercross, backcross, consomic, and congenic mice derived from the C57BL/6ByJ (host) and 129P3/J (donor) strains. The results from these mapping populations were concordant and showed that Burly1 is located between 151.9 and 152.7 Mb (rs33197365 to rs3700604) on mouse chromosome 2. The congenic region harboring Burly1 contains 26 protein-coding genes, 11 noncoding RNA elements (e.g., lncRNA), and 4 pseudogenes, with 1949 predicted functional variants. Of the protein-coding genes, 7 have missense variants, including genes that may contribute to lean body weight, such as Angpt41, Slc52c3, and Rem1. Lean body mass was increased by the B6-derived variant relative to the 129-derived allele. Burly1 influenced lean body weight at all ages but not food intake or locomotor activity. However, congenic mice with the B6 allele produced more heat per kilogram of lean body weight than did controls, pointing to a genotype effect on lean mass metabolism. These results show the value of integrating information from several mapping populations to refine the map location of body composition QTLs and to identify a short list of candidate genes.

Adiposity QTL Adip20 decomposes into at least four loci when dissected using congenic strains

An average mouse in midlife weighs between 25 and 30 g, with about a gram of tissue in the largest adipose depot (gonadal), and the weight of this depot differs between inbred strains. Specifically, C57BL/6ByJ mice have heavier gonadal depots on average than do 129P3/J mice. To understand the genetic contributions to this trait, we mapped several quantitative trait loci (QTLs) for gonadal depot weight in an F2 intercross population. Our goal here was to fine-map one of these QTLs, Adip20 (formerly Adip5), on mouse chromosome 9. To that end, we analyzed the weight of the gonadal adipose depot from newly created congenic strains. Results from the sequential comparison method indicated at least four rather than one QTL; two of the QTLs were less than 0.5 Mb apart, with opposing directions of allelic effect. Different types of evidence (missense and regulatory genetic variation, human adiposity/body mass index orthologues, and differential gene expression) implicated numerous candidate genes from the four QTL regions. These results highlight the value of mouse congenic strains and the value of this sequential method to dissect challenging genetic architecture.

Identification of Candidate Genes for Generalized Tonic-Clonic Seizures in Noda Epileptic Rat

The Noda epileptic rat (NER) exhibits generalized tonic-clonic seizures (GTCS). A genetic linkage analysis identified two GTCS-associated loci, Ner1 on Chr 1 and Ner3 on Chr 5. The wild-type Ner1 and Ner3 alleles suppressed GTCS when combined in double-locus congenic lines, but not when present in single-locus congenic lines. Global expression analysis revealed that cholecystokinin B receptor (Cckbr) and suppressor of tumorigenicity 5 (St5), which map within Ner1, and PHD finger protein 24 (Phf24), which maps within Ner3, were significantly downregulated in NER. De novo BAC sequencing detected an insertion of an endogenous retrovirus sequence in intron 2 of the Phf24 gene in the NER genome, and PHF24 protein was almost absent in the NER brain. Phf24 encodes a G_αi-interacting protein involved in GABA_B receptor signaling pathway. Based on these findings, we conclude that Cckbr, St5, and Phf24 are strong candidate genes for GTCS in NER.

From Peas to Disease: Modifier Genes, Network Resilience, and the Genetics of Health

Phenotypes are rarely consistent across genetic backgrounds and environments, but instead vary in many ways depending on allelic variants, unlinked genes, epigenetic factors, and environmental exposures. In the extreme, individuals carrying the same causal DNA sequence variant but on different backgrounds can be classified as having distinct conditions. Similarly, some individuals that carry disease alleles are nevertheless healthy despite affected family members in the same environment. These genetic background effects often result from the action of so-called "modifier genes" that modulate the phenotypic manifestation of target genes in an epistatic manner. While complicating the prospects for gene discovery and the feasibility of mechanistic studies, such effects are opportunities to gain a deeper understanding of gene interaction networks that provide organismal form and function as well as resilience to perturbation. Here, we review the principles of modifier genetics and assess progress in studies of modifier genes and their targets in both simple and complex traits. We propose that modifier effects emerge from gene interaction networks whose structure and function vary with genetic background and argue that these effects can be exploited as safe and effective ways to prevent, stabilize, and reverse disease and dysfunction.

If genetic variation could talk: What genomic data may teach us about the importance of gene expression regulation in the genetics of autism

Autism spectrum disorder (ASD) has been long known to have substantial genetic etiology. Much research has attempted to identify specific genes contributing to ASD risk with the goal of tying gene function to a molecular pathological explanation for ASD. A unifying molecular pathology would potentially increase understanding of what is going wrong during development, and could lead to diagnostic biomarkers or targeted preventative or therapeutic directions. We review past and current genetic mapping approaches and discuss major results, leading to the hypothesis that global dysregulation of gene or protein expression may be implicated in ASD rather than disturbance of brain-specific functions. If substantiated, this hypothesis might indicate the need for novel experimental and analytical approaches in order to understand this neurodevelopmental disorder, develop biomarkers, or consider treatment approaches.

High-resolution mapping of a novel rat blood pressure locus on chromosome 9 to a region containing the Spp2 gene and colocalization of a QTL for bone mass

Through linkage analysis of the Dahl salt-sensitive (S) rat and the spontaneously hypertensive rat (SHR), a blood pressure (BP) quantitative trait locus (QTL) was previously located on rat chromosome 9. Subsequent substitution mapping studies of this QTL revealed multiple BP QTLs within the originally identified logarithm of odds plot by linkage analysis. The focus of this study was on a 14.39 Mb region, the distal portion of which remained unmapped in our previous studies. High-resolution substitution mapping for a BP QTL in the setting of a high-salt diet indicated that an SHR-derived congenic segment of 787.9 kb containing the gene secreted phosphoprotein-2 (Spp2) lowered BP and urinary protein excretion. A nonsynonymous G/T polymorphism in the Spp2 gene was detected between the S and S.SHR congenic rats. A survey of 45 strains showed that the T allele was rare, being detected only in some substrains of SHR and WKY. Protein modeling prediction through SWISSPROT indicated that the predicted protein product of this variant was significantly altered. Importantly, in addition to improved cardiovascular and renal function, high salt-fed congenic animals carrying the SHR T variant of Spp2 had significantly lower bone mass and altered bone microarchitecture. Total bone volume and volume of trabecular bone, cortical thickness, and degree of mineralization of cortical bone were all significantly reduced in congenic rats. Our study points to opposing effects of a congenic segment containing the prioritized candidate gene Spp2 on BP and bone mass.

Body Composition QTLs Identified in Intercross Populations Are Reproducible in Consomic Mouse Strains

Genetic variation contributes to individual differences in obesity, but defining the exact relationships between naturally occurring genotypes and their effects on fatness remains elusive. As a step toward positional cloning of previously identified body composition quantitative trait loci (QTLs) from F2 crosses of mice from the C57BL/6ByJ and 129P3/J inbred strains, we sought to recapture them on a homogenous genetic background of consomic (chromosome substitution) strains. Male and female mice from reciprocal consomic strains originating from the C57BL/6ByJ and 129P3/J strains were bred and measured for body weight, length, and adiposity. Chromosomes 2, 7, and 9 were selected for substitution because previous F2 intercross studies revealed body composition QTLs on these chromosomes. We considered a QTL confirmed if one or both sexes of one or both reciprocal consomic strains differed significantly from the host strain in the expected direction after correction for multiple testing. Using these criteria, we confirmed two of two QTLs for body weight (Bwq5-6), three of three QTLs for body length (Bdln3-5), and three of three QTLs for adiposity (Adip20, Adip26 and Adip27). Overall, this study shows that despite the biological complexity of body size and composition, most QTLs for these traits are preserved when transferred to consomic strains; in addition, studying reciprocal consomic strains of both sexes is useful in assessing the robustness of a particular QTL.

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

BACKGROUND/OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

High-resolution genetic mapping of complex traits from a combined analysis of F2 and advanced intercross mice

Genetic influences on anxiety disorders are well documented; however, the specific genes underlying these disorders remain largely unknown. To identify quantitative trait loci (QTL) for conditioned fear and open field behavior, we used an F2 intercross (n = 490) and a 34th-generation advanced intercross line (AIL) (n = 687) from the LG/J and SM/J inbred mouse strains. The F2 provided strong support for several QTL, but within wide chromosomal regions. The AIL yielded much narrower QTL, but the results were less statistically significant, despite the larger number of mice. Simultaneous analysis of the F2 and AIL provided strong support for QTL and within much narrower regions. We used a linear mixed-model approach, implemented in the program QTLRel, to correct for possible confounding due to familial relatedness. Because we recorded the full pedigree, we were able to empirically compare two ways of accounting for relatedness: using the pedigree to estimate kinship coefficients and using genetic marker estimates of "realized relatedness." QTL mapping using the marker-based estimates yielded more support for QTL, but only when we excluded the chromosome being scanned from the marker-based relatedness estimates. We used a forward model selection procedure to assess evidence for multiple QTL on the same chromosome. Overall, we identified 12 significant loci for behaviors in the open field and 12 significant loci for conditioned fear behaviors. Our approach implements multiple advances to integrated analysis of F2 and AILs that provide both power and precision, while maintaining the advantages of using only two inbred strains to map QTL.

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

Quantitative trait loci (QTLs) are being used to study genetic networks, protein functions, and systems properties that underlie phenotypic variation and disease risk in humans, model organisms, agricultural species, and natural populations. The challenges are many, beginning with the seemingly simple tasks of mapping QTLs and identifying their underlying genetic determinants. Various specialized resources have been developed to study complex traits in many model organisms. In the mouse, remarkably different pictures of genetic architectures are emerging. Chromosome Substitution Strains (CSSs) reveal many QTLs, large phenotypic effects, pervasive epistasis, and readily identified genetic variants. In contrast, other resources as well as genome-wide association studies (GWAS) in humans and other species reveal genetic architectures dominated with a relatively modest number of QTLs that have small individual and combined phenotypic effects. These contrasting architectures are the result of intrinsic differences in the study designs underlying different resources. The CSSs examine context-dependent phenotypic effects independently among individual genotypes, whereas with GWAS and other mouse resources, the average effect of each QTL is assessed among many individuals with heterogeneous genetic backgrounds. We argue that variation of genetic architectures among individuals is as important as population averages. Each of these important resources has particular merits and specific applications for these individual and population perspectives. Collectively, these resources together with high-throughput genotyping, sequencing and genetic engineering technologies, and information repositories highlight the power of the mouse for genetic, functional, and systems studies of complex traits and disease models.

Highly polygenic variation in environmental perception determines dauer larvae formation in growing populations of Caenorhabditis elegans

Background

Determining how complex traits are genetically controlled is a requirement if we are to predict how they evolve and how they might respond to selection. This requires understanding how distinct, and often more simple, life history traits interact and change in response to environmental conditions. In order to begin addressing such issues, we have been analyzing the formation of the developmentally arrested dauer larvae of Caenorhabditis elegans under different conditions.

Results

We find that 18 of 22 previously identified quantitative trait loci (QTLs) affecting dauer larvae formation in growing populations, assayed by determining the number of dauer larvae present at food patch exhaustion, can be recovered under various environmental conditions. We also show that food patch size affects both the ability to detect QTLs and estimates of effect size, and demonstrate that an allele of nath-10 affects dauer larvae formation in growing populations. To investigate the component traits that affect dauer larvae formation in growing populations we map, using the same introgression lines, QTLs that affect dauer larvae formation in response to defined amounts of pheromone. This identifies 36 QTLs, again demonstrating the highly polygenic nature of the genetic variation underlying dauer larvae formation.

Conclusions

These data indicate that QTLs affecting the number of dauer larvae at food exhaustion in growing populations of C. elegans are highly reproducible, and that nearly all can be explained by variation affecting dauer larvae formation in response to defined amounts of pheromone. This suggests that most variation in dauer larvae formation in growing populations is a consequence of variation in the perception of the food and pheromone environment (i.e. chemosensory variation) and in the integration of these cues.

Widespread genomic incompatibilities in Caenorhabditis elegans

In the Bateson-Dobzhansky-Muller (BDM) model of speciation, incompatibilities emerge from the deleterious interactions between alleles that are neutral or advantageous in the original genetic backgrounds, i.e., negative epistatic effects. Within species such interactions are responsible for outbreeding depression and F2 (hybrid) breakdown. We sought to identify BDM incompatibilities in the nematode Caenorhabditis elegans by looking for genomic regions that disrupt egg laying; a complex, highly regulated, and coordinated phenotype. Investigation of introgression lines and recombinant inbred lines derived from the isolates CB4856 and N2 uncovered multiple incompatibility quantitative trait loci (QTL). These QTL produce a synthetic egg-laying defective phenotype not seen in CB4856 and N2 nor in other wild isolates. For two of the QTL regions, results are inconsistent with a model of pairwise interaction between two loci, suggesting that the incompatibilities are a consequence of complex interactions between multiple loci. Analysis of additional life history traits indicates that the QTL regions identified in these screens are associated with effects on other traits such as lifespan and reproduction, suggesting that the incompatibilities are likely to be deleterious. Taken together, these results indicate that numerous BDM incompatibilities that could contribute to reproductive isolation can be detected and mapped within C. elegans.

A cautionary note on ignoring polygenic background when mapping quantitative trait loci via recombinant congenic strains

In gene mapping, it is common to test for association between the phenotype and the genotype at a large number of loci, i.e., the same response variable is used repeatedly to test a large number of non-independent and non-nested hypotheses. In many of these genetic problems, the underlying model is a mixed model consistent of one or very few major genes concurrently with a genetic background effect, usually thought as of polygenic nature and, consequently, modeled through a random effects term with a well-defined covariance structure dependent upon the kinship between individuals. Either because the interest lies only on the major genes or to simplify the analysis, it is habitual to drop the random effects term and use a simple linear regression model, sometimes complemented with testing via resampling as an attempt to minimize the consequences of this practice. Here, it is shown that dropping the random effects term has not only extreme negative effects on the control of the type I error rate, but it is also unlikely to be fixed by resampling because, whenever the mixed model is correct, this practice does not allow to meet some basic requirements of resampling in a gene mapping context. Furthermore, simulations show that the type I error rates when the random term is ignored can be unacceptably high. As an alternative, this paper introduces a new bootstrap procedure to handle the specific case of mapping by using recombinant congenic strains under a linear mixed model. A simulation study showed that the type I error rates of the proposed procedure are very close to the nominal ones, although they tend to be slightly inflated for larger values of the random effects variance. Overall, this paper illustrates the extent of the adverse consequences of ignoring random effects term due to polygenic factors while testing for genetic linkage and warns us of potential modeling issues whenever simple linear regression for a major gene yields multiple significant linkage peaks.

Multigenic natural variation underlies Caenorhabditis elegans olfactory preference for the bacterial pathogen Serratia marcescens

The nematode Caenorhabditis elegans can use olfaction to discriminate among different kinds of bacteria, its major food source. We asked how natural genetic variation contributes to choice behavior, focusing on differences in olfactory preference behavior between two wild-type C. elegans strains. The laboratory strain N2 strongly prefers the odor of Serratia marcescens, a soil bacterium that is pathogenic to C. elegans, to the odor of Escherichia coli, a commonly used laboratory food source. The divergent Hawaiian strain CB4856 has a weaker attraction to Serratia than the N2 strain, and this behavioral difference has a complex genetic basis. At least three quantitative trait loci (QTLs) from the CB4856 Hawaii strain (HW) with large effect sizes lead to reduced Serratia preference when introgressed into an N2 genetic background. These loci interact and have epistatic interactions with at least two antagonistic QTLs from HW that increase Serratia preference. The complex genetic architecture of this C. elegans trait is reminiscent of the architecture of mammalian metabolic and behavioral traits.

Genetic mapping of variation in dauer larvae development in growing populations of Caenorhabditis elegans

In the nematode Caenorhabditis elegans, the appropriate induction of dauer larvae development within growing populations is likely to be a primary determinant of genotypic fitness. The underlying genetic architecture of natural genetic variation in dauer formation has, however, not been thoroughly investigated. Here, we report extensive natural genetic variation in dauer larvae development within growing populations across multiple wild isolates. Moreover, bin mapping of introgression lines (ILs) derived from the genetically divergent isolates N2 and CB4856 reveals 10 quantitative trait loci (QTLs) affecting dauer formation. Comparison of individual ILs to N2 identifies an additional eight QTLs, and sequential IL analysis reveals six more QTLs. Our results also show that a behavioural, laboratory-derived, mutation controlled by the neuropeptide Y receptor homolog npr-1 can affect dauer larvae development in growing populations. These findings illustrate the complex genetic architecture of variation in dauer larvae formation in C. elegans and may help to understand how the control of variation in dauer larvae development has evolved.

A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F2 cross between CSS-10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS-10 and B6. We then produced congenic strains to fine-map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121-129.068 Mb; build 37) appeared to account for all the difference between CSS-10 and B6. The smaller congenic strain (Line 2: 127.277-129.068 Mb) was intermediate between CSS-10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis-eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F2 crosses can be dissected into multiple smaller QTLs shows a weaknesses of two-stage approaches that seek to use coarse mapping to identify large regions followed by fine-mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine-mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine-mapping QTLs.

Resistance to germline RNA interference in a Caenorhabditis elegans wild isolate exhibits complexity and nonadditivity

Resolving the genetic complexity of heritable phenotypic variation is fundamental to understanding the mechanisms of evolution and the etiology of human disease. Trait variation among isolates from genetically efficient model organisms offers the opportunity to dissect genetic architectures and identify the molecular mechanisms of causation. Here we present a genetic analysis of loss of sensitivity to gene knockdown via exogenous RNA interference in the germline of a wild isolate of the roundworm Caenorhabditis elegans. We find that the loss of RNA interference sensitivity in the wild isolate CB4856 is recessive to the sensitivity of the lab strain N2. A cross of the strains produced F2 with intermediate sensitivities, and the segregation of the trait among F2s strongly deviated from a single locus recessive allele expectation. Linkage analysis in recombinant inbred lines derived from CB4856 and N2 identified a single significant locus on chromosome I that includes the argonaute gene ppw-1. The alleles for ppw-1 were unable to explain the sensitivity of 18 (12.1%) of the recombinant inbred lines. Complementation tests and F2 segregation analysis of these recombinant inbred lines revealed cases of complex epistatic suppression and enhancement of the effects of ppw-1. We conclude that the variation in RNA interference sensitivity between CB4856 and N2 likely involves the nonadditive interactions of eight or more genes in addition to ppw-1.

Genome-wide association studies in mice

Genome-wide association studies (GWASs) have transformed the field of human genetics and have led to the discovery of hundreds of genes that are implicated in human disease. The technological advances that drove this revolution are now poised to transform genetic studies in model organisms, including mice. However, the design of GWASs in mouse strains is fundamentally different from the design of human GWASs, creating new challenges and opportunities. This Review gives an overview of the novel study designs for mouse GWASs, which dramatically improve both the statistical power and resolution compared to classical gene-mapping approaches.

Chromosome substitution strains: gene discovery, functional analysis, and systems studies

Laboratory mice are valuable in biomedical research in part because of the extraordinary diversity of genetic resources that are available for studies of complex genetic traits and as models for human biology and disease. Chromosome substitution strains (CSSs) are important in this resource portfolio because of their demonstrated use for gene discovery, genetic and epigenetic studies, functional characterizations, and systems analysis. CSSs are made by replacing a single chromosome in a host strain with the corresponding chromosome from a donor strain. A complete CSS panel involves a total of 22 engineered inbred strains, one for each of the 19 autosomes, one each for the X and Y chromosomes, and one for mitochondria. A genome survey simply involves comparing each phenotype for each of the CSSs with the phenotypes of the host strain. The CSS panels that are available for laboratory mice have been used to dissect a remarkable variety of phenotypes and to characterize an impressive array of disease models. These surveys have revealed considerable phenotypic diversity even among closely related progenitor strains, evidence for strong epistasis and for heritable epigenetic changes. Perhaps most importantly, and presumably because of their unique genetic constitution, CSSs, and congenic strains derived from them, the genetic variants underlying quantitative trait loci (QTLs) are readily identified and functionally characterized. Together these studies show that CSSs are important resource for laboratory mice.

The juxtaparanodal proteins CNTNAP2 and TAG1 regulate diet-induced obesity

Despite considerable effort, the identification of genes that regulate complex multigenic traits such as obesity has proven difficult with conventional methodologies. The use of a chromosome substitution strain-based mapping strategy based on deep congenic analysis overcame many of the difficulties associated with gene discovery and led to the finding that the juxtaparanodal proteins CNTNAP2 and TAG1 regulate diet-induced obesity. The effects of a mild Cntnap2 mutation on body weight were highly dependent on genetic background, as both obesity-promoting and obesity-resistant effects of Cntnap2 were observed on different genetic backgrounds. The more severe effect of complete TAG1 deficiency, by decreasing food intake, completely prevented the weight gain normally associated with high-fat-diet feeding. Together, these studies implicate two novel proteins in the regulation of diet-induced obesity. Moreover, as juxtaparanodal proteins have previously been implicated in various neurological disorders, our results suggest a potential genetic and molecular link between obesity and diseases such as autism and epilepsy.

Genome-wide association for methamphetamine sensitivity in an advanced intercross mouse line

Sensitivity to the locomotor stimulant effects of methamphetamine (MA) is a heritable trait that utilizes neurocircuitry also associated with the rewarding effects of drugs. We used the power of a C57BL/6J × DBA/2J F(2) intercross (n = 676) and the precision of a C57BL/6J × DBA/2J F(8) advanced intercross line (Aap: B6, D2-G8; or F(8) AIL; n = 552) to identify and narrow quantitative trait loci (QTLs) associated with sensitivity to the locomotor stimulant effects of MA. We used the program QTLRel to simultaneously map QTL in the F(2) and F(8) AIL mice. We identified six genome-wide significant QTLs associated with locomotor activity at baseline and seven genome-wide significant QTLs associated with MA-induced locomotor activation. The average per cent decrease in QTL width between the F(2) and the integrated analysis was 65%. Additionally, these QTLs showed a distinct temporal specificity within each session that allowed us to further refine their locations, and identify one QTL with a 1.8-LOD support interval of 1.47 Mb. Next, we utilized publicly available bioinformatics resources to exploit strain-specific sequence data and strain- and region-specific expression data to identify candidate genes. These results illustrate the power of AILs in conjunction with sequence and gene expression data to investigate the genetic underpinnings of behavioral and other traits.

Use of contiguous congenic strains in analyzing compound QTLs

Genetic analysis of polygenic traits in rats and mice has been very useful for finding the approximate chromosomal locations of the genes causing quantitative phenotypic variation, so-called quantitative trait loci (QTL). Further localization of the causative genes and their ultimate identification has, however, proven to be slow and frustrating. A major technique for gene identification in such models utilizes series of congenic strains with progressively smaller chromosomal segments introgressed from one inbred strain into another inbred strain. Under the assumption that a single causative locus underlies a QTL, nested series of congenic strains were earlier suggested as an appropriate configuration for the congenic strains. It is now known that most QTL are compound, that is, the QTL signal is caused by clusters of loci where alleles exert positive, negative, and interactive effects on the trait in a given strain comparison. It is argued that in this situation an initial series of nonoverlapping contiguous congenic strains over a relatively large chromosomal region will lead to a better appreciation of the underlying complexity of the QTL and therefore more rapid gene identification. Examples from the literature where this strategy would be helpful, as well as a case where it would be potentially counterproductive, are given.

The QTN program and the alleles that matter for evolution: all that's gold does not glitter

The search for the alleles that matter, the quantitative trait nucleotides (QTNs) that underlie heritable variation within populations and divergence among them, is a popular pursuit. But what is the question to which QTNs are the answer? Although their pursuit is often invoked as a means of addressing the molecular basis of phenotypic evolution or of estimating the roles of evolutionary forces, the QTNs that are accessible to experimentalists, QTNs of relatively large effect, may be uninformative about these issues if large-effect variants are unrepresentative of the alleles that matter. Although 20th century evolutionary biology generally viewed large-effect variants as atypical, the field has recently undergone a quiet realignment toward a view of readily discoverable large-effect alleles as the primary molecular substrates for evolution. I argue that neither theory nor data justify this realignment. Models and experimental findings covering broad swaths of evolutionary phenomena suggest that evolution often acts via large numbers of small-effect polygenes, individually undetectable. Moreover, these small-effect variants are different in kind, at the molecular level, from the large-effect alleles accessible to experimentalists. Although discoverable QTNs address some fundamental evolutionary questions, they are essentially misleading about many others.

Fine-mapping alleles for body weight in LG/J × SM/J F₂ and F(34) advanced intercross lines

The present study measured variation in body weight using a combined analysis in an F(2) intercross and an F(34) advanced intercross line (AIL). Both crosses were derived from inbred LG/J and SM/J mice, which were selected for large and small body size prior to inbreeding. Body weight was measured at 62 (± 5) days of age. Using an integrated GWAS and forward model selection approach, we identified 11 significant QTLs that affected body weight on ten different chromosomes. With these results we developed a full model that explained over 18% of the phenotypic variance. The median 1.5-LOD support interval was 5.55 Mb, which is a significant improvement over most prior body weight QTLs. We identified nonsynonymous coding SNPs between LG/J and SM/J mice in order to further narrow the list of candidate genes. Three of the genes with nonsynonymous coding SNPs (Rad23b, Stk33, and Anks1b) have been associated with adiposity, waist circumference, and body mass index in human GWAS, thus providing evidence that these genes may underlie our QTLs. Our results demonstrate that a relatively small number of loci contribute significantly to the phenotypic variance in body weight, which is in marked contrast to the situation in humans. This difference is likely to be the result of strong selective pressure and the simplified genetic architecture, both of which are important advantages of our system.

Mouse genomic variation and its effect on phenotypes and gene regulation

We report genome sequences of 17 inbred strains of laboratory mice and identify almost ten times more variants than previously known. We use these genomes to explore the phylogenetic history of the laboratory mouse and to examine the functional consequences of allele-specific variation on transcript abundance, revealing that at least 12% of transcripts show a significant tissue-specific expression bias. By identifying candidate functional variants at 718 quantitative trait loci we show that the molecular nature of functional variants and their position relative to genes vary according to the effect size of the locus. These sequences provide a starting point for a new era in the functional analysis of a key model organism.

Mapping a mouse limbic seizure susceptibility locus on chromosome 10

PURPOSE

Mapping seizure susceptibility loci in mice provides a framework for identifying potentially novel candidate genes for human epilepsy. Using C57BL/6J × A/J chromosome substitution strains (CSS), we previously identified a locus on mouse chromosome 10 (Ch10) conferring susceptibility to pilocarpine, a muscarinic cholinergic agonist that models human temporal lobe epilepsy by inducing initial limbic seizures and status epilepticus (status), followed by hippocampal cell loss and delayed-onset chronic spontaneous limbic seizures. Herein we report further genetic mapping of pilocarpine quantitative trait loci (QTLs) on Ch10.

METHODS

Seventy-nine Ch10 F(2) mice were used to map QTLs for duration of partial status epilepticus and the highest stage reached in response to pilocarpine. Based on those results we created interval-specific congenic lines to confirm and extend the results, using sequential rounds of breeding selectively by genotype to isolate segments of A/J Ch10 genome on a B6 background.

KEY FINDINGS

Analysis of Ch10 F(2) genotypes and seizure susceptibility phenotypes identified significant, overlapping QTLs for duration of partial status and severity of pilocarpine-induced seizures on distal Ch10. Interval-specific Ch10 congenics containing the susceptibility locus on distal Ch10 also demonstrated susceptibility to pilocarpine-induced seizures, confirming results from the F(2) mapping population and strongly supporting the presence of a QTL between rs13480781 (117.6 Mb) and rs13480832 (127.7 Mb).

SIGNIFICANCE

QTL mapping can identify loci that make a quantitative contribution to a trait, and eventually identify the causative DNA-sequence polymorphisms. We have mapped a locus on mouse Ch10 for pilocarpine-induced limbic seizures. Novel candidate genes identified in mice can be investigated in functional studies and tested for their role in human epilepsy.

Refined mapping of blood pressure quantitative trait loci using congenic strains developed from two genetically hypertensive rat models

Previously linkage and substitution mapping were conducted between the Dahl Salt-sensitive (S) rat and the Spontaneously Hypertensive Rat (SHR) to address the hypothesis that genetic contributions to blood pressure (BP) in two genetically hypertensive rat strains are different. Among the BP quantitative trait loci (QTLs) detected, two are located on chromosome 9 within large genomic segments. The goal of the current study was to develop new iterations of congenic substrains, to further resolve both of these BP QTLs on chromosome 9 as independent congenic segments. A total of 10 new congenic substrains were developed and characterized. The newly developed congenic substrains S.SHR(9)x8Ax11A and S.SHR(9)x10Ax1, with introgressed segments of 2.05 and 6.14 Mb, represented the shortest genomic segments. Both of these congenic substrains, S.SHR(9)x8Ax11A and S.SHR(9)x10Ax1 lowered BP of the S rat by 56 mm Hg (P<0.001) and 15 mm Hg (P<0.039), respectively. The BP measurements were corroborated by radiotelemetry. Urinary protein excretion was significantly lowered by SHR alleles within S.SHR(9)x10Ax1 but not by S.SHR(9)x8Ax11A. The shorter of the two congenic segments, 2.05 Mb was further characterized and found to contain a single differentially expressed protein-coding gene, Tomoregulin-2 (Tmeff2). The protein expression of Tmeff2 was higher in the S rat compared with S.SHR(9)x8Ax11A, which also had lower cardiac hypertrophy as measured by echocardiography. Tmeff2 is known to be upregulated in patients from multiple cohorts with cardiac hypertrophy. Taken together, Tmeff2 can be prioritized as a candidate gene for hypertension and associated cardiac hypertrophy in both rats and in humans.

The emerging role for rat models in gene discovery

Rat models have been used for many decades to study physiological and pathophysiological mechanisms. Prior to the release of the rat genome and new technologies for targeting gene manipulation, the rat had been the underdog in the genomics era, despite the abundance of physiological data compared to the mouse. The overarching goal of biomedical research is to improve health and advance medical science. Translating human disease gene discovery and validation in the rat, through the use of emerging technologies and integrated tools and databases, is providing power to understand the genetics, environmental influences, and biology of disease. In this review we briefly outline the rat models, bioinformatics tools, and technologies that are changing the landscape of translational research. The strategies used to translate disease traits to genes to function, and, ultimately, to improve human health is discussed. Finally, our perspective on how rat models will continue to positively impact biomedical research is provided.

Dark matter: are mice the solution to missing heritability?

Genome-wide association studies (GWAS) in humans have identified hundreds of single nucleotide polymorphisms associated with complex traits, yet for most traits studied, the sum total of all these identified variants fail to explain a significant portion of the heritable variation. Reasons for this “missing heritability” are thought to include the existence of rare causative variants not captured by current genotyping arrays, structural variants that go undetected by existing technology, insufficient power to identify multi-gene interactions, small sample sizes, and the influence of environmental and epigenetic effects. As genotyping technologies have evolved it has become inexpensive and relatively straightforward to perform GWAS in mice. Mice offer a powerful tool for elucidating the genetic architecture of behavioral and physiological traits, and are complementary to human studies. Unlike F₂ crosses of inbred strains, advanced intercross lines, heterogeneous stocks, outbred, and wild-caught mice have more rapid breakdown of linkage disequilibrium which allow for increasingly high resolution mapping. Because some of these populations are created using a small number of founder chromosomes they are not expected to harbor rare alleles. We discuss the differences between these mouse populations and examine their potential to overcome some of the pitfalls that have plagued human GWAS studies.

Deep congenic analysis identifies many strong, context-dependent QTLs, one of which, Slc35b4, regulates obesity and glucose homeostasis

Although central to many studies of phenotypic variation and disease susceptibility, characterizing the genetic architecture of complex traits has been unexpectedly difficult. For example, most of the susceptibility genes that contribute to highly heritable conditions such as obesity and type 2 diabetes (T2D) remain to be identified despite intensive study. We took advantage of mouse models of diet-induced metabolic disease in chromosome substitution strains (CSSs) both to characterize the genetic architecture of diet-induced obesity and glucose homeostasis and to test the feasibility of gene discovery. Beginning with a survey of CSSs, followed with genetic and phenotypic analysis of congenic, subcongenic, and subsubcongenic strains, we identified a remarkable number of closely linked, phenotypically heterogeneous quantitative trait loci (QTLs) on mouse chromosome 6 that have unexpectedly large phenotypic effects. Although fine-mapping reduced the genomic intervals and gene content of these QTLs over 3000-fold, the average phenotypic effect on body weight was reduced less than threefold, highlighting the "fractal" nature of genetic architecture in mice. Despite this genetic complexity, we found evidence for 14 QTLs in only 32 recombination events in less than 3000 mice, and with an average of four genes located within the three body weight QTLs in the subsubcongenic strains. For Obrq2a1, genetic and functional studies collectively identified the solute receptor Slc35b4 as a regulator of obesity, insulin resistance, and gluconeogenesis. This work demonstrated the unique power of CSSs as a platform for studying complex genetic traits and identifying QTLs.

Intersubspecific subcongenic mouse strain analysis reveals closely linked QTLs with opposite effects on body weight

A previous genome-wide QTL study revealed many QTLs affecting postnatal body weight and growth in an intersubspecific backcross mouse population between the C57BL/6J (B6) strain and wild Mus musculus castaneus mice captured in the Philippines. Subsequently, several closely linked QTLs for body composition traits were revealed in an F(2) intercross population between B6 and B6.Cg-Pbwg1, a congenic strain on the B6 genetic background carrying the growth QTL Pbwg1 on proximal chromosome 2. However, no QTL affecting body weight has been duplicated in the F(2) population, except for mapping an overdominant QTL that causes heterosis of body weight. In this study, we developed 17 intersubspecific subcongenic strains with overlapping and nonoverlapping castaneus regions from the B6.Cg-Pbwg1 congenic strain in order to search for and genetically dissect QTLs affecting body weight into distinct closely linked loci. Phenotypic comparisons of several developed subcongenic strains with the B6 strain revealed that two closely linked but distinct QTLs that regulate body weight, named Pbwg1.11 and Pbwg1.12, are located on an 8.9-Mb region between D2Mit270 and D2Mit472 and on the next 3.6-Mb region between D2Mit205 and D2Mit182, respectively. Further analyses using F(2) segregating populations obtained from intercrosses between B6 and each of the two selected subcongenic strains confirmed the presence of these two body weight QTLs. Pbwg1.11 had an additive effect on body weight at 6, 10, and 13 weeks of age, and its castaneus allele decreased it. In contrast, the castaneus allele at Pbwg1.12 acted in a dominant fashion and surprisingly increased body weight at 6, 10, and 13 weeks of age despite the body weight of wild castaneus mice being 60% of that of B6 mice. These findings illustrate the complex genetic nature of body weight regulation and support the importance of subcongenic mouse analysis to dissect closely linked loci.

Drosophila provides rapid modeling of renal development, function, and disease

The evolution of specialized excretory cells is a cornerstone of the metazoan radiation, and the basic tasks performed by Drosophila and human renal systems are similar. The development of the Drosophila renal (Malpighian) tubule is a classic example of branched tubular morphogenesis, allowing study of mesenchymal-to-epithelial transitions, stem cell-mediated regeneration, and the evolution of a glomerular kidney. Tubule function employs conserved transport proteins, such as the Na(+), K(+)-ATPase and V-ATPase, aquaporins, inward rectifier K(+) channels, and organic solute transporters, regulated by cAMP, cGMP, nitric oxide, and calcium. In addition to generation and selective reabsorption of primary urine, the tubule plays roles in metabolism and excretion of xenobiotics, and in innate immunity. The gene expression resource FlyAtlas.org shows that the tubule is an ideal tissue for the modeling of renal diseases, such as nephrolithiasis and Bartter syndrome, or for inborn errors of metabolism. Studies are assisted by uniquely powerful genetic and transgenic resources, the widespread availability of mutant stocks, and low-cost, rapid deployment of new transgenics to allow manipulation of renal function in an organotypic context.

Defining a rat blood pressure quantitative trait locus to a <81.8 kb congenic segment: comprehensive sequencing and renal transcriptome analysis

Evidence from multiple linkage and genome-wide association studies suggest that human chromosome 2 (HSA2) contains alleles that influence blood pressure (BP). Homologous to a large segment of HSA2 is rat chromosome 9 (RNO9), to which a BP quantitative trait locus (QTL) was previously mapped. The objective of the current study was to further resolve this BP QTL. Eleven congenic strains with introgressed segments spanning <81.8 kb to <1.33 Mb were developed by introgressing genomic segments of RNO9 from the Dahl salt-resistant (R) rat onto the genome of the Dahl salt-sensitive (S) rat and tested for BP. The congenic strain with the shortest introgressed segment spanning <81.8 kb significantly lowered BP of the hypertensive S rat by 25 mmHg and significantly increased its mean survival by 45 days. In contrast, two other congenic strains had increased BP compared with the S. We focused on the <81.8 kb congenic strain, which represents the shortest genomic segment to which a BP QTL has been mapped to date in any species. Sequencing of this entire region in both S and R rats detected 563 variants. The region did not contain any known or predicted rat protein coding genes. Furthermore, a whole genome renal transcriptome analysis between S and the <81.8 kb S.R congenic strain revealed alterations in several critical genes implicated in renal homeostasis. Taken together, our results provide the basis for future studies to examine the relationship between the candidate variants within the QTL region and the renal differentially expressed genes as potential causal mechanisms for BP regulation.