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.     

Segregation of a QTL cluster for home-cage activity using a new mapping method based on regression analysis of congenic mouse strains

Recent genetic studies have shown that genetic loci with significant effects in whole-genome quantitative trait loci (QTL) analyses were lost or weakened in congenic strains. Characterisation of the genetic basis of this attenuated QTL effect is important to our understanding of the genetic mechanisms of complex traits. We previously found that a consomic strain, B6-Chr6C^MSM, which carries chromosome 6 of a wild-derived strain MSM/Ms on the genetic background of C57BL/6J, exhibited lower home-cage activity than C57BL/6J. In the present study, we conducted a composite interval QTL analysis using the F2 mice derived from a cross between C57BL/6J and B6-Chr6C^MSM. We found one QTL peak that spans 17.6 Mbp of chromosome 6. A subconsomic strain that covers the entire QTL region also showed lower home-cage activity at the same level as the consomic strain. We developed 15 congenic strains, each of which carries a shorter MSM/Ms-derived chromosomal segment from the subconsomic strain. Given that the results of home-cage activity tests on the congenic strains cannot be explained by a simple single-gene model, we applied regression analysis to segregate the multiple genetic loci. The results revealed three loci (loci 1–3) that have the effect of reducing home-cage activity and one locus (locus 4) that increases activity. We also found that the combination of loci 3 and 4 cancels out the effects of the congenic strains, which indicates the existence of a genetic mechanism related to the loss of QTLs.     

Genetics of body weight in the LXS recombinant inbred mouse strains

This is the first phenotypic analysis of 75 new recombinant inbred (RI) strains derived from ILS and ISS progenitors. We analyzed body weight in two independent cohorts of female mice at various ages and in males at 60 days. Body weight is a complex trait which has been mapped in numerous crosses in rodents. The LXS RI strains displayed a large range of weights, transgressing those of the inbred progenitors, supporting the utility of this large panel for mapping traits not selected in the progenitors. Numerous QTLs for body weight mapped in single- and multilocus scans. We assessed replication between these and previously reported QTLs based on overlapping confidence intervals of published QTLs for body weight at 60 days and used meta-analyses to determine combined p values for three QTL regions located on Chromosomes 4, 5, and 11. Strain distribution patterns of microsatellite marker genotypes, weight, and other phenotypes are available on WebQTL () and allow genetic mapping of any heritable quantitative phenotype measured in these strains. We report one such analysis, correlating brain and body weights. Large reference panels of RI strains, such as the LXS, are invaluable for identifying genetic correlations, GXE (Gene X Environment) interactions, and replicating previously identified QTLs. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users.     

Genome-wide gene expression profiling of human mast cells stimulated by IgE or FcεRI-aggregation reveals a complex network of genes involved in inflammatory responses

Background

High growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds.

Results

The first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects.

Conclusion

The speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.     

Genetic determinants of atherosclerosis,obesity, and energy balance in consomic mice

Metabolic diseases such as obesity and atherosclerosis result from complex interactions between environmental factors and genetic variants. A panel of chromosome substitution strains (CSSs) was developed to characterize genetic and dietary factors contributing to metabolic diseases and other biological traits and biomedical conditions. Our goal here was to identify quantitative trait loci (QTLs) contributing to obesity, energy expenditure, and atherosclerosis. Parental strains C57BL/6 and A/J together with a panel of 21 CSSs derived from these progenitors were subjected to chronic feeding of rodent chow and atherosclerotic (females) or diabetogenic (males) test diets, and evaluated for a variety of metabolic phenotypes including several traits unique to this report, namely fat pad weights, energy balance, and atherosclerosis. A total of 297 QTLs across 35 traits were discovered, two of which provided significant protection from atherosclerosis, and several dozen QTLs modulated body weight, body composition, and circulating lipid levels in females and males. While several QTLs confirmed previous reports, most QTLs were novel. Finally, we applied the CSS quantitative genetic approach to energy balance, and identified three novel QTLs controlling energy expenditure and one QTL modulating food intake. Overall, we identified many new QTLs and phenotyped several novel traits in this mouse model of diet-induced metabolic diseases.     

Dissection of multigenic obesity traits in congenic mouse strains

Previous quantitative trait locus mapping (QTL) identified multigenic obesity (MOB) loci on mouse Chromosome (Chr) 2 that influence the interrelated phenotypes of obesity, insulin resistance, and dyslipidemia. To better localize and characterize the MOB locus, three congenic mouse strains were created. Overlapping genomic intervals from the lean CAST/Ei (CAST) strain were introgressed onto an obesity-susceptible C57BL/6 (BL6) background to create proximal (15 Mb–73 Mb), middle (63 Mb–165 Mb), and distal (83 Mb–182 Mb) congenic strains. The congenic strains showed differences in obesity, insulin, and lipid traits consistent with the original QTL analysis for the locus. Importantly, characterization of the MOB congenics localized the effects of genes that underlie obesity-related traits to an introgressed interval (73–83 Mb) unique to the middle MOB congenic. Conversely, significant differences between the lipid and insulin profiles of the middle and distal MOB congenics implicated the presence of at least two genes that underlie these traits. When fed an atherogenic diet, several traits associated with metabolic syndrome were observed in the distal MOB congenic, while alterations in plasma lipoproteins were observed in the middle MOB congenic strain.     

Genetics and bone. Using the mouse to understand man

The rationale for use of inbred strains of mice in bone research is well recognized and includes: a) practical factors (economics of scale, rapid development of adult status, pre-existing knowledge, down-sized technologies) and b) proven methodologies for genetic studies (polygenic trait analyses, mapping tools, genomic sequencing, methods for gene manipulation). Initial investigations of inbred strains of mice showed that femoral and lumbar vertebral volumetric bone mineral density (BMD, mg/mm(3)) by pQCT varied in excess of 50% for femurs and 9% in vertebral BMD. Two strains - low BMD C57BL/6J (B6) mice and high BMD C3H/HeJ (C3H) - were investigated for insights to their BMD diversity. B6C3F2 females derived from intercrossing B6C3F1s were raised to adult skeletal status at 4 months, then necropsied for phenotyping of bone and genotyping of genomic DNA. 1000 F2 females were genotyped for PCR product polymorphisms on all 19 autosomes at approximately 15 cM. Genome wide analyses for genotype-phenotype correlations showed 10 chromosomes (Chrs) carried genes for femoral and 7 Chrs for vertebral BMD. LOD scores ranged from 2.90 to 24.4, and percent of F2 variance accounted for ranged from 1 to 10%. Analyses of main effects revealed both dominant-recessive and additive inheritance patterns. Both progenitor strains carried alleles with positive and negative effects on BMD of each bone sites. A remarkable array of additonal skeletal phenotypes (femur and vertebral geometry, strength measures, serum markers) also proved polygenic in nature, with complex segregation patterns. Verification of BMD quantitative trait loci (QTLs) was undertaken by creating congenic B6 strains carrying individual QTL regions from C3H. Following 6 cycles of backcrossing a QTL-containing region from C3H to the B6 strain, N6F2 congenic strain mice were aged to 4 months, then genotyped for the QTL region and phenotyped for skeletal traits. Comparison of mice homozygous for C3H alleles versus homozygous for B6 alleles in the QTL regions showed that femoral BMD increased or decreased significantly in congenic strains, as was predicted from F2 data. Gender differences specific to BMD QTLs have been revealed, as have more than 30 additional phenotypes associated with cortical and trabecular structural parameters and biomechanical properties.     

A Sequential Quantitative Trait Locus Fine-Mapping Strategy Using Recombinant-Derived Progeny

A thorough understanding of the quantitative trait loci(QTLs)that underlie agronomically important traits in crops would greatly increase agricultural productivity.Although advances have been made in QTL cloning,the majority of QTLs remain unknown because of their low heritability and minor contributions to phenotypic performance.Here we summarize the key advantages and disadvantages of current QTL fine-mapping methodologies,and then introduce a sequential QTL fine-mapping strategy based on both genotypes and phenotypes of progeny derived from recombinants.With this mapping strategy,experimental errors could be dramatically diminished so as to reveal the authentic genetic effect of target QTLs.The number of progeny required to detect QTLs atvarious R~2 values was calculated,and the backcross generation suitable to start QTL fine-mapping was also estimated.This mapping strategy has proved to be very powerful in narrowing down QTL regions,particularly minor-effect QTLs,as revealed by fine-mapping of various resistance QTLs in maize.Application of this sequential QTL mapping strategy should accelerate cloning of agronomically important QTLs,which is currently a substantial challenge in crops.     

Congenic mapping of a blood pressure QTL region on rat chromosome 10 using the Dahl salt-sensitive rat with introgressed alleles from the Milan normotensive strain

Multiple blood pressure (BP) quantitative trait loci (QTLs) are reported on rat chromosome 10 (RNO10). Of these, QTLs detected by contrasting the genome of the hypertensive Dahl salt-sensitive (S) rat with two different relatively normotensive strains, Lewis (LEW) and the Milan normotensive strain (MNS), are reported. Because the deduced QTL regions of both S vs. LEW and S vs. MNS comparisons are within large genomic segments encompassing more than 2 cM, there was a need to further localize these QTLs and determine whether the QTLs are unique to specific strain comparisons. Previously, the S.MNS QTL1 was mapped to less than 2.6 cM as a differential segment between two congenic strains. In this study, multiple congenic strains spanning the projected interval were studied. The BP effect of each strain was interpreted as the net effect of alleles introgressed within that congenic strain. The results suggest that the MNS alleles within the previously proposed differential segment (D10Rat27-D10Rat24) do not independently lower BP of the S rat. However, another congenic strain, S.MNS(10) × 9, containing introgressed MNS alleles that are outside of the previously proposed differential segment is of interest because (1) it demonstrated a BP-lowering effect, (2) it is contained within a single congenic strain and is not based on the observed effect of a differential segment, and, more importantly, (3) it overlaps with the previously identified S.LEW BP QTL region. Identification of the same QTL affecting BP in multiple rat strains will provide further support for the QTL’s involvement and importance in human essential hypertension.     

Closely linked non-additive blood pressure quantitative trait loci

There is enough evidence through linkage and substitution mapping to indicate that rat chromosome 1 harbors multiple blood pressure (BP) quantitative trait loci (QTLs). Of these, BP QTL1b was previously reported from our laboratory using congenic strains derived by introgressing normotensive alleles from the LEW rat onto the genetic background of the hypertensive Dahl salt-sensitive (S) rat. The region spanned by QTL1b is quite large (20.92 Mb), thus requiring further mapping with improved resolution so as to facilitate systematic identification of the underlying genetic determinant(s). Using congenic strains containing the LEW rat chromosomal segments on the Dahl salt-sensitive (S) rat background, further iterations of congenic substrains were constructed and characterized. Collective data obtained from this new iteration of congenic substrains provided evidence for further fragmentation of QTL1b with improved resolution. At least two separate genetic determinants of blood pressure underlie QTL1b. These are within 7.40 Mb and 7.31 Mb and are known as the QTL1b1 region and the QTL1b2 region, respectively. A genetic interaction was detected between the two BP QTLs. Interestingly, five of the previously reported differentially expressed genes located within the newly mapped QTL1b1 region remained differentially expressed. The congenic strain S.LEW(D1Mco36-D1Mco101), which harbors the QTL1b1 region alone but not the QTL1b2 region, serves as a genetic tool for further dissection of the QTL1b1 region and validation of Nr2f2 as a positional candidate gene. Overall, this study represents an intermediary yet obligatory progression towards the identification of genetic elements controlling BP. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. E. J. Toland and Y. Saad contributed equally to this work.     

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 .     

QTL mapping of bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) grown under controlled conditions of an agroecobiological testing ground

To determine the effects of physiological and genetic interaction between the genotype and environment, QTL (quantitative trait loci) mapping of valuable traits of bread wheat (Triticum aestivum L.) manifesting under controlled conditions of an agroecobiological testing ground has been first carried out. In the course of two experiments, differing from each other only by temperature and illumination regimes and providing the strict control and invariability of other growing parameters, 99 QTLs determining 30 different agronomically important traits have been identified. According to the results of the QTL mapping and a single-factor ANOVA, changes in the temperature and illumination regimes did not influence 21 of 30 studied traits, which remained stable in their manifestation; only nine traits varied under these conditions, which indicates that their manifestation is dependent on changes in these environmental factors. Both statistical approaches used in this study demonstrated complementary results; for each of them, the maximum likelihood criterion was used, statistical significance was determined, and significance of results was evaluated. The significance of a correlation between the identified QTLs and the polymorphism of individual traits studied was assessed using the threshold value of LOD (logarithm of odds) score. In addition, QTL analysis allowed a block structure of the T. aestivum genome to be revealed, the percentage of a phenotypic variability determined by each of the identified QTLs to be calculated, and the determination of which of the parents donated individual QTL alleles. The obtained results can be used for the further study of the physiological and genetic mechanisms of realization of traits evaluated within the framework of the “genotype–environment” interaction and also for the marker-assisted breeding of wheat.     

Quantitative trait loci for sensitivity to ethanol intoxication in a C57BL/6J?×?129S1/SvImJ inbred mouse cross

Individual variation in sensitivity to acute ethanol (EtOH) challenge is associated with alcohol drinking and is a predictor of alcohol abuse. Previous studies have shown that the C57BL/6J (B6) and 129S1/SvImJ (S1) inbred mouse strains differ in responses on certain measures of acute EtOH intoxication. To gain insight into genetic factors contributing to these differences, we performed quantitative trait locus (QTL) analysis of measures of EtOH-induced ataxia (accelerating rotarod), hypothermia, and loss of righting reflex (LORR) duration in a B6×S1 F2 population. We confirmed that S1 showed greater EtOH-induced hypothermia (specifically at a high dose) and longer LORR compared to B6. QTL analysis revealed several additive and interacting loci for various phenotypes, as well as examples of genotype interactions with sex. QTLs for different EtOH phenotypes were largely non-overlapping, suggesting separable genetic influences on these behaviors. The most compelling main-effect QTLs were for hypothermia on chromosome 16 and for LORR on chromosomes 4 and 6. Several QTLs overlapped with loci repeatedly linked to EtOH drinking in previous mouse studies. The architecture of the traits we examined was complex but clearly amenable to dissection in future studies. Using integrative genomics strategies, plausible functional and positional candidates may be found. Uncovering candidate genes associated with variation in these phenotypes in this population could ultimately shed light on genetic factors underlying sensitivity to EtOH intoxication and risk for alcoholism in humans.     

Genes on mouse Chromosomes 2 and 9 determine variation in ethanol consumption

Quantitative trait locus (QTL) mapping efforts in alcohol (ethanol) research are beginning to generate promising data that may ultimately lead to the identification of genes influencing alcohol addiction. Rodents have been extensively utilized to study ethanol's rewarding and aversive effects, and to demonstrate the existence of genetic influences on traits such as free-choice ethanol-consumption, ethanol-conditioned place preference and ethanol-conditioned taste aversion. The purpose of the current investigation was to verify or eliminate from further consideration putative QTLs for free-choice ethanol consumption originally identified in BXD Recombinant Inbred (RI) strains and other informative genetic crosses. B6D2F₂ mice were utilized in a verification testing strategy to evaluate the viability of putative ethanol consumption QTLs. When data were combined from BXD RI, B6D2F₂ and short-term selected line (STSL) mapping studies, verification was obtained for two QTLs, one on Chromosome (Chr) 9 (proximal-mid) and another on Chr 2 (distal), and suggestive verification was obtained for QTLs on Chrs 2 (proximal), 3, 4, 7, and 15. In addition, the possible genetic association of ethanol consumption with conditioned place preference was evaluated. Genetic correlations were estimated from BXD RI strain means, and QTL maps for these traits were compared to evaluate the possibility of a genetic association. The correlational analysis yielded a trend (r = 0.34, p = 0.09), but no statistically significant results. However, comparisons of QTL mapping results between phenotypes suggested some possible genetic overlap for these traits, both putative measures of ethanol reward. These data suggest that the determinants of these two measures are genetically diverse, but may share some common genetic elements. Received: 15 September 1998 / Accepted: 8 October 1998     

QTL Analysis of High Thermotolerance with Superior and Downgraded Parental Yeast Strains Reveals New Minor QTLs and Converges on Novel Causative Alleles Involved in RNA Processing

Revealing QTLs with a minor effect in complex traits remains difficult. Initial strategies had limited success because of interference by major QTLs and epistasis. New strategies focused on eliminating major QTLs in subsequent mapping experiments. Since genetic analysis of superior segregants from natural diploid strains usually also reveals QTLs linked to the inferior parent, we have extended this strategy for minor QTL identification by eliminating QTLs in both parent strains and repeating the QTL mapping with pooled-segregant whole-genome sequence analysis. We first mapped multiple QTLs responsible for high thermotolerance in a natural yeast strain, MUCL28177, compared to the laboratory strain, BY4742. Using single and bulk reciprocal hemizygosity analysis we identified MKT1 and PRP42 as causative genes in QTLs linked to the superior and inferior parent, respectively. We subsequently downgraded both parents by replacing their superior allele with the inferior allele of the other parent. QTL mapping using pooled-segregant whole-genome sequence analysis with the segregants from the cross of the downgraded parents, revealed several new QTLs. We validated the two most-strongly linked new QTLs by identifying NCS2 and SMD2 as causative genes linked to the superior downgraded parent and we found an allele-specific epistatic interaction between PRP42 and SMD2. Interestingly, the related function of PRP42 and SMD2 suggests an important role for RNA processing in high thermotolerance and underscores the relevance of analyzing minor QTLs. Our results show that identification of minor QTLs involved in complex traits can be successfully accomplished by crossing parent strains that have both been downgraded for a single QTL. This novel approach has the advantage of maintaining all relevant genetic diversity as well as enough phenotypic difference between the parent strains for the trait-of-interest and thus maximizes the chances of successfully identifying additional minor QTLs that are relevant for the phenotypic difference between the original parents.     

Genome-Wide Association Mapping for Yield and Other Agronomic Traits in an Elite Breeding Population of Tropical Rice (Oryza sativa)

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.     

A New Method to Infer Causal Phenotype Networks Using QTL and Phenotypic Information

In the context of genetics and breeding research on multiple phenotypic traits, reconstructing the directional or causal structure between phenotypic traits is a prerequisite for quantifying the effects of genetic interventions on the traits. Current approaches mainly exploit the genetic effects at quantitative trait loci (QTLs) to learn about causal relationships among phenotypic traits. A requirement for using these approaches is that at least one unique QTL has been identified for each trait studied. However, in practice, especially for molecular phenotypes such as metabolites, this prerequisite is often not met due to limited sample sizes, high noise levels and small QTL effects. Here, we present a novel heuristic search algorithm called the QTL+phenotype supervised orientation (QPSO) algorithm to infer causal directions for edges in undirected phenotype networks. The two main advantages of this algorithm are: first, it does not require QTLs for each and every trait; second, it takes into account associated phenotypic interactions in addition to detected QTLs when orienting undirected edges between traits. We evaluate and compare the performance of QPSO with another state-of-the-art approach, the QTL-directed dependency graph (QDG) algorithm. Simulation results show that our method has broader applicability and leads to more accurate overall orientations. We also illustrate our method with a real-life example involving 24 metabolites and a few major QTLs measured on an association panel of 93 tomato cultivars. Matlab source code implementing the proposed algorithm is freely available upon request.     

A growth QTL (<Emphasis Type="Italic">Pbwg1</Emphasis>) region of mouse chromosome 2 contains closely linked loci affecting growth and body composition

Previous QTL studies have identified 24 QTLs for body weight and growth from 3 to 10 weeks after birth in an intersubspecific backcross mouse population between C57BL/6J and wild Mus musculus castaneus that has 60% of the body size of C57BL/6J. The castaneus allele at the most potent QTL (Pbwg1) on proximal chromosome 2 retards growth. In this study we have developed a congenic strain with a 44.1-Mb interval containing the castaneus allele at Pbwg1 by recurrent backcrossing to C57BL/6J. The congenic mouse developed was characterized by significantly higher body weight gain between 1 and 3 weeks of age and lower weight of white fat pads at 10 weeks of age than C57BL/6J. However, no clear difference in body weight at 1–10 weeks of age was observed between congenic and C57BL/6J strains. QTL analysis with 269 F₂ mice between the two strains did not identify any QTLs for body weight at 1, 3, 6, and 10 weeks of age, but it discovered eight closely linked QTLs affecting body weight gain from 1 to 3 weeks of age, lean body weight, weight of white fat pads, and body length within the Pbwg1 region. The castaneus alleles at all fat pad QTLs reduced the phenotypes, whereas at the remaining growth and body composition QTLs, they increased the trait values. These results illustrate that Pbwg1, which initially appeared to be a single locus, was resolved into several loci with opposite effects on the composition traits of overall body weight. This gives a reason for the loss of the Pbwg1 effect found in the original backcross population. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Pleiotropic effects on mandibular morphology II: differential epistasis and genetic variation in morphological integration

The evolution of morphological modularity through the sequestration of pleiotropy to sets of functionally and developmentally related traits requires genetic variation in the relationships between traits. Genetic variation in relationships between traits can result from differential epistasis, where epistatic relationships for pairs of loci are different for different traits. This study maps relationship quantitative trait loci (QTLs), specifically QTLs that affect the relationship between individual mandibular traits and mandible length, across the genome in an F2 intercross of the LG/J and SM/J inbred mouse strains (N = 1045). We discovered 23 relationship QTLs scattered throughout the genome. All mandibular traits were involved in one or more relationship QTL. When multiple traits were affected at a relationship QTL, the traits tended to come from a developmentally restricted region of the mandible, either the muscular processes or the alveolus. About one-third of the relationship QTLs correspond to previously located trait QTLs affecting the same traits. These results comprise examples of genetic variation necessary for an evolutionary response to selection on the range of pleiotropic effects.