Advanced Intercross Line Research Articles

Mapping QTL Associated with Resistance to Avian Oncogenic Marek's Disease Virus (MDV) Reveals Major Candidate Genes and Variants.

Marek’s disease (MD) represents a significant global economic and animal welfare issue. Marek’s disease virus (MDV) is a highly contagious oncogenic and highly immune-suppressive α-herpes virus, which infects chickens, causing neurological effects and tumour formation. Though partially controlled by vaccination, MD continues to have a profound impact on animal health and on the poultry industry. Genetic selection provides an alternative and complementary method to vaccination. However, even after years of study, the genetic mechanisms underlying resistance to MDV remain poorly understood. The Major Histocompatability Complex (MHC) is known to play a role in disease resistance, along with a handful of other non-MHC genes. In this study, one of the largest to date, we used a multi-facetted approach to identify quantitative trait locus regions (QTLR) influencing resistance to MDV, including an F6 population from a full-sib advanced intercross line (FSIL) between two elite commercial layer lines differing in resistance to MDV, RNA-seq information from virus challenged chicks, and genome wide association study (GWAS) from multiple commercial lines. Candidate genomic elements residing in the QTLR were further tested for association with offspring mortality in the face of MDV challenge in eight pure lines of elite egg-layer birds. Thirty-eight QTLR were found on 19 chicken chromosomes. Candidate genes, microRNAs, long non-coding RNAs and potentially functional mutations were identified in these regions. Association tests were carried out in 26 of the QTLR, using eight pure lines of elite egg-layer birds. Numerous candidate genomic elements were strongly associated with MD resistance. Genomic regions significantly associated with resistance to MDV were mapped and candidate genes identified. Various QTLR elements were shown to have a strong genetic association with resistance. These results provide a large number of significant targets for mitigating the effects of MDV infection on both poultry health and the economy, whether by means of selective breeding, improved vaccine design, or gene-editing technologies.

The Gene scb-1 Underlies Variation in Caenorhabditis elegans Chemotherapeutic Responses.

Pleiotropy, the concept that a single gene controls multiple distinct traits, is prevalent in most organisms and has broad implications for medicine and agriculture. The identification of the molecular mechanisms underlying pleiotropy has the power to reveal previously unknown biological connections between seemingly unrelated traits. Additionally, the discovery of pleiotropic genes increases our understanding of both genetic and phenotypic complexity by characterizing novel gene functions. Quantitative trait locus (QTL) mapping has been used to identify several pleiotropic regions in many organisms. However, gene knockout studies are needed to eliminate the possibility of tightly linked, non-pleiotropic loci. Here, we use a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to identify a single large-effect QTL on the center of chromosome V associated with variation in responses to eight chemotherapeutics. We validate this QTL with near-isogenic lines and pair genome-wide gene expression data with drug response traits to perform mediation analysis, leading to the identification of a pleiotropic candidate gene, scb-1, for some of the eight chemotherapeutics. Using deletion strains created by genome editing, we show that scb-1, which was previously implicated in response to bleomycin, also underlies responses to other double-strand DNA break-inducing chemotherapeutics. This finding provides new evidence for the role of scb-1 in the nematode drug response and highlights the power of mediation analysis to identify causal genes.

Haplotype Purging After Relaxation of Selection in Lines of Chickens that Had Undergone Long-Term Selection for High and Low Body Weight.

Bi-directional selection for increased and decreased 56-day body weights (BW56) has been applied to two lines of White Plymouth Rock chickens—the Virginia high (HWS) and low (LWS) body weight lines. Correlated responses have been observed, including negative effects on traits related to fitness. Here, we use high and low body weight as proxies for fitness. On a genome-wide level, relaxed lines (HWR, LWR) bred from HWS and LWS purged some genetic variants in the selected lines. Whole-genome re-sequencing was here used to identify individual loci where alleles that accumulated during directional selection were purged when selection was relaxed. In total, 11 loci with significant purging signals were identified, five in the low (LW) and six in the high (HW) body weight lineages. Associations between purged haplotypes in these loci and BW56 were tested in an advanced intercross line (AIL). Two loci with purging signals and haplotype associations to BW56 are particularly interesting for further functional characterization, one locus on chromosome 6 in the LW covering the sour-taste receptor gene PKD2L1, a functional candidate gene for the decreased appetite observed in the LWS and a locus on chromosome 20 in the HW containing a skeletal muscle hypertrophy gene, DNTTIP1.

Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity.

There has been extensive discussion of the “Replication Crisis” in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner’s Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.

Three Quantitative Trait Loci Explain More than 60% of Variation for Chill Coma Recovery Time in a Natural Population of Drosophila ananassae.

Ectothermic species such as insects are particularly vulnerable to climatic fluctuations. Nevertheless, many insects that evolved and diversified in the tropics have successfully colonized temperate regions all over the globe. To shed light on the genetic basis of cold tolerance in such species, we conducted a quantitative trait locus (QTL) mapping experiment for chill coma recovery time (CCRT) in Drosophila ananassae, a cosmopolitan species that has expanded its range from tropical to temperate regions. We created a mapping population of recombinant inbred advanced intercross lines (RIAILs) from two founder strains with diverging CCRT phenotypes. The RIAILs were phenotyped for their CCRT and, together with the founder strains, genotyped for polymorphic markers with double-digest restriction site-associated DNA (ddRAD) sequencing. Using a hierarchical mapping approach that combined standard interval mapping and a multiple-QTL model, we mapped three QTL which altogether explained 64% of the phenotypic variance. For two of the identified QTL, we found evidence of epistasis. To narrow down the list of cold tolerance candidate genes, we cross-referenced the QTL intervals with genes that we previously identified as differentially expressed in response to cold in D. ananassae, and with thermotolerance candidate genes of D. melanogaster. Among the 58 differentially expressed genes that were contained within the QTL, GF15058 showed a significant interaction of the CCRT phenotype and gene expression. Further, we identified the orthologs of four D. melanogaster thermotolerance candidate genes, MtnA, klarsicht, CG5246 (D.ana/GF17132) and CG10383 (D.ana/GF14829) as candidates for cold tolerance in D. ananassae.

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.

Gut–lung axis: discomfort, dysphagia and cough

Dysregulation of TNF is an important pathophysiological phenotype for many diseases. Recently, certain genetically regulated loci have been identified to regulate several inflammatory diseases. We hypothesized that a region on...

Genetical Genomics of Tonic Immobility in the Chicken.

Identifying the molecular mechanisms of animal behaviour is an enduring goal for researchers. Gaining insight into these mechanisms enables us to gain a greater understanding of behaviour and their genetic control. In this paper, we perform Quantitative Trait Loci (QTL) mapping of tonic immobility behaviour in an advanced intercross line between wild and domestic chickens. Genes located within the QTL interval were further investigated using global expression QTL (eQTL) mapping from hypothalamus tissue, as well as causality analysis. This identified five candidate genes, with the genes PRDX4 and ACOT9 emerging as the best supported candidates. In addition, we also investigated the connection between tonic immobility, meat pH and struggling behaviour, as the two candidate genes PRDX4 and ACOT9 have previously been implicated in controlling muscle pH at slaughter. We did not find any phenotypic correlations between tonic immobility, struggling behaviour and muscle pH in a smaller additional cohort, despite these behaviours being repeatable within-test.

Assessing the Architecture of Drosophila mojavensis Locomotor Evolution with Bulk Segregant Analysis.

Behavior is frequently predicted to be especially important for evolution in novel environments. If these predictions are accurate, there might be particular patterns of genetic architecture associated with recently diverged behaviors. Specifically, it has been predicted that behaviors linked to population divergence should be underpinned by a few genes of relatively large effect, compared to architectures of intrapopulation behavioral variation, which is considered to be highly polygenic. More mapping studies of behavioral variation between recently diverged populations are needed to continue assessing the generality of these predictions. Here, we used a bulk segregant mapping approach to dissect the genetic architecture of a locomotor trait that has evolved between two populations of the cactophilic fly Drosophila mojavensis. We created an F8 mapping population of 1,500 individuals from advanced intercross lines and sequenced the 10% of individuals with the highest and lowest levels of locomotor activity. Using three alternative statistical approaches, we found strong evidence for two relatively large-effect QTL that is localized in a region homologous to a region of densely packed behavior loci in Drosophila melanogaster, suggesting that clustering of behavior genes may display relatively deep evolutionary conservation. Broadly, our data are most consistent with a polygenic architecture, though with several loci explaining a high proportion of variation in comparison to similar behavioral traits. We further note the presence of several antagonistic QTL linked to locomotion and discuss these results in light of theories regarding behavioral evolution and the effect size and direction of QTL for diverging traits in general.

Turning Observed Founder Alleles into Expected Relationships in an Intercross Population.

Pedigree-derived relationships for individuals from an intercross of several lines cannot easily account for the segregation variance that is mainly caused by loci with alternative alleles fixed in different lines. However, when all founders are genotyped for a large number of markers, such relationships can be derived for descendants as expected genomic relationships conditional on the observed founder allele frequencies. A tabular method was derived in detail for autosomes and the X-chromosome. As a case study, we analyzed litter size and body weights at three different ages in an advanced mouse intercross (29 generations, total pedigree size 19,266) between a line selected for high litter size (FL1) and a highly inbred control line (DUKsi). Approximately 60% of the total genetic variance was due to segregation variance. Estimated heritability values were 0.20 (0.03), 0.34 (0.04), 0.23 (0.03), 0.41 (0.03) and 0.47 (0.02) for litter size, litter weight and body weight at ages of 21, 42 and 63 days, respectively (standard errors in brackets). These values were between 12% and 65% higher than observed in analyses that treated founders as unrelated. Fields of applications include experimental populations (selection experiments or advanced intercross lines) with a limited number of founders, which can be genotyped at a reasonable cost. In principle any number of founder lines can be treated. Additional genotypes from individuals in later generations can be combined into a joint relationship matrix by capitalizing on previously published approaches.

Effects of High-Fat Diet and Body Mass on Bone Morphology and Mechanical Properties in 1100 Advanced Intercross Mice.

Obesity is generally protective against osteoporosis and bone fracture. However, recent studies indicate that the influence of obesity on the skeleton is complex and can be detrimental. We evaluated the effects of a high-fat, obesogenic diet on the femur and radius of 1100 mice (males and females) from the Large-by-Small advanced intercross line (F34 generation). At age 5 months, bone morphology was assessed by microCT and mechanical properties by three-point bending. Mice raised on a high-fat diet had modestly greater cortical area, bending stiffness, and strength. Size-independent material properties were unaffected by a high-fat diet, indicating that diet influenced bone quantity but not quality. Bone size and mechanical properties were strongly correlated with body mass. However, the increases in many bone traits per unit increase in body mass were less in high-fat diet mice than low-fat diet mice. Thus, although mice raised on a high-fat diet have, on average, bigger and stronger bones than low-fat-fed mice, a high-fat diet diminished the positive relationship between body mass and bone size and whole-bone strength. The findings support the concept that there are diminishing benefits to skeletal health with increasing obesity. © 2019 American Society for Bone and Mineral Research.

Genome wide association analysis in a mouse advanced intercross line

The LG/J x SM/J advanced intercross line of mice (LG x SM AIL) is a multigenerational outbred population. High minor allele frequencies, a simple genetic background, and the fully sequenced LG and SM genomes make it a powerful population for genome-wide association studies. Here we use 1,063 AIL mice to identify 126 significant associations for 50 traits relevant to human health and disease. We also identify thousands of cis- and trans-eQTLs in the hippocampus, striatum, and prefrontal cortex of ~200 mice. We replicate an association between locomotor activity and Csmd1, which we identified in an earlier generation of this AIL, and show that Csmd1 mutant mice recapitulate the locomotor phenotype. Our results demonstrate the utility of the LG x SM AIL as a mapping population, identify numerous novel associations, and shed light on the genetic architecture of mammalian behavior.

Shared Genomic Regions Underlie Natural Variation in Diverse Toxin Responses.

Phenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis often find that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins, and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome substitution strains, and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation.

The Collaborative Cross mouse model for dissecting genetic susceptibility to infectious diseases.

Infectious diseases, also known as communicable diseases, refer to a full range of maladies caused by pathogen invasion to the host body. Host response towards an infectious pathogen varies between individuals, and can be defined by responses from asymptomatic to lethal. Host response to infectious pathogens is considered as a complex trait controlled by gene-gene (host-pathogen) and gene-environment interactions, leading to the extensive phenotypic variations between individuals. With the advancement of the human genome mapping approaches and tools, various genome-wide association studies (GWAS) were performed, aimed at mapping the genetic basis underlying host susceptibility towards infectious pathogens. In parallel, immense efforts were invested in enhancing the genetic mapping resolution and gene-cloning efficacy, using advanced mouse models including advanced intercross lines; outbred populations; consomic, congenic; and recombinant inbred lines. Notwithstanding the evident advances achieved using these mouse models, the genetic diversity was low and quantitative trait loci (QTL) mapping resolution was inadequate. Consequently, the Collaborative Cross (CC) mouse model was established by full-reciprocal mating of eight divergent founder strains of mice (A/J, C57BL/6J, 129S1/SvImJ, NOD/LtJ, NZO/HiLtJ, CAST/Ei, PWK/PhJ, and WSB/EiJ) generating a next-generation mouse genetic reference population (CC lines). Presently, the CC mouse model population comprises a set of about 200 recombinant inbred CC lines exhibiting a unique high genetic diversity and which are accessible for multidisciplinary studies. The CC mouse model efficacy was validated by various studies in our lab and others, accomplishing high-resolution (< 1MB) QTL genomic mapping for a variety of complex traits, using about 50 CC lines (3-4 mice per line). Herein, we present a number of studies demonstrating the power of the CC mouse model, which has been utilized in our lab for mapping the genetic basis of host susceptibility to various infectious pathogens. These include Aspergillus fumigatus, Klebsiella pneumoniae, Porphyromonas gingivalis and Fusobacterium nucleatum (causing oral mixed infection), Pseudomonas aeruginosa, and the bacterial toxins Lipopolysaccharide and Lipoteichoic acid.

Haplotype-based allele mining in the Japan-MAGIC rice population

Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations.

Replication and discovery of musculoskeletal QTLs in LG/J and SM/J advanced intercross lines.

The genetics underlying variation in health‐related musculoskeletal phenotypes can be investigated in a mouse model. Quantitative trait loci (QTLs) affecting musculoskeletal traits in the LG/J and SM/J strain lineage remain to be refined and corroborated. The aim of this study was to map muscle and bone traits in males (n = 506) of the 50th filial generation of advanced intercross lines (LG/SM AIL) derived from the two strains. Genetic contribution to variation in all musculoskeletal traits was confirmed; the SNP heritability of muscle mass ranged between 0.46 and 0.56; and the SNP heritability of tibia length was 0.40. We used two analytical software, GEMMA and QTLRel, to map the underlying QTLs. GEMMA required substantially less computation and recovered all the QTLs identified by QTLRel. Seven significant QTLs were identified for muscle weight (Chr 1, 7, 11, 12, 13, 15, and 16), and two for tibia length, (Chr 1 and 13). Each QTL explained 4–5% of phenotypic variation. One muscle and both bone loci replicated previous findings; the remaining six were novel. Positional candidates for the replicated QTLs were prioritized based on in silico analyses and gene expression in muscle tissue. In summary, we replicated existing QTLs and identified novel QTLs affecting muscle weight, and replicated bone length QTLs in LG/SM AIL males. Heritability estimates substantially exceed the cumulative effect of the QTLs, hence a richer genetic architecture contributing to muscle and bone variability could be uncovered with a larger sample size.

Improved detection of gene-microbe interactions in the mouse skin microbiota using high-resolution QTL mapping of 16S rRNA transcripts

BackgroundRecent studies highlight the utility of quantitative trait locus (QTL) mapping for determining the contribution of host genetics to interindividual variation in the microbiota. We previously demonstrated that similar to the gut microbiota, abundances of bacterial taxa in the skin are significantly influenced by host genetic variation. In this study, we analyzed the skin microbiota of mice from the 15th generation of an advanced intercross line using a novel approach of extending bacterial trait mapping to both the 16S rRNA gene copy (DNA) and transcript (RNA) levels, which reflect relative bacterial cell number and activity, respectively.ResultsRemarkably, the combination of highly recombined individuals and 53,203 informative SNPs allowed the identification of genomic intervals as small as <0.1 megabases containing single genes. Furthermore, the inclusion of 16S rRNA transcript-level mapping dramatically increased the number of significant associations detected, with five versus 21 significant SNP-bacterial trait associations based on DNA- compared to RNA-level profiling, respectively. Importantly, the genomic intervals identified contain many genes involved in skin inflammation and cancer and are further supported by the bacterial traits they influence, which in some cases have known genotoxic or probiotic capabilities.ConclusionsThese results indicate that profiling based on the relative activity levels of bacterial community members greatly enhances the capability of detecting interactions between the host and its associated microbes. Finally, the identification of several genes involved in skin cancer suggests that similar to colon carcinogenesis, the resident microbiota may play a role in skin cancer susceptibility and its potential prevention and/or treatment.

The genetic architecture in Saccharomyces cerevisiae that contributes to variation in drug response to the antifungals benomyl and ketoconazole.

The genetic basis of variation in drug response was investigated in individual Saccharomyces cerevisiae strains that exhibited different susceptibility to two antifungal agents: benomyl and ketoconazole. Following dose-response screening of 25 strains, 4 were selected on the basis of resistance or sensitivity relative to the standard laboratory strain BY. UWOPS87-2421 and L-1374 were respectively resistant and sensitive to benomyl; DBVPG6044 and Y12 were respectively resistant and sensitive to ketoconazole. We used advanced intercross lines and next generation sequencing-bulk segregant analysis to characterise the quantitative trait loci (QTL) underpinning drug responses after drug selection. Drug response was controlled by multiple QTL, ranging from a minimum of 5 to a maximum of 60 loci, almost all of which were not the primary drug target. For each drug, the resistant and the sensitive strain exhibited a number of shared loci, but also had strain-specific QTL. In our analysis, it was possible to estimate genetic effect of QTL, and a number of those shared between resistant and sensitive strains exhibited variable effect on the response phenotype. Thus, drug responses arise as a result of different genetic architectures, depending on the genetic background of the individual strain in question.

Fine mapping of a distal chromosome 4 QTL affecting growth and muscle mass in a chicken advanced intercross line

In our previous research, QTL analysis in an F2 cross between the inbred New Hampshire (NHI) and White Leghorn (WL77) lines revealed a growth QTL in the distal part of chromosome 4. To physically reduce the chromosomal interval and the number of potential candidate genes, we performed fine mapping using individuals of generations F10 , F11 and F12 in an advanced intercross line that had been established from the initial F2 mapping population. Using nine single nucleotide polymorphism (SNP) markers within the QTL region for an association analysis with several growth traits from hatch to 20weeks and body composition traits at 20weeks, we could reduce the confidence interval from 26.9 to 3.4Mb. Within the fine mapped region, markers rs14490774, rs314961352 and rs318175270 were in full linkage disequilibrium (D'=1.0) and showed the strongest effect on growth and muscle mass (LOD≥4.00). This reduced region contains 30 genes, compared to 292 genes in the original region. Chicken 60K and 600K SNP chips combined with DNA sequencing of the parental lines were used to call mutations in the reduced region. In the narrowed-down region, 489 sequence variants were detected between NHI and WL77. The most deleterious variants are a missense variant in ADGRA3 (SIFT=0.02) and a frameshift deletion in the functional unknown gene ENSGALG00000014401 in NHI chicken. In addition, five synonymous variants were discovered in genes PPARGC1A, ADGRA3, PACRGL, SLIT2 and FAM184B. In our study, the confidence interval and the number of potential genes could be reduced 8- and 10- fold respectively. Further research will focus on functional effects of mutant genes.

Fine-mapping of genes determining extrafusal fiber properties in murine soleus muscle.

Muscle fiber cross-sectional area (CSA) and proportion of different fiber types are important determinants of muscle function and overall metabolism. Genetic variation plays a substantial role in phenotypic variation of these traits; however, the underlying genes remain poorly understood. This study aimed to map quantitative trait loci (QTL) affecting differences in soleus muscle fiber traits between the LG/J and SM/J mouse strains. Fiber number, CSA, and proportion of oxidative type I fibers were assessed in the soleus of 334 genotyped female and male mice of the F34 generation of advanced intercross lines (AIL) derived from the LG/J and SM/J strains. To increase the QTL detection power, these data were combined with 94 soleus samples from the F2 intercross of the same strains. Transcriptome of the soleus muscle of LG/J and SM/J females was analyzed by microarray. Genome-wide association analysis mapped four QTL (genome-wide P < 0.05) affecting the properties of muscle fibers to chromosome 2, 3, 4, and 11. A 1.5-LOD QTL support interval ranged between 2.36 and 4.67 Mb. On the basis of the genomic sequence information and functional and transcriptome data, we identified candidate genes for each of these QTL. The combination of analyses in F2 and F34 AIL populations with transcriptome and genomic sequence data in the parental strains is an effective strategy for refining QTL and nomination of the candidate genes.