Project description:Copy number variation is an important dimension of genetic diversity and has implications in development and disease. As an important model organism, the mouse is a prime candidate for copy number variant (CNV) characterization, but this has yet to be completed for a large sample size. Here we report CNV analysis of publicly available, high-density microarray data files for 351 mouse tail samples, including 290 mice that had not been characterized for CNVs previously.We found 9634 putative autosomal CNVs across the samples affecting 6.87% of the mouse reference genome. We find significant differences in the degree of CNV uniqueness (single sample occurrence) and the nature of CNV-gene overlap between wild-caught mice and classical laboratory strains. CNV-gene overlap was associated with lipid metabolism, pheromone response and olfaction compared to immunity, carbohydrate metabolism and amino-acid metabolism for wild-caught mice and classical laboratory strains, respectively. Using two subspecies of wild-caught Mus musculus, we identified putative CNVs unique to those subspecies and show this diversity is better captured by wild-derived laboratory strains than by the classical laboratory strains. A total of 9 genic copy number variable regions (CNVRs) were selected for experimental confirmation by droplet digital PCR (ddPCR).The analysis we present is a comprehensive, genome-wide analysis of CNVs in Mus musculus, which increases the number of known variants in the species and will accelerate the identification of novel variants in future studies.
Project description:BACKGROUND:Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600?K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations. RESULTS:Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35?days-of-age (BW35), and 41?days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1-4, 6-7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens. CONCLUSIONS:The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs.
Project description:BACKGROUND: Mus spretus diverged from Mus musculus over one million years ago. These mice are genetically and phenotypically divergent. Despite the value of utilizing M. musculus and M. spretus for quantitative trait locus (QTL) mapping, relatively little genomic information on M. spretus exists, and most of the available sequence and polymorphic data is for one strain of M. spretus, Spret/Ei. In previous work, we mapped fifteen loci for skin cancer susceptibility using four different M. spretus by M. musculus F1 backcrosses. One locus, skin tumor susceptibility 5 (Skts5) on chromosome 12, shows strong linkage in one cross. RESULTS: To identify potential candidate genes for Skts5, we sequenced 65 named and unnamed genes and coding elements mapping to the peak linkage area in outbred spretus, Spret/EiJ, FVB/NJ, and NIH/Ola. We identified polymorphisms in 62 of 65 genes including 122 amino acid substitutions. To look for polymorphisms consistent with the linkage data, we sequenced exons with amino acid polymorphisms in two additional M. spretus strains and one additional M. musculus strain generating 40.1 kb of sequence data. Eight candidate variants were identified that fit with the linkage data. To determine the degree of variation across M. spretus, we conducted phylogenetic analyses. The relatedness of the M. spretus strains at this locus is consistent with the proximity of region of ascertainment of the ancestral mice. CONCLUSION: Our analyses suggest that, if Skts5 on chromosome 12 is representative of other regions in the genome, then published genomic data for Spret/EiJ are likely to be of high utility for genomic studies in other M. spretus strains.
Project description:OBJECTIVE:Obesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, outbred heterogeneous stock (HS) rats were used in controlled environmental conditions to fine-map novel genetic modifiers of adiposity. METHODS:Body weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome-wide. Quantitative trait loci (QTL) were identified by genome-wide association of imputed single-nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively. RESULTS:HS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine-mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus. CONCLUSIONS:These data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits.
Project description:Rodent betaherpesviruses vary considerably in genomic content, and these variations can result in a distinct pathogenicity. Therefore, the identification of unknown betaherpesviruses in house mice (Mus musculus), the most important rodent host species in basic research, is of importance. During a search for novel herpesviruses in house mice using herpesvirus consensus PCR and attempts to isolate viruses in tissue culture, we identified a previously unknown betaherpesvirus. The primary PCR search in mouse organs revealed the presence of known strains of murine cytomegalovirus (Murid herpesvirus 1) and of Mus musculus rhadinovirus 1 only. However, the novel virus was detected after incubation of organ pieces in fibroblast tissue culture and subsequent PCR analysis of the supernatants. Long-distance PCR amplification including the DNA polymerase and glycoprotein B genes revealed a 3.4 kb sequence that was similar to sequences of rodent cytomegaloviruses. Pairwise sequence comparisons and phylogenetic analyses showed that this newly identified murine virus is most similar to the English isolate of rat cytomegalovirus, thereby raising the possibility that two distinct CMV lineages have evolved in both Mus musculus and Rattus norvegicus.
Project description:<b>Background and aims: </b>Associated with numerous metabolic and behavioral abnormalities, obesity is classified by metrics reliant on body weight (such as body mass index). However, overnutrition is the common cause of obesity, and may independently contribute to these obesity-related abnormalities. Here, we use dietary challenges to parse apart the relative influence of diet and/or energy balance from body weight on various metabolic and behavioral outcomes.<br><br><b>Materials and methods: </b>Seventy male mice (mus musculus) were subjected to the diet switch feeding paradigm, generating groups with various body weights and energetic imbalances. Spontaneous activity patterns, blood metabolite levels, and unbiased gene expression of the nutrient-sensing ventral hypothalamus (using RNA-sequencing) were measured, and these metrics were compared using standardized multivariate linear regression models.<br><br><b>Results: </b>Spontaneous activity patterns were negatively related to body weight (p<0.0001) but not diet/energy balance (p = 0.63). Both body weight and diet/energy balance predicted circulating glucose and insulin levels, while body weight alone predicted plasma leptin levels. Regarding gene expression within the ventral hypothalamus, only two genes responded to diet/energy balance (neuropeptide y [npy] and agouti-related peptide [agrp]), while others were related only to body weight.<br><br><b>Conclusions: </b>Collectively, these results demonstrate that individual components of obesity-specifically obesogenic diets/energy imbalance and elevated body mass-can have independent effects on metabolic and behavioral outcomes. This work highlights the shortcomings of using body mass-based indices to assess metabolic health, and identifies novel associations between blood biomarkers, neural gene expression, and animal behavior following dietary challenges.
Project description:We previously constructed a congenic mouse, B6.S-D2Mit194-D2Mit311 (B6.S-2) with SPRET/Ei donor DNA on distal chromosome 2 in a C57BL/6J background that captured an obesity quantitative trait locus (QTL). Mice homozygous for SPRET/Ei alleles at the donor region had decreased body weight and obesity related phenotypes. The B6.S-2 congenic donor region spanned a minimum of 26 Mb. In this study, we constructed five overlapping subcongenics with smaller SPRET/Ei donor regions to fine map the underlying gene(s). One of the five subcongenic lines derived from the B6.S-2 founding congenic, B6.S-2A, captures most of the body weight and adiposity phenotypes in a donor region with a maximum size of 7.4 Mb. Homozygous SPRET/Ei donor alleles in both the founding congenic and the derived B6.S-2A subcongenic exhibit significant decreases in body weight, multiple fat pad weights with the greatest decrease in mesenteric fat pad weight, and Adiposity Index (total fat pad weight divided by body weight). Interval specific microarray analysis in four tissues for donor region genes from the founding B6.S-2 congenic identified several differentially expressed genes mapping to the B6.S-2A subcongenic donor region, including prohormone convertase 2 (PC2). Quantitative real-time PCR confirmed a modest decrease of PC2 expression in whole brains of mice homozygous for SPRET/Ei donor alleles. Analysis of the relative levels of mRNA for B6 and SPRET/Ei in heterozygous congenic mice showed differentially higher expression of the C57BL/6J allele over the SPRET/Ei allele indicating a cis regulation of differential expression. Using subcongenic mapping, we have successfully narrowed a body weight and obesity QTL interval and identified PC2 as a positional candidate gene. Keywords: Two strain comparison for gene discovery Overall design: Two genotypes of B6.S-2 background and congenic strains- for each strain four tissues (whole brain, liver, adipose, muscle) were collected with 3 biological replicates.
Project description:Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with >60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits.
Project description:Aim of the present study was to investigate whether body weight (BW) in broilers is associated with functional modular genes. To this end, first a GWAS for BW was conducted using 6,598 broilers and the high density SNP array. The next step was to search for positional candidate genes and QTLs within strong LD genomic regions around the significant SNPs. Using all positional candidate genes, a network was then constructed and community structure analysis was performed. Finally, functional enrichment analysis was applied to infer the functional relevance of modular genes. A total number of 645 positional candidate genes were identified in strong LD genomic regions around 11 genome-wide significant markers. 428 of the positional candidate genes were located within growth related QTLs. Community structure analysis detected 5 modules while functional enrichment analysis showed that 52 modular genes participated in developmental processes such as skeletal system development. An additional number of 14 modular genes (GABRG1, NGF, APOBEC2, STAT5B, STAT3, SMAD4, MED1, CACNB1, SLAIN2, LEMD2, ZC3H18, TMEM132D, FRYL and SGCB) were also identified as related to body weight. Taken together, current results suggested a total number of 66 genes as most plausible functional candidates for the trait examined.
Project description:Very few causal genes have been identified by quantitative trait loci (QTL) mapping because of the large size of QTL, and most of them were identified thanks to functional links already known with the targeted phenotype. Here, we propose to combine selection signature detection, coding SNP annotation, and cis-expression QTL analyses to identify potential causal genes underlying QTL identified in divergent line designs. As a model, we chose experimental chicken lines divergently selected for only one trait, the abdominal fat weight, in which several QTL were previously mapped. Using new haplotype-based statistics exploiting the very high SNP density generated through whole-genome resequencing, we found 129 significant selective sweeps. Most of the QTL colocalized with at least one sweep, which markedly narrowed candidate region size. Some of those sweeps contained only one gene, therefore making them strong positional causal candidates with no presupposed function. We then focused on two of these QTL/sweeps. The absence of nonsynonymous SNPs in their coding regions strongly suggests the existence of causal mutations acting in cis on their expression, confirmed by cis-eQTL identification using either allele-specific expression or genetic mapping analyses. Additional expression analyses of those two genes in the chicken and mice contrasted for adiposity reinforces their link with this phenotype. This study shows for the first time the interest of combining selective sweeps mapping, coding SNP annotation and cis-eQTL analyses for identifying causative genes for a complex trait, in the context of divergent lines selected for this specific trait. Moreover, it highlights two genes, JAG2 and PARK2, as new potential negative and positive key regulators of adiposity in chicken and mice.