Untangling HDL quantitative trait loci on mouse chromosome 5 and identifying Scarb1 and Acads as the underlying genes

Two high-density lipoprotein cholesterol quantitative trait loci (QTL), Hdlq1 at 125 Mb and Hdlq8 at 113 Mb, were previously identified on mouse distal chromosome 5. Our objective was to identify the underlying genes. We first used bioinformatics to narrow the Hdlq1 locus to 56 genes. The most likely candidate, Scarb1 (scavenger receptor B1), was supported by gene expression data consistent with knockout and transgenic mouse models. Then we confirmed Hdlq8 as an independent QTL by detecting it in an intercross between NZB and NZW (LOD = 12.7), two mouse strains that have identical genotypes for Scarb1. Haplotyping narrowed this QTL to 9 genes; the most likely candidate was Acads (acyl-coenzymeA dehydrogenase, short chain). Sequencing showed that Acads had an amino acid polymorphism, Gly94Asp, in a conserved region; Western blotting showed that protein levels were significantly different between parental strains. A previously known spontaneous deletion causes loss of ACADS activity in BALB/cBy mice. We showed that HDL levels were significantly elevated in BALB/cBy compared with BALB/c mice and that this HDL difference cosegregated with the Acads mutation. We confirmed that Hdlq1 and Hdlq8 are independent QTL on mouse chromosome 5 and demonstrated that Scarb1 and Acads are the underlying genes.     

Analysis of Allele-Specific Expression in Mouse Liver by RNA-Seq: A Comparison With Cis-eQTL Identified Using Genetic Linkage

We report an analysis of allele-specific expression (ASE) and parent-of-origin expression in adult mouse liver using next generation sequencing (RNA-Seq) of reciprocal crosses of heterozygous F₁ mice from the parental strains C57BL/6J and DBA/2J. We found a 60% overlap between genes exhibiting ASE and putative cis-acting expression quantitative trait loci (cis-eQTL) identified in an intercross between the same strains. We discuss the various biological and technical factors that contribute to the differences. We also identify genes exhibiting parental imprinting and complex expression patterns. Our study demonstrates the importance of biological replicates to limit the number of false positives with RNA-Seq data.     

High genetic differentiation between an African and a non-African strain of <Emphasis Type="Italic">Drosophila simulans</Emphasis> revealed by segregation distortion and reduced crossover frequency

Drosophila simulans strains originating from Madagascar and nearby islands in the Indian Ocean often differ from those elsewhere in the number of sex comb teeth and the degree of morphological anomaly in hybrids with D. melanogaster. Here, we report a strong segregation distortion in the F1 intercross between two D. simulans strains originating from Madagascar and the US, possibly at both the gametic and zygotic levels. Strong bias against alleles of the Madagascar strain was observed for all ten marker loci distributed over the entire second chromosome in the F1 intercross, but only a few showed a weak distortion in the isogenic backgrounds of either strains. Significant deviations of genotype frequencies from Hardy–Weinberg proportions were consistently observed for the second chromosome. By contrast, the X and third chromosomes did not show any strong segregation distortion. Crossover frequency on the second chromosome was uniformly reduced in isogenic backgrounds whereas the map lengths in the F1 intercross were comparable to or larger than that of the standard D. melanogaster map. We discuss these findings in relation to previous studies on other traits and interspecific differences between D. mauritiana, which is endemic to Mauritius Island, and D. simulans.     

Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, “genetical genomic” analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE^−/−) background. This BXH.ApoE^−/− population recapitulates several “metabolic syndrome” phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits.     

Joint tests for quantitative trait loci in experimental crosses

Selective genotyping is common because it can increase the expected correlation between QTL genotype and phenotype and thus increase the statistical power of linkage tests (i.e., regression-based tests). Linkage can also be tested by assessing whether the marginal genotypic distribution conforms to its expectation, a marginal-based test. We developed a class of joint tests that, by constraining intercepts in regression-based analyses, capitalize on the information available in both regression-based and marginal-based tests. We simulated data corresponding to the null hypothesis of no QTL effect and the alternative of some QTL effect at the locus for a backcross and an F2 intercross between inbred strains. Regression-based and marginal-based tests were compared to corresponding joint tests. We studied the effects of random sampling, selective sampling from a single tail of the phenotypic distribution, and selective sampling from both tails of the phenotypic distribution. Joint tests were nearly as powerful as all competing alternatives for random sampling and two-tailed selection under both backcross and F2 intercross situations. Joint tests were generally more powerful for one-tailed selection under both backcross and F2 intercross situations. However, joint tests cannot be recommended for one-tailed selective genotyping if segregation distortion is suspected.     

Fine Mapping of Gene Regions Regulating Neurodegeneration

Background

Damage to nerve cells and axons leading to neurodegeneration is a characteristic feature of many neurological diseases. The degree of genetic influence on susceptibility to axotomy-induced neuronal death has so far been unknown. We have examined two gene regions, Vra1 and Vra2, previously linked to nerve cell loss after ventral root avulsion in a rat F2 intercross between the DA and PVG inbred rat strains.

Methodology/Principal Findings

In this study, we use two generations (G8 and G10 cohorts) of an advanced intercross line between DA and PVG^av1 to reproduce linkage to Vra1 and to fine-map this region. By isolating the effect from Vra1 in congenic strains, we demonstrate that Vra1 significantly regulates the loss of motoneurons after avulsion. The regulatory effect mediated by Vra1 thus resides in a congenic fragment of 9 megabases. Furthermore, we have used the advanced intercross lines to give more support to Vra2, originally detected as a suggestive QTL.

Conclusions/Significance

The results demonstrated here show that naturally occurring allelic variations affect susceptibility to axotomy-induced nerve cell death. Vra1 and Vra2 represent the first quantitative trait loci regulating this phenotype that are characterized and fine mapped in an advanced intercross line. In addition, congenic strains provide experimental evidence for the Vra1 effect on the extent of injury-induced neurodegeneration. Identification of the underlying genetic variations will increase our understanding of the regulation and mechanisms of neurodegeneration.     

A locus on chromosome 9 is associated with differential response of 129S1/SvImJ and FVB/NJ strains of mice to systemic LPS

Although polymorphisms in TLR receptors and downstream signaling molecules affect the innate immune response, these variants account for only a portion of the ability of the host to respond to microorganisms. To identify novel genes that regulate the host response to systemic lipopolysaccharide (LPS), we created an F2 intercross between susceptible (FVB/NJ) and resistant (129S1/SvImJ) strains, challenged F2 progeny with LPS via intraperitoneal injection, and phenotyped 605 animals for survival and another 500 mice for serum concentrations of IL-1?? and IL-6. Genome-wide scans were performed on pools of susceptible and resistant mice for survival, IL-1??, and IL-6. This approach identified a locus on the telomeric end of the q arm of chromosome 9 (0?C40?Mb) that was associated with the differences in morbidity and serum concentrations of IL-1?? and IL-6 following systemic LPS in FVB/NJ and 129S1/SvImJ strains of mice. Fine mapping narrowed the locus to 3.7?Mb containing 11 known genes, among which are three inflammatory caspases. We studied expression of genes within the locus by quantitative RT-PCR and showed that Casp1 and Casp12 levels are unaffected by LPS in both strains, whereas Casp4 is highly induced by LPS in FVB/NJ but not in 129S1/SvImJ mice. In conclusion, our mapping results indicate that a 3.7-Mb region on chromosome 9 contains a gene that regulates differential response to LPS in 129S1/SvImJ and FVB/NJ strains of mice. Differences in the induction of Casp4 expression by LPS in the two strains suggest that Casp4 is the most likely candidate gene in this region.     

Identification of genetic loci involved in diabetes using a rat model of depression

While diabetic patients often present with comorbid depression, the underlying mechanisms linking diabetes and depression are unknown. The Wistar Kyoto (WKY) rat is a well-known animal model of depression and stress hyperreactivity. In addition, the WKY rat is glucose intolerant and likely harbors diabetes susceptibility alleles. We conducted a quantitative trait loci (QTL) analysis in the segregating F₂ population of a WKY × Fischer 344 (F344) intercross. We previously published QTL analyses for depressive behavior and hypothalamic-pituitary-adrenal (HPA) activity in this cross. In this study we report results from the QTL analysis for multiple metabolic phenotypes, including fasting glucose, post-restraint stress glucose, postprandial glucose and insulin, and body weight. We identified multiple QTLs for each trait and many of the QTLs overlap with those previously identified using inbred models of type 2 diabetes (T2D). Significant correlations were found between metabolic traits and HPA axis measures, as well as forced swim test behavior. Several metabolic loci overlap with loci previously identified for HPA activity and forced swim behavior in this F₂ intercross, suggesting that the genetic mechanisms underlying these traits may be similar. These results indicate that WKY rats harbor diabetes susceptibility alleles and suggest that this strain may be useful for dissecting the underlying genetic mechanisms linking diabetes, HPA activity, and depression.     

Integrating genetic and network analysis to characterize genes related to mouse weight

Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight–related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.     

Quantitative trait loci controlling leaf venation in Arabidopsis

Leaf veins provide the mechanical support and are responsible for the transport of nutrients and water to the plant. High vein density is a prerequisite for plants to have C4 photosynthesis. We investigated the genetic variation and genetic architecture of leaf venation traits within the species Arabidopsis thaliana using natural variation. Leaf venation traits, including leaf vein density (LVD) were analysed in 66 worldwide accessions and 399 lines of the multi‐parent advanced generation intercross population. It was shown that there is no correlation between LVD and photosynthesis parameters within A. thaliana. Association mapping was performed for LVD and identified 16 and 17 putative quantitative trait loci (QTLs) in the multi‐parent advanced generation intercross and worldwide sets, respectively. There was no overlap between the identified QTLs suggesting that many genes can affect the traits. In addition, linkage mapping was performed using two biparental recombinant inbred line populations. Combining linkage and association mapping revealed seven candidate genes. For one of the candidate genes, RCI2c, we demonstrated its function in leaf venation patterning.     

Transcriptomic Identification of ADH1B as a Novel Candidate Gene for Obesity and Insulin Resistance in Human Adipose Tissue in Mexican Americans from the Veterans Administration Genetic Epidemiology Study (VAGES)

Type 2 diabetes (T2D) is a complex metabolic disease that is more prevalent in ethnic groups such as Mexican Americans, and is strongly associated with the risk factors obesity and insulin resistance. The goal of this study was to perform whole genome gene expression profiling in adipose tissue to detect common patterns of gene regulation associated with obesity and insulin resistance. We used phenotypic and genotypic data from 308 Mexican American participants from the Veterans Administration Genetic Epidemiology Study (VAGES). Basal fasting RNA was extracted from adipose tissue biopsies from a subset of 75 unrelated individuals, and gene expression data generated on the Illumina BeadArray platform. The number of gene probes with significant expression above baseline was approximately 31,000. We performed multiple regression analysis of all probes with 15 metabolic traits. Adipose tissue had 3,012 genes significantly associated with the traits of interest (false discovery rate, FDR ≤ 0.05). The significance of gene expression changes was used to select 52 genes with significant (FDR ≤ 10^-4) gene expression changes across multiple traits. Gene sets/Pathways analysis identified one gene, alcohol dehydrogenase 1B (ADH1B) that was significantly enriched (P < 10^-60) as a prime candidate for involvement in multiple relevant metabolic pathways. Illumina BeadChip derived ADH1B expression data was consistent with quantitative real time PCR data. We observed significant inverse correlations with waist circumference (2.8 x 10^-9), BMI (5.4 x 10^-6), and fasting plasma insulin (P < 0.001). These findings are consistent with a central role for ADH1B in obesity and insulin resistance and provide evidence for a novel genetic regulatory mechanism for human metabolic diseases related to these traits.     

Construction of a Quadruple Auxotrophic Mutant of an Industrial Polyploid Saccharomyces cerevisiae Strain by Using RNA-Guided Cas9 Nuclease

Industrial polyploid yeast strains harbor numerous beneficial traits but suffer from a lack of available auxotrophic markers for genetic manipulation. Here we demonstrated a quick and efficient strategy to generate auxotrophic markers in industrial polyploid yeast strains with the RNA-guided Cas9 nuclease. We successfully constructed a quadruple auxotrophic mutant of a popular industrial polyploid yeast strain, Saccharomyces cerevisiae ATCC 4124, with ura3, trp1, leu2, and his3 auxotrophies through RNA-guided Cas9 nuclease. Even though multiple alleles of auxotrophic marker genes had to be disrupted simultaneously, we observed knockouts in up to 60% of the positive colonies after targeted gene disruption. In addition, growth-based spotting assays and fermentation experiments showed that the auxotrophic mutants inherited the beneficial traits of the parental strain, such as tolerance of major fermentation inhibitors and high temperature. Moreover, the auxotrophic mutants could be transformed with plasmids containing selection marker genes. These results indicate that precise gene disruptions based on the RNA-guided Cas9 nuclease now enable metabolic engineering of polyploid S. cerevisiae strains that have been widely used in the wine, beer, and fermentation industries.     

Genetic analysis of craniofacial traits in the medaka

Family and twin studies suggest that a substantial genetic component underlies individual differences in craniofacial morphology. In the current study, we quantified 444 craniofacial traits in 100 individuals from two inbred medaka (Oryzias latipes) strains, HNI and Hd-rR. Relative distances between defined landmarks were measured in digital images of the medaka head region. A total of 379 traits differed significantly between the two strains, indicating that many craniofacial traits are controlled by genetic factors. Of these, 89 traits were analyzed via interval mapping of 184 F(2) progeny from an intercross between HNI and Hd-rR. We identified quantitative trait loci for 66 craniofacial traits. The highest logarithm of the odds score was 6.2 for linkage group (LG) 9 and 11. Trait L33, which corresponds to the ratio of head length to head height at eye level, mapped to LG9; trait V15, which corresponds to the ratio of snout length to head width measured behind the eyes, mapped to LG11. Our initial results confirm the potential of the medaka as a model system for the genetic analysis of complex traits such as craniofacial morphology.     

Differences in DBA/1J and DBA/2J reveal lipid QTL genes

Recent advances in mouse genomics have revealed considerable variation in the form of single-nucleotide polymorphisms (SNPs) among common inbred strains. This has made it possible to characterize closely related strains and to identify genes that differ; such genes may be causal for quantitative phenotypes. The mouse strains DBA/1J and DBA/2J differ by just 5.6% at the SNP level. These strains exhibit differences in a number of metabolic and lipid phenotypes, such as plasma levels of triglycerides (TGs) and HDL. A cross between these strains revealed multiple quantitative trait loci (QTLs) in 294 progeny. We identified significant TG QTLs on chromosomes (Chrs) 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 16, and 19, and significant HDL QTLs on Chrs 3, 9, and 16. Some QTLs mapped to chromosomes with limited variability between the two strains, thus facilitating the identification of candidate genes. We suggest that Tshr is the QTL gene for Chr 12 TG and HDL levels and that Ihh may account for the TG QTL on Chr 1. This cross highlights the advantage of crossing closely related strains for subsequent identification of QTL genes.     

Genetic factors and diet affect long-bone length in the F34 LG,SM advanced intercross

Previous studies on the LG,SM advanced intercross line have identified approximately 40 quantitative trait loci (QTL) for long -bone (humerus, ulna, femur, and tibia) lengths. In this study, long-bone-length QTL were fine-mapped in the F₃₄ generation (n?=?1424) of the LG,SM advanced intercross. Environmental effects were assessed by dividing the population by sex between high-fat and low-fat diets, producing eight sex/diet cohorts. We identified 145 individual bone-length QTL comprising 45 pleiotropic QTL; 69 replicated QTL from previous studies, 35 were new traits significant at previously identified loci, and 41 were novel QTL. Many QTL affected only a subset of the population based on sex and/or diet. Eight of ten known skeletal growth genes were upregulated in 3-week-old LG/J male proximal tibial growth plates relative to SM/J.The sequences of parental strains LG/J and SM/J indicated the presence of over half a million polymorphisms in the confidence intervals of these 45 QTL. We examined 526 polymorphisms and found that 97 represented radical changes to amino acid composition while 40 were predicted to be deleterious to protein function.Additional experimentation is required to understand how changes in gene regulation or protein function can alter the genetic architecture and interact with the environment to produce phenotypic variation.     

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.     

Genomic analysis of metabolic pathway gene expression in mice

Background  

A segregating population of (C57BL/6J × DBA/2J)F2 intercross mice was studied for obesity-related traits and for global gene expression in liver. Quantitative trait locus analyses were applied to the subcutaneous fat-mass trait and all gene-expression data. These data were then used to identify gene sets that are differentially perturbed in lean and obese mice.