Analysing complex genetic traits with chromosome substitution strains

Many valuable animal models of human disease are known and new models are continually being generated in existing inbred strains,. Some disease models are simple mendelian traits, but most have a polygenic basis. The current approach to identifying quantitative trait loci (QTLs) that underlie such traits is to localize them in crosses, construct congenic strains carrying individual QTLs, and finally map and clone the genes. This process is time-consuming and expensive, requiring the genotyping of large crosses and many generations of breeding. Here we describe a different approach in which a panel of chromosome substitution strains (CSSs) is used for QTL mapping. Each of these strains has a single chromosome from the donor strain substituting for the corresponding chromosome in the host strain. We discuss the construction, applications and advantages of CSSs compared with conventional crosses for detecting and analysing QTLs, including those that have weak phenotypic effects.     

Genome-wide genetic association of complex traits in heterogeneous stock mice

Difficulties in fine-mapping quantitative trait loci (QTLs) are a major impediment to progress in the molecular dissection of complex traits in mice. Here we show that genome-wide high-resolution mapping of multiple phenotypes can be achieved using a stock of genetically heterogeneous mice. We developed a conservative and robust bootstrap analysis to map 843 QTLs with an average 95% confidence interval of 2.8 Mb. The QTLs contribute to variation in 97 traits, including models of human disease (asthma, type 2 diabetes mellitus, obesity and anxiety) as well as immunological, biochemical and hematological phenotypes. The genetic architecture of almost all phenotypes was complex, with many loci each contributing a small proportion to the total variance. Our data set, freely available at http://gscan.well.ox.ac.uk, provides an entry point to the functional characterization of genes involved in many complex traits.     

Dopa decarboxylase (Ddc) affects variation in Drosophila longevity

Mutational analyses in model organisms have shown that genes affecting metabolism and stress resistance regulate life span, but the genes responsible for variation in longevity in natural populations are largely unidentified. Previously, we mapped quantitative trait loci (QTLs) affecting variation in longevity between two Drosophila melanogaster strains. Here, we show that the longevity QTL in the 36E;38B cytogenetic interval on chromosome 2 contains multiple closely linked QTLs, including the Dopa decarboxylase (Ddc) locus. Complementation tests to mutations show that Ddc is a positional candidate gene for life span in these strains. Linkage disequilibrium (LD) mapping in a sample of 173 alleles from a single population shows that three common molecular polymorphisms in Ddc account for 15.5% of the genetic contribution to variance in life span from chromosome 2. The polymorphisms are in strong LD, and the effects of the haplotypes on longevity suggest that the polymorphisms are maintained by balancing selection. DDC catalyzes the final step in the synthesis of the neurotransmitters, dopamine and serotonin. Thus, these data implicate variation in the synthesis of bioamines as a factor contributing to natural variation in individual life span.     

Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population

Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.     

Nuclear genetic control of mitochondrial DNA segregation

Mammalian mitochondrial DNA (mtDNA) is a high copy-number, maternally inherited genome that codes for a small number of essential proteins involved in oxidative phosphorylation. Mutations in mtDNA are responsible for a broad spectrum of clinical disorders. The segregation pattern of pathogenic mtDNA mutants is an important determinant of the nature and severity of mitochondrial disease, but it varies with the specific mutation, cell type and nuclear background and generally does not correlate well with mitochondrial dysfunction. To identify nuclear genes that modify the segregation behavior of mtDNA, we used a heteroplasmic mouse model derived from two inbred strains (BALB/c and NZB; ref. 12), in which we had previously demonstrated tissue-specific and age-dependent directional selection for different mtDNA genotypes in the same mouse. Here we show that this phenotype segregates in F2 mice from a genetic cross (BALB/c x CAST/Ei) and that it maps to at least three quantitative-trait loci (QTLs). Genome-wide scans showed linkage of the trait to loci on Chromosomes 2, 5 and 6, accounting for 16-35% of the variance in the trait, depending on the tissue and age of the mouse. This is the first genetic evidence for nuclear control of mammalian mtDNA segregation.     

Functional screening of an asthma QTL in YAC transgenic mice.

Many quantitative trait loci (QTLs) contributing to genetically complex conditions have been discovered, but few causative genes have been identified. This is mainly due to the large size of QTLs and the subtle connection between genotype and quantitative phenotype associated with these conditions. Transgenic mice have been successfully used to analyse well-characterized genes suspected of contributing to quantitative traits. Although this approach is powerful for examining one gene at a time, it can be impractical for surveying the large genomic intervals containing many genes that are typically associated with QTLs. To screen for genes contributing to an asthma QTL mapped to human chromosome 5q3 (refs 6,7), we characterized a panel of large-insert 5q31 transgenics based on studies demonstrating that altering gene dosage frequently affects quantitative phenotypes normally influenced by that gene. This panel of human YAC transgenics, propagating a 1-Mb interval of chromosome 5q31 containing 6 cytokine genes and 17 partially characterized genes, was screened for quantitative changes in several asthma-associated phenotypes. Multiple independent transgenic lines with altered IgE response to antigen treatment shared a 180-kb region containing 5 genes, including those encoding human interleukin 4 (IL4) and interleukin 13 (IL13 ), which induce IgE class switching in B cells. Further analysis of these mice and mice transgenic for mouse Il4 and Il13 demonstrated that moderate changes in Il4 and Il13 expression affect asthma-associated phenotypes in vivo. This functional screen of large-insert transgenics enabled us to identify genes that influence the QTL phenotype in vivo.     

Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease

Integration of genome-wide expression profiling with linkage analysis is a new approach to identifying genes underlying complex traits. We applied this approach to the regulation of gene expression in the BXH/HXB panel of rat recombinant inbred strains, one of the largest available rodent recombinant inbred panels and a leading resource for genetic analysis of the highly prevalent metabolic syndrome. In two tissues important to the pathogenesis of the metabolic syndrome, we mapped cis- and trans-regulatory control elements for expression of thousands of genes across the genome. Many of the most highly linked expression quantitative trait loci are regulated in cis, are inherited essentially as monogenic traits and are good candidate genes for previously mapped physiological quantitative trait loci in the rat. By comparative mapping we generated a data set of 73 candidate genes for hypertension that merit testing in human populations. Mining of this publicly available data set is expected to lead to new insights into the genes and regulatory pathways underlying the extensive range of metabolic and cardiovascular disease phenotypes that segregate in these recombinant inbred strains.     

A rice quantitative trait locus for salt tolerance encodes a sodium transporter

Many important agronomic traits in crop plants, including stress tolerance, are complex traits controlled by quantitative trait loci (QTLs). Isolation of these QTLs holds great promise to improve world agriculture but is a challenging task. We previously mapped a rice QTL, SKC1, that maintained K(+) homeostasis in the salt-tolerant variety under salt stress, consistent with the earlier finding that K(+) homeostasis is important in salt tolerance. To understand the molecular basis of this QTL, we isolated the SKC1 gene by map-based cloning and found that it encoded a member of HKT-type transporters. SKC1 is preferentially expressed in the parenchyma cells surrounding the xylem vessels. Voltage-clamp analysis showed that SKC1 protein functions as a Na(+)-selective transporter. Physiological analysis suggested that SKC1 is involved in regulating K(+)/Na(+) homeostasis under salt stress, providing a potential tool for improving salt tolerance in crops.     

SNP and haplotype mapping for genetic analysis in the rat

The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.     

Candidate lung tumor susceptibility genes identified through whole-genome association analyses in inbred mice

We performed a whole-genome association analysis of lung tumor susceptibility using dense SNP maps ( approximately 1 SNP per 20 kb) in inbred mice. We reproduced the pulmonary adenoma susceptibility 1 (Pas1) locus identified in previous linkage studies and further narrowed this quantitative trait locus (QTL) to a region of less than 0.5 Mb in which at least two genes, Kras2 (Kirsten rat sarcoma oncogene 2) and Casc1 (cancer susceptibility candidate 1; also known as Las1), are strong candidates. Casc1 knockout mouse tumor bioassays showed that Casc1-deficient mice were susceptible to chemical induction of lung tumors. We also found three more genetic loci for lung adenoma development. Analysis of one of these candidate loci identified a previously uncharacterized gene Lasc1, bearing a nonsynonymous substitution (D102E). We found that the Lasc1 Glu102 allele preferentially promotes lung tumor cell growth. Our findings demonstrate the prospects for using dense SNP maps in laboratory mice to refine previous QTL regions and identify genetic determinants of complex traits.     

A phenylalanine in DGAT is a key determinant of oil content and composition in maize

Plant oil is an important renewable resource for biodiesel production and for dietary consumption by humans and livestock. Through genetic mapping of the oil trait in plants, studies have reported multiple quantitative trait loci (QTLs) with small effects, but the molecular basis of oil QTLs remains largely unknown. Here we show that a high-oil QTL (qHO6) affecting maize seed oil and oleic-acid contents encodes an acyl-CoA:diacylglycerol acyltransferase (DGAT1-2), which catalyzes the final step of oil synthesis. We further show that a phenylalanine insertion in DGAT1-2 at position 469 (F469) is responsible for the increased oil and oleic-acid contents. The DGAT1-2 allele with F469 is ancestral, whereas the allele without F469 is a more recent mutant selected by domestication or breeding. Ectopic expression of the high-oil DGAT1-2 allele increases oil and oleic-acid contents by up to 41% and 107%, respectively. This work provides insights into the molecular basis of natural variation of oil and oleic-acid contents in plants and highlights DGAT as a promising target for increasing oil and oleic-acid contents in other crops.     

Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice

Here we present a strategy to determine the genetic basis of variance in complex phenotypes that arise from natural, as opposed to induced, genetic variation in mice. We show that a commercially available strain of outbred mice, MF1, can be treated as an ultrafine mosaic of standard inbred strains and accordingly used to dissect a known quantitative trait locus influencing anxiety. We also show that this locus can be subdivided into three regions, one of which contains Rgs2, which encodes a regulator of G protein signaling. We then use quantitative complementation to show that Rgs2 is a quantitative trait gene. This combined genetic and functional approach should be applicable to the analysis of any quantitative trait.     

Quantitative trait loci mapped to single-nucleotide resolution in yeast

Identifying the genetic variation underlying quantitative trait loci remains problematic. Consequently, our molecular understanding of genetically complex, quantitative traits is limited. To address this issue directly, we mapped three quantitative trait loci that control yeast sporulation efficiency to single-nucleotide resolution in a noncoding regulatory region (RME1) and to two missense mutations (TAO3 and MKT1). For each quantitative trait locus, the responsible polymorphism is rare among a diverse set of 13 yeast strains, suggestive of genetic heterogeneity in the control of yeast sporulation. Additionally, under optimal conditions, we reconstituted approximately 92% of the sporulation efficiency difference between the two genetically distinct parents by engineering three nucleotide changes in the appropriate yeast genome. Our results provide the highest resolution to date of the molecular basis of a quantitative trait, showing that the interaction of a few genetic variants can have a profound phenotypic effect.     

Susceptibility to testicular germ-cell tumours in a 129.MOLF-Chr 19 chromosome substitution strain.

The identification of genes that control susceptibility to testicular germ-cell tumours (TGCTs), the most common cancer affecting young men, has been difficult. In laboratory mice, TGCTs arise from primordial germ cells in only the 129 inbred strains, and susceptibility is under multigenic control. The spontaneously arising mutation Ter (ref. 5) on mouse chromosome 18 (Refs 6,7) increases TGCT frequency on a 129/Sv background. We originally used Ter in genetic crosses to identify loci that control tumorigenesis. A genome scan of tumour-bearing progeny from backcrosses between the 129/Sv-Ter/+ and MOLF/Ei strains provided modest evidence that MOLF-derived alleles on chromosome 19 enhance development of bilateral TGCTs (ref. 9). To obtain independent evidence for linkage to the MOLF chromosome, we made an autosomal chromosome substitution strain (CSS; or 'consomic strain') in which chromosome 19 of 129/Sv+/+ was replaced by its MOLF-derived homologue. The unusually high frequency of TGCTs in this CSS (even in the absence of the Ter mutation) provides evidence confirming the genome survey results, identifies linkage for a naturally occurring strain variant allele that confers susceptibility to TGCTs and illustrates the power of CSSs in complex trait analysis.     

Genetic variation in Mon1a affects protein trafficking and modifies macrophage iron loading in mice

We undertook a quantitative trait locus (QTL) analysis in mice to identify modifier genes that might influence the severity of human iron disorders. We identified a strong QTL on mouse chromosome 9 that differentially affected macrophage iron burden in C57BL/10J and SWR/J mice. A C57BL/10J missense allele of an evolutionarily conserved gene, Mon1a, cosegregated with the QTL in congenic mouse lines. We present evidence that Mon1a is involved in trafficking of ferroportin, the major mammalian iron exporter, to the surface of iron-recycling macrophages. Differences in amounts of surface ferroportin correlate with differences in cellular iron content. Mon1a is also important for trafficking of cell-surface and secreted molecules unrelated to iron metabolism, suggesting that it has a fundamental role in the mammalian secretory apparatus.     

A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase

Grain weight is one of the most important components of grain yield and is controlled by quantitative trait loci (QTLs) derived from natural variations in crops. However, the molecular roles of QTLs in the regulation of grain weight have not been fully elucidated. Here, we report the cloning and characterization of GW2, a new QTL that controls rice grain width and weight. Our data show that GW2 encodes a previously unknown RING-type protein with E3 ubiquitin ligase activity, which is known to function in the degradation by the ubiquitin-proteasome pathway. Loss of GW2 function increased cell numbers, resulting in a larger (wider) spikelet hull, and it accelerated the grain milk filling rate, resulting in enhanced grain width, weight and yield. Our results suggest that GW2 negatively regulates cell division by targeting its substrate(s) to proteasomes for regulated proteolysis. The functional characterization of GW2 provides insight into the mechanism of seed development and is a potential tool for improving grain yield in crops.