Mapping and analysis of quantitative trait loci in experimental populations

An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait Loci

Assessing genome-wide statistical significance is an important and difficult problem in multipoint linkage analysis. Due to multiple tests on the same genome, the usual pointwise significance level based on the chi-square approximation is inappropriate. Permutation is widely used to determine genome-wide significance. Theoretical approximations are available for simple experimental crosses. In this article, we propose a resampling procedure to assess the significance of genome-wide QTL mapping for experimental crosses. The proposed method is computationally much less intensive than the permutation procedure (in the order of 10(2) or higher) and is applicable to complex breeding designs and sophisticated genetic models that cannot be handled by the permutation and theoretical methods. The usefulness of the proposed method is demonstrated through simulation studies and an application to a Drosophila backcross.

Adding confidence to gene expression clustering

It has been well established that gene expression data contain large amounts of random variation that affects both the analysis and the results of microarray experiments. Typically, microarray data are either tested for differential expression between conditions or grouped on the basis of profiles that are assessed temporally or across genetic or environmental conditions. While testing differential expression relies on levels of certainty to evaluate the relative worth of various analyses, cluster analysis is exploratory in nature and has not had the benefit of any judgment of statistical inference. By using a novel dissimilarity function to ascertain gene expression clusters and conditional randomization of the data space to illuminate distinctions between statistically significant clusters of gene expression patterns, we aim to provide a level of confidence to inferred clusters of gene expression data. We apply both permutation and convex hull approaches for randomization of the data space and show that both methods can provide an effective assessment of gene expression profiles whose coregulation is statistically different from that expected by random chance alone.

In silico fine-mapping: narrowing disease-associated loci by intergenomics

Genetic linkage and association studies define quantitative trait loci (QTLs) and susceptibility loci (SLs) that influence the phenotype of polygenic traits. A web-accessible application was created to identify intergenomic consensuses to fine map QTLs and SLs in silico and select particularly promising candidate genes for such traits. Furthermore, this approach offers an empirical evaluation of animal models for their applicability to the study of human traits.

AVAILABILITY

http://qtl.pzr.uni-rostock.de/qtlmix.php

CONTACT

serrano@pzr.uni-rostock.de.

The genetic basis of male fertility in relation to haplodiploid reproduction in Leptopilina clavipes (Hymenoptera: Figitidae)

Traits under relaxed selection are expected to become reduced or disappear completely, a process called vestigialization. In parthenogenetic populations, traits historically involved in sexual reproduction are no longer under selection and potentially subject to such reduction. In Leptopilina clavipes, thelytokous (parthenogenetic) populations are infected by Wolbachia bacteria. Arrhenotokous populations do not harbor Wolbachia. When antibiotics are applied to infected females, they are cured from their infection and males arise. Such males are capable of producing offspring with uninfected females, but with lower fertilization success than sexual males. This can be attributed to the lack of selection on male fertility in thelytokous lines. In this study we used this variation in L. clavipes male fertility to determine the genetic basis of this trait. Males from cured thelytokous populations were crossed to females from uninfected populations. Using AFLP markers, a genetic linkage map was generated, consisting of five linkage groups and spanning a total distance of 219.9 cM. A single QTL of large effect (explaining 46.5% of the phenotypic variance) was identified for male fertility, which we call male fertility factor (mff). We discuss possible mechanisms underlying the effect of mff, as well as mechanisms involved in vestigialization of traits involved in sexual reproduction.

Intergenomic consensus in multifactorial inheritance loci: the case of multiple sclerosis

Genetic linkage and association studies define chromosomal regions, quantitative trait loci (QTLs), which influence the phenotype of polygenic diseases. Here, we describe a global approach to determine intergenomic consensus of those regions in order to fine map QTLs and select particularly promising candidate genes for disease susceptibility or other polygenic traits. Exemplarily, human multiple sclerosis (MS) susceptibility regions were compared for sequence similarity with mouse and rat QTLs in its animal model experimental allergic encephalomyelitis (EAE). The number of intergenomic MS/EAE consensus genes (295) is significantly higher than expected if the animal model was unrelated to the human disease. Hence, this approach contributes to the empirical evaluation of animal models for their applicability to the study of human diseases.

Quantitative genetics of vector competence for La Crosse virus and body size in Ochlerotatus hendersoni and Ochlerotatus triseriatus interspecific hybrids

La Crosse virus is a leading cause of pediatric encephalitis in the United States. The mosquito Ochlerotatus triseriatus is an efficient vector for La Crosse virus, whereas the closely related O. hendersoni transmits only at very low rates. Quantitative trait loci (QTL) affecting the ability to orally transmit this virus and adult body size were identified in 164 F(2) female individuals from interspecific crosses of O. hendersoni females and O. triseriatus males using a combination of composite interval mapping (CIM), interval mapping (IM) for binary traits, and single-marker mapping. For oral transmission (OT), no genome locations exceeded the 95% experimentwise threshold for declaring a QTL using IM, but single-marker analysis identified four independent regions significantly associated with OT that we considered as tentative QTL. With two QTL, an increase in OT was associated with alleles from the refractory vector, O. hendersoni, and likely reflect epistatic interactions between genes that were uncovered by our interspecific crosses. For body size, two QTL were identified using CIM and a third tentative QTL was identified using single-marker analysis. The genome regions associated with body size also contain three QTL controlling OT, suggesting that these regions contain either single genes with pleiotropic effects or multiple linked genes independently determining each trait.

Genetic bases of estrogen-induced pituitary tumorigenesis: identification of genetic loci determining estrogen-induced pituitary growth in reciprocal crosses between the ACI and Copenhagen rat strains

Estrogens stimulate proliferation and enhance survival of the prolactin (PRL)-producing lactotroph of the anterior pituitary gland and induce development of PRL-producing pituitary tumors in certain inbred rat strains but not others. The goal of this study was to elucidate the genetic bases of estrogen-induced pituitary tumorigenesis in reciprocal intercrosses between the genetically related ACI and Copenhagen (COP) rat strains. Following 12 weeks of treatment with the synthetic estrogen diethylstilbestrol (DES), pituitary mass, an accurate surrogate marker of absolute lactotroph number, was increased 10.6-fold in ACI rats and 4.5-fold in COP rats. Composite interval mapping analyses of the phenotypically defined F(2) progeny from the reciprocal crosses identified six quantitative trait loci (QTL) that determine the pituitary growth response to DES. These loci reside on chromosome 6 [Estrogen-induced pituitary tumor (Ept)1], chromosome 3 (Ept2 and Ept6), chromosome 10 (Ept9), and chromosome 1 (Ept10 and Ept13). Together, these six Ept loci and one additional suggestive locus on chromosome 4 account for an estimated 40% of the phenotypic variance exhibited by the combined F(2) population, while 34% of the phenotypic variance was estimated to result from environmental factors. These data indicate that DES-induced pituitary mass behaves as a quantitative trait and provide information that will facilitate identification of genes that determine the tumorigenic response of the pituitary gland to estrogens.

A model selection-based interval-mapping method for autopolyploids

While extensive progress has been made in quantitative trait locus (QTL) mapping for diploid species, similar progress in QTL mapping for polyploids has been limited due to the complex genetic architecture of polyploids. To date, QTL mapping in polyploids has focused mainly on tetraploids with dominant and/or codominant markers. Here, we extend this view to include any even ploidy level under a dominant marker system. Our approach first selects the most likely chromosomal marker configurations using a Bayesian selection criterion and then fits an interval-mapping model to each candidate. Profiles of the likelihood-ratio test statistic and the maximum-likelihood estimates (MLEs) of parameters including QTL effects are obtained via the EM algorithm. Putative QTL are then detected using a resampling-based significance threshold, and the corresponding parental configuration is identified to be the underlying parental configuration from which the data are observed. Although presented via pseudo-doubled backcross experiments, this approach can be readily extended to other breeding systems. Our method is applied to single-dose restriction fragment autotetraploid alfalfa data, and the performance is investigated through simulation studies.

The landscape of genetic complexity across 5,700 gene expression traits in yeast

Many studies have identified quantitative trait loci (QTLs) that contribute to continuous variation in heritable traits of interest. However, general principles regarding the distribution of QTL numbers, effect sizes, and combined effects of multiple QTLs remain to be elucidated. Here, we characterize complex genetics underlying inheritance of thousands of transcript levels in a cross between two strains of Saccharomyces cerevisiae. Most detected QTLs have weak effects, with a median variance explained of 27% for highly heritable transcripts. Despite the high statistical power of the study, no QTLs were detected for 40% of highly heritable transcripts, indicating extensive genetic complexity. Modeling of QTL detection showed that only 3% of highly heritable transcripts are consistent with single-locus inheritance, 17-18% are consistent with control by one or two loci, and half require more than five loci under additive models. Strikingly, analysis of parent and progeny trait distributions showed that a majority of transcripts exhibit transgressive segregation. Sixteen percent of highly heritable transcripts exhibit evidence of interacting loci. Our results will aid design of future QTL mapping studies and may shed light on the evolution of quantitative traits.

The potential of microarrays to assist shrimp breeding and production: a review

The shrimp aquaculture industry is a relatively new livestock industry, having developed over the past 30 years. Thus, it is poised to take advantage of new technologies from the outset of selective breeding programs. This contrasts with long established livestock industries, where there are already highly specialised breeds. This review focuses specifically on the potential application of microarrays to shrimp breeding. Potential applications of microarrays in selective breeding programs are summarised. Microarrays can be used as a rapid means to generate molecular markers for genetic linkage mapping, and genetic maps have been constructed for yeast, Arabidopsis and barley using microarray technology. Microarrays can also be used in the hunt for candidate genes affecting particular traits, leading to development of perfect markers for these traits (i.e. causative mutations). However, this requires that microarray analysis be combined with genetic linkage mapping, and that substantial genomic information is available for the species in question. A novel application of microarrays is to treat gene expression as a quantitative trait in itself and to combine this with linkage mapping to identify quantitative trait loci controlling the levels of gene expression; this approach may identify higher level regulatory genes in specific pathways. Finally, patterns of gene expression observed using microarrays may themselves be treated as phenotypic traits in selection programs (e.g. a particular pattern of gene expression might be indicative of a disease tolerant individual). Microarrays are now being developed for a number of shrimp species in laboratories around the world, primarily with a focus on identifying genes involved in the immune response. However, at present, there is no central repository of shrimp genomic information, which limits the rate at which shrimp genomic research can be progressed. The application of microarrays to shrimp breeding will be extremely limited until there is a shared repository of genomic information for shrimp, and the collective will and resources to develop comprehensive genomic tools for shrimp.

Selective phenotyping for increased efficiency in genetic mapping studies

The power of a genetic mapping study depends on the heritability of the trait, the number of individuals included in the analysis, and the genetic dissimilarity among them. In experiments that involve microarrays or other complex physiological assays, phenotyping can be expensive and time-consuming and may impose limits on the sample size. A random selection of individuals may not provide sufficient power to detect linkage until a large sample size is reached. We present an algorithm for selecting a subset of individuals solely on the basis of genotype data that can achieve substantial improvements in sensitivity compared to a random sample of the same size. The selective phenotyping method involves preferentially selecting individuals to maximize their genotypic dissimilarity. Selective phenotyping is most effective when prior knowledge of genetic architecture allows us to focus on specific genetic regions. However, it can also provide modest improvements in efficiency when applied on a whole-genome basis. Importantly, selective phenotyping does not reduce the efficiency of mapping as compared to a random sample in regions that are not considered in the selection process. In contrast to selective genotyping, inferences based solely on a selectively phenotyped population of individuals are representative of the whole population. The substantial improvement introduced by selective phenotyping is particularly useful when phenotyping is difficult or costly and thus limits the sample size in a genetic mapping study.

Mammalian circadian biology: elucidating genome-wide levels of temporal organization

During the past decade, the molecular mechanisms underlying the mammalian circadian clock have been defined. A core set of circadian clock genes common to most cells throughout the body code for proteins that feed back to regulate not only their own expression, but also that of clock output genes and pathways throughout the genome. The circadian system represents a complex multioscillatory temporal network in which an ensemble of coupled neurons comprising the principal circadian pacemaker in the suprachiasmatic nucleus of the hypothalamus is entrained to the daily light/dark cycle and subsequently transmits synchronizing signals to local circadian oscillators in peripheral tissues. Only recently has the importance of this system to the regulation of such fundamental biological processes as the cell cycle and metabolism become apparent. A convergence of data from microarray studies, quantitative trait locus analysis, and mutagenesis screens demonstrates the pervasiveness of circadian regulation in biological systems. The importance of maintaining the internal temporal homeostasis conferred by the circadian system is revealed by animal models in which mutations in genes coding for core components of the clock result in disease, including cancer and disturbances to the sleep/wake cycle.

Quantitative trait locus analyses and the study of evolutionary process

The past decade has seen a proliferation of studies that employ quantitative trait locus (QTL) approaches to diagnose the genetic basis of trait evolution. Advances in molecular techniques and analytical methods have suggested that an exact genetic description of the number and distribution of genes affecting a trait can be obtained. Although this possibility has met with some success in model systems such as Drosophila and Arabidopsis, the pursuit of an exact description of QTL effects, i.e. individual gene effect, in most cases has proven problematic. We discuss why QTL methods will have difficulty in identifying individual genes contributing to trait variation, and distinguish between the identification of QTL (or marker intervals) and the identification of individual genes or nucleotide differences within genes (QTN). This review focuses on what ecologists and evolutionary biologists working with natural populations can realistically expect to learn from QTL studies. We highlight representative issues in ecology and evolutionary biology and discuss the range of questions that can be addressed satisfactorily using QTL approaches. We specifically address developing approaches to QTL analysis in outbred populations, and discuss practical considerations of experimental (cross) design and application of different marker types. Throughout this review we attempt to provide a balanced description of the benefits of QTL methodology to studies in ecology and evolution as well as the inherent assumptions and limitations that may constrain its application.

The genomics of gene expression

The study of gene regulation on a genomic scale has been constrained by the modest pace with which new trans-regulatory factors have been identified and by the fact that cis-regulatory sequences have to date been described even in part for only a small fraction of vertebrate genes. An indirect approach for assessing the significance of cis- and trans-regulatory mechanisms on a global scale is to utilize gene expression as a surrogate for transcriptional regulation and to combine genome-scale transcriptional profiling with studies of genetic variation, classical genetic techniques such as linkage analysis, and examination of allelic expression patterns that reveal cis-regulatory variability. A number of recent studies employing these methods provide insight into questions of central importance to our understanding of the larger role of transcriptional regulation in the organization of the human and other complex genomes.

Genes and osteoporosis

Genes play an important role in the development of osteoporosis. Twin and family studies have consistently shown that peak bone mass, ultrasound properties of bone, skeletal geometry, bone turnover, and fracture are heritable. Yet, as we report in this paper, few candidate genes have been implicated without ambiguity. Osteoporosis is thought to be a polygenic disorder, determined by multiple genes and environmental risk factors, each with small to modest effect on bone mass and fracture. Here we argue that future success in finding genes is only possible with improved study design and the use of more rigorous analytic approaches that are now becoming available.

Current Gene-Mapping Strategies in Experimental Models of Multiple Sclerosis

Both family-based linkage analyses and population-based association studies have failed to identify disease-regulatory non-human leucocyte antigen genes of importance in multiple sclerosis (MS). Instead, investigators have employed experimental models, which offer major advantages in genetic studies. We summarize the current main methodologies used and the status of both the human and experimental approaches. Why is it important to find genes regulating MS? There is an immense number of cellular and molecular interactions defined in the immunological field and it is very difficult to unravel those that are critical to an inflammatory disease, such as MS, by classical hypothesis-driven research. Unbiased genetics defines evolutionary conserved gene polymorphisms and pathways regulated by these genes, which are central in the pathogenesis. These, in turn, are of interest as therapeutic targets and pharmacogenetic markers.

Genomic approaches to analyzing natural variation in Arabidopsis thaliana

The genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Abundant polymorphic markers aid quantitative trait locus (QTL) mapping, the fully sequenced genome provides rapid identification of candidate loci, and extensive knockout collections allow those candidate loci to be tested. Combining QTL mapping of classic phenotypic traits with biochemical or expression analysis is providing mechanistic insight into the traits of interest. Conversely, natural variation studies are now being done on genomic traits such as methylation or chiasma frequency.

QTL analysis of quantitative resistance toPhytophthora infestans(late blight) in tomato and comparisons with potato

Quantitative trait loci (QTLs) for resistance to Phytophthora infestans (late blight) were mapped in tomato. Reciprocal backcross populations derived from cultivated Lycopersicon esculentum × wild Lycopersicon hirsutum (BC-E, backcross to L. esculentum; BC-H, backcross to L. hirsutum) were phenotyped in three types of replicated disease assays (detached-leaflet, whole-plant, and field). Linkage maps were constructed for each BC population with RFLPs. Resistance QTLs were identified on all 12 tomato chromosomes using composite interval mapping. Six QTLs in BC-E (lb1a, lb2a, lb3, lb4, lb5b, and lb11b) and two QTLs in BC-H (lb5ab and lb6ab) were most consistently detected in replicated experiments or across assay methods. Lycopersicon hirsutum alleles conferred resistance at all QTLs except lb2a. Resistance QTLs coincided with QTLs for inoculum droplet dispersal on leaves, a trait in L. hirsutum that may contribute to resistance, and dispersal was mainly associated with leaf resistance. Some P. infestans resistance QTLs detected in tomato coincided with chromosomal locations of previously mapped R genes and QTLs for resistance to P. infestans in potato, suggesting functional conservation of resistance within the Solanaceae.Key words: late blight, tomato, Lycopersicon hirsutum, QTL mapping, disease resistance, potato.

A large-sample QTL study in mice: II. Body composition

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from male F2 mice (n = 552) detected 50 QTL on 15 chromosomes impacting weights of various organ and adipose subcomponents of growth, including heart, liver, kidney, spleen, testis, and subcutaneous and epididymal fat depots. Nearly all aggregate growth QTL could be interpreted in terms of the organ and fat subcomponents measured. More than 25% of QTL detected map to MMU2, accentuating the relevance of this chromosome to growth and fatness in the context of this cross. Regions of MMU7, 15, and 17 also emerged as important obesity "hot-spots." Average degrees of directional dominance are close to additivity, matching expectations for body composition traits. A strong QTL congruency is evident among heart, liver, kidney, and spleen weights. Liver and testis are organs whose genetic architectures are, respectively, most and least aligned with that for aggregate body weight. In this study, growth and body weight are interpreted in terms of organ subcomponents underlying the macro aggregate traits, and anchored on the corresponding genomic locations.

WebQTL: web-based complex trait analysis

WebQTL is a website that combines databases of complex traits with fast software for mapping quantitative trait loci (QTLs) and for searching for correlations among traits. WebQTL also includes well-curated genotype data for five sets of mouse recombinant inbred (RI) lines. Thus, to identify QTLs, users need provide only quantitative trait data from one of the supported populations. The WebQTL databases include both biological traits--neuroanatomical, pharmacological, and behavioral traits--and microarray-based gene expression data from BXD RI lines. A search function finds correlations between RNA expression and biological traits, and mapping functions find QTLs for either type of trait. The WebQTL service is available at http://www.webqtl.org/.

The genetic basis of neuroticism

Gray has drawn upon genetic evidence to argue for the existence of rodent emotionality, a model of human neuroticism. With the advent of molecular mapping techniques it has become possible to test this hypothesis. Here I review the progress that has been made, largely in animal genetic studies, demonstrating that a common set of genes act pleiotropically on measures of emotionality. More recently, evidence has emerged supporting the view that the same genes influence variation in both rodent and human phenotypes.

Quantitative trait locus analysis of growth-related traits in a new Arabidopsis recombinant inbred population

Arabidopsis natural variation was used to analyze the genetics of plant growth rate. Screening of 22 accessions revealed a large variation for seed weight, plant dry weight and relative growth rate but not for water content. A positive correlation was observed between seed weight and plant area 10 d after planting, suggesting that seed weight affects plant growth during early phases of development. During later stages of plant growth this correlation was not significant, indicating that other factors determine growth rate during this phase. Quantitative trait locus (QTL) analysis, using 114 (F9 generation) recombinant inbred lines derived from the cross between Landsberg erecta (Ler, from Poland) and Shakdara (Sha, from Tadjikistan), revealed QTLs for seed weight, plant area, dry weight, relative growth rate, chlorophyll fluorescence, flowering time, and flowering-related traits. Growth traits (plant area, dry weight, and relative growth rate) colocated at five genomic regions. At the bottom of chromosome 5, colocation was found of QTLs for leaf area, leaf initiation speed, specific leaf area, and chlorophyll fluorescence but not for dry weight, indicating that this locus might be involved in leaf development. No consistent relation between growth traits and flowering time was observed despite some colocations. Some of the QTLs detected for flowering time overlapped with loci detected in other recombinant inbred line populations, but also new loci were identified. This study shows that Arabidopsis can successfully be used to study the genetic basis of complex traits like plant growth rate.

Efficient algorithms for quantitative trait loci mapping problems

Rapid advances in molecular genetics push the need for efficient data analysis. Advanced algorithms are necessary for extracting all possible information from large experimental data sets. We present a general linear algebra framework for quantitative trait loci (QTL) mapping, using both linear regression and maximum likelihood estimation. The formulation simplifies future comparisons between and theoretical analyses of the methods. We show how the common structure of QTL analysis models can be used to improve the kernel algorithms, drastically reducing the computational effort while retaining the original analysis results. We have evaluated our new algorithms on data sets originating from two large F(2) populations of domestic animals. Using an updating approach, we show that 1-3 orders of magnitude reduction in computational demand can be achieved for matrix factorizations. For interval-mapping/composite-interval-mapping settings using a maximum likelihood model, we also show how to use the original EM algorithm instead of the ECM approximation, significantly improving the convergence and further reducing the computational time. The algorithmic improvements makes it feasible to perform analyses which have previously been deemed impractical or even impossible. For example, using the new algorithms, it is reasonable to perform permutation testing using exhaustive search on populations of 200 individuals using an epistatic two-QTL model.

Mapping major quantitative trait loci for postnatal growth in an intersubspecific backcross between C57BL/6J and Philippine wild mice by using principal component analysis

A number of quantitative trait loci (QTLs) for postnatal growth have previously been reported in mice. As effects of the QTLs are usually small and similar to one another in magnitude, it is generally difficult to know which loci are major contributors to postnatal growth. We applied principal component analysis to a genome-wide search for QTLs affecting postnatal growth in body weight weekly recorded from 3 to 10 weeks of age in an intersubspecific backcross population of C57BL/6J inbred mice (Mus musculus domesticus) and wild mice (M. m. castaneus) captured in the Philippines, in order to discover new QTLs from a gene pool of the wild mice and uncover major loci underlying variation in postnatal growth. Principal component analysis classified phenotypic variation in body weights at different ages into two independent principal components: the first principal component (PC1) extracted information on the entire growth process and the second principal component (PC2) contrasted middle (3-6 weeks of age) with late (6-10 weeks) growth phases. Simple interval mapping and composite interval mapping revealed 10 significant QTLs with main effects on PC1 or PC2 on eight chromosomes. Of these, the six main-effect QTLs interacted epistatically with one another or three new additional QTLs on different chromosomal regions without main effects. Several of the identified QTLs with main effects and/or epistatic interaction effects appeared to be sex specific. These results suggest that the identified 13 QTLs, most of which affected the entire growth process, are very important contributors to complex genetic networks of postnatal growth.

Update of Mouse Microsatellite Database of Japan (MMDBJ)

We updated a database of microsatellite marker polymorphisms found in inbred strains of the mouse, most of which were derived from the wild stocks of four Mus musculus subspecies, M. m. domesticus, M. m. musculus, M. m.castaneus and M. m. molossinus. The major aim of constructing this database was to establish the genetic status of these inbred strains as resources for linkage analysis and positional cloning. The inbred strains incorporated in our database are A/J, C57BL/6J, CBA/J, DBA/2J, SM/J, SWR/J, 129Sv/J, MSM/Ms, JF1/Ms, CAST/Ei, NC/Nga, BLG2/Ms, NJL/Ms, PGN2/Ms, SK/CamEi and SWN/Ms, which have not or have only been poorly incorporated in the Whitehead Institute/MIT (WI/MIT) microsatellite database. The number of polymorphic microsatellite loci incorporated in our database is over 1,000 in all strains, and the URL site for our database is located at http:// www.shigen.nig.ac.jp /mouse/mmdbj/mouse.html.

Expressionview: visualization of quantitative trait loci and gene-expression data in Ensembl

We present here a software tool for combined visualization of gene-expression data and quantitative trait loci (QTL). The application is implemented as an extension to the Ensembl project and caters for a direct transition from microarray experiments of gene or protein expression levels to the genomic context of individual genes and QTL. It supports the visualization of gene clusters and the selection of functional candidate genes in the context of research on complex traits.

Mathematical multi-locus approaches to localizing complex human trait genes

Statistical analysis methods for gene mapping originated in counting recombinant and non-recombinant offspring, but have now progressed to sophisticated approaches for the mapping of complex trait genes. Here, we outline new statistical methods that capture the simultaneous effects of multiple gene loci and thereby achieve a more global view of gene action and interaction than is possible by traditional gene-by-gene analysis. We aim to show that the work of statisticians goes far beyond the running of computer programs.

Application of microarray technology in environmental and comparative physiology

DNA microarray technology is revolutionizing many aspects of biological research, allowing the expression of many thousands of gene transcripts to be monitored simultaneously. This provides powerful tools for the genome-wide correlation of gene transcript levels with physiological responses and alterations in physiological states. To date, microarray analyses have been applied almost exclusively to a few model species for which the abundant gene sequence data permit the fabrication of whole-genome microarrays. However, many interesting physiological traits and responses are poorly expressed or absent in model species and may be better illustrated in nonmodel organisms. Comparative approaches to understanding function traditionally focus on species that by virtue of their unusual adaptations, lifestyles, and phylogeny are particularly suited to address a specific biological process or problem. In this review, we show that microarray technology can be successfully applied to these nonmodel species and used to generate new insights of comparative and evolutionary significance into animal function.

Identification and characterization of aluminum tolerance loci in Arabidopsis (Landsberg erecta x Columbia) by quantitative trait locus mapping. A physiologically simple but genetically complex trait

Aluminum (Al) toxicity, which is caused by the solubilization of Al3+ in acid soils resulting in inhibition of root growth and nutrient/water acquisition, is a serious limitation to crop production, because up to one-half of the world's potentially arable land is acidic. To date, however, no Al tolerance genes have yet been cloned. The physiological mechanisms of tolerance are somewhat better understood; the major documented mechanism involves the Al-activated release of Al-binding organic acids from the root tip, preventing uptake into the primary site of toxicity. In this study, a quantitative trait loci analysis of Al tolerance in Arabidopsis was conducted, which also correlated Al tolerance quantitative trait locus (QTL) with physiological mechanisms of tolerance. The analysis identified two major loci, which explain approximately 40% of the variance in Al tolerance observed among recombinant inbred lines derived from Landsberg erecta (sensitive) and Columbia (tolerant). We characterized the mechanism by which tolerance is achieved, and we found that the two QTL cosegregate with an Al-activated release of malate from Arabidopsis roots. Although only two of the QTL have been identified, malate release explains nearly all (95%) of the variation in Al tolerance in this population. Al tolerance in Landsberg erecta x Columbia is more complex genetically than physiologically, in that a number of genes underlie a single physiological mechanism involving root malate release. These findings have set the stage for the subsequent cloning of the genes responsible for the Al tolerance QTL, and a genomics-based cloning strategy and initial progress on this are also discussed.

Plant genetics: a decade of integration

The last decade provided the plant science community with the complete genome sequence of Arabidopsis thaliana and rice, tools to investigate the function of potentially every plant gene, methods to dissect virtually any aspect of the plant life cycle, and a wealth of information on gene expression and protein function. Focusing on Arabidopsis as a model system has led to an integration of the plant sciences that triggered the development of new technologies and concepts benefiting plant research in general. These enormous changes led to an unprecedented increase in our understanding of the genetic basis and molecular mechanisms of developmental, physiological and biochemical processes, some of which will be discussed in this article.

Large-scale identification of single-feature polymorphisms in complex genomes

We have developed a high-throughput genotyping platform by hybridizing genomic DNA from Arabidopsis thaliana accessions to an RNA expression GeneChip (AtGenome1). Using newly developed analytical tools, a large number of single-feature polymorphisms (SFPs) were identified. A comparison of two accessions, the reference strain Columbia (Col) and the strain Landsberg erecta (Ler), identified nearly 4000 SFPs, which could be reliably scored at a 5% error rate. Ler sequence was used to confirm 117 of 121 SFPs and to determine the sensitivity of array hybridization. Features containing sequence repeats, as well as those from high copy genes, showed greater polymorphism rates. A linear clustering algorithm was developed to identify clusters of SFPs representing potential deletions in 111 genes at a 5% false discovery rate (FDR). Among the potential deletions were transposons, disease resistance genes, and genes involved in secondary metabolism. The applicability of this technique was demonstrated by genotyping a recombinant inbred line. Recombination break points could be clearly defined, and in one case delimited to an interval of 29 kb. We further demonstrate that array hybridization can be combined with bulk segregant analysis to quickly map mutations. The extension of these tools to organisms with complex genomes, such as Arabidopsis, will greatly increase our ability to map and clone quantitative trait loci (QTL).

Congenic mice: cutting tools for complex immune disorders

Autoimmune diseases are, in general, under complex genetic control and subject to strong interactions between genetics and the environment. Greater knowledge of the underlying genetics will provide immunologists with a framework for study of the immune dysregulation that occurs in such diseases. Ascertaining the number of genes that are involved and their characterization have, however, proven to be difficult. Improved methods of genetic analysis and the availability of a draft sequence of the complete mouse genome have markedly improved the outlook for such research, and they have emphasized the advantages of mice as a model system. In this review, we provide an overview of the genetic analysis of autoimmune diseases and of the crucial role of congenic and consomic mouse strains in such research.

Mouse models for genetic dissection of polygenic gastrointestinal diseases

Many diseases with a major public health impact are the result of complex interactions between environmental factors and multiple genes. In the past decade, methods for genome analysis, in particular quantitative trait locus (QTL) analysis in animal models, were developed to identify and localize the genes responsible for multifactorial (polygenic) diseases; QTL analysis is based on experimental crosses between inbred strains with high and low genetic susceptibility. Recently the genes underlying several QTLs could be cloned successfully. Here we describe the impact of these genomic approaches in mice on our understanding of the multifactorial genetics of three gastrointestinal diseases related to metabolism (cholesterol cholelithiasis), development (gastroschisis), and colorectal cancer. The examples demonstrate how mouse models continue to be an invaluable tool in unravelling complex pathomechanisms and unlocking our understanding of human diseases.

Analysis of quantitative trait loci that influence animal behavior

Behavioral differences between inbred strains of mice and rats have a genetic basis that can now be dissected using quantitative trait locus (QTL) analysis. Over the last 10 years, a large number of genetic loci that influence behavior have been mapped. In this article I review what that information has revealed about the genetic architecture of behavior. I show that most behaviors are influenced by QTL of small effect, each contributing to less than 10% of the variance of a behavioral trait. The small effect of each QTL on behavioral variation suggests that the mutational spectrum is different from that which results in Mendelian disorders. Regions of DNA should be appropriately prioritized to find the molecular variants, for instance by looking at sequences that control the level of gene expression rather than variants in coding regions. While the number of allelic loci that can contribute to a trait is large, this is not necessarily the case: the analysis of selected strains shows that a remarkably small number of QTL can explain the bulk of the genetic variation in behavior. I conclude by arguing that genetic mapping has more to offer than a starting point for positional cloning projects. With advances in multivariate analyses, mapping can also test hypotheses about the psychological processes that give rise to behavioral variation.

Gene expression profiling: methodological challenges, results, and prospects for addiction research

This review describes the current methods used to profile gene expression. These methods include microarrays, spotted arrays, serial analysis of gene expression (SAGE), and massive parallel signature sequencing (MPSS). Methodological and statistical problems in interpreting microarray and spotted array experiments are also discussed. Methods and formats such as minimum information about microarray experiments (MIAME) needed to share gene expression data are described. The last part of the review provides an overview of the application of gene-expression profiling technology to substance abuse research and discusses future directions.

Initial sequencing and comparative analysis of the mouse genome

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

Identification of blood pressure quantitative trait loci that differentiate two hypertensive strains

OBJECTIVE

To describe genetic loci that differentiate blood pressures in two genetically hypertensive strains, the Dahl salt-sensitive (S) rat and the Albino Surgery (AS) rat.

METHODS

A genome scan was performed using 222 genetic markers on an F2 population derived from two hypertensive strains, S and AS. The F2 rats were fed 8% NaCl for 5 weeks before blood pressure measurements were taken.

RESULTS

Three blood pressure quantitative trait loci (QTL) were detected, one on each of rat chromosomes (RNO) 2, 4 and 8. The QTL on RNO4, unlike those on RNO2 and RNO8, was not detected in any of the previous seven linkage analyses reported with the S rat as one of the parental strains. Interactions between genetic loci throughout the genome were sought and interactions involving RNO4 with RNO8 and RNO4 with RNO14 were found. Including the new RNO4 locus identified in the present study, 16 distinct regions of the S rat genome have been demonstrated, by linkage analyses, to harbour loci that control blood pressure in the S rat.

CONCLUSIONS

Increased blood pressure in two hypertensive strains, S and AS, is differentially regulated by genetic factors present on RNOs 2, 4 and 8. Therefore, of the 16 distinct genomic regions known to harbour blood pressure QTL in S rats, 13 are likely to contain blood pressure alleles that function similarly in the S rat and the AS rat, whereas three regions differentiate the two strains.

Genotype-phenotype mapping: genes as computer programs

The effects of genes on phenotype are mediated by processes that are typically unknown but whose determination is desirable. The conversion from gene to phenotype is not a simple function of individual genes, but involves the complex interactions of many genes; it is what is known as a nonlinear mapping problem. A computational method called genetic programming allows the representation of candidate nonlinear mappings in several possible trees. To find the best model, the trees are 'evolved' by processes akin to mutation and recombination, and the trees that more closely represent the actual data are preferentially selected. The result is an improved tree of rules that represent the nonlinear mapping directly. In this way, the encoding of cellular and higher-order activities by genes is seen as directly analogous to computer programs. This analogy is of utility in biological genetics and in problems of genotype-phenotype mapping.

Multiple cross mapping (MCM) markedly improves the localization of a QTL for ethanol-induced activation

This study examines the use of multiple cross mapping (MCM) to reduce the interval for an ethanol response QTL on mouse chromosome 1. The phenotype is the acute locomotor response to a 1.5-g/kg i.p. dose of ethanol. The MCM panel consisted of the six unique intercrosses that can be obtained from the C57BL/6J (B6), DBA/2J (D2), BALB/cJ (C) and LP/J (LP) inbred mouse strains (N > or = 600/cross). Ethanol response QTL were detected only with the B6xD2 and B6xC intercrosses. For both crosses, the D2 and C alleles were dominant and decreased ethanol response. The QTL information was used to develop an algorithm for sorting and editing the chromosome 1 Mit microsatellite marker set (http://www.jax.org). This process yielded a cluster of markers between 82 and 85cM (MGI). Evidence that the QTL was localized in or near this interval was obtained by the analysis of a sample (n = 550) of advanced cross heterogenous stock animals. In addition, it was observed that one of the BXD recombinant inbred strains (BXD-32) had a recombination in the interval of interest which produced the expected change in behavior. Overall, the data obtained suggest that the information available within existing genetic maps coupled with MCM data can be used to reduce the QTL interval. In addition, the MCM data set can be used to interrogate gene expression data to estimate which polymorphisms within the interval of interest are relevant to the QTL.