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EYE on bioinformatics: dissecting complex disease traits in silico.

Bioinformatics has provided an unprecedented power and resource for us to decipher the enigma of complex diseases. It can reveal otherwise promiscuous information from the tremendous amount of data generated by the new, powerful and high-throughput technologies of genomics and proteomics. In this paper, we review the cutting edge developments in complex disease trait mapping, databases, computational gene recognition, gene function prediction, pathway reconstruction and disease classification by expression profiling, and computational modelling of living systems. Integration of all this knowledge and the different technologies, alongside cooperation between experts from different fields, will enhance our understanding of the molecular and mechanistic abnormalities in disease state, and greatly assist the rational development of effective therapies.

Chromosome Mapping↗

Harnessing the mouse to unravel the genetics of human disease.

Complex traits, i.e. those with multiple genetic and environmental determinants, represent the greatest challenge for genetic analysis, largely due to the difficulty of isolating the effects of any one gene amid the noise of other genetic and environmental influences. Methods exist for detecting and mapping the Quantitative Trait Loci (QTLs) that influence complex traits. However, once mapped, gene identification commonly involves reduction of focus to single candidate genes or isolated chromosomal regions. To reach the next level in unraveling the genetics of human disease will require moving beyond the focus on one gene at a time, to explorations of pleiotropism, epistasis and environment-dependency of genetic effects. Genetic interactions and unique environmental features must be as carefully scrutinized as are single gene effects. No one genetic approach is likely to possess all the necessary features for comprehensive analysis of a complex disease. Rather, the entire arsenal of behavioral genomic and other approaches will be needed, such as random mutagenesis, QTL analyses, transgenic and knockout models, viral mediated gene transfer, pharmacological analyses, gene expression assays, antisense approaches and importantly, revitalization of classical genetic methods. In our view, classical breeding designs are currently underutilized, and will shorten the distance to the target of understanding the complex genetic and environmental interactions associated with disease. We assert that unique combinations of classical approaches with current behavioral and molecular genomic approaches will more rapidly advance the field.

Animals↗

A simplified QTL mapping approach for screening and mapping of novel AFLP markers associated with beef marbling.

Genome screening of quantitative trait loci (QTL) for a complex trait is usually costly and highly laborious, as it requires a large number of markers spanning the whole genome. Here we present a simplified approach for screening and mapping of QTL-linked markers for beef marbling using a WagyuxLimousin F(2) reference population. This simplified approach involves integration of the amplified fragment length polymorphism (AFLP) with DNA pooling and selective genotyping and comparative bioinformatics tools. AFLP analysis on two high and two low marbling DNA pools yielded ten visually different markers. Among them, four were confirmed based on individual AFLP validation. Sequencing and in silico characterization assigned two of these AFLP markers to bovine chromosomes 1 (BTA1) and 13 (BTA13), which are orthologous to human chromosomes HSA21q22.2 and HSA10p11.23 with both regions harboring QTL for obesity-related phenotypes. Both AFLP markers showed significantly large additive genetic effects (0.28+/-0.11 on BTA1 and 0.54+/-0.21 on BTA13) on beef-marbling score (BMS) (P<0.05). Overall, this approach is less time consuming, inexpensive and in particular, suitable for screening and mapping QTL-linked markers when targeting one or a few complex traits.

Animals↗

Genetic architectures of brain-related traits are shaped by strong selective constraints.

Genome-wide association studies (GWAS) have identified hundreds of significant loci for psychiatric disorders, yet the strength of these associations remains modest compared to other human complex traits with similar numbers of hits. Whether this pattern reflects statistical artifacts or real biological differences-and, if the latter, what underlies it-remains unclear. In addition to psychiatric disorders, we find that other traits with functional enrichment in the central nervous system (CNS), whether binary or quantitative, also share similar genetic architectures, characterized by GWAS hits of limited statistical significance and generally higher allele frequencies. In comparing the architecture of binary and quantitative traits, we adjust for statistical power in their respective studies. After this adjustment, we fit an evolutionary model of architecture and show that CNS-enriched traits have large mutational target sizes, with contributing variants and genes experiencing stronger selection than those for other traits. Our findings reveal heterogeneity among complex traits and provide insights into traits that more effectively capture fitness-relevant processes. More broadly, our results suggest that the genetic architectures of complex traits are shaped by the tissues through which these traits are mediated.

Humans↗

QTL for microstructural and biophysical muscle properties and body composition in pigs.

BACKGROUND: The proportion of muscle fibre types and their size affect muscularity as well as functional properties of the musculature and meat quality. We aimed to identify QTL for microstructural muscle properties including muscle fibre size, their numbers and fibre type proportions as well as biophysical parameters of meat quality and traits related to body composition, i.e. pH, conductivity, area of M. longissimus dorsi and lean meat content. A QTL scan was conducted in a porcine experimental population that is based on Duroc and Berlin Miniature Pig. RESULTS: Least square regression interval mapping revealed five significant and 42 suggestive QTL for traits related to muscle fibre composition under the line-cross model as well as eight significant and 40 suggestive QTL under the half-sib model. For traits related to body composition and biophysical parameters of meat quality five and twelve significant plus nine and 22 suggestive QTL were found under the line-cross and half-sib model, respectively. Regions with either significant QTL for muscle fibre traits or significant QTL for meat quality and muscularity or both were detected on SSC1, 2, 3, 4, 5, 13, 14, 15, and 16. QTL for microstructural properties explained a larger proportion of variance than did QTL for meat quality and body composition. CONCLUSION: Microstructural properties of pig muscle and meat quality are governed by genetic variation at many loci distributed throughout the genome. QTL analysis under both, the line-cross and half-sib model, allows detecting QTL in case of fixation or segregation of the QTL alleles among the founder populations and thus provide comprehensive insight into the genetic variation of the traits under investigation. Genomic regions affecting complex traits of muscularity and meat quality as well as microstructural properties might point to QTL that in first instance affect muscle fibre traits and by this in second instance meat quality. Disentangling complex traits in their constituent phenotypes might facilitate the identification of QTL and the elucidation of the pleiotropic nature of QTL effects.

Animals↗

Development of a wide population of chromosome single-segment substitution lines in the genetic background of an elite cultivar of rice (Oryza sativa L.).

Naturally occurring allelic variations underlying complex traits are useful resources for the functional analysis of plant genes. To facilitate the genetic analysis of complex traits and the use of marker-assisted breeding in rice, we developed a wide population consisting of 217 chromosome single-segment substitution lines (SSSLs) using Oryza sativa L. 'Hua-Jing-Xian74' (HJX74), an elite Indica cultivar, as recipient, and 6 other accessions, including 2 Indica and 4 Japonica, as donors. Each SSSL contains a single substituted chromosome segment derived from 1 of the 6 donors in the genetic background of HJX74. The total size of the substituted segments in the SSSL population was 4695.0 cM, which was 3.1 times that of rice genome. To evaluate the potential application of these SSSLs for quantitative trait loci detection, phenotypic variations of the quantitative traits of days to heading and grain length in the population consisting of 210 SSSLs were observed under natural environmental conditions. The results demonstrated that there was a wide range of phenotypic variation in the traits in the SSSL population. These genetic materials will be powerful tools to dissect complex traits into a set of monogenic loci and to assign phenotypic values to different alleles at the locus of interest.

Chromosome Mapping↗

[Genes, behavior and disease. A sceptic's view of gene mapping and gene therapy].

This paper contains four parts. The first focuses on The Human Genome Project (HGP). The concept of a "normal sequence" seems problematic. The second part reviews what is meant by "genetically-caused" and by "a (several) gene(s) for a trait". Genes work in concert, and it is likely that many genes together influence most complex traits. A difference in traits between two individuals, however, can be due to a difference in a single gene, as is the case for several thousand rare "genetic diseases". Such diseases were the original focus of gene therapy. Could gene therapy also be applied to more common complex traits? Diagnostic problems and the unsuccessful attempts to find a single gene difference in patients with manic depressive disorder, schizophrenia and Alzheimer's disease are discussed. Part three reviews future genetic research into complex traits and what kind of treatment can realistically be expected. It is concluded that improved diagnostics is the most likely outcome, not therapy. Part four raises arguments from the emerging Darwinian approach to medicine and states that it is far too early to even think of gene therapy. The needed knowledge about genes, behaviour and disease will not come from the one-sided genetic effort represented by HGP, and the resources should instead be invested in several different approaches to these complex issues.

Behavior↗

Affected-sib-pair interval mapping and exclusion for complex genetic traits: sampling considerations.

We describe an extension of Risch's [(1990a,b) Am J Hum Genet 46:222-228, 229-241] method of linkage detection and exclusion for complex genetic traits. The method uses interval mapping to infer disease locus identity-by-descent (IBD) sharing for affected sib pairs (ASPs) based on marker information for the ASP and other genotyped family members. The method is likelihood based, and makes use of Risch's parameterization in terms of recurrence risk ratios for relatives. We describe specific linkage detection and exclusion tests for use as genome screening tools to prioritize genomic regions for further study. We also examine issues of optimal study design. We advocate initially typing a large panel of ASPs (and no additional family members) with a map of genetic markers evenly spaced at 10-20-cM intervals. We recommend a screening procedure that 1) investigates further all regions with maximum lod scores greater than 1 and 2) excludes from consideration those regions that result in lod scores less than -2 at the smallest genetic effect that is viewed as important to detect. Further investigation of an interval might include typing other available families or family members, typing additional markers in the interval, and carrying out further statistical analyses. This strategy is efficient in the number of genotypings required and focuses attention on regions most likely to harbor a disease gene with a substantial impact on disease risk, while resulting in the pursuit of a manageable number of false-positive linkage results. Modification may be required if insufficient ASPs are available or if families come from a significantly admixed population.

Chromosome Mapping↗

Genetic mechanisms and evolutionary significance of natural variation in Arabidopsis.

Genomic studies of natural variation in model organisms provide a bridge between molecular analyses of gene function and evolutionary investigations of adaptation and natural selection. In the model plant species Arabidopsis thaliana, recent studies of natural variation have led to the identification of genes underlying ecologically important complex traits, and provided new insights about the processes of genome evolution, geographic population structure, and the selective mechanisms shaping complex trait variation in natural populations. These advances illustrate the potential for a new synthesis to elucidate mechanisms for the adaptive evolution of complex traits from nucleotide sequences to real-world environments.

Adaptation, Biological↗

Male pregnancy and the evolution of body segmentation in seahorses and pipefishes.

The evolution of complex traits, which are specified by the interplay of multiple genetic loci and environmental effects, is a topic of central importance in evolutionary biology. Here, we show that body and tail vertebral numbers in fishes of the pipefish and seahorse family (Syngnathidae) can serve as a model for studies of quantitative trait evolution. A quantitative genetic analysis of body and tail vertebrae from field-collected families of the Gulf pipefish, Syngnathus scovelli, shows that both traits exhibit significantly positive additive genetic variance, with heritabilities of 0.75 +/- 0.13 (mean +/- standard error) and 0.46 +/- 0.18, respectively. We do not find any evidence for either phenotypic or genetic correlations between the two traits. Pipefish are characterized by male pregnancy, and phylogenetic consideration of body proportions suggests that the position of eggs on the pregnant male's body may have contributed to the evolution of vertebral counts. In terms of numbers of vertebrae, tail-brooding males have longer tails for a given trunk size than do trunk-brooding males. Overall, these results suggest that vertebral counts in pipefish are heritable traits, capable of a response to selection, and they may have experienced an interesting history of selection due to the phenomenon of male pregnancy. Given that these traits vary among populations within species as well as among species, they appear to provide an excellent model for further research on complex trait evolution. Body segmentation may thus afford excellent opportunities for comparative study of homologous complex traits among disparate vertebrate taxa.

Animals↗

Immunity to intracellular pathogens as a complex genetic trait.

Although the role of host heredity in susceptibility to infectious diseases is significant, the genetic control of immunity to infection remains poorly understood. Advances in experimental and epidemiological analyses of complex genetic traits have led to the discoveries of novel genetic determinants of host resistance. New loci that control susceptibility to a number of intracellular pathogens have been identified using mouse models of infectious diseases. The contributions of individual loci, however, vary in quantitative and qualitative manner, depending on mechanisms of pathogen virulence and genetic background of the host. In this review, we discuss how genetic analysis of host resistance contributes to further understanding of host immunity and pathogenesis of intracellular infections.

Animals↗

Genetic and molecular dissection of quantitative traits in rice.

Recent progress in the generation of a molecular genetic map and markers for rice has made possible a new phase of mapping individual genes associated with complex traits. This type of analysis is often referred to as quantitative trait locus (QTL) analysis. Increasing numbers of QTL analyses are providing enormous amounts of information about QTLs, such as the numbers of loci involved, their chromosomal locations and gene effects. Clarification of genetic bases of complex traits has a big impact not only on fundamental research on rice plant development, but it also has practical benefits for rice breeding. In this review, we summarize recent progress of QTL analysis of several complex traits in rice. A strategy for positional cloning of genes at QTLs is also discussed.

Chromosome Mapping↗

Identification of genes involved in Drosophila melanogaster geotaxis, a complex behavioral trait.

Identifying the genes involved in polygenic traits has been difficult. In the 1950s and 1960s, laboratory selection experiments for extreme geotaxic behavior in fruit flies established for the first time that a complex behavioral trait has a genetic basis. But the specific genes responsible for the behavior have never been identified using this classical model. To identify the individual genes involved in geotaxic response, we used cDNA microarrays to identify candidate genes and assessed fly lines mutant in these genes for behavioral confirmation. We have thus determined the identities of several genes that contribute to the complex, polygenic behavior of geotaxis.

Animals↗

Finding genetic markers for complex phenotypic traits in parasites.

The identification, mapping and eventual cloning of genes which determine or influence important epidemiological traits in parasites can have great benefits for the control of parasitic disease. In this review, strategies are outlined for identifying genetic markers for complex, quantitative traits. A genetic marker is a variable DNA sequence which co-occurs with a variable quantitative trait. Candidate markers are chosen because they are thought to directly influence the trait whereas random markers are expected to be linked to another DNA sequence which influences the trait. Association studies compare the value of a quantitative trait between different marker genotype classes in a population, without regard to family structure. Linkage studies compare the value of a quantitative trait between marker genotype classes within families or within a population (usually derived from a cross between inbred lines) which is segregating for both marker and quantitative trait loci. The most commonly used analytical methods for determining the significance of association or linkage between marker and quantitative trait loci, and for estimating parameters such as recombination rate and quantitative gene action, are least-squares and maximum likelihood. Both methods may be used to test either single markers or the interval between flanking markers, and both suffer from the need to minimize type I and type II error rates with multiple tests.

Animals↗

Physical mapping of male fertility and meiotic drive quantitative trait loci in the mouse t complex using chromosome deficiencies.

The t complex spans 20 cM of the proximal region of mouse chromosome 17. A variant form, the t haplotype (t), exists at significant frequencies in wild mouse populations and is characterized by the presence of inversions that suppress recombination with wild-type (+) chromosomes. Transmission ratio distortion and sterility are associated with t and affect males only. It is hypothesized that these phenomena are caused by trans-acting distorter/sterility factors that interact with a responder locus (Tcr(t)) and that the distorter and sterility factors are the same because homozygosity of the distorters causes male sterility. One factor, Tcd1, was previously shown to be amorphic using a chromosome deletion. To overcome limitations imposed by recombination suppression, we used a series of deletions within the t complex in trans to t chromosomes to characterize the Tcd1 region. We find that the distorter activity of Tcd1 is distinct from a linked sterility factor, originally called tcs1. YACs mapped with respect to deletion breakpoints localize tcs1 to a 1.1-Mb interval flanked by D17Aus9 and Tctex1. We present evidence for the existence of multiple proximal t complex regions that exhibit distorter activity. These studies demonstrate the utility of chromosome deletions for complex trait analysis.

Animals↗

Linkage studies of schizophrenia.

The study of schizophrenia genetics has revealed much about the disease but none of the essential secrets of its etiology, so far, for numerous reasons. First, schizophrenia is a complex trait, influenced by both genes and environment. Second, it appears to be a highly heterogeneous disease, with locus and allelic heterogeneity both between and within families likely. Third, since it is common, it is likely that the genetic liability variants are common, and so are found with relatively high frequency in the general population. Fourth, linkage methods, which deliver rapid coverage of the genome, have great power to identify single genes causing Mendelian disorders but are poorly suited to the genetic architecture of complex traits. Although association methods are undeniably more powerful in such situations, affordable technologies to deliver the much higher density whole genome coverage required are not yet available and candidate gene studies of schizophrenia have not produced robust and replicable results. In spite of these limitations, there are now sufficient data to support several conclusions. Numerous regions of the human genome give consistent, though by no means unanimous, support for linkage. The precise nature of these signals is not yet understood, and power to position the effects is poor, but metanalyses show the co-occurrence is unlikely to be due to chance. Combined approaches utilizing linkage for rapid genome coverage and association for fine-scale follow-up have identified several promising candidate genes. Although the definition of replication in a complex trait is itself complex, a number of these candidates have been supported by numerous studies. These converging lines of evidence suggest that the genetics of schizophrenia, long considered a most intractable problem, are at last beginning to be unraveled.

Chromosome Mapping↗

Cancer as a complex genetic trait: tumor susceptibility in humans and mouse models.

Cancer directly affects at least one-third of the human population, but the inherited genetic determinants of cancer risk remain largely unknown. Mouse models of human cancer are helping us to understand this disease as a complex genetic trait and thus to identify the multiple genetic variant alleles involved in pathways that affect individual cancer susceptibility.

Alleles↗

[Construction of chromosome segment substitution lines carrying overlapping chromosome segments of the whole wild rice genome and identification of quantitative trait loci for rice quality].

Rice is one of the major staple cereal grains. Most of the important traits of crops are complex traits controlled by quantitative trait loci (QTL). Detection and genetic identification of QTLs can provide insights into molecular and biological mechanisms of development and physiology. Chromosome segment substitution lines (CSSLs) have been proposed as a simple and powerful way to identify QTLs. The demand for rice grain quality becomes increasingly important. The primary components of rice grain quality include appearance, milling and physico-chemical, cooking and eating quality. Most of these traits are complex and controlled by QTLs, so genetic characterization of these traits is more difficult than that of traits each controlled by a singular gene such as Waxy, which controls glutinousness of rice grain. We constructed 133 chromosome segment substitution lines (CSSLs) from backcross progenies (BC3F2) derived from a cross between Teqing (an O. sativa L. ssp. indica variety) as the recurrent parent and wild rice (O. rufipogon Griff.) as the donor parent. In this process, we carried out marker-assisted selection (MAS) by using 118 CAPS or SSR markers covering the whole rice genome (Figs.1, 2). Because phenotypic values of quality trait were significantly different between cultivar Teqing and wild rice, the CSSLs were used to identify QTLs for rice quality traits. Three appearance quality traits (head rice percentage, HRP; percentage of chalky rice grains, PCRG; transparency, TP) and five physico-chemical properties (gelatinization temperature, GT; gel consistency, GC; amylose content, AC; protein content, PC; fat content, FC) were scored using 133 CSSLs which substituted segments covering the whole genome of wild rice. A total of 15 QTLs for five of the eight traits mentioned above (HRP, PCRG, TP, PC and FC) were identified on nine chromosomes, and several QTLs affecting different quality traits were mapped in the same regions (Fig.3, Table 1).

Chromosomes, Plant↗