Genetic Basis Of Complex Traits Research Articles

A protocol for high-throughput phenotyping, suitable for quantitative trait analysis in mice

Whole-genome genetic association studies in outbred mouse populations represent a novel approach to identifying the molecular basis of naturally occurring genetic variants, the major source of quantitative variation between inbred strains of mice. Measuring multiple phenotypes in parallel on each mouse would make the approach cost effective, but protocols for phenotyping on a large enough scale have not been developed. In this article we describe the development and deployment of a protocol to collect measures on three models of human disease (anxiety, type II diabetes, and asthma) as well as measures of mouse blood biochemistry, immunology, and hematology. We report that the protocol delivers highly significant differences among the eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6 J, DBA/2 J, and LP/J), the progenitors of a genetically heterogeneous stock (HS) of mice. We report the successful collection of multiple phenotypes from 2000 outbred HS animals. The phenotypes measured in the protocol form the basis of a large-scale investigation into the genetic basis of complex traits in mice designed to examine interactions between genes and between genes and environment, as well as the main effects of genetic variants on phenotypes.

Multiple association analysis via simulated annealing (MASSA)

Genome-wide association studies are now technically feasible and likely to become a fundamental tool in unraveling the ultimate genetic basis of complex traits. However, new statistical and computational methods need to be developed to extract the maximum information in a realistic computing time. Here we propose a new method for multiple association analysis via simulated annealing that allows for epistasis and any number of markers. It consists of finding the model with lowest Bayesian information criterion using simulated annealing. The data are described by means of a mixed model and new alternative models are proposed using a set of rules, e.g. new sites can be added (or deleted), or new epistatic interactions can be included between existing genetic factors. The method is illustrated with simulated and real data. An executable version of the program (MASSA) running under the Linux OS is freely available, together with documentation, at http://www.icrea.es/pag.asp?id=Miguel.Perez.

Ab initio genotype–phenotype association reveals intrinsic modularity in genetic networks

Microbial species express an astonishing diversity of phenotypic traits, behaviors, and metabolic capacities. However, our molecular understanding of these phenotypes is based almost entirely on studies in a handful of model organisms that together represent only a small fraction of this phenotypic diversity. Furthermore, many microbial species are not amenable to traditional laboratory analysis because of their exotic lifestyles and/or lack of suitable molecular genetic techniques. As an adjunct to experimental analysis, we have developed a computational information-theoretic framework that produces high-confidence gene–phenotype predictions using cross-species distributions of genes and phenotypes across 202 fully sequenced archaea and eubacteria. In addition to identifying the genetic basis of complex traits, our approach reveals the organization of these genes into generic preferentially co-inherited modules, many of which correspond directly to known enzymatic pathways, molecular complexes, signaling pathways, and molecular machines.

Mapping Fiber and Yield QTLs with Main, Epistatic, and QTL × Environment Interaction Effects in Recombinant Inbred Lines of Upland Cotton

Most agronomic traits of cotton (Gossypium hirsutum L.) are quantitatively inherited and affected by environment. The importance of epistasis as the genetic basis for complex traits has been reported in many crops. In this study, a linkage map was constructed by means of a recombinant inbred line (RIL) population derived from 7235×TM‐1. Main effects, epistatic effects, and environmental interaction effects of quantitative trait loci (QTLs) controlling fiber and yield component traits were determined by mixed linear model based QTL mapping in two to four environments. Sixteen main effect QTLs for 12 traits and 19 digenic interaction QTLs for 12 traits were detected. The amount of variation explained by the QTLs of main effect was larger than the QTLs involved in epistatic interactions. Among seven QTLs having QTL × Environment (QE) interaction effects, five produced significant additive effects and two did not, but only one interaction showed significant additive × additive × environment (AAE) interaction effects. Some QTLs with large effects detected in specific environments could be associated with environmental response elements.

The canine genome

The dog has emerged as a premier species for the study of morphology, behavior, and disease. The recent availability of a high-quality draft sequence lifts the dog system to a new threshold. We provide a primer to use the dog genome by first focusing on its evolutionary history. We overview the relationship of dogs to wild canids and discuss their origin and domestication. Dogs clearly originated from a substantial number of gray wolves and dog breeds define distinct genetic units that can be divided into at least four hierarchical groupings. We review evidence showing that dogs have high levels of linkage disequilibrium. Consequently, given that dog breeds express specific phenotypic traits and vary in behavior and the incidence of genetic disease, genomic-wide scans for linkage disequilibrium may allow the discovery of genes influencing breed-specific characteristics. Finally, we review studies that have utilized the dog to understand the genetic underpinning of several traits, and we summarize genomic resources that can be used to advance such studies. We suggest that given these resources and the unique characteristics of breeds, that the dog is a uniquely valuable resource for studying the genetic basis of complex traits.

Genomic screening and replication using the same data set in family-based association testing

The Human Genome Project and its spin-offs are making it increasingly feasible to determine the genetic basis of complex traits using genome-wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome-wide family-based association studies, using single SNPs or haplotypes, can identify associations that achieve genome-wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease-susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease-susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype-tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome-wide significance, as population-based designs do.

Testing hypotheses regarding the genetics of adaptation

Many of the hypotheses regarding the genetics of adaptation require that one know specific details about the genetic basis of complex traits, such as the number and effects of the loci involved. Developments in molecular biology have made it possible to create relatively dense maps of markers that can potentially be used to map genes underlying specific traits. However, there are a number of reasons to doubt that such mapping will provide the level of resolution necessary to specifically address many evolutionary questions. Moreover, evolutionary change is built upon the substitution of individual mutations, many of which may now be cosegregating in the same allele. In order for this developing area not to become a mirage that traps the efforts of an entire field, the genetic dissection of adaptive traits should be conducted within a strict hypothesis-testing framework and within systems that promise a reasonable chance of identifying the specific genetic changes of interest. Continuing advances in molecular technology may lead the way here, but some form of genetic testing is likely to be forever required.

Assessment of multiple displacement amplification for polymorphism discovery and haplotype determination at a highly polymorphic locus,MC1R

The identification of common genetic variants such as single nucleotide polymorphisms (SNPs) in the human genome has become central in human population genetics and evolution studies, as well as in the study of the genetic basis of complex traits and diseases. Crucial for the accurate identification of genetic variants is the availability of high quality genomic DNA (gDNA). Since popular sources of gDNA (buccal cells, lymphocytes, hair bulb) often do not yield sufficient quantities of DNA for molecular genetic applications, whole genome amplification methods have recently been introduced to generate a renewable source of double-stranded linear DNA. Here, we assess the fidelity of one method, multiple displacement amplification (MDA), which utilizes bacteriophage Phi29 DNA polymerase to generate amplified DNA from an original source of gDNA, in a representative SNP discovery and genetic association study at the melanocortin 1 receptor (MC1R) locus, a highly polymorphic gene in humans involved in skin and hair pigmentation. We observed that MDA has high fidelity for novel SNP discovery and can be a valuable tool in generating a potentially indefinite source of DNA. However, we observed an allele amplification bias that causes genotype miscalls at heterozygous sites. At loci with multiple polymorphic sites in linkage disequilibrium, such as at MC1R, this bias can create a significant number of heterozygote genotype errors that subsequently misrepresents haplotypes.

Angiotensinogen promoter haplotypes are associated with blood pressure in untreated hypertensives.

The polymorphic angiotensinogen (AGT) gene is one of the most promising candidates for blood pressure (BP) regulation and essential hypertension. To investigate whether AGT haplotype analysis adds significant information compared to single polymorphism analysis with respect to different BP phenotypes in an untreated hypertensive sample. Two hundred and twelve untreated hypertensive subjects of Caucasian origin were genotyped for the AGT polymorphisms C-532T, A-20C, C-18T, and G-6A. In single variant analyses, untreated hypertensives, carrying the AGT -532T or -6A alleles had significantly higher systolic blood pressure (SBP) and diastolic blood pressure (DBP), as well as ambulatory BP values compared to respective non-carriers. In haplotype-based analyses, combining all four AGT promoter variants, we demonstrate that AGT haplotypes containing different allele combinations at positions -532 and -6 were significantly associated with different BP values: (1) -532T and -6A with higher, (2) -532C and -6G with lower, (3) -532C and -6A with intermediate BP values. Since the result for the -532C/-20A/-18C/-6G haplotype was due to differences between non-carriers and carriers of this haplotype on both chromosomes, a recessive inheritance model for BP effects could be assumed. Our results designate the C-532T and G-6A as the best candidates for functional studies on the AGT gene. Haplotype-based analyses should greatly aid in the dissection of the genetic basis of complex traits, such as BP regulation and hypertension.

Thomas Henry Huxley (1825-1895) puts us in our place.

Thomas Huxley was one of the 19th century's most active defenders of Darwin's idea that life has evolved through natural processes. An anatomist and paleontologist, he extended his energies to science and education policy, the democratization of science, and the broad societal implications of evolution. Since his time the fossil record has greatly improved and the genetic 'revolution' has occurred, deepening our understanding of primate and human evolution in ways that would please Huxley: improved systematics relies heavily on genetic data, and molecular technologies are opening our understanding of the genetic basis of complex traits of traditional anthropological interest-but in ways that are thoroughly dependent on the fact of evolution. A more unified biological synthesis is forming that unites genes, developmental process, structure, and inheritance. But the tempo and mode of evolution remain unresolved. Huxley was one of many who have had trouble accepting Darwin's gradual natural selection as the central evolutionary mechanism, and views spanning the antipodes of gradualism and saltation find advocates even in our genetic era.

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.

A candidate gene association study on preterm delivery: application of high-throughput genotyping technology and advanced statistical methods.

Preterm delivery (PTD) is the leading cause of infant mortality and morbidity worldwide. The etiology of PTD is largely unknown but is believed to be complex, encompassing multiple genetic and environmental determinants. To date, reports of genetic studies on PTD are sparse. We conducted a large-scale case-control study exploring the associations of 426 single-nucleotide polymorphisms with PTD in 300 mothers with PTD and 458 mothers with term deliveries at the Boston Medical Center. Twenty-five candidate genes were included in the final haplotype analysis, and a significant association of F5 gene haplotype with PTD was revealed and remained significant after Bonferroni correction for multiple testing (P=0.025). We applied different statistical algorithms (both Gibbs sampling and expectation-maximization) in reconstructing haplotype phases and different tests (both likelihood ratio test and permutation test) in association analyses, and all yielded similar results. We also performed exploratory ethnicity-specific analyses, which confirmed the consistent findings of the F5 gene across the ethnic groups. Moreover, IL1R2 (P=0.002 in Blacks), NOS2A (P<0.001 in Whites) and OPRM1 (P=0.004 in Hispanics) gene haplotypes were associated with PTD in specific ethnic groups but not at global significance level. In summary, our results underscore the potentially important role of F5 gene variants in the pathogenesis of PTD, and demonstrate the utility of high-throughput genotyping and a haplotype-based approach in dissecting genetic basis of complex traits.

Classical twin studies and beyond.

Twin studies have been a valuable source of information about the genetic basis of complex traits. To maximize the potential of twin studies, large, worldwide registers of data on twins and their relatives have been established. Here, we provide an overview of the current resources for twin research. These can be used to obtain insights into the genetic epidemiology of complex traits and diseases, to study the interaction of genotype with sex, age and lifestyle factors, and to study the causes of co-morbidity between traits and diseases. Because of their design, these registers offer unique opportunities for selected sampling for quantitative trait loci linkage and association studies.

Genomics in pure and applied entomology.

Genomics is the study of the structure and function of the genome: the set of genetic information encoded in the DNA of the nucleus and organelles of an organism. It is a dynamic field that combines traditional paths of inquiry with new approaches that would have been impossible without recent technological developments. Much of the recent focus has been on obtaining the sequence of entire genomes, determining the order and organization of the genes, and developing libraries that provide immediate physical access to any desired DNA fragment. This has enabled functional studies on a genome-wide level, including analysis of the genetic basis of complex traits, quantification of global patterns of gene expression, and systematic gene disruption projects. The successful contribution of genomics to problems in applied entomology requires the cooperation of the private and public sectors to build upon the knowledge derived from the Drosophila genome and effectively develop models for other insect Orders.

QTL analysis of proteome and transcriptome variations for dissecting the genetic architecture of complex traits in maize.

In this review, we present some studies on genetic analysis of proteome and transcriptome variations, which exemplify new strategies for a better understanding of the molecular and genetic bases of complex traits. A large genetic variability was revealed at the proteome expression level, which raised the possibility to predict phenotypical performance on the basis of gene product variability. This approach yielded limited results, but could be re-newed by extensive identification of proteins now allowed by mass spectrometry. The dissection of the genetic basis of the variation of individual protein amounts proves very powerful to select 'candidate' proteins, physiologically relevant for a given phenotypical trait, as shown by a study on the effect of water stress in maize. In order to investigate factors of grain quality in maize, we selected a regulatory locus known to control the expression of several storage protein genes, Opaque-2, and investigated the relationships between variability in zein amount and composition and the molecular polymorphism at this locus. Moreover, a QTL analysis revealed that the variability in Opaque-2 transcript abundance was controlled by several polymorphic trans-acting regulators unlinked to the Opaque-2 structural gene. Such genetic approaches should represent additional tools for physiological analysis of the huge amounts of data generated by transcritome and proteome projects.

Procreative Beneficence: Why We Should Select the Best Children

Eugenic selection of embryos is now possible by employing in vitro fertilization (IVF) and preimplantation genetic diagnosis (PGD). While PGD is currently being employed for the purposes of detecting chromosomal abnormalities or inherited genetic abnormalities, it could in principle be used to test any genetic trait such as hair colour or eye colour. Genetic research is rapidly progressing into the genetic basis of complex traits like intelligence and a gene has been identified for criminal behaviour in one family. Once the decision to have IVF is made, PGD has few 'costs' to couples, and people would be more inclined to use it to select less serious medical traits, such as a lower risk of developing Alzheimer Disease, or even for non-medical traits. PGD has already been used to select embryos of a desired gender in the absence of any history of sex-linked genetic disease. I will argue that: (1) some non-disease genes affect the likelihood of us leading the best life; (2) we have a reason to use information which is available about such genes in our reproductive decision-making; (3) couples should select embryos or fetuses which are most likely to have the best life, based on available genetic information, including information about non-disease genes. I will also argue that we should allow selection for non-disease genes even if this maintains or increases social inequality. I will focus on genes for intelligence and sex selection. I will defend a principle which I call Procreative Beneficence: couples (or single reproducers) should select the child, of the possible children they could have, who is expected to have the best life, or at least as good a life as the others, based on the relevant, available information.

The biological basis of epistasis between quantitative trait loci for flavone and 3-deoxyanthocyanin synthesis in maize (Zea maysL.)

A major weakness in our understanding of the genetic basis of complex traits has been that of defining the extent and biological basis of epistasis. Our research group has been studying the genetic control of the accumulation of maysin, a C-glycosyl flavone, in maize, Zea mays (L.), silks. Previously, we demonstrated the importance of the p1 locus as a QTL for maysin synthesis. The p1 locus often exhibits significant epistatic interactions with other loci. We developed a mapping population, (W23al x GT119)F2, specifically designed to test whether genes in an intersecting pathway might be detected as QTLs for maysin synthesis and result in epistatic interaction effects. The a1 gene is not required for the synthesis of flavones but is required for the synthesis of 3-deoxyanthocyanins, an intersecting pathway, in maize silks. The p1 locus (P < 0.0001) was a QTL for both flavones and 3-deoxyanthocyanins. The a1 locus was also highly significant (P < 0.0001) for both traits, as was the p1 x a1 epistatic interaction (P < 0.0001). Our results demonstrate that altering the flux of biochemical intermediates between pathways may be the biological basis of major QTL effects and epistatic interactions.

Composite interval mapping reveals a major locus influencing embryonic development rate in rainbow trout (Oncorhynchus mykiss).

Little is known about the genetics controlling the rate of embryonic development in salmonids, despite the fact that this trait plays an important role in the life history of wild and cultured stocks. We investigated the genetics of embryonic development rate by performing an analysis of quantitative trait loci (QTL) on two families of androgenetically derived doubled haploid rainbow trout produced from a hybrid of two clonal lines with divergent embryonic development rates. A total of 170 doubled haploid individuals were genotyped at 222 marker loci [219 amplified fragment length polymorphism (AFLP) markers, 2 microsatellites, and p53]. A genetic linkage analysis resulted in a map consisting of 27 linkage groups with 21 of the markers remaining unlinked at a minimum LOD of 3.0 and maximum theta of 0.40. Eight of these linkage groups were matched to published rainbow trout linkage groups. Composite interval mapping (CIM) revealed evidence for two QTL influencing time to hatch, and suggestive evidence for a third. These QTL accounted for a total of 24.6% of the variation in time to hatch. One of these QTL had a large effect on development rate, especially in one family of doubled haploids, in which it explained 25.6% of the variance in time to hatch. QTL influencing embryonic length and weight at the commencement of exogenous feeding were also identified. The QTL with the strongest effect on embryonic length (lenR13) mapped to the same position as the QTL with the strongest effect on time to hatch (tthR13), suggesting a single QTL may have a pleiotropic effect on both these traits. These results suggest that the use of clonal lines with a doubled haploid crossing design is an effective way of analyzing the genetic basis of complex traits in salmonids.

Quantitative trait loci (QTLs) associated with resistance/susceptibility to infectious pancreatic necrosis virus (IPNV) in rainbow trout (Oncorhynchus mykiss).

Infectious pancreatic necrosis (IPN) is a well-known acute viral disease of salmonid species. We have identified quantitative trait loci (QTLs) associated with resistance to this disease in rainbow trout. We searched for linkage among 51 microsatellite markers used to construct a framework linkage map in backcross families of rainbow trout (Oncorhynchus mykiss), produced by crossing IPN-resistant (YN-RT201) and -susceptible (YK-RT101) strains. Two putative QTLs affecting disease resistance were detected on chromosomes A (IPN R S-1) and C (IPN R/S-2), respectively, suggesting that this is a polygenic trait in rainbow trout. These markers have great potential for use in marker-assisted selection (MAS) for IPN resistance and provide the basis for cloning of IPN resistance genes. Clarification of the genetic bases of complex traits has broad implications for fundamental research, but will also be of practical benefit to fish breeding.

Patterns of genetic variation in Mendelian and complex traits.

This review discusses the prospects for understanding the genetic basis of complex traits in humans. We take the view that work done on Drosophila melanogaster can serve as a model for understanding complex traits in humans, and the literature on this model system, as well as on humans, is reviewed. The prospects for success in understanding the genetic basis of complex traits depend, in part, on the nature of the forces acting on genetic variation. We suggest that different experimental approaches should be undertaken for traits caused by common genetic variants versus those arising from rare genetic variants.