Genetic Basis Of Complex Traits Research Articles

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.

Differential response to dietary fat in large (LG/J) and small (SM/J) inbred mouse strains.

The "large" (LG/J) and "small" (SM/J) inbred mouse strains differ for a wide variety of traits related to body size and obesity. Ninety-three LG/J and SM/J mice were divided into two treatment categories and fed a moderately high-fat diet (21% kcal fat) or a low-fat diet (12% kcal fat) from weaning to necropsy. Strain differences in obesity-related traits and differential response to dietary fat increases were analyzed using ANOVA. LG/J animals grow faster from 3 to 10 wk, have longer tails, and have heavier body weight, liver weight, and fat pad weight than SM/J animals. SM/J animals grow faster after 10 wk of age and have higher fasting glucose levels than LG/J animals. SM/J mice were more responsive to increased dietary fat than LG/J mice for growth after 10 wk, necropsy weight, liver weight, fat pad weights, and fasting glucose levels (in males). The growth from 3 to 10 wk had a much greater response in the LG/J strain, whereas tail length had no response. This pattern of dietary response is similar to that expected under the "thrifty" phenotype hypothesis. Genes affecting strain differences and the differential response of the strains to dietary fat can be successfully mapped in the intercross of the LG/J and SM/J strains. This intercross provides an excellent multigenic model for the genetic basis of complex traits and diseases related to body size and obesity.

Genetics of complex disease: approaches, problems, and solutions.

Complex or multifactorial diseases are defined as diseases that are ultimately determined by a number of genetic and environmental factors. Although there are many technologies and strategies that can be used to detect genetic factors influencing complex diseases, these technologies and strategies have inherent limitations. In fact, the very name "complex disease" suggests that the results from relevant studies will not be simple to decipher. Ultimately, both the detection and precise characterization of a factor's contribution to a complex disease are difficult undertakings, because the effect of any one factor may be obscured or confounded by other factors. However, the genetic dissection of complex diseases can be greatly facilitated by paying heed to two very basic distinctions. The first distinction is between complexity at the level of individuals and complexity at the level of populations. The second distinction is between the two sequentially pursued components of gene discovery paradigms: gene identification and gene effect characterization. Although genetic epidemiology, as a research field, is oriented to both components of gene discovery for complex diseases, it is suited to gene effect characterization at the population level more than anything else. This paper reviews the origins of the genetic basis of complex traits, as well as the problems plaguing genetic epidemiologic analysis strategies, with the hope of showing how greater attention to these distinctions, as well as a greater integration of relevant knowledge, can alleviate confusion and shape future investigations. In addition, a new discipline, "phenomics" or "phenometrics," could be initiated that would complement genomic research as presently performed.

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.

Comparative maps: the mammalian jigsaw puzzle

Chromosomal rearrangements such as inversions and translocations have played an important role in defining genome organization in existing mammals. The number of rearrangements that have occurred since divergence from the ‘primordial’ mammal has been modest and the distribution of these rearrangements among chromosomes seems to be random. As a result, each mammalian species has a unique arrangement of conserved and disrupted chromosomal segments as compared to other mammalian species. Genes are excellent markers for these chromosomal segments because homologies can be detected in highly divergent species. By comparing the chromosomal location of homologous genes in different species, maps of conserved chromosomal segments can be obtained. These comparative maps can be used to predict gene locations in other species, identify candidate disease genes, characterize the genetic basis for complex traits, and find modulators of disease susceptibility. Equally important is the use of comparative maps for addressing questions about genome organization and evolution.