同卵双胞胎在复杂性状DNA甲基化调控机制研究中的应用

同卵双胞胎来源于同一个受精卵,DNA序列基本一致,但在某些重要表型上如复杂疾病,并不完全一样。利用表型不一致的同卵双胞胎进行研究,能在遗传背景、母体效应、年龄性别效应等一致的基础上,深入研究分析复杂性状的表观调控机制。而DNA甲基化是最为稳定的一类表观遗传修饰。在人类中,利用同卵双胞胎对印记异常疾病、精神类疾病、自身免疫病及癌症等疾病的DNA甲基化调控研究已经揭示了多个致病基因,为研究疾病的表观调控以及表观遗传学药物的应用打下了基础。本文着重对同卵双胞胎DNA甲基化状态、DNA甲基化遗传力计算以及复杂性状DNA甲基化调控的研究应用及其进展展开综述,以期为复杂性状表观调控机制研究提供借鉴和参考。     

The mechanism of emergenesis

Since each individual produced by the sexual process contains a unique set of genes, very exceptional combinations of genes are unlikely to appear twice even within the same family. E. O. Wilson (1978)The intraclass correlations of monozygotic twins who were separated in infancy and reared apart (MZA twins) provide estimates of trait heritability, and the Minnesota Study of Twins Reared Apart [MISTRA: Bouchard et al. (1990), The sources of human psychological differences: the Minnesota study of twins reared apart, Science 250, 223-228] has demonstrated that MZA pairs are as similar in most respects as MZ pairs reared together. Some polygenic traits--e.g. stature, IQ, harm avoidance, negative emotionality, interest in sports--are polygenic-additive, so pairs of relatives resemble one another on the given trait in proportion to their genetic similarity. But the existence and the intensity of other important psychological traits seem to be emergent properties of gene configurations (or configurations of independent and partially genetic traits) that interact multiplicatively rather than additively. Monozygotic (MZ) twins may be strongly correlated on such emergenic traits, while the similarity of dizygotic (DZ) twins, sibs or parent-offspring pairs may be much less than half that of MZ pairs. Some emergenic traits, although strongly genetic, do not appear to run in families. MISTRA has provided at least two examples of traits for which MZA twins are strongly correlated, and DZA pairs correlate near zero, while DZ pairs reared together (DZTs) are about half as similar as MZTs. These findings suggest that even more traits may be emergenic than those already identified. Studies of adoptees reared together (who are perhaps more common than twins reared apart) may help to identify traits that are emergenic, but that also are influenced by a common rearing environment.     

Novel integrative genomics strategies to identify genes for complex traits

Forward genetics is a common approach to dissecting complex traits like common human diseases. The ultimate aim of this approach was the identification of genes that are causal for disease or other phenotypes of interest. However, the forward genetics approach is by definition restricted to the identification of genes that have incurred mutations over the course of evolution or that incurred mutations as a result of chemical mutagenesis, and that as a result lead to disease or to variations in other phenotypes of interest. Genes that harbour no such mutations, but that play key roles in parts of the biological network that lead to disease, are systematically missed by this class of approaches. Recently, a class of novel integrative genomics approaches has been devised to elucidate the complexity of common human diseases by intersecting genotypic, molecular profiling, and clinical data in segregating populations. These novel approaches take a more holistic view of biological systems and leverage the vast network of gene–gene interactions, in combination with DNA variation data, to establish causal relationships among molecular profiling traits and Fbetween molecular profiling and disease (or other classic phenotypes). A number of novel genes for disease phenotypes have been identified as a result of these approaches, highlighting the utility of integrating orthogonal sources of data to get at the underlying causes of disease.     

Integrated Methods to Solve the Biological Basis of Common Diseases

Biological variations influence population variations of many common traits. Identification of the biological basis of many common diseases has been particularly difficult, but new reagents and analytical tools will greatly facilitate this process. The goal of this review is to discuss how to identify the biological basis of common traits by using mouse models. No single method will work for all traits. Understanding complex problems will require broadly based holistic approaches that use a wide array of tools and resources. A multiplicity of developed methods together provide the tools needed to identify the biological basis of any common trait. These tools, whole-genome linkage maps, maps of expressed genes, and statistical methods, deal with the complexities of multiple loci or correlated traits. This review provides some criteria for making choices about the likely productive approaches at each stage in the process of finding genes that influence common traits.     

Detection of genes for ordinal traits in nuclear families and a unified approach for association studies

There is growing interest in genomewide association analysis using single-nucleotide polymorphisms (SNPs), because traditional linkage studies are not as powerful in identifying genes for common, complex diseases. Tests for linkage disequilibrium have been developed for binary and quantitative traits. However, since many human conditions and diseases are measured in an ordinal scale, methods need to be developed to investigate the association of genes and ordinal traits. Thus, in the current report we propose and derive a score test statistic that identifies genes that are associated with ordinal traits when gametic disequilibrium between a marker and trait loci exists. Through simulation, the performance of this new test is examined for both ordinal traits and quantitative traits. The proposed statistic not only accommodates and is more powerful for ordinal traits, but also has similar power to that of existing tests when the trait is quantitative. Therefore, our proposed statistic has the potential to serve as a unified approach to identifying genes that are associated with any trait, regardless of how the trait is measured. We further demonstrated the advantage of our test by revealing a significant association (P = 0.00067) between alcohol dependence and a SNP in the growth-associated protein 43.     

Chinese National Twin Registry as a resource for genetic epidemiologic studies of common and complex diseases in China.

Twins, due to their unique genetic and environmental relationships, have provided crucial insight in our understanding of genetic contributions to numerous etiologically complex disorders in developed countries. As the leading cause of death and adult disability, cardio- and cerebrovascular diseases are common in China, followed by cancer. Obesity and psychological disorders are increasing. The overall goal of this program is to develop a resource for genetic epidemiologic studies of these and other common and complex diseases in China. Our initial focus is to delineate the genetic and environmental determinants of vascular diseases in general, coronary artery disease (CAD) and stroke in particular. To date, we have over 4500 twin pairs registered and about 700 twin pairs studied for various metabolic traits (e.g., lipids, glucose, insulin, etc.). The long-term plan of this program is to (1) establish a population-based twin registry from several selected regions in China for future studies of specific common complex diseases; (2) conduct detailed phenotyping for clinical and intermediate traits related to cardiovascular diseases; (3) expand studies of twins to twin families by including their parents, siblings, and offspring for genetic linkage and association studies; and (4) follow up twins in the registry longitudinally. The goals of the program are health education and promotion of healthy behavior, early identification of cases to provide timely medical attention, and the evaluation of long-term effects of identified risk factors. We want to develop collaborations with investigators who have expertise in cancer, psychological disorders, and other disease areas.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

Anchoring of canine linkage groups with chromosome-specific markers

A high-resolution genetic map with polymorphic markers spaced frequently throughout the genome is a key resource for identifying genes that control specific traits or diseases. The lack of rigorous selection against genetic disorders has resulted in many breeds of dog suffering from a very high frequency of genetic diseases, which tend to be breed-specific and usually inherited as autosomal recessive or apparently complex genetic traits. Many of these closely resemble human genetic disorders in their clinical and pathologic features and are likely to be caused by mutations in homologous genes. To identify loci important in canine disease genes, as well as traits associated with morphological and behavioral variation, we are developing a genetic map of the canine genome. Here we report on an updated version of the canine linkage map, which includes 341 mapped markers distributed over the X and 37 autosomal linkage groups. The average distance between markers on the map is 9.0 cM, and the linkage groups provide estimated coverage of over 95% of the genome. Fourteen linkage groups contain either gene-associated or anonymous markers localized to cosmids that have been assigned to specific canine chromosomes by FISH. These 14 linkage groups contain 150 microsatellite markers and allow us to assign 40% of the linkage groups to specific canine chromosomes. This new version of the map is of sufficient density and characterization to initiate mapping of traits of interest. Received: 23 February 1999 / Accepted: 28 April 1999     

The Danish Twin Registry: 127 birth cohorts of twins.

The Danish Twin Registry is the oldest national twin register in the world, initiated in 1954 by ascertainment of twins born from 1870 to 1910. During a number of studies birth cohorts have been added to the register, and by the recent addition of birth cohorts from 1931 to 1952 the Registry now comprizes 127 birth cohorts of twins from 1870 to 1996, with a total of more than 65,000 twin pairs included. In all cohorts the ascertainment has been population-based and independent of the traits studied, although different procedures of ascertainment have been employed. In the oldest cohorts only twin pairs with both twins surviving to age 6 have been included while from 1931 all ascertained twins are included. The completeness of the ascertainment after adjustment for infant mortality is high, with approximately 90% ascertained up to 1968, and complete ascertainment of all liveborn twin pairs since 1968. The Danish Twin Registry is used as a source for large studies on genetic influence on aging and age-related health problems, normal variation in clinical parameters associated with the metabolic syndrome and cardiovascular diseases, and clinical studies of specific diseases. The combination of survey data with data obtained by linkage to national health related registers enables follow-up studies both of the general twin population and of twins from clinical studies.     

Twins. Novel uses to study complex traits and genetic diseases

The challenge faced by research into the genetic basis of complex disease is to identify genes of small relative effect against a background of substantial genetic and environmental variation. This has focused interest on a classical epidemiological design: the study of twins. Through their precise matching for age, the common family environment and background environmental variation, studying diseases in non-identical twins provides a means to enhance the power of conventional strategies to detect genetic influence through linkage and association. The unique matching of identical twins provides researchers with ways to isolate the function of individual genes involved in disease together with approaches to understanding how genes and the environment interact.     

Human Complex Trait Genetics: Lifting the Lid of the Genomics Toolbox - from Pathways to Prediction

During the initial stages of the genome revolution human genetics was hugely successful in discovering the underlying genes for monogenic diseases. Over 3,000 monogenic diseases have been discovered with simple patterns of inheritance. The unravelling and identification of the genetic variants underlying complex or multifactorial traits, however, is proving much more elusive. There have been over 1,000 significant variants found for many quantitative and binary traits yet they explain very little of the estimated genetic variance or heritability evident from family analysis. There are many hypotheses as to why this might be the case. This apparent lack of information is holding back the clinical application of genetics and shedding doubt on whether more of the same will reveal where the remainder of the variation lies. Here we explore the current state of play, the types of variants we can detect and how they are currently exploited. Finally we look at the future challenges we must face to persuade the human genome to yield its secrets.     

Selection strategies for linkage studies using twins.

Genetic linkage analysis for complex diseases offers a major challenge to geneticists. In these complex diseases multiple genetic loci are responsible for the disease and they may vary in the size of their contribution; the effect of any single one of them is likely to be small. In many situations, like in extensive twin registries, trait values have been recorded for a large number of individuals, and preliminary studies have revealed summary measures for those traits, like mean, variance and components of variance, including heritability. Given the small effect size, a random sample of twins will require a prohibitively large sample size. It is well known that selective sampling is far more efficient in terms of genotyping effort. In this paper we derive easy expressions for the information contributed by sib pairs for the detection of linkage to a quantitative trait locus (QTL). We consider random samples as well as samples of sib pairs selected on the basis of their trait values. These expressions can be rapidly computed and do not involve simulation. We extend our results for quantitative traits to dichotomous traits using the concept of a liability threshold model. We present tables with required sample sizes for height, insulin levels and migraine, three of the traits studied in the GenomEUtwin project.     

X inactivation as a source of behavioural differences in monozygotic female twins.

Although members of monozygotic twin pairs are identical in genome sequence, they may differ in patterns of gene expression. One early and irreversible process affecting gene expression, which can create differences within pairs of female monozygotic twins, is X inactivation - one twin can express mainly paternally-received genes on the X chromosome while the other twin expresses mainly maternally-received genes. It follows that non-identical X chromosome expression may cause female monozygotic twins to correlate less strongly than male monozygotic twins on complex behavioural traits affected by X-linked loci. We tested this hypothesis using data from around 4000 same-sex twin pairs on 9 social, behavioural and cognitive measures at ages 2, 3 and 4. Consistent with our hypothesis, monozygotic males were generally more similar than monozygotic females. Three of four significant differences were in traits showing higher correlations in males than females, and these traits - prosocial behaviour, peer problems, and verbal ability - have all been proposed previously in the literature as being influenced by genes on the X chromosome. Interestingly, dizygotic twins showed the reverse pattern of correlations for similar variables, which is also consistent with the X inactivation hypothesis; taken together, then, our monozygotic and dizygotic results suggest the presence of quantitative trait loci on the X chromosome.     

Dissecting cause and effect in the pathogenesis of psychiatric disorders: genes, environment and behaviour

It has long been established that the development of psychiatric illness results from a complex interplay between genetic and environmental factors. Postmortem and genetic linkage studies have identified a number of promising candidate genes which have been reinforced by replication and functional studies. However, the fact that concordance rates for monozygotic twins rarely approach 100% highlights the involvement of environmental factors. Whilst epidemiological studies of psychiatric cohorts have demonstrated potential risk factors, such studies are clearly limited and in many cases the potential mechanism linking a given risk factor with pathogenesis remains unclear. A very powerful method of elucidating the mechanisms underlying gene-environment interactions is the use of appropriate animal models of psychiatric pathology. Whilst animals cannot be used to map the entire complexity of diseases such as schizophrenia, dissecting the symptom profile into more simply encapsulated traits or endophenotypes has proved to be a successful approach. Such endophenotypes provide a measurable link between aetiological factors and phenotypic outcome. Given the potential for the careful control and modification of an experimental animal's environment, the combination of studies of candidate genes with investigations of environmental factors is an effective heuristic tool, allowing examination of behavioural endophenotypes in conjunction with cellular and molecular outcomes. This review will consider the extant genetic, molecular, pharmacological and lesion-based models of psychiatric disorders, and the relevant methods of environmental manipulation appearing in the literature. We will discuss studies where such models have been combined, and the potential for future experimentation in this area.     

Rare variants regulate expression of nearby individual genes in multiple tissues

The rapid decrease in sequencing cost has enabled genetic studies to discover rare variants associated with complex diseases and traits. Once this association is identified, the next step is to understand the genetic mechanism of rare variants on how the variants influence diseases. Similar to the hypothesis of common variants, rare variants may affect diseases by regulating gene expression, and recently, several studies have identified the effects of rare variants on gene expression using heritability and expression outlier analyses. However, identifying individual genes whose expression is regulated by rare variants has been challenging due to the relatively small sample size of expression quantitative trait loci studies and statistical approaches not optimized to detect the effects of rare variants. In this study, we analyze whole-genome sequencing and RNA-seq data of 681 European individuals collected for the Genotype-Tissue Expression (GTEx) project (v8) to identify individual genes in 49 human tissues whose expression is regulated by rare variants. To improve statistical power, we develop an approach based on a likelihood ratio test that combines effects of multiple rare variants in a nonlinear manner and has higher power than previous approaches. Using GTEx data, we identify many genes regulated by rare variants, and some of them are only regulated by rare variants and not by common variants. We also find that genes regulated by rare variants are enriched for expression outliers and disease-causing genes. These results suggest the regulatory effects of rare variants, which would be important in interpreting associations of rare variants with complex traits.     

Identification of genetic markers associated with fatness and leg weakness traits in the pig

Pigs have undergone long-term selection in commercial conditions for improved rate and efficiency of lean gain. Interestingly, it has been observed in both experimental and field conditions that leg weakness has increased over time, concurrent with the selection for improved rate of lean gain, while fatter animals tend to have better leg action, and foot and leg (FL) structure. The exact molecular mechanisms or individual genes responsible for this apparent genetic correlation between fatness and leg weakness and other physical adaptability traits have been less well reported. Based on our recent studies involving candidate genes and leg weakness traits, the present investigation has identified 30 SNPs from 26 genes that were found to be associated with 10th rib backfat in a sow population consisting of 2066 animals. The specific alleles associated with increased backfat tended to be associated with better overall leg action, as shown for the genes including MTHFR, WNT2, APOE, BMP8, GNRHR and OXTR , while inconsistent associations with the single FL structure trait and backfat were observed for other genes. This study suggests that in some cases there may be a common genetic mechanism or linked genes regulating fatness and leg weakness. Such relationships are clearly complex, and the utilization of genetic markers associated with both traits should be treated cautiously.     

A twin approach to unraveling epigenetics

The regulation of gene expression plays a pivotal role in complex phenotypes, and epigenetic mechanisms such as DNA methylation are essential to this process. The availability of next-generation sequencing technologies allows us to study epigenetic variation at an unprecedented level of resolution. Even so, our understanding of the underlying sources of epigenetic variability remains limited. Twin studies have played an essential role in estimating phenotypic heritability, and these now offer an opportunity to study epigenetic variation as a dynamic quantitative trait. High monozygotic twin discordance rates for common diseases suggest that unexplained environmental or epigenetic factors could be involved. Recent genome-wide epigenetic studies in disease-discordant monozygotic twins emphasize the power of this design to successfully identify epigenetic changes associated with complex traits. We describe how large-scale epigenetic studies of twins can improve our understanding of how genetic, environmental and stochastic factors impact upon epigenetics, and how such studies can provide a comprehensive understanding of how epigenetic variation affects complex traits.