人类身高的遗传学研究进展

人类身高是由环境和遗传因素共同决定的,遗传学研究发现遗传因素对身高差异的影响更大。身高是典型的多基因遗传性状,科研人员试图运用传统的连锁分析和关联分析寻找和发现对人类身高具有显著影响的常见DNA序列变异,但进展缓慢。近年来,随着基因分型和DNA测序技术的发展,人类身高的遗传学研究取得了很多突破性进展。全基因组关联分析(GWAS)的应用,发现和证实了上百个与人类身高相关的单核苷酸多态性位点(SNPs),拓展了人们对人类生长和发育的相关遗传学认识,同时也为研究人类其他复杂性状提供了理论依据和借鉴。本文综述了人类身高的遗传学研究进展,探讨了目前该研究领域所存在的问题和未来发展方向,以期为今后人类身高相关的遗传学研究提供参考和借鉴。     

Transmission of human craniofacial dimensions

The transmissibilities of 11 human craniofacial dimensions are estimated by path analysis based upon familial correlations obtained in four different populations. Estimates from both the individual populations and from pooled correlations indicate that the observed variation in craniofacial dimensions is determined by genetic and nongenetic factors in roughly equal measure (.45 less than t 2 less than .60). These results implicate the possibility of complex gene-environment and gene-gene interactions in the development of the size and shape of the head and face and call for more detailed familial studies of these traits. This additional complexity further suggests the need for caution in interpreting such metrical variation, especially from a diagnostic or classificatory viewpoint.     

The epigenetics of CHARGE syndrome

In biology, we continue to appreciate the fact that the DNA sequence alone falls short when attempting to explain the intricate inheritance patterns for complex traits. This is particularly true for human disorders that appear to have simple genetic causes. The study of epigenetics, and the increased access to the epigenetic profiles of different tissues has begun to shed light on the genetic complexity of many basic biological processes, both physiological and pathological. Epigenetics refers to heritable changes in gene expression that are not due to alterations in the DNA sequence. Various mechanisms of epigenetic regulation exist, including DNA methylation and histone modification. The identification, and increased understanding of key players and mechanisms of epigenetic regulation have begun to provide significant insight into the underlying origins of various human genetic disorders. One such disorder is CHARGE syndrome (OMIM #214800), which is a leading cause of deaf-blindness worldwide. A majority of CHARGE syndrome cases are caused by haploinsufficiency for the CHD7 gene, which encodes an ATP-dependent chromatin remodeling protein involved in the epigenetic regulation of gene expression. The CHD7 protein has been highly conserved throughout evolution, and research into the function of CHD7 homologs in multiple model systems has increased our understanding of this family of proteins, and epigenetic mechanisms in general. Here we provide a review of CHARGE syndrome, and discuss the epigenetic functions of CHD7 in humans and CHD7 homologs in model organisms.     

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。     

全基因组关联分析的进展与反思

全基因组关联分析(genomewide association study,GWAS)是应用人类基因组中数以百万计的单核苷酸多态性(single nucleotide polymorphism,SNP)为标记进行病例-对照关联分析,以期发现影响复杂性疾病发生的遗传特征的一种新策略。近年来,随着人类基因组计划和基因组单倍体图谱计划的实施,人们已通过GWAS方法发现并鉴定了大量与人类性状或复杂性疾病关联的遗传变异,为进一步了解控制人类复杂性疾病发生的遗传特征提供了重要的线索。然而,由于造成复杂性疾病/性状的因素较多,而且GWAS研究系统较为复杂,因此目前GWAS本身亦存在诸多的问题。本文将从研究方式、研究对象、遗传标记,以及统计分析等方面,探讨GWAS的研究现状以及存在的潜在问题,并展望GWAS今后的发展方向。     

Mapping quantitative trait loci associated with root penetration ability of wheat in contrasting environments

The aim of this research was to investigate the genetic basis for variation in root penetration ability and associated traits in the mapping population derived from the Australian bread wheat cultivars Halberd and Cranbrook in soil columns containing wax layers grown in controlled conditions and to compare this with performance in the field. Root and shoot traits of the doubled haploid line (DHL) from a cross of Halberd and Cranbrook were evaluated in soil columns containing wax layers. Contrasting DHLs that varied in the ability to penetrate a wax layer in soil columns were then evaluated for maximum root depth in the field on contrasting soils at Merredin, Western Australia. Genetic control was complex, and numerous quantitative trait loci (QTL) (53 in total) were located across most chromosomes that had a small genetic effect (LOD scores of 3.2–9.1). Of these QTL, 29 were associated with root traits, 37 % of which were contributed positively by the Halberd with key traits being located on chromosomes 2D, 4A, 6B, and 7B. Variation in root traits of DHL in soil columns was linked with field performance. Despite the complexity of the traits and a large number of small QTL, the results can be potentially used to explore allelic diversity in root traits for hardpan penetration.     

Integrating QTL and high-density SNP analyses in mice to identify Insig2 as a susceptibility gene for plasma cholesterol levels

The use of inbred strains of mice to dissect the genetic complexity of common diseases offers a viable alternative to human studies, given the control over experimental parameters that can be exercised. Central to efforts to map susceptibility loci for common diseases in mice is a comprehensive map of DNA variation among the common inbred strains of mice. Here we present one of the most comprehensive high-density, single nucleotide polymorphism (SNP) maps of mice constructed to date. This map consists of 10,350 SNPs genotyped in 62 strains of inbred mice. We demonstrate the utility of these data via a novel integrative genomics approach to mapping susceptibility loci for complex traits. By integrating in silico quantitative trait locus (QTL) mapping with progressive QTL mapping strategies in segregating mouse populations that leverage large-scale mapping of the genetic determinants of gene expression traits, we not only facilitate identification of candidate quantitative trait genes, but also protect against spurious associations that can arise in genetic association studies due to allelic association among unlinked markers. Application of this approach to our high-density SNP map and two previously described F2 crosses between strains C57BL/6J (B6) and DBA/2J and between B6 ApoE(-/-) and C3H/HeJ ApoE(-/-) results in the identification of Insig2 as a strong candidate susceptibility gene for total plasma cholesterol levels.     

New molecular tools to improve the efficiency of breeding for increased drought resistance

The advent of molecular markers (particularly RFLP- and PCR-derived) for use as probes for genomic DNA has revolutionized the genetic analysis of crop plants and provided not only geneticists, but also physiologists, agronomists and breeders with valuable new tools to identify traits of importance in improving resistance to abiotic stresses. For the breeder, a genetic map saturated with molecular markers allows selection for certain characters to be carried out much more efficiently and effectively than was possible previously. Two areas of molecular marker technology that are proving particularly useful in identifying traits of value for stress resistance and introducing them into improved varieties are in situ hybridization with fluorescent-labelled molecular probes and quantitative trait locus (QTL) analysis with either radioactively- or cold-labelled probes. Fluorescence in situ hybridization (FISH) takes out much of the cytological tedium previously associated with monitoring the introgression of chromosomes and DNA fragments from one species to another. Labelled DNA can be prepared that is specific to a particular species and used to visualize in chromosome preparations the presence of chromosomes or chromosomal fragments from that species amongst the recipient's chromosomes. This is being used to help transfer genes for drought resistance and salt tolerance from alien species into Graminaceous crops. DNA probes showing polymorphism between the donor and recipient species can also be used to monitor the incorporation of alien genes from chromosome addition lines into the recipient species. High density molecular maps allow the location of all major genes regulating the expression of a particular trait to be determined. Statistical methods have been developed to allow QTL for the trait to be identified. Not only does this allow the complexity of genetic control of any trait to be determined, but by comparing the extent to which confidence intervals of QTL for different traits overlap it is possible to examine the likelihood that traits are pleiotropically linked. Thus, the traits most likely to be important in determining yield under droughted conditions can be identified. Examples are given of traits that could be incorporated into breeding programmes to improve drought resistance using techniques of marker-assisted selection.     

猪的基因图谱及数量性状位点定位

在人类基因组计划的带动下,猪的遗传连锁图谱和细胞遗传学图谱有了较大的进步,利用目前猪基因组图谱的研究成果,通过基因组扫描法和候选基因法,可以对猪重要经济性状的主效基因位点进行区域定位,进而图位克隆,找到主效基因,为现代遗传育种奠定理论基础。     

An update on molecular genetic studies of human personality traits

Personality is a complex phenotype and people differ considerably when they are evaluated by self-report questionnaires. There is convincing evidence from twin studies that basic personality dimensions in men and women have a considerable genetic component. However, only recently have common genetic polymorphisms been associated with particular personality traits, especially the dopamine D4 receptor with novelty seeking and the serotonin transporter with anxiety-related traits or neuroticism. The current review examines progress in the past few years in molecular personality genetics and focuses on the reasons for difficulties in replicating first findings as well as the prospects for future studies in this area. The molecular genetic structure of human personality is worth studying both for its intrinsic interest in helping us to understand individual differences in human behaviour and the light it will shed on more complex behavioural disorders that are likely to partially share some common genetic variants.     

MAINTENANCE OF GENETIC VARIATION IN HUMAN PERSONALITY: TESTING EVOLUTIONARY MODELS BY ESTIMATING HERITABILITY DUE TO COMMON CAUSAL VARIANTS AND INVESTIGATING THE EFFECT OF DISTANT INBREEDING

Personality traits are basic dimensions of behavioral variation, and twin, family, and adoption studies show that around 30% of the between‐individual variation is due to genetic variation. There is rapidly growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome‐wide single nucleotide polymorphism (SNP) data from > 8000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation–selection balance.     

Rapid generation of plant traits via regulation of DNA mismatch repair

The reversible inhibition of DNA repair is a novel approach to maximize genetic diversity within a plant's genome in order to generate offspring exhibiting important de novo output traits. This process is based on the inhibition of the evolutionarily conserved mismatch repair (MMR) system. In this process, a human dominant negative MMR gene allele is introduced into the germline of a target plant, yielding progeny that can be screened to identify variants with commercially important agronomic output traits. Using this novel strategy, we generated MMR-deficient Arabidopsis thaliana plants that showed genome-wide instability of nucleotide repeats associated with chromosomal microsatellites, in addition to base substitution mutations. Functional screenings of the MMR-deficient Arabidopsis offspring identified variants expressing selectable traits (ethylene insensitivity and salt tolerance), as well as plants exhibiting altered morphologic traits (albinos and dwarfs). We determined by segregation analyses of variant plants that the de novo phenotypes were due to both recessive and dominant genetic mutations. Mutations caused by MMR deficiency showed a different spectrum compared with those derived using ethylmethane sulphonate (EMS) mutagenesis. Our finding demonstrates the feasibility of using reversible MMR deficiency via transient expression of a single human gene product to enhance genetic diversity in plants.     

Determining the effective dimensionality of the genetic variance-covariance matrix

Determining the dimensionality of G provides an important perspective on the genetic basis of a multivariate suite of traits. Since the introduction of Fisher's geometric model, the number of genetically independent traits underlying a set of functionally related phenotypic traits has been recognized as an important factor influencing the response to selection. Here, we show how the effective dimensionality of G can be established, using a method for the determination of the dimensionality of the effect space from a multivariate general linear model introduced by Amemiya (1985). We compare this approach with two other available methods, factor-analytic modeling and bootstrapping, using a half-sib experiment that estimated G for eight cuticular hydrocarbons of Drosophila serrata. In our example, eight pheromone traits were shown to be adequately represented by only two underlying genetic dimensions by Amemiya's approach and factor-analytic modeling of the covariance structure at the sire level. In contrast, bootstrapping identified four dimensions with significant genetic variance. A simulation study indicated that while the performance of Amemiya's method was more sensitive to power constraints, it performed as well or better than factor-analytic modeling in correctly identifying the original genetic dimensions at moderate to high levels of heritability. The bootstrap approach consistently overestimated the number of dimensions in all cases and performed less well than Amemiya's method at subspace recovery.     

Optimising the identification of causal variants across varying genetic architectures in crops

Association studies use statistical links between genetic markers and the phenotype variation across many individuals to identify genes controlling variation in the target phenotype. However, this approach, particularly conducted on a genome‐wide scale (GWAS), has limited power to identify the genes responsible for variation in traits controlled by complex genetic architectures. In this study, we employ real‐world genotype datasets from four crop species with distinct minor allele frequency distributions, population structures and linkage disequilibrium patterns. We demonstrate that different GWAS statistical approaches provide favourable trade‐offs between power and accuracy for traits controlled by different types of genetic architectures. FarmCPU provides the most favourable outcomes for moderately complex traits while a Bayesian approach adopted from genomic prediction provides the most favourable outcomes for extremely complex traits. We assert that by estimating the complexity of genetic architectures for target traits and selecting an appropriate statistical approach for the degree of complexity detected, researchers can substantially improve the ability to dissect the genetic factors controlling complex traits such as flowering time, plant height and yield component.     

Nature vs nurture: are leaders born or made? A behavior genetic investigation of leadership style.

With the recent resurgence in popularity of trait theories of leadership, it is timely to consider the genetic determination of the multiple factors comprising the leadership construct. Individual differences in personality traits have been found to be moderately to highly heritable, and so it follows that if there are reliable personality trait differences between leaders and non-leaders, then there may be a heritable component to these individual differences. Despite this connection between leadership and personality traits, however, there are no studies of the genetic basis of leadership using modern behavior genetic methodology. The present study proposes to address the lack of research in this area by examining the heritability of leadership style, as measured by self-report psychometric inventories. The Multifactor Leadership Questionnaire (MLQ), the Leadership Ability Evaluation, and the Adjective Checklist were completed by 247 adult twin pairs (183 monozygotic and 64 same-sex dizygotic). Results indicated that most of the leadership dimensions examined in this study are heritable, as are two higher level factors (resembling transactional and transformational leadership) derived from an obliquely rotated principal components factors analysis of the MLQ. Univariate analyses suggested that 48% of the variance in transactional leadership may be explained by additive heritability, and 59% of the variance in transformational leadership may be explained by non-additive (dominance) heritability. Multivariate analyses indicated that most of the variables studied shared substantial genetic covariance, suggesting a large overlap in the underlying genes responsible for the leadership dimensions.     

草莓DNA分子标记及其应用

综述了限制性长度多态性(RFLP)、随机扩增多态性DNA(RAPD)、扩增片段长度多态性(AFLP)、简单重复序列(SSR)等不同类型分子标记在草莓指纹图谱构建、品种鉴别、遗传多样性、进化、遗传作图以及相关性状的标记等方面的应用,分析了草莓分子标记研究中的关键问题,提出了今后研究方向。     

The phenotypic and genetic covariance structure of drosphilid wings

Evolutionary constraint results from the interaction between the distribution of available genetic variation and the position of selective optima. The availability of genetic variance in multitrait systems, as described by the additive genetic variance-covariance matrix (G), has been the subject of recent attempts to assess the prevalence of genetic constraints. However, evolutionary constraints have not yet been considered from the perspective of the phenotypes available to multivariate selection, and whether genetic variance is present in all phenotypes potentially under selection. Determining the rank of the phenotypic variance-covariance matrix (P) to characterize the phenotypes available to selection, and contrasting it with the rank of G, may provide a general approach to determining the prevalence of genetic constraints. In a study of a laboratory population of Drosophila bunnanda from northern Australia we applied factor-analytic modeling to repeated measures of individual wing phenotypes to determine the dimensionality of the phenotypic space described by P. The phenotypic space spanned by the 10 wing traits had 10 statistically supported dimensions. In contrast, factor-analytic modeling of G estimated for the same 10 traits from a paternal half-sibling breeding design suggested G had fewer dimensions than traits. Statistical support was found for only five and two genetic dimensions, describing a total of 99% and 72% of genetic variance in wing morphology in females and males, respectively. The observed mismatch in dimensionality between P and G suggests that although selection might act to shift the intragenerational population mean toward any trait combination, evolution may be restricted to fewer dimensions.     

Genetic basis of drought resistance at reproductive stage in rice: separation of drought tolerance from drought avoidance

Drought tolerance (DT) and drought avoidance (DA) are two major mechanisms in drought resistance of higher plants. In this study, the genetic bases of DT and DA at reproductive stage in rice were analyzed using a recombinant inbred line population from a cross between an indica lowland and a tropical japonica upland cultivar. The plants were grown individually in PVC pipes and two cycles of drought stress were applied to individual plants with unstressed plants as the control. A total of 21 traits measuring fitness, yield, and the root system were investigated. Little correlation of relative yield traits with potential yield, plant size, and root traits was detected, suggesting that DT and DA were well separated in the experiment. A genetic linkage map consisting of 245 SSR markers was constructed for mapping QTL for these traits. A total of 27 QTL were resolved for 7 traits of relative performance of fitness and yield, 36 QTL for 5 root traits under control, and 38 for 7 root traits under drought stress conditions, suggesting the complexity of the genetic bases of both DT and DA. Only a small portion of QTL for fitness- and yield-related traits overlapped with QTL for root traits, indicating that DT and DA had distinct genetic bases.     

Genetic dissection of the syndrome X in the rat

In 1988, Reaven used the term syndrome X to describe a relation between several disorders including hypertension, dyslipidemia, impaired glucose tolerance, obesity, and coronary heart disease. Despite a number of studies dealing with syndrome X, its genetic basis remains poorly understood. Regarding the complexity of this syndrome, it is important to use animal models developing the traits of the disease. Here we show a genetic dissection of syndrome X in the WOKW rat, an animal model of genetically determined syndrome X. We found a major quantitative trait locus (QTL) for glucose metabolism on chromosome 3 and further QTLs influencing obesity and body weight on chromosomes 1 and 5. Genetic determinants of dyslipidemia were mapped to chromosomes 4 and 17. In addition, suggestive linkage for serum insulin was found on chromosome 1 to the region previously shown to be associated with type-1 diabetes mellitus. This is the first study demonstrating independent genetic factors influencing traits of the syndrome X in the rat as well as a possible genetic relationships between syndrome X and diabetes mellitus. Moreover, regarding the close similarities between WOKW rat and human syndrome X, the study could help in a search of genetic factors involved in this complex metabolic disorder in human.     

Apportionment of global human genetic diversity based on craniometrics and skin color

A number of analyses of classical genetic markers and DNA polymorphisms have shown that the majority of human genetic diversity exists within local populations (approximately 85%), with much less among local populations (approximately 5%) or between major geographic regions or "races" (approximately 10%). Previous analysis of craniometric variation (Relethford [1994] Am J Phys Anthropol 95:53-62) found that between 11-14% of global diversity exists among geographic regions, with the remaining diversity existing within regions. The methods used in this earlier paper are extended to a hierarchical partitioning of genetic diversity in quantitative traits, allowing for assessment of diversity among regions, among local populations within regions, and within local populations. These methods are applied to global data on craniometric variation (57 traits) and skin color. Multivariate analysis of craniometric variation shows results similar to those obtained from genetic markers and DNA polymorphisms: roughly 13% of the total diversity is among regions, 6% among local populations within regions, and 81% within local populations. This distribution is concordant with neutral genetic markers. Skin color shows the opposite pattern, with 88% of total variation among regions, 3% among local populations within regions, and 9% within local populations, a pattern shaped by natural selection. The apportionment of genetic diversity in skin color is atypical, and cannot be used for purposes of classification. If racial groups are based on skin color, it appears unlikely that other genetic and quantitative traits will show the same patterns of variation.