Epistasis plays an important role as genetic basis of heterosis in rice

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利用DH或RIL群体检测QTL体系并估计其遗传效应

利用ＤＨ和ＲＩＫＬ群体并结合重复内分组随机区组设计对和物产量等遗传率较低的数量性状进行分离分析可提高遗传分析的精度。根据混合分布理论菜了利用ＤＨ或ＲＩＬ群体重复实验数据鉴定数量性状混合遗传模型的分离分析法,特别是２对链锁主基因＋多基因模型。该方法可鉴定数量性状的遗传模型和主基因的作用方式,估计主基因、多基因的遗传疚和遗传方差,在两主基因存在连锁可可估计其重组率。下面通过应用举例说明该方法。     

A bivariate quantitative genetic model for a threshold trait and a survival trait

Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.     

Quantitative trait loci affecting delta13C and response to differential water availibility in Arabidopsis thaliana

Phenotypic plasticity is an important response mechanism of plants to environmental heterogeneity. Here, we explored the genetic basis of plastic responses of Arabidopsis thaliana to water deficit by experimentally mapping quantitative trait loci (QTL) in two recombinant inbred populations (Cvi x Ler and Ler x Col). We detected genetic variation and significant genotype-by-environment interactions for many traits related to water use. We also mapped 26 QTL, including six for carbon isotope composition (delta13C). Negative genetic correlations between fruit length and fruit production as well as between flowering time and branch production were corroborated by QTL colocalization, suggesting these correlations are due to pleiotropy or physical linkage. Water-limited plants were more apically dominant with greater root:shoot ratios and higher delta13C (higher water-use efficiency) when compared to well-watered plants. Many of the QTL effects for these traits interacted significantly with the irrigation treatment, suggesting that the observed phenotypic plasticity is genetically based. We specifically searched for epistatic (QTL-QTL) interactions using a two-dimensional genome scan, which allowed us to detect epistasis regardless of additive genetic effects. We found several significant QTL-QTL interactions including three that exhibited environmental dependence. These results provide preliminary evidence for proposed genetic mechanisms underlying phenotypic plasticity.     

质量—数量性状遗传参数估计的P1,P2,F1,B1,B2联合分析方法

提出利用亲本Ｐ_１和Ｐ_２、杂种Ｆ_１、回交Ｂ_１和Ｂ_１五个世代联合分析包括两个位点主基因控制的质量－数量性状遗传的统计方法,共建立了可供选择的微基因遗传、一对主基因＋微基因混合遗传、二对主基因＋微基因混合遗传三类五种（套）共 ２８个遗传模型,采用 ＡＩＣ信息准则选择最适模型,并通过适合性检验对所选择的遗传模型做进一步的检验．文章最后还讨论了两种变型设计．     

A G matrix analogue to capture the cumulative effects of nongenetic inheritance

The genetic variance‐covariance ( G ) matrix describes the variances and covariances of genetic traits under strict genetic inheritance. Genetically expressed traits often influence trait expression in another via nongenetic forms of transmission and inheritance, however. The importance of non‐genetic influences on phenotypic evolution is increasingly clear, but how genetic and nongenetic inheritance interact to determine the response to selection is not well understood. Here, we use the ‘reachability matrix’ – a key analytical tool of geometric control theory – to integrate both forms of inheritance, capturing how the consequences of generation‐lagged maternal effects accumulate. Building on the classic Lande and Kirkpatrick model that showed how nongenetic (maternal) inheritance fundamentally alters the expected path of phenotypic evolution, we make novel inferences through decomposition of the reachability matrix. In particular, we quantify how nongenetic inheritance affects the distribution (orientation and shape) of ellipses of phenotypic change and how these distributions influence subsequent evolution. This interweaving of phenotypic means and variances accumulates generation by generation and is described analytically by the reachability matrix, which acts as an analogue of G when genetic and nongenetic inheritance both act.     

Quantitative Trait Loci Identification by Estimating the Genetic Model based on the Extremal Samples

Background In genetic association studies with quantitative trait loci (QTL), the association between a candidate genetic marker and the trait of interest is commonly examined by the omnibus F test or by the t-test corresponding to a given genetic model or mode of inheritance. It is known that the t-test with a correct model specification is more powerful than the F test. However, since the underlying genetic model is rarely known in practice, the use of a model-specific t-test may incur substantial power loss. Robust-efficient tests, such as the Maximin Efficiency Robust Test (MERT) and MAX3 have been proposed in the literature.Methods In this paper, we propose a novel two-step robust-efficient approach, namely, the genetic model selection (GMS) method for quantitative trait analysis. GMS selects a genetic model by testing Hardy-Weinberg disequilibrium (HWD) with extremal samples of the population in the first step and then applies the corresponding genetic model-specific t-test in the second step.Results Simulations show that GMS is not only more efficient than MERT and MAX3, but also has comparable power to the optimal t-test when the genetic model is known.Conclusion Application to the data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort demonstrates that the proposed approach can identify meaningful biological SNPs on chromosome 19.     

Selected aspects of transgenerational epigenetic inheritance and resetting in plants

Transgenerational epigenetic inheritance (TEI), which is the inheritance of expression states and thus traits that are not determined by the DNA sequence, is often postulated but the molecular mechanisms involved are only rarely verified. This especially applies to the heritability of environmentally induced traits, which have gained interest over the last years. Here we will discuss selected examples of epigenetic inheritance in plants and artificially divide them according to the occurrence of inter-generational resetting. The decision which epigenetic marks are reset and which ones are not is crucial for the understanding of TEI. We will consider examples of epialleles found in natural populations and epialleles induced by genetic and/or environmental factors used in experimental setups.     

Multiple pathways influence mitochondrial inheritance in budding yeast

Yeast mitochondria form a branched tubular network. Mitochondrial inheritance is tightly coupled with bud emergence, ensuring that daughter cells receive mitochondria from mother cells during division. Proteins reported to influence mitochondrial inheritance include the mitochondrial rho (Miro) GTPase Gem1p, Mmr1p, and Ypt11p. A synthetic genetic array (SGA) screen revealed interactions between gem1Delta and deletions of genes that affect mitochondrial function or inheritance, including mmr1Delta. Synthetic sickness of gem1Delta mmr1Delta double mutants correlated with defective mitochondrial inheritance by large buds. Additional studies demonstrated that GEM1, MMR1, and YPT11 each contribute to mitochondrial inheritance. Mitochondrial accumulation in buds caused by overexpression of either Mmr1p or Ypt11p did not depend on Gem1p, indicating these three proteins function independently. Physical linkage of mitochondria with the endoplasmic reticulum (ER) has led to speculation that distribution of these two organelles is coordinated. We show that yeast mitochondrial inheritance is not required for inheritance or spreading of cortical ER in the bud. Moreover, Ypt11p overexpression, but not Mmr1p overexpression, caused ER accumulation in the bud, revealing a potential role for Ypt11p in ER distribution. This study demonstrates that multiple pathways influence mitochondrial inheritance in yeast and that Miro GTPases have conserved roles in mitochondrial distribution.     

ENVIRONMENTAL AND GENETIC CONTROL OF BRAIN AND SONG STRUCTURE IN THE ZEBRA FINCH

Birdsong is a classic example of a learned trait with cultural inheritance, with selection acting on trait expression. To understand how song responds to selection, it is vital to determine the extent to which variation in song learning and neuroanatomy is attributable to genetic variation, environmental conditions, or their interactions. Using a partial cross fostering design with an experimental stressor, we quantified the heritability of song structure and key brain nuclei in the song control system of the zebra finch and the genotype‐by‐environment (G × E) interactions. Neuroanatomy and song structure both showed low levels of heritability and are unlikely to be under selection as indicators of genetic quality. HVC, in particular, was almost entirely under environmental control. G × E interaction was important for brain development and may provide a mechanism by which additive genetic variation is maintained, which in turn may promote sexual selection through female choice. Our study suggests that selection may act on the genes determining vocal learning, rather than directly on the underlying neuroanatomy, and emphasizes the fundamental importance of environmental conditions for vocal learning and neural development in songbirds.     

Morphological traits defining species differences in wild relatives of maize are controlled by multiple quantitative trait loci

We analyzed the genetic basis of morphological differences between two wild species of teosinte (Zea diploperennis and Z. mays ssp. parviglumis), which are relatives of maize. These two species differ in a number of taxonomically important traits including the structure of the tassel (male inflorescence), which is the focus of this report. To investigate the genetic inheritance of six tassel traits, quantitative trait locus (QTL) mapping with 95 RFLP markers was employed on a population of 425 F2 plants. Each trait was analyzed by interval mapping (IM) and composite interval mapping (CIM) to identify and characterize the QTL controlling the differences in tassel morphology. We detected two to eight QTL for each trait. In total, 30 QTL with IM and 33 QTL with CIM were found for tassel morphology. QTL for several of the traits mapped near each other, suggesting pleiotropy and/or linkage of QTL. The QTL showed small to moderate magnitudes of effect. No QTL of exceptionally large effect were found as seen under domestication and in the case of some other natural species. Thus, the model involving major QTL of large effect seems not to apply to the traits and species analyzed. A mixture of QTL with positive and negative allelic effects was found for most tassel traits and may suggest a history of periodic changes in the direction of selection during the divergence of Z. diploperennis and Z. mays ssp. parviglumis or fixation of QTL alleles by random genetic drift rather than selection.     

Testing genetic models in populations which contain pedigree errors

In a genetic analysis of a polymorphic system, differences between the observed type of an individual and that expected from the parental types can arise either from an incorrect model or from pedigree errors. Such pedigree errors can cause severe difficulties in studies of the mode of inheritance of a novel polymorphic system. A method is proposed which overcomes the problem by including sire and dam error rates explicitly in the genetic model. The error rates are estimated by maximum likelihood, and likelihood ratio tests used to compare different models or estimates from different data sets. The proposals are applied to a study of the inheritance of the bovine serum AmI amylases.     

质量性状和数量性状含义的辨析

植物或动物的性状一般分为质量性状和数量性状,而实际上,许多性状并不是绝对的质量性状或数量性状,而是同时受到一个或少数几个主基因和或数量性状多基因的控制.因此,在遗传学教学中,有必要对此类性状进行分析.为加深学生对此类性状的遗传及这两个概念的理解,通过性状次数分布图分析,结合最新的遗传学研究成果,对之进行了分析和讨论.     

Methodologies for segregation analysis and QTL mapping in plants

Most characters of biological interest and economic importance are quantitative traits. To uncover the genetic architecture of quantitative traits, two approaches have become popular in China. One is the establishment of an analytical model for mixed major-gene plus polygenes inheritance and the other the discovery of quantitative trait locus (QTL). Here we review our progress employing these two approaches. First, we proposed joint segregation analysis of multiple generations for mixed major-gene plus polygenes inheritance. Second, we extended the multilocus method of Lander and Green (1987), Jiang and Zeng (1997) to a more generalized approach. Our methodology handles distorted, dominant and missing markers, including the effect of linked segregation distortion loci on the estimation of map distance. Finally, we developed several QTL mapping methods. In the Bayesian shrinkage estimation (BSE) method, we suggested a method to test the significance of QTL effects and studied the effect of the prior distribution of the variance of QTL effect on QTL mapping. To reduce running time, a penalized maximum likelihood method was adopted. To mine novel genes in crop inbred lines generated in the course of normal crop breeding work, three methods were introduced. If a well-documented genealogical history of the lines is available, two-stage variance component analysis and multi-QTL Haseman-Elston regression were suggested; if unavailable, multiple loci in silico mapping was proposed.     

Niche and area of distribution modeling: a population ecology perspective

Statistical modeling of areas of distribution of species by correlative analysis of the environmental features of known presences has become widespread. However, to a large degree, the logic and the functioning of many of these applications remain obscure, not only due to the fact that some of the modeling methods are intrinsically complex (neural networks, genetic algorithms, generalized additive models, for example), but mainly because the role of other ecological processes affecting the species distributions sometimes is not explicitly stated. Resorting to fundamental principles of population ecology, a scheme of analysis based on separation of three factors affecting species distributions (environment, biotic interactions and movements) is used to clarify some results of niche modeling exercises. The area of distribution of a virtual species which was generated by both environmental and biotic factors serves to illustrate the possibility that, at coarse resolutions, the distribution can be approximately recovered using only information about the environmental factors and ignoring the biotic interactions. Finally, information on the distribution of a butterfly species, Baronia brevicornis , is used to illustrate the importance of interpreting the results of niche models by including hypothesis about one class of movements. The results clarify the roles of the three factors in interpreting the results of using correlative approaches to modeling species distributions or their niches.     

Distribution of lod scores under uncertain mode of inheritance.

We consider probability distributions of alternative lod statistics, differing in their treatment of segregation parameters when mode of inheritance is uncertain. A particular pedigree structure and a dominant genetic system displaying incomplete penetrance are analyzed. Lod scores calculated assuming an incorrect segregation model appear to conform quite well to the chi 2 distribution in the absence of linkage. In the presence of linkage, some power is lost. However, if lod scores are calculated under several different segregation models and the best one is accepted, opportunity for chance occurrence of high lod scores is enhanced. The distribution is still chi 2, but with extra degrees of freedom. These results hold over a wide range of sample sizes and segregation models, including small samples and low levels of penetrance.     

The significance of mitochondria for embryo development in cloned farm animals

The role of mitochondria in remodeling of the donor cell nucleus in cloned animals has gained increased attention, as mitochondria interact in direct or indirect ways with the donor cell nuclear DNA. Mitochondria comprise 1% of the genetic material that is contributed to the developing embryo by the recipient oocyte and provide the energy that is required for embryo development. In this review we compare mitochondria distribution in various species and the importance of mitochondria distribution for embryo development. We also compare the inheritance pattern of mitochondria in cloned embryos that remains unresolved, as the donor cell nucleus is typically transferred with surrounding cytoplasm including mitochondria which become destroyed in some but not all species. We review the role of mitochondria in cloned farm animals with emphasis on nucleo-cytoplasmic interactions and consequences for embryo development.     

A genetic interaction network model of a complex neurological disease

Absence epilepsy (AE) is a complex, heritable disease characterized by a brief disruption of normal behavior and accompanying spike‐wave discharges (SWD) on the electroencephalogram. Only a handful of genes has been definitively associated with AE in humans and rodent models. Most studies suggest that genetic interactions play a large role in the etiology and severity of AE, but mapping and understanding their architecture remains a challenge, requiring new computational approaches. Here we use combined analysis of pleiotropy and epistasis (CAPE) to detect and interpret genetic interactions in a meta‐population derived from three C3H × B6J strain crosses, each of which is fixed for a different SWD‐causing mutation. Although each mutation causes SWD through a different molecular mechanism, the phenotypes caused by each mutation are exacerbated on the C3H genetic background compared with B6J, suggesting common modifiers. By combining information across two phenotypic measures – SWD duration and frequency – CAPE showed a large, directed genetic network consisting of suppressive and enhancing interactions between loci on 10 chromosomes. These results illustrate the power of CAPE in identifying novel modifier loci and interactions in a complex neurological disease, toward a more comprehensive view of its underlying genetic architecture.     

血脂异常遗传性疾病的研究现状

血脂异常(Dyslipidemia)是指血浆中胆固醇和(或)甘油三酯水平升高, 可导致严重的心血管疾病, 常以冠心病和脑中风为首发表现, 该类疾病严重危害着人们的健康。一些血脂异常疾病具有遗传性, 主要包括孟德尔遗传和多基因遗传。传统检测血脂异常相关基因的方法主要有DNA测序和连锁分析, 适合于孟德尔遗传性血脂异常疾病。最近几年兴起的新一代测序技术(Next-generation sequencing)不仅适用于孟德尔遗传性血脂异常疾病的研究, 同样适用于复杂性血脂异常疾病。2006年至今, 运用全基因组关联分析(Genome wide association study, GWAS)筛出许多与血脂异常疾病相关的基因, 这些基因和早期孟德尔遗传家系确定的基因多数相同。GWAS频谱分析发现, 复杂性疾病相关的基因变异频率存在差异, 并且几乎所有筛查出的与血脂异常疾病相关的单核苷酸多态性(Single nucleotide polymorphisms, SNPs)变异均位于非编码区, 使得人们逐渐对非编码区基因变异展开了研究。血脂异常致病基因的发现和基因变异致病机制的阐明, 为血脂异常疾病提供新的治疗靶点, 并为新一代药物筛选提供新思路。文章对血脂异常遗传性疾病的研究现状进行了综述。     

Stochastic approach to molecular interactions and computational theory of metabolic and genetic regulations

The underlying molecular mechanisms of metabolic and genetic regulations are computationally identical and can be described by a finite state Markov process. We establish a common computational model for both regulations based on the stationary distribution of the Markov process with the aim of establishing a unified, quantitative model of general biological regulations. Various existing results regarding intracellular regulations are derived including the classical Michaelis-Menten equation and its generalization to more complex allosteric enzymes in a systematic way. The notion of probability flow is introduced to distinguish the equilibrium stationary distribution from the non-equilibrium one; it plays a crucial role in the analysis of stationary state equations. A graphical criterion to guarantee the existence of an equilibrium stationary distribution is derived, which turns out to be identical to the classical Wegscheider condition. Simple graphical methods to compute the equilibrium and non-equilibrium stationary distributions are derived based crucially on the probability flow, which dramatically simplifies the classical methods still used in enzymology.