Theoretical strategies for high-resolution mapping of complex genetic disorders in humans

Positional cloning of gene(s) underlying a complex disease trait poses requirement of a highresolution linkage map between the disease locus and genetic marker loci. Recent researches have shown that this may be achieved through appropriately modeling and screening linkage disequilibrium between the candidate marker locus and the major trait locus. However, these models were restricted to the circumstances where genotyping at the disease locus was feasible. The major limitations of pedigree-based linkage analyses were addressed in the light of positional cloning and positional candidate gene identification in humans. It summarizes the recent efforts in developing theories for fine-scale mapping of genes underlying complex genetic variations where the one-to-one relationship no longer exists between phenotype of the genetic disorders and the corresponding genotype. Dedicated to Dr. C. C. Tan for his 90th birthday.     

全基因组关联研究中的遗传位点分析方法

提出多种模型方法,对高维位点数据进行分析,为基因定位和复杂疾病性状遗传等方面的研究提供新的技术支持。为了实现关联位点在基因中的定位,首先建立映射模型,对每个位点的碱基对重新编码;然后,提出将质量控制模型与关联分析模型相结合的方法,确定位点的关联程度;随后利用基于随机森林的重要性排序,筛选与该遗传疾病最相关的致病位点;最后,设计出高维RBF神经网络,得到每个位点对性状的相关性系数,探索出与疾病多类性状相关的位点。结合多种检验方式,验证所建模型能够较为准确地定位与疾病相关的位点及基因。各类模型具有极强的推广性,广泛适用于筛选占有各自权值的大样本数据。     

Identifying Micro RNA and Gene Expression Networks Using Graph Communities

Integrative network analysis is powerful in helping understand the underlying mechanisms of genetic and epigenetic perturbations for disease studies.Although it becomes clear that micro RNAs,one type of epigenetic factors,have direct effect on target genes,it is unclear how micro RNAs perturb downstream genetic neighborhood.Hence,we propose a network community approach to integrate micro RNA and gene expression profiles,to construct an integrative genetic network perturbed by micro RNAs.We apply this approach to an ovarian cancer dataset from The Cancer Genome Atlas project to identify the fluctuation of micro RNA expression and its effects on gene expression.First,we perform expression quantitative loci analysis between micro RNA and gene expression profiles via both a classical regression framework and a sparse learning model.Then,we apply the spin glass community detection algorithm to find genetic neighborhoods of the micro RNAs and their associated genes.Finally,we construct an integrated network between micro RNA and gene expression based on their community structure.Various disease related micro RNAs and genes,particularly related to ovarian cancer,are identified in this network.Such an integrative network allows us to investigate the genetic neighborhood affected by micro RNA expression that may lead to disease manifestation and progression.     

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P?相似文献   

表观遗传学研究进展

 概述了表观遗传调节模式、表观遗传调节的效应、植物表观遗传学的研究进展等。在每种细胞中,都会发生一部分特异基因激活、另一部分基因抑制的现象,形成多种基因表达模式。表观遗传指DNA序列不发生变化,而基因表达发生可遗传改变的现象。表观遗传学改变包括DNA甲基化、组蛋白修饰、非编码RNA作用等,产生基因组印记、母性影响、基因沉默、核仁显性、休眠转座子激活等效应。表观遗传变异是环境因素和细胞内遗传物质间交互作用的结果,其效应通过调节基因表达,控制生物学表型来实现。正是因为表观修饰对于维持生物体内环境和各器官系统功能的重要性,表观遗传的异常会引发疾病,这也成为药物和治疗方案设计的着眼点。     

Epistasis and balanced polymorphism influencing complex trait variation

Complex traits such as human disease, growth rate, or crop yield are polygenic, or determined by the contributions from numerous genes in a quantitative manner. Although progress has been made in identifying major quantitative trait loci (QTL), experimental constraints have limited our knowledge of small-effect QTL, which may be responsible for a large proportion of trait variation. Here, we identified and dissected a one-centimorgan chromosome interval in Arabidopsis thaliana without regard to its effect on growth rate, and examined the signature of historical sequence polymorphism among Arabidopsis accessions. We found that the interval contained two growth rate QTL within 210 kilobases. Both QTL showed epistasis; that is, their phenotypic effects depended on the genetic background. This amount of complexity in such a small area suggests a highly polygenic architecture of quantitative variation, much more than previously documented. One QTL was limited to a single gene. The gene in question displayed a nucleotide signature indicative of balancing selection, and its phenotypic effects are reversed depending on genetic background. If this region typifies many complex trait loci, then non-neutral epistatic polymorphism may be an important contributor to genetic variation in complex traits.     

复杂遗传性状连锁不平衡基因定位的理论基础(英)

复杂遗传疾病基因的定位克隆要求首先获得疾病位点与遗传标记位点间的高分辨率连锁图谱．研究表明,这一目标可通过建立和筛选适当的候选标记位点与目标性状位点间的连锁不平衡的理论分析模型而实现．但这些模型只适用于位点基因型可以通过实验而准确分型的范围．本文报道在不可测基因型复杂遗传疾病的细微定位理论与方法方面所取得的研究成果．     

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.     

Copy-number variations associated with neuropsychiatric conditions

Neuropsychiatric conditions such as autism and schizophrenia have long been attributed to genetic alterations, but identifying the genes responsible has proved challenging. Microarray experiments have now revealed abundant copy-number variation--a type of variation in which stretches of DNA are duplicated, deleted and sometimes rearranged--in the human population. Genes affected by copy-number variation are good candidates for research into disease susceptibility. The complexity of neuropsychiatric genetics, however, dictates that assessment of the biomedical relevance of copy-number variants and the genes that they affect needs to be considered in an integrated context.     

The glycoprotein encoded by the X-linked chronic granulomatous disease locus is a component of the neutrophil cytochrome b complex

The bacteriocidal capacity of phagocytic cells is impaired in X-linked chronic granulomatous disease (X-CGD), a disorder characterized by the absence of functional plasma-membrane-associated NADPH oxidase. The components of this oxidase system, their correspondence with specific genetic loci, and the primary protein defect in X-CGD remain incompletely defined. We recently reported cloning of the putative X-CGD gene on the basis of DNA linkage. To identify the predicted protein in vivo, antibodies were raised to a synthetic peptide derived from the complementary DNA sequence and to a fusion protein produced in Escherichia coli. In Western blots antisera detect a neutrophil protein of relative molecular mass in 90,000 (90K) that is absent in X-CGD patients. Antisera also react with the larger component of cytochrome b recently purified from neutrophil plasma membranes as a complex of glycosylated 90K and non-glycosylated 22K polypeptides. Based on our identification of the X-CGD protein in vivo, we propose that one of its critical roles is to interact with the 22K species to form a functional cytochrome b complex.     

林木分子育种研究的基因组学信息资源述评

分子育种是指利用与性状相关的DNA标记进行选育,也称标记辅助选择或标记辅助育种,广义上还包括基因工程育种和基因组学辅助育种。林木分子育种为早期选择和加速育种提供了极具潜力的高效手段。笔者对林木分子育种研究的基因组学信息资源进行了进展综述和前景展望。近30年来,林木分子标记技术从早期的低通量方法发展到目前基于微阵列芯片和新一代测序的高通量技术,如测序分型、转录组测序、重测序、扩增子测序和外显子组测序等,并广泛用于连锁作图、关联分析和基因组选择等林木性状相关的DNA变异检测研究。随着2006年毛果杨基因组序列的发表,已有50余个树种完成了基因组测序。基于连锁作图和关联研究检测了林木10余个属生长、材性和抗逆及非木质产品品质等性状相关的大量基因组位点,主要趋势表现为：① 表型广泛,涵盖经济性状、生理指标和代谢成分等;②标记数量成千上万甚至上百万,覆盖全基因组;③转录组和降解组等多组学的分子变异开始应用;④ 利用大群体以提高位点检测的精度;⑤ 重视环境的影响,大田试验设置多个地点,解析QTL与环境、年份的互作效应;⑥ 结合参考基因组序列和/或转录组差异表达基因进一步挖掘性状相关的候选基因,建立了桉属、松属和云杉属等主要造林树种的基因组选择模型。此外,积累了泛基因组、相关软件和算法、功能基因、基因组编辑技术及网站和数据库等其他信息资源。林木分子育种面临的挑战主要包括：① 如何获得稳定性好的性状相关基因组位点和基因组选择（GS）模型;② 缺乏自动化、无损和高通量的表型测定技术;③对大基因组的针叶树和一些多倍体树种,仍难获得高质量的基因组序列;④ 标记辅助选择增加了常规育种之外的费用,且存在不确定性;⑤多数树种的加速育种仍较困难。后基因组时代的林木分子育种将有效结合到常规育种程序中,显著促进遗传增益的提高。     

Type 1 diabetes in mice is linked to the interleukin-1 receptor and Lsh/Ity/Bcg genes on chromosome 1.

Human type 1 (insulin-dependent) diabetes is a common auto-immune disease of the insulin-producing beta cells of the pancreas which is caused by both genetic and environmental factors. Several features of the genetics and immunopathology of diabetes in nonobese diabetic (NOD) mice are shared with the human disease. Of the three diabetes-susceptibility genes, Idd-1 -3 and -4 that have been mapped in mice to date, only in the case of Idd-1 is there any evidence for the identity of the gene product: allelic variation within the murine immune response I-A beta gene and its human homologue HLA-DQB1 correlates with susceptibility, implying that I-A beta is a component of Idd-1. We report here the mapping of Idd-5 to the proximal region of mouse chromosome 1. This region contains at least two candidate susceptibility genes, the interleukin-1 receptor gene and Lsh/Ity/Bcg, which encodes resistance to bacterial and parasitic infections and affects the function of macrophages.     

Engineered gene circuits

A central focus of postgenomic research will be to understand how cellular phenomena arise from the connectivity of genes and proteins. This connectivity generates molecular network diagrams that resemble complex electrical circuits, and a systematic understanding will require the development of a mathematical framework for describing the circuitry. From an engineering perspective, the natural path towards such a framework is the construction and analysis of the underlying submodules that constitute the network. Recent experimental advances in both sequencing and genetic engineering have made this approach feasible through the design and implementation of synthetic gene networks amenable to mathematical modelling and quantitative analysis. These developments have signalled the emergence of a gene circuit discipline, which provides a framework for predicting and evaluating the dynamics of cellular processes. Synthetic gene networks will also lead to new logical forms of cellular control, which could have important applications in functional genomics, nanotechnology, and gene and cell therapy.     

Human chromosome 11 DNA sequence and analysis including novel gene identification

Chromosome 11, although average in size, is one of the most gene- and disease-rich chromosomes in the human genome. Initial gene annotation indicates an average gene density of 11.6 genes per megabase, including 1,524 protein-coding genes, some of which were identified using novel methods, and 765 pseudogenes. One-quarter of the protein-coding genes shows overlap with other genes. Of the 856 olfactory receptor genes in the human genome, more than 40% are located in 28 single- and multi-gene clusters along this chromosome. Out of the 171 disorders currently attributed to the chromosome, 86 remain for which the underlying molecular basis is not yet known, including several mendelian traits, cancer and susceptibility loci. The high-quality data presented here--nearly 134.5 million base pairs representing 99.8% coverage of the euchromatic sequence--provide scientists with a solid foundation for understanding the genetic basis of these disorders and other biological phenomena.