Phenotyping genetic diseases using an extension of mu-scores for multivariate data

As the field of genomics matures, more complex genotypes and phenotypes are being studied. Fanconi anemia (FA), for example, is an inherited chromosome instability syndrome with a complex array of variable disease phenotypes including congenital malformations, hematological manifestations, and cancer. To better understand specific aspects of the genetic etiology of FA and other rare diseases with complex phenotypes, it is often necessary to reduce the dimensions of the disease phenotype information. Towards this end, we extend a novel non-parametric approach to include information about a hierarchical structure among disease phenotypes. The proposed extension increases information content of the phenotype scores obtained and, thereby, the power of genotype-phenotype relationships studies.     

Genetic insight of schizophrenia: past and future perspectives

Schizophrenia (SCZ) has a heritability of about 80%, and the search for the genetic basis of this disease has been frustrating. Because schizophrenia has no distinguishing pathology or diagnostic criteria, it is difficult to relate gene changes to discrete physiological or biochemical changes associated with the disease. Schizophrenia fits the profile of a complex disorder in which multiple genes interact along with environmental influences to produce a range of phenotypes. There is accumulating evidence that both common genetic variants with small effects and rare genetic lesions with large effects determine risk of SCZ. As recently shown, thousands of common single nucleotide polymorphisms (SNPs), each with small effect, cumulatively could explain about 30% of the underlying genetic risk of SCZ. The ability of positional genetics to implicate novel genes and pathways will open up new vistas for neurobiological research, and all the signs are that genetic research is poised to deliver crucial insights into the nature of schizophrenia. In this review, we outline a general theoretical background of genetic mechanisms involved in SCZ.     

Do genetic variations alter the effects of exercise training on cardiovascular disease and can we identify the candidate variants now or in the future?

Cardiovascular disease (CVD) and CVD risk factors are highly heritable, and numerous lines of evidence indicate they have a strong genetic basis. While there is nothing known about the interactive effects of genetics and exercise training on CVD itself, there is at least some literature addressing their interactive effect on CVD risk factors. There is some evidence indicating that CVD risk factor responses to exercise training are also heritable and, thus, may have a genetic basis. While roughly 100 studies have reported significant effects of genetic variants on CVD risk factor responses to exercise training, no definitive conclusions can be generated at the present time, because of the lack of consistent and replicated results and the small sample sizes evident in most studies. There is some evidence supporting "possible" candidate genes that may affect these responses to exercise training: APO E and CETP for plasma lipoprotein-lipid profiles; eNOS, ACE, EDN1, and GNB3 for blood pressure; PPARG for type 2 diabetes phenotypes; and FTO and BAR genes for obesity-related phenotypes. However, while genotyping technologies and statistical methods are advancing rapidly, the primary limitation in this field is the need to generate what in terms of exercise intervention studies would be almost incomprehensible sample sizes. Most recent diabetes, obesity, and blood pressure genetic studies have utilized populations of 10,000-250,000 subjects, which result in the necessary statistical power to detect the magnitude of effects that would probably be expected for the impact of an individual gene on CVD risk factor responses to exercise training. Thus at this time it is difficult to see how this field will advance in the future to the point where robust, consistent, and replicated data are available to address these issues. However, the results of recent large-scale genomewide association studies for baseline CVD risk factors may drive future hypothesis-driven exercise training intervention studies in smaller populations addressing the impact of specific genetic variants on well-defined physiological phenotypes.     

The basic importance of the physiological approach in clinical medicine: the experience in the area of hypertension

Since Claude Bernard the physiological approach has dramatically contributed to the unprecedented progress that clinical medicine has seen during the second half of the 19th and throughout the 20th century. If I go back to about fifty years ago, when I started as a medical student and investigator under the guidance of Giuseppe Moruzzi and Cesare Bartorelli our understanding of arterial hypertension was very small and our therapeutic abilities close to nothing, but progressive knowledge of the physiology of the sympathetic nervous system, of the kidney, of the renin-angiotensin system, etc, led to a progressive understanding of the mechanisms of elevated blood pressure and to the development of an array of effective blood pressure lowering drugs, thanks to which hypertension is now a controllable disease. The supremacy of the physiological approach to clinical medicine has been recently endangered by the rising of two new approaches, whose worshippers consider the ultimate ones promising solid conclusions and unforeseen progress. These are the large randomized therapeutics trials, that are often arrogantly defined as evidence-based medicine (as if they were to provide the only real "evidence") and molecular and genetic medicine. Needless to say, both are important new tools in medicine, but neither can make the physiological method obsolete. The risk of the pretended superiority of the new approaches (and the new fashions) is that these claims are unbalancing research activity and its financial support, thus weakening the very basis upon which these new methodologies are founded and have developed.     

Utility and efficiency of linked marker genes for genetic counseling. II. Identification of linkage phase by offspring phenotypes

For a linked marker locus to be useful for genetic counseling, the counselee must be heterozygous for both disease and marker loci and his or her linkage phase must be known. It is shown that when the phenotypes of the counselee's previous children for the disease and marker loci are known, the linkage phase can often be inferred with a high probability, and thus it is possible to conduct genetic counseling. To evaluate the utility of linked marker genes for genetic counseling, the accuracy of prediction of the risk for a prospective child with a given marker gene to develop the genetic disease and the proportion of families in which a particular marker locus can be used for genetic counseling are studied for X-linked recessive, autosomal dominant, and autosomal recessive diseases. In the case of X-linked genetic diseases, information from children is very useful for determining the linkage phase of the counselee and predicting the genetic disease. In the case of autosomal dominant diseases, not all children are informative, but if the number of children is large, the phenotypes of children are often more informative than the information from grandparents. In the case of autosomal recessive diseases, information from grandparents is usually useless, since they show a normal phenotype for the disease locus. If we use information on the phenotypes of children, however, the linkage phase of the counselee and the risk of a prospective child can be inferred with a high probability. The proportion of informative families depends on the dominance relationship and frequencies of marker alleles, and the number of children. In general, codominant markers are more useful than are dominant markers, and a locus with high heterozygosity is more useful than is a locus with low heterozygosity.     

Metabolic selection of glycosylation defects in human cells

Changes in glycosylation are often associated with disease progression, but the genetic and metabolic basis of these events is rarely understood in detail at a molecular level. We describe a metabolism-based approach to the selection of mutants in glycoconjugate biosynthesis that provides insight into regulatory mechanisms for oligosaccharide expression and metabolic flux. Unnatural intermediates are used to challenge a specific pathway, and cell surface expression of their metabolic products provides a readout of flux in that pathway and a basis for selecting genetic mutants. The approach was applied to the sialic acid metabolic pathway in human cells, yielding novel mutants with phenotypes related to the inborn metabolic defect sialuria and metastatic tumor cells.     

Expression QTL modules as functional components underlying higher-order phenotypes

Systems genetics studies often involve the mapping of numerous regulatory relations between genetic loci and expression traits. These regulatory relations form a bipartite network consisting of genetic loci and expression phenotypes. Modular network organizations may arise from the pleiotropic and polygenic regulation of gene expression. Here we analyzed the expression QTL (eQTL) networks derived from expression genetic data of yeast and mouse liver and found 65 and 98 modules respectively. Computer simulation result showed that such modules rarely occurred in randomized networks with the same number of nodes and edges and same degree distribution. We also found significant within-module functional coherence. The analysis of genetic overlaps and the evidences from biomedical literature have linked some eQTL modules to physiological phenotypes. Functional coherence within the eQTL modules and genetic overlaps between the modules and physiological phenotypes suggests that eQTL modules may act as functional units underlying the higher-order phenotypes.     

Revealing the architecture of gene regulation: the promise of eQTL studies

Expression quantitative trait loci (eQTL) mapping studies have become a widely used tool for identifying genetic variants that affect gene regulation. In these studies, expression levels are viewed as quantitative traits, and gene expression phenotypes are mapped to particular genomic loci by combining studies of variation in gene expression patterns with genome-wide genotyping. Results from recent eQTL mapping studies have revealed substantial heritable variation in gene expression within and between populations. In many cases, genetic factors that influence gene expression levels can be mapped to proximal (putatively cis) eQTLs and, less often, to distal (putatively trans) eQTLs. Beyond providing great insight into the biology of gene regulation, a combination of eQTL studies with results from traditional linkage or association studies of human disease may help predict a specific regulatory role for polymorphic sites previously associated with disease.     

Characterization of single nucleotide polymorphisms for a forward genetics approach using genetic crosses in C57BL/6 and BALB/c substrains of mice

Forward genetics is a powerful approach based on chromosomal mapping of phenotypes and has successfully led to the discovery of many mouse mutations in genes responsible for various phenotypes. Although crossing between genetically remote strains can produce F₂ and backcross mice for chromosomal mapping, the phenotypes are often affected by background effects from the partner strains in genetic crosses. Genetic crosses between substrains might be useful in genetic mapping to avoid genetic background effects. In this study, we investigated single nucleotide polymorphisms (SNPs) available for genetic mapping using substrains of C57BL/6 and BALB/c mice. In C57BL/6 mice, 114 SNP markers were developed and assigned to locations on all chromosomes for full utilization for genetic mapping using genetic crosses between the C57BL/6J and C57BL/6N substrains. Moreover, genetic differences were identified in the 114 SNP markers among the seven C57BL/6 substrains from five production breeders. In addition, 106 SNPs were detected on all chromosomes of BALB/cAJcl and BALB/cByJJcl substrains. These SNPs could be used for genotyping in BALB/cJ, BALB/cAJcl, BALB/cAnNCrlCrlj, and BALB/cCrSlc mice, and they are particularly useful for genetic mapping using crosses between BALB/cByJJcl and other BALB/c substrains. The SNPs characterized in this study can be utilized for genetic mapping to identify the causative mutations of the phenotypes induced by N-ethyl-N-nitrosourea mutagenesis and the SNPs responsible for phenotypic differences between the substrains of C57BL/6 and BALB/c mice.     

The genomic and physiological basis of life history variation in a butterfly metapopulation

Unravelling the mechanisms underlying variation in life history traits is of fundamental importance for our understanding of adaptation by natural selection. While progress has been made in mapping fitness-related phenotypes to genotypes, mainly in a handful of model organisms, functional genomic studies of life history adaptations are still in their infancy. In particular, despite a few notable exceptions, the genomic basis of life history variation in natural populations remains poorly understood. This is especially true for the genetic underpinnings of life history phenotypes subject to diversifying selection driven by ecological dynamics in patchy environments--as opposed to adaptations involving strong directional selection owing to major environmental changes, such as latitudinal gradients, extreme climatic events or transitions from salt to freshwater. In this issue of Molecular Ecology,Wheat et al. (2011) now make a significant leap forward by applying the tools of functional genomics to dispersal-related life history variation in a butterfly metapopulation. Using a combination of microarrays, quantitative PCR and physiological measurements, the authors uncover several metabolic and endocrine factors that likely contribute to the observed life history phenotypes. By identifying molecular candidate mechanisms of fitness variation maintained by dispersal dynamics in a heterogeneous environment,they also begin to address fascinating interactions between the levels of physiology, ecology and evolution.     

Neurodegenerative mutants in Drosophila: a means to identify genes and mechanisms involved in human diseases?

There are 50 ways to leave your lover (Simon 1987) but many more to kill your brain cells. Several neurodegenerative diseases in humans, like Alzheimer’s disease, have been intensely studied but the underlying cellular and molecular mechanisms are still unknown for most of them. For those syndromes where associated gene products have been identified their biochemistry and physiological as well as pathogenic function is often still under debate. This is in part due to the inherent limitations of genetic analyses in humans and other mammals and therefore experimentally accessible invertebrate in vivo models, such as Caenorhabditis elegans and Drosophila melanogaster, have recently been introduced to investigate neurodegenerative syndromes. Several laboratories have used transgenic approaches in Drosophila to study the human genes associated with neurodegenerative diseases. This has added substantially to our understanding of the mechanisms leading to neurodegenerative diseases in humans. The isolation and characterization of Drosophila mutants, which display a variety of neurodegenerative phenotypes, also provide valuable insights into genes, pathways, and mechanisms causing neurodegeneration. So far only about two dozen such mutants have been described but already their characterization reveals an involvement of various cellular functions in neurodegeneration, ranging from preventing oxidative stress to RNA editing. Some of the isolated genes can already be associated with human neurodegenerative diseases and hopefully the isolation and characterization of more of these mutants, together with an analysis of homologous genes in vertebrate models, will provide insights into the genetic and molecular basis of human neurodegenerative diseases.     

Genetic mappings in artificial genomes

This paper concerns processing of genomes of artificial (computer-simulated) organisms. Of special interest is the process of translation of genotypes into phenotypes, and utilizing the mapping information obtained during such translation. If there exists more than one genetic encoding in a single artificial life model, then the translation may also occur between different encodings. The obtained mapping information allows to present genes-phenes relationships visually and interactively to a person, in order to increase understanding of the genotype-tophenotype translation process and genetic encoding properties. As the mapping associates parts of the source sequence with the translated destination, it may be also used to trace genes, phenes, and their relationships during simulated evolution. A mappings composition procedure is formally described, and a simple method of visual mapping presentation is established. Finally, advanced visualizations of gene-phene relationships are demonstrated as practical examples of introduced techniques. These visualizations concern genotypes expressed in various encodings, including an encoding which exhibits polygenic and pleiotropic properties.     

Multitrait GWAS to connect disease variants and biological mechanisms

Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.     

Genetic and familial factors in essential hypertension and related traits

The health significance of essential hypertension “high blood pressure of undefined origin” is well established. It is a major factor contributing to coronary heart disease, stroke, and kidney failure. It directly affects about one in five Americans. Factors which are known to be associated with blood pressure include: body composition as it relates to overall mass and fat mass; physiological variables involving the sympathetic and parasympathetic nervous systems; biochemical variables such as renin, aldosterone, kallikrein, lipids, and lipoproteins, etc.; environmental variables such as sodium intake, heavy metals, and noise; and psychological variables involving personality type and mental stress. There is a definite, well-established genetic involvement in hypertension, but specific genetic mechanisms remain a mystery. Familial aggregation occurs for many of the associated traits listed above. For some, specific polymorphic major genes have been identified, but for others genetic factors are unidentified. Essential hypertension is undoubtedly a heterogeneous group of diseases with the common end result of elevated blood pressure. Because of its health significance, there is considerable interest in identifying genetic mechanisms resulting in essential hypertension. One area that currently shows some potential for the identification of a specific genetic mechanism is related to the transmembrane transport of sodium and potassium cations.     

利用果蝇模型研究人类心脏早期发育的分子机理(英文)

近年来 ,果蝇心脏特化的遗传机制已初步研究清楚 ,但控制人类心脏早期发育的基因尚待鉴定。因为调控果蝇和脊椎动物早期心脏细胞命运定型的途径具有保守性 ,果蝇是一种探讨人类心脏早期发育的分子机理的理想动物模式。为此目的 ,我们采用P转座子和EMS诱变技术建立了约 3 0 0 0个隐性致死基因平衡系。通过心脏前体细胞特异性抗体免疫组化筛选 ,我们检出 2 0 0余个表现心脏突变表型的平衡致死系。我们进一步利用RNAi技术对一些基因的功能进行了初步的研究 ,证明这些基因表现RNAi的突变表型 ,该类突变表型与基因突变时表现的表型相似 ,即心管呈缺陷型或无心脏前体细胞形成。利用果蝇和人类基因组计划获得的成果 ,我们从果蝇心脏侯选基因中初步克隆和鉴定了 5 0个人类同源基因 ,其中 2 0个是新基因。Northen印迹分析表明 ,一部分人类基因在心脏组织中有表达 ,从而为研究这些基因在人类心脏早期发育中的作用提供了信息。目前 ,我们正在建立转基因果蝇 ,以此为模型研究这些基因是否对心肌细胞发生或心肌功能起调控作用。产生心肌细胞突变类型的基因如果类似于人类心脏病综合症 ,则可以作为人类心脏疾病侯选基因作进一步的分析。     

Use with caution: Developmental systems divergence and potential pitfalls of animal models

Transgenic animal models have played an important role in elucidating gene functions and the molecular basis development, physiology, behavior, and pathogenesis. Transgenic models have been so successful that they have become a standard tool in molecular genetics and biomedical studies and are being used to fulfill one of the main goals of the post-genomic era: to assign functions to each gene in the genome. However, the assumption that gene functions and genetic systems are conserved between models and humans is taken for granted, often in spite of evidence that gene functions and networks diverge during evolution. In this review, I discuss some mechanisms that generate functional divergence and highlight recent examples demonstrating that gene functions and regulatory networks diverge through time. These examples suggest that annotation of gene functions based solely on mutant phenotypes in animal models, as well as assumptions of conserved functions between species, can be wrong. Therefore, animal models of gene function and human disease may not provide appropriate information, particularly for rapidly evolving genes and systems.     

Genetic regulation of liver lipids in a mouse model of insulin resistance and hepatic steatosis

To elucidate the contributions of specific lipid species to metabolic traits, we integrated global hepatic lipid data with other omics measures and genetic data from a cohort of about 100 diverse inbred strains of mice fed a high‐fat/high‐sucrose diet for 8 weeks. Association mapping, correlation, structure analyses, and network modeling revealed pathways and genes underlying these interactions. In particular, our studies lead to the identification of Ifi203 and Map2k6 as regulators of hepatic phosphatidylcholine homeostasis and triacylglycerol accumulation, respectively. Our analyses highlight mechanisms for how genetic variation in hepatic lipidome can be linked to physiological and molecular phenotypes, such as microbiota composition.     

How far are we from unravelling self-incompatibility in grasses?

The genetic and physiological mechanisms involved in limiting self-fertilization in angiosperms, referred to as self-incompatibility (SI), have significant effects on population structure and have potential diversification and evolutionary consequences. Up to now, details of the underlying genetic control and physiological basis of SI have been elucidated in two different gametophytic SI (GSI) systems, the S-RNase SI and the Papaver SI systems, and the sporophytic SI (SSI) system (Brassica). In the grass family (Poaceae), which contains all the cereal and major forage crops, SI has been known for half a century to be controlled gametophytically by two multiallelic and independent loci, S and Z. But still none of the gene products for S and Z is known and only limited information on related biochemical responses is available. Here we compare current knowledge of grass SI with that of other well-characterized SI systems and speculate about the relationship between SSI and grass SI. Additionally, we discuss comparative mapping as a tool for the further investigation of grass SI.     

原发性高血压全基因组关联研究进展

原发性高血压是一种由遗传与环境因素共同导致的复杂疾病,具有高度的遗传异质性。自2007年首个高血压全基因组关联研究(Genome-wide association studies,GWAS)报道以来,许多GWAS相继开展。文章首先对2007年1月至2011年9月期间报道的24篇血压/高血压易感基因的GWAS按人种与染色体位置对其结果进行汇总,经统计位点rs17249754、rs1378942和rs11191548报道频数最多。其次介绍了GWAS方法学的研究进展,包括选择高质量的数量表型和选择多阶段研究设计来增加研究发现阳性关联的机会。统计分析方面,除强调了已经报道过的多重比较和重复(验证)研究等问题外,文章还介绍了通过Meta分析对GWAS数据进行深度发掘,并应用基因型填补法对缺失数据进行填补可以提高全基因组遗传标记的覆盖率的方法。尽管GWAS发现了许多我们未知的基因与疾病表型的关联,为了解高血压的发病机制提供了更多线索,但是目前GWAS发现的血压/高血压相关变异多为对人群血压的影响极其微弱的常见变异。因此今后的研究中可加强深度功能学研究对易感基因精细定位和外显子组测序技术的应用,结合GWAS的成果进行生物信息学通路分析和表观遗传学机制研究等,逐步揭示高血压的遗传机制。     

Modifier genes in mice and humans

An emerging theme of studies with spontaneous, engineered and induced mutant mice is that phenotypes often depend on genetic background, implying that genetic modifiers have a role in guiding the functional consequences of genetic variation. Understanding the molecular and cellular basis by which modifier genes exert their influence will provide insights into developmental and physiological pathways that are critical to fundamental biological processes, as well as into novel targets for therapeutic interventions in human diseases.