A score test for the linkage analysis of qualitative and quantitative traits based on identity by descent data from sib-pairs

We propose a general likelihood-based approach to the linkage analysis of qualitative and quantitative traits using identity by descent (IBD) data from sib-pairs. We consider the likelihood of IBD data conditional on phenotypes and test the null hypothesis of no linkage between a marker locus and a gene influencing the trait using a score test in the recombination fraction theta between the two loci. This method unifies the linkage analysis of qualitative and quantitative traits into a single inferential framework, yielding a simple and intuitive test statistic. Conditioning on phenotypes avoids unrealistic random sampling assumptions and allows sib-pairs from differing ascertainment mechanisms to be incorporated into a single likelihood analysis. In particular, it allows the selection of sib-pairs based on their trait values and the analysis of only those pairs having the most informative phenotypes. The score test is based on the full likelihood, i.e. the likelihood based on all phenotype data rather than just differences of sib-pair phenotypes. Considering only phenotype differences, as in Haseman and Elston (1972) and Kruglyak and Lander (1995), may result in important losses in power. The linkage score test is derived under general genetic models for the trait, which may include multiple unlinked genes. Population genetic assumptions, such as random mating or linkage equilibrium at the trait loci, are not required. This score test is thus particularly promising for the analysis of complex human traits. The score statistic readily extends to accommodate incomplete IBD data at the test locus, by using the hidden Markov model implemented in the programs MAPMAKER/SIBS and GENEHUNTER (Kruglyak and Lander, 1995; Kruglyak et al., 1996). Preliminary simulation studies indicate that the linkage score test generally matches or outperforms the Haseman-Elston test, the largest gains in power being for selected samples of sib-pairs with extreme phenotypes.     

Limits of resolution of genetic linkage studies: implications for the positional cloning of human disease genes.

Positional cloning studies to identify disease genes are being carried out for many human genetic diseases. Such studies often include a genome-scan linkage analysis to identify the rough chromosomal location of a disease gene, fine structure genetic mapping to define and narrow the chromosomal interval in which the disease gene may be located, and physical mapping and gene identification in the genetically defined interval to clone the disease gene. During the planning of a positional cloning study, it is important to know that, if linkage is found, the genetic interval identified is likely to be sufficiently narrow to be dissected efficiently by methods of physical mapping and gene identification. Thus, we wish to know the limits of resolution of a genetic linkage study. In this paper, I determine for Mendelian diseases the distributions and moments of three measures of linkage resolution: (1) in a set of N chromosomes, the distance between the nearest crossovers that flank a disease locus, (2) the distance between the nearest genetic markers that flank the pair of flanking crossovers after a genome scan, and (3) the distance between the nearest flanking markers after additional randomly placed markers are generated and typed in an identified interval. These results provide explicit sample-size guidelines for future positional cloning studies of Mendelian diseases and make possible a more objective evaluation of whether a proposed positional cloning study is likely to be successful. I also briefly discuss the more difficult problem of linkage resolution for complex genetic diseases.     

Simulations provide support for the common disease-common variant hypothesis

The success of mapping genes involved in complex diseases, using association or linkage disequilibrium methods, depends heavily on the number and frequency of susceptibility alleles of these genes. These methods will be economically and statistically feasible if common diseases are usually influenced by one or a few susceptibility alleles at each locus (common disease-common variant, CDCV, hypothesis), but not so if there is a high degree of allelic heterogeneity. Here, we use forward-time population simulations to investigate the impact of various genetic and demographic factors on the allelic spectra of human diseases, on the basis of two models proposed by Reich and Lander and by Pritchard. Factors considered are more complex demographies, a finite-allele mutation model, population structure and migration, and interaction between disease susceptibility loci. The conclusion is that the CDCV hypothesis holds and that the phenomenon is caused by transient effects of demography (population expansion). As a result, we devise a multilocus generalization of the Reich and Lander model and demonstrate how interaction between loci with respect to their response to selection may lead to complex effects. We discuss the implications for mapping of complex diseases.     

An initial genetic linkage map of the rhesus macaque (Macaca mulatta) genome using human microsatellite loci

Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate species in biomedical research. To create new opportunities for genetic and genomic studies using rhesus monkeys, we constructed a genetic linkage map of the rhesus genome. This map consists of 241 microsatellite loci, all previously mapped in the human genome. These polymorphisms were genotyped in five pedigrees of rhesus monkeys totaling 865 animals. The resulting linkage map covers 2048 cM including all 20 rhesus autosomes, with average spacing between markers of 9.3 cM. Average heterozygosity among those markers is 0.73. This linkage map provides new comparative information concerning locus order and interlocus distances in humans and rhesus monkeys. The map will facilitate whole-genome linkage screens to locate quantitative trait loci (QTLs) that influence individual variation in phenotypic traits related to basic primate anatomy, physiology, and behavior, as well as QTLs relevant to risk factors for human disease.     

Localization and identification of human quantitative trait loci: king harvest has surely come

The scientific process of localization and subsequent identification of genes influencing risk of common diseases is still in its infancy. Initial localization of disease-related loci has traditionally been performed using family-based linkage methods to scan the genome. Early pronouncements of the failure of this approach for common diseases were premature and based on comparing suboptimal linkage designs with overly optimistic and empirically unproven association-based designs. On the contrary, substantial recent progress in the positional cloning of genes influencing such complex phenotypes suggests that modern approaches based around a family-based linkage paradigm will be successful. In particular, the rapidly growing emphasis on the analysis of the genetic basis of quantitative correlates of disease risk represents a novel and promising approach in which initial localization is performed using linkage and subsequent identification utilizes association approaches in positional candidate genes.     

Positional cloning of disease genes: advantages of genetic isolates.

Genetic isolates with a history of a small founder population, long-lasting isolation and population bottlenecks represent exceptional resources in the identification of disease genes. Specific rare, monogenic diseases become enriched, and families with multiple affected individuals occur frequently enough to be used in linkage analyses for locus identification. Further, the vast majority of cases are caused by the same mutation, and disease alleles reveal linkage disequilibrium (LD) with markers over significant genetic intervals; this facilitates disease locus identification by similarity search for a shared genotype or haplotype in small study samples consisting of few affected individuals. LD observed in disease alleles adds power to linkage analyses and helps to define the exact location of disease loci on the genetic map. Typically, based on the linkage disequilibrium and the ancient haplotype, the critical DNA region can be defined from the original 1- to 2-cM resolution obtained in linkage analysis to 50-200 kb, greatly facilitating the targeting of physical cloning and sequencing efforts. These advantages have been well demonstrated in the positional cloning of several rare monogenic diseases enriched in population isolates like the example of Finland used here. How useful genetic isolates will prove to be in the identification of complex disease genes is dependent on the genealogical history of the isolate, including the size of the founding population and the expansion rate during the history of the population.     

Isolates and their potential use in complex gene mapping efforts

Linkage disequilibrium (LD), detectable with microsatellites in disease alleles over wide genetic intervals in population isolates, has facilitated mapping and positional cloning of numerous disease genes. We, among others, have shown that the LD intervals reach up to 1 Mb in general alleles of young subisolates, and that this feature most probably offers an avenue for the initial locus positioning for complex traits. Development of efficient SNP genotyping and characterization of haploblock structure of the human genome have introduced new prospects to LD-based fine mapping and haplotype-association studies. Encouraging associations have been reported for several complex diseases. Final breakthroughs in mapping of complex disease loci have emerged on large pedigrees in population isolates. Conversely, ignoring genealogical makeup of the study population seems to disclose false negative and false positive associations, directing resources down the drain.     

Systematic identification of genes that regulate neuronal wiring in the Drosophila visual system

Forward genetic screens in model organisms are an attractive means to identify those genes involved in any complex biological process, including neural circuit assembly. Although mutagenesis screens are readily performed to saturation, gene identification rarely is, being limited by the considerable effort generally required for positional cloning. Here, we apply a systematic positional cloning strategy to identify many of the genes required for neuronal wiring in the Drosophila visual system. From a large-scale forward genetic screen selecting for visual system wiring defects with a normal retinal pattern, we recovered 122 mutations in 42 genetic loci. For 6 of these loci, the underlying genetic lesions were previously identified using traditional methods. Using SNP-based mapping approaches, we have now identified 30 additional genes. Neuronal phenotypes have not previously been reported for 20 of these genes, and no mutant phenotype has been previously described for 5 genes. The genes encode a variety of proteins implicated in cellular processes such as gene regulation, cytoskeletal dynamics, axonal transport, and cell signalling. We conducted a comprehensive phenotypic analysis of 35 genes, scoring wiring defects according to 33 criteria. This work demonstrates the feasibility of combining large-scale gene identification with large-scale mutagenesis in Drosophila, and provides a comprehensive overview of the molecular mechanisms that regulate visual system wiring.     

Evolution, revolution and heresy in the genetics of infectious disease susceptibility

Infectious pathogens have long been recognized as potentially powerful agents impacting on the evolution of human genetic diversity. Analysis of large-scale case-control studies provides one of the most direct means of identifying human genetic variants that currently impact on susceptibility to particular infectious diseases. For over 50 years candidate gene studies have been used to identify loci for many major causes of human infectious mortality, including malaria, tuberculosis, human immunodeficiency virus/acquired immunodeficiency syndrome, bacterial pneumonia and hepatitis. But with the advent of genome-wide approaches, many new loci have been identified in diverse populations. Genome-wide linkage studies identified a few loci, but genome-wide association studies are proving more successful, and both exome and whole-genome sequencing now offer a revolutionary increase in power. Opinions differ on the extent to which the genetic component to common disease susceptibility is encoded by multiple high frequency or rare variants, and the heretical view that most infectious diseases might even be monogenic has been advocated recently. Review of findings to date suggests that the genetic architecture of infectious disease susceptibility may be importantly different from that of non-infectious diseases, and it is suggested that natural selection may be the driving force underlying this difference.     

复杂疾病基因定位策略与肿瘤易感基因鉴定

对于不存在某单一基因位点经典的孟德尔显性或隐性遗传模式的疾病,称为复杂疾病,肿瘤是最常见的类型之一 . 目前,以连锁和相关分析为基础的功能克隆、功能候选克隆、定位克隆、定位候选克隆、系统生物学等复杂疾病易感基因定位策略逐渐发展起来 . 其中,系统生物学策略由于整合了从 DNA 到蛋白质的各个层面的信息,对复杂疾病基因调控网络做出了良好诠释,使其成为最有潜力的方法之一 . 目前,虽然已有近 100 种肿瘤 / 遗传性癌综合症的易感基因被鉴定出来,但未来的复杂疾病易感基因定位工作仍充满了挑战 .     

70个水稻微卫星标记染色体位置的更正

微卫星标记(SSR)因其操作简单和稳定可靠的特点而成为一种重要的分子标记,被广泛应用于遗传作图和种质鉴定等方面。但其在染色体上位置的正确性将直接影响到基因定位的正确性和后续研究的方向。利用美国国家生物信息技术中心(NCBI)网站的Blast程序,将2740个SSR标记的前后引物序列与水稻粳稻品种日本晴基因组进行比对,共发现70个标记位于另一条染色体,对这70个标记重新锚定的染色体进行了更正。这将有助于今后水稻分子标记遗传连锁图的正确构建。     

A second-generation genetic linkage map of the baboon (Papio hamadryas) genome

Construction of genetic linkage maps for nonhuman primate species provides information and tools that are useful for comparative analysis of chromosome structure and evolution and facilitates comparative analysis of meiotic recombination mechanisms. Most importantly, nonhuman primate genome linkage maps provide the means to conduct whole genome linkage screens for localization and identification of quantitative trait loci that influence phenotypic variation in primate models of common complex human diseases such as atherosclerosis, hypertension, and diabetes. In this study we improved a previously published baboon whole genome linkage map by adding more loci. New loci were added in chromosomal regions that did not have sufficient marker density in the initial map. Relatively low heterozygosity loci from the original map were replaced with higher heterozygosity loci. We report in detail on baboon chromosomes 5, 12, and 18 for which the linkage maps are now substantially improved due to addition of new informative markers.     

Alteration of Fatty-Acid-Metabolizing Enzymes Affects Mitochondrial Form and Function in Hereditary Spastic Paraplegia

Hereditary spastic paraplegia (HSP) is considered one of the most heterogeneous groups of neurological disorders, both clinically and genetically. The disease comprises pure and complex forms that clinically include slowly progressive lower-limb spasticity resulting from degeneration of the corticospinal tract. At least 48 loci accounting for these diseases have been mapped to date, and mutations have been identified in 22 genes, most of which play a role in intracellular trafficking. Here, we identified mutations in two functionally related genes (DDHD1 and CYP2U1) in individuals with autosomal-recessive forms of HSP by using either the classical positional cloning or a combination of whole-genome linkage mapping and next-generation sequencing. Interestingly, three subjects with CYP2U1 mutations presented with a thin corpus callosum, white-matter abnormalities, and/or calcification of the basal ganglia. These genes code for two enzymes involved in fatty-acid metabolism, and we have demonstrated in human cells that the HSP pathophysiology includes alteration of mitochondrial architecture and bioenergetics with increased oxidative stress. Our combined results focus attention on lipid metabolism as a critical HSP pathway with a deleterious impact on mitochondrial bioenergetic function.     

Primary genetic linkage maps of the ascidian, Ciona intestinalis

For whole-genome analysis in a basal chordate (protochordate), we used F1 pseudo-testcross mapping strategy and amplified fragment length polymorphism (AFLP) markers to construct primary linkage maps of the ascidian tunicate Ciona intestinalis. Two genetic maps consisted of 14 linkage groups, in agreement with the haploid chromosome number, and contained 276 and 125 AFLP loci derived from crosses between British and Neapolitan individuals. The two maps covered 4218.9 and 2086.9 cM, respectively, with an average marker interval of 16.1 and 18.9 cM. We observed a high recombinant ratio, ranging from 25 to 49 kb/cM, which can explain the high degree of polymorphism in this species. Some AFLP markers were converted to sequence tagged sites (STSs) by sequence determination, in order to create anchor markers for the fragmental physical map. Our recombination tools provide basic knowledge of genetic status and whole genome organization, and genetic markers to assist positional cloning in C. intestinalis.     

Accurate haplotype inference for multiple linked single-nucleotide polymorphisms using sibship data

Sibships are commonly used in genetic dissection of complex diseases, particularly for late-onset diseases. Haplotype-based association studies have been advocated as powerful tools for fine mapping and positional cloning of complex disease genes. Existing methods for haplotype inference using data from relatives were originally developed for pedigree data. In this study, we proposed a new statistical method for haplotype inference for multiple tightly linked single-nucleotide polymorphisms (SNPs), which is tailored for extensively accumulated sibship data. This new method was implemented via an expectation-maximization (EM) algorithm without the usual assumption of linkage equilibrium among markers. Our EM algorithm does not incur extra computational burden for haplotype inference using sibship data when compared with using unrelated parental data. Furthermore, its computational efficiency is not affected by increasing sibship size. We examined the robustness and statistical performance of our new method in simulated data created from an empirical haplotype data set of human growth hormone gene 1. The utility of our method was illustrated with an application to the analyses of haplotypes of three candidate genes for osteoporosis.     

Inherent bias toward the null hypothesis in conventional multipoint nonparametric linkage analysis

Traditional nonparametric "multipoint" statistical procedures have been developed for assigning allele-sharing values at a locus of interest to pairs of relatives for linkage studies. These procedures attempt to accommodate a lack of informativity, nongenotyped loci, missing data, and related issues concerning the genetic markers used in a linkage study. However, such procedures often cannot overcome these phenomena in compelling ways and, as a result, assign relevant relative pairs allele-sharing values that are "expected" for those pairs. The practice of assigning expected allele-sharing values to relative pairs in the face of a lack of explicit allele-transmission information can bias traditional nonparametric linkage test statistics toward the null hypothesis of no locus effect. This bias is due to the use of expected values, rather than to a lack of information about actual allele sharing at relevant marker loci. The bias will vary from study to study on the basis of the DNA markers, sample size, relative-pair types, and pedigree structures used, but it can be extremely pronounced and could contribute to a lack of consistent success in the application of traditional nonparametric linkage analyses to complex human traits and diseases. There are several potential ways to overcome this problem, but their foundations deserve greater research. We expose many of the issues concerning allele sharing with data from a large affected-sibling-pair study investigating the genetic basis of autism.     

Patterns of linkage disequilibrium in the human genome

Particular alleles at neighbouring loci tend to be co-inherited. For tightly linked loci, this might lead to associations between alleles in the population a property known as linkage disequilibrium (LD). LD has recently become the focus of intense study in the hope that it might facilitate the mapping of complex disease loci through whole-genome association studies. This approach depends crucially on the patterns of LD in the human genome. In this review, we draw on empirical studies in humans and Drosophila, as well as simulation studies, to assess the current state of knowledge about patterns of LD, and consider the implications for the use of LD as a mapping tool.     

A novel framework for sib pair linkage analysis

Sib pair linkage analysis of a dichotomous trait is a popular method for narrowing the search for genes that influence complex diseases. Although the pedigree structures are uncomplicated and the underlying genetic principles straightforward, a surprising degree of complexity is involved in implementing a sib pair study and interpreting the results. Ascertainment may be based on affected, discordant, or unaffected sib pairs, as well as on pairs defined by threshold values for quantitative traits, such as extreme discordant sib pairs. To optimize power, various domain restrictions and null hypotheses have been proposed for each of these designs, yielding a wide array of choices for the analyst. To begin, we systematically classify the major sources of discretion in sib pair linkage analysis. Then, we extend the work of Kruglyak and Lander (1995), to bring the various forms into a unified framework and to facilitate a more general approach to the analysis. Finally, we describe a new, freely available computer program, Splat (Sib Pair Linkage Analysis Testing), that can perform any sib pair statistical test currently in use, as well as any user-defined test yet to be proposed. Splat uses the expectation maximization algorithm to calculate maximum-likelihood estimates of sharing (subject to user-specified conditions) and then plots LOD scores versus chromosomal position. It includes a novel grid-scanning capability that enables simultaneous visualization of multiple test statistics. This can lead to further insight into the genetic basis of the disease process under consideration. In addition, phenotype definitions can be modified without the recalculation of inheritance vectors, thereby providing considerable flexibility for exploratory analysis. The application of Splat will be illustrated with data from studies on the genetics of diabetic nephropathy.     

Comparison of the power and accuracy of biallelic and microsatellite markers in population-based gene-mapping methods.

Because of their great abundance and amenability to fully automated genotyping, single-nucleotide polymorphisms (SNPs) and simple insertion/deletion are emerging as a new generation of markers for positional cloning. Although the efficiency and cost associated with the markers are important in the mapping of human disease genes, the power to detect the linkage between the marker and the disease locus, as well as the accuracy of the estimation of the map location of the disease gene, dictate the selection of the markers. Both the power and the accuracy depend not only on the type of the markers but also on other factors, such as the age of the disease mutation, the magnitude of the genetic effect, the marker-allele distribution in the population, mutation rates of marker loci, the frequency of the disease allele, the recombination fraction, and the methods for mapping the human disease genes. In this article, we develop a mathematical framework and the analytical formulas for calculation of the power and the accuracy and investigate the impact that the aforementioned factors have on the power and the accuracy, by using two population-based gene-mapping methods-likelihood-based linkage-disequilibrium mapping and the transmission/disequilibrium test, for both biallelic SNPs and microsatellites. These studies provide not only guidance in selection of the markers and in the design of the sample scheme for positional cloning but also insight into the biological bases of the mapping of human disease genes.     

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。