Finding genes underlying risk of complex disease by linkage disequilibrium mapping

Identification of genes that harbor variation associated with inter-individual differences in risk of complex diseases remains one of the most challenging and important problems in human genetics. For genetic variants that are sufficiently common and have sufficiently large effects, direct tests of association through linkage disequilibrium with anonymous SNPs may prove effective. But the two critical parameters - the frequency of risk-inflating alleles and the magnitudes of their effect on risk - remain largely unknown. In this review we consider the latest information regarding the likely efficacy of the linkage disequilibrium mapping approach.     

Cost-effective designs for linkage disequilibrium mapping of complex traits

The current development of densely spaced collections of single nucleotide polymorphisms (SNPs) will lead to genomewide association studies for a wide range of diseases in many different populations. Determinations of the appropriate number of SNPs to genotype involve a balancing of power and cost. Several variables are important in these determinations. We show that there are different combinations of sample size and marker density that can be expected to achieve the same power. Within certain bounds, investigators can choose between designs with more subjects and fewer markers or those with more markers and fewer subjects. Which designs are more cost-effective depends on the cost of phenotyping versus the cost of genotyping. We show that, under the assumption of a set cost for genotyping, one can calculate a "threshold cost" for phenotyping; when phenotyping costs per subject are less than this threshold, designs with more subjects will be more cost-effective than designs with more markers. This framework for determining a cost-effective study will aid in the planning of studies, especially if there are choices to be made with respect to phenotyping methods or study populations.     

Complex inheritance of ABCR mutations in Stargardt disease: linkage disequilibrium, complex alleles, and pseudodominance

Stargardt disease is a recessively transmitted disease caused by mutations in the ABCR gene. Linkage disequilibrium has recently been reported between a polymorphism, 2828 A, and a common Western European founder mutation, 2588 C. Here, we confirm this linkage disequilibrium in a North American population. We also describe two complex alleles involving the 2828 A and 2588 C alterations and suggest a possible order of clinical severity of mutations identified in trans to the complex alleles. Finally, we report pseudodominance of Stargardt disease in a family with the 2588 C mutation, further supporting a high frequency of carriers for ABCR mutations in our population.     

Combined linkage disequilibrium and linkage mapping: Bayesian multilocus approach

Quantitative trait loci (QTL) affecting the phenotype of interest can be detected using linkage analysis (LA), linkage disequilibrium (LD) mapping or a combination of both (LDLA). The LA approach uses information from recombination events within the observed pedigree and LD mapping from the historical recombinations within the unobserved pedigree. We propose the Bayesian variable selection approach for combined LDLA analysis for single-nucleotide polymorphism (SNP) data. The novel approach uses both sources of information simultaneously as is commonly done in plant and animal genetics, but it makes fewer assumptions about population demography than previous LDLA methods. This differs from approaches in human genetics, where LDLA methods use LA information conditional on LD information or the other way round. We argue that the multilocus LDLA model is more powerful for the detection of phenotype–genotype associations than single-locus LDLA analysis. To illustrate the performance of the Bayesian multilocus LDLA method, we analyzed simulation replicates based on real SNP genotype data from small three-generational CEPH families and compared the results with commonly used quantitative transmission disequilibrium test (QTDT). This paper is intended to be conceptual in the sense that it is not meant to be a practical method for analyzing high-density SNP data, which is more common. Our aim was to test whether this approach can function in principle.     

DMLE+: Bayesian linkage disequilibrium gene mapping

SUMMARY: The program DMLE+ allows Bayesian inference of the location of a gene carrying a mutation influencing a discrete trait (such as a disease) and/or other parameters of interest (such as mutation age) based on the observed linkage disequilibrium at multiple genetic markers. DMLE+ uses either individual marker genotypes, or haplotypes, integrates over uncertain population allele frequencies, and can incorporate prior information about gene location from an annotated human genome sequence. AVAILABILITY: DMLE+ is available in both Windows GUI and portable UNIX command line versions at http://dmle.org.     

International collaboration provides convincing linkage replication in complex disease through analysis of a large pooled data set: Crohn disease and chromosome 16

Numerous familial, non-Mendelian (i.e., complex) diseases have been screened by linkage analysis for regions harboring susceptibility genes. Except for rare, high-penetrance syndromes showing Mendelian inheritance, such as BRCA1 and BRCA2, most attempts have failed to produce replicable linkage findings. For example, in multiple sclerosis and other complex diseases, there have been many reports of significant linkage, followed by numerous failures to replicate. In inflammatory bowel disease (IBD), linkage to two regions has elsewhere been reported at genomewide significance levels: the pericentromeric region on chromosome 16 (IBD1) and chromosome 12q (IBD2). As with other complex diseases, the subsequent support for these localizations has been variable. In this article, we report the results of an international collaborative effort to investigate these putative localization by pooling of data sets that do not individually provide convincing evidence for linkage to these regions. Our results, generated by the genotyping and analysis of 12 microsatellite markers in 613 families, provide unequivocal replication of linkage for a common human disease: a Crohn disease susceptibility locus on chromosome 16 (maximum LOD score 5.79). Despite failure to replicate the previous evidence for linkage on chromosome 12, the results described herein indicate the need to further investigate the potential role of this locus in susceptibility to ulcerative colitis. This report provides a convincing example of the collaborative approach necessary to obtain the sample numbers required to achieve statistical power in studies of complex human traits.     

Linkage disequilibrium mapping of complex disease: fantasy or reality?

In the past year, data about the level and nature of linkage disequilibrium between alleles of tightly linked SNPs have started to become available. Furthermore, increasing evidence of allelic heterogeneity at the loci predisposing to complex disease has been observed, which has lead to initial attempts to develop methods of linkage disequilibrium detection allowing for this difficulty. It has also become more obvious that we will need to think carefully about the types of populations we need to analyze in an attempt to identify these elusive genes, and it is becoming clear that we need to carefully reevaluate the prognosis of the current paradigm with regard to its robustness to the types of problems that are likely to exist.     

Dissecting linkage disequilibrium in African-American genomes: roles of markers and individuals

Substantial increases of linkage disequilibrium (LD) both in magnitude and in range have been observed in recently admixed populations such as African-American (AfA). On the other hand, it has also been shown that LD in AfAs was very similar to that of African. In this study, we attempted to resolve these contradicting observations by conducting a systematic examination of the LD structure in AfAs by genotyping a sample of AfA individuals at 24,341 single nucleotide polymorphisms (SNPs) spanning almost the entire chromosome 21, with an average density of 1.5 kb/SNP. The overall LD in AfAs is similar to that in African populations and much less than that in European populations. Even when the ancestry-informative markers (AIMs) were used, extended LD in AfA was found to be limited to certain magnitude range (0.2 < or = r(2) < or = 0.8) and certain distance range, that is, between-marker distance more than 200 kb. Furthermore, the inclusion of AfA individuals with predominant African ancestry was found to reduce the overall magnitude of LD. Elevation of LD in the AfA population, compared with its parental populations, can only be observed at the markers with large allele frequency differences between 2 parental populations at limited scenario. AfA individuals of wholly African ancestry contribute little to the extended LD in the AfA population, and further genotyping or association analysis conducted using only admixed individuals may lead to higher statistical power and possibly reduced cost.     

A first insight into population structure and linkage disequilibrium in the US peanut minicore collection

Knowledge of genetic diversity, population structure, and degree of linkage disequilibrium (LD) in target association mapping populations is of great importance and is a prerequisite for LD-based mapping. In the present study, 96 genotypes comprising 92 accessions of the US peanut minicore collection, a component line of the tetraploid variety Florunner, diploid progenitors A. duranensis (AA) and A. ipaënsis (BB), and synthetic amphidiploid accession TxAG-6 were investigated with 392 simple sequence repeat (SSR) marker bands amplified using 32 highly-polymorphic SSR primer pairs. Both distance- and model-based (Bayesian) cluster analysis revealed the presence of structured diversity. In general, the wild-species accessions and the synthetic amphidiploid grouped separately from most minicore accessions except for COC155, and were eliminated from most subsequent analyses. UPGMA analysis divided the population into four subgroups, two major subgroups representing subspecies fastigiata and hypogaea, a third group containing individuals from each subspecies or possibly of mixed ancestry, and a fourth group, either consisting of COC155 alone if wild species were excluded, or of COC155, the diploid species, and the synthetic amphidiploid. Model-based clustering identified four subgroups- one each for fastigiata and hypogaea subspecies, a third consisting of individuals of both subspecies or of mixed ancestry predominantly from Africa or Asia, and a fourth group, consisting of individuals predominantly of var fastigiata, peruviana, and aequatoriana accessions from South America, including COC155. Analysis of molecular variance (AMOVA) revealed statistically-significant (P < 0.0001) genetic variance of 16.87% among subgroups. A total of 4.85% of SSR marker pairs revealed significant LD (at r² ≥ 0.1). Of the syntenic marker pairs separated by distances < 10 cM, 11–20 cM, 21–50 cM, and > 50 cM, 19.33, 5.19, 6.25 and 5.29% of marker pairs were found in strong LD (P ≤ 0.01), in accord with LD extending to great distances in self pollinated crops. A threshold value of r² > 0.035 was found to distinguish mean r² values of linkage distance groups statistically from the mean r² values of unlinked markers; LD was found to extend to 10 cM over the entire minicore collection by this criterion. However, there were large differences in r² values among marker pairs even among tightly-linked markers. The implications of these findings with regard to the possibility of using association mapping for detection of genome-wide SSR marker-phenotype association are discussed.     

Structure of the calmodulin alphaII-spectrin complex provides insight into the regulation of cell plasticity

AlphaII-spectrin is a major cortical cytoskeletal protein contributing to membrane organization and integrity. The Ca2+-activated binding of calmodulin to an unstructured insert in the 11th repeat unit of alphaII-spectrin enhances the susceptibility of spectrin to calpain cleavage but abolishes its sensitivity to several caspases and to at least one bacterially derived pathologic protease. Other regulatory inputs including phosphorylation by c-Src also modulate the proteolytic susceptibility of alphaII-spectrin. These pathways, acting through spectrin, appear to control membrane plasticity and integrity in several cell types. To provide a structural basis for understanding these crucial biological events, we have solved the crystal structure of a complex between bovine calmodulin and the calmodulin-binding domain of human alphaII-spectrin (Protein Data Bank ID code 2FOT). The structure revealed that the entire calmodulin-spectrin-binding interface is hydrophobic in nature. The spectrin domain is also unique in folding into an amphiphilic helix once positioned within the calmodulin-binding groove. The structure of this complex provides insight into the mechanisms by which calmodulin, calpain, caspase, and tyrosine phosphorylation act on spectrin to regulate essential cellular processes.     

Three-dimensional reconstruction of protein networks provides insight into human genetic disease

To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies.     

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.     

Efficient mining of haplotype patterns for linkage disequilibrium mapping

Effective identification of disease-causing gene locations can have significant impact on patient management decisions that will ultimately increase survival rates and improve the overall quality of health care. Linkage disequilibrium mapping is the process of finding disease gene locations through comparisons of haplotype frequencies between disease chromosomes and normal chromosomes. This work presents a new method for linkage disequilibrium mapping. The main advantage of the proposed algorithm, called LinkageTracker, is its consistency in producing good predictive accuracy under different conditions, including extreme conditions where the occurrence of disease samples with the mutation of interest is very low and there is presence of error or noise. We compared our method with some leading methods in linkage disequilibrium mapping such as HapMiner, Blade, GeneRecon, and Haplotype Pattern Mining (HPM). Experimental results show that for a substantial class of problems, our method has good predictive accuracy while taking reasonably short processing time. Furthermore, LinkageTracker does not require any population ancestry information about the disease and the genealogy of the haplotypes. Therefore, it is useful for linkage disequilibrium mapping when the users do not have such information about their datasets.     

Combination of linkage evidence in complex inheritance

The central problem of complex inheritance is to combine evidence from data that typically differ in markers, phenotypes, ascertainment, and other factors, without sacrificing the reliability that lods have given to linkage mapping for major loci. Here we evaluate 5 possible solutions on 200 replicates simulated in Genetic Analysis Workshop 10. Two methods differ from less efficient ones by distinguishing the tails of a normal distribution. Maximum likelihood scores (currently implemented only for the BETA model) and the approach of Self and Liang perform about as well as pooling samples, which is not feasible with heterogeneous data. With moderately heterogeneous data the Self and Liang method appears to be more efficient than maximum likelihood scores. Although improvements are being made in sample design and statistical analysis, the problem of combining linkage evidence from multiple data sets appears to have been solved. Allelic association presents different problems not yet addressed.     

Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution

Dominance (intralocus allelic interactions) plays often an important role in quantitative trait variation. However, few studies about dominance in QTL mapping have been reported in outbred animal or human populations. This is because common dominance effects can be predicted mainly for many full sibs, which do not often occur in outbred or natural populations with a general pedigree. Moreover, incomplete genotypes for such a pedigree make it infeasible to estimate dominance relationship coefficients between individuals. In this study, identity-by-descent (IBD) coefficients are estimated on the basis of population-wide linkage disequilibrium (LD), which makes it possible to track dominance relationships between unrelated founders. Therefore, it is possible to use dominance effects in QTL mapping without full sibs. Incomplete genotypes with a complex pedigree and many markers can be efficiently dealt with by a Markov chain Monte Carlo method for estimating IBD and dominance relationship matrices (D(RM)). It is shown by simulation that the use of D(RM) increases the likelihood ratio at the true QTL position and the mapping accuracy and power with complete dominance, overdominance, and recessive inheritance modes when using 200 genotyped and phenotyped individuals.     

The complete plastid genome provides insight into maternal plastid inheritance mode of the living fossil plant Ginkgo biloba

<正>The plastid is widely present in algae and plants with important functions in the process of photosynthesis,carbon fixation,and stress response (Shi et al.,2022).Despite the consistency between plastid genomes in plants,size variation of the plastid genome,gene loss,structure changes,and pseudogenes have been frequently observed (Ivanova et al.,2017).Plastid genome has currently shown a wide application in research of phylogeny,     

Joint linkage and linkage disequilibrium mapping of quantitative trait loci in natural populations

Linkage analysis and allelic association (also referred to as linkage disequilibrium) studies are two major approaches for mapping genes that control simple or complex traits in plants, animals, and humans. But these two approaches have limited utility when used alone, because they use only part of the information that is available for a mapping population. More recently, a new mapping strategy has been designed to integrate the advantages of linkage analysis and linkage disequilibrium analysis for genome mapping in outcrossing populations. The new strategy makes use of a random sample from a panmictic population and the open-pollinated progeny of the sample. In this article, we extend the new strategy to map quantitative trait loci (QTL), using molecular markers within the EM-implemented maximum-likelihood framework. The most significant advantage of this extension is that both linkage and linkage disequilibrium between a marker and QTL can be estimated simultaneously, thus increasing the efficiency and effectiveness of genome mapping for recalcitrant outcrossing species. Simulation studies are performed to test the statistical properties of the MLEs of genetic and genomic parameters including QTL allele frequency, QTL effects, QTL position, and the linkage disequilibrium of the QTL and a marker. The potential utility of our mapping strategy is discussed.     

Structure of acid beta-glucosidase with pharmacological chaperone provides insight into Gaucher disease

Gaucher disease results from mutations in the lysosomal enzyme acid beta-glucosidase (GCase). Although enzyme replacement therapy has improved the health of some affected individuals, such as those with the prevalent N370S mutation, oral treatment with pharmacological chaperones may be therapeutic in a wider range of tissue compartments by restoring sufficient activity of endogenous mutant GCase. Here we demonstrate that isofagomine (IFG, 1) binds to the GCase active site, and both increases GCase activity in cell lysates and restores lysosomal trafficking in cells containing N370S mutant GCase. We also compare the crystal structures of IFG-bound GCase at low pH with those of glycerol-bound GCase at low pH and apo-GCase at neutral pH. Our data indicate that IFG induces active GCase, which is secured by interactions with Asn370. The design of small molecules that stabilize substrate-bound conformations of mutant proteins may be a general therapeutic strategy for diseases caused by protein misfolding and mistrafficking.