Genomic mismatch scanning identifies human genomic DNA shared identical by descent

Population genetic inference from genomic sequence variation

Population genetics has evolved from a theory-driven field with little empirical data into a data-driven discipline in which genome-scale data sets test the limits of available models and computational analysis methods. In humans and a few model organisms, analyses of whole-genome sequence polymorphism data are currently under way. And in light of the falling costs of next-generation sequencing technologies, such studies will soon become common in many other organisms as well. Here, we assess the challenges to analyzing whole-genome sequence polymorphism data, and we discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection.

Power comparisons between similarity-based multilocus association methods, logistic regression, and score tests for haplotypes

Recently, a genomic distance-based regression for multilocus associations was proposed (Wessel and Schork [2006] Am. J. Hum. Genet. 79:792-806) in which either locus or haplotype scoring can be used to measure genetic distance. Although it allows various measures of genomic similarity and simultaneous analyses of multiple phenotypes, its power relative to other methods for case-control analyses is not well known. We compare the power of traditional methods with this new distance-based approach, for both locus-scoring and haplotype-scoring strategies. We discuss the relative power of these association methods with respect to five properties: (1) the marker informativity; (2) the number of markers; (3) the causal allele frequency; (4) the preponderance of the most common high-risk haplotype; (5) the correlation between the causal single-nucleotide polymorphism (SNP) and its flanking markers. We found that locus-based logistic regression and the global score test for haplotypes suffered from power loss when many markers were included in the analyses, due to many degrees of freedom. In contrast, the distance-based approach was not as vulnerable to more markers or more haplotypes. A genotype counting measure was more sensitive to the marker informativity and the correlation between the causal SNP and its flanking markers. After examining the impact of the five properties on power, we found that on average, the genomic distance-based regression that uses a matching measure for diplotypes was the most powerful and robust method among the seven methods we compared.

Relatedness mapping and tracts of relatedness for genome-wide data in the presence of linkage disequilibrium

Estimates of relatedness have several applications such as the identification of relatives or in identifying disease related genes through identity by descent (IBD) mapping. Here we present a new method for identifying IBD tracts among individuals from genome-wide single nucleotide polymorphisms data. We use a continuous time Markov model where the hidden states are the number of alleles shared IBD between pairs of individuals at a given position. In contrast to previous methods, our method accurately accounts for linkage disequilibrium using pairwise haplotype probabilities. The method provides a map of the local relatedness along the genome. We illustrate the potential of the method for mapping disease genes on a real data set, and show that the method has the potential to map causative disease mutations using only a handful of affected individuals. The new IBD mapping method provides considerable improvement in mapping power in natural populations compared to standard association mapping methods.

Robust physical methods that enrich genomic regions identical by descent for linkage studies: confirmation of a locus for osteogenesis imperfecta

BACKGROUND

The monogenic disease osteogenesis imperfecta (OI) is due to single mutations in either of the collagen genes ColA1 or ColA2, but within the same family a given mutation is accompanied by a wide range of disease severity. Although this phenotypic variability implies the existence of modifier gene variants, genome wide scanning of DNA from OI patients has not been reported. Promising genome wide marker-independent physical methods for identifying disease-related loci have lacked robustness for widespread applicability. Therefore we sought to improve these methods and demonstrate their performance to identify known and novel loci relevant to OI.

RESULTS

We have improved methods for enriching regions of identity-by-descent (IBD) shared between related, afflicted individuals. The extent of enrichment exceeds 10- to 50-fold for some loci. The efficiency of the new process is shown by confirmation of the identification of the Col1A2 locus in osteogenesis imperfecta patients from Amish families. Moreover the analysis revealed additional candidate linkage loci that may harbour modifier genes for OI; a locus on chromosome 1q includes COX-2, a gene implicated in osteogenesis.

CONCLUSION

Technology for physical enrichment of IBD loci is now robust and applicable for finding genes for monogenic diseases and genes for complex diseases. The data support the further investigation of genetic loci other than collagen gene loci to identify genes affecting the clinical expression of osteogenesis imperfecta. The discrimination of IBD mapping will be enhanced when the IBD enrichment procedure is coupled with deep resequencing.

Estimation of pairwise identity by descent from dense genetic marker data in a population sample of haplotypes

I present a new approach for calculating probabilities of identity by descent for pairs of haplotypes. The approach is based on a joint hidden Markov model for haplotype frequencies and identity by descent (IBD). This model allows for linkage disequilibrium, and the method can be applied to very dense marker data. The method has high power for detecting IBD tracts of genetic length of 1 cM, with the use of sufficiently dense markers. This enables detection of pairwise IBD between haplotypes from individuals whose most recent common ancestor lived up to 50 generations ago.

Detecting disease gene in DNA haplotype sequences by nonparametric dissimilarity test

Association studies for complex diseases based on haplotype data have received increasing attention in the last few years. A commonly used nonparametric method, which takes haplotype structure into consideration, is to use the U-statistic to compare the similarities between genetic compositions in the case and control populations. Although the method and its variants are convenient to use in practice, there are some areas where the tests cannot detect even large differences between cases and controls. To overcome this problem and enhance the power, we propose a new form of the weighted U-statistic, which directly compares the dissimilarity between the haplotype structures in the case and control populations. We show that this test statistic is asymptotically a linear combination of the absolute values of normal random variables under the null hypothesis, and shifts strictly toward the right under the alternative, and therefore has no blind areas of detection. Simulation studies indicate that our test statistic overcomes the weakness of the existing ones and is robust and powerful as well.

DNA reassociation using oscillating phenol emulsions

Reassociating double-stranded DNA from single-stranded components is necessary for many molecular genetics experiments. The choice of a DNA reassociation method is dictated by the complexity of the starting material. Reassociation of simple oligomers needs only slow cooling in an aqueous environment, whereas reannealing the many single-stranded DNAs of complex genomic mixtures requires both a phenol emulsion to accelerate DNA reassociation and dedicated equipment to maintain the emulsion. We present a method that is equally suitable for reassociating either simple or complex DNA mixtures. The Oscillating Phenol Emulsion Reassociation Technique (OsPERT) was primarily developed to prepare heteroduplex DNA from alkali-denatured high molecular weight human genomic DNA samples in which hundreds of thousands of fragments need to be reannealed, but the simplicity of the technique makes it practical for less demanding DNA reassociation applications.

Haplotypes in the gene encoding protein kinase c-beta (PRKCB1) on chromosome 16 are associated with autism

Autism is a developmental disorder characterized by impairments in social interaction and communication associated with repetitive patterns of interest or behavior. Autism is highly influenced by genetic factors. Genome-wide linkage and candidate gene association approaches have been used to try and identify autism genes. A few loci have repeatedly been reported linked to autism. Several groups reported evidence for linkage to a region on chromosome 16p. We have applied a direct physical identity-by-descent (IBD) mapping approach to perform a high-density (0.85 megabases) genome-wide linkage scan in 116 families from the AGRE collection. Our results confirm linkage to a region on chromosome 16p with autism. High-resolution single-nucleotide polymorphism (SNP) genotyping and analysis of this region show that haplotypes in the protein kinase c-beta gene are strongly associated with autism. An independent replication of the association in a second set of 167 trio families with autism confirmed our initial findings. Overall, our data provide evidence that the PRKCB1 gene on chromosome 16p may be involved in the etiology of autism.

Complex trait mapping in isolated populations: Are specific statistical methods required?

In this paper, we review the statistical methods that can be used in isolated populations to map genes involved in complex diseases. Our intention is to highlight the fact that if the features of population isolates may help in the identification of susceptibility factors for complex traits, the choice and design of methods for statistical analysis in these populations deserve particular care. We show that methods designed for outbred samples are generally not appropriate for isolated populations and could lead to false conclusions.

Direct IBD mapping: identical-by-descent mapping without genotyping

Direct identical-by-descent (IBD) mapping is a technique, that combines genomic mismatch scanning (GMS) and DNA microarray technology, for mapping regions shared IBD between two individuals without locus-by-locus genotyping or sequencing. The lack of reagents has limited its widespread application. In particular, two key reagents have been limiting, 1). mismatch repair proteins MutS, L and H, and 2). genomic microarrays for identifying the genomic locations of the GMS-selected IBD fragments. Here, we describe steps that optimized the procedure and resources that will facilitate the development of direct IBD mapping.

On the identification of disease mutations by the analysis of haplotype similarity and goodness of fit

The observation that haplotypes from a particular region of the genome differ between affected and unaffected individuals or between chromosomes transmitted to affected individuals versus those not transmitted is sound evidence for a disease-liability mutation in the region. Tests for differentiation of haplotype distributions often take the form of either Pearson's chi(2) statistic or tests based on the similarity among haplotypes in the different populations. In this article, we show that many measures of haplotype similarity can be expressed in the same quadratic form, and we give the general form of the variance. As we describe, these methods can be applied to either phase-known or phase-unknown data. We investigate the performance of Pearson's chi(2) statistic and haplotype similarity tests through use of evolutionary simulations. We show that both approaches can be powerful, but under quite different conditions. Moreover, we show that the power of both approaches can be enhanced by clustering rare haplotypes from the distributions before performing a test.

Microsatellite loci are not abundant in all arthropod genomes: analyses in the hard tick, Ixodes scapularis and the yellow fever mosquito, Aedes aegypti

Plasmid libraries enriched for microsatellites were generated in the tick, Ixodes scapularis and in the mosquito Aedes aegypti. Libraries were enriched for genomic DNA containing (AC)n, (AG)n, (ATG)n, (CAG)n, (TAG)n, (AAT)n, (CTGY)n or (GATA)n motifs. Clones containing each motif were sequenced in both species for PCR primer design. In I. scapularis, most primers amplified a single locus and alleles varied in the number of microsatellite repeats and segregated as codominant markers. In contrast (AC)n, (TAG)n and (GATA)n microsatellite loci extracted from Ae. aegypti appeared to be members of multigene families. A primer pair designed to amplify a particular TAG locus instead amplified many independently segregating loci, some of which did not contain TAG microsatellites. Alleles at the TAG loci segregated as dominant markers and there was limited evidence for length variation among alleles. These results suggest that microsatellite loci are not universally abundant in arthropod genomes nor do alleles always segregate as codominant markers.

PCR candidate region mismatch scanning: adaptation to quantitative, high-throughput genotyping

Linkage and association analyses were performed to identify loci affecting disease susceptibility by scoring previously characterized sequence variations such as microsatellites and single nucleotide polymorphisms. Lack of markers in regions of interest, as well as difficulty in adapting various methods to high-throughput settings, often limits the effectiveness of the analyses. We have adapted the Escherichia coli mismatch detection system, employing the factors MutS, MutL and MutH, for use in PCR-based, automated, high-throughput genotyping and mutation detection of genomic DNA. Optimal sensitivity and signal-to-noise ratios were obtained in a straightforward fashion because the detection reaction proved to be principally dependent upon monovalent cation concentration and MutL concentration. Quantitative relationships of the optimal values of these parameters with length of the DNA test fragment were demonstrated, in support of the translocation model for the mechanism of action of these enzymes, rather than the molecular switch model. Thus, rapid, sequence-independent optimization was possible for each new genomic target region. Other factors potentially limiting the flexibility of mismatch scanning, such as positioning of dam recognition sites within the target fragment, have also been investigated. We developed several strategies, which can be easily adapted to automation, for limiting the analysis to intersample heteroduplexes. Thus, the principal barriers to the use of this methodology, which we have designated PCR candidate region mismatch scanning, in cost-effective, high-throughput settings have been removed.

The genetics of essential hypertension

Essential hypertension is an escalating problem for industrialized populations. It is currently seen as a 'complex' genetic trait caused by multiple susceptibility genes the effects of which are modulated by gene-environment and gene-gene interactions. Nevertheless, the success to date in identifying these susceptibility genes has been very limited. A number of candidates has been proposed, but demonstrating consistently the linkage or association with hypertension has been problematic. The data for angiotensinogen is undoubtedly the most extensive and meta-analysis has confirmed a significant association overall, although the risk contributed by this gene appears to be modest (odds ratio of 1.2). Identifying further genes - probably conferring even smaller attributable risks - represents a major challenge for future developments in this area. This contrasts markedly with the success that has been achieved in the past 5 years in solving the molecular genetics of a number of rare familial hypertension syndromes. The true incidences of some of these disorders may be higher than first appreciated, but it is still unclear if the genes for these syndromes also play a part in essential hypertension. A more complete understanding of the genetic basis of essential hypertension should be possible in the coming years using new strategies that take advantage of the information provided by the human genome project. This knowledge will irrevocably change the way we approach this disease in terms of its diagnosis, risk assessment for end-points such as stroke and heart disease, and the customised treatment that might be offered in the future.

CIS--cloning of identical sequences between two complex genomes

Development of the methods permitting cloning of identical sequences between two sources of DNA can be very useful for many purposes, including isolation of disease genes. Here we describe a new method called CIS (cloning of identical sequences). A combination of digestion with MvnI, treatment with mung bean nuclease, UDG (uracil-DNA glycosylase) and PCR with 5'-methyl-dCTP and dUTP was used to isolate identical sequences between two micro-cell hybrid lines (MCH). In a control experiment, mouse MCH903.1 and MCH939.2 containing human chromosome 3 from different individuals, were compared using the CIS procedure. Only background fluorescence in-situ hybridization (FISH) was achieved. In another experiment, mouse MCH903.1, containing complete human chromosome 3, and rat MCH429.11, containing a part of human 3q from the same chromosome were compared. The experiment showed that the original MCH429.11 and the DNA purified using the CIS procedure had identical FISH patterns to human metaphase chromosomes, thus demonstrating the efficiency of CIS.

A resource of mapped human bacterial artificial chromosome clones

To date, despite the increasing number of genomic tools, there is no repository of ordered human BAC clones that covers entire chromosomes. This project presents a resource of mapped large DNA fragments that span eight human chromosomes at approximately 1-Mb resolution. These DNA fragments are bacterial artificial chromosome (BAC) clones anchored to sequence tagged site (STS) markers. This clone collection, which currently contains 759 mapped clones, is useful in a wide range of applications from microarray-based gene mapping to identification of chromosomal mutations. In addition to the clones themselves, we describe a database, GenMapDB (http://genomics.med.upenn.edu/genmapdb), that contains information about each clone in our collection.

The integration of microarray information in the drug development process

In the past year, microarray technologies have moved beyond the proof-of-principle stage. Microarrays are now being used for genome-wide expression monitoring, large-scale polymorphism screening and mapping, and for the evaluation of drug candidates.

Linkage-disequilibrium mapping without genotyping

Genomic mismatch scanning (GMS) is a technique that enriches for regions of identity by descent (IBD) between two individuals without the need for genotyping or sequencing. Regions of IBD selected by GMS are mapped by hybridization to a microarray containing ordered clones of genomic DNA from chromosomes of interest. Here we demonstrate the feasibility and efficacy of this form of linkage-mapping, using congenital hyperinsulinism (HI), an autosomal recessive disease, whose relatively high frequency in Ashkenazi Jews suggests a founder effect. The gene responsible (SUR1) encodes the sulfonylurea receptor, which maps to chromosome 11p15.1. We show that the combination of GMS and hybridization of IBD products to a chromosome-11 microarray correctly maps the HI gene to a 2-Mb region, thereby demonstrating linkage-disequilibrium mapping without genotyping.

Enrichment for loci identical-by-descent between pairs of mouse or human genomes by genomic mismatch scanning

Mapping genes that underlie complex genetic traits, including genes that determine susceptibility to common diseases, requires an efficient method for high-resolution genotyping. Single-nucleotide differences between pairs of allelic sequences from unrelated individuals occur approximately once in every kilobase. Genomic mismatch scanning (GMS), by analyzing numerous single-nucleotide polymorphisms in a single genome-wide step, offers a potentially powerful and efficient approach to linkage analysis. GMS, originally developed in a yeast system, is shown here to be applicable to the more complex mouse and human genomes.