The effect of pedigree complexity on quantitative trait linkage analysis

Proband Whole-Exome Sequencing Identified Genes Responsible for Autosomal Recessive Non-Syndromic Hearing Loss in 33 Chinese Nuclear Families

Autosomal recessive non-syndromic hearing loss (ARNSHL) is a highly heterogeneous disease involving more than 70 pathogenic genes. However, most ARNSHL families have small-sized pedigrees with limited genetic information, rendering challenges for the molecular diagnosis of these patients. Therefore, we attempted to establish a strategy for identifying deleterious variants associated with ARNSHL by applying proband whole-exome sequencing (proband-WES). Aside from desiring to improve molecular diagnostic rates, we also aimed to search for novel deafness genes shared by patients with similar phenotype, making up for the deficiency of small ARNSHL families. In this study, 48.5% (16/33) families were detected the pathogenic variants in eight known deafness genes, including 10 novel variants identified in TMPRSS3 (MIM 605551), MYO15A (MIM 602666), TMC1 (MIM 606706), ADGRV1 (MIM 602851), and PTPRQ (MIM 603317). Apart from six novel variants with a truncating effect (nonsense, deletion, insertion, and splice-site), four novel missense variants were not found in 200 unrelated control population by using Sanger sequencing. It is important to note that none of novel genes were shared across different pedigrees, indicating that a larger sample size might be needed. Proband-WES is a cost-effective and precise way of identifying causative variants in nuclear families with ARNSHL. This economical strategy may be appropriated as a clinical application to provide molecular diagnostics, genetic counseling, and individualized health maintenance measures for patients with ARNSHL at hearing clinics.

Contribution of Inbred Singletons to Variance Component Estimation of Heritability and Linkage

OBJECTIVES

An interesting consequence of consanguinity is that the inbred singleton becomes informative for genetic variance. We determine the contribution of an inbred singleton to variance component analysis of heritability and linkage.

METHODS

Statistical theory for the power of variance component analysis of quantitative traits is used to determine the expected contribution of an inbred singleton to likelihood-ratio tests of heritability and linkage.

RESULTS

In variance component models, an inbred singleton contributes relatively little to a test of heritability but can contribute substantively to a test of linkage. For small-to-moderate quantitative trait locus (QTL) effects and a level of inbreeding comparable to matings between first cousins (the preferred form of union in many human populations), an inbred singleton can carry nearly 25% of the information of a non-inbred sib pair. In more highly inbred contexts available with experimental animal populations, nonhuman primate colonies, and some human subpopulations, the contribution of an inbred singleton relative to a sib pair can exceed 50%.

CONCLUSIONS

Inbred individuals, even in isolation from other members of a sample, can contribute to variance component estimation and tests of heritability and linkage. Under certain conditions, the informativeness of the inbred singleton can approach that of a non-inbred sib pair.

Combinatorial Conflicting Homozygosity (CCH) analysis enables the rapid identification of shared genomic regions in the presence of multiple phenocopies

Background

The ability to identify regions of the genome inherited with a dominant trait in one or more families has become increasingly valuable with the wide availability of high throughput sequencing technology. While a number of methods exist for mapping of homozygous variants segregating with recessive traits in consanguineous families, dominant conditions are conventionally analysed by linkage analysis, which requires computationally demanding haplotype reconstruction from marker genotypes and, even using advanced parallel approximation implementations, can take substantial time, particularly for large pedigrees. In addition, linkage analysis lacks sensitivity in the presence of phenocopies (individuals sharing the trait but not the genetic variant responsible). Combinatorial Conflicting Homozygosity (CCH) analysis uses high density biallelic single nucleotide polymorphism (SNP) marker genotypes to identify genetic loci within which consecutive markers are not homozygous for different alleles. This allows inference of identical by descent (IBD) inheritance of a haplotype among a set or subsets of related or unrelated individuals.

Results

A single genome-wide conflicting homozygosity analysis takes <3 seconds and parallelisation permits multiple combinations of subsets of individuals to be analysed quickly. Analysis of unrelated individuals demonstrated that in the absence of IBD inheritance, runs of no CH exceeding 4 cM are not observed. At this threshold, CCH is >97% sensitive and specific for IBD regions within a pedigree exceeding this length and was able to identify the locus responsible for a dominantly inherited kidney disease in a Turkish Cypriot family in which six out 17 affected individuals were phenocopies. It also revealed shared ancestry at the disease-linked locus among affected individuals from two different Cypriot populations.

Conclusions

CCH does not require computationally demanding haplotype reconstruction and can detect regions of shared inheritance of a haplotype among subsets of related or unrelated individuals directly from SNP genotype data. In contrast to parametric linkage allowing for phenocopies, CCH directly provides the exact number and identity of individuals sharing each locus. CCH can also identify regions of shared ancestry among ostensibly unrelated individuals who share a trait. CCH is implemented in Python and is freely available (as source code) from http://sourceforge.net/projects/cchsnp/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1360-4) contains supplementary material, which is available to authorized users.

A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees

MOTIVATION

The use of dense single nucleotide polymorphism (SNP) data in genetic linkage analysis of large pedigrees is impeded by significant technical, methodological and computational challenges. Here we describe Superlink-Online SNP, a new powerful online system that streamlines the linkage analysis of SNP data. It features a fully integrated flexible processing workflow comprising both well-known and novel data analysis tools, including SNP clustering, erroneous data filtering, exact and approximate LOD calculations and maximum-likelihood haplotyping. The system draws its power from thousands of CPUs, performing data analysis tasks orders of magnitude faster than a single computer. By providing an intuitive interface to sophisticated state-of-the-art analysis tools coupled with high computing capacity, Superlink-Online SNP helps geneticists unleash the potential of SNP data for detecting disease genes.

RESULTS

Computations performed by Superlink-Online SNP are automatically parallelized using novel paradigms, and executed on unlimited number of private or public CPUs. One novel service is large-scale approximate Markov Chain-Monte Carlo (MCMC) analysis. The accuracy of the results is reliably estimated by running the same computation on multiple CPUs and evaluating the Gelman-Rubin Score to set aside unreliable results. Another service within the workflow is a novel parallelized exact algorithm for inferring maximum-likelihood haplotyping. The reported system enables genetic analyses that were previously infeasible. We demonstrate the system capabilities through a study of a large complex pedigree affected with metabolic syndrome.

AVAILABILITY

Superlink-Online SNP is freely available for researchers at http://cbl-hap.cs.technion.ac.il/superlink-snp. The system source code can also be downloaded from the system website.

CONTACT

omerw@cs.technion.ac.il

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identity by descent estimation with dense genome-wide genotype data

We present a novel method, IBDLD, for estimating the probability of identity by descent (IBD) for a pair of related individuals at a locus, given dense genotype data and a pedigree of arbitrary size and complexity. IBDLD overcomes the challenges of exact multipoint estimation of IBD in pedigrees of potentially large size and eliminates the difficulty of accommodating the background linkage disequilibrium (LD) that is present in high-density genotype data. We show that IBDLD is much more accurate at estimating the true IBD sharing than methods that remove LD by pruning SNPs and is highly robust to pedigree errors or other forms of misspecified relationships. The method is fast and can be used to estimate the probability for each possible IBD sharing state at every SNP from a high-density genotyping array for hundreds of thousands of pairs of individuals. We use it to estimate point-wise and genomewide IBD sharing between 185,745 pairs of subjects all of whom are related through a single, large and complex 13-generation pedigree and genotyped with the Affymetrix 500 k chip. We find that we are able to identify the true pedigree relationship for individuals who were misidentified in the collected data and estimate empirical kinship coefficients that can be used in follow-up QTL mapping studies. IBDLD is implemented as an open source software package and is freely available.

Identification of novel susceptibility loci for Guam neurodegenerative disease: challenges of genome scans in genetic isolates

Amyotrophic lateral sclerosis/parkinsonism-dementia complex (ALS/PDC) is a fatal neurodegenerative disease found in the Chamorro people of Guam and other Pacific Island populations. The etiology is unknown, although both genetic and environmental factors appear important. To identify loci for ALS/PDC, we conducted both genome-wide linkage and association analyses, using approximately 400 microsatellite markers, in the largest sample assembled to date, comprising a nearly complete sample of all living and previously sampled deceased cases. A single, large, complex pedigree was ascertained from a village on Guam, with smaller families and a case-control sample ascertained from the rest of Guam by population-based neurological screening and archival review. We found significant evidence for two regions with novel ALS/PDC loci on chromosome 12 and supportive evidence for the involvement of the MAPT region on chromosome 17. D12S1617 on 12p gave the strongest evidence of linkage (maximum LOD score, Z(max) = 4.03) in our initial scan, with additional support in the complete case-control sample in the form of evidence of allelic association at this marker and another nearby marker. D12S79 on 12q also provided significant evidence of linkage (Z(max) = 3.14) with support from flanking markers. Our results suggest that ALS/PDC may be influenced by as many as three loci, while illustrating challenges that are intrinsic in genetic analyses of isolated populations, as well as analytical strategies that are useful in this context. Elucidation of the genetic basis of ALS/PDC should improve our understanding of related neurodegenerative disorders including Alzheimer disease, Parkinson disease, frontotemporal dementia and ALS.

PedStr software for cutting large pedigrees for haplotyping, IBD computation and multipoint linkage analysis

We propose an automatic heuristic algorithm for splitting large pedigrees into fragments of no more than a user-specified bit size. The algorithm specifically aims to split large pedigrees where many close relatives are genotyped and to produce a set of sub-pedigrees for haplotype reconstruction, IBD computation or multipoint linkage analysis with the help of the Lander-Green-Kruglyak algorithm. We demonstrate that a set of overlapping pedigree fragments constructed with the help of our algorithm allows fast and effective haplotype reconstruction and detection of an allele's parental origin. Moreover, we compared pedigree fragments constructed with the help of our algorithm and existing programs PedCut and Jenti for multipoint linkage analysis. Our algorithm demonstrated significantly higher linkage power than the algorithm of Jenti and significantly shorter running time than the algorithm of PedCut. The software package PedStr implementing our algorithms is available at http://mga.bionet.nsc.ru/soft/index.html.

A multiple splitting approach to linkage analysis in large pedigrees identifies a linkage to asthma on chromosome 12

Large genealogies are potentially very informative for linkage analysis. However, the software available for exact non-parametric multipoint linkage analysis is limited with respect to the complexity of the families it can handle. A solution is to split the large pedigrees into sub-families meeting complexity constraints. Different methods have been proposed to "best" split large genealogies. Here, we propose a new procedure in which linkage is performed on several carefully chosen sub-pedigree sets from the genealogy instead of using just a single sub-pedigree set. Our multiple splitting procedure capitalizes on the sensitivity of linkage results to family structure and has been designed to control computational feasibility and global type I error. We describe and apply this procedure to the extreme case of the highly complex Hutterite pedigree and use it to perform a genome-wide linkage analysis on asthma. The detection of a genome-wide significant linkage for asthma on chromosome 12q21 illustrates the potential of this multiple splitting approach.

A genomewide screen for chronic rhinosinusitis genes identifies a locus on chromosome 7q

OBJECTIVE/HYPOTHESIS

Chronic rhinosinusitis (CRS) is an important public health problem with substantial impact on patient quality of life and health care costs. We hypothesized that genetic variation may be one factor that affects this disease.

STUDY DESIGN

Identification of genetic variation underlying susceptibility to CRS using linkage analysis in a founder population.

METHODS

We studied a religious isolate that practices a communal lifestyle and shares common environmental exposures. Using physical examination, medical interviews, and a review of medical records, we identified eight individuals with CRS of 291 screened. These eight individuals were related to each other in a single 60 member, nine generation pedigree. A genome-wide screen for loci influencing susceptibility to CRS using 1123 genome-wide markers was conducted.

RESULTS

The largest linkage peak (P = .0023; 127.15 cM, equivalent to limit of detection = 2.01) was on chromosome 7q31.1-7q32.1, 7q31 (127.15 cM; 1-limit of detection support region: 115-135 cM) and included the CFTR locus. Genotyping of 38 mutations in the CFTR gene did not reveal variation accounting for this linkage signal.

CONCLUSIONS

Understanding the genes involved in CRS may lead to improvements in its diagnosis and treatment. Our results represent the first genome-wide screen for CRS and suggest that a locus on 7q31.1-7q32.1 influences disease susceptibility. This may be the CFTR gene or another nearby locus.

An approach for cutting large and complex pedigrees for linkage analysis

Utilizing large pedigrees in linkage analysis is a computationally challenging task. The pedigree size limits applicability of the Lander-Green-Kruglyak algorithm for linkage analysis. A common solution is to split large pedigrees into smaller computable subunits. We present a pedigree-splitting method that, within a user supplied bit-size limit, identifies subpedigrees having the maximal number of subjects of interest (eg patients) who share a common ancestor. We compare our method with the maximum clique partitioning method using a large and complex human pedigree consisting of 50 patients with Alzheimer's disease ascertained from genetically isolated Dutch population. We show that under a bit-size limit our method can assign more patients to subpedigrees than the clique partitioning method, particularly when splitting deep pedigrees where the subjects of interest are scattered in recent generations and are relatively distantly related via multiple genealogic connections. Our pedigree-splitting algorithm and associated software can facilitate genome-wide linkage scans searching for rare mutations in large pedigrees coming from genetically isolated populations. The software package PedCut implementing our approach is available at http://mga.bionet.nsc.ru/soft/index.html.

Ignoring distant genealogic loops leads to false-positives in homozygosity mapping

Distant consanguineous loops are often unknown or ignored during homozygosity mapping analysis. This may potentially lead to an increased rate of false-positive linkage results. We show that failure to take into account the distant loops may seriously underestimate the degree of consanguinity, especially for people from genetically isolated populations; in 6 Alzheimer's disease (AD) patients the distant loops accounted for 57.7 % of inbreeding on average. Theoretical evaluation showed that ignoring distant loops, which account for 18-75% of inbreeding, inflates the frequency of false positive conclusions substantially in 2-point linkage analysis, up to several hundred times. In multipoint linkage analysis of the 6 AD patients a chromosome-wide "empirical" significance of 5% corresponded to a true false positive rate of 11.1%. We show that converting multiple loops to a hypothetical loop capturing all inbreeding may be a convenient solution to avoid false positive results. When extended genealogic data are not available a hypothetical loop may still be constructed based on genomic data.

New susceptibility locus for hypertension on chromosome 8q by efficient pedigree-breaking in an Italian isolate

Essential hypertension (EH) affects a large proportion of the adult population in Western countries and is a major risk factor for cardiovascular diseases. EH is a multifactorial disease with a complex genetic component. To tackle the complexity of this genetic component, we have initiated a study of Campora, an isolated village in South Italy. A random sample of 389 adults was genotyped for a very dense microsatellite genome scan and phenotyped for EH. Of this sample, 173 affected individuals were all related through a 2,180-member pedigree and could be integrated within a linkage analysis. The complexity of the pedigree prevented its direct use for a non-parametric linkage (NPL) analysis. Therefore, the method proposed by Falchi et al. [2004, Am. J. Hum. Genet., 75, 1015-1031] was used for automatic pedigree-breaking. We identified a new locus for EH on chromosome 8q22-23 and detected linkage with two known loci for EH: 1q42-43 and 4p16. Simulations showed that the linkage with 8q22-23 is highly genome-wide significant, even when accounting for the breaking of the pedigree. An extension to qualitative traits of another pedigree-breaking approach [Pankratz et al., 2001, Genet. Epidemiol., 21 (Suppl. 1), S258-S263] also detected a significant linkage on 8q22-23 using a remarkably different set of sub-pedigrees and helped to refine the location of the linkage signal. This work both identifies a new locus strongly linked to hypertension and shows that the power of linkage analysis can be improved by the appropriate use of efficient pedigree-breaking strategies.

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.

Inheritance of total serum IgE in the isolated Tangier Island population from Virginia: complexities associated with genealogical depth of pedigrees in segregation analyses

OBJECTIVES

This study was aimed at performing a segregation analysis of total serum immunoglobulin E (tIgE) in an isolated population using maximal genealogical information permitted by current software and computer capacities, while assessing the reliability of the best-fitting model of inheritance for tIgE through simulations.

METHODS

All current Tangier Island, VA, residents (n = 664) belonged to one large extended pedigree (n = 3,501) spanning 13 generations, with an average inbreeding coefficient of 0.009. Phenotype data were obtained on 453 (68.2%) of the residents using a population-based recruitment scheme. Due to computational limitations resulting from the extremely complex pedigree structure, analysis on only two pedigree reconstructions was feasible: a reduced pedigree retaining all phenotyped individuals and their parents as 57 distinct families, and 922 nuclear families.

RESULTS

Familial correlations and heritability calculations reveal a significant genetic component to tIgE in these data (heritability = 26%). The most parsimonious model to explain tIgE distribution indicated by the reduced pedigree structure was a two-distribution Mendelian model. However, larger and non-genetic models could not be rejected. Simulations over 200 replicates performed to evaluate the reliability of this model, indicated that using restricted genealogical information had minimal impact on results of segregation analyses performed here.

A genomewide search using an original pairwise sampling approach for large genealogies identifies a new locus for total and low-density lipoprotein cholesterol in two genetically differentiated isolates of Sardinia

A powerful approach to mapping the genes for complex traits is to study isolated founder populations, in which genetic heterogeneity and environmental noise are likely to be reduced and in which extended genealogical data are often available. Using graph theory, we applied an approach that involved sampling from the large number of pairwise relationships present in an extended genealogy to reconstruct sets of subpedigrees that maximize the useful information for linkage mapping while minimizing calculation burden. We investigated, through simulation, the properties of the different sets in terms of bias in identity-by-descent (IBD) estimation and power decrease under various genetic models. We applied this approach to a small isolated population from Sardinia, the village of Talana, consisting of a unique large and complex pedigree, and performed a genomewide search through variance-components linkage analysis for serum lipid levels. We identified a region of significant linkage on chromosome 2 for total serum cholesterol and low-density lipoprotein (LDL) cholesterol. Through higher-density mapping, we obtained an increased linkage for both traits on 2q21.2-q24.1, with a LOD score of 4.3 for total serum cholesterol and of 3.9 for LDL cholesterol. A replication study was performed in an independent and larger set from a genetically differentiated isolated population of the same region of Sardinia, the village of Perdasdefogu. We obtained consistent linkage to the region for total serum cholesterol (LOD score 1.4) and LDL cholesterol (LOD score 2.2), with a level of concordance uncommon for complex traits, and refined the location of the quantitative-trait locus. Interestingly, the 2q21.1-22 region has also been linked to premature coronary heart disease in Finns, and, in the adjacent 2q14 region, significant linkage with triglycerides has been reported in Hutterites.

Genómica de la regulación del peso corporal: mecanismos moleculares que predisponen a la obesidad

Obesity has become a worldwide public health problem which affects millions of people. Substantial progress has been made in elucidating the pathogenesis of energy homeostasis over the past few years. The fact that obesity is under strong genetic control has been well established. Twin, adoption and family studies have shown that genetic factors play a significant role in the pathogenesis of obesity. Human monogenic obesity is rare in large populations. The most common form of obesity is considered to be a polygenic disorder. New treatments are currently required for this common metabolic disease and type 2 diabetes. The identification of physiological and biochemical factors that underlie the metabolic disturbances observed in obesity is a key step in developing better therapeutic outcomes. The discovery of new genes and pathways involved in the pathogenesis of such a disease is critical to this process. However, identification of genes that contribute to the risk of developing the disease represents a significant challenge since obesity is a complex disease with many genetic and environmental causes. A number of diverse approaches have been used to discover and validate potential new genes for obesity. To date, DNA-based approaches using candidate genes and genome-wide linkage analysis have not had a great success in identifying genomic regions or genes involved in the development of these diseases. Recent advances in the ability to evaluate linkage analysis data from large family pedigrees (using variance components-based linkage analysis) show great promise in robustly identifying genomic regions associated with the development of obesity. Studying rare mutations in humans and animal models has provided fundamental insight into a complex physiological process, and has complemented population-based studies that seek to reveal primary causes. Remarkable progress has been made in both fronts and the pace of advance is likely to accelerate as functional genomics and the human genome project expand and mature. Approaches based on Mendelian and quantitative genetics may well converge, and ultimately lead to more rational and selective therapies.

Genomewide scan in families with schizophrenia from the founder population of Afrikaners reveals evidence for linkage and uniparental disomy on chromosome 1

We report on our initial genetic linkage studies of schizophrenia in the genetically isolated population of the Afrikaners from South Africa. A 10-cM genomewide scan was performed on 143 small families, 34 of which were informative for linkage. Using both nonparametric and parametric linkage analyses, we obtained evidence for a small number of disease loci on chromosomes 1, 9, and 13. These results suggest that few genes of substantial effect exist for schizophrenia in the Afrikaner population, consistent with our previous genealogical tracing studies. The locus on chromosome 1 reached genomewide significance levels (nonparametric LOD score of 3.30 at marker D1S1612, corresponding to an empirical P value of.012) and represents a novel susceptibility locus for schizophrenia. In addition to providing evidence for linkage for chromosome 1, we also identified a proband with a uniparental disomy (UPD) of the entire chromosome 1. This is the first time a UPD has been described in a patient with schizophrenia, lending further support to involvement of chromosome 1 in schizophrenia susceptibility in the Afrikaners.

Genome-wide scan in a large complex pedigree with predominantly male schizophrenics from the island of Kosrae: evidence for linkage to chromosome 2q

It is widely accepted that founder populations hold promise for mapping loci for complex traits. However, the outcome of these mapping efforts will most likely depend on the individual demographic characteristics and historical circumstances surrounding the founding of a given genetic isolate. The 'ideal' features of a founder population are currently unknown. The Micronesian islandic population of Kosrae, one of the four islands comprising the Federated States of Micronesia (FSM), was founded by a small number of settlers and went through a secondary genetic 'bottleneck' in the mid-19th century. The potential for reduced etiological (genetic and environmental) heterogeneity, as well as the opportunity to ascertain extended and statistically powerful pedigrees makes the Kosraen population attractive for mapping schizophrenia susceptibility genes. Our exhaustive case ascertainment from this islandic population identified 32 patients who met DSM-IV criteria for schizophrenia or schizoaffective disorder. Three of these were siblings in one nuclear family, and 27 were from a single large and complex schizophrenia kindred that includes a total of 251 individuals. One of the most startling findings in our ascertained sample was the great difference in male and female disease rates. A genome-wide scan provided initial suggestive evidence for linkage to markers on chromosomes 1, 2, 3, 7, 13, 15, 19, and X. Follow-up multipoint analyses gave additional support for a region on 2q37 that includes a schizophrenia locus previously identified in another small genetic isolate, with a well-established recent genealogical history and a small number of founders, located on the eastern border of Finland. In addition to providing further support for a schizophrenia susceptibility locus at 2q37, our results highlight the analytic challenges associated with extremely large and complex pedigrees, as well as the limitations associated with genetic studies of complex traits in small islandic populations.

Genes on chromosomes 1 and 13 have significant effects on Ascaris infection

Nematode parasites show a characteristic aggregated distribution among hosts. This observation has important implications for pathogenesis, immunology, and control of these infections, but the relative roles of environment and genetics in determining these patterns have remained uncertain. This paper presents the results of the first genome scan for susceptibility to infection with roundworm (Ascaris lumbricoides). Data on 375 genetic markers were generated for each of 444 members of a genetically isolated Nepalese population, the Jirels. Ascaris worm burden as assessed by egg counts was measured in these same individuals by using the Kato Katz thick smear method. The extensive genealogical data available for the population allowed assignment of all 444 individuals to a single pedigree that contained 6,209 pairs of relatives that were informative for genetic analysis. A variance components linkage analysis resulted in the unequivocal localization of two genes (one on chromosome 1 and another on chromosome 13) with clear, significant effects on susceptibility to Ascaris infection. This is the first evidence that individual quantitative trait loci influence variation in Ascaris burden in humans.

Quantitative-trait homozygosity and association mapping and empirical genomewide significance in large, complex pedigrees: fasting serum-insulin level in the Hutterites

We present methods for linkage and association mapping of quantitative traits for a founder population with a large, known genealogy. We detect linkage to quantitative-trait loci (QTLs) through a multipoint homozygosity-mapping method. We propose two association methods, one of which is single point and uses a general two-allele model and the other of which is multipoint and uses homozygosity by descent for a particular allele. In all three methods, we make extensive use of the pedigree and genotype information, while keeping the computations simple and efficient. To assess significance, we have developed a permutation-based test that takes into account the covariance structure due to relatedness of individuals and can be used to determine empirical genomewide and locus-specific P values. In the case of multivariate-normally distributed trait data, the permutation-based test is asymptotically exact. The test is broadly applicable to a variety of mapping methods that fall within the class of linear statistical models (e.g., variance-component methods), under the assumption of random ascertainment with respect to the phenotype. For obtaining genomewide P values, our proposed method is appropriate when positions of markers are independent of the observed linkage signal, under the null hypothesis. We apply our methods to a genome screen for fasting insulin level in the Hutterites. We detect significant genomewide linkage on chromosome 19 and suggestive evidence of QTLs on chromosomes 1 and 16.