Unexpected Relationships and Inbreeding in HapMap Phase III Populations

Correct annotation of the genetic relationships between samples is essential for population genomic studies, which could be biased by errors or omissions. To this end, we used identity-by-state (IBS) and identity-by-descent (IBD) methods to assess genetic relatedness of individuals within HapMap phase III data. We analyzed data from 1,397 individuals across 11 ethnic populations. Our results support previous studies (Pemberton et al., 2010; Kyriazopoulou-Panagiotopoulou et al., 2011) assessing unknown relatedness present within this population. Additionally, we present evidence for 1,657 novel pairwise relationships across 9 populations. Surprisingly, significant Cotterman''s coefficients of relatedness K1 (IBD1) values were detected between pairs of known parents. Furthermore, significant K2 (IBD2) values were detected in 32 previously annotated parent-child relationships. Consistent with a hypothesis of inbreeding, regions of homozygosity (ROH) were identified in the offspring of related parents, of which a subset overlapped those reported in previous studies (Gibson et al. 2010; Johnson et al. 2011). In total, we inferred 28 inbred individuals with ROH that overlapped areas of relatedness between the parents and/or IBD2 sharing at a different genomic locus between a child and a parent. Finally, 8 previously annotated parent-child relationships had unexpected K0 (IBD0) values (resulting from a chromosomal abnormality or genotype error), and 10 previously annotated second-degree relationships along with 38 other novel pairwise relationships had unexpected IBD2 (indicating two separate paths of recent ancestry). These newly described types of relatedness may impact the outcome of previous studies and should inform the design of future studies relying on the HapMap Phase III resource.     

Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices

Genomic selection based on the single-step genomic best linear unbiased prediction (ssGBLUP) approach is becoming an important tool in forest tree breeding. The quality of the variance components and the predictive ability of the estimated breeding values (GEBV) depends on how well marker-based genomic relationships describe the actual genetic relationships at unobserved causal loci. We investigated the performance of GEBV obtained when fitting models with genomic covariance matrices based on two identity-by-descent (IBD) and two identity-by-state (IBS) relationship measures. Multiple-trait multiple-site ssGBLUP models were fitted to diameter and stem straightness in five open-pollinated progeny trials of Eucalyptus dunnii, genotyped using the EUChip60K. We also fitted the conventional ABLUP model with a pedigree-based covariance matrix. Estimated relationships from the IBD estimators displayed consistently lower standard deviations than those from the IBS approaches. Although ssGBLUP based in IBS estimators resulted in higher trait-site heritabilities, the gain in accuracy of the relationships using IBD estimators has resulted in higher predictive ability and lower bias of GEBV, especially for low-heritability trait-site. ssGBLUP based on IBS and IBD approaches performed considerably better than the traditional ABLUP. In summary, our results advocate the use of the ssGBLUP approach jointly with the IBD relationship matrix in open-pollinated forest tree evaluation.Subject terms: Plant breeding, Genomics     

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.     

Nonparametric trend statistic incorporating dispersion differences in sib pair linkage for quantitative traits

The Haseman-Elston (HE) regression method and its extensions are widely used in genetic studies for detecting linkage to quantitative trait loci (QTL) using sib pairs. The principle underlying the simple HE regression method is that the similarity in phenotypes between two siblings increases as they share an increasing number of alleles identical by descent (IBD) from their parents at a particular marker locus. In such a procedure, similarity was identified with the locations, that is, means of groups of sib pairs sharing 0, 1, and 2 alleles IBD. A more powerful, rank-based nonparametric test to detect increasing similarity in sib pairs is presented by combining univariate trend statistics not only of locations, but also of dispersions of the squared phenotypic differences of two siblings for three groups. This trend test does not rely on distributional assumptions, and is applicable to the skewed or leptokurtic phenotypic distributions, in addition to normal or near normal phenotypic distributions. The performances of nonparametric trend statistics, including nonparametric regression slope, are compared with the HE regression methods as genetic linkage strategies.     

Preliminary Observations of Population Genetics and Relatedness of the Broadnose Sevengill Shark,Notorynchus cepedianus,in Two Northeast Pacific Estuaries

The broadnose sevengill shark, Notorynchus cepedianus, a common coastal species in the eastern North Pacific, was sampled during routine capture and tagging operations conducted from 2005–2012. One hundred and thirty three biopsy samples were taken during these research operations in Willapa Bay, Washington and in San Francisco Bay, California. Genotypic data from seven polymorphic microsatellites (derived from the related sixgill shark, Hexanchus griseus) were used to describe N. cepedianus genetic diversity, population structure and relatedness. Diversity within N. cepedianus was found to be low to moderate with an average observed heterozygosity of 0.41, expected heterozygosity of 0.53, and an average of 5.1 alleles per microsatellite locus. There was no evidence of a recent population bottleneck based on genetic data. Analyses of genetic differences between the two sampled estuaries suggest two distinct populations with some genetic mixing of sharks sampled during 2005–2006. Relatedness within sampled populations was high, with percent relatedness among sharks caught in the same area indicating 42.30% first-order relative relationships (full or half siblings). Estuary-specific familial relationships suggest that management of N. cepedianus on the U.S. West Coast should incorporate stock-specific management goals to conserve this ecologically important predator.     

Genomewide Association Studies for 50 Agronomic Traits in Peanut Using the ‘Reference Set’ Comprising 300 Genotypes from 48 Countries of the Semi-Arid Tropics of the World

Peanut is an important and nutritious agricultural commodity and a livelihood of many small-holder farmers in the semi-arid tropics (SAT) of world which are facing serious production threats. Integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. Therefore, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the ‘reference set’ of peanut. This study reports comprehensive analyses of allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in peanut. Distinctness of all the genotypes can be established by using either an unique allele detected by a single SSR or a combination of unique alleles by two or more than two SSR markers. As expected, DArT features (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSRs (22.21 alleles /locus, 0.715 PIC). Both marker types clearly differentiated the genotypes of diploids from tetraploids. Multi-allelic SSRs identified three sub-groups (K = 3) while the LD simulation trend line based on squared-allele frequency correlations (r²) predicted LD decay of 15–20 cM in peanut genome. Detailed analysis identified a total of 524 highly significant MTAs (pvalue >2.1×10–6) with wide phenotypic variance (PV) range (5.81–90.09%) for 36 traits. These MTAs after validation may be deployed in improving biotic resistance, oil/ seed/ nutritional quality, drought tolerance related traits, and yield/ yield components.     

Estimating the magnitude of genetic factors by calculating the genetic relative risk of stroke in first-ever lacunar stroke patients

Background

Positive family history of stroke is an independent risk factor for lacunar stroke. However, the magnitude of familial aggregation of a certain disease is better evaluated by the genetic relative risk. This is calculated by dividing the prevalence of specific disease in family members of patients by the prevalence of this disease in the general population. In a cohort of lacunar stroke patients, who were subtyped clinically and radiologically, we determined the genetic relative risk of stroke.

Methods

By questionnaire and additional interview, we obtained a complete first-degree family history of stroke. The prevalence of stroke in first-degree relatives of these lacunar stroke patients was compared to the self-reported prevalence of stroke in a Dutch community based cohort of elderly volunteers. Secondly, the influence of proband characteristics and family composition on parental and sibling history of stroke were evaluated.

Principal Findings

We collected data of 1066 first-degree relatives of 195 lacunar stroke patients. Strokes occurred in 13.5% of first-degree relatives. The genetic relative risk was 2.94 (95%CI 2.45–3.53) for overall first-degree relatives, 4.52 (95%CI 3.61–5.65) for patients'' parents and 2.10 (95%CI 1.63–2.69) for patients'' siblings. Age of proband and proband status for hypertension influenced the chance of having a parent with a history of stroke whereas the likelihood of having a concordant sibling increased with sibship size.

Conclusions

We found an increased genetic relative risk of stroke in first-degree relatives of patients with lacunar stroke. Our data warrant further genomic research in this well-defined high risk population for stroke.     

Isolation-by-distance in landscapes: considerations for landscape genetics

In landscape genetics, isolation-by-distance (IBD) is regarded as a baseline pattern that is obtained without additional effects of landscape elements on gene flow. However, the configuration of suitable habitat patches determines deme topology, which in turn should affect rates of gene flow. IBD patterns can be characterized either by monotonically increasing pairwise genetic differentiation (for example, F_ST) with increasing interdeme geographic distance (case-I pattern) or by monotonically increasing pairwise genetic differentiation up to a certain geographical distance beyond which no correlation is detectable anymore (case-IV pattern). We investigated if landscape configuration influenced the rate at which a case-IV pattern changed to a case-I pattern. We also determined at what interdeme distance the highest correlation was measured between genetic differentiation and geographic distance and whether this distance corresponded to the maximum migration distance. We set up a population genetic simulation study and assessed the development of IBD patterns for several habitat configurations and maximum migration distances. We show that the rate and likelihood of the transition of case-IV to case-I F_ST–distance relationships was strongly influenced by habitat configuration and maximum migration distance. We also found that the maximum correlation between genetic differentiation and geographic distance was not related to the maximum migration distance and was measured across all deme pairs in a case-I pattern and, for a case-IV pattern, at the distance where the F_ST–distance curve flattens out. We argue that in landscape genetics, separate analyses should be performed to either assess IBD or the landscape effects on gene flow.     

Graphics for relatedness research

Studies of relatedness have been crucial in molecular ecology over the last decades. Good evidence of this is the fact that studies of population structure, evolution of social behaviours, genetic diversity and quantitative genetics all involve relatedness research. The main aim of this article was to review the most common graphical methods used in allele sharing studies for detecting and identifying family relationships. Both IBS‐ and IBD‐based allele sharing studies are considered. Furthermore, we propose two additional graphical methods from the field of compositional data analysis: the ternary diagram and scatterplots of isometric log‐ratios of IBS and IBD probabilities. We illustrate all graphical tools with genetic data from the HGDP‐CEPH diversity panel, using mainly 377 microsatellites genotyped for 25 individuals from the Maya population of this panel. We enhance all graphics with convex hulls obtained by simulation and use these to confirm the documented relationships. The proposed compositional graphics are shown to be useful in relatedness research, as they also single out the most prominent related pairs. The ternary diagram is advocated for its ability to display all three allele sharing probabilities simultaneously. The log‐ratio plots are advocated as an attempt to overcome the problems with the Euclidean distance interpretation in the classical graphics.     

Efficiency of typing unaffected relatives in an affected-sib-pair linkage study with single-locus and multiple tightly linked markers.

In an affected-sib-pair study, the parents are often unavailable for typing, particularly for diseases of late onset. In many cases, however, it is possible to sample unaffected siblings. It is therefore desirable to assess the contribution of such siblings to the power of such a study. The likelihood ratio introduced by Risch and improved by Holmans was extended to incorporate data from unaffected siblings. Tests based on two likelihoods were considered: the full likelihood of the data, based on the identity-by-descent (IBD) sharing states of the entire sibship, and a pseudolikelihood based on the IBD sharing states of the affected pair only, using the unaffected siblings to infer parental genotypes. The latter approach was found to be more powerful, except when penetrance was high. Typing an unaffected sibling, or just one parent, was found to give only a small increase in power except when the PIC of the marker was low. Even then, typing an unaffected relative increased the overall number of individuals that had to be typed to achieve a given power. If there is no highly informative marker locus in the area under study, it may be possible to "build" one by combining the alleles from two or more neighboring tightly linked loci into haplotypes. Typing two loci gave a sizeable power increase over a single locus, but typing further loci gave much smaller gains. Building haplotypes will introduce phase uncertainties, with the result that such a system will yield less power than will a single locus with the same number of alleles. This power loss was small, however, and did not affect the conclusions regarding the worth of typing unaffected relatives.     

Using haplotypes for the prediction of allelic identity to fine-map QTL: characterization and properties

Background

Numerous methods have been developed over the last decade to predict allelic identity at unobserved loci between pairs of chromosome segments along the genome. These loci are often unobserved positions tested for the presence of quantitative trait loci (QTL). The main objective of this study was to understand from a theoretical standpoint the relation between linkage disequilibrium (LD) and allelic identity prediction when using haplotypes for fine mapping of QTL. In addition, six allelic identity predictors (AIP) were also compared in this study to determine which one performed best in theory and application.

Results

A criterion based on a simple measure of matrix distance was used to study the relation between LD and allelic identity prediction when using haplotypes. The consistency of this criterion with the accuracy of QTL localization, another criterion commonly used to compare AIP, was evaluated on a set of real chromosomes. For this set of chromosomes, the criterion was consistent with the mapping accuracy of a simulated QTL with either low or high effect. As measured by the matrix distance, the best AIP for QTL mapping were those that best captured LD between a tested position and a QTL. Moreover the matrix distance between a tested position and a QTL was shown to decrease for some AIP when LD increased. However, the matrix distance for AIP with continuous predictions in the [0,1] interval was algebraically proven to decrease less rapidly up to a lower bound with increasing LD in the simplest situations, than the discrete predictor based on identity by state between haplotypes (IBS _hap), for which there was no lower bound. The expected LD between haplotypes at a tested position and alleles at a QTL is a quantity that increases naturally when the tested position gets closer to the QTL. This behavior was demonstrated with pig and unrelated human chromosomes.

Conclusions

When the density of markers is high, and therefore LD between adjacent loci can be assumed to be high, the discrete predictor IBS _hap is recommended since it predicts allele identity correctly when taking LD into account.     

Genetic and immunologic aspects of type 1 diabetes mellitus

Prediction of type 1 diabetes mellitus (IDDM) and its identification in preclinical period is one of the central problems in modern medicine. They are based comprehensive genetic, immunologic and metabolic evaluations. We observed four hundred seven first-degree relatives of patients with IDDM (240 families in which one of the children or one of the parents had IDDM) have been included in the study. The study of HLA-DQA1, HLA-DQB1 polymorphic alleles and DRB1 genes and their combinations. The genetic study included searching HLA loci (HLA-DQA1, HLA-DQB1 polymorphic alleles and DRB1 genes) loci. To evaluate the genetic risk two approaches we used: first--carrying predisposing HLA-DQ alleles and DRB1-genes and it's combination (mainly associated in Russian population was DRB1*04-DQB1*0302, DRB1*04-DQA1*0301, DQA1*0301-DQB1*0302, DQA1*0301-DQB1*0302 and four susceptible alleles in A- and B- chains (Asp 57-, Arg 52+)) and second--IBD (identity by descent), in Russian population HLA-identical for 2 haplotypes sibs had risk of development of IDDM of 18%, for 1 haplotype--3%, for 0 haplotype-0.9%. The antibodies (ICA, IAA) prevalence rate has not depended on availability of predisposing HLA-DQ alleles and DRB1-genes and haploidentity of normal sibs and sibs with IDDM. However, GADA prevalence rate in groups having high predisposed alleles has been noticed as significantly higher (28.6%) comparing with 7.7% in groups that had no predisposing alleles (p < 0.05). The comparison of antibodies prevalence rate to sibs HLA-identity has shown the significant increase or GADA prevalence rate in group of siblings identical for one haplotype comparing with non-identical sibs (27.3% and 0% respectively, p < 0.001).     

Genetic analysis of kifafa, a complex familial seizure disorder.

Kifafa is the Swahili name for an epileptic seizure disorder, first reported in the early 1960s, that is prevalent in the Wapogoro tribe of the Mahenge region of Tanzania in eastern Africa. A 1990 epidemiological survey of seizure disorders in this region reported a prevalence in the range of 19/1,000-36/1,000, with a mean age at onset of 11.6 years; 80% of those affected had onset prior to 20 years of age. A team of investigators returned to Tanzania in 1992 and collected data on > 1,600 relatives of 26 probands in 20 kifafa families. We have undertaken a genetic analysis of these data in order to detect the presence of familial clustering and whether such aggregation could be attributed to genetic factors. Of the 127 affected individuals in these pedigrees, 23 are first-degree relatives (parent, full sibling, or offspring) of the 26 probands; 20 are second-degree relatives (half-sibling, grandparent, uncle, or aunt). When corrected for age, the risk to first-degree relatives is .15; the risk to second-degree relatives is .063. These risks are significantly higher than would be expected if there were no familial clustering. Segregation analysis, using PAP (rev.4.0), was undertaken to clarify the mode of inheritance. Among the Mendelian single-locus models, an additive model was favored over either a dominant, recessive, or codominant model. The single-locus model could be rejected when compared with the mixed Mendelian model (inclusion of a polygenic background), although the major-gene component tends to be recessive.(ABSTRACT TRUNCATED AT 250 WORDS)     

Analysis of the CC chemokine receptor 5 (CCR5) delta-32 polymorphism in inflammatory bowel disease

The inflammatory bowel diseases (IBD) Crohn's disease (CD) and ulcerative colitis (UC) are complex multifactorial traits involving both environmental and genetic factors. Recent studies have shown the important role of pro-inflammatory cytokines and chemokines, including RANTES, in IBD. RANTES is the natural ligand for the CC-chemokine receptor 5 (CCR5). The chromosomal location of the CCR5 gene on 3p21 coincides with an IBD-susceptibility locus identified by genome-wide scanning. A 32-bp deletion (A32) in the CCR5 gene results in a nonfunctional receptor and is found with high frequency in Caucasians. In this study, we investigated the presence of the CCR5delta32 allele in a large cohort of IBD patients and in a healthy control population. Blood samples were obtained from 538 unselected IBD cases (433 unrelated IBD patients: 289 CD, 142 UC, 2 indeterminate colitis; 105 affected first-degree relatives) and 135 unaffected first-degree family members. Of the IBD patients, 36% had familial IBD with at least two members being affected. There were no significant differences in the CCR5delta32 mutation frequency between IBD patients and healthy controls, nor between CD and UC patients. There was no correlation between the CCR5delta32 genotype and the age at IBD-diagnosis, the frequency of surgical intervention, or disease localization. Only the association between CCR5delta32 homozygosity and the presence of anal lesions in CD patients was statistically significant (P=0.007). Analysis by the transmission/disequilibrium test showed no significant transmission distortion to the probands or their clinically silent siblings. Based on these results, it is unlikely that the CCR5delta32 allele is an important marker for predisposition to IBD.     

The Immunogenetic Architecture of Autoimmune Disease

The development of most autoimmune diseases includes a strong heritable component. This genetic contribution to disease ranges from simple Mendelian inheritance of causative alleles to the complex interactions of multiple weak loci influencing risk. The genetic variants responsible for disease are being discovered through a range of strategies from linkage studies to genome-wide association studies. Despite the rapid advances in genetic analysis, substantial components of the heritable risk remain unexplained, either owing to the contribution of an as-yet unidentified, “hidden,” component of risk, or through the underappreciated effects of known risk loci. Surprisingly, despite the variation in genetic control, a great deal of conservation appears in the biological processes influenced by risk alleles, with several key immunological pathways being modified in autoimmune diseases covering a broad spectrum of clinical manifestations. The primary translational potential of this knowledge is in the rational design of new therapeutics to exploit the role of these key pathways in influencing disease. With significant further advances in understanding the genetic risk factors and their biological mechanisms, the possibility of genetically tailored (or “personalized”) therapy may be realized.Autoimmune diseases affect a significant proportion of the population, with >4% of the European population suffering from one or more of these disorders (Vyse and Todd 1996; Cooper et al. 2009; Eaton et al. 2010). Although all autoimmune diseases share similarities in the basic immunological mechanisms, in other aspects, such as clinical manifestation and age of onset, individual diseases vary widely. A few rare autoimmune diseases with Mendelian inheritance patterns within families occur including APS-1 (autoimmune polyendocrine syndrome type 1), IPEX (immunodysregulation, polyendocrinopathy, and enteropathy X-linked) syndrome, and ALPS (autoimmune lymphoproliferative syndrome). Most autoimmune diseases are, however, multifactorial in nature, with susceptibility controlled by multiple genetic and environmental factors.The genetic component of more common autoimmune diseases can be calculated in several different manners, including the sibling recurrence risk (λ_s) and the twin concordance rate. The sibling recurrence risk is the ratio of the lifetime risk in siblings of patients to the lifetime population risk, whereas the twin concordance rate measures the proportion of the siblings of affected twins that are also affected. Most common autoimmune diseases, such as multiple sclerosis (MS), type 1 diabetes (T1D), rheumatoid arthritis (RA), and inflammatory bowel disease (IBD) are characterized by a sibling recurrence risk between 6 and 20 (Vyse and Todd 1996), and concordance rates of 25%–50% in monozygotic twins and 2%–12% in dizygotic twins (Cooper et al. 1999). A substantial proportion of relatives may also have subclinical evidence of autoimmunity without developing clinically overt disease. For example, 19% of healthy siblings of MS patients show antibody production in the cerebrospinal fluid, compared to 4% of unrelated healthy controls (Haghighi et al. 2000), whereas 4% of healthy first-degree relatives display lesions that are indistinguishable from those seen in patients and are not seen in unrelated healthy controls (De Stefano et al. 2006). Furthermore, comorbidity with the development of several autoimmune diseases in the same patient and clustering of several autoimmune diseases within families above what is expected by chance appear common (Cooper et al. 2009; Zhernakova et al. 2009). Together these data show a strong genetic component to autoimmune disease development.     

Familial Correlations of Onset Age of Hepatocellular Carcinoma: A Population-Based Case-Control Family Study

Background

There was lack of evidence for familial aggregation in onset age of hepatocellular carcinoma (HCC) in Chinese population. We conducted a population-based case-control family study to examine familial correlation of age of HCC onset in Taixing, China.

Methods

A total of 202 cases and 202 matched controls as well as their relatives were included in the study. Lifetime cumulative risks of HCC were estimated using the Kaplan-Meier approach. Cross ratios (CRs) were obtained from stratified Cox proportional hazard models, to assess the familial correlation of onset age.

Results

The mean age of HCC onset was decreased as increasing number of HCC cases in a family. The onset age was the earliest for first-degree relatives, intermediate for second-degree relatives, and latest for non-blood relatives (spouse) (log-rank test, P<0.01). The onset age was significantly correlated between probands and their relatives. In stratified Cox proportional hazard models, the CRs for the probands versus their fathers, mothers, siblings and uncles/aunts were 6.25 (95% confidence interval (CI): 1.84–21.25), 9.81 (95% CI: 1.24–77.56), 6.22 (95% CI: 1.37–28.36) and 3.24 (95% CI: 1.26–8.33), respectively. After adjustment for hepatitis B virus infection, the CRs remained significant.

Conclusion

This current study suggested a significant correlation of onset age for HCC among blood relatives. Familial HCC cases yielded earlier age of onset and their relatives have higher HCC risk in early age, highlighting intensive surveillance should be start at an earlier age for individuals with family history of HCC.     

Constructing a linkage–linkage disequilibrium map using dominant-segregating markers

The relationship between linkage disequilibrium (LD) and recombination fraction can be used to infer the pattern of genetic variation and evolutionary process in humans and other systems. We described a computational framework to construct a linkage–LD map from commonly used biallelic, single-nucleotide polymorphism (SNP) markers for outcrossing plants by which the decline of LD is visualized with genetic distance. The framework was derived from an open-pollinated (OP) design composed of plants randomly sampled from a natural population and seeds from each sampled plant, enabling simultaneous estimation of the LD in the natural population and recombination fraction due to allelic co-segregation during meiosis. We modified the framework to infer evolutionary pasts of natural populations using those marker types that are segregating in a dominant manner, given their role in creating and maintaining population genetic diversity. A sophisticated two-level EM algorithm was implemented to estimate and retrieve the missing information of segregation characterized by dominant-segregating markers such as single methylation polymorphisms. The model was applied to study the relationship between linkage and LD for a non-model outcrossing species, a gymnosperm species, Torreya grandis, naturally distributed in mountains of the southeastern China. The linkage–LD map constructed from various types of molecular markers opens a powerful gateway for studying the history of plant evolution.     

Visualization of Shared Genomic Regions and Meiotic Recombination in High-Density SNP Data

Background

A fundamental goal of single nucleotide polymorphism (SNP) genotyping is to determine the sharing of alleles between individuals across genomic loci. Such analyses have diverse applications in defining the relatedness of individuals (including unexpected relationships in nominally unrelated individuals, or consanguinity within pedigrees), analyzing meiotic crossovers, and identifying a broad range of chromosomal anomalies such as hemizygous deletions and uniparental disomy, and analyzing population structure.

Principal Findings

We present SNPduo, a command-line and web accessible tool for analyzing and visualizing the relatedness of any two individuals using identity by state. Using identity by state does not require prior knowledge of allele frequencies or pedigree information, and is more computationally tractable and is less affected by population stratification than calculating identity by descent probabilities. The web implementation visualizes shared genomic regions, and generates UCSC viewable tracks. The command-line version requires pedigree information for compatibility with existing software and determining specified relationships even though pedigrees are not required for IBS calculation, generates no visual output, is written in portable C++, and is well-suited to analyzing large datasets. We demonstrate how the SNPduo web tool identifies meiotic crossover positions in siblings, and confirm our findings by visualizing meiotic recombination in synthetic three-generation pedigrees. We applied SNPduo to 210 nominally unrelated Phase I / II HapMap samples and, consistent with previous findings, identified six undeclared pairs of related individuals. We further analyzed identity by state in 2,883 individuals from multiplex families with autism and identified a series of anomalies including related parents, an individual with mosaic loss of chromosome 18, an individual with maternal heterodisomy of chromosome 16, and unexplained replicate samples.

Conclusions

SNPduo provides the ability to explore and visualize SNP data to characterize the relatedness between individuals. It is compatible with, but distinct from, other established analysis software such as PLINK, and performs favorably in benchmarking studies for the analyses of genetic relatedness.     

Identification of close relatives in the HUGO Pan-Asian SNP database

The HUGO Pan-Asian SNP Consortium has recently released a genome-wide dataset, which consists of 1,719 DNA samples collected from 71 Asian populations. For studies of human population genetics such as genetic structure and migration history, this provided the most comprehensive large-scale survey of genetic variation to date in East and Southeast Asia. However, although considered in the analysis, close relatives were not clearly reported in the original paper. Here we performed a systematic analysis of genetic relationships among individuals from the Pan-Asian SNP (PASNP) database and identified 3 pairs of monozygotic twins or duplicate samples, 100 pairs of first-degree and 161 second-degree of relationships. Three standardized subsets with different levels of unrelated individuals were suggested here for future applications of the samples in most types of population-genetics studies (denoted by PASNP1716, PASNP1640 and PASNP1583 respectively) based on the relationships inferred in this study. In addition, we provided gender information for PASNP samples, which were not included in the original dataset, based on analysis of X chromosome data.