The relationship between parental genetic or phenotypic divergence and progeny variation in the maize nested association mapping population

Appropriate selection of parents for the development of mapping populations is pivotal to maximizing the power of quantitative trait loci detection. Trait genotypic variation within a family is indicative of the family's informativeness for genetic studies. Accurate prediction of the most useful parental combinations within a species would help guide quantitative genetics studies. We tested the reliability of genotypic and phenotypic distance estimators between pairs of maize inbred lines to predict genotypic variation for quantitative traits within families derived from biparental crosses. We developed 25 families composed of ~200 random recombinant inbred lines each from crosses between a common reference parent inbred, B73, and 25 diverse maize inbreds. Parents and families were evaluated for 19 quantitative traits across up to 11 environments. Genetic distances (GDs) among parents were estimated with 44 simple sequence repeat and 2303 single-nucleotide polymorphism markers. GDs among parents had no predictive value for progeny variation, which is most likely due to the choice of neutral markers. In contrast, we observed for about half of the traits measured a positive correlation between phenotypic parental distances and within-family genetic variance estimates. Consequently, the choice of promising segregating populations can be based on selecting phenotypically diverse parents. These results are congruent with models of genetic architecture that posit numerous genes affecting quantitative traits, each segregating for allelic series, with dispersal of allelic effects across diverse genetic material. This architecture, common to many quantitative traits in maize, limits the predictive value of parental genotypic or phenotypic values on progeny variance.     

Linkage information content and efficiency of full-sib and half-sib designs for gene mapping

The accuracy of a genetic map depends on the amount of linkage information contained in the data set used for construction of the map. The amount of linkage information is related to the designs employed for linkage analysis. The purpose of this study was to provide general formulations for various genotyping schemes and family structures in order to evaluate the amount of linkage information in a data set. Linkage information content (LIC) was defined as the frequency of fully informative gametes, which are gametes from doubly heterozygous parents with known linkage phases. Depending on the design, LIC is based on two generations if the parental phases are determined statistically, or three generations if the parental phases are determined genetically. Different schemes were considered in deriving LIC: (1) genotyping of one parent or two parents, and (2) genotyping of two or three generation families. The LIC for a full-sib design was found to be generally greater than for a half-sib design but requires typing a large number of individuals when at least one locus has only two alleles. The efficiency of the full-sib design is reduced significantly if a sex-specific linkage map is sought.     

Linkage maps of microsatellite DNA markers for the Pacific oyster Crassostrea gigas

We constructed male and female consensus linkage maps for the Pacific oyster Crassostrea gigas, using a total of 102 microsatellite DNA markers typed in 11-day-old larvae from three families. We identified 11 and 12 linkage groups in the male and female consensus maps, respectively. Alignment of these separate maps, however, suggests 10 linkage groups, which agrees with the haploid chromosome number. The male linkage map comprises 88 loci and spans 616.1 cM, while the female map comprises 86 loci and spans 770.5 cM. The male and the female maps share 74 loci; 2 markers remain unlinked. The estimated coverages for the consensus linkage maps are 79% for the male and 70-75% for the female, on the basis of two estimates of genome length. Ninety-five percent of the genome is expected to lie within 16 and 21 cM of markers on the male and female maps, respectively, while 95% of simulated minimum distances to the male and female maps are within 10.1 and 13.6 cM, respectively. Females have significantly more recombination than males, across 118 pairs of linked markers in common to the parents of the three families. Significant differences in recombination and orders of markers are also evident among same-sex parents of different families as well as sibling parents of opposite sex. These observations suggest that polymorphism for chromosomal rearrangements may exist in natural populations, which could have profound implications for interpreting the evolutionary genetics of the oyster. These are the first linkage maps for a bivalve mollusc that use microsatellite DNA markers, which should enable them to be transferred to other families and to be useful for further genetic analyses such as QTL mapping.     

Detection of linkage between quantitative trait loci and restriction fragment length polymorphisms using inbred lines

Summary In segregating populations, large numbers of individuals are needed to detect linkage between markers, such as restriction fragment length polymorphisms (RFLPs), and quantitative trait loci (QTL), limiting the potential use of such markers for detecting linkage. Fewer individuals from inbred lines are needed to detect linkage. Simulation data were used to test the utility of two methods to detect linkage: maximum likelihood and comparison of marker genotype means. When there is tight linkage, the two methods have similar power, but when there is loose linkage, maximum likelihood is much more powerful. Once inbred lines have been established, they can be screened rapidly to detect QTL for several traits simultaneously. If there is sufficient coverage of the genome with RFLPs, several QTL for each trait may be detected.     

Incorporating genotypes of relatives into a test of linkage disequilibrium.

Genetic data from autosomal loci in diploids generally consist of genotype data for which no phase information is available, making it difficult to implement a test of linkage disequilibrium. In this paper, we describe a test of linkage disequilibrium based on an empirical null distribution of the likelihood of a sample. Information on the genotypes of related individuals is explicitly used to help reconstruct the gametic phase of the independent individuals. Simulation studies show that the present approach improves on estimates of linkage disequilibrium gathered from samples of completely independent individuals but only if some offspring are sampled together with their parents. The failure to incorporate some parents sharply decreases the sensitivity and accuracy of the test. Simulations also show that for multiallelic data (more than two alleles) our testing procedure is not as powerful as an exact test based on known haplotype frequencies, owing to the interaction between departure from Hardy-Weinberg equilibrium and linkage disequilibrium.     

PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals

A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER's advantages over other packages by example.     

Detection of parent-of-origin effects based on complete and incomplete nuclear families with multiple affected children

Parent-of-origin effects are important in studying genetic traits. More than 1% of all mammalian genes are believed to show parent-of-origin effects. Some statistical methods may be ineffective or fail to detect linkage or association for a gene with parent-of-origin effects. Based on case-parents trios, the parental-asymmetry test (PAT) is simple and powerful in detecting parent-of-origin effects. However, it is common in practice to collect nuclear families with both parents as well as nuclear families with only one parent. In this paper, when only one parent is available for each family with an arbitrary number of affected children, we firstly develop a new test statistic 1-PAT to test for parent-of-origin effects in the presence of association between an allele at the marker locus under study and a disease gene. Then we extend the PAT to accommodate complete nuclear families each with one or more affected children. Combining families with both parents and families with only one parent, the C-PAT is proposed to detect parent-of-origin effects. The validity of the test statistics is verified by simulation in various scenarios of parameter values. A power study shows that using the additional information from incomplete nuclear families in the analysis greatly improves the power of the tests, compared to that based on only complete nuclear families. Also, utilizing all affected children in each family, the proposed tests have a higher power than when only one affected child from each family is selected. Additional power comparison also demonstrates that the C-PAT is more powerful than a number of other tests for detecting parent-of-origin effects.     

Circadian and Ultradian Periodicities of Grooming Behavior in Family Groups of Common Marmosets (Callithrix jacchus) in Captivity

Three families' groups of common marmosets were observed to describe the characteristics of their grooming rhythmicity, as the duration of the episodes of self- and social grooming made and received by the animals, in captivity under natural environmental conditions. Data were collected by focal animal sampling, at 20 min hourly intervals during 16 non-consecutive days, from January to March in 1994 (sunrise: 05:24 h ± 2 min; sunset: 17:34 h ± 1 min). Time series were obtained for each individual and for each family through hourly duration of grooming. Family time serie was obtained through the mean of its individuals time series. Spectral analysis revealed statistically significant circadian rhythms for all families and individuals. Ultradian components were detected in 50% of the families and in 46.7% of the animals. Acrophases of self- and social grooming calculated by Single Cosinor took place between 9:21 h and 10:39 h, for the families. For individuals self- and social grooming made and received, acrophases occurred from 8:35 h to 12:43 h. The confidence limits of acrophases did not show differences between the families and the individuals within the families, irrespective of their sex, age and reproductive condition, suggesting that this behavior has a stronger temporal marking. Grooming has circadian and ultradian components of rhythmicity in captive families' groups of common marmosets, under natural environmental conditions. Since only some animals showed the ultradian component, it may be consequence of social or environmental masking, or yet phenotypic plasticity of temporal genotype. Further studies are needed to test these possibilities.     

Genomewide significant linkage to stuttering on chromosome 12

Stuttering is a common and sometimes severe communication disorder, of unknown primary etiology, that exists in populations worldwide. Many types of evidence suggest a genetic contribution to stuttering; however, the complex inheritance of this disorder has hindered identification of these factors. We have employed highly inbred families to increase the power of linkage analysis of this disorder. Forty-four Pakistani families with documented or probable consanguinity, from the city of Lahore and surrounding areas, were included. Each family contained multiple cases of stuttering, which were diagnosed using the Stuttering Severity Instrument. Using the Marshfield Weber 9 marker panel, we performed a genomewide linkage scan focused on affected individuals and their parents. The analysis included 199 genotyped individuals, 144 affected and 55 unaffected. The Pedigree Relationship Statistical Test (PREST) was used to identify pedigrees that required additional specification of inbreeding. Initial nonparametric analysis gave evidence of linkage on chromosomes 1, 5, 7, and 12. Additional genotyping was performed on chromosome 12 to a 5-cM level of resolution, and 16 additional individuals were then included, bringing the number of families to 46. Analysis of the enlarged data set provided consistent evidence of linkage on chromosome 12: the S(homoz) scoring function gave a nonparametric LOD score of 4.61, and a LOD score of 3.51 was obtained using the S(all) scoring function. These results suggest that a locus on chromosome 12q may contain a gene with a large effect in this sample.     

A test for linkage and association in general pedigrees: the pedigree disequilibrium test

Family-based tests of linkage disequilibrium typically are based on nuclear-family data including affected individuals and their parents or their unaffected siblings. A limitation of such tests is that they generally are not valid tests of association when data from related nuclear families from larger pedigrees are used. Standard methods require selection of a single nuclear family from any extended pedigrees when testing for linkage disequilibrium. Often data are available for larger pedigrees, and it would be desirable to have a valid test of linkage disequilibrium that can use all potentially informative data. In this study, we present the pedigree disequilibrium test (PDT) for analysis of linkage disequilibrium in general pedigrees. The PDT can use data from related nuclear families from extended pedigrees and is valid even when there is population substructure. Using computer simulations, we demonstrated validity of the test when the asymptotic distribution is used to assess the significance, and examined statistical power. Power simulations demonstrate that, when extended pedigree data are available, substantial gains in power can be attained by use of the PDT rather than existing methods that use only a subset of the data. Furthermore, the PDT remains more powerful even when there is misclassification of unaffected individuals. Our simulations suggest that there may be advantages to using the PDT even if the data consist of independent families without extended family information. Thus, the PDT provides a general test of linkage disequilibrium that can be widely applied to different data structures.     

A computer simulation study on the number of loci and trees required to estimate genetic variability in cacao (Theobroma cacao L.)

Current methods for measures of genetic diversity of populations and germplasm collections are often based on statistics calculated from molecular markers. The objective of this study was to investigate the precision and accuracy of the most common estimators of genetic variability and population structure, as calculated from simple sequence repeat (SSR) marker data from cacao (Theobroma cacao L.). Computer simulated genomes of replicate populations were generated from initial allele frequencies estimated using SSR data from cacao accessions in a collection. The simulated genomes consisted of ten linkage groups of 100 cM in length each. Heterozygosity, gene diversity and the F statistics were studied as a function of number of loci and trees sampled. The results showed that relatively small random samples of trees were needed to achieve consistency in the observed estimations. In contrast, very large random samples of loci per linkage group were required to enable reliable inferences on the whole genome. Precision of estimates was increased by more than 50% with an increase in sample size from one to five loci per linkage group or 50 per genome, and up to 70% with ten loci per linkage group, or equivalently, 100 loci per genome. The use of fewer, highly polymorphic loci to analyze genetic variability led to estimates with substantially smaller variance but with an upward bias. Nevertheless, the relative differences of estimates among populations were generally consistent for the different levels of polymorphism considered.     

Use of microsatellite loci to classify individuals by relatedness

This study investigates the use of microsatellite loci for estimating relatedness between individuals in wild, outbred, vertebrate populations. We measured allele frequencies at 20 unlinked, dinucleotide-repeat microsatellite loci in a population of wild mice ( Mus musculus ), and used these observed frequencies to generate the expected distributions of pairwise relatedness among full sib, half sib, and unrelated pairs of individuals, as would be estimated from the microsatellite data. In this population one should be able to discriminate between unrelated and full-sib dyads with at least 97% accuracy, and to discriminate half-sib pairs from unrelated pairs or from full-sib pairs with better than 80% accuracy. If one uses the criterion that parent-offspring pairs must share at least one allele per locus, then only 15% of full-sib pairs, 2% of half-sib pairs, and 0% of unrelated pairs in this population would qualify as potential parent-offspring pairs. We verified that the simulation results (which assume a random mating population in Hardy-Weinberg and linkage equilibrium) accurately predict results one would obtain from this population in real life by scoring laboratory-bred full- and half-sib families whose parents were wild-caught mice from the study population. We also investigated the effects of using different numbers of loci, or loci of different average heterozygosities ( He ), on misclassification frequencies. Both variables have strong effects on misclassification rate. For example, it requires almost twice as many loci of He = 0.62 to achieve the same accuracy as a given number of loci of He = 0.75. Finally, we tested the ability of UPGMA clustering to identify family groups in our population. Clustering of allele matching scores among the offspring of four sets of independent maternal half sibships (four females, each mated to two different males) perfectly recovered the true family relationships.     

Effect of genotyping error on type-I error rate of affected sib pair studies with genotyped parents

OBJECTIVE: In affected sib pair studies without genotyped parents the effect of genotyping error is generally to reduce the type I error rate and power of tests for linkage. The effect of genotyping error when parents have been genotyped is unknown. We investigated the type I error rate of the single-point Mean test for studies in which genotypes of both parents are available. METHODS: Datasets were simulated assuming no linkage and one of five models for genotyping error. In each dataset, Mendelian-inconsistent families were either excluded or regenotyped, and then the Mean test applied. RESULTS: We found that genotyping errors lead to an inflated type I error rate when inconsistent families are excluded. Depending on the genotyping-error model assumed, regenotyping inconsistent families has one of several effects. It may produce the same type I error rate as if inconsistent families are excluded; it may reduce the type I error, but still leave an anti-conservative test; or it may give a conservative test. Departures of the type I error rate from its nominal level increase with both the genotyping error rate and sample size. CONCLUSION: We recommend that markers with high error rates either be excluded from the analysis or be regenotyped in all families.     

Estimating allelic number and identity in state of QTLs in interconnected families

When multiple related families derived from inbred lines are jointly analysed to detect quantitative trait loci (QTLs), the analysis should estimate allelic effects as accurately as possible and estimate the probability that different parents carry alleles that are identical in state. Analyses exist that assume that all parents carry unique alleles or that all parents but one carry the same allele. In practice, many configurations are possible that group different parents according to their identity-in-state condition at a putative QTL allele. Here, we propose a variable model Bayesian analysis that selects among possible identity-in-state configurations and jointly estimates the allelic effects of identical-in-state parents. We contrast this analysis with a fixed model analysis that estimates unique allelic effects for all parents. We analyse two simulated mating designs: an experimental design in which three inbred parents were crossed to generate two families of 150 doubled haploid lines; and a breeding design in which 20 inbred parents were crossed to generate 60 families of 20 doubled haploid lines, with each parent contributing to six families. In all cases where some parents were simulated to carry alleles of identical effect (that is, they were identical in state), the variable analysis estimated allelic effects with lower mean-squared error than the fixed analysis. The variable analysis showed that, unless each family contains many individuals (more than 100), there is insufficient information in DNA-marker and phenotypic data to determine with high probability the QTL allelic number.     

Accounting for linkage in family-based tests of association with missing parental genotypes

In studies of complex diseases, a common paradigm is to conduct association analysis at markers in regions identified by linkage analysis, to attempt to narrow the region of interest. Family-based tests for association based on parental transmissions to affected offspring are often used in fine-mapping studies. However, for diseases with late onset, parental genotypes are often missing. Without parental genotypes, family-based tests either compare allele frequencies in affected individuals with those in their unaffected siblings or use siblings to infer missing parental genotypes. An example of the latter approach is the score test implemented in the computer program TRANSMIT. The inference of missing parental genotypes in TRANSMIT assumes that transmissions from parents to affected siblings are independent, which is appropriate when there is no linkage. However, using computer simulations, we show that, when the marker and disease locus are linked and the data set consists of families with multiple affected siblings, this assumption leads to a bias in the score statistic under the null hypothesis of no association between the marker and disease alleles. This bias leads to an inflated type I error rate for the score test in regions of linkage. We present a novel test for association in the presence of linkage (APL) that correctly infers missing parental genotypes in regions of linkage by estimating identity-by-descent parameters, to adjust for correlation between parental transmissions to affected siblings. In simulated data, we demonstrate the validity of the APL test under the null hypothesis of no association and show that the test can be more powerful than the pedigree disequilibrium test and family-based association test. As an example, we compare the performance of the tests in a candidate-gene study in families with Parkinson disease.     

Haplotype reconstruction and estimation of haplotype frequencies from nuclear families with only one parent available

Recent literature has suggested that haplotype inference through close relatives, especially from nuclear families can be an alternative strategy in determining the linkage phase. In this paper, haplotype reconstruction and estimation of haplotype frequencies via expectation maximization (EM) algorithm including nuclear families with only one parent available is proposed. Parent and his (her) child are treated as parent-child pair with one shared haplotype. This reduces the number of potential haplotype pairs for both parent and child separately, resulting in a higher accuracy of the estimation. In a series of simulations, the comparisons of PHASE, GENEHUNTER, EM-based approach for complete nuclear families and our approach are carried out. In all situations, EM-based approach for trio data is comparable but slightly worse error rate than PHASE, our approach is slightly better and much faster than PHASE for incomplete trios, the performance of GENEHUNTER is very bad in simple nuclear family settings and dramatically decreased with the number of markers being increased. On the other hand, the comparison result of different sampling designs demonstrates that sampling trios is the most efficient design to estimate haplotype frequencies in populations under same genotyping cost.     

An extension of the admixture test for the study of genetic heterogeneity in hereditary multiple exostoses

Hereditary multiple exostoses (EXT) is an autosomal dominant disorder characterized by the presence of multiple cartilage-capped exostoses in the juxta-epiphyseal regions of the long bones. EXT is heterogeneous with at least three different locations currently having been identified on chromosomes 8, 11 and 19. We have tested a series of 29 EXT families for possible linkage to the three disease loci and estimated the probability of linkage of the disease to each locus in our series, by using an extension of the admixture test, which makes modelling of heterogeneous monogenic disease feasible. The maximum likelihood was obtained for proportions of 44%, 28% and 28% of families being linked to chromosome 8, 11 and 19, respectively. The a posteriori probability of linkage of the disease to EXT1, EXT2 and EXT3 was greater than 80% for 8/29, 5/29 and 3/29 families, respectively, and did not give evidence of a fourth locus for the disease. The present approach can be generalized to the investigation of genetic heterogeneity in other monogenic diseases, as it simultaneously estimates the location of each disease gene and the proportion of families linked to each locus. Received: 28 May 1996 / Revised: 7 October 1996     

Polymorphic DNA haplotypes at the phenylalanine hydroxylase (PAH) locus in Asian families with phenylketonuria (PKU)

DNA polymorphisms at the phenylalanine hydroxylase (PAH) locus have proved highly effective in linkage diagnosis of phenylketonuria (PKU) in Caucasian families. More than 10 RFLP sites have been reported within the PAH structural locus in Caucasians. With information from affected and unaffected offspring in PKU families it is often possible to reconstruct complete RFLP haplotypes in parents and to use these haplotypes to follow the segregation of PKU within families and to determine the distribution of PKU chromosomes within populations. To establish the utility of these RFLPs in characterizing Asian families with PKU, we typed eight DNA sites in 21 Chinese families and 12 Japanese families with classical PKU. The eight RFLPs were chosen for their informativeness in Caucasians. From these families we reconstructed a total of 91 complete PAH haplotypes, 44 from non-PKU chromosomes and 47 from PKU-bearing chromosomes. Although all eight marker sites are polymorphic in both Chinese and Japanese, there is much less haplotypic variation in Asians than in Caucasians. In particular, one haplotype alone, haplotype 4, accounts for more than 77% of non-PKU chromosomes and for more than 80% of PKU-bearing chromosomes. Haplotype 4 is also relatively common in Caucasians. The next most common Asian haplotype is 10 times less frequent than haplotype 4. By contrast, in many Caucasian populations the sum of the frequencies of the five most common haplotypes is still less than 80%, and several of the most common haplotypes are equally frequent. Even though the extent of haplotypic variation in Asians is severely limited, the few haplotypes that are found often differ at a number of RFLP sites.(ABSTRACT TRUNCATED AT 250 WORDS)     

Design and analysis of admixture mapping studies

Admixture between populations originating on different continents can be exploited to detect disease susceptibility loci at which risk alleles are distributed differentially between these populations. We first examine the statistical power and mapping resolution of this approach in the limiting situation in which gamete admixture and locus ancestry are measured without uncertainty. We show that, for a rare disease, the most efficient design is to study affected individuals only. In a typical African American population (two-way admixture proportions 0.8/0.2, ancestry crossover rate 2 per 100 cM), a study of 800 affected individuals has 90% power to detect at P values <10(-5) a locus that generates a risk ratio of 2 between populations, with an expected mapping resolution (size of 95% confidence region for the position of the locus) of 4 cM. In practice, to infer locus ancestry from marker data requires Bayesian computationally intensive methods, as implemented in the program ADMIXMAP. Affected-only study designs require strong prior information on the frequencies of each allele given locus ancestry. We show how data from unadmixed and admixed populations can be combined to estimate these ancestry-specific allele frequencies within the admixed population under study, allowing for variation between allele frequencies in unadmixed and admixed populations. Using simulated data based on the genetic structure of the African American population, we show that 60% of information can be extracted in a test for linkage using markers with an ancestry information content of 36% at 3-cM spacing. As in classic linkage studies, the most efficient strategy is to use markers at a moderate density for an initial genome search and then to saturate regions of putative linkage with additional markers, to extract nearly all information about locus ancestry.     

Evidence of linkage with HLA-DR in DRB1*15-negative families with multiple sclerosis

The importance of the HLA-DR locus to multiple sclerosis (MS) susceptibility was assessed in 542 sib pairs with MS and in their families. By genotyping 1,978 individuals for HLA-DRB1 alleles, we confirmed the well-established association of MS with HLA-DRB1*15 (HLA-DRB1*1501 and HLA-DRB5*0101), by the transmission/disequilibrium test (chi2=138.3; P<.0001). We obtained significant evidence of linkage throughout the whole data set (mlod=4.09; 59.9% sharing). Surprisingly, similar sharing was also observed in 58 families in which both parents lacked the DRB1*15 allele (mlod=1.56; 62.7% sharing; P=.0081). Our findings suggest that the notion that HLA-DRB1*15 is the sole major-histocompatibility-complex determinant of susceptibility in northern-European populations with MS may be incorrect. It remains possible that the association of MS with HLA-DRB1*15 is due to linkage disequilibrium with a nearby locus and/or to the presence of disease-influencing allele(s) in DRB1*15-negative haplotypes.