Linkage and association analyses of microsatellites and single-nucleotide polymorphisms in nuclear families

Several simulation studies have suggested that a high-density single-nucleotide polymorphisms (SNPs) marker set may be as useful as a traditional microsatellites (MS) marker set in performing whole-genome linkage analysis. However, very few studies have directly tested the SNPs-based genome-wide scan. In the present study, we compared the linkage results from the SNPs-based scan with a map density of 3-cM spacing with those from the MS scan using a 10-cM marker set among 300 nuclear families each from the Aipotu (AI), Danacaa (DA), and Karangar (KA) populations from the simulated Genetic Analysis Workshop 14 Problem 2 data. We found that information contents obtained from the SNPs scan were somewhat lower than those from the MS scan. However, the linkage results obtained from the two scans showed a high degree of similarity. Both scans identified a similar number of chromosomal regions attaining nominal significance (p < 0.05). Specifically, both scans detected confirmed evidence for linkage (NPL >or= 4.07, p = 2 x 10(-5)) to chromosome 1 in the AI families, chromosomes 1 and 3 in the DA families, and chromosomes 3, 5, and 9 in the KA families. An additional confirmed linkage to chromosome 5 in the AI families was detected only by the MS scan. We also observed slightly wider 1-LOD intervals for more of the SNP peaks than for the MS peaks, which is likely due to lower information contents for the SNPs. Subsequent fine-mapping association analysis further identified 2 to 3 markers significantly associated with disease status in each population; B03T3056, B03T3058, and B05T4139 in the AI population, B03T3056 and B03T3058 in the KA population, and B03T3056, B03T3057, and B03T3058 in the DA population. Among the four markers, three were chosen based on results obtained from the two scans, but one was solely from the SNP scan. In summary, our finding suggests that the SNP-based genome scan has the potential to be as powerful as the traditional MS-based scan and offers good identification of peak location for further fine-mapped association analysis.     

Approaches to mapping genetically correlated complex traits

Our Markov chain Monte Carlo (MCMC) methods were used in linkage analyses of the Framingham Heart Study data using all available pedigrees. Our goal was to detect and map loci associated with covariate-adjusted traits log triglyceride (lnTG) and high-density lipoprotein cholesterol (HDL) using multipoint LOD score analysis, Bayesian oligogenic linkage analysis and identity-by-descent (IBD) scoring methods. Each method used all marker data for all markers on a chromosome. Bayesian linkage analysis detected a linkage signal on chromosome 7 for lnTG and HDL, corroborating previously published results. However, these results were not replicated in a classical linkage analysis of the data or by using IBD scoring methods.We conclude that Bayesian linkage analysis provides a powerful paradigm for mapping trait loci but interpretation of the Bayesian linkage signals is subjective. In the absence of a LOD score method accommodating genetically complex traits and linkage heterogeneity, validation of these signals remains elusive.     

Genetic homogeneity of autoimmune polyglandular disease type I.

Autoimmune polyglandular disease type I (APECED) is an autosomal recessive autoimmune disease (MIM 240300) characterized by hypoparathyroidism, primary adrenocortical failure, and chronic mucocutaneous candidiasis. The disease is highly prevalent in two isolated populations, the Finnish population and the Iranian Jewish one. Sporadic cases have been identified in many other countries, including almost all European countries. The APECED locus has previously been assigned to chromosome 21q22.3 by linkage analyses in 14 Finnish families. Locus heterogeneity is a highly relevant question in this disease affecting multiple tissues and with great phenotypic diversity. To solve this matter, we performed linkage and haplotype analyses on APECED families rising from different populations. Six microsatellite markers on the critical chromosomal region of 2.6 cM on 21q22.3 were analyzed. Pairwise linkage analyses revealed significant LOD scores for all these markers, maximum LOD score being 10.23. The obtained haplotype data and the geographic distribution of the great-grandparents of the Finnish APECED patients suggest the presence of one major, relatively old mutation responsible for approximately 90% of the Finnish cases. Similar evidence for one founder mutation was also found in analyses of Iranian Jewish APECED haplotypes. These haplotypes, however, differed totally from the Finnish ones. The linkage analyses in 21 non-Finnish APECED families originating from several European countries provided independent evidence for linkage to the same chromosomal region on 21q22.3 and revealed no evidence for locus heterogeneity. The haplotype analyses of APECED chromosomes suggest that in different populations APECED is due to a spectrum of mutations in a still unknown gene on chromosome 21.     

A Locus in 2p13–p14 (OFC2), in Addition to That Mapped in 6p23, Is Involved in Nonsyndromic Familial Orofacial Cleft Malformation

An allelic association between the transforming growth factor α gene (TGFA) situated in the chromosome 2p13 region and nonsyndromic cleft lip with or without cleft palate, also named orofacial cleft (OFC), was found in several population studies. However, no linkage between gene and malformation has shown up until now, probably due to the presence of genetic heterogeneity and the small sample size analyzed. Previously, we employed a collection of 38 OFC families to demonstrate linkage to the 6p23 chromosome region with the presence of genetic heterogeneity. In the present study we tested whether, in the same sample, linkage between OFC and markers on 2p13 could be determined. Evidence for genetic heterogeneity in our family set was apparent, by both pairwise and multipoint linkage analyses. Moreover, lod scores >3 were found for marker D2S378 when families linked to the 6p23 markers were analyzed. Taken together these results indicate a role for the TGFA, or for another gene physically close to it, and suggest an interaction between two different genes, OFC1 and OFC2, mapped in 6p23 and 2p13, respectively, in the development of the cleft.     

Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis

We explored the power and consistency to detect linkage and association with meta-analysis and pooled data analysis using Genetic Analysis Workshop 14 simulated data. The first 10 replicates from Aipotu population were used. Significant linkage and association was found at all 4 regions containing the major loci for Kofendrerd Personality Disorder (KPD) using both combined analyses although no significant linkage and association was found at all these regions in a single replicate. The linkage results from both analyses are consistent in terms of the significance level of linkage test and the estimate of locus location. After correction for multiple-testing, significant associations were detected for the same 8 single-nucleotide polymorphisms (SNP) in both analyses. There were another 2 SNPs for which significant associations with KPD were found only by pooled data analysis. Our study showed that, under homogeneous condition, the results from meta-analysis and pooled data analysis are similar in both linkage and association studies and the loss of power is limited using meta-analysis. Thus, meta-analysis can provide an overall evaluation of linkage and association when the original raw data is not available for combining.     

Genomewide linkage scan for schizophrenia susceptibility loci among Ashkenazi Jewish families shows evidence of linkage on chromosome 10q22

Previous linkage studies in schizophrenia have been discouraging due to inconsistent findings and weak signals. Genetic heterogeneity has been cited as one of the primary culprits for such inconsistencies. We have performed a 10-cM autosomal genomewide linkage scan for schizophrenia susceptibility regions, using 29 multiplex families of Ashkenazi Jewish descent. Although there is no evidence that the rate of schizophrenia among the Ashkenazim differs from that in other populations, we have focused on this population in hopes of reducing genetic heterogeneity among families and increasing the detectable effects of any particular locus. We pursued both allele-sharing and parametric linkage analyses as implemented in Genehunter, version 2.0. Our strongest signal was achieved at chromosome 10q22.3 (D10S1686), with a nonparametric linkage score (NPL) of 3.35 (genomewide empirical P=.035) and a dominant heterogeneity LOD score (HLOD) of 3.14. Six other regions gave NPL scores >2.00 (on chromosomes 1p32.2, 4q34.3, 6p21.31, 7p15.2, 15q11.2, and 21q21.2). Upon follow-up with an additional 23 markers in the chromosome 10q region, our peak NPL score increased to 4.27 (D10S1774; empirical P=.00002), with a 95% confidence interval of 12.2 Mb for the location of the trait locus (D10S1677 to D10S1753). We find these results encouraging for the study of schizophrenia among Ashkenazi families and suggest further linkage and association studies in this chromosome 10q region.     

A genome-wide association study reveals loci influencing height and other conformation traits in horses

The molecular analysis of genes influencing human height has been notoriously difficult. Genome-wide association studies (GWAS) for height in humans based on tens of thousands to hundreds of thousands of samples so far revealed ～200 loci for human height explaining only 20% of the heritability. In domestic animals isolated populations with a greatly reduced genetic heterogeneity facilitate a more efficient analysis of complex traits. We performed a genome-wide association study on 1,077 Franches-Montagnes (FM) horses using ～40,000 SNPs. Our study revealed two QTL for height at withers on chromosomes 3 and 9. The association signal on chromosome 3 is close to the LCORL/NCAPG genes. The association signal on chromosome 9 is close to the ZFAT gene. Both loci have already been shown to influence height in humans. Interestingly, there are very large intergenic regions at the association signals. The two detected QTL together explain ～18.2% of the heritable variation of height in horses. However, another large fraction of the variance for height in horses results from ECA 1 (11.0%), although the association analysis did not reveal significantly associated SNPs on this chromosome. The QTL region on ECA 3 associated with height at withers was also significantly associated with wither height, conformation of legs, ventral border of mandible, correctness of gaits, and expression of the head. The region on ECA 9 associated with height at withers was also associated with wither height, length of croup and length of back. In addition to these two QTL regions on ECA 3 and ECA 9 we detected another QTL on ECA 6 for correctness of gaits. Our study highlights the value of domestic animal populations for the genetic analysis of complex traits.     

Comparison of genome screens for two independent cohorts provides replication of suggestive linkage of bone mineral density to 3p21 and 1p36

Low bone mineral density (BMD) is a major risk factor for osteoporotic fracture. Studies of BMD in families and twins have shown that this trait is under strong genetic control. To identify regions of the genome that contain quantitative trait loci (QTL) for BMD, we performed independent genomewide screens, using two complementary study designs. We analyzed unselected nonidentical twin pairs (1,094 pedigrees) and highly selected, extremely discordant or concordant (EDAC) sib pairs (254 pedigrees). Nonparametric multipoint linkage (NPL) analyses were undertaken for lumbar spine and total-hip BMD in both cohorts and for whole-body BMD in the unselected twin pairs. The maximum evidence of linkage in the unselected twins (spine BMD, LOD 2.7) and the EDAC pedigrees (spine BMD, LOD 2.1) was observed at chromosome 3p21 (76 cM and 69 cM, respectively). These combined data indicate the presence, in this region, of a gene that regulates BMD. Furthermore, evidence of linkage in the twin cohort (whole-body BMD; LOD 2.4) at chromosome 1p36 (17 cM) supports previous findings of suggestive linkage to BMD in the region. Weaker evidence of linkage (LOD 1.0-2.3) in either cohort, but not both, indicates the locality of additional QTLs. These studies validate the use, in linkage analysis, of large cohorts of unselected twins phenotyped for multiple traits, and they highlight the importance of conducting genome scans in replicate populations as a prelude to positional cloning and gene discovery.     

Standard linkage and association methods identify the mechanism of four susceptibility genes for a simulated complex disease

The simulated dataset of the Genetic Analysis Workshop 14 provided affection status and the presence or absence of 12 traits. It was determined that all affected individuals must have traits E, F and H (EFH phenotype) and they must also have either trait B (B subtype) or traits C, D, and G (CDG subtype). A genome screen was performed, and linkage peaks were identified on chromosomes 1, 3, 5, and 9 using microsatellite markers. Dense panels of single-nucleotide polymorphism (SNP) markers were ordered for each of the four linkage peaks. In each case, association analyses identified a single SNP that accounted for the linkage evidence. The SNP on chromosome 1 appeared to primarily influence the B subtype, while the SNPs on chromosomes 5 and 9 primarily influenced the CDG subtype. The chromosome 3 SNP had the strongest effect and influenced both subtypes, as well as the requisite EFH phenotype. Recognizing the two subtypes prior to linkage analysis was key to identifying these loci using only a single replicate. This highlights the need in real life situations for careful examination of the phenotypic data prior to genetic analysis.     

Identifying genomic regions for fine-mapping using genome scan meta-analysis (GSMA) to identify the minimum regions of maximum significance (MRMS) across populations

In order to detect linkage of the simulated complex disease Kofendrerd Personality Disorder across studies from multiple populations, we performed a genome scan meta-analysis (GSMA). Using the 7-cM microsatellite map, nonparametric multipoint linkage analyses were performed separately on each of the four simulated populations independently to determine p-values. The genome of each population was divided into 20-cM bin regions, and each bin was rank-ordered based on the most significant linkage p-value for that population in that region. The bin ranks were then averaged across all four studies to determine the most significant 20-cM regions over all studies. Statistical significance of the averaged bin ranks was determined from a normal distribution of randomly assigned rank averages. To narrow the region of interest for fine-mapping, the meta-analysis was repeated two additional times, with each of the 20-cM bins offset by 7 cM and 13 cM, respectively, creating regions of overlap with the original method. The 6-7 cM shared regions, where the highest averaged 20-cM bins from each of the three offsets overlap, designated the minimum region of maximum significance (MRMS). Application of the GSMA-MRMS method revealed genome wide significance (p-values refer to the average rank assigned to the bin) at regions including or adjacent to all of the simulated disease loci: chromosome 1 (p < 0.0001 for 160-167 cM, including D1), chromosome 3 (p-value < 0.0000001 for 287-294 cM, including D2), chromosome 5 (p-value < 0.001 for 0-7 cM, including D3), and chromosome 9 (p-value < 0.05 for 7-14 cM, the region adjacent to D4). This GSMA analysis approach demonstrates the power of linkage meta-analysis to detect multiple genes simultaneously for a complex disorder. The MRMS method enhances this powerful tool to focus on more localized regions of linkage.     

Robust estimation of experimentwise P values applied to a genome scan of multiple asthma traits identifies a new region of significant linkage on chromosome 20q13

Over 30 genomic regions show linkage to asthma traits. Six asthma genes have been cloned, but the putative loci in many linked regions have not been identified. To search for asthma susceptibility loci, we performed genomewide univariate linkage analyses of seven asthma traits, using 202 Australian families ascertained through a twin proband. House-dust mite sensitivity (Dpter) exceeded the empirical threshold for significant linkage at 102 cM on chromosome 20q13, near marker D20S173 (empirical pointwise P = .00001 and genomewide P = .005, both uncorrected for multiple-trait testing). Atopy, bronchial hyperresponsiveness (BHR), and forced expiratory volume in 1 s (FEV1) were also linked to this region. In addition, 16 regions were linked to at least one trait at the suggestive level, including 12q24, which has consistently shown linkage to asthma traits in other studies. Some regions were expected to be false-positives arising from multiple-trait testing. To address this, we developed a new approach to estimate genomewide significance that accounts for multiple-trait testing and for correlation between traits and that does not require a Bonferroni correction. With this approach, Dpter remained significantly linked to 20q13 (empirical genomewide P = .042), and airway obstruction remained linked to 12q24 at the suggestive level. Finally, we extended this method to show that the linkage of Dpter, atopy, BHR, FEV1, asthma, and airway obstruction to chromosome 20q13 is unlikely to be due to chance and may result from a quantitative trait locus in this region that affects several of these traits.     

Genetic linkage and heterogeneity in type I Charcot-Marie-Tooth disease (hereditary motor and sensory neuropathy type I).

The segregation patterns of DNA markers from the pericentromeric regions of chromosomes 1 and 17 were studied in seven pedigrees segregating an autosomal dominant gene for Charcot-Marie-Tooth neuropathy type I (CMT I; hereditary motor and sensory neuropathy I). A multilocus analysis with four markers (pMCR-3, pMUC10, FY, and pMLAJ1) spanning the pericentromeric region of chromosome 1 excluded the CMT I gene from this region in six pedigrees but gave some evidence for linkage to the region of Duffy in one pedigree. Linkage of the CMT I gene to markers in the pericentromeric region of chromosome 17 (markers pA10-41, pEW301, p3.6, and pTH17.19) was established; however, in these seven pedigrees homogeneity analysis with chromosome 17 markers detected significant genetic heterogeneity. This analysis suggested that three of the seven pedigrees are not linked to this same region. Overall, two of the seven CMT I pedigrees were not linked to markers tested from chromosomes 1 or 17. These results confirm genetic heterogeneity in CMT I and implicate the existence of a third autosomal locus, in addition to a locus on chromosome 17, and a probable locus on chromosome 1. This evidence of etiological heterogeneity, supported by statistical tests, will have to be taken into consideration when fine-structure genetic maps of the regions around CMT I are constructed.     

Bivariate linkage analysis of the insulin resistance syndrome phenotypes on chromosome 7q

Metabolic abnormalities of the insulin resistance syndrome (IRS) have been shown to aggregate in families and to exhibit trait-pair correlations, suggesting a common genetic component. A broad region on chromosome 7q has been implicated in several studies to contain loci that cosegregate with IRS-related traits. However, it is not clear whether such loci have any common genetic (pleiotropic) influences on the correlated traits. Also, it is not clear whether the chromosomal regions contain more than one locus influencing the IRS-related phenotypes. In this study we present evidence for linkage of five IRS-related traits [body mass index (BMI), waist circumference (WC), In split proinsulin (LSPI), In triglycerides (LTG), and high-density lipoprotein cholesterol (HDLC)] to a region at 7q11.23. Subsequently, to gain further insight into the genetic component(s) mapping to this region, we explored whether linkage of these traits is due to pleiotropic effects using a bivariate linkage analytical technique, which has been shown to localize susceptibility regions with precision. Four hundred forty individuals from 27 Mexican American families living in Texas were genotyped for 19 highly polymorphic markers on chromosome 7. Multipoint variance component linkage analysis was used to identify genetic location(s) influencing IRS-related traits of obesity (BMI and WC), dyslipidemia (LTG and HDLC), and insulin levels (LSPI); the analysis identified a broad chromosomal region spanning approximately 24 cM. To gain more precision in localization, we used a bivariate linkage approach for each trait pair. These analyses suggest localization of most of these bivariate traits to an approximately 6-cM region near marker D7S653 [7q11.23, 103-109 cM; a maximum bivariate LOD of 4.51 was found for the trait pair HDLC and LSPI (the LODeq score is 3.94)]. We observed evidence of pleiotropic effects in this region on obesity and insulin-related trait pairs.     

Comparative QTL analysis of early short-time drought tolerance in Polish fodder and malting spring barleys

Key message

An effective approach for the further evolution of QTL markers, may be to create mapping populations for locally adapted gene pools, and to phenotype the studied trait under local conditions.

Abstract

Mapping populations of Polish fodder and malting spring barleys (Hordeum vulgare L.) were used to analyze traits describing short-time drought response at the seedlings stage. High-throughput genotyping (Diversity Array Technology (DArT) markers) and phenotyping techniques were used. The results showed high genetic diversity of the studied populations which allowed the creation of high-density linkage maps. There was also high diversity in the physiological responses of the barleys. Quantitative trait locus (QTL) analysis revealed 18 QTLs for nine physiological traits on all chromosomes except 1H in malting barley and 15 QTLs for five physiological traits on chromosomes 2H, 4H, 5H and 6H in fodder barley. Chromosomes 4H and 5H contained QTLs which explained most of the observed phenotypic variations in both populations. There was a major QTL for net photosynthetic rate in the malting barley located on chromosome 5H and two major QTLs for overall photochemical performance (PI) located on 5H and 7H. One major QTL related to photochemical quenching of chlorophyll fluorescence was located on chromosome 4H in fodder barley. Three QTL regions were common to both mapping populations but the corresponding regions explained different drought-induced traits. One region was for QTLs related to PSII photosynthetic activity stress index in malting barley, and the corresponding region in fodder barley was related to the water content stress index. These results are in accordance with previous studies which showed that different traits were responsible for drought tolerance variations in fodder and malting barleys.     

The origin of selection signatures on bovine chromosome 6

The extent and pattern of linkage disequilibrium (LD) between closely spaced markers contain information about population history, including past population size and selection history. Selection signatures can be identified by comparing the LD surrounding a putative selected allele at a locus to the putative non-selected allele. In livestock populations, locations of selection signatures identified in this way should be correlated with QTL affecting production traits, as the populations have been under strong artificial selection for these traits. We used a dense SNP map of bovine chromosome 6 to characterize the pattern of LD on this chromosome in Norwegian Red cattle, a breed which has been strongly selected for milk production. The pattern of LD was generally consistent with strong selection in regions containing QTL affecting milk production traits, including a strong selection signature in a region containing a mutation known to affect milk production. The results demonstrate that in livestock populations, the origin of selection signatures will often be QTL for livestock production traits, and illustrate the value of selection signatures in uncovering new mutations with potential effects on quantitative traits.     

Genetic analysis of the maximum drinks phenotype

Using data provided by the Collaborative Study on the Genetics of Alcoholism we studied the genetics of a quantitative trait: the maximum number of drinks consumed in a 24-hour period. A two-stage method was used. First, linkage analysis was performed, followed by association analysis in regions where linkage was detected. Additionally, the extent of linkage disequilibrium among single-nucleotide polymorphisms (SNP) associated with the phenotype was assessed. Linkage to chromosomes 2 and 7 was detected, and follow-up association analysis found multiple trait-associated SNPs in the chromosome 7 linkage region. Chromosome 4, which has been implicated in previous studies of the maximum drinks phenotype, did not pass our threshold for linkage evidence in stage 1, but secondary analyses of this chromosome indicated modest evidence for both linkage and association. The evidence suggests that chromosome 7 may harbor an additional locus influencing the maximum drinks consumption phenotype.     

Genetic evidence for a distinct subtype of schizophrenia characterized by pervasive cognitive deficit

A novel phenotyping strategy in schizophrenia, targeting different neurocognitive domains, neurobehavioral features, and selected personality traits, has allowed us to identify a homogeneous familial subtype of the disease, characterized by pervasive neurocognitive deficit. Our genome scan data indicate that this subtype, which accounts for up to 50% of our sample, has a distinct genetic basis and explains linkage to chromosome 6p24 reported previously. If representative of other populations, the ratio of schizophrenia subtypes observed in our families could have a profound impact on sample heterogeneity and on the power of genetic studies to detect linkage and association. Our proposed abbreviated battery of tests should facilitate phenotype characterization for future genetic analyses and allow a focus on a crisply defined schizophrenia subtype, thus promoting a more informed search for susceptibility genes.     

Mutation screening of two candidate genes from 13q32 in families affected with Bipolar disorder: human peptide transporter (SLC15A1) and human glypican5 (GPC5)

Background  

Multiple candidate regions as sites for Schizophrenia and Bipolar susceptibility genes have been reported, suggesting heterogeneity of susceptibility genes or oligogenic inheritance. Linkage analysis has suggested chromosome 13q32 as one of the regions with evidence of linkage to Schizophrenia and, separately, to Bipolar disorder (BP). SLC15A1 and GPC5 are two of the candidate genes within an approximately 10-cM region of linkage on chromosome 13q32. In order to identify a possible role for these candidates as susceptibility genes, we performed mutation screening on the coding regions of these two genes in 7 families (n-20) affected with Bipolar disorder showing linkage to 13q32.     

Genetic and physical mapping and population studies of a fibronectin receptor beta-subunit-like sequence on human chromosome 19

A cDNA clone of the beta subunit of human fibronectin receptor (FNRB) detects two different polymorphic loci: (a) a codominant system previously mapped to the pericentromeric region of chromosome 10, the site of the functional FNRB gene; and (b) a dominant system not linked to the first one or to any chromosome 10 marker tested. This second polymorphism is characterized by the presence or absence of a band (or a set of bands). We have used linkage analysis and biotin-labeled in situ hybridization to map this dominant polymorphism to the short arm of chromosome 19; we hypothesize that it may be due to the insertion of part of the cDNA from the chromosome 10 gene into chromosome 19. This "insertion" is polymorphic in all populations studied.