Linkage and association mapping of the LRP5 locus on chromosome 11q13 in type 1 diabetes

Linkage of chromosome 11q13 to type 1 diabetes (T1D) was first reported from genome scans (Davies et al. 1994; Hashimoto et al. 1994) resulting in P <2.2 x 10(-5) (Luo et al. 1996) and designated IDDM4 ( insulin dependent diabetes mellitus 4). Association mapping under the linkage peak using 12 polymorphic microsatellite markers suggested some evidence of association with a two-marker haplotype, D11S1917*03-H0570POLYA*02, which was under-transmitted to affected siblings and over-transmitted to unaffected siblings ( P=1.5 x 10(-6)) (Nakagawa et al. 1998). Others have reported evidence for T1D association of the microsatellite marker D11S987, which is approximately 100 kb proximal to D11S1917 (Eckenrode et al. 2000). We have sequenced a 400-kb interval surrounding these loci and identified four genes, including the low-density lipoprotein receptor related protein (LRP5) gene, which has been considered as a functional candidate gene for T1D (Hey et al. 1998; Twells et al. 2001). Consequently, we have developed a comprehensive SNP map of the LRP5 gene region, and identified 95 SNPs encompassing 269 kb of genomic DNA, characterised the LD in the region and haplotypes (Twells et al. 2003). Here, we present our refined linkage curve of the IDDM4 region, comprising 32 microsatellite markers and 12 SNPs, providing a peak MLS=2.58, P=5 x 10(-4), at LRP5 g.17646G>T. The disease association data, largely focused in the LRP5 region with 1,106 T1D families, provided no further evidence for disease association at LRP5 or at D11S987. A second dataset, comprising 1,569 families from Finland, failed to replicate our previous findings at LRP5. The continued search for the variants of the putative IDDM4 locus will greatly benefit from the future development of a haplotype map of the genome.     

Detecting genome wide haplotype sharing using SNP or microsatellite haplotype data

Genome wide association studies using high throughput technology are already being conducted despite the significant hurdles that need to be overcome (Nat Rev Genet 6:95–108, 2005; Nat Rev Genet 6:109–118, 2005). Methods for detecting haplotype association signals in genome wide haplotype datasets are as yet very limited. Much methodological research has already been devoted to linkage disequilibrium (LD) fine mapping where the focus is the identification of the disease locus rather than the detection of a disease signal. Applications of these approaches to genome wide scanning are limited by the strong model assumptions of the sharing process, which lead to computational complexity. We describe a new algorithm for the initial identification of disease susceptibility loci in genome wide haplotype association studies. Excess sharing of ancestral haplotypes, which indicates the presence of a disease locus, is detected with a simple, easy to interpret, χ ² based statistic. The method allows genome wide scanning for qualitative traits within reasonable computational timeframes and can serve as a first pass analysis prior to the usage of likelihood based methods, providing candidate regions and inferred susceptibility haplotypes. Our method makes no assumptions regarding the population history or the pattern of background LD. Statistical significance is evaluated with permutation tests. The method is illustrated on simulated and real data where it is applied to simple (cystic fibrosis) and complex disease (multiple sclerosis) examples. The statistic has low type I error and greater power to map disease loci over conventional single marker tests for low to moderate levels of LD.     

Performance of random forest when SNPs are in linkage disequilibrium

Background  

Single nucleotide polymorphisms (SNPs) may be correlated due to linkage disequilibrium (LD). Association studies look for both direct and indirect associations with disease loci. In a Random Forest (RF) analysis, correlation between a true risk SNP and SNPs in LD may lead to diminished variable importance for the true risk SNP. One approach to address this problem is to select SNPs in linkage equilibrium (LE) for analysis. Here, we explore alternative methods for dealing with SNPs in LD: change the tree-building algorithm by building each tree in an RF only with SNPs in LE, modify the importance measure (IM), and use haplotypes instead of SNPs to build a RF.     

The reliability of haplotyping inference in nuclear families: misassignment rates for SNPs and microsatellites

Single nucleotide polymorphisms (SNPs) are widely used when investigators try to map complex disease genes. Although biallelic SNP markers are less informative than microsatellite markers, one can increase their information content by using haplotypes. However, assigning haplotypes (i.e., assigning phase) correctly can be problematic in the presence of SNP heterozygosity. For example, a doubly heterozygous individual, with genotype 12, 12, could have haplotypes 1-1/2-2 or 1-2/2-1 with equal probability; in the absence of additional information, there is no way to determine which haplotype is correct. Thus an algorithm that assigns haplotypes to such an individual will assign the wrong one 50% of the time. We have studied the frequency of haplotype misassignments, i.e., haplotypes that are misassigned solely because of inherent marker ambiguity (not because of errors in genotyping or calculation). We examined both SNPs and microsatellite markers. We used the computer programs GENEHUNTER and SIMWALK to assign the haplotypes. We simulated (a) families with 1-5 children, (b) haplotypes involving different numbers of marker loci (3, 5, 7 and 10 loci, all in linkage equilibrium), and (c) different allele frequencies. Misassignment rates are highest (a) in small families, (b) with many SNP loci, and (c) for loci with the greatest heterozygosity (i.e., where both alleles have frequency 0.5). For example, for triads (i.e., one-child families with both parents genotyped), misassignment rates for SNPs can reach almost 50%. Family sizes of 4-5 children are required in order to ensure a misassignment frequency of < or = 5% for ten-SNP haplotypes with allele frequencies of 0.25-0.5. For microsatellites, a family size of at least 2-3 children is necessary to keep haplotyping misassignments < or = 5%. Finally, we point out that it is misleading for a computer program to yield haplotype assignments without indicating that they may have been misassigned, and we discuss the implications of these misassignments for association and linkage analysis.     

Utilizing linkage disequilibrium information from Indian Genome Variation Database for mapping mutations: SCA12 case study

Stratification in heterogeneous populations poses an enormous challenge in linkage disequilibrium (LD) based identification of causal loci using surrogate markers. In this study, we demonstrate the enormous potential of endogamous Indian populations for mapping mutations in candidate genes using minimal SNPs, mainly due to larger regions of LD. We show this by a case study of the PPP2R2B gene (∼400 kb) that harbours a CAG repeat, expansion of which has been implicated in spinocerebellar ataxia type 12 (SCA12). Using LD information derived from Indian Genome Variation database (IGVdb) on populations which share similar ethnic and linguistic backgrounds as the SCA12 study population, we could map the causal loci using a minimal set of three SNPs, without the generation of additional basal data from the ethnically matched population. We could also demonstrate transferability of tagSNPs from a related HapMap population for mapping the mutation. Composition first described in Hum. Genet. 2005, 118, 1–11     

Quantification of random mutations in the mitochondrial genome

Mitochondrial DNA (mtDNA) mutations contribute to the pathology of a number of age-related disorders, including Parkinson disease [A. Bender et al., Nat. Genet. 38 (2006) 515,Y. Kraytsberg et al., Nat. Genet. 38 (2006) 518], muscle-wasting [J. Wanagat, Z. Cao, P. Pathare, J.M. Aiken, FASEB J. 15 (2001) 322], and the metastatic potential of cancers [K. Ishikawa et al., Science 320 (2008) 661]. The impact of mitochondrial DNA mutations on a wide variety of human diseases has made it increasingly important to understand the mechanisms that drive mitochondrial mutagenesis. In order to provide new insight into the etiology and natural history of mtDNA mutations, we have developed an assay that can detect mitochondrial mutations in a variety of tissues and experimental settings [M. Vermulst et al., Nat. Genet. 40 (2008) 4, M. Vermulst et al., Nat. Genet. 39 (2007) 540]. This methodology, termed the Random Mutation Capture assay, relies on single-molecule amplification to detect rare mutations among millions of wild-type bases [J.H. Bielas, L.A. Loeb, Nat. Methods 2 (2005) 285], and can be used to analyze mitochondrial mutagenesis to a single base pair level in mammals.     

Entropy as a measure for linkage disequilibrium over multilocus haplotype blocks

OBJECTIVE: The presence of linkage disequilibrium (LD) forms the basis for a range of uses, including the fine-mapping of diseases and studies on human genealogy. Recent findings indicate that single nucleotide polymorphisms (SNP) can occur in blocks of limited haplotypic diversity with high degrees of LD. Commonly used measures for LD, such as r(2) and D', consider only two loci and might miss information to appropriately describe LD in larger haplotypic structures. METHODS: We introduce the Normalized Entropy Difference, epsilon, as a new multilocus measure for LD. A related quantity, deltaS, provides an approximate chi(2) test for the significance of LD. The ability of the measure to detect haplotype blocks is investigated using simulated data sets as well as a real data set previously analyzed by Daly et al. (2001). RESULTS: epsilon allows for arbitrary numbers of loci, describes LD with regard to the loci sequence, and can be interpreted as a multilocus extension of r(2). The application of epsilon to the data sets demonstrated the measure's ability to appropriately describe simultaneous multilocus LD and to detect haplotype blocks. CONCLUSIONS: epsilon is a reasonable multilocus LD measure and might be of potential use in the construction of the human haplotype map.     

Genetics of ethanol-induced locomotor activation: detection of QTLs in a C57BL/6J × DBA/2J F2 intercross

Moderate doses of ethanol (1–2 g/kg) markedly increase locomotor activity in some inbred mouse strains, for example, the DBA/2J (D2), but have relatively little effect in other strains, for example, the C57BL/6J (B6). In the present study, we conducted a genome-wide search in a B6D2 F₂ intercross (N = 925) for quantitative trait loci (QTLs) associated with the locomotor response. A QTL with a LOD score of 8.4 was detected on Chromosome (Chr) 2; this QTL accounted for 11.4% of the phenotypic variance and approximately 30% of the genetic variance. The QTL on Chr 2 is in the same general region as QTLs previously described for ethanol preference/consumption (Rodriguez et al. Alcohol Clin Exp Res 19, 367, 1995; Melo et al. Nat Genet 13, 147, 1996; Phillips et al. Mamm Genome, in press), acute ethanol withdrawal (Buck et al. J. Neurosci 17, 3946, 1997) and nitrous oxide withdrawal severity (Belknap et al. Behav Genet 23, 213, 1993). A logical candidate gene in the region of interest is the enzyme which synthesizes GABA, glutamic acid decarboxylase 1 (GadI). Received: 15 September 1998 / Accepted: 8 October 1998     

Evaluation of linkage disequilibrium and its effect on non-parametric multipoint linkage analysis using two high density single-nucleotide polymorphism mapping panels

Genotype data from the Illumina Linkage III SNP panel (n = 4,720 SNPs) and the Affymetrix 10 k mapping array (n = 11,120 SNPs) were used to test the effects of linkage disequilibrium (LD) between SNPs in a linkage analysis in the Collaborative Study on the Genetics of Alcoholism pedigree collection (143 pedigrees; 1,614 individuals). The average r2 between adjacent markers across the genetic map was 0.099 +/- 0.003 in the Illumina III panel and 0.17 +/- 0.003 in the Affymetrix 10 k array. In order to determine the effect of LD between marker loci in a nonparametric multipoint linkage analysis, markers in strong LD with another marker (r2 > 0.40) were removed (n = 471 loci in the Illumina panel; n = 1,804 loci in the Affymetrix panel) and the linkage analysis results were compared to the results using the entire marker sets. In all analyses using the ALDX1 phenotype, 8 linkage regions on 5 chromosomes (2, 7, 10, 11, X) were detected (peak markers p < 0.01), and the Illumina panel detected an additional region on chromosome 6. Analysis of the same pedigree set and ALDX1 phenotype using short tandem repeat markers (STRs) resulted in 3 linkage regions on 3 chromosomes (peak markers p < 0.01). These results suggest that in this pedigree set, LD between loci with spacing similar to the SNP panels tested may not significantly affect the overall detection of linkage regions in a genome scan. Moreover, since the data quality and information content are greatly improved in the SNP panels over STR genotyping methods, new linkage regions may be identified due to higher information content and data quality in a dense SNP linkage panel.     

Comparative LD mapping using single SNPs and haplotypes identifies QTL for plant height and biomass as secondary traits of drought tolerance in maize

Drought often delays developmental events so that plant height and above-ground biomass are reduced, resulting in yield loss due to inadequate photosynthate. In this study, plant height and biomass measured by the Normalized Difference Vegetation Index (NDVI) were used as criteria for drought tolerance. A total of 305 lines representing temperate, tropical and subtropical maize germplasm were genotyped using two single nucleotide polymorphism (SNP) chips each containing 1536 markers, from which 2052 informative SNPs and 386 haplotypes each constructed with two or more SNPs were used for linkage disequilibrium (LD) or association mapping. Single SNP- and haplotype-based LD mapping identified two significant SNPs and three haplotype loci [a total of four quantitative trait loci (QTL)] for plant height under well-watered and water-stressed conditions. For biomass, 32 SNPs and 12 haplotype loci (30 QTL) were identified using NDVIs measured at seven stages under the two water regimes. Some significant SNP and haplotype loci for NDVI were shared by different stages. Comparing significant loci identified by single SNP- and haplotype-based LD mapping, we found that six out of the 14 chromosomal regions defined by haplotype loci each included at least one significant SNP for the same trait. Significant SNP haplotype loci explained much higher phenotypic variation than individual SNPs. Moreover, we found that two significant SNPs (two QTL) and one haplotype locus were shared by plant height and NDVI. The results indicate the power of comparative LD mapping using single SNPs and SNP haplotypes with QTL shared by plant height and biomass as secondary traits for drought tolerance in maize.     

Evaluation of Linkage Disequilibrium Pattern and Association Study on Seed Oil Content in Brassica napus Using ddRAD Sequencing

High-density genetic markers are the prerequisite for understanding linkage disequilibrium (LD) and genome-wide association studies (GWASs) of complex traits in crops. To evaluate the LD pattern in oilseed rape, we sequenced a previous association panel containing 189 B. napus inbred lines using double-digested restriction-site associated DNA (ddRAD) and genotyped 19,327 RAD tags. A total of 15,921 RAD tags were assigned to a published genetic linkage map and the majority (71.1%) of these tags was uniquely mapped to the draft reference genome “Darmor-bzh.” The distance of LD decay was 1,214 kb across the genome at the background level (r² = 0.26), with the distances of LD decay being 405 kb and 2,111 kb in the A and C subgenomes, respectively. A total of 361 haplotype blocks with length > 100 kb were identified in the entire genome. The association panel could be classified into two groups, P1 and P2, which are essentially consistent with the geographical origins of varieties. A large number of group-specific haplotypes were identified, reflecting that varieties in the P1 and P2 groups experienced distinct selection in breeding programs to adapt their different growth habitats. GWAS repeatedly detected two loci significantly associated with oil content of seeds based on the developed SNPs, suggesting that the high-density SNPs were useful for understanding the genetic determinants of complex traits in GWAS.     

An integrated genetic linkage map with 1,137 markers constructed from five F2 crosses of autoimmune disease-prone and -resistant inbred rat strains

The rat (Rattus norvegicus) is an important experimental model for many human diseases including arthritis, diabetes, and other autoimmune and chronic inflammatory diseases. The rat genetic linkage map, however, is less well developed than those of mouse and human. Integrated rat genetic linkage maps have been previously reported by Pravenec et al. (1996, Mamm. Genome 7: 117-127) (500 markers mapped in one cross), Bihoreau et al. (1997, Genome Res. 7: 434-440) (767 markers mapped in three crosses), Wei et al. (1998, Mamm. Genome 9: 1002-1007) (562 markers mapped in two crosses), Brown et al. (1998, Mamm. Genome 9: 521-530) (678 markers mapped in four crosses), and Nordquist et al. (1999, Rat Genome 5: 15-20) (330 markers mapped in two crosses). The densest linkage map combined with a radiation hybrid map, reported by Steen et al. (1999, Genome Res. 9: AP1-AP8), includes 4736 markers mapped in two crosses. Here, we present an integrated linkage map with 1137 markers. We have constructed this map by genotyping F2 progeny of five crosses: F344/NHsd x LEW/NHsd (673 markers), DA/Bkl x F344/NHsd (531 markers), BN/SsN x LEW/N (714 markers), DA/Bkl x BN/SsNHsd (194 markers), and DA/Bkl x ACI/SegHsd (245 markers). These inbred rat strains vary in susceptibility/resistance to multiple autoimmune diseases and are used extensively for many types of investigation. The integrated map includes 360 loci mapped in three or more crosses. The map contains 196 new SSLP markers developed by our group, as well as many SSLP markers developed by other groups. Two hundred forty genes are incorporated in the map. This integrated map should allow comparison of rat genetic maps from different groups and thereby facilitate genetic studies of rat autoimmune and related disease models.     

Methods for assessing gene content diversity of KIR with examples from a global set of populations

A number of statistical methods are widely used to describe allelic variation at specific genetic loci and its implication on the evolutionary history of these loci. Although the methods were developed primarily to study allelic variation at loci that are virtually always present in the genome, they are often applied to data of gene content variation (i.e., presence/absence of multiple homologous genes) at the killer cell immunoglobulin-like receptor (KIR) gene cluster. In this paper, we discuss methodological issues involved in the analysis of gene content variation data in the KIR region and also its covariation with polymorphism at the human leukocyte antigen class I loci, which encode ligands for KIR. A comparison of several statistical methods and measures (gene frequency, haplotype frequency, and linkage disequilibrium estimation) using the Centre d’Etude du Polymorphisme Humain data will be provided using KIR haplotypes that have been determined by segregation analysis, noting the strengths and weaknesses of the methods when only the presence/absence data is considered. Finally, application of these methods to a set of globally distributed populations is described (see Single et al., Nat Genet 39:1114–1119, 2007) in order to illustrate the challenges faced when inferring the joint effects of natural selection and demographic history on these immune-related genes.     

Quantitative trait loci affecting plant regeneration from protoplasts of<Emphasis Type="Italic"> Brassica oleracea</Emphasis>

Quantitative trait loci (QTLs) controlling the plant-regeneration ability of Brassica oleracea protoplasts were mapped in a population of 128 F₂ plants derived from a cross between the high-responding, rapid-cycling line and a low-responding, broccoli breeding line of B. oleracea. A modified bulked segregant analysis with AFLP markers identified two QTLs for plant regeneration. In a multiple regression analysis, the two QTLs explained 83% of the total genetic variation for regeneration recorded 15 weeks after initial transfer of microcalli to regeneration medium. Both QTLs showed additive effects, and the alleles contributing to the high regeneration frequencies were derived from the high-responding, rapid-cycling line. Using microsatellites with known location, the two QTLs were mapped to linkage groups O2 and O9 on the map published by Sebastian et al. [(2000) Theor Appl Genet 100:75–81] or to chromosomes C8 and C7 on the map published by Saal et al. [(2001) Theor Appl Genet 102:695–699]. QTLs for the early flowering trait of the rapid-cycling parent have previously been mapped to the same two linkage groups. Association between flowering time and regeneration ability was, however, not found in the present material, indicating that plant-regeneration ability can be transferred between cultivars independently of the early flowering trait. The detection of two major QTLs for plant regeneration in B. oleracea may provide the initial step towards the identification of markers suitable for marker-assisted selection of regeneration ability.     

Characterizing linkage disequilibrium in pig populations

Knowledge of the extent and range of linkage disequilibrium (LD), defined as non-random association of alleles at two or more loci, in animal populations is extremely valuable in localizing genes affecting quantitative traits, identifying chromosomal regions under selection, studying population history, and characterizing/managing genetic resources and diversity. Two commonly used LD measures, r(2) and D', and their permutation based adjustments, were evaluated using genotypes of more than 6,000 pigs from six commercial lines (two terminal sire lines and four maternal lines) at ~4,500 autosomal SNPs (single nucleotide polymorphisms). The results indicated that permutation only partially removed the dependency of D' on allele frequency and that r(2) is a considerably more robust LD measure. The maximum r(2) was derived as a function of allele frequency. Using the same genotype dataset, the extent of LD in these pig populations was estimated for all possible syntenic SNP pairs using r(2) and the ratio of r(2) over its theoretical maximum. As expected, the extent of LD highest for SNP pairs was found in tightest linkage and decreased as their map distance increased. The level of LD found in these pig populations appears to be lower than previously implied in several other studies using microsatellite genotype data. For all pairs of SNPs approximately 3 centiMorgan (cM) apart, the average r(2) was equal to 0.1. Based on the average population-wise LD found in these six commercial pig lines, we recommend a spacing of 0.1 to 1 cM for a whole genome association study in pig populations.     

A first-generation metric linkage disequilibrium map of bovine chromosome 6

We constructed a metric linkage disequilibrium (LD) map of bovine chromosome 6 (BTA6) on the basis of data from 220 SNPs genotyped on 433 Australian dairy bulls. This metric LD map has distances in LD units (LDUs) that are analogous to centimorgans in linkage maps. The LD map of BTA6 has a total length of 8.9 LDUs. Within the LD map, regions of high LD (represented as blocks) and regions of low LD (steps) are observed, when plotted against the integrated map in kilobases. At the most stringent block definition, namely a set of loci with zero LDU increase over the span of these markers, BTA6 comprises 40 blocks, accounting for 41% of the chromosome. At a slightly lower stringency of block definition (a set of loci covering a maximum of 0.2 LDUs on the LD map), up to 81% of BTA6 is spanned by 46 blocks and with 13 steps that are likely to reflect recombination hot spots. The mean swept radius (the distance over which LD is likely to be useful for mapping) is 13.3 Mb, confirming extensive LD in Holstein-Friesian dairy cattle, which makes such populations ideal for whole-genome association studies.     

Systems biology of epistasis: Shedding light on genetic interaction network “hubs”

Comment on: Szappanos B, et al. Nat Genet 2011; 43:656-62.     

Accuracy of marker-assisted selection with single markers and marker haplotypes in cattle

A key question for the implementation of marker-assisted selection (MAS) using markers in linkage disequilibrium with quantitative trait loci (QTLs) is how many markers surrounding each QTL should be used to ensure the marker or marker haplotypes are in sufficient linkage disequilibrium (LD) with the QTL. In this paper we compare the accuracy of MAS using either single markers or marker haplotypes in an Angus cattle data set consisting of 9323 genome-wide single nucleotide polymorphisms (SNPs) genotyped in 379 Angus cattle. The extent of LD in the data set was such that the average marker-marker r2 was 0.2 at 200 kb. The accuracy of MAS increased as the number of markers in the haplotype surrounding the QTL increased, although only when the number of markers in the haplotype was 4 or greater did the accuracy exceed that achieved when the SNP in the highest LD with the QTL was used. A large number of phenotypic records (>1000) were required to accurately estimate the effects of the haplotypes.     

TAGster: efficient selection of LD tag SNPs in single or multiple populations

Genetic association studies increasingly rely on the use of linkage disequilibrium (LD) tag SNPs to reduce genotyping costs. We developed a software package TAGster to select, evaluate and visualize LD tag SNPs both for single and multiple populations. We implement several strategies to improve the efficiency of current LD tag SNP selection algorithms: (1) we modify the tag SNP selection procedure of Carlson et al. to improve selection efficiency and further generalize it to multiple populations. (2) We propose a redundant SNP elimination step to speed up the exhaustive tag SNP search algorithm proposed by Qin et al. (3) We present an additional multiple population tag SNP selection algorithm based on the framework of Howie et al., but using our modified exhaustive search procedure. We evaluate these methods using resequenced candidate gene data from the Environmental Genome Project and show improvements in both computational and tagging efficiency. AVAILABILITY: The software Package TAGster is freely available at http://www.niehs.nih.gov/research/resources/software/tagster/