Characterization of a divergent chromosome region in the willow warbler Phylloscopus trochilus using avian genomic resources

Genome scans have made it possible to find outlier markers thought to have been influenced by divergent selection in almost any wild population. However, the lack of genomic information in nonmodel species often makes it difficult to associate these markers with certain genes or chromosome regions. Furthermore, the extent of linkage disequilibrium (LD) in the genome will determine the density of markers required to identify the genes under selection. In this study, we investigated a chromosome region in the willow warbler Phylloscopus trochilus surrounding a single marker previously identified in a genome scan. We first located the marker in the assembled genome of another species, the zebra finch Taeniopygia guttata, and amplified surrounding sequences in Fennoscandian willow warblers. Within an investigated chromosome region of 7.3 Mb as mapped to the zebra finch genome, we observed elevated genetic differentiation between a southern and a northern population across a 2.5-Mb interval comprising numerous coding genes. Within the southern and northern populations, higher values of LD were mostly found between SNPs within the same locus, but extended across distantly situated loci when the analyses were restricted to sampling sites showing intermediate allele frequencies of southern and northern alleles. Our study shows that cross-species genome information is a useful resource to obtain candidate sequences adjacent to outlier markers in nonmodel species.     

The extent of linkage disequilibrium in four populations with distinct demographic histories

The design and feasibility of whole-genome-association studies are critically dependent on the extent of linkage disequilibrium (LD) between markers. Although there has been extensive theoretical discussion of this, few empirical data exist. The authors have determined the extent of LD among 38 biallelic markers with minor allele frequencies >.1, since these are most comparable to the common disease-susceptibility polymorphisms that association studies aim to detect. The markers come from three chromosomal regions-1,335 kb on chromosome 13q12-13, 380 kb on chromosome 19q13.2, and 120 kb on chromosome 22q13.3-which have been extensively mapped. These markers were examined in approximately 1,600 individuals from four populations, all of European origin but with different demographic histories; Afrikaners, Ashkenazim, Finns, and East Anglian British. There are few differences, either in allele frequencies or in LD, among the populations studied. A similar inverse relationship was found between LD and distance in each genomic region and in each population. Mean D' is.68 for marker pairs <5 kb apart and is.24 for pairs separated by 10-20 kb, and the level of LD is not different from that seen in unlinked marker pairs separated by >500 kb. However, only 50% of marker pairs at distances <5 kb display sufficient LD (delta>.3) to be useful in association studies. Results of the present study, if representative of the whole genome, suggest that a whole-genome scan searching for common disease-susceptibility alleles would require markers spaced < or = 5 kb apart.     

Evidence of a large-scale functional organization of mammalian chromosomes

Evidence from inbred strains of mice indicates that a quarter or more of the mammalian genome consists of chromosome regions containing clusters of functionally related genes. The intense selection pressures during inbreeding favor the coinheritance of optimal sets of alleles among these genetically linked, functionally related genes, resulting in extensive domains of linkage disequilibrium (LD) among a set of 60 genetically diverse inbred strains. Recombination that disrupts the preferred combinations of alleles reduces the ability of offspring to survive further inbreeding. LD is also seen between markers on separate chromosomes, forming networks with scale-free architecture. Combining LD data with pathway and genome annotation databases, we have been able to identify the biological functions underlying several domains and networks. Given the strong conservation of gene order among mammals, the domains and networks we find in mice probably characterize all mammals, including humans.     

A Scale-Corrected Comparison of Linkage Disequilibrium Levels between Genic and Non-Genic Regions

The understanding of non-random association between loci, termed linkage disequilibrium (LD), plays a central role in genomic research. Since causal mutations are generally not included in genomic marker data, LD between those and available markers is essential for capturing the effects of causal loci on localizing genes responsible for traits. Thus, the interpretation of association studies requires a detailed knowledge of LD patterns. It is well known that most LD measures depend on minor allele frequencies (MAF) of the considered loci and the magnitude of LD is influenced by the physical distances between loci. In the present study, a procedure to compare the LD structure between genomic regions comprising several markers each is suggested. The approach accounts for different scaling factors, namely the distribution of MAF, the distribution of pair-wise differences in MAF, and the physical extent of compared regions, reflected by the distribution of pair-wise physical distances. In the first step, genomic regions are matched based on similarity in these scaling factors. In the second step, chromosome- and genome-wide significance tests for differences in medians of LD measures in each pair are performed. The proposed framework was applied to test the hypothesis that the average LD is different in genic and non-genic regions. This was tested with a genome-wide approach with data sets for humans (Homo sapiens), a highly selected chicken line (Gallus gallus domesticus) and the model plant Arabidopsis thaliana. In all three data sets we found a significantly higher level of LD in genic regions compared to non-genic regions. About 31% more LD was detected genome-wide in genic compared to non-genic regions in Arabidopsis thaliana, followed by 13.6% in human and 6% chicken. Chromosome-wide comparison discovered significant differences on all 5 chromosomes in Arabidopsis thaliana and on one third of the human and of the chicken chromosomes.     

Patterns of diversity and linkage disequilibrium within the cosmopolitan inversion In(3R)Payne in Drosophila melanogaster are indicative of coadaptation

The cosmopolitan inversion In(3R)Payne in Drosophila melanogaster decreases in frequency with increasing distance from the equator on three continents, indicating it is subject to strong natural selection. We investigated patterns of genetic variation and linkage disequilibrium (LD) in 24 molecular markers located within and near In(3R)Payne to determine if different parts of the inversion responded to selection the same way. We found reduced variation in the markers we used compared to others distributed throughout the genome, consistent with the inversion having a relatively recent origin (相似文献   

Extent and distribution of linkage disequilibrium in three genomic regions

The positional cloning of genes underlying common complex diseases relies on the identification of linkage disequilibrium (LD) between genetic markers and disease. We have examined 127 polymorphisms in three genomic regions in a sample of 575 chromosomes from unrelated individuals of British ancestry. To establish phase, 800 individuals were genotyped in 160 families. The fine structure of LD was found to be highly irregular. Forty-five percent of the variation in disequilibrium measures could be explained by physical distance. Additional factors, such as allele frequency, type of polymorphism, and genomic location, explained <5% of the variation. Nevertheless, disequilibrium was occasionally detectable at 500 kb and was present for over one-half of marker pairs separated by <50 kb. Although these findings are encouraging for the prospects of a genomewide LD map, they suggest caution in interpreting localization due to allelic association.     

Evaluation of linkage disequilibrium measures between multi-allelic markers as predictors of linkage disequilibrium between single nucleotide polymorphisms

Effectiveness of marker-assisted selection (MAS) and quantitative trait locus (QTL) mapping using population-wide linkage disequilibrium (LD) between markers and QTLs depends on the extent of LD and how it declines with distance between markers and QTLs in a population. Marker-QTL LD can be predicted from LD between markers. Our previous work evaluated LD measures between multi-allelic markers as predictors of usable LD of multi-allelic markers with QTLs. Since single nucleotide polymorphisms (SNPs) are the current marker of choice for high-density genotyping and LD-mapping of QTLs, the objective of this study was to use LD between multi-allelic markers to predict LD among biallelic SNPs or between SNPs and QTLs. Observable LD between multi-allelic markers was evaluated using nine measures. These included two pooled and standardized measures of LD between pairs of alleles at two markers based on Lewontin's LD measure, two pooled measures of squared correlations between alleles, one standardized measure using Hardy-Weinberg heterozygosities, and four measures based on the chi-square statistic for testing for association between alleles at two loci. The standardized chi-square measure that best predicted usable LD between multi-allelic markers and QTLs, based on our previous work, overestimated usable SNP-SNP or SNP-QTL LD. Instead, three other measures were found to be good predictors of usable SNP-SNP or SNP-QTL LD when LD is generated by drift. Therefore, the LD measure between multi-allelic markers that is best for predicting usable LD in a population depends on the type of markers (i.e. multi-allelic or biallelic) that will eventually be used for QTL mapping or MAS.     

The extent of linkage disequilibrium in rice (Oryza sativa L.)

Despite its status as one of the world's major crops, linkage disequilibrium (LD) patterns have not been systematically characterized across the genome of Asian rice (Oryza sativa). Such information is critical to fully exploit the genome sequence for mapping complex traits using association techniques. Here we characterize LD in five 500-kb regions of the rice genome in three major cultivated rice varieties (indica, tropical japonica, and temperate japonica) and in the wild ancestor of Asian rice, Oryza rufipogon. Using unlinked SNPs to determine the amount of background linkage disequilibrium in each population, we find that the extent of LD is greatest in temperate japonica (probably >500 kb), followed by tropical japonica (approximately 150 kb) and indica (approximately 75 kb). LD extends over a shorter distance in O. rufipogon (<40 kb) than in any of the O. sativa groups assayed here. The differences in the extent of LD among these groups are consistent with differences in outcrossing and recombination rate estimates. As well as heterogeneity between groups, our results suggest variation in LD patterns among genomic regions. We demonstrate the feasibility of genomewide association mapping in cultivated Asian rice using a modest number of SNPs.     

High-throughput single-nucleotide polymorphism discovery and the search for candidate genes for long-term SIVmac nonprogression in Chinese rhesus macaques (Macaca mulatta)

Background Genetic differences between Indian and Chinese rhesus macaques contribute to the phenotypic variance of clinical trials, including infection with SIVmac. The completion of the rhesus genome has facilitated the discovery of several thousand markers. Methods We developed a genome‐wide SNP map for rhesus macaques containing 3869 validated markers with an average distance of 0.88 Mb and used the program VarLD to identify genomic areas with significant differences in linkage disequilibrium (LD) between Indian‐derived and Chinese rhesus macaques. Results Forty‐one statistically significant differences in LD between Chinese and Indian‐origin rhesus were detected on chromosomes 1, 4, 5 and 11. The region of greatest LD difference was located on the proximal end of chromosome one, which also contained the genes ELAVL4, MAST2 and HIVEP3. Conclusion These genomic areas provide entry to more detailed studies of gene function. This method is also applicable to the study of differences in biomarkers between regional populations of other species.     

Linkage Disequilibrium in Salt Tolerant Genotypes of Rice (Oryza sativa L)

Genome wide linkage disequilibrium (LD) was investigated in a set of 32 genotypes representing salt tolerant improved varieties and landraces and six salt sensitive genotypes of rice with 64 microsatellite markers to identify the genomic regions that are associated with salt tolerance in rice. Out of 64 markers analyzed, 36% SSR pairs exhibited significant LD at 0.05. A few regions were identified as targets of selection in 10 chromosomes with high r ² values. The model-based groups from Bayesian clustering analysis are largely consistent with known pedigrees of the lines. The increased percentage of association of SSR loci in the improved varieties indicated the role of selection in linkage disequilibrium especially for salt tolerance. LD was extended as far as 100 cM in the present study. Most of the markers (43.8%) with significant LD values were observed in the genomic regions of reported QTL for salt tolerance in rice.     

Linkage disequilibrium and inference of ancestral recombination in 538 single-nucleotide polymorphism clusters across the human genome

The prospect of using linkage disequilibrium (LD) for fine-scale mapping in humans has attracted considerable attention, and, during the validation of a set of single-nucleotide polymorphisms (SNPs) for linkage analysis, a set of data for 4,833 SNPs in 538 clusters was produced that provides a rich picture of local attributes of LD across the genome. LD estimates may be biased depending on the means by which SNPs are first identified, and a particular problem of ascertainment bias arises when SNPs identified in small heterogeneous panels are subsequently typed in larger population samples. Understanding and correcting ascertainment bias is essential for a useful quantitative assessment of the landscape of LD across the human genome. Heterogeneity in the population recombination rate, rho=4Nr, along the genome reflects how variable the density of markers will have to be for optimal coverage. We find that ascertainment-corrected rho varies along the genome by more than two orders of magnitude, implying great differences in the recombinational history of different portions of our genome. The distribution of rho is unimodal, and we show that this is compatible with a wide range of mixtures of hotspots in a background of variable recombination rate. Although rho is significantly correlated across the three population samples, some regions of the genome exhibit population-specific spikes or troughs in rho that are too large to be explained by sampling. This result is consistent with differences in the genealogical depth of local genomic regions, a finding that has direct bearing on the design and utility of LD mapping and on the National Institutes of Health HapMap project.     

Identification of positive selection signatures in pigs by comparing linkage disequilibrium variances

Selection affects the patterns of linkage disequilibrium (LD) around the site of a beneficial allele with an increase in LD among the hitchhiking alleles. Comparing the differences in regional LD between pig populations could help to identify putative genomic regions with potential adaptations for economic traits. In this study, using Illumina Porcine SNP60K BeadChip genotyping data from 207 Chinese indigenous, 117 South American village and 408 Large White pigs, we estimated the variation of genome‐wide LD between populations using the varld program. The top 0.1% standardized VarLD scores were used as a criterion for all comparisons, and compared with LD blocks, a total of four selection signatures on Sus scrofa chromosome (SSC) 7, 9, 13 and 14 were identified in all populations. These signatures overlapped with quantitative trait loci for linoleic acid content, age at puberty, number of muscle fibers per unit area, hip structure and body weight traits in pigs. Among them, one of the signatures (56.5–56.6 Mb on SSC7) in Large White pigs harbored the ADAMTSL3 gene, which is known to affect body length. The findings of this study seem to point toward recent selection in different pig populations. Further investigations are encouraged to confirm the selection signatures detected by varld in the present study.     

Linkage disequilibrium and historical effective population size in the Thoroughbred horse

Many genomic methodologies rely on the presence and extent of linkage disequilibrium (LD) between markers and genetic variants underlying traits of interest, but the extent of LD in the horse has yet to be comprehensively characterized. In this study, we evaluate the extent and decay of LD in a sample of 817 Thoroughbreds. Horses were genotyped for over 50,000 single nucleotide polymorphism (SNP) markers across the genome, with 34,848 autosomal SNPs used in the final analysis. Linkage disequilibrium, as measured by the squared correlation coefficient (r(2)), was found to be relatively high between closely linked markers (>0.6 at 5 kb) and to extend over long distances, with average r(2) maintained above non-syntenic levels for single nucleotide polymorphisms (SNPs) up to 20 Mb apart. Using formulae which relate expected LD to effective population size (N(e)), and assuming a constant actual population size, N(e) was estimated to be 100 in our population. Values of historical N(e), calculated assuming linear population growth, suggested a decrease in N(e) since the distant past, reaching a minimum twenty generations ago, followed by a subsequent increase until the present time. The qualitative trends observed in N(e) can be rationalized by current knowledge of the history of the Thoroughbred breed, and inbreeding statistics obtained from published pedigree analyses are in agreement with observed values of N(e). Given the high LD observed and the small estimated N(e), genomic methodologies such as genomic selection could feasibly be applied to this population using the existing SNP marker set.     

Evaluation of linkage disequilibrium in wheat with an L1-regularized sparse Markov network

Linkage disequilibrium (LD) is defined as a stochastic dependence between alleles at two or more loci. Although understanding LD is important in the study of the genetics of many species, little attention has been paid on how a covariance structure between many loci distributed across the genome should be represented. Given that biological systems at the cellular level often involve gene networks, it is appealing to evaluate LD from a network perspective, i.e., as a set of associated loci involved in a complex system. We applied a Markov network (MN) to study LD using data on 1,279 markers derived from 599 wheat inbred lines. The MN attempts to account for association between two markers, conditionally on the remaining markers in the network model. In this study, the recovery of the structure of a LD network was done through two variants of pseudo-likelihoods subject to an L1 penalty on the MN parameters. It is shown that, while the L1-regularized Markov network preserves features of a Bayesian network (BN), the nodes in the resulting networks have fewer links. The resulting sparse network, encoding conditional independencies, provides a clearer picture of association than marginal LD metrics, and a sparse graph eases interpretation markedly, since it includes a smaller number of edges than a BN. Thus, an L1-regularized sparse Markov network seems appealing for representing conditional LD with high-dimensional genomic data, where variables, e.g., single nucleotide polymorphism markers, are expected to be sparsely connected.     

Consistent long-range linkage disequilibrium generated by admixture in a Bantu-Semitic hybrid population

Both the optimal marker density for genome scans in case-control association studies and the appropriate study design for the testing of candidate genes depend on the genomic pattern of linkage disequilibrium (LD). In this study, we provide the first conclusive demonstration that the diverse demographic histories of human populations have produced dramatic differences in genomewide patterns of LD. Using a panel of 66 markers spanning the X chromosome, we show that, in the Lemba, a Bantu-Semitic hybrid population, markers 2 cM. Moreover, analysis of Bantu and Ashkenazi populations as putative parental populations of the Lemba shows a significant relationship between allele-frequency differentials and the LD observed in the Lemba, which demonstrates that much of the excess LD is due to admixture. Our results suggest that demographic history has such a profound effect on LD that it will not be possible to predict patterns a priori but that it will be necessary to empirically evaluate the patterns in all populations of interest.     

Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population

Background

A haplotype approach to genomic prediction using high density data in dairy cattle as an alternative to single-marker methods is presented. With the assumption that haplotypes are in stronger linkage disequilibrium (LD) with quantitative trait loci (QTL) than single markers, this study focuses on the use of haplotype blocks (haploblocks) as explanatory variables for genomic prediction. Haploblocks were built based on the LD between markers, which allowed variable reduction. The haploblocks were then used to predict three economically important traits (milk protein, fertility and mastitis) in the Nordic Holstein population.

Results

The haploblock approach improved prediction accuracy compared with the commonly used individual single nucleotide polymorphism (SNP) approach. Furthermore, using an average LD threshold to define the haploblocks (LD≥0.45 between any two markers) increased the prediction accuracies for all three traits, although the improvement was most significant for milk protein (up to 3.1 % improvement in prediction accuracy, compared with the individual SNP approach). Hotelling’s t-tests were performed, confirming the improvement in prediction accuracy for milk protein. Because the phenotypic values were in the form of de-regressed proofs, the improved accuracy for milk protein may be due to higher reliability of the data for this trait compared with the reliability of the mastitis and fertility data. Comparisons between best linear unbiased prediction (BLUP) and Bayesian mixture models also indicated that the Bayesian model produced the most accurate predictions in every scenario for the milk protein trait, and in some scenarios for fertility.

Conclusions

The haploblock approach to genomic prediction is a promising method for genomic selection in animal breeding. Building haploblocks based on LD reduced the number of variables without the loss of information. This method may play an important role in the future genomic prediction involving while genome sequences.     

Selection of genetic markers for association analyses,using linkage disequilibrium and haplotypes

The genotyping of closely spaced single-nucleotide polymorphism (SNP) markers frequently yields highly correlated data, owing to extensive linkage disequilibrium (LD) between markers. The extent of LD varies widely across the genome and drives the number of frequent haplotypes observed in small regions. Several studies have illustrated the possibility that LD or haplotype data could be used to select a subset of SNPs that optimize the information retained in a genomic region while reducing the genotyping effort and simplifying the analysis. We propose a method based on the spectral decomposition of the matrices of pairwise LD between markers, and we select markers on the basis of their contributions to the total genetic variation. We also modify Clayton's "haplotype tagging SNP" selection method, which utilizes haplotype information. For both methods, we propose sliding window-based algorithms that allow the methods to be applied to large chromosomal regions. Our procedures require genotype information about a small number of individuals for an initial set of SNPs and selection of an optimum subset of SNPs that could be efficiently genotyped on larger numbers of samples while retaining most of the genetic variation in samples. We identify suitable parameter combinations for the procedures, and we show that a sample size of 50-100 individuals achieves consistent results in studies of simulated data sets in linkage equilibrium and LD. When applied to experimental data sets, both procedures were similarly effective at reducing the genotyping requirement while maintaining the genetic information content throughout the regions. We also show that haplotype-association results that Hosking et al. obtained near CYP2D6 were almost identical before and after marker selection.     

Linkage disequilibrium in synthetic varieties of perennial ryegrass

Synthetic varieties obtained after three to four panmictic generations are variable, not structured and so can be used for association studies. The pattern of linkage disequilibrium (LD) decay determines whether a genome scan or a candidate gene approach can be used for an association study between genotype and phenotype. Our goal was to evaluate the effect of the number of parents used to build the synthetic varieties on the pattern of LD decay. LD was investigated in the gibberelic acid insensitive gene (GAI) region in three synthetic varieties of perennial ryegrass (Lolium perenne L.) chosen for their contrasted number of parents in the initial polycrosses. Results were compared with those obtained from a core collection. STS and SSR markers were used to evaluate variation, structuration and LD in each variety. As expected, the varieties variability increased with the number of parents almost up to the core collection variability. No structuration was observed in the varieties. Significant LDs were observed up to 1.6 Mb in a variety originated from six related parents and not above 174 kb in a variety originated from 336 parents. These results suggest that a candidate gene approach can be used when varieties have a large number of parents and a genome scan approach can be envisaged in specific regions when varieties have a low number of parents. Nevertheless, we strongly recommend to estimate the pattern of LD decay in the population and in the genomic region studied before performing an association study.     

Linkage disequilibrium between microsatellite markers in the Swedish Sami relative to a worldwide selection of populations

The pattern of linkage disequilibrium (LD) is affected by a number of factors, including population demography. High LD is seen in populations with a relatively limited and constant size, presumably because of genetic drift. We have examined the extent of LD among over 300 genome-wide pattern microsatellite loci in 29 populations from around the world. The pattern of LD varied between populations, with a larger extent of LD in populations with limited size relative to larger populations. In addition, the LD between 88 less well-spaced microsatellite markers from 10 different genomic regions was examined in the Sami compared with the general Swedish population. For these markers, increased LD extending up to 5 Mb was detected in the Sami. The amount of LD also differed between the chromosomal regions. The amount of LD in the Sami makes this population suitable for the mapping of complex genetic traits.Åsa Johansson, Veronika Vavruch-Nilsson contributed equally to the report