The effect of marker characteristics on the power to detect linkage disequilibrium due to single or multiple ancestral mutations

Population structure in sorghum accessions from West Africa differing in race and maturity class

Accounting for population structure to minimize spurious associations in association analyses is of crucial importance. With sorghum genomic sequence information being available, there is a growing interest in performing such association studies for a number of important agronomic traits using a candidate gene approach. The aims of our study were to conduct a systematic survey of molecular genetic diversity and analyze the population structure in cultivated sorghum [Sorghum bicolor (L.) Moench] accessions from West Africa. Our analysis included 219 West African cultivated sorghum accessions with differing maturity intended for a marker-trait association study. A total of 27 SSRs were used, which resulted in detection of 513 alleles. Genetic diversity estimates for the accessions were found to be high. The accessions were divided into two subgroups using a model-based approach. Our findings partly agree with previous studies in that the guinea race accessions could be distinguished clearly from other accessions included in the analysis. Race and geographical origin of the accessions may be responsible for the structure we observed in our material. The extent of linkage disequilibrium for all combinations of SSRs was in agreement with expectations based on the mating system.

A linkage map of the Atlantic salmon (Salmo salar) based on EST-derived SNP markers

Background

The Atlantic salmon is a species of commercial and ecological significance. Like other salmonids, the species displays residual tetrasomy and a large difference in recombination rate between sexes. Linkage maps with full genome coverage, containing both type I and type II markers, are needed for progress in genomics. Furthermore, it is important to estimate levels of linkage disequilibrium (LD) in the species. In this study, we developed several hundred single nucleotide polymorphism (SNP) markers for the Atlantic salmon, and constructed male and female linkage maps containing SNP and microsatellite markers. We also investigated further the distribution of male and female recombination events across the genome, and estimated levels of LD between pairs of markers.

Results

The male map had 29 linkage groups and was 390 cM long. The female map had 30 linkage groups as was 1983 cM long. In total, the maps contained 138 microsatellite markers and 304 SNPs located within genes, most of which were successfully annotated. The ratio of male to female recombination events was either close to zero or very large, indicating that there is little overlap between regions in which male and female crossovers occur. The female map is likely to have close to full genome coverage, while the majority of male linkage groups probably lack markers in telomeric regions where male recombination events occur. Levels of r² increased with decreasing inter-marker distance in a bimodal fashion; increasing slowly from ~60 cM, and more rapidly more from ~12 cM. Long-ranging LD may be consequence of recent admixture in the population, the population being a 'synthetic' breeding population with contributions from several distinct rivers. Levels of r² dropped to half its maximum value (above baseline) within 15 cM, and were higher than 0.2 above baseline for unlinked markers ('useful LD') at inter-marker distances less than 5 cM.

Conclusion

The linkage map presented here is an important resource for genetic, comparative, and physical mapping of the Atlantic salmon. The female map is likely to have a map coverage that is not far from complete, whereas the male map length is likely to be significantly shorter than the true map, due to suboptimal marker coverage in the apparently small physical regions where male crossovers occur. 'Useful LD' was found at inter-marker distances less than 5 cM.

Investigation into the ability of SNP chipsets and microsatellites to detect association with a disease locus

We wished to investigate the ability of different SNP chipsets to detect association with a disease and to investigate the linkage disequilibrium (LD) relationships between microsatellites and nearby SNPs in order to assess their potential usefulness to detect association.

SNP genotypes were obtained from HapMap and microsatellite genotypes from CEPH. 5000 SNPs were simulated as disease genes which increased penetrance from 0.01 to 0.02 in a sample of 400 cases and 400 controls. The power of flanking SNPs to detect association was tested using sets of 1, 2, 3 or 4 markers analysed with haplotype analysis or logistic regression and using either all HapMap markers or those from the Affymetrix 500K, Illumina 300K or Illumina 550K chipsets. Additionally, LD relationships between 10 microsatellites and SNPs within 2Mb of each other were studied.

The power for one of the markers to detect association at p = 0.001 was around 0.4. Power was slightly better for logistic regression than haplotype analysis and for two-marker as opposed to single marker analysis but analysing with larger numbers markers had little benefit. The Illumina 550K marker set was better able to detect association than the other two and was almost as powerful as using all HapMap markers. Microsatellites had detectable LD with only a small number of nearby SNPs and the pattern of LD was very variable.

Available chipsets have quite good ability to detect association although obviously results will be critically dependent on the nature of the genetic effect on risk, sample size and the actual LD relationships of the susceptibility polymorphisms involved. Microsatellites seem ill-suited for systematic studies to detect association.

The future of association studies: gene-based analysis and replication

Historically, association tests were limited to single variants, so that the allele was considered the basic unit for association testing. As marker density increases and indirect approaches are used to assess association through linkage disequilibrium, association is now frequently considered at the haplotypic level. We suggest that there are difficulties in replicating association findings at the single-nucleotide-polymorphism (SNP) or the haplotype level, and we propose a shift toward a gene-based approach in which all common variation within a candidate gene is considered jointly. Inconsistencies arising from population differences are more readily resolved by use of a gene-based approach rather than either a SNP-based or a haplotype-based approach. A gene-based approach captures all of the potential risk-conferring variations; thus, negative findings are subject only to the issue of power. In addition, chance findings due to multiple testing can be readily accounted for by use of a genewide-significance level. Meta-analysis procedures can be formalized for gene-based methods through the combination of P values. It is only a matter of time before all variation within genes is mapped, at which point the gene-based approach will become the natural end point for association analysis and will inform our search for functional variants relevant to disease etiology.