The fine-scale genetic structure of the British population.

Fine-scale genetic variation between human populations is interesting as a signature of historical demographic events and because of its potential for confounding disease studies. We use haplotype-based statistical methods to analyse genome-wide single nucleotide polymorphism (SNP) data from a carefully chosen geographically diverse sample of 2,039 individuals from the United Kingdom. This reveals a rich and detailed pattern of genetic differentiation with remarkable concordance between genetic clusters and geography. The regional genetic differentiation and differing patterns of shared ancestry with 6,209 individuals from across Europe carry clear signals of historical demographic events. We estimate the genetic contribution to southeastern England from Anglo-Saxon migrations to be under half, and identify the regions not carrying genetic material from these migrations. We suggest significant pre-Roman but post-Mesolithic movement into southeastern England from continental Europe, and show that in non-Saxon parts of the United Kingdom, there exist genetically differentiated subgroups rather than a general 'Celtic' population.

People of the British Isles: preliminary analysis of genotypes and surnames in a UK-control population.

There is a great deal of interest in a fine-scale population structure in the UK, both as a signature of historical immigration events and because of the effect population structure may have on disease association studies. Although population structure appears to have a minor impact on the current generation of genome-wide association studies, it is likely to have a significant part in the next generation of studies designed to search for rare variants. A powerful way of detecting such structure is to control and document carefully the provenance of the samples involved. In this study, we describe the collection of a cohort of rural UK samples (The People of the British Isles), aimed at providing a well-characterised UK-control population that can be used as a resource by the research community, as well as providing a fine-scale genetic information on the British population. So far, some 4000 samples have been collected, the majority of which fit the criteria of coming from a rural area and having all four grandparents from approximately the same area. Analysis of the first 3865 samples that have been geocoded indicates that 75% have a mean distance between grandparental places of birth of 37.3 km, and that about 70% of grandparental places of birth can be classed as rural. Preliminary genotyping of 1057 samples demonstrates the value of these samples for investigating a fine-scale population structure within the UK, and shows how this can be enhanced by the use of surnames.

Multiplexed shotgun genotyping for rapid and efficient genetic mapping.

We present a new approach to genotyping based on multiplexed shotgun sequencing that can identify recombination breakpoints in a large number of individuals simultaneously at a resolution sufficient for most mapping purposes, such as quantitative trait locus (QTL) mapping and mapping of induced mutations. We first describe a simple library construction protocol that uses just 10 ng of genomic DNA per individual and makes the approach accessible to any laboratory with standard molecular biology equipment. Sequencing this library results in a large number of sequence reads widely distributed across the genomes of multiplexed bar-coded individuals. We develop a Hidden Markov Model to estimate ancestry at all genomic locations in all individuals using these data. We demonstrate the utility of the approach by mapping a dominant marker allele in D. simulans to within 105 kb of its true position using 96 F1-backcross individuals genotyped in a single lane on an Illumina Genome Analyzer. We further demonstrate the utility of our method by genetically mapping more than 400 previously unassembled D. simulans contigs to linkage groups and by evaluating the quality of targeted introgression lines. At this level of multiplexing and divergence between strains, our method allows estimation of recombination breakpoints to a median of 38-kb intervals. Our analysis suggests that higher levels of multiplexing and/or use of strains with lower levels of divergence are practicable.

Fast left ventricular mass and volume assessment in mice with three-dimensional guide-point modeling.

PURPOSE: To investigate the accuracy (vs. standard manual analysis) and precision (scan-rescan reproducibility) of three-dimensional guide-point modeling (GPM) for the assessment of left ventricular (LV) function in mice. METHODS: Six male wildtype C57/Bl6 mice (weight 26.2 +/- 1.1 g) were scanned twice, 3 days apart. Each scan was performed twice, at 0.2 mm/pixel with one average and at 0.1 mm/pixel with two averages. The 24 studies were anonymized and analyzed in blinded fashion using GPM and standard manual slice summation. RESULTS: The average error between GPM and standard analysis was 2.3 +/- 5.8 mg in mass, 1.7 +/- 3.2 microL in end-diastolic volume, 2.3 +/- 3.1 microL in end-systolic volume, -2.7 +/- 4.3% in ejection fraction, -0.6 +/- 3.3 microL in stroke volume, and -0.31 +/- 1.56 ml . min(-1) in cardiac output (mean difference +/- SD of differences, n = 24). The average time taken was 8.0 +/- 2.5 minutes for 3D GPM and 48.5 +/- 8.9 minutes for standard analysis (n = 24). Scan-rescan reproducibility results were similar to the standard analysis. No significant differences were found using linear mixed effects modeling in either accuracy or precision between scan resolutions or analysis method. CONCLUSION: 3D GPM enables fast analysis of mouse LV function, with similar accuracy and reproducibility to standard analysis. An image resolution of 0.2 mm/pixel with one average is adequate for LV function studies.

Worldwide population differentiation at disease-associated SNPs.

BACKGROUND: Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs). METHODS: We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals. RESULTS: On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations. CONCLUSION: Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants.

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.