Estimating individual genome-wide autozygosity is important both in the identification of recessive disease variants via homozygosity mapping and in the investigation of the effects of genome-wide homozygosity on traits of biomedical importance. Approaches have tended to involve either single-point estimates or rather complex multipoint methods of inferring individual autozygosity, all on the basis of limited marker data. Now, with the availability of high-density genome scans, a multipoint, observational method of estimating individual autozygosity is possible. Using data from a 300,000 SNP panel in 2618 individuals from two isolated and two more-cosmopolitan populations of European origin, we explore the potential of estimating individual autozygosity from data on runs of homozygosity (ROHs). Termed F(roh), this is defined as the proportion of the autosomal genome in runs of homozygosity above a specified length. Mean F(roh) distinguishes clearly between subpopulations classified in terms of grandparental endogamy and population size. With the use of good pedigree data for one of the populations (Orkney), F(roh) was found to correlate strongly with the inbreeding coefficient estimated from pedigrees (r = 0.86). Using pedigrees to identify individuals with no shared maternal and paternal ancestors in five, and probably at least ten, generations, we show that ROHs measuring up to 4 Mb are common in demonstrably outbred individuals. Given the stochastic variation in ROH number, length, and location and the fact that ROHs are important whether ancient or recent in origin, approaches such as this will provide a more useful description of genomic autozygosity than has hitherto been possible.

Pulmonary function measures are heritable traits that predict morbidity and mortality and define chronic obstructive pulmonary disease (COPD). We tested genome-wide association with forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in the SpiroMeta consortium (n = 20,288 individuals of European ancestry). We conducted a meta-analysis of top signals with data from direct genotyping (n ≤ 32,184 additional individuals) and in silico summary association data from the CHARGE Consortium (n = 21,209) and the Health 2000 survey (n ≤ 883). We confirmed the reported locus at 4q31 and identified associations with FEV1 or FEV1/FVC and common variants at five additional loci: 2q35 in TNS1 (P = 1.11 × 10−12), 4q24 in GSTCD (2.18 × 10−23), 5q33 in HTR4 (P = 4.29 × 10−9), 6p21 in AGER (P = 3.07 × 10−15) and 15q23 in THSD4 (P = 7.24 × 10−15). mRNA analyses showed expression of TNS1, GSTCD, AGER, HTR4 and THSD4 in human lung tissue. These associations offer mechanistic insight into pulmonary function regulation and indicate potential targets for interventions to alleviate respiratory disease.

SummaryIn any partially inbred population, ' junctions' are the loci that form boundaries between segments of ancestral chromosomes. Here we show that the expected number of junctions per Morgan in such a population is linearly related to the inbreeding coefficient of the population, with a maximum in a completely inbred population corresponding to the prediction given by Stam (1980). We further show that high-density marker maps (fully informative markers with average densities of up to 200 per cM) will fail to detect a significant proportion of the junctions present in highly inbred populations. The number of junctions detected is lower than that which would be expected if junctions were distributed randomly along the chromosome, and we show that junctions are not, in fact randomly spaced. This non-random spacing of junctions significantly increases the number of markers that is required to detect 90 % of the junctions present on any chromosome : a marker count of at least 12 times the number of junctions present will be needed to detect this proportion.

Differences in genomic structure between individuals are ubiquitous features of human genetic variation. Specific copy number variants (CNVs) have been associated with susceptibility to numerous complex psychiatric disorders, including attention-deficit-hyperactivity disorder, autism-spectrum disorders and schizophrenia. These disorders often display co-morbidity with low intelligence. Rare chromosomal deletions and duplications are associated with these disorders, so it has been suggested that these deletions or duplications may be associated with differences in intelligence. Here we investigate associations between large (≥500kb), rare (<1% population frequency) CNVs and both fluid and crystallized intelligence in community-dwelling older people. We observe no significant associations between intelligence and total CNV load. Examining individual CNV regions previously implicated in neuropsychological disorders, we find suggestive evidence that CNV regions around SHANK3 are associated with fluid intelligence as derived from a battery of cognitive tests. This is the first study to examine the effects of rare CNVs as called by multiple algorithms on cognition in a large non-clinical sample, and finds no effects of such variants on general cognitive ability.

Genetic biobanking studies are becoming increasingly common as researchers recognise the need for large samples to identify the genetic basis of susceptibility to complex disease. In the present review, the authors give a brief overview of some of the issues that should be considered when implementing such a large-scale project, from study design to sample management, data coding and storage to the statistical analysis and engagement with the public. Specific solutions to these issues are presented, as implemented in the Generation Scotland projects, but the general principles outlined are relevant to any biobanking study.

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