The creation of 'consistent areas through time' (CATTs) in Scotland, 1981-2001

Small area analysis of sociodemographic change over time is often impeded by the changing configuration of census zones for each decennial UK census. Approaches for matching zone configurations exist, but these typically require population estimation techniques, which inevitably involve some error. Because of the postcode-based geographical zoning system used in Scottish censuses, it is possible to create a local-area geography which is consistent for recent censuses. Here we present a methodology used to create three sets of consistent areas through time (CATTs) that can be used for analysing comparable small area data output from the 1981, 1991 and 2001 Censuses.     

The genome sequence of the rice blast fungus Magnaporthe grisea

Magnaporthe grisea is the most destructive pathogen of rice worldwide and the principal model organism for elucidating the molecular basis of fungal disease of plants. Here, we report the draft sequence of the M. grisea genome. Analysis of the gene set provides an insight into the adaptations required by a fungus to cause disease. The genome encodes a large and diverse set of secreted proteins, including those defined by unusual carbohydrate-binding domains. This fungus also possesses an expanded family of G-protein-coupled receptors, several new virulence-associated genes and large suites of enzymes involved in secondary metabolism. Consistent with a role in fungal pathogenesis, the expression of several of these genes is upregulated during the early stages of infection-related development. The M. grisea genome has been subject to invasion and proliferation of active transposable elements, reflecting the clonal nature of this fungus imposed by widespread rice cultivation.     

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean. These links are extensive, influencing a range of climate processes such as hurricane activity and African Sahel and Amazonian droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures, but climate models have so far failed to reproduce these interactions and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860-2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910-1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol-cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol-cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

MYH9 is associated with nondiabetic end-stage renal disease in African Americans

As end-stage renal disease (ESRD) has a four times higher incidence in African Americans compared to European Americans, we hypothesized that susceptibility alleles for ESRD have a higher frequency in the West African than the European gene pool. We carried out a genome-wide admixture scan in 1,372 ESRD cases and 806 controls and found a highly significant association between excess African ancestry and nondiabetic ESRD (lod score = 5.70) but not diabetic ESRD (lod = 0.47) on chromosome 22q12. Each copy of the European ancestral allele conferred a relative risk of 0.50 (95% CI = 0.39-0.63) compared to African ancestry. Multiple common SNPs (allele frequencies ranging from 0.2 to 0.6) in the gene encoding nonmuscle myosin heavy chain type II isoform A (MYH9) were associated with two to four times greater risk of nondiabetic ESRD and accounted for a large proportion of the excess risk of ESRD observed in African compared to European Americans.     

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.     

Osteoclast-poor human osteopetrosis due to mutations in the gene encoding RANKL

Autosomal recessive osteopetrosis is usually associated with normal or elevated numbers of nonfunctional osteoclasts. Here we report mutations in the gene encoding RANKL (receptor activator of nuclear factor-KB ligand) in six individuals with autosomal recessive osteopetrosis whose bone biopsy specimens lacked osteoclasts. These individuals did not show any obvious defects in immunological parameters and could not be cured by hematopoietic stem cell transplantation; however, exogenous RANKL induced formation of functional osteoclasts from their monocytes, suggesting that they could, theoretically, benefit from exogenous RANKL administration.     

Data Mining the Intellectual Revival of ‘Catastrophic’ Mother Nature

Earth-shaping catastrophic events have long focused the attention of the geographical and geological sciences, and captured the public imagination. During the past 40 years, neocatastrophism has emerged as a key paradigm that reflects widespread changes involving cultural, scientific, political and technological spheres. Nonetheless, the extent, chronology and origin of this trend are equivocal. Here, we use Google Ngram to quantitatively explore the recent development of catastrophism. We elucidate a discernable rise in neocatastrophic thinking during the last quarter of the twenty-first century that can be linked to the environmental awakening of the 1960s. It is suggested that these discourses of ‘shock’ and ‘fear’ partly correspond to a media-driven dramatization of natural hazards, exploited by scientists and journalists to attract wider readership.