Genome of an arbuscular mycorrhizal fungus provides insight into the oldest plant symbiosis.

The mutualistic symbiosis involving Glomeromycota, a distinctive phylum of early diverging Fungi, is widely hypothesized to have promoted the evolution of land plants during the middle Paleozoic. These arbuscular mycorrhizal fungi (AMF) perform vital functions in the phosphorus cycle that are fundamental to sustainable crop plant productivity. The unusual biological features of AMF have long fascinated evolutionary biologists. The coenocytic hyphae host a community of hundreds of nuclei and reproduce clonally through large multinucleated spores. It has been suggested that the AMF maintain a stable assemblage of several different genomes during the life cycle, but this genomic organization has been questioned. Here we introduce the 153-Mb haploid genome of Rhizophagus irregularis and its repertoire of 28,232 genes. The observed low level of genome polymorphism (0.43 SNP per kb) is not consistent with the occurrence of multiple, highly diverged genomes. The expansion of mating-related genes suggests the existence of cryptic sex-related processes. A comparison of gene categories confirms that R. irregularis is close to the Mucoromycotina. The AMF obligate biotrophy is not explained by genome erosion or any related loss of metabolic complexity in central metabolism, but is marked by a lack of genes encoding plant cell wall-degrading enzymes and of genes involved in toxin and thiamine synthesis. A battery of mycorrhiza-induced secreted proteins is expressed in symbiotic tissues. The present comprehensive repertoire of R. irregularis genes provides a basis for future research on symbiosis-related mechanisms in Glomeromycota.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.

HIV-1 vaccines and adaptive trial designs.

Developing a vaccine against the human immunodeficiency virus (HIV) poses an exceptional challenge. There are no documented cases of immune-mediated clearance of HIV from an infected individual, and no known correlates of immune protection. Although nonhuman primate models of lentivirus infection have provided valuable data about HIV pathogenesis, such models do not predict HIV vaccine efficacy in humans. The combined lack of a predictive animal model and undefined biomarkers of immune protection against HIV necessitate that vaccines to this pathogen be tested directly in clinical trials. Adaptive clinical trial designs can accelerate vaccine development by rapidly screening out poor vaccines while extending the evaluation of efficacious ones, improving the characterization of promising vaccine candidates and the identification of correlates of immune protection.