Over 30 mutations of the B-RAF gene associated with human cancers have been identified, the majority of which are located within the kinase domain. Here we show that of 22 B-RAF mutants analyzed, 18 have elevated kinase activity and signal to ERK in vivo. Surprisingly, three mutants have reduced kinase activity towards MEK in vitro but, by activating C-RAF in vivo, signal to ERK in cells. The structures of wild type and oncogenic V599EB-RAF kinase domains in complex with the RAF inhibitor BAY43-9006 show that the activation segment is held in an inactive conformation by association with the P loop. The clustering of most mutations to these two regions suggests that disruption of this interaction converts B-RAF into its active conformation. The high activity mutants signal to ERK by directly phosphorylating MEK, whereas the impaired activity mutants stimulate MEK by activating endogenous C-RAF, possibly via an allosteric or transphosphorylation mechanism.

SUMMARY The complex network of specialized cells and molecules in the immune system has evolved to defend against pathogens, but inadvertent immune system attacks on “self” result in autoimmune disease. Both genetic regulation of immune cell levels and their relationships with autoimmunity are largely undetermined. Here, we report genetic contributions to quantitative levels of 95 cell types encompassing 272 immune traits, in a cohort of 1,629 individuals from four clustered Sardinian villages. We first estimated trait heritability, showing that it can be substantial, accounting for up to 87% of the variance (mean 41%). Next, by assessing ~8.2 million variants that we identified and confirmed in an extended set of 2,870 individuals, 23 independent variants at 13 loci associated with at least one trait. Notably, variants at three loci (HLA, IL2RA, and SH2B3/ATXN2) overlap with known autoimmune disease associations. These results connect specific cellular phenotypes to specific genetic variants, helping to explicate their involvement in disease.

We report ~17.6M genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from prior sequencing-based compilations and enriched for predicted functional consequence. Furthermore, ~76K variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. Fourteen signals, including two major new loci, were observed for lipid levels, and 19, including two novel loci, for inflammatory markers. New associations would be missed in analyses based on 1000 Genomes data, underlining the advantages of large-scale sequencing in this founder population.

Epithelial ovarian cancer (EOC) is the leading cause of death from gynecological malignancy in the developed world accounting for 4 percent of deaths from cancer in women1. We performed a three-phase genome-wide association study of EOC survival in 8,951 EOC cases with available survival time data, and a parallel association analysis of EOC susceptibility. Two SNPs at 19p13.11, rs8170 and rs2363956, showed evidence of association with survival (overall P=5×10−4 and 6×10−4), but did not replicate in phase 3. However, the same two SNPs demonstrated genome-wide significance for risk of serous EOC (P=3×10−9 and 4×10−11 respectively). Expression analysis of candidate genes at this locus in ovarian tumors supported a role for the BRCA1 interacting gene C19orf62, also known as MERIT40, which contains rs8170, in EOC development.

Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover, and evolution of new pathogen lineages. In order to tackle these grand challenges, a new set of tools that include disease surveillance and improved detection technologies including pathogen sensors and predictive modeling and data analytics are needed to prevent future outbreaks. Herein, we describe an integrated research agenda that could help mitigate future plant disease pandemics.