The measurement of circulating nucleic acids has transformed the management of chronic viral infections such as HIV. The development of analogous markers for individuals with cancer could similarly enhance the management of their disease. DNA containing somatic mutations is highly tumor specific and thus, in theory, can provide optimum markers. However, the number of circulating mutant gene fragments is small compared to the number of normal circulating DNA fragments, making it difficult to detect and quantify them with the sensitivity required for meaningful clinical use. In this study, we applied a highly sensitive approach to quantify circulating tumor DNA (ctDNA) in 162 plasma samples from 18 subjects undergoing multimodality therapy for colorectal cancer. We found that ctDNA measurements could be used to reliably monitor tumor dynamics in subjects with cancer who were undergoing surgery or chemotherapy. We suggest that this personalized genetic approach could be generally applied to individuals with other types of cancer.

Mouse embryonic stem (ES) cells are competent for production of all fetal and adult cell types. However, the utility of ES cells as a developmental model or as a source of defined cell populations for pharmaceutical screening or transplantation is compromised because their differentiation in vitro is poorly controlled. Specification of primary lineages is not understood and consequently differentiation protocols are empirical, yielding variable and heterogeneous outcomes. Here we report that neither multicellular aggregation nor coculture is necessary for ES cells to commit efficiently to a neural fate. In adherent monoculture, elimination of inductive signals for alternative fates is sufficient for ES cells to develop into neural precursors. This process is not a simple default pathway, however, but requires autocrine fibroblast growth factor (FGF). Using flow cytometry quantitation and recording of individual colonies, we establish that the bulk of ES cells undergo neural conversion. The neural precursors can be purified to homogeneity by fluorescence activated cell sorting (FACS) or drug selection. This system provides a platform for defining the molecular machinery of neural commitment and optimizing the efficiency of neuronal and glial cell production from pluripotent mammalian stem cells.

Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ∼ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ∼ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.