In the PNAS Early Edition this week, the University of Chicago's Yong Woo and Wen-Hsiung Li describe the relationships among the "gene clustering pattern, promoter architecture, and gene expression stability in eukaryotic genomes." In a budding yeast model, Woo and Li found that "genes with a short upstream distance tend to have low gene expression variability, and their [promoters are] flanked by strongly positioned nucleosomes and [tend] to have low nucleosome occupancy." The pair also reports that head-to-head genes, when compared with head-to-tail genes, show decreased gene expression variability across a diverse set of eukaryotes.
A team led by investigators at the University of California, Los Angeles, reports its comprehensive gene expression investigation in human leukocyte subtypes, in which it "mapped the cellular origin of transcripts found to be differentially expressed in the circulating immune cells from chronically lonely individuals." The team found that genes associated with loneliness derive "primarily from plasmacytoid dendritic cells, monocytes, and, to a lesser extent, B lymphocytes," and more broadly, they observed "per-cell changes in the expression of inducible genes and related more strongly to the subjective experience of loneliness than to objective social network size."
Researchers in Switzerland present a two-stage method for serum cancer biomarker detection and report their application of this approach to accurately detect cancer-causing mutations — Pten inactivation, among others — in prostate cancer. Using label-free quantitative proteomics on a mouse model, the researchers "showed that Pten inactivation leads to measurable perturbations in the murine prostate and serum glycoproteome," as they report in PNAS this week. "Following bioinformatic prioritization, in a second stage we applied targeted proteomics to detect and quantify 39 human ortholog candidate biomarkers in the sera of [prostate cancer] patients and control individuals." The team suggests that its two-stage approach represents an effective strategy for cancer biomarker detection "based on the integration of experimental mouse models, proteomics-based technologies, and computational modeling."
A trio of investigators at the Southern Illinois University School of Medicine shows that "human mismatch correction reactions in cell-free extracts occur during concomitant nick-dependent nucleosome assembly shaped by the replication histone chaperone CAF-I." In addition, this dependent nucelosome assembly protects discontinuous mistmatch-containing strands from degradation by mismatch-repair machinery. "There is active crosstalk between MMR and replication-dependent nucleosome assembly during the correction of DNA replication errors," the authors write in PNAS.