Precise Regulation of Gene Expression Dynamics Favors Complex Promoter Architectures

Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Dynamics and Correlation of Serum Cortisol and Corticosterone under Different Physiological or Stressful Conditions in Mice

Although plasma corticosterone is considered the main glucocorticoid involved in regulation of stress responses in rodents, the presence of plasma cortisol and whether its level can be used as an indicator for rodent activation of stress remain to be determined. In this study, effects of estrous cycle stage, circadian rhythm, and acute and chronic (repeated or unpredictable) stressors of various severities on dynamics and correlation of serum cortisol and corticosterone were examined in mice. A strong (r = 0.6-0.85) correlation between serum cortisol and corticosterone was observed throughout the estrous cycle, all day long, and during acute or repeated restraints, chronic unpredictable stress and acute forced swimming or heat stress. Both hormones increased to the highest level on day 1 of repeated-restraint or unpredictable stresses, but after that, whereas the concentration of cortisol did not change, that of corticosterone showed different dynamics. Thus, whereas corticosterone declined dramatically during repeated restraints, it remained at the high level during unpredictable stress. During forced swimming or heat stress, whereas cortisol increased to the highest level within 3 min., corticosterone did not reach maximum until 40 min. of stress. Analysis with HPLC and HPLC-MS further confirmed the presence of cortisol in mouse serum. Taken together, results (i) confirmed the presence of cortisol in mouse serum and (ii) suggested that mouse serum cortisol and corticosterone are closely correlated in dynamics under different physiological or stressful conditions, but, whereas corticosterone was a more adaptation-related biomarker than cortisol during chronic stress, cortisol was a quicker responder than corticosterone during severe acute stress