Notes

CTCF manages NELF, DSIF as well as P-TEFb recruiting in the course of transcription.
Microorganisms play vital roles in modulating organic matter decomposition and nutrient cycling in soil ecosystems. The enzyme latch paradigm posits microbial degradation of polyphenols is hindered in anoxic peat leading to polyphenol accumulation, and consequently diminished microbial activity. This model assumes that polyphenols are microbially unavailable under anoxia, a supposition that has not been thoroughly investigated in any soil type. Here, we use anoxic soil reactors amended with and without a chemically defined polyphenol to test this hypothesis, employing metabolomics and genome-resolved metaproteomics to interrogate soil microbial polyphenol metabolism. Challenging the idea that polyphenols are not bioavailable under anoxia, we provide metabolite evidence that polyphenols are depolymerized, resulting in monomer accumulation, followed by the generation of small phenolic degradation products. Further, we show that soil microbiome function is maintained, and possibly enhanced, with polyphenol addition. In summary, this study provides chemical and enzymatic evidence that some soil microbiota can degrade polyphenols under anoxia and subvert the assumed polyphenol lock on soil microbial metabolism.Annotation of structural variations (SVs) and base-level karyotyping in cancer cells remains challenging. Here, we present Integrative Framework for Genome Reconstruction (InfoGenomeR)-a graph-based framework that can reconstruct individual SVs into karyotypes based on whole-genome sequencing data, by integrating SVs, total copy number alterations, allele-specific copy numbers, and haplotype information. Using whole-genome sequencing data sets of patients with breast cancer, glioblastoma multiforme, and ovarian cancer, we demonstrate the analytical potential of InfoGenomeR. We identify recurrent derivative chromosomes derived from chromosomes 11 and 17 in breast cancer samples, with homogeneously staining regions for CCND1 and ERBB2, and double minutes and breakage-fusion-bridge cycles in glioblastoma multiforme and ovarian cancer samples, respectively. Moreover, we show that InfoGenomeR can discriminate private and shared SVs between primary and metastatic cancer sites that could contribute to tumour evolution. These findings indicate that InfoGenomeR can guide targeted therapies by unravelling cancer-specific SVs on a genome-wide scale.Rapid-response vaccine production platform technologies, including RNA vaccines, are being developed to combat viral epidemics and pandemics. A key enabler of rapid response is having quality-oriented disease-agnostic manufacturing protocols ready ahead of outbreaks. We are the first to apply the Quality by Design (QbD) framework to enhance rapid-response RNA vaccine manufacturing against known and future viral pathogens. This QbD framework aims to support the development and consistent production of safe and efficacious RNA vaccines, integrating a novel qualitative methodology and a quantitative bioprocess model. The qualitative methodology identifies and assesses the direction, magnitude and shape of the impact of critical process parameters (CPPs) on critical quality attributes (CQAs). The mechanistic bioprocess model quantifies and maps the effect of four CPPs on the CQA of effective yield of RNA drug substance. Consequently, the first design space of an RNA vaccine synthesis bioreactor is obtained. The cost-yield optimization together with the probabilistic design space contribute towards automation of rapid-response, high-quality RNA vaccine production.Gain of chromosome 1q (+1q) is one of the most common recurrent cytogenetic abnormalities in multiple myeloma (MM), occurring in approximately 40% of newly diagnosed cases. Although it is often considered a poor prognostic marker in MM, +1q has not been uniformly adopted as a high-risk cytogenetic abnormality in guidelines. Controversy exists regarding the importance of copy number, as well as whether +1q is itself a driver of poor outcomes or merely a common passenger genetic abnormality in biologically unstable disease. Although the identification of a clear pathogenic mechanism from +1q remains elusive, many genes at the 1q21 locus have been proposed to cause early progression and resistance to anti-myeloma therapy. read more The plethora of potential drivers suggests that +1q is not only a causative factor or poor outcomes in MM but may be targetable and/or predictive of response to novel therapies. This review will summarize our current understanding of the pathogenesis of +1q in plasma cell neoplasms, the impact of 1q copy number, identify potential genetic drivers of poor outcomes within this subset, and attempt to clarify its clinical significance and implications for the management of patients with multiple myeloma.The peopling of Sahul (the combined continent of Australia and New Guinea) represents the earliest continental migration and settlement event of solely anatomically modern humans, but its patterns and ecological drivers remain largely conceptual in the current literature. We present an advanced stochastic-ecological model to test the relative support for scenarios describing where and when the first humans entered Sahul, and their most probable routes of early settlement. The model supports a dominant entry via the northwest Sahul Shelf first, potentially followed by a second entry through New Guinea, with initial entry most consistent with 50,000 or 75,000 years ago based on comparison with bias-corrected archaeological map layers. The model's emergent properties predict that peopling of the entire continent occurred rapidly across all ecological environments within 156-208 human generations (4368-5599 years) and at a plausible rate of 0.71-0.92 km year-1. More broadly, our methods and approaches can readily inform other global migration debates, with results supporting an exit of anatomically modern humans from Africa 63,000-90,000 years ago, and the peopling of Eurasia in as little as 12,000-15,000 years via inland routes.Osteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction.
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