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The extracellular loops of bacterial outer membrane (OM) transporters are thought to sample a range of conformations in the apo state but to undergo a gating motion and assume a more defined conformation upon the binding of substrate. Here, we use pulse electron paramagnetic resonance to examine the conformations of the extracellular loops of BtuB, the Escherichia coli TonB-dependent vitamin B12 transporter, in whole cells. Unlike previous measurements carried out in vitro, the loops assume well-defined configurations in situ that closely match the in surfo crystal structures. Moreover, there is no evidence that the loops undergo significant gating motions upon the binding of substrate. The results demonstrate that the structure of BtuB is dependent upon an intact native OM environment, in which a critical component is likely to be the extracellular lipopolysaccharide. In general, this work indicates that measurements on OM proteins in reconstituted membrane systems may not reflect the native state of the protein in vivo.Genetic information is encoded in the DNA double helix, which, in its physiological milieu, is characterized by the iconical Watson-Crick nucleo-base pairing. Recent NMR relaxation experiments revealed the transient presence of an alternative, Hoogsteen (HG) base pairing pattern in naked DNA duplexes, and estimated its relative stability and lifetime. In contrast with DNA, such structures were not observed in RNA duplexes. Understanding HG base pairing is important because the underlying "breathing" motion between the two conformations can significantly modulate protein binding. However, a detailed mechanistic insight into the transition pathways and kinetics is still missing. We performed enhanced sampling simulation (with combined metadynamics and adaptive force-bias method) and Markov state modeling to obtain accurate free energy, kinetics, and the intermediates in the transition pathway between Watson-Crick and HG base pairs for both naked B-DNA and A-RNA duplexes. The Markov state model constructed from our unbiased MD simulation data revealed previously unknown complex extrahelical intermediates in the seemingly simple process of base flipping in B-DNA. Extending our calculation to A-RNA, for which HG base pairing is not observed experimentally, resulted in relatively unstable, single-hydrogen-bonded, distorted Hoogsteen-like bases. Unlike B-DNA, the transition pathway primarily involved base paired and intrahelical intermediates with transition timescales much longer than that of B-DNA. The seemingly obvious flip-over reaction coordinate (i.e., the glycosidic torsion angle) is unable to resolve the intermediates. Instead, a multidimensional picture involving backbone dihedral angles and distance between hydrogen bond donor and acceptor atoms is required to gain insight into the molecular mechanism.With mounting interest in translating genome-wide association study (GWAS) hits from large meta-analyses (meta-GWAS) in diverse clinical settings, evaluating their generalizability in target populations is crucial. Here, we consider long-term survivors of childhood cancers from the St. Jude Lifetime Cohort Study, and we show the limited generalizability of 1,376 robust SNP associations reported in the general population across 12 complex anthropometric and cardiometabolic phenotypes (n = 2,231; observed-to-expected replication ratio = 0.70, p = 6.2 × 10-8). An examination of five comparable phenotypes in a second independent cohort of survivors from the Childhood Cancer Survivor Study corroborated the overall limited generalizability of meta-GWAS hits to survivors (n = 4,212; observed-to-expected replication ratio = 0.55, p = 5.6 × 10-15). Finally, in direct comparisons of survivor samples against independent equivalently powered general population samples from the UK Biobank, we consistently observed lower meta-GWAS hit replication rates and poorer polygenic risk score predictive performance in survivor samples for multiple phenotypes. As a possible explanation, we found that meta-GWAS hits were less likely to be replicated in survivors who had been exposed to cancer therapies that are associated with phenotype risk. [https://www.selleckchem.com/products/jh-re-06.html selleck chemicals] Examination of complementary DNA methylation data in a subset of survivors revealed that treatment-related methylation patterns at genomic sites linked to meta-GWAS hits may disrupt established genetic signals in survivors.Analyzing genomic data across populations is central to understanding the role of genetic factors in health and disease. Successful data sharing relies on public support, which requires attention to whether people around the world are willing to donate their data that are then subsequently shared with others for research. However, studies of such public perceptions are geographically limited and do not enable comparison. This paper presents results from a very large public survey on attitudes toward genomic data sharing. Data from 36,268 individuals across 22 countries (gathered in 15 languages) are presented. In general, publics across the world do not appear to be aware of, nor familiar with, the concepts of DNA, genetics, and genomics. Willingness to donate one's DNA and health data for research is relatively low, and trust in the process of data's being shared with multiple users (e.g., doctors, researchers, governments) is also low. Participants were most willing to donate DNA or health information for ronation, and subsequent sharing, is integral to this.Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs.