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Many regulatory networks appear to involve partially redundant enhancers. Traditionally, such enhancers have been hypothesized to originate mainly by sequence duplication. An alternative model postulates that they arise independently, through convergent evolution. This mechanism appears to be counterintuitive to natural selection: Redundant sequences are expected to either diverge and acquire new functions or accumulate mutations and become nonfunctional. Nevertheless, we show that at least 31% of the redundant enhancer pairs in the human genome (and 17% in the mouse genome) indeed originated in this manner. Specifically, for virtually all transposon-derived redundant enhancer pairs, both enhancer partners have evolved independently, from the exaptation of two different transposons. In addition to conferring robustness to the system, redundant enhancers could provide an evolutionary advantage by fine-tuning gene expression. Consistent with this hypothesis, we observed that the target genes of redundant enhancers exhibit higher expression levels and tissue specificity as compared with other genes. Finally, we found that although enhancer redundancy appears to be an intrinsic property of certain mammalian regulatory networks, the corresponding enhancers are largely species-specific. In other words, the redundancy in these networks is most likely a result of convergent evolution.

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The human genome is organized into topologically associating domains (TADs), which represent contiguous regions with a higher frequency of intra-interactions as opposed to inter-interactions. TADs contribute to gene expression regulation by restricting the interactions between their regulatory elements, and TAD disruption has been associated with cancer. Here, we provide a proof of principle that mutations within TADs can be used to predict the survival of cancer patients. Specifically, we constructed a set of 1467 consensus TADs representing the three-dimensional organization of the human genome and used Cox regression analysis to identify a total of 35 prognostic TADs in different cancer types. Interestingly, only 46% of the 35 prognostic TADs comprised genes with known clinical relevance. Moreover, in the vast majority of such cases, the prognostic value of the TAD was not directly related to the presence/absence of mutations in the gene(s), emphasizing the importance of regulatory mutations. In addition, we found that 34% of the prognostic TADs show strong structural perturbations in the cancer genome, consistent with the widespread, global epigenetic dysregulation often observed in cancer patients. In summary, this study elucidates the mechanisms through which non-coding variants may influence cancer progression and opens new avenues for personalized medicine.

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Comparative genomic studies have identified thousands of conserved noncoding elements (CNEs) in the mammalian genome, many of which have been reported to exert cis-regulatory activity. We analyzed ∼5,500 pairs of adjacent CNEs in the human genome and found that despite divergence at the nucleotide sequence level, the inter-CNE distances of the pairs are under strong evolutionary constraint, with inter-CNE sequences featuring significantly lower transposon densities than expected. Further, we show that different degrees of conservation of the inter-CNE distance are associated with distinct cis-regulatory functions at the CNEs. Specifically, the CNEs in pairs with conserved and mildly contracted inter-CNE sequences are the most likely to represent active or poised enhancers. In contrast, CNEs in pairs with extremely contracted or expanded inter-CNE sequences are associated with no cis-regulatory activity. Furthermore, we observed that functional CNEs in a pair have very similar epigenetic profiles, hinting at a functional relationship between them. Taken together, our results support the existence of epistatic interactions between adjacent CNEs that are distance-sensitive and disrupted by transposon insertions and deletions, and contribute to our understanding of the selective forces acting on cis-regulatory elements, which are crucial for elucidating the molecular mechanisms underlying adaptive evolution and human genetic diseases.

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Neutron scattering is a powerful tool to study relaxation processes in biological membrane mimics in space and time. Combining different inelastic and quasielastic neutron scattering techniques, a large dynamic range can be covered: from atomic to mesoscopic lengths and from femto- to some hundreds of nanoseconds in time. This allows studies on e.g. the diffusion of lipids, the membrane undulation motions, the dispersion of sound waves in membranes as well as the mutual interactions of membrane constituents such as lipids, proteins, and additives. In particular, neutron scattering provides a quite direct experimental approach to the inter-atomic and inter-molecular potentials on length and time scales which are perfectly accessible by molecular dynamics (MD) simulations. Neutron scattering experiments may thus substantially support the further refinement of biomolecular force fields for MD simulations by supplying structural and dynamical information with high spatial and temporal resolution. In turn, MD simulations support the interpretation of neutron scattering data. The combination of both, neutron scattering experiments and MD simulations, yields an unprecedented insight into the molecular interactions governing the structure and dynamics of biological membranes. This review provides an overview of the molecular dynamics in biological membrane mimics as revealed by neutron scattering. It focuses on the latest findings such as the fundamental molecular mechanism of lateral lipid diffusion as well as the influence of additives and proteins on the short-time dynamics of lipids. Special emphasis is placed on the comparison of recent neutron scattering and MD simulation data with respect to molecular membrane dynamics on the pico- to nanosecond time scale.

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