综合性期刊最新文献

DNA storage has shown potential to transcend current silicon-based data storage technologies in storage density, longevity and energy consumption^1,2,3. However, writing large-scale data directly into DNA sequences by de novo synthesis remains uneconomical in time and cost⁴. We present an alternative, parallel strategy that enables the writing of arbitrary data on DNA using premade nucleic acids. Through self-assembly guided enzymatic methylation, epigenetic modifications, as information bits, can be introduced precisely onto universal DNA templates to enact molecular movable-type printing. By programming with a finite set of 700 DNA movable types and five templates, we achieved the synthesis-free writing of approximately 275,000 bits on an automated platform with 350 bits written per reaction. The data encoded in complex epigenetic patterns were retrieved high-throughput by nanopore sequencing, and algorithms were developed to finely resolve 240 modification patterns per sequencing reaction. With the epigenetic information bits framework, distributed and bespoke DNA storage was implemented by 60 volunteers lacking professional biolab experience. Our framework presents a new modality of DNA data storage that is parallel, programmable, stable and scalable. Such an unconventional modality opens up avenues towards practical data storage and dual-mode data functions in biomolecular systems.

Age-related cataracts is a highly prevalent eye disorder that results in the clouding of the crystalline lens and is one of the leading causes of visual impairment and blindness. The disease is influenced by multiple factors including genetics, prolonged exposure to ultraviolet radiation, and a history of diabetes. However, the extent to which each of these factors contributes to the development of cataracts remains unclear. Our study identified 101 independent genome-wide significant loci, 57 of which are novel. We identified multiple genes and biological pathways associated with the cataracts, including four drug-gene interactions. Our results suggest a causal association between type 1 diabetes and cataracts. Also, we highlighted a surrogate measure of UV light exposure as a marker of cataract risk in adults.

We present SpliceTransformer (SpTransformer), a deep-learning framework that predicts tissue-specific RNA splicing alterations linked to human diseases based on genomic sequence. SpTransformer outperforms all previous methods on splicing prediction. Application to approximately 1.3 million genetic variants in the ClinVar database reveals that splicing alterations account for 60% of intronic and synonymous pathogenic mutations, and occur at different frequencies across tissue types. Importantly, tissue-specific splicing alterations match their clinical manifestations independent of gene expression variation. We validate the enrichment in three brain disease datasets involving over 164,000 individuals. Additionally, we identify single nucleotide variations that cause brain-specific splicing alterations, and find disease-associated genes harboring these single nucleotide variations with distinct expression patterns involved in diverse biological processes. Finally, SpTransformer analysis of whole exon sequencing data from blood samples of patients with diabetic nephropathy predicts kidney-specific RNA splicing alterations with 83% accuracy, demonstrating the potential to infer disease-causing tissue-specific splicing events. SpTransformer provides a powerful tool to guide biological and clinical interpretations of human diseases.

Engineering the electronic band structures upon doping is crucial to improve the thermoelectric performance of materials. Understanding how dopants influence the electronic states near the Fermi level is thus a prerequisite to precisely tune band structures. Here, we demonstrate that the Sn-s states in SnTe contribute to the density of states at the top of the valence band. This is a consequence of the half-filled p-p σ-bond (metavalent bonding) and its resulting symmetry of the orbital phases at the valence band maximum (L point of the Brillouin zone). This insight provides a recipe for identifying superior dopants. The overlap between the dopant s- and the Te p-state is maximized, if the spatial overlap of both orbitals is maximized and their energetic difference is minimized. This simple design rule has enabled us to screen out Al as a very efficient dopant to enhance the local density of states for SnTe. In conjunction with doping Sb to tune the carrier concentration and alloying with AgBiTe₂ to promote band convergence, as well as introducing dislocations to impede phonon propagation, a record-high average ZT of 1.15 between 300 and 873 K and a large ZT of 0.36 at 300 K is achieved in Sn_0.8Al_0.08Sb_0.15Te-4%AgBiTe₂.

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing and stimulus responses, which collectively define the thousands of unique cell types in the body^1,2,3. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for these intended purposes has arisen naturally. Here we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell-type specificity. We take advantage of innovations in deep neural network modelling of CRE activity across three cell types, efficient in silico optimization and massively parallel reporter assays to design and empirically test thousands of CREs^4,5,6,7,8. Through large-scale in vitro validation, we show that synthetic sequences are more effective at driving cell-type-specific expression in three cell lines compared with natural sequences from the human genome and achieve specificity in analogous tissues when tested in vivo. Synthetic sequences exhibit distinct motif vocabulary associated with activity in the on-target cell type and a simultaneous reduction in the activity of off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs from massively parallel reporter assay models and demonstrate the required literacy to write fit-for-purpose regulatory code.

Evidence suggests that, when compact objects such as black holes and neutron stars form, they may receive a ‘natal kick’, during which the stellar remnant gains momentum. Observational evidence for neutron star kicks is substantial^1,2, yet is limited for black hole natal kicks, and some proposed black hole formation scenarios result in very small kicks^3,4,5. Here we report that the canonical black hole low-mass X-ray binary (LMXB) V404 Cygni is part of a wide hierarchical triple with a tertiary companion at least 3,500 astronomical units (au) away from the inner binary. Given the orbital configuration, the black hole probably received a sub-5 km s⁻¹ kick to have avoided unbinding the tertiary. This discovery lends support to the idea that at least some black holes form with nearly no natal kick. Furthermore, the tertiary in this system lends credence to evolutionary models of LMXBs involving a hierarchical triple structure⁶. Remarkably, the tertiary is evolved, indicating that the system formed 3–5 billion years ago and that the black hole has removed at least half a solar mass of matter from its evolved secondary companion. During the event in which the black hole formed, it is required that at least half of the mass of the black hole progenitor collapsed into the black hole; it may even have undergone a complete implosion, enabling the tertiary to remain loosely bound.

Harvesting energy from nonlinear systems has been at the centre of research in the energy harvesting community. Many such proposed systems are single nonlinear harvester. While these systems show an increase in bandwidth of harvesting frequency, overall, they are not effective enough in power generation. This article studies power harvesting and frequency bandwidth characteristics of an array of harvesters. Multiple harvesters are considered with linear and nonlinear coupling between the harvesters. The phenomena of internal resonance (IR) and stochastic resonance (SR) are reported. The IR in multiple coupled nonlinear harvesters is explored using multiple-scale analysis. A parametric study is conducted to demonstrate the effect of coupling strength, frequency mistuning, innate nonlinearity and other parameters. The parametric study helped establish effective ways to increase bandwidth. Moreover, a stochastically loaded linearly coupled bistable harvester array is numerically analysed to find the effect of coupling strength and array size on the phenomenon of SR and on the system's harvesting performance. Through these studies, the potential of multiple coupled nonlinear harvesters in enhanced energy harvesting is demonstrated under both harmonic and stochastic excitation.This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

Anderson localization and non-Hermitian skin effect are two paradigmatic wave localization phenomena, resulting from wave interference and the intrinsic non-Hermitian point gap, respectively. In this study, we unveil a novel localization phenomenon associated with long-range asymmetric coupling, termed scale-tailored localization, where the number of induced localized modes and their localization lengths scale exclusively with the coupling range. We show that the long-range coupling fundamentally reshapes the energy spectra and eigenstates by creating multiple connected paths on the lattice. Furthermore, we present experimental observations of scale-tailored localization in non-Hermitian electrical circuits utilizing adjustable voltage followers and switches. The circuit admittance spectra possess separate point-shaped and loop-shaped components in the complex energy plane, corresponding respectively to skin modes and scale-tailored localized states. Our findings not only expand and deepen the understanding of peculiar effects induced by non-Hermiticity but also offer a feasible experimental platform for exploring and controlling wave localizations.