Deep-learning electronic-structure calculation of magnetic superstructures

Ab initio study of magnetic superstructures (e.g., magnetic skyrmion) is indispensable to the research of novel materials but bottlenecked by its formidable computational cost. For solving the bottleneck problem, we develop a deep equivariant neural network method (named xDeepH) to represent density functional theory Hamiltonian $H_\text{DFT}$ as a function of atomic and magnetic structures and apply neural networks for efficient electronic structure calculation. Intelligence of neural networks is optimized by incorporating a priori knowledge about the important locality and symmetry properties into the method. Particularly, we design a neural-network architecture fully preserving all equivalent requirements on $H_\text{DFT}$ by the Euclidean and time-reversal symmetries ($E(3) \times \{I, T\}$), which is essential to improve method performance. High accuracy (sub-meV error) and good transferability of xDeepH are shown by systematic experiments on nanotube, spin-spiral, and Moir\'{e} magnets, and the capability of studying magnetic skyrmion is also demonstrated. The method could find promising applications in magnetic materials research and inspire development of deep-learning ab initio methods

Efficient hybrid density functional calculation by deep learning

Hybrid density functional calculation is indispensable to accurate description of electronic structure, whereas the formidable computational cost restricts its broad application. Here we develop a deep equivariant neural network method (named DeepH-hybrid) to learn the hybrid-functional Hamiltonian from self-consistent field calculations of small structures, and apply the trained neural networks for efficient electronic-structure calculation by passing the self-consistent iterations. The method is systematically checked to show high efficiency and accuracy, making the study of large-scale materials with hybrid-functional accuracy feasible. As an important application, the DeepH-hybrid method is applied to study large-supercell Moir\'{e} twisted materials, offering the first case study on how the inclusion of exact exchange affects flat bands in the magic-angle twisted bilayer graphene

Mitogenomes Provide Insights into the Species Boundaries and Phylogenetic Relationships among Three <i>Dolycoris</i> Sloe Bugs (Hemiptera: Pentatomidae) from China

(1) Background: The three sloe bugs, Dolycoris baccarum, Dolycoris indicus, and Dolycoris penicillatus, are found in the Chinese mainland and are morphologically similar. The species boundaries and phylogenetic relationships of the three species remain uncertain; (2) Methods: In this study, we generated multiple mitochondrial genomes (mitogenomes) for each of the three species and conducted comparative mitogenomic analysis, species delimitation, and phylogenetic analysis based on these data; (3) Results: Mitogenomes of the three Dolycoris species are conserved in nucleotide composition, gene arrangement, and codon usage. All protein-coding genes (PCGs) were found to be under purifying selection, and the ND4 evolved at the fastest rate. Most species delimitation analyses based on the COI gene and the concatenated 13 PCGs retrieved three operational taxonomic units (OTUs), which corresponded well with the three Dolycoris species identified based on morphological characters. A clear-cut barcode gap was discovered between the interspecific and intraspecific genetic distances of the three Dolycoris species. Phylogenetic analyses strongly supported the monophyly of Dolycoris, with interspecific relationship inferred as (D. indicus + (D. baccarum + D. penicillatus)); (4) Conclusions: Our study provides the first insight into the species boundaries and phylogenetic relationships of the three Dolycoris species distributed across the Chinese mainland

Rescuing ocular development in an anophthalmic pig by blastocyst complementation

Abstract Porcine‐derived xenogeneic sources for transplantation are a promising alternative strategy for providing organs for treatment of end‐stage organ failure in human patients because of the shortage of human donor organs. The recently developed blastocyst or pluripotent stem cell (PSC) complementation strategy opens a new route for regenerating allogenic organs in miniature pigs. Since the eye is a complicated organ with highly specialized constituent tissues derived from different primordial cell lineages, the development of an intact eye from allogenic cells is a challenging task. Here, combining somatic cell nuclear transfer technology (SCNT) and an anophthalmic pig model (MITFL247S/L247S), allogenic retinal pigmented epithelium cells (RPEs) were retrieved from an E60 chimeric fetus using blastocyst complementation. Furthermore, all structures were successfully regenerated in the intact eye from the injected donor blastomeres. These results clearly demonstrate that not only differentiated functional somatic cells but also a disabled organ with highly specialized constituent tissues can be generated from exogenous blastomeres when delivered to pig embryos with an empty organ niche. This system may also provide novel insights into ocular organogenesis

Ago2 facilitates Rad51 recruitment and DNA double-strand break repair by homologous recombination

DNA double-strand breaks (DSBs) are highly cytotoxic lesions and pose a major threat to genome stability if not properly repaired. We and others have previously shown that a class of DSB-induced small RNAs (diRNAs) is produced from sequences around DSB sites. DiRNAs are associated with Argonaute (Ago) proteins and play an important role in DSB repair, though the mechanism through which they act remains unclear. Here, we report that the role of diRNAs in DSB repair is restricted to repair by homologous recombination (HR) and that it specifically relies on the effector protein Ago2 in mammalian cells. Interestingly, we show that Ago2 forms a complex with Rad51 and that the interaction is enhanced in cells treated with ionizing radiation. We demonstrate that Rad51 accumulation at DSB sites and HR repair depend on catalytic activity and small RNA-binding capability of Ago2. In contrast, DSB resection as well as RPA and Mre11 loading is unaffected by Ago2 or Dicer depletion, suggesting that Ago2 very likely functions directly in mediating Rad51 accumulation at DSBs. Taken together, our findings suggest that guided by diRNAs, Ago2 can promote Rad51 recruitment and/or retention at DSBs to facilitate repair by HR

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines

We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens. This study also demonstrates the value of releasing pre-publication data publicly to engage the community in an open research collaboration. Gönen et al. report the results of an open-participation DREAM challenge to critically assess the ability to predict gene essentiality on a novel functional screening dataset of 149 cancer cell lines. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens