Customized TALENs and Cas9/gRNAs have been used for targeted mutagenesis in zebrafish to induce indels into protein-coding genes. However, indels are usually not sufficient to disrupt the function of non-coding genes, gene clusters or regulatory sequences, whereas large genomic deletions or inversions are more desirable for this purpose. By injecting two pairs of TALEN mRNAs or two gRNAs together with Cas9 mRNA targeting distal DNA sites of the same chromosome, we obtained predictable genomic deletions or inversions with sizes ranging from several hundred bases to nearly 1 Mb. We have successfully achieved this type of modifications for 11 chromosomal loci by TALENs and 2 by Cas9/gRNAs with different combinations of gRNA pairs, including clusters of miRNA and protein-coding genes. Seven of eight TALEN-targeted lines transmitted the deletions and one transmitted the inversion through germ line. Our findings indicate that both TALENs and Cas9/gRNAs can be used as an efficient tool to engineer genomes to achieve large deletions or inversions, including fragments covering multiple genes and non-coding sequences. To facilitate the analyses and application of existing ZFN, TALEN and CRISPR/Cas data, we have updated our EENdb database to provide a chromosomal view of all reported engineered endonucleases targeting human and zebrafish genomes.

Recent technology has made it possible to simultaneously perform multi-platform genomic profiling (e.g. DNA methylation (DM) and gene expression (GE)) of biological samples, resulting in so-called ‘multi-dimensional genomic data’. Such data provide unique opportunities to study the coordination between regulatory mechanisms on multiple levels. However, integrative analysis of multi-dimensional genomics data for the discovery of combinatorial patterns is currently lacking. Here, we adopt a joint matrix factorization technique to address this challenge. This method projects multiple types of genomic data onto a common coordinate system, in which heterogeneous variables weighted highly in the same projected direction form a multi-dimensional module (md-module). Genomic variables in such modules are characterized by significant correlations and likely functional associations. We applied this method to the DM, GE, and microRNA expression data of 385 ovarian cancer samples from the The Cancer Genome Atlas project. These md-modules revealed perturbed pathways that would have been overlooked with only a single type of data, uncovered associations between different layers of cellular activities and allowed the identification of clinically distinct patient subgroups. Our study provides an useful protocol for uncovering hidden patterns and their biological implications in multi-dimensional ‘omic’ data.

Magnetic skyrmions, which are topologically protected spin textures, are promising candidates for ultralow-energy and ultrahigh-density magnetic data storage and computing applications. To date, most experiments on skyrmions have been carried out at low temperatures. The choice of available materials is limited, and there is a lack of electrical means to control skyrmions in devices. In this work, we demonstrate a new method for creating a stable skyrmion bubble phase in the CoFeB-MgO material system at room temperature, by engineering the interfacial perpendicular magnetic anisotropy of the ferromagnetic layer. Importantly, we also demonstrate that artificially engineered symmetry breaking gives rise to a force acting on the skyrmions, in addition to the current-induced spin-orbit torque, which can be used to drive their motion. This room-temperature creation and manipulation of skyrmions offers new possibilities to engineer skyrmionic devices. The results bring skyrmionic memory and logic concepts closer to realization in industrially relevant and manufacturable thin film material systems.

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization. (14), and single-cell (15) and in situ Hi-C (16)], close chromatin contacts can now be identified at increasing resolution, providing new insight into genome organization. These methods measure the relative frequencies of chromosome interactions averaged over a large population of cells. However, individual 3D genome structures can vary dramatically from cell to cell even within an isogenic sample, especially with respect to long-range interactions (15,17,18). This structural variability poses a great challenge to the interpretation of ensemble-averaged Hi-C data (14,(19)(20)(21)(22)(23) and prevents the direct detection of cooperative interactions co-occurring in the same cell. This problem is particularly evident for long-range (cis) and interchromosomal (trans) interactions, which are generally observed at relatively low frequencies and are therefore present only in a small subset of individual cells at any given time (3,11,15). Despite their low frequencies, long-range and interchromosome interaction patterns are not random noise. In fact, these interactions are more informative than short-range interactions in determining the global genome architectures in cells and are often functionally relevant-interactions between transcriptionally active regions are often interchromosomal in nature (14). Owing to their variable nature, long-range and trans interactions can be part of alternative, structurally different conformations, which makes their interpretation in form of consensus structures impossible. However, inferring which of the long-range interactions co-occur in the same cell from ensemble Hi-C data remains a major challenge.These challenges cannot be easily overcome even by the new single-cell Hi-C techno...

We propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. CancerLocator outperforms two established multi-class classification methods on simulations and real data, even with the low proportion of tumor-derived DNA in the cell-free DNA scenarios. CancerLocator also achieves promising results on patient plasma samples with low DNA methylation sequencing coverage.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1191-5) contains supplementary material, which is available to authorized users.

Myocardial ischemic disease affects the prognosis in perioperative patients. Diabetes can aggravate myocardial injury. The purpose of this research is to investigate the effect of ferroptosis in the process of diabetes mellitus (DM) myocardial ischemia/reperfusion (I/R) injury (IRI). Endoplasmic reticulum stress (ERS) is investigated whether aggravates cardiomyocytes injury. Rat DM+I/R (DIR), cell high glucose (HG), hypoxia reoxygenation (H/R), and high-glucose H/R (HH/R) models were established. Ferroptosis inhibitor Ferrostatin-1, ferroptosis agonist Erastin, ERS inhibitor Salubrinal, and ERS agonist Tunicamycin were administered. Serum creatine kinase-MB (CK-MB), cell viability, lactate dehydrogenase (LDH), malondialdehyde (MDA), superoxide dismutase (SOD), reactive oxygen species (ROS), and cellular ferrous ion concentration were examined. The level of ACSL4, GPX4, ATF4, CHOP, BCL-2, and BAX was detected. Myocardial tissue pathological change was detected by hematoxylin-eosin staining. Cardiac function was monitored by invasive hemodynamic measurements. Evans Blue-triphenyltetrazolium chloride double staining was used to detect the myocardial infarct size. In DM+sham (DS) (or HG) and I/R (or H/R) models, cardiomyocytes were injured accompanied by increased level of ferroptosis and ERS. Moreover, the cell injury was more serious in rat DIR or cell HH/R models. Inhibition of ferroptosis in DIR model could reduce ERS and myocardial injury. Inhibition of ferroptosis in H9c2 cells HG, H/R, and HH/R models could reduce cell injury. Erastin could aggravate ERS and cell injury by stimulating ferroptosis in HH/R cell model. Meanwhile, inhibition of ERS could alleviate ferroptosis and cell injury. Ferroptosis is involved in DIR injury that is related to ERS. Moreover, inhibition of ferroptosis can alleviate DIR injury, which may provide a therapeutic regent for myocardial ischemic disease.

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Background and Purpose Long-term exposure to ambient air pollution is associated with cerebrovascular disease and cognitive impairment, but whether it is related to structural changes in the brain is not clear. We examined the associations between residential long-term exposure to ambient air pollution and markers of brain aging using magnetic resonance imaging (MRI). Methods Framingham Offspring Study participants who attended the seventh examination, were at least 60 years old and free of dementia and stroke were included. We evaluated associations between exposures (fine particulate matter (PM2.5) and residential proximity to major roadways) and measures of total cerebral brain volume, hippocampal volume, white matter hyperintensity volume (log-transformed and extensive white matter hyperintensity volume for age) and covert brain infarcts. Models were adjusted for age, clinical covariates, indicators of socioeconomic position, and temporal trends. Results A 2 μg/m3 increase in PM2.5 was associated with -0.32% (95%CI: -0.59, -0.05) smaller total cerebral brain volume and 1.46 (95%CI: 1.10, 1.94) higher odds of covert brain infarcts. Living further away from a major roadway was associated with 0.10 (95%CI: 0.01, 0.19) greater log-transformed white matter hyperintensity volume for an interquartile range difference in distance, but no clear pattern of association was observed for extensive white matter. Conclusions Exposure to elevated levels of PM2.5 was associated with smaller total cerebral brain volume, a marker of age-associated brain atrophy, and with higher odds of covert brain infarcts. These findings suggest that air pollution is associated with insidious effects on structural brain aging even in dementia-and stroke-free persons.