Daniela Gerovska

Automatic interpretation of magnetic data based on Euler deconvolution with unprescribed structural index

A tool for fully automatic magnetic data interpretation, solving Eulers homogeneity equation with unprescribed structural index and for a linear background in each moving window, is presented here. The implemented Euler deconvolution algorithm is based on the properties of the differential similarity transformation, which decouples the coordinates and the structural index of the singular point and the parameters of the linear background field. Since the deconvolution algorithm resolves the singular point locations well, this allows the application of a two stage clustering technique, focusing the estimated singular point coordinates and structural indices, followed by a statistical analysis of the final solutions. The automatic technique was tested on simple and complex 3D model magnetic anomalies. Finally, the technique was applied to real magnetic anomaly data from the Burgas region and the adjoining Black Sea shelf of Bulgaria. The tool consists of two main functions, written in Matlab v.5.3, requiring Matlabs SPLINE and STATISTICS toolkits.

Calculation of magnitude magnetic transforms with high centricity and low dependence on the magnetization vector direction

We present a Matlab tool that calculates five magnitude magnetic transforms (MMTs) from an input measured anomalous magnetic field. The MMTs are all based on the total magnitude anomaly (TMA), and consist of the TMA itself, the modulus of the gradient of the TMA, the Laplacian of the TMA, half of the square root of the Laplacian of the square of the TMA, and the square root of the product of the TMA plus the Laplacian of the TMA. These MMTs produce anomalies that are closer to the magnetic source’s true horizontal position and are simpler to interpret than the measured anomalous magnetic field itself. While the conventional magnetic transforms of reduction-to-the-pole (RTP), the pseudogravity field, and the analytic signal (AS) also have these properties, these MMTs have several additional advantages. They require only first-order, horizontal derivatives for their calculation. They are also more stable at low magnetic latitudes than the RTP, and have a pattern that is independent of the geomagnetic-field ...

P3BSseq: Parallel processing pipeline software for automatic analysis of bisulfite sequencing data

Motivation: Bisulfite sequencing (BSseq) processing is among the most cumbersome next generation sequencing (NGS) applications. Though some BSseq processing tools are available, they are scattered, require puzzling parameters and are running‐time and memory‐usage demanding. Results: We developed P3BSseq, a parallel processing pipeline for fast, accurate and automatic analysis of BSseq reads that trims, aligns, annotates, records the intermediate results, performs bisulfite conversion quality assessment, generates BED methylome and report files following the NIH standards. P3BSseq outperforms the known BSseq mappers regarding running time, computer hardware requirements (processing power and memory use) and is optimized to process the upcoming, extended BSseq reads. We optimized the P3BSseq parameters for directional and non‐directional libraries, and for single‐end and paired‐end reads of Whole Genome and Reduced Representation BSseq. P3BSseq is a user‐friendly streamlined solution for BSseq upstream analysis, requiring only basic computer and NGS knowledge. Availability and Implementation: P3BSseq binaries and documentation are available at: http://sourceforge.net/p/p3bsseq/wiki/Home/ Contact: mararabra@yahoo.co.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Automatic inversion of magnetic anomalies from two height levels using finite-difference similarity transforms

We solve the inverse magnetic problem for the depth and shape of simple sources in the presence of a regional field and truly random noise. We do not use noise-generating derivatives nor are we forced to solve complex systems of equations. Our inverse operator applies a new geometric type of field transform, the finite-difference similarity transform (FDST), that is based on a postulated degree of homogeneity in the potential field. Magnetic data from two height levels are required for the calculation of the FDSTs. The FDSTs are generated for an assumed central point of similarity (CPS) and a trial value (index) for the coefficient of similarity, and they are sensitive to the distance between the source and the CPS and to the agreement between the index and the degree of homogeneity in the data. When the CPS converges to a singular point in the potential field, say, the center or the topedge of the source, and when the trial index converges on the degree of homogeneity present in the data, the FDST drops ...

Does mouse embryo primordial germ cell activation start before implantation as suggested by single-cell transcriptomics dynamics?

STUDY HYPOTHESISnDoes primordial germ cell (PGC) activation start before mouse embryo implantation, and does the possible regulation of the DNA (cytosine-5-)-methyltransferase 3-like (Dnmt3l) by transcription factor AP-2, gamma (TCFAP2C) have a role in this activation and in the primitive endoderm (PE)-epiblast (EPI) lineage specification?nnnSTUDY FINDINGnA burst of expression of PGC markers, such as Dppa3/Stella, Ifitm2/Fragilis, Fkbp6 and Prdm4, is observed from embryonic day (E) 3.25, and some of them, together with the late germ cell markers Zp3, Mcf2 and Morc1, become restricted to the EPI subpopulation at E4.5, while the dynamics analysis of the PE-EPI transitions in the single-cell data suggests that TCFAP2C transitorily represses Dnmt3l in EPI cells at E3.5 and such repression is withdrawn with reactivation of Dnmt3l expression in PE and EPI cells at E4.5.nnnWHAT IS KNOWN ALREADYnIn the mouse preimplantation embryo, cells with the same phenotype take different fates based on the orchestration between topological clues (cell polarity, positional history and division orientation) and gene regulatory rules (at transcriptomics and epigenomics level), prompting the proposal of positional, stochastic and combined models explaining the specification mechanism. PGC specification starts at E6.0-6.5 post-implantation. In view of the important role of DNA methylation in developmental events, the cross-talk between some transcription factors and DNA methyltransferases is of particular relevance. TCFAP2C has a CpG DNA methylation motif that is not methylated in pluripotent cells and that could potentially bind on DNMT3L, the stimulatory DNA methyltransferase co-factor that assists in the process of de novo DNA methylation. Chromatin-immunoprecipitation analysis has demonstrated that Dnmt3l is indeed a target of TCFAP2C.nnnSTUDY DESIGN, SAMPLES/MATERIALS, METHODSnWe aimed to assess the timing of early preimplantation events and to understand better the segregation of the inner cell mass (ICM) into PE and EPI. We designed a single-cell transcriptomics dynamics computational study to identify markers of the PE-EPI bifurcation in ICM cells through searching for statistically significant (using the Students t-test method) differently expressed genes (DEGs) between PE and EPI cells from E3.5 to E4.5. The DEGs common for E3.5 and E4.5 were used as the markers defining the steady states. We collected microarray and next-generation sequencing transcriptomics data from public databases from bulk populations and single cells from mice at E3.25, E3.5 and E4.5. The results are based on three independent single-cell transcriptomics data sets, with a fold change of 3 and P-value <0.01 for the DEG selection.nnnMAIN RESULTS AND THE ROLE OF CHANCEnThe dynamics analysis revealed new transitory E3.5 and steady PE and EPI markers. Among the transitory E3.5 PE markers (Dnmt3l, Dusp4, Cpne8, Akap13, Dcaf12l1, Aaed1, B4galt6, BC100530, Rnpc3, Tfpi, Lgalsl, Ckap4 and Fbxl20), several (Dusp4, Akap13, Cpn8, Dcaf12l1 and Tfpi) are related to the extracellular regulated kinase pathway. We also identified new transitory E3.5 EPI markers (Sgk1, Mal, Ubxn2a, Atg16l2, Gm13102, Tcfap2c, Hexb, Slc1a1, Svip, Liph and Mier3), six new stable PE markers (Sdc4, Cpn1, Dkk1, Havcr1, F2r/Par1 and Slc7a6os) as well as three new stable EPI markers (Zp3, Mcf2 and Hexb), which are known to be late stage germ cell markers. We found that mouse PGC marker activation starts at least at E3.25 preimplantation. The transcriptomics dynamics analyses support the regulation of Dnmt3l expression by TCFAP2C.nnnLIMITATIONS, REASONS FOR CAUTIONnSince the regulation of Dnmt3l by TCFAP2C is based on computational prediction of DNA methylation motifs, Chip-Seq and transcriptomics data, functional studies are required to validate this result.nnnWIDER IMPLICATIONS OF THE FINDINGSnWe identified a collection of previously undescribed E3.5-specific PE and EPI markers, and new steady PE and EPI markers. Identification of these genes, many of which encode cell membrane proteins, will facilitate the isolation and characterization of early PE and EPI populations. Since it is so well established in the literature that mouse PGC specification is a post-implantation event, it was surprising for us to see activation of PGC markers as early as E3.25 preimplantation, and identify the newly found steady EPI markers as late germ cell markers. The discovery of such early activation of PGC markers has important implications in the derivation of germ cells from pluripotent cells (embryonic stem cells or induced pluripotent stem cells), since the initial stages of such derivation resemble early development. The early activation of PGC markers points out the difficulty of separating PGC cells from pluripotent populations. Collectively, our results suggest that the combining of the precision of single-cell omics data with dynamic analysis of time-series data can establish the timing of some developmental stages as earlier than previously thought.nnnLARGE-SCALE DATAnNot applicable.nnnSTUDY FUNDING AND COMPETING INTERESTSnThis work was supported by grants DFG15/14 and DFG15/020 from Diputación Foral de Gipuzkoa (Spain), and grant II14/00016 from I + D + I National Plan 2013-2016 (Spain) and FEDER funds. The authors declare no conflict of interest.

PR-LncRNA signature regulates glioma cell activity through expression of SOX factors

Long non-coding RNAs (LncRNAs) have emerged as a relevant class of genome regulators involved in a broad range of biological processes and with important roles in tumor initiation and malignant progression. We have previously identified a p53-regulated tumor suppressor signature of LncRNAs (PR-LncRNAs) in colorectal cancer. Our aim was to identify the expression and function of this signature in gliomas. We found that the expression of the four PR-LncRNAs tested was high in human low-grade glioma samples and diminished with increasing grade of disease, being the lowest in glioblastoma samples. Functional assays demonstrated that PR-LncRNA silencing increased glioma cell proliferation and oncosphere formation. Mechanistically, we found an inverse correlation between PR-LncRNA expression and SOX1, SOX2 and SOX9 stem cell factors in human glioma biopsies and in glioma cells in vitro. Moreover, knock-down of SOX activity abolished the effect of PR-LncRNA silencing in glioma cell activity. In conclusion, our results demonstrate that the expression and function of PR-LncRNAs are significantly altered in gliomagenesis and that their activity is mediated by SOX factors. These results may provide important insights into the mechanisms responsible for glioblastoma pathogenesis.

Rules governing the mechanism of epigenetic reprogramming memory

AIMnDisclosing the mechanisms that regulate reprogramming memory.nnnMATERIALS & METHODSnWe established computational procedure to find DNA methylation somatic memory sites (SMSs) at single CpGs and integrated them with genomics, epigenomics, transcriptomics and imprinting information.nnnRESULTS & CONCLUSIONnReprogramming memory persists at late passages in low methylated regions. Contrarily to hypomethylated, hypermethylated SMSs occur at evolutionary conserved sites overlapping active transcription loci in dynamic chromatin regions. The epigenetic-memory molecular origin is the expression of source-cell transcription factors protecting hypomethylated SMSs in euchromatin from de novoxa0methylation, keeping source-cell lineage-specific loci in induced pluripotent stem (iPS) cells incompletely silenced. Sites in lineage-specific genes of different-from-those-of-the-source-cell lineages remain hypermethylated in heterochromatin regions becoming permanently silenced. SMSs cause differential expression between iPS cells and embryonic stem cells through two mechanisms: epigenetic/expression memory rule, the DNA unreprogramming methylation status coupled with chromatin states induces differentially expressed genes. Imprinting control, the change of DNA methylation status in imprinting control regions induces differential expression of imprinted genes.

DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism

BackgroundDNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers.ResultsWe investigated the relationship between DNA methylation and active chromatin marks through genome-wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized “seesaw” dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state. We summarize these observations into a rule of thumb of one-out-of-three methylation marks: “In each genomic region only one out of these three methylation marks {DNA methylation, H3K4me1, H3K4me3} is high. If it is the DNA methylation, the region is inactive. If it is H3K4me1, the region is an enhancer, and if it is H3K4me3, the region is a promoter”. To test our model, we used available genome-wide datasets of H3K4 methyltransferases knockouts. Our analysis suggests that CXXC proteins, as readers of non-methylated CpGs would regulate the “seesaw” mechanism that focuses H3K4me3 to unmethylated sites, while being repulsed from H3K4me1 decorated enhancers and CpG island shores.ConclusionsOur results show that DNA methylation discriminates promoters from enhancers through H3K4me1-H3K4me3 seesaw mechanism, and suggest its possible function in the inheritance of chromatin marks after cell division. Our analyses suggest aberrant formation of promoter-like regions and ectopic transcription of hypomethylated regions of DNA. Such mechanism process can have important implications in biological process in where it has been reported abnormal DNA methylation status such as cancer and aging.

Euler Inversion of Magnetic Anomalies Using Analytical Continuation

Summary Some properties of the analytical expressions of potential fields as homogeneous functions allow the inverse problem for magnetic anomalies, caused by simple sources, to be solved in a direct way, without use of derivatives and a system of equations. The tool in the proposed here new inversion technique is the finite-difference similarity transform (FDST). FDSTs are generated from a set of central points of similarity (CPS). These transforms are sensitive to the distance between a chosen CPS and the source. The CPS and the degree of homogeneity that give minimal values of the respective FDST indicate the source position and shape. The technique requires calculation of an upward analytical continuation of the inverted field, or measured field at two height levels. The approach shows possibilities for obtaining stable solutions in an automated inverse procedure. 2D model and field examples illustrate the effectiveness of inversion using FDST. 2D gravity, as well as 3D magnetic and gravity inversions, are possible on the same theoretical base.