Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part I-Algorithm and Morphology

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (Ne). In this study, we developed an optimal estimation (OE) method to retrieve Ne profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε \u3c 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the Ne inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large Ne oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric Ne morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the Ne variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links

Allele-specific demethylation at an imprinted mammalian promoter

A screen for imprinted genes on mouse Chromosome 7 recently identified Inpp5f_v2, a paternally expressed retrogene lying within an intron of Inpp5f. Here, we identify a novel paternally expressed variant of the Inpp5f gene (Inpp5f_v3) that shows a number of unusual features. Inpp5f_v3 initiates from a CpG-rich repeat region adjoining two B1 elements, despite previous reports that SINEs are generally excluded from imprinted promoters. Accordingly, we find that the Inpp5f_v3 promoter acquires methylation around the time of implantation, when many repeat families undergo de novo epigenetic silencing. Methylation is then lost specifically on the paternally derived allele during the latter stages of embryonic development, resulting in imprinted transcriptional activation on the demethylated allele. Methylation analyses in embryos lacking maternal methylation imprints suggest that the primary imprinting mark resides within an intronic CpG island ∼1 kb downstream of the Inpp5f_v3 transcriptional start site. These data support the hypothesis that SINEs can influence gene expression by attracting de novo methylation during development, a property likely to explain their exclusion from other imprinted promoters

Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science

Highly individual methylation patterns of alternative glucocorticoid receptor promoters suggest individualized epigenetic regulatory mechanisms

The transcription start sites (TSS) and promoters of many genes are located in upstream CpG islands. Methylation within such islands is known for both imprinted and oncogenes, although poorly studied for other genes, especially those with complex CpG islands containing multiple first exons and promoters. The glucocorticoid receptor (GR) CpG island contains seven alternative first exons and their promoters. Here we show for the five GR promoters activated in PBMCs that methylation patterns are highly variable between individuals. The majority of positions were methylated at levels >25% in at least one donor affecting each promoter and TSS. We also examined the evolutionarily conserved transcription factor binding sites (TFBS) using an improved in silico phylogenetic footprinting technique. The majority of these contain methylatable CpG sites, suggesting that methylation may orchestrates alternative first exon usage, silencing and controlling tissue-specific expression. The heterogeneity observed may reflect epigenetic mechanisms of GR fine tuning, programmed by early life environment and events. With 78% of evolutionarily conserved alternative first exons falling into such complex CpG islands, their internal structure and epigenetic modifications are bound to be biologically important, and may be a common transcriptional control mechanism used throughout many phyla

Comparative analysis of sequence characteristics of imprinted genes in human, mouse, and cattle

Genomic imprinting is an epigenetic mechanism that results in monoallelic expression of genes depending on parent-of-origin of the allele. Although the conservation of genomic imprinting among mammalian species has been widely reported for many genes, there is accumulating evidence that some genes escape this conservation. Most known imprinted genes have been identified in the mouse and human, with few imprinted genes reported in cattle. Comparative analysis of genomic imprinting across mammalian species would provide a powerful tool for elucidating the mechanisms regulating the unique expression of imprinted genes. In this study we analyzed the imprinting of 22 genes in human, mouse, and cattle and found that in only 11 was imprinting conserved across the three species. In addition, we analyzed the occurrence of the sequence elements CpG islands, C + G content, tandem repeats, and retrotransposable elements in imprinted and in nonimprinted (control) cattle genes. We found that imprinted genes have a higher G + C content and more CpG islands and tandem repeats. Short interspersed nuclear elements (SINEs) were notably fewer in number in imprinted cattle genes compared to control genes, which is in agreement with previous reports for human and mouse imprinted regions. Long interspersed nuclear elements (LINEs) and long terminal repeats (LTRs) were found to be significantly underrepresented in imprinted genes compared to control genes, contrary to reports on human and mouse. Of considerable significance was the finding of highly conserved tandem repeats in nine of the genes imprinted in all three species

CG dinucleotide clustering is a species-specific property of the genome

Cytosines at cytosine-guanine (CG) dinucleotides are the near-exclusive target of DNA methyltransferases in mammalian genomes. Spontaneous deamination of methylcytosine to thymine makes methylated cytosines unusually susceptible to mutation and consequent depletion. The loci where CG dinucleotides remain relatively enriched, presumably due to their unmethylated status during the germ cell cycle, have been referred to as CpG islands. Currently, CpG islands are solely defined by base compositional criteria, allowing annotation of any sequenced genome. Using a novel bioinformatic approach, we show that CG clusters can be identified as an inherent property of genomic sequence without imposing a base compositional a priori assumption. We also show that the CG clusters co-localize in the human genome with hypomethylated loci and annotated transcription start sites to a greater extent than annotations produced by prior CpG island definitions. Moreover, this new approach allows CG clusters to be identified in a species-specific manner, revealing a degree of orthologous conservation that is not revealed by current base compositional approaches. Finally, our approach is able to identify methylating genomes (such as Takifugu rubripes) that lack CG clustering entirely, in which it is inappropriate to annotate CpG islands or CG clusters

DLEC1 is a functional 3p22.3 tumour suppressor silenced by promoter CpG methylation in colon and gastric cancers

Promoter CpG methylation of tumour suppressor genes (TSGs) is an epigenetic biomarker for TSG identification and molecular diagnosis. We screened genome wide for novel methylated genes through methylation subtraction of a genetic demethylation model of colon cancer (double knockout of DNMT1 and DNMT3B in HCT116) and identified DLEC1 (Deleted in lung and oesophageal cancer 1), a major 3p22.3 TSG, as one of the methylated targets. We further found that DLEC1 was downregulated or silenced in most colorectal and gastric cell lines due to promoter methylation, whereas broadly expressed in normal tissues including colon and stomach, and unmethylated in expressing cell lines and immortalised normal colon epithelial cells. DLEC1 expression was reactivated through pharmacologic or genetic demethylation, indicating a DNMT1/DNMT3B-mediated methylation silencing. Aberrant methylation was further detected in primary colorectal (10 out of 34, 29%) and gastric tumours (30 out of 89, 34%), but seldom in paired normal colon (0 out of 17) and gastric (1 out of 20, 5%) samples. No correlation between DLEC1 methylation and clinical parameters of gastric cancers was found. Ectopic expression of DLEC1 in silenced HCT116 and MKN45 cells strongly inhibited their clonogenicity. Thus, DLEC1 is a functional tumour suppressor, being frequently silenced by epigenetic mechanism in gastrointestinal tumours

Particle Swarm Optimization with Reinforcement Learning for the Prediction of CpG Islands in the Human Genome

BACKGROUND: Regions with abundant GC nucleotides, a high CpG number, and a length greater than 200 bp in a genome are often referred to as CpG islands. These islands are usually located in the 5' end of genes. Recently, several algorithms for the prediction of CpG islands have been proposed. METHODOLOGY/PRINCIPAL FINDINGS: We propose here a new method called CPSORL to predict CpG islands, which consists of a complement particle swarm optimization algorithm combined with reinforcement learning to predict CpG islands more reliably. Several CpG island prediction tools equipped with the sliding window technique have been developed previously. However, the quality of the results seems to rely too much on the choices that are made for the window sizes, and thus these methods leave room for improvement. CONCLUSIONS/SIGNIFICANCE: Experimental results indicate that CPSORL provides results of a higher sensitivity and a higher correlation coefficient in all selected experimental contigs than the other methods it was compared to (CpGIS, CpGcluster, CpGProd and CpGPlot). A higher number of CpG islands were identified in chromosomes 21 and 22 of the human genome than with the other methods from the literature. CPSORL also achieved the highest coverage rate (3.4%). CPSORL is an application for identifying promoter and TSS regions associated with CpG islands in entire human genomic. When compared to CpGcluster, the islands predicted by CPSORL covered a larger region in the TSS (12.2%) and promoter (26.1%) region. If Alu sequences are considered, the islands predicted by CPSORL (Alu) covered a larger TSS (40.5%) and promoter (67.8%) region than CpGIS. Furthermore, CPSORL was used to verify that the average methylation density was 5.33% for CpG islands in the entire human genome