Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

Background: Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is important, but current approaches tackle average methylation within a genomic locus and are often limited to specific genomic regions. Results: We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict CpG site methylation levels using as features neighboring CpG site methylation levels and genomic distance, and co-localization with coding regions, CGIs, and regulatory elements from the ENCODE project, among others. Our approach achieves 91% -- 94% prediction accuracy of genome-wide methylation levels at single CpG site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs. Our classifier outperforms state-of-the-art methylation classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation status, CpG island status, co-localized DNase I hypersensitive sites, and specific transcription factor binding sites were found to be most predictive of methylation levels. Conclusions: Our observations of DNA methylation patterns led us to develop a classifier to predict site-specific methylation levels that achieves the best DNA methylation predictive accuracy to date. Furthermore, our method identified genomic features that interact with DNA methylation, elucidating mechanisms involved in DNA methylation modification and regulation, and linking different epigenetic processes

Evolution of the Belomorian Belt: NORDSIM U-Pb zircon dating of the Chupa paragneisses, magmatism, and metamorphic stages

The U-Pb systematics of accessory zircons were studied by secondary ion mass spectrometry (NORDSIM ion microprobe). This study revealed two main age groups of terrigenous zircons, 3000 and 2900 Ma, in the metasedimentary rocks of the Chupa nappe of the Belomorian belt. Zircon older than 3200 Ma was not found, which is consistent with the available Sm-Nd model ages. Older terrigenous zircons (3100-3200 Ma) were found only in the northern part of the belt, which is probably a consequence of the input of Mesoarchean material from the Karelian craton and/or the Kola province. The oldest metamorphic zircons of Belomorian paragneisses were formed 2820 +/- 15 Ma ago. Zircons with an age of 2710 15 Ma provide a record of collisional metamorphism of the high-pressure granulite, eclogite, and amphibolite facies, which was completed by several magmatic and migmatitic events 2615 +/- 15 Ma ago. The basic magmatism of 2450-2400 Ma did not produce accessory zircons in the supracrustal complexes of the Belomorian belt. In contrast, the later Svecofennian metamorphism of the amphibolite facies resulted in the reequilibration of the U-Pb isotopic system of sphene and growth of a new zircon generation, especially in the zones of migmatization and pegmatite formation between 1900 and 1800 Ma. Early Proterozoic tectonothermal processes only partially obliterated the record of the Archean history of the Belomorian belt, which does not prevent the reconstruction of Archean tectonic settings. New more accurate isotopic data supported the previously proposed geodynamic model of the evolution of the Belomorian belt. According to this model, its formation occurred under the influence of oceanic crust subduction 2900-2800 Ma ago and subsequent collision with the Karelian craton 2730-2710 Ma ago

Plasmonic Optical Imaging of Gold Nanorods Localization in Small Animals

Gold nanoparticles (GNP) have been intensively investigated for applications in cancer imaging and therapy. Most imaging studies focused on microscopic imaging. Their potential as optical imaging probes for whole body small animal imaging has rarely been explored. Taking advantage of their surface plasmon resonance (SPR) properties, we aim to develop a noninvasive diffuse optical imaging method to map the distribution of a special type of GNP, gold nanorods (GNR), in small animals. We developed an integrated dual-modality imaging system capable of both x-ray computed tomography (XCT) and diffuse optical tomography (DOT). XCT provides the animal anatomy and contour required for DOT; DOT maps the distribution of GNR in the animal. This SPR enhanced optical imaging (SPROI) technique was investigated using simulation, phantom and mouse experiments. The distribution of GNR at various concentrations (0.1-100 nM, or 3.5 ug/g-3.5 mg/g) was successfully reconstructed from centimeter-scaled volumes. SPROI detected GNR at 18 μg/g concentration in the mouse breast tumor, and is 3 orders more sensitive than x-ray imaging. This study demonstrated the high sensitivity of SPROI in mapping GNR distributions in small animals. It does not require additional imaging tags other than GNR themselves. SPROI can be used to detect tumors targeted by GNR via passive targeting based on enhanced permeability and retention or via active targeting using biologically conjugated ligands