Find research datasets worth reusing

opencc-by-4.0Apr 2020View details →

Raw diffraction data (CBF) for a structure of SARS-CoV-2 Main Protease bound to 2-Methyl-1-tetralone

Data collected at beamline P11/PETRAIII Deutsches Elektronen Synchrotron DESY Info: run type:            regular run name:            l6p17_09_001 start angle:         0.000000deg frames:              1000 degrees/frame:       0.200000deg exposure time:       40.000000ms energy:              11.999832keV wavelength:          1.033214A detector distance:   200.000000mm resolution:          1.304257A aperture:            100um filter transmission: 71.798748% filter thickness:    75um ring current:        119.222664mA Crystal-info: Co-crystallization of Sars-CoV-2 MPro with the compound was achieved by equlibrating a 6.25 mg/ml protein solution in 20 mM HEPES buffer (pH 7.8) containing 1 mM DTT, 1mM EDTA, and 150 mM NaCl against a reservoir solution of 100 mM MIB buffer (2:3:3 molar ratio of malonic acid, imidazole, and boric acid), pH 7.5, containing 25% v/v PEG 1500 and 5% v/v DMSO. Prior to crystallization compound solutions in DMSO were dried onto the wells of SwissCI 96-well plates. To achieve reproducible crystal growth seeding was used. Crystals appeared within a few hours and reached their final size after 2 -3 days. Crystals were manually harvested and flash cooled in liquid nitrogen for subsequent X-ray diffraction data collection.

opencc-by-4.0Aug 2020View details →

Structural dynamics of DNA depending on methylation pattern: Simulation dataset

Dataset of molecular dynamics simulations of double-stranded DNA (repeats of CpG dinucleotides with regular patterns of methylation). - Input: Parameters and initial structures - Output: Trajectories NAMD 2.13 (multi-core with CUDA) was used for the simulations.

opencc-by-4.0Sep 2016View details →

TCGA Breast Cancer 450K Methylation Data

The archived folder holds level 1 450K DNA methylation IDAT files for the TCGA Breast Cancer dataset. The data is used in the analysis pipeline associated with the GitHub repository: https://github.com/gwaygenomics/brca_lowstage_DMGRs

opencc-zeroNov 2023View details →

Data from: Non-invasive age estimation based on fecal DNA using methylation-sensitive high-resolution melting for Indo-Pacific bottlenose dolphins

Age is necessary information for the study of life history of wild animals. A general method to estimate the age of odontocetes is counting dental growth layer groups (GLGs). However, this method is highly invasive as it requires the capture and handling of individuals to collect their teeth. Recently, the development of DNA-based age estimation methods has been actively studied as an alternative to such invasive methods, of which many have used biopsy samples. However, if DNA-based age estimation can be developed from fecal samples, age estimation can be performed without touching or disrupting individuals, thus establishing an entirely non-invasive method. We developed an age estimation model using the methylation rate of two gene regions, GRIA2 and CDKN2A, measured through methylation-sensitive high-resolution melting (MS-HRM) from fecal samples of wild Indo-Pacific bottlenose dolphins (Tursiops aduncus). The age of individuals was known through conducting longitudinal individual identification surveys underwater. Methylation rates were quantified from 36 samples. Both gene regions showed a significant correlation between age and methylation rate. The age estimation model was constructed based on the methylation rates of both genes which achieved sufficient accuracy (after LOOCV: MAE = 5.08, R2 = 0.34) for the ecological studies of the Indo-Pacific bottlenose dolphins, with a lifespan of 40-50 years. This is the first study to report the use of non-invasive fecal samples to estimate the age of marine mammals.

opencc-by-4.0Nov 2023View details →

Germline CpG methylation signatures in the human population inferred from genetic polymorphism

This repository contains data released accompanying the manuscript "Germline CpG methylation signatures in the human population inferred from genetic polymorphism".

opencc-by-4.0Nov 2023View details →

Data from: Methylation-based markers for the estimation of age in African Cheetah, Acinonyx jubatus

This is a dataset for methylation analyses in cheetah done by EpiTYPER mass array.

opencc-zeroNov 2023View details →

Age estimation of captive Asian elephants (Elephas maximus) based on DNA methylation: An exploratory analysis using methylation-sensitive high-resolution melting (MS-HRM)

Age is an important parameter for bettering the understanding of biodemographic trends-development, survival, reproduction and environmental effects-critical for conservation. However, current age estimation methods are challenging to apply to many species, and no standardised technique has been adopted yet. This study examined the potential use of methylation-sensitive high-resolution melting (MS-HRM), a labour, time, and cost-effective method to estimate chronological age from DNA methylation in Asian elephants (Elephas maximus). The objective of this study was to investigate the accuracy and validation of MS-HRM use for age determination in long-lived species, such as Asian elephants. The average lifespan of Asian elephants is between 50-70 years but some have been known to survive for more than 80 years. DNA was extracted from 53 blood samples of captive Asian elephants across 11 zoos in Japan, with known ages ranging from a few months to 65 years. Methylation rates of two candidate age-related epigenetic genes, RALYL and TET2, were significantly correlated with chronological age. Finally, we established a linear, unisex age estimation model with a mean absolute error (MAE) of 7.36 years. This exploratory study suggests an avenue to further explore MS-HRM as an alternative method to estimate the chronological age of Asian elephants.

opencc-by-4.0Dec 2022View details →

Data from "Stability of genome-wide methylation patterns and parental environmental effects in the widespread, long-lived Lombardy poplar"

Data from : 'Stability of genome-wide methylation patterns and parental environmental effects in the widespread, long-lived Lombardy poplar' An Vanden Broeck*, Tim Meese*, Pieter Verschelde, Karen Cox, Berthold Heinze, Dieter Deforce, Ellen De Meester and Filip Van Nieuwerburgh   Related publication: Vanden Broeck, A.*, Meese, T.*, Verschelde, P. et al. Genome-wide methylome stability and parental effects in the worldwide distributed Lombardy poplar. BMC Biol 22, 30 (2024). https://doi.org/10.1186/s12915-024-01816-1 <ul> <li>* These authors contributed equally.</li> </ul> -------------------------------------------------- Background: Despite the increasing number of epigenomic studies in plants, little is known about the forces that shape the methylome in long-lived woody perennials. The Lombardy poplar (Populus nigra cv. 'Italica' Duroi) offers an ideal opportunity to investigate the impact of the individual environmental history of trees on the methylome. Results: We present the results of three interconnected experiments on Lombardy poplar. In the first experiment, we investigated methylome variability during a growing season and across vegetatively reproduced generations. We found that ramets collected over Europe and raised in common conditions have stable methylomes in symmetrical CG-contexts. In contrast, seasonal dynamics occurred in methylation patterns in CHH-context. In the second experiment, we investigated whether methylome patterns of plants grown in a non-parental environment correlate with the parental climate. We did not observe any biological relevant pattern that significantly correlates with the parental climate. Finally, we investigated whether the parental environment has persistent carry-over effects on the vegetative offspring's' phenotype. We combined new bud set observations of three consecutive growing seasons with former published bud set data. Using a linear mixed effects analysis, we found a statistically significant but weak short-term, parental carry-over effect on the timing of bud set. However, this effect was negligible compared to the direct effects of the offspring environment. Conclusions: Genome-wide cytosine methylation patterns in symmetrical GC-context are stable in Lombardy poplar and appear to be mainly the result of random processes. In this widespread poplar clone, methylation patterns in GC-context can be used as bio-markers to infer a common ancestor and thus to investigate the environmental history of a specific Lombardy poplar on short time-scales. The Lombardy poplar shows high phenotypic plasticity in a novel environment which enabled this clonal tree to adapt and survive all over the temperate regions of the world.   ADDITIONAL FILES Additional file 1. CSV-file with information on the Lombardy poplar trees samples used for whole genome bisulfite sequencing (WGBS) in the two methylome experiments (metadata). The raw fastq datafiles obtained by whole genome bisulfite sequencing (WGBS) are available at the <a href="https://www.ncbi.nlm.nih.gov/geo/">Gene Expression Omnibus (GEO) database</a> (submission  GSE225596). Additional file 2. CSV-file with mapping statistics, bisulfite conversion rates and percentages of cytosine methylation for each DNA-sample analyzed by whole genome bisulfite sequencing (WGBS). (processed data). Additional file 3. CSV-file with the total list of GO terms that were enriched in DMRs. DMRs were identified between groups by grouping the WGBS data from 16 individual Lombardy poplar ramets by their corresponding parent-of-origin (ortet ‘HUN4’ located in Hungary, ‘ITS3’ in Italy, ‘SPC1’ in Spain and ‘UKD2’ in the UK, respectively) (processed data). Additional file 4. POWERPOINT-file. Heatmaps with GO terms over-represented in promoters containing DMRs in CpG-context per between-group pairwise comparison. DMRs were identified between groups by grouping the WGBS data from 16 individual Lombardy poplar ramets by their corresponding parent-of-origin (ortet ‘HUN4’ located in Hungary, ‘ITS3’ in Italy, ‘SPC1’ in Spain and ‘UKD2’ in the UK, respectively). A. HUN4 versus ITS3; B. HUN4 versus UKD2, C; ITS3 versus SPC1; D. HUN4 versus SCP1,  E. SPC1 versus UKD2 Additional file 5. CSV-file with the raw data of the bud set observations in the common garden experiment (raw data). Additional file 6. HTML-file with the R source codes to reproduce the results of the bud set analysis (code, R script). Additional file 7. A text-file representing the Snakefile (i.e. a readable Python-based workflow) including the different steps and rules of the bioinformatics of the WGBS data analyses (code, Snakefile). Additional file 8. RMD-file with the code to reproduce the analyses to identify differential methylated predefined regions (code, R script). Additional file 9. R-script with the code to reproduce the clustering and visualizing of the GO enrichment results (code, R script). Supporting files 1. Zip-folder with: i) excel-files listing the genes in DMRs, and ii) PNG-files with the ‘Biological Coefficient of Variation (BCV)’-plots between any of the six pairwise comparisons of Lombardy poplars grouped per ortet and identified with Bioconductor package edgeR. DMRs were identified between groups by grouping the WGBS data from 16 individual Lombardy poplar ramets by their corresponding parent-of-origin (‘HUN4’ located in Hungary, ‘ITS3’ in Italy, ‘SPC1’ in Spain and ‘UKD2’ in the UK, respectively) (processed data). Supporting files 2. Zip-folder with PNG-files representing heatmaps and excel-files with clustered GO terms significant over-represented in promoters and gene regions located in DMRs. DMRs were identified between groups by grouping the WGBS data from 16 individual Lombardy poplar ramets by their corresponding parent-of-origin (ortet ‘HUN4’ located in Hungary, ‘ITS3’ in Italy, ‘SPC1’ in Spain and ‘UKD2’ in the UK, respectively. The files were obtained with the Bioconductor package simplifyEnrichment (processed data). --------------------------------------------------------- Version 3: <ul> <li>Renaming of file names according to the publisher's guidelines</li> <li>Additional file 2 includes also bisulfite conversion rates per sample</li> </ul>

opencc-zeroJan 2024View details →

Data from: A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus), and Panthera species, using targeted bisulfite sequencing and machine learning models

Knowledge of individual age can help both in-situ and ex-situ conservation programs to design more efficient and suitable management plans for targeted wildlife species. DNA methylation is one of the epigenetic aging markers that has emerged as a promising tool that can estimate age with high accuracy using only a tiny amount of biological material, which can be collected in a minimally invasive way. Here, we sequenced five targeted genetic regions and used 8–23 selected CpG sites to build age estimation models with machine learning methods with about only $3–7 per sample, using blood samples of seven Felidae species—ranging from small to big, and domestic to endangered species: domestic cats (Felis catus, 139 samples), Tsushima leopard cats (Prionailurus bengalensis euptilurus, 84 samples), and five Panthera species (96 samples). The models built achieved satisfactory accuracy—the mean absolute error of the best models was 1.966, 1.348, and 1.552 years in domestic cats, Tsushima leopard cats, and Panthera spp., respectively. Our models in domestic cats and Tsushima leopard cats were applicable to individuals regardless of health conditions, indicating the high applicability of our models to samples collected from diverse situations, e.g., rescued individuals in the context of conservation. We also showed the possibility of developing universal age estimation models for the five Panthera spp. using two of the five genetic regions, suggesting an even lower cost to use our models for future applications.

opencc-zeroFeb 2024View details →

Early developmental carry-over effects on exploratory behaviour and DNA methylation in wild great tits (Parus major)

Adverse, postnatal conditions experienced during development are known to induce lingering effects on morphology, behaviour, reproduction and survival. Despite the importance of early developmental stress for shaping the adult phenotype, it is largely unknown which molecular mechanisms allow for the induction and maintenance of such phenotypic effects once the early environmental conditions are released. Here we aimed to investigate whether lasting early developmental phenotypic changes are associated with post-developmental DNA methylation changes. We used a cross-foster and brood size experiment in great tit (Parus major) nestlings, which induced post-fledging effects on biometric measures and exploratory behaviour, a validated personality trait. We investigated whether these post-fledging effects are associated with DNA methylation levels of CpG sites in erythrocyte DNA. Individuals raised in enlarged broods caught up on their developmental delay after reaching independence and became more explorative as days since fledging passed, while the exploratory scores of individuals that were raised in reduced broods remained stable. Although we previously found that brood enlargement hardly affected pre-fledging methylation levels, we found 420 CpG sites that were differentially methylated between fledged individuals that were raised in small versus large sized broods. A considerable number of the affected CpG sites were located in or near genes involved in metabolism, growth, behaviour and cognition. Since the biological functions of these genes line up with the observed post-fledging phenotypic effects of brood size, our results suggest that DNA methylation provides organisms the opportunity to modulate their condition once the environmental conditions allow it. In conclusion, this study shows that nutritional stress during early development associates with indirect, carry-over effects on DNA methylation. We propose that treatment-associated DNA methylation differences arise as a consequence of pre-fledging phenotypic changes, rather than that they cause early environmentally-induced effects.

Genetic architecture of immune cell DNA methylation in the rhesus macaque

Complete model outputs from rhesus macaque (Macaca mulatta) whole blood meQTL and eQTL analyses in article, "Genetic architecture of immune cell DNA methylation in the rhesus macaque".  cis meQTL model output (SNP-CpG associations):  <ol> <li>IMAGE_573_meqtl_model_res_wPVE.txt:  <ul> <li>Model results from IMAGE meQTL mapping including all genome, chromatin state annotations, and PVE estimates</li> </ul> </li> <li>pqlseq_allimagesnps_res_converged_wpve.txt: <ul> <li>Model results from PQLseq meQTL mapping including PVE estimates </li> </ul> </li> </ol> cis eQTL model output (SNP-gene associations):  <ol> <li>eqtl_res_sva5_gemma_172samples_qvalue.txt:  <ul> <li>Model results from GEMMA eQTL mapping </li> </ul> </li> </ol>

Multi-cell type deconvolution using a probabilistic model for single-molecule DNA methylation haplotypes

Files required to run deconvolution with CelFIE-ISH and Epistate, in U250 regions from Loyfer et al. 2023, in both "pat" and "epiread" formats.

Title: Health-Related Quality of Life and DNA Methylation-Based Aging Biomarkers among Survivors of Childhood Cancer

Abstract Background: Childhood cancer survivors are at high risk for morbidity and mortality and poor patient-reported outcomes, typically health-related-quality-of-life (HRQOL). However, associations between DNA methylation (DNAm)-based aging biomarkers and HRQOL have not been evaluated. Methods: DNAm was generated with Infinium EPIC BeadChip on blood-derived DNA (median[range] for age at blood draw=34.5[18.5-66.6] years) and HRQOL was assessed with age at survey (32.3[18.4-64.5] years) from 2,206 survivors in the St. Jude Lifetime Cohort. DNAm-based aging biomarkers, including epigenetic age using multiple clocks (e.g., GrimAge) and others (e.g., DNAmB2M: beta-2-microglobulin; DNAmADM: adrenomedullin), were derived from the DNAm Age Calculator (https://dnamage.genetics.ucla.edu). HRQOL was assessed using the Medical Outcomes Study 36-Item Short-Form Health Survey to capture eight domains, and physical and mental component summaries (PCS and MCS). General linear models evaluated associations between HRQOL and epigenetic age acceleration (EAA, e.g., EAA_GrimAge) or other age-adjusted DNAm-based biomarkers (e.g., ageadj_DNAmB2M) after adjusting for age at blood draw, sex, cancer treatments, and DNAm-based surrogate for smoking pack-years. All P values were 2-sided. Results: Worse HRQOL was associated with greater EAA_GrimAge (PCS: β[95%CI]=-0.18[-0.251,-0.11] years, P=1.85×10-5; and four individual HRQOL domains), followed by ageadj_DNAmB2M (PCS: -0.08[-0.124,-0.037], P=0.003; and three individual HRQOL domains), and ageadj_DNAmADM (PCS: -0.082[-0.125,-0.039], P=0.002; and two HRQOL domains). EAA_Hannum (Hannum clock) was not associated with any HRQOL. Conclustion: Overall and domain-specific measures of HRQOL are associated with DNAm measures of biological aging. Future longitudinal studies should test biological aging as a potential mechanism.

DNA methylation in sperm of rats at two ages exposed or not to 2,2',4,4'-tetrabromodiphenyl ether

Introduction This study was designed to determine the potential of environmentally relevant levels of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) to induce age-dependent changes in a rat’s sperm epigenome. The methods used to generate the files are described below.   Experimental design Twelve seven-week-old pregnant Wistar rats were divided into two groups (6 per group) – control and BDE-47 exposed group. Between pregnancy day 8 and postnatal day 21 (PND21), dams in each group were fed from the tip of pipette 0.2 µL/g body weight of the vehicle (tocopherol-stripped corn oil) or the same volume of a 1 mg/mL solution of BDE-47 daily. The BDE-47 group resulted in an exposure level of 0.2 mg/kg body weight of BDE-47 per day. On PND65 and PND120, one male pup randomly selected from each litter was euthanized, and epididymal motile spermatozoa were collected via the swim-up procedure as described in detail elsewhere (Suvorov et al., 2018). Sperm DNA was extracted using the rapid method (Wu et al., 2015). Extracted sperm DNA was subjected to reduced representation bisulfite sequencing (RRBS).   Reduced representation bisulfite sequencing For RRBS, bisulfite-converted libraries were prepared from 100 ng of the sperm DNA using Ovation RRBS Methyl-Seq System and EpiTect Fast DNA Bisulfite Kit (Cat. #59824, Qiagen) following manufacturers’ protocols. Sequencing of libraries was done using the HiSeq 2500 sequencing system (Illumina) in Deep Sequencing Core Facility of the University of Massachusetts Medical School (Schrewsbury, MA) with an average of 18.0 million unique reads per sample.   Bioinformatic analysis Raw reads from the sequence were processed following the recommended protocol for libraries prepared with Ovation RRBS Methyl-Seq System (NuGEN) and then mapped to the rn6 Rattus norvegicus reference genome using Bismark (version 0.16.1) and bowtie-2 (version 2.2.9). PCR duplicates were removed using nudup.py (version 2.2). The resulting SAM files for the control and BDE-47 group for the two ages, PND65 and 120 are uploaded.

opencc-by-4.0Apr 2022View details →

Figure 2 in Effects of methyl farnesoate injection on spermatozoa number and reproductive indices in the narrow-clawed crayfish Pontastacus leptodactylus

Figure 2. Effect of MF injection on reproductive system weight and GSI in male Pontastacus leptodactylus. Letters indicate significant difference groupings (P <0.05) (mean ± S.D; n = 15).

opencc-by-4.0Jun 2024View details →

Raw diffraction data for CCDC 2364133 – crystal structure of 2,2'-[ethane-1,2-diylbis(sulfanediyl)]bis(2-methyl-1,4-dithiane)

X-ray diffraction data from a single crystal of 2,2'-[ethane-1,2-diylbis(sulfanediyl)]bis(2-methyl-1,4-dithiane)

opencc-by-4.0Dec 2021View details →

DNA methylation in clonal Duckweed lineages (Lemna minor L.) reflects current and historical environmental exposures.

The following depository contains raw phenotypic data and intermediate DNA methylation data presented in the article "DNA methylation in clonal Duckweed lineages (Lemna minor L.) reflects current and historical environmental exposures." : 1) Raw phenotypic data - Frond_area_Phase1_Phase2 -> Frond area measured at different time points (week 1, 6, 7 and 8) during the experiment. - Frond_number_Phase1_Phase2 -> Frond number measured at different time points (week 1, 6, 7 and 8) during the experiment. 2) Intermediate files obtained from running the epiGBS2 pipeline. The following files are available: - consensus_cluster.renamed.fa ->  epiGBS de novo loci. This file consists of the de novo epiGBS reference sequence file obtained during the de novo reference creation. - methylation.filtMETH -> The filtered DNA methylation data. This data was obtained after filtering the raw DNA methylation data. Cytosines which had a 10X coverage or higher and which were present in 80% of all samples were kept for further analysis. Demultiplexed and raw data were deposited at NCBI: BioProject: PRJNA883550