Dnmt2-dependent methylomes lack defined DNA methylation patterns

Several organisms have retained methyltransferase 2 (Dnmt2) as their only candidate DNA methyltransferase gene. However, information about Dnmt2-dependent methylation patterns has been limited to a few isolated loci and the results have been discussed controversially. In addition, recent studies have shown that Dnmt2 functions as a tRNA methyltransferase, which raised the possibility that Dnmt2-only genomes might be unmethylated. We have now used whole-genome bisulfite sequencing to analyze the methylomes of Dnmt2-only organisms at single-base resolution. Our results show that the genomes of Schistosoma mansoni and Drosophila melanogaster lack detectable DNA methylation patterns. Residual unconverted cytosine residues shared many attributes with bisulfite deamination artifacts and were observed at comparable levels in Dnmt2-deficient flies. Furthermore, genetically modified Dnmt2-only mouse embryonic stem cells lost the DNA methylation patterns found in wild-type cells. Our results thus uncover fundamental differences among animal methylomes and suggest that DNA methylation is dispensable for a considerable number of eukaryotic organisms

NIPTeR:an R package for fast and accurate trisomy prediction in non-invasive prenatal testing

BACKGROUND: Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed.RESULTS: NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies.CONCLUSION: NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.</p

Solenosmilia variabilis-bearing cold-water coral mounds off Brazil

Cold-water corals (CWC), dominantly Desmophyllum pertusum (previously Lophelia pertusa), and their mounds have been in the focus of marine research during the last two decades; however, little is known about the mound-forming capacity of other CWC species. Here, we present new 230Th/U age constraints of the relatively rarely studied framework-building CWC Solenosmilia variabilis from a mound structure off the Brazilian margin combined with computed tomography (CT) acquisition. Our results show that S. variabilis can also contribute to mound formation, but reveal coral-free intervals of hemipelagic sediment deposits, which is in contrast to most of the previously studied CWC mound structures. We demonstrate that S. variabilis only occurs in short episodes of < 4 kyr characterized by a coral content of up to 31 vol%. In particular, it is possible to identify distinct clusters of enhanced aggradation rates (AR) between 54 and 80 cm ka−1. The determined AR are close to the maximal growth rates of individual S. variabilis specimens, but are still up to one order of magnitude smaller than the AR of D. pertusum mounds. Periods of enhanced S. variabilis AR predominantly fall into glacial periods and glacial terminations that were characterized by a 60–90 m lower sea level. The formation of nearby D. pertusum mounds is also associated with the last glacial termination. We suggest that the short-term periods of coral growth and mound formation benefited from enhanced organic matter supply, either from the adjacent exposed shelf and coast and/or from enhanced sea-surface productivity. This organic matter became concentrated on a deeper water-mass boundary between South Atlantic Central Water and the Antarctic Intermediate Water and may have been distributed by a stronger hydrodynamic regime. Finally, periods of enhanced coral mound formation can also be linked to advection of nutrient-rich intermediate water masses that in turn might have (directly or indirectly) further facilitated coral growth and mound formation

Targeted RNA-Sequencing Enables Detection of Relevant Translocations and Single Nucleotide Variants and Provides a Method for Classification of Hematological Malignancies-RANKING

BACKGROUND: Patients with hematological malignancies (HMs) carry a wide range of chromosomal and molecular abnormalities that impact their prognosis and treatment. Since no current technique can detect all relevant abnormalities, technique(s) are chosen depending on the reason for referral, and abnormalities can be missed. We tested targeted transcriptome sequencing as a single platform to detect all relevant abnormalities and compared it to current techniques. MATERIAL AND METHODS: We performed RNA-sequencing of 1385 genes (TruSight RNA Pan-Cancer, Illumina) in bone marrow from 136 patients with a primary diagnosis of HM. We then applied machine learning to expression profile data to perform leukemia classification, a method we named RANKING. Gene fusions for all the genes in the panel were detected, and overexpression of the genes EVI1, CCND1, and BCL2 was quantified. Single nucleotide variants/indels were analyzed in acute myeloid leukemia (AML), myelodysplastic syndrome and patients with acute lymphoblastic leukemia (ALL) using a virtual myeloid (54 genes) or lymphoid panel (72 genes). RESULTS: RANKING correctly predicted the leukemia classification of all AML and ALL samples and improved classification in 3 patients. Compared to current methods, only one variant was missed, c.2447A>T in KIT (RT-PCR at 10(-4)), and BCL2 overexpression was not seen due to a t(14; 18)(q32; q21) in 2% of the cells. Our RNA-sequencing method also identified 6 additional fusion genes and overexpression of CCND1 due to a t(11; 14)(q13; q32) in 2 samples. CONCLUSIONS: Our combination of targeted RNA-sequencing and data analysis workflow can improve the detection of relevant variants, and expression patterns can assist in establishing HM classification

Climate Vulnerability and the Cost of Debt

We use indices from the Notre Dame Global Adaptation Initiative to investigate the impact of climate vulnerability on bond yields. Our methodology invokes panel ordinary least squares with robust standard errors and principal component analysis. The latter serves to address the multicollinearity between a set of vulnerability measures. We find that countries with higher exposure to climate vulnerability, such as the member countries of the V20 climate vulnerable forum, exhibit 1.174 percent higher cost of debt on average. This effect is significant after accounting for a set of macroeconomic controls. Specifically, we estimate the incremental debt cost due to higher climate vulnerability, for the V20 countries, to have exceeded USD 62 billion over the last ten years. In other words, for every ten dollars they pay in interest cost, they pay another dollar for being climate vulnerable. We also find that a measure of social readiness, which includes education and infrastructure, has a negative and significant effect on bond yields, implying that social and physical investments can mitigate climate risk related debt costs and help to stabilize the cost of debt for vulnerable countries

CoNVaDING:Single Exon Variation Detection in Targeted NGS Data

We have developed a tool for detecting single exon copy number variations (CNVs) in targeted next-generation sequencing data: CoNVaDING (Copy Number Variation Detection In Next-generation sequencing Gene panels). CoNVaDING includes a stringent quality control metric, that excludes or flags low quality exons. Since this quality control shows exactly which exons can be reliably analysed and which exons are in need of an alternative analysis method, CoNVaDING is not only useful for CNV detection in a research setting, but also in clinical diagnostics. During the validation phase, CoNVaDING detected all known CNVs in high quality targets in 320 samples analysed, giving 100% sensitivity and 99.998% specificity for 308,574 exons. CoNVaDING outperforms existing tools by exhibiting a higher sensitivity and specificity and by precisely identifying low-quality samples and regions. This article is protected by copyright. All rights reserved.</p