scholarly journals Focal disruption of DNA methylation dynamics at enhancers in IDH-mutant AML cells

Leukemia ◽  
2021 ◽  
Author(s):  
Elisabeth R. Wilson ◽  
Nichole M. Helton ◽  
Sharon E. Heath ◽  
Robert S. Fulton ◽  
Jacqueline E. Payton ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Myeloid Leukemia ◽  
Bisulfite Sequencing ◽  
Sequencing Data ◽  
Genome Wide ◽  
Cd34 Cells ◽  
Recurrent Mutations ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data ◽  
Acute Myeloid

AbstractRecurrent mutations in IDH1 or IDH2 in acute myeloid leukemia (AML) are associated with increased DNA methylation, but the genome-wide patterns of this hypermethylation phenotype have not been comprehensively studied in AML samples. We analyzed whole-genome bisulfite sequencing data from 15 primary AML samples with IDH1 or IDH2 mutations, which identified ~4000 focal regions that were uniquely hypermethylated in IDHmut samples vs. normal CD34+ cells and other AMLs. These regions had modest hypermethylation in AMLs with biallelic TET2 mutations, and levels of 5-hydroxymethylation that were diminished in IDH and TET-mutant samples, indicating that this hypermethylation results from inhibition of TET-mediated demethylation. Focal hypermethylation in IDHmut AMLs occurred at regions with low methylation in CD34+ cells, implying that DNA methylation and demethylation are active at these loci. AML samples containing IDH and DNMT3AR882 mutations were significantly less hypermethylated, suggesting that IDHmut-associated hypermethylation is mediated by DNMT3A. IDHmut-specific hypermethylation was highly enriched for enhancers that form direct interactions with genes involved in normal hematopoiesis and AML, including MYC and ETV6. These results suggest that focal hypermethylation in IDH-mutant AML occurs by altering the balance between DNA methylation and demethylation, and that disruption of these pathways at enhancers may contribute to AML pathogenesis.

Development of a method for identifying and functionally analyzing allele-specific DNA methylation based on BS-seq data

Epigenomics ◽  
2019 ◽  
Vol 11 (15) ◽  
pp. 1679-1692
Author(s):  
Jiang Zhu ◽  
Mu Su ◽  
Yue Gu ◽  
Xingda Zhang ◽  
Wenhua Lv ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Throughput ◽  
Bisulfite Sequencing ◽  
The Cancer Genome Atlas ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data ◽  
Allele Specific ◽  
New Perspective

Aim: To comprehensively identify allele-specific DNA methylation (ASM) at the genome-wide level. Methods: Here, we propose a new method, called GeneASM, to identify ASM using high-throughput bisulfite sequencing data in the absence of haplotype information. Results: A total of 2194 allele-specific DNA methylated genes were identified in the GM12878 lymphocyte lineage using GeneASM. These genes are mainly enriched in cell cytoplasm function, subcellular component movement or cellular linkages. GM12878 methylated DNA immunoprecipitation sequencing, and methylation sensitive restriction enzyme sequencing data were used to evaluate ASM. The relationship between ASM and disease was further analyzed using the The Cancer Genome Atlas (TCGA) data of lung adenocarcinoma (LUAD), and whole genome bisulfite sequencing data. Conclusion: GeneASM, which recognizes ASM by high-throughput bisulfite sequencing and heterozygous single-nucleotide polymorphisms, provides new perspective for studying genomic imprinting.

AKSmooth: Enhancing low-coverage bisulfite sequencing data via kernel-based smoothing

2014 ◽  
Vol 12 (06) ◽  
pp. 1442005
Author(s):  
Junfang Chen ◽  
Pavlo Lutsik ◽  
Ruslan Akulenko ◽  
Jörn Walter ◽  
Volkhard Helms
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Human Colon ◽  
Sequencing Data ◽  
Human Colon Cancer ◽  
High Coverage ◽  
Comprehensive Picture ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data ◽  
Low Coverage

Whole-genome bisulfite sequencing (WGBS) is an approach of growing importance. It is the only approach that provides a comprehensive picture of the genome-wide DNA methylation profile. However, obtaining a sufficient amount of genome and read coverage typically requires high sequencing costs. Bioinformatics tools can reduce this cost burden by improving the quality of sequencing data. We have developed a statistical method Ajusted Local Kernel Smoother (AKSmooth) that can accurately and efficiently reconstruct the single CpG methylation estimate across the entire methylome using low-coverage bisulfite sequencing (Bi-Seq) data. We demonstrate the AKSmooth performance on the low-coverage (~ 4×) DNA methylation profiles of three human colon cancer samples and matched controls. Under the best set of parameters, AKSmooth-curated data showed high concordance with the gold standard high-coverage sample (Pearson 0.90), outperforming the popular analogous method. In addition, AKSmooth showed computational efficiency with runtime benchmark over 4.5 times better than the reference tool. To summarize, AKSmooth is a simple and efficient tool that can provide an accurate human colon methylome estimation profile from low-coverage WGBS data. The proposed method is implemented in R and is available at https://github.com/Junfang/AKSmooth .

scholarly journals Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data

2014 ◽  
Vol 30 (13) ◽  
pp. 1933-1934 ◽  
Author(s):  
Kemal Akman ◽  
Thomas Haaf ◽  
Silvia Gravina ◽  
Jan Vijg ◽  
Achim Tresch
Keyword(s):  
Dna Methylation ◽  
Quantitative Analysis ◽  
Bisulfite Sequencing ◽  
Sequencing Data ◽  
Genome Wide ◽  
Bisulfite Sequencing Data

scholarly journals Analyzing whole genome bisulfite sequencing data from highly divergent genotypes

2019 ◽  
Vol 47 (19) ◽  
pp. e117-e117 ◽  
Author(s):  
Phillip Wulfridge ◽  
Ben Langmead ◽  
Andrew P Feinberg ◽  
Kasper D Hansen
Keyword(s):  
Dna Methylation ◽  
Genetic Variation ◽  
Bisulfite Sequencing ◽  
Joint Analysis ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data ◽  
Personal Genomes

Abstract In the study of DNA methylation, genetic variation between species, strains or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here, we use whole-genome bisulfite sequencing data on two highly divergent mouse strains to study this problem. We show that alignment to personal genomes is necessary for valid methylation quantification. We introduce a method for including strain-specific CpGs in differential analysis, and show that this increases power. We apply our method to a human normal-cancer dataset, and show this improves accuracy and power, illustrating the broad applicability of our approach. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, while accounting for differences in the spatial occurrences of CpGs. Our results have implications for joint analysis of genetic variation and DNA methylation using bisulfite-converted DNA, and unlocks the use of personal genomes for addressing this question.

scholarly journals Analyzing whole genome bisulfite sequencing data from highly divergent genotypes

2016 ◽  
Author(s):  
Phillip Wulfridge ◽  
Ben Langmead ◽  
Andrew P. Feinberg ◽  
Kasper D. Hansen
Keyword(s):  
Dna Methylation ◽  
Genetic Variation ◽  
Bisulfite Sequencing ◽  
Inbred Mouse ◽  
Mouse Strains ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

AbstractIn the study of DNA methylation, genetic variation between species, strains, or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here we use whole-genome bisulfite sequencing data on two highly divergent inbred mouse strains to study this problem. We find that while the large number of strain-specific CpGs necessitates considerations regarding the reference genomes used during alignment, properties such as CpG density are surprisingly conserved across the genome. We introduce a method for including strain-specific CpGs in differential analysis, and show that accounting for strain-specific CpGs increases the power to find differentially methylated regions between the strains. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, and also allowing us to account for differences in the spatial occurrences of CpGs. Our results have implications for analysis of genetic variation and DNA methylation using bisulfite-converted DNA.

scholarly journals Genome-wide bisulfite sequencing data of normal and Ascosphaera apis-infected larval guts of eastern honeybee

2020 ◽  
Author(s):  
Yu Du ◽  
Zhiwei Zhu ◽  
Huazhi Chen ◽  
Yuanchan Fan ◽  
Jie Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bisulfite Sequencing ◽  
Apis Cerana ◽  
Systematic Investigation ◽  
Regulation Mechanism ◽  
List Type ◽  
Sequencing Data ◽  
Ascosphaera Apis ◽  
Genome Wide ◽  
Bisulfite Sequencing Data

ABSTRACTApis cerana cerana, a subspecies of eastern honey, Apis cerana, plays a specific role in beekeeping industry and ecosystem in China and other Asian countries. Larvae of A. c. cerana can be infected by Ascosphaera apis, the fungal pathogen of chalkbrood. In this article, normal 4-, 5-, and 6-day-old larval guts (AcCK1, AcCK2, AcCK3) and A. apis-infected 4-, 5- and 6-day-old larval guts (AcT1, AcT2, AcT3) of A. c. cerana workers were respectively harvested followed by DNA isolation, bisulfite conversion, cDNA library construction and Illumina sequencing. Based on genome-wide bisulfite sequencing, 79167210, 82175052, 79331489, 81051009, 74742842 and 74849091 raw reads were generated from AcCK1, AcCK2, AcCK3, AcT1, AcT2 and AcT3, and after quality control, 73417030 (92.73%), 76660370 (93.27%), 71804727 (90.44%), 75046507 (92.82%), 67487782 (90.30%) and 67367023 (90.04%) clean reads were obtained, respectively. Additionally, 73333333, 76533333, 71466667, 75066667, 67590965 and 67200000 clean reads were mapped to the reference genome of A. cerana, including 54656767, 58583415, 54127407, 57943220, 52547867 and 51295824 unique mapped clean reads, and 8624392, 8789458, 7531333, 7747337, 6249679 and 5394174 multiple mapped clean reads. The genome-wide bisulfite sequencing data reported here can be used for genome-wide identification of 5mC methylation sites in eastern honeybee larval guts and systematic investigation of DNA methylation-mediated host response to A. apis infection.Value of the dataThe current dataset contributes to genome-wide identification of 5mC methylation sites in normal and A. apis-infected larval guts of eastern honeybee.The reported data could be used for systematic investigation of DNA methylation-mediated response of eastern honeybee larvae to A. apis infection.Our data offers a valuable genetic resource for better understanding epigenetic regulation mechanism involved in eastern honeybee larvae-A. apis interaction.

scholarly journals GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data

2012 ◽  
Vol 41 (4) ◽  
pp. e55-e55 ◽  
Author(s):  
Touati Benoukraf ◽  
Sarawut Wongphayak ◽  
Luqman Hakim Abdul Hadi ◽  
Mengchu Wu ◽  
Richie Soong
Keyword(s):  
Bisulfite Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Genome Bisulfite Sequencing ◽  
Genome Bisulfite Sequencing ◽  
Bisulfite Sequencing Data

scholarly journals Low-pass whole genome bisulfite sequencing of neonatal dried blood spots identifies a role for RUNX1 in Down syndrome DNA methylation profiles

2020 ◽  
Author(s):  
Benjamin I Laufer ◽  
Hyeyeon Hwang ◽  
Julia M Jianu ◽  
Charles E Mordaunt ◽  
Ian F Korf ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Down Syndrome ◽  
Early Life ◽  
Trisomy 21 ◽  
Bisulfite Sequencing ◽  
Dried Blood Spots ◽  
Whole Genome ◽  
Genome Wide ◽  
Low Pass ◽  
Genome Bisulfite Sequencing

Abstract Neonatal dried blood spots (NDBS) are a widely banked sample source that enables retrospective investigation into early life molecular events. Here, we performed low-pass whole genome bisulfite sequencing (WGBS) of 86 NDBS DNA to examine early life Down syndrome (DS) DNA methylation profiles. DS represents an example of genetics shaping epigenetics, as multiple array-based studies have demonstrated that trisomy 21 is characterized by genome-wide alterations to DNA methylation. By assaying over 24 million CpG sites, thousands of genome-wide significant (q < 0.05) differentially methylated regions (DMRs) that distinguished DS from typical development and idiopathic developmental delay were identified. Machine learning feature selection refined these DMRs to 22 loci. The DS DMRs mapped to genes involved in neurodevelopment, metabolism, and transcriptional regulation. Based on comparisons with previous DS methylation studies and reference epigenomes, the hypermethylated DS DMRs were significantly (q < 0.05) enriched across tissues while the hypomethylated DS DMRs were significantly (q < 0.05) enriched for blood-specific chromatin states. A ~28 kb block of hypermethylation was observed on chromosome 21 in the RUNX1 locus, which encodes a hematopoietic transcription factor whose binding motif was the most significantly enriched (q < 0.05) overall and specifically within the hypomethylated DMRs. Finally, we also identified DMRs that distinguished DS NDBS based on the presence or absence of congenital heart disease (CHD). Together, these results not only demonstrate the utility of low-pass WGBS on NDBS samples for epigenome-wide association studies, but also provide new insights into the early life mechanisms of epigenomic dysregulation resulting from trisomy 21.

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