High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias.
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ABSTRACT:
PROVIDER: PRJNA882066 | ENA |
REPOSITORIES: ENA
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Project description:Aberrant DNA methylation at CpG dinucleotides is a cancer hallmark that is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole-genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Analyses of available datasets confirmed TF binding to their target genes and conservation of the same gene-regulatory networks in large patient cohorts. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.
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Project description:Aberrant DNA-methylation at CpG dinucleotides is a hallmark of cancer and is associated with the emergence of resistance to anti-cancer treatment, though molecular mechanisms and biological signifi- cance remain elusive. Genome-scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG-rich regions (CpG islands). We report the first high-coverage whole-genome map in cancer using the long-read nanopore technol- ogy, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, af- ter chemotherapy. Long-read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution (> 99% CpGs), extending analyses of CpG is- lands to sparse CpGs, which represent half of all differentially-methylated regions. We showed that the
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Project description:Aberrant DNA-methylation at CpG dinucleotides is a hallmark of cancer and is associated with the emergence of resistance to anti-cancer treatment, though molecular mechanisms and biological signifi- cance remain elusive. Genome-scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG-rich regions (CpG islands). We report the first high-coverage whole-genome map in cancer using the long-read nanopore technol- ogy, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, af- ter chemotherapy. Long-read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution (> 99% CpGs), extending analyses of CpG is- lands to sparse CpGs, which represent half of all differentially-methylated regions. We showed that the
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