Dataset Information

AIMER: A SNP-independent software for identifying imprinting-like allelic methylated regions from DNA methylome.

ABSTRACT: Genomic imprinting is essential for mammalian growth and embryogenesis. High-throughput bisulfite sequencing accompanied with parental haplotype-specific information allows analysis of imprinted genes and imprinting control regions (ICRs) on a large scale. Currently, although several allelic methylated regions (AMRs) detection software were developed, methods for detecting imprinted AMRs is still limited. Here, we developed a SNP-independent statistical approach, AIMER, to detect imprinting-like AMRs. By using the mouse frontal cortex methylome as input, we demonstrated that AIMER performs very well in detecting known germline ICRs compared with other methods. Furthermore, we found the putative parental AMRs AIMER detected could be distinguished from sequence-dependent AMRs. Finally, we found a novel germline imprinting-like AMR using WGBS data from 17 distinct mouse tissue samples. The results indicate that AIMER is a good choice for detecting imprinting-like (parent-of-origin-dependent) AMRs. We hope this method will be helpful for future genomic imprinting studies. The Python source code for our project is now publicly available on both GitHub (https://github.com/ZhaoLab-TMU/AIMER) and Gitee (https://gitee.com/zhaolab_tmu/AIMER).

SUBMITTER: Luo Y

PROVIDER: S-EPMC10809074 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature

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Publications

AIMER: A SNP-independent software for identifying imprinting-like allelic methylated regions from DNA methylome.

Luo Yanrui Y Zhou Tong T Liu Deng D Wang Fan F Zhao Qian Q

Computational and structural biotechnology journal 20240103

Genomic imprinting is essential for mammalian growth and embryogenesis. High-throughput bisulfite sequencing accompanied with parental haplotype-specific information allows analysis of imprinted genes and imprinting control regions (ICRs) on a large scale. Currently, although several allelic methylated regions (AMRs) detection software were developed, methods for detecting imprinted AMRs is still limited. Here, we developed a SNP-independent statistical approach, AIMER, to detect imprinting-like ...[more]

PMID: 38274999

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Project description:BackgroundImprinted genes are regulated by DNA methylation at imprinting-associated differentially methylated regions (iDMRs). Abnormal expression of imprinted genes is implicated in imprinting disorders and tumors. In colorectal cancer (CRC), methylation and imprinting status of the IGF2/H19 domain have been studied. However, no comprehensive methylation analysis of iDMRs in CRC has been reported. Furthermore, the relationship between iDMR methylation status and other methylation-related issues, such as CpG island methylator phenotype (CIMP) and long interspersed element-1 (LINE-1) methylation, remains unclear.ResultsWe analyzed the methylation status of 38 iDMRs in 106 CRC patients. We also investigated CIMP, LINE-1 methylation, KRAS and BRAF gene mutations, and loss of imprinting (LOI) of IGF2. We further examined the relationship between these factors and clinicopathological factors. The overall trend in iDMR methylation was towards hypermethylation, and iDMRs could be grouped into three categories: susceptible, resistant, and intermediate-to-aberrant methylation. The susceptible and resistant iDMRs consisted of all types of iDMR (gametic and somatic, maternally and paternally methylated). Hypermethylation of multiple iDMRs (HyMiD)-positive status was statistically associated with CIMP-positive status, but not associated with mutations in the BRAF and KRAS genes. HyMiD-positive status was inversely associated with LINE-1 methylation. Among four iDMRs within the IGF2/H19 domain, IGF2-DMR0 hypomethylation occurred most frequently, but was not associated with IGF2 LOI. Finally, we statistically calculated predictive prognostic scores based on aberrant methylation status of three iDMRs.ConclusionIn CRC tissues, some iDMRs were susceptible to hypermethylation independent of the type of iDMR and genomic sequence. Although HyMiD-positive status was associated with CIMP-positive status, this was independent of the BRAF and KRAS pathways, which are responsible for CIMP. Since IGF2-DMR0 hypomethylation and aberrant methylation of other iDMRs within the IGF2/H19 domain were not associated with IGF2 LOI, dysfunction of any of the molecular components related to imprinting regulation may be involved in IGF2 LOI. The prognostic score calculated based on aberrant methylation of three iDMRs has potential clinical applications as a prognostic predictor in patients. Further study is required to understand the biological significance of, and mechanisms behind, aberrant methylation of iDMRs and IGF2 LOI in CRCs.

Project description:BACKGROUND:DNA methylation is an epigenetic modification that is studied at a single-base resolution with bisulfite treatment followed by high-throughput sequencing. After alignment of the sequence reads to a reference genome, methylation counts are analyzed to determine genomic regions that are differentially methylated between two or more biological conditions. Even though a variety of software packages is available for different aspects of the bioinformatics analysis, they often produce results that are biased or require excessive computational requirements. RESULTS:DMRfinder is a novel computational pipeline that identifies differentially methylated regions efficiently. Following alignment, DMRfinder extracts methylation counts and performs a modified single-linkage clustering of methylation sites into genomic regions. It then compares methylation levels using beta-binomial hierarchical modeling and Wald tests. Among its innovative attributes are the analyses of novel methylation sites and methylation linkage, as well as the simultaneous statistical analysis of multiple sample groups. To demonstrate its efficiency, DMRfinder is benchmarked against other computational approaches using a large published dataset. Contrasting two replicates of the same sample yielded minimal genomic regions with DMRfinder, whereas two alternative software packages reported a substantial number of false positives. Further analyses of biological samples revealed fundamental differences between DMRfinder and another software package, despite the fact that they utilize the same underlying statistical basis. For each step, DMRfinder completed the analysis in a fraction of the time required by other software. CONCLUSIONS:Among the computational approaches for identifying differentially methylated regions from high-throughput bisulfite sequencing datasets, DMRfinder is the first that integrates all the post-alignment steps in a single package. Compared to other software, DMRfinder is extremely efficient and unbiased in this process. DMRfinder is free and open-source software, available on GitHub ( github.com/jsh58/DMRfinder ); it is written in Python and R, and is supported on Linux.

Dataset Information

AIMER: A SNP-independent software for identifying imprinting-like allelic methylated regions from DNA methylome.

Publications

AIMER: A SNP-independent software for identifying imprinting-like allelic methylated regions from DNA methylome.

Similar Datasets

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