Dataset Information

Use of Combined MSAP and NGS Techniques to Identify Differentially Methylated Regions in Somaclones: A Case Study of Two Stable Somatic Wheat Mutants.

ABSTRACT: The appearance of somaclonal variability induced by in vitro cultivation is relatively frequent and can, in some cases, provide a valuable source of new genetic variation for crop improvement. The cause of this phenomenon remains unknown; however, there are a number of reports suggesting that epigenetics, including DNA methylations, are an important factor. In addition to the non-heritable DNA methylation changes caused by transient and reversible stress-responsive gene regulation, recent evidence supports the existence of mitotically and meiotically inherited changes. The induction of phenotypes via stable DNA methylation changes has occasionally great economical value; however, very little is known about the genetic or molecular basis of these phenotypes. We used a novel approach consisting of a standard MSAP analysis followed by deep amplicon sequencing to better understand this phenomenon. Our models included two wheat genotypes, and their somaclones induced using in vitro cultivation with a changed heritable phenotype (shortened stem height and silenced high molecular weight glutenin). Using this novel procedure, we obtained information on the dissimilarity of DNA methylation landscapes between the standard cultivar and its respective somaclones, and we extracted the sequences and genome regions that were differentially methylated between subjects. Transposable elements were identified as the most likely factor for producing changes in somaclone properties. In summary, the novel approach of combining MSAP and NGS is relatively easy and widely applicable, which is a rather unique feature compared with the currently available techniques in the epigenetics field.

SUBMITTER: Baranek M

PROVIDER: S-EPMC5085084 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Use of Combined MSAP and NGS Techniques to Identify Differentially Methylated Regions in Somaclones: A Case Study of Two Stable Somatic Wheat Mutants.

Baránek Miroslav M Čechová Jana J Kovacs Tamas T Eichmeier Aleš A Wang Shunli S Raddová Jana J Nečas Tomáš T Ye Xingguo X

PloS one 20161028 10

The appearance of somaclonal variability induced by in vitro cultivation is relatively frequent and can, in some cases, provide a valuable source of new genetic variation for crop improvement. The cause of this phenomenon remains unknown; however, there are a number of reports suggesting that epigenetics, including DNA methylations, are an important factor. In addition to the non-heritable DNA methylation changes caused by transient and reversible stress-responsive gene regulation, recent eviden ...[more]

PMID: 27792769

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Project description:BackgroundGrowing evidence shows that epigenetic modifications play a role in Alzheimer's disease (AD). We performed an epigenome-wide association study (EWAS) to evaluate the DNA methylation differences using postmortem superior temporal gyrus (STG) and inferior frontal gyrus (IFG) samples.ResultsSamples from 72 AD patients and 62 age-matched cognitively normal controls were assayed using Illumina© Infinium MethylationEPIC BeadChip. Five and 14 differentially methylated positions (DMPs) associated with pathology (i.e., Braak stage) with p value less than Bonferroni correction threshold of 6.79 × 10-8 in the STG and IFG were identified, respectively. These cytosine-phosphate-guanine (CpG) sites included promoter associated cg26263477 annotated to ABCA7 in the STG (p = 1.21 × 10-11), and cg14058329 annotated to the HOXA5/HOXA3/HOXA-AS3 gene cluster (p = 1.62 × 10-9) and cg09448088 (p = 3.95 × 10-9) annotated to MCF2L in the IFG. These genes were previously reported to harbor DMPs and/or differentially methylated regions (DMRs). Previously reported DMPs annotated to RMGA, GNG7, HOXA3, GPR56, SPG7, PCNT, RP11-961A15.1, MCF2L, RHBDF2, ANK1, PCNT, TPRG1, and RASGEF1C were replicated (p < 0.0001). One hundred twenty-one and 173 DMRs associated with pathology in the STG and IFG, respectively, were additionally identified. Of these, DMRs annotated to 30 unique genes were also identified as significant DMRs in the same brain region in a recent meta-analysis, while additional DMRs annotated to 12 genes were reported as DMRs in a different brain region or in a cross-cortex meta-analysis. The significant DMRs were enriched in promoters, CpG islands, and exons in the genome. Gene set enrichment analysis of DMPs and DMRs showed that gene sets involved in neuroinflammation (e.g., microglia differentiation), neurogenesis, and cognition were enriched (false discovery rate (FDR) < 0.05).ConclusionsTwenty-two DMPs and 30 DMRs associated with pathology were replicated, and novel DMPs and DMRs were discovered.

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

Use of Combined MSAP and NGS Techniques to Identify Differentially Methylated Regions in Somaclones: A Case Study of Two Stable Somatic Wheat Mutants.

Publications

Use of Combined MSAP and NGS Techniques to Identify Differentially Methylated Regions in Somaclones: A Case Study of Two Stable Somatic Wheat Mutants.

Similar Datasets

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