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Related Experiment Video

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Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution
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A comprehensive evaluation of alignment software for reduced representation bisulfite sequencing data.

Xiwei Sun1, Yi Han1, Liyuan Zhou1

  • 1Department of Respiratory Medicine, Sir Run Run Shaw Hospital and Institute of Translational Medicine.

Bioinformatics (Oxford, England)
|March 27, 2018
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Summary

Evaluating methylation analysis software for reduced representation bisulfite sequencing (RRBS) is crucial. This study introduces RRBSsim, a simulator that identifies challenges in aligning DNA methylation data, especially for CpG sites near CpG islands.

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Area of Science:

  • Genomics
  • Epigenetics
  • Bioinformatics

Background:

  • Next-generation sequencing enables genome-wide DNA methylation studies at single-base resolution.
  • Aligning bisulfite-converted sequencing reads is challenging due to unmethylated cytosine depletion.
  • Comprehensive evaluation of methylation read alignment tools, particularly for reduced representation bisulfite sequencing (RRBS) targeting CpG islands (CGIs), is lacking.

Purpose of the Study:

  • To develop and utilize a simulator, RRBSsim, for benchmarking RRBS data analysis.
  • To compare the performance of seven mapping algorithms for methylation analysis using both real and simulated RRBS data.
  • To identify specific CpG sites and genomic regions where methylation analysis tools exhibit inconsistencies.

Main Methods:

  • Developed RRBSsim, a specialized simulator for RRBS data benchmarking.
  • Performed extensive comparisons of seven mapping algorithms on real RRBS data from lung tumors and matched adjacent tissues.
  • Validated findings using simulated RRBS data to assess recall and precision for vulnerable CpG sites.

Main Results:

  • Methylation results showed inconsistencies between software tools for CpG sites with low sequencing depth, medium methylation levels, or located on CGI shores or gene bodies.
  • Simulations confirmed lower recall and precision for detecting and estimating methylation levels at these vulnerable CpG sites.
  • bwa-meth and BS-Seeker2 (bowtie2) were identified as preferred aligners for RRBS data based on recall, precision, and speed.

Conclusions:

  • Existing aligners struggle with moderately methylated CpG sites and those on CGI shores or gene bodies, necessitating cautious interpretation of methylation results from these regions.
  • The study highlights inherent features of methylation data and provides guidance for advancing sequence-based methylation data analysis.
  • RRBSsim serves as a valuable tool for methodological development and benchmarking in RRBS data analysis.