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Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

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Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

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

Junfang Chen¹, Pavlo Lutsik, Ruslan Akulenko

¹Center for Bioinformatics, Saarland University, Saarbrücken 66123, Germany , Department of Genetics, Saarland University, Saarbrücken 66123, Germany.

Journal of Bioinformatics and Computational Biology

|January 3, 2015

Summary

This summary is machine-generated.

Whole-genome bisulfite sequencing (WGBS) can be costly. Our new tool, AKSmooth, accurately reconstructs DNA methylation profiles from low-coverage data, reducing costs for researchers studying the human colon methylome.

Keywords:

DNA methylation read coverage whole-genome bisulfite sequencing

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Area of Science:

Genomics
Epigenetics
Bioinformatics

Background:

Whole-genome bisulfite sequencing (WGBS) is crucial for comprehensive DNA methylation profiling.
High sequencing costs due to coverage requirements limit WGBS accessibility.
Bioinformatics tools can mitigate costs by enhancing low-coverage data quality.

Purpose of the Study:

To develop a statistical method for accurate methylome reconstruction from low-coverage bisulfite sequencing (Bi-Seq) data.
To reduce the cost burden associated with obtaining high-coverage WGBS data.
To provide an efficient tool for estimating single CpG methylation across the entire methylome.

Main Methods:

Developed AKSmooth (Ajusted Local Kernel Smoother), a statistical method for methylome reconstruction.
Applied AKSmooth to low-coverage (~4x) WGBS data from human colon cancer samples and controls.
Benchmarked AKSmooth performance against a gold standard high-coverage sample and a reference tool.

Main Results:

AKSmooth accurately reconstructs single CpG methylation estimates from low-coverage Bi-Seq data.
AKSmooth-curated data showed high concordance (Pearson 0.90) with high-coverage data.
AKSmooth demonstrated superior computational efficiency, with a runtime over 4.5 times faster than the reference tool.

Conclusions:

AKSmooth is a simple, efficient, and accurate tool for human colon methylome estimation from low-coverage WGBS data.
The method significantly reduces the cost of obtaining comprehensive DNA methylation profiles.
AKSmooth is implemented in R and publicly available.