Nanopore Sequencing: Bioinformatics Analysis of ONT DataPosted by kiko on November 29th, 2023 Oxford Nanopore Technologies (ONT) sequencing has witnessed significant progress in recent years, becoming a key player in the genomics field. As the technology matures, so does the bioinformatics analysis of ONT data. Researchers have been diligently developing specialized tools and algorithms to better utilize the unique characteristics of ONT data, such as long read lengths and ionic current signals. This article explores the latest bioinformatics advancements that enable enhanced base calling, base modification detection, error correction, assembly, and alignment of ONT data. Data Analysis Pipeline for ONT Sequencing The bioinformatics analysis of ONT data typically involves a multi-step pipeline to transform raw electrical signals into meaningful genomic information. The pipeline includes base calling, error correction, alignment, variant calling, and additional steps for specialized analyses, such as detecting modifications and assessing transcriptome complexity. Base Calling and Base Modification Detection Base calling is a fundamental step in ONT data analysis, converting the raw ionic current signals into DNA base sequences. Early versions of base callers had relatively high error rates, hindering downstream analyses. However, with continuous improvements, modern base callers, such as Guppy and Chiron, have significantly enhanced accuracy and now offer real-time base calling capabilities. Furthermore, ONT technology is uniquely suited to detect epigenetic modifications, such as DNA methylation. Specialized algorithms, including Tombo and DeepSignal, have been developed to identify base modifications by analyzing specific changes in the ionic current signal associated with modified bases. This epigenetic information is crucial for understanding gene regulation and other biological processes. Detecting DNA and RNA Modifications in ONT Sequencing One of the key advantages of Oxford Nanopore Technologies (ONT) sequencing is its ability to directly detect DNA and RNA modifications. By distinguishing the unique current shifts caused by modified bases from those of unmodified bases, ONT sequencing offers insights into epigenetic modifications and post-transcriptional RNA modifications. In this section, we explore the methodologies and tools developed for the detection of DNA and RNA modifications using ONT sequencing data. CD Genomics offers Epigenetics and Methylation Analysis Using Long-Read Sequencing for both DNA and RNA modifications. DNA Modification Detection ONT sequencing enables the direct detection of certain DNA modifications, such as 5-methylcytosine (5mC), 6-methyladenine (6mA), and N4-methylcytosine (4mC), at different levels of resolution, ranging from bulk-level detection to the single-molecule level. Several tools have been developed to identify DNA modifications from ONT data:
RNA Modification Detection Detecting RNA modifications directly using ONT sequencing has also shown promise, although the resolution varies, and single-nucleotide resolution at the single-molecule level is yet to be demonstrated. In the past, PacBio sequencing was used to detect N6-methyladenosine (m6A) modifications in RNA molecules. More recently, ONT direct RNA sequencing has generated robust data of reasonable quality, paving the way for the detection of RNA modifications. Several pilot studies have successfully detected bulk-level RNA modifications using various methodologies:
Although these pilot studies have detected bulk-level RNA modifications, achieving single-nucleotide resolution at the single-molecule level remains a challenge. Like it? Share it! More by this author |