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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Analysis of Software Read Cross-Contamination in DNBSEQ Data.

Dmitry N Konanov¹, Vera Y Tereshchuk², Ignat V Sonets^1,3

¹Research Institute for System Biology and Medicine, Moscow 117246, Russia.

|June 26, 2025

Summary

This summary is machine-generated.

DNA nanoball sequencing (DNBSEQ) PE300 kits can yield high data but may cause "software contamination" artifacts. These issues, like improper read pairing, occur when libraries have different insert sizes or loading, impacting genomic and transcriptomic analyses.

Keywords:

DNBSEQ data filtering read duplicates sequencing artifacts

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Area of Science:

Genomics
Next-Generation Sequencing
Bioinformatics

Background:

DNA nanoball sequencing (DNBSEQ) is a rapidly advancing sequencing technology.
New PE300 kits for DNBSEQ-G99 and G400 offer high data yield, suitable for genomic and transcriptomic studies.
Combining diverse DNA libraries in a single run can introduce data artifacts.

Purpose of the Study:

Investigate the causes of "software contamination" artifacts observed in DNBSEQ PE300 runs.
Characterize the nature of these artifacts, including read pairing and demultiplexing errors.
Assess the impact of these artifacts on genomic and transcriptomic data analysis.

Main Methods:

Analysis of DNBSEQ PE300 sequencing data, including MGI demo datasets.
Examination of read pairing, demultiplexing, and chimeric read generation.
Comparison of DNBSEQ data with Illumina sequencing data using NA12878 human exome data.

Main Results:

"Software contamination" artifacts, such as improper read pairing and demultiplexing, were observed in all analyzed DNBSEQ runs.
These artifacts stem from the misinterpretation of signals from neighboring DNA nanoballs, particularly with short insert sequences.
The improper pairing rate in DNBSEQ data is comparable to Illumina, with issues arising from varied insert size distributions or flow cell loading.
Raw DNBSEQ data may contain approximately 2% optical duplicates due to closely spaced DNA nanoballs.

Conclusions:

The artifacts in DNBSEQ PE300 sequencing are primarily caused by signal interference between adjacent DNA nanoballs.
These artifacts significantly affect data quality when sequencing libraries with dissimilar insert size distributions or flow cell loading.
While the improper pairing rate is comparable to Illumina, careful library preparation and data analysis are crucial for accurate genomic and transcriptomic results using DNBSEQ.