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Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
Daniel Aird1, Michael G Ross, Wei-Sheng Chen
1Genome Sequencing and Analysis Program, Broad Institute of MIT and Harvard, 320 Charles Street, Cambridge, MA 02141, USA.
Genome Biology
|February 23, 2011
Summary
Illumina sequencing often misses DNA regions with extreme GC content. This study identifies PCR amplification during library prep as a key bias source, with optimized conditions significantly reducing this issue.
Area of Science:
- Genomics
- Molecular Biology
- Biotechnology
Background:
- High-throughput sequencing technologies like Illumina generate vast amounts of data.
- Genomic regions with extreme GC content (very high or very low) are frequently under-represented or absent in sequencing datasets.
- This bias complicates comprehensive genomic analysis and understanding of genome structure.
Purpose of the Study:
- To investigate the sources of base-composition bias in Illumina sequencing data.
- To identify specific steps in the sequencing workflow contributing to this bias.
- To develop and validate an optimized protocol for reducing base-composition bias.
Main Methods:
- Genomic DNA sequences with GC content ranging from 6% to 90% were analyzed.
- Quantitative PCR (qPCR) was employed to trace the representation of these sequences throughout the library preparation process.
- PCR conditions were systematically optimized to mitigate observed biases.
Main Results:
- Polymerase Chain Reaction (PCR) during library preparation was identified as a primary source of base-composition bias.
- Optimization of PCR conditions led to a significant reduction in amplification bias.
- The improved protocol minimized the impact of PCR instrument variability and temperature ramp rate on sequence representation.
Conclusions:
- Base-composition bias in Illumina sequencing is significantly influenced by PCR amplification steps.
- Optimized PCR protocols can effectively reduce bias associated with extreme GC content.
- This work provides a method to improve the accuracy and completeness of genomic data generated by high-throughput sequencing.
