The study investigates PCR amplification bias in Illumina sequencing libraries and proposes an optimized protocol to reduce it. Researchers traced genomic sequences with varying GC content through the library preparation process using quantitative PCR (qPCR) and identified PCR as the main source of bias. They optimized PCR conditions, including thermocycling protocols, enzyme selection, and chemical modifications, to minimize GC bias. The optimized protocol significantly reduced amplification bias and minimized the effects of PCR instrument and temperature ramp rate. The study found that PCR amplification during library preparation introduced significant bias, particularly affecting GC-rich and AT-rich regions. By adjusting denaturation times, using betaine, and modifying thermocycling protocols, the researchers improved the evenness of amplification across a wide range of GC compositions. The optimized protocol produced libraries with more uniform coverage, reducing the underrepresentation of GC-rich and AT-rich regions. The study also compared PCR-amplified and PCR-free libraries, finding that PCR-free libraries had better coverage for AT-rich regions but were less effective for GC-rich regions. However, the optimized PCR protocol provided a better balance between GC-rich and AT-rich regions. The results showed that the optimized protocol significantly improved the representation of GC-rich and AT-rich regions in the human genome, particularly for genes with GC-rich promoter regions. The study concludes that optimizing PCR conditions is crucial for reducing amplification bias in Illumina sequencing libraries. The optimized protocol is more robust and effective than the standard protocol, providing more even coverage across a wide range of GC compositions. The findings suggest that optimizing PCR conditions is essential for improving the accuracy and completeness of Illumina sequencing data, particularly for regions with extreme base compositions.The study investigates PCR amplification bias in Illumina sequencing libraries and proposes an optimized protocol to reduce it. Researchers traced genomic sequences with varying GC content through the library preparation process using quantitative PCR (qPCR) and identified PCR as the main source of bias. They optimized PCR conditions, including thermocycling protocols, enzyme selection, and chemical modifications, to minimize GC bias. The optimized protocol significantly reduced amplification bias and minimized the effects of PCR instrument and temperature ramp rate. The study found that PCR amplification during library preparation introduced significant bias, particularly affecting GC-rich and AT-rich regions. By adjusting denaturation times, using betaine, and modifying thermocycling protocols, the researchers improved the evenness of amplification across a wide range of GC compositions. The optimized protocol produced libraries with more uniform coverage, reducing the underrepresentation of GC-rich and AT-rich regions. The study also compared PCR-amplified and PCR-free libraries, finding that PCR-free libraries had better coverage for AT-rich regions but were less effective for GC-rich regions. However, the optimized PCR protocol provided a better balance between GC-rich and AT-rich regions. The results showed that the optimized protocol significantly improved the representation of GC-rich and AT-rich regions in the human genome, particularly for genes with GC-rich promoter regions. The study concludes that optimizing PCR conditions is crucial for reducing amplification bias in Illumina sequencing libraries. The optimized protocol is more robust and effective than the standard protocol, providing more even coverage across a wide range of GC compositions. The findings suggest that optimizing PCR conditions is essential for improving the accuracy and completeness of Illumina sequencing data, particularly for regions with extreme base compositions.