From Bottleneck to Breakthrough Bias-Free Library Preparation for High-Throughput Genomics Cores

Presented at ESHG 2026

High‑throughput genomics cores are under pressure to move more samples, faster—without sacrificing data quality or fairness across users. In this ESHG 2026 presentation, SciLifeLab’s Anja Mezger shares how her team partnered with n6 to replace fixed‑cycle PCR with iconPCR™ and AutoNorm™ adaptive amplification, turning normalization from a tedious bottleneck into an automated, bias‑free step built directly into their amplicon workflows. She walks through benchmarking data from 16S sequencing projects spanning 150,000 samples a year, showing how per‑well adaptive control delivers uniform libraries from highly variable inputs, reduces hands‑on time and plastic waste, and gives core facilities the confidence to accept non‑normalized plates at scale.

What You'll Learn

• Why fixed‑cycle PCR is a hidden bottleneck in high‑throughput cores, driving over‑ and under‑amplification, dropouts, and unfair variability between user projects—even when inputs are “pre‑normalized.”
• How iconPCR with AutoNorm technology independently controls amplification in every well, stopping each library at its sample‑specific optimum rather than a guessed cycle number.
• How SciLifeLab’s Genomics Applications Unit re‑engineered their 16S amplicon workflows to accept non‑normalized input plates, pool libraries by volume, and eliminate individual well‑by‑well QC and manual normalization.
• Quantitative results from benchmarking linear and logarithmic microbial standards spiked with human background DNA, and how adaptive amplification preserved taxonomic profiles while tightening replicate variability.
• The impact on core operations: reduced hands‑on time and tip usage, simpler training for new staff, and a more sustainable pipeline that keeps up with 150,000‑sample annual volumes.
• How the same approach can extend beyond 16S into 18S, Visium spatial, single‑cell, ATAC‑seq, and other PCR‑based library preps—without changing your preferred chemistries or sequencing platforms.