A recent study from the Gencove and Element Biosciences teams has demonstrated the efficacy of low-pass sequencing plus imputation using avidity sequencing compared to sequencing by synthesis. Here's a breakdown of our findings:
Low-pass whole-genome sequencing (lpWGS) followed by imputation has emerged as a cost-effective genotyping method. Traditional short-read sequencing relies on sequencing by synthesis (SBS). The study introduces a newer methodology, avidity sequencing, which promises comparable accuracy to SBS while reducing data duplication, and evaluates its performance in the context of imputation.
Avidity sequencing involves a unique process where linear library molecules are circularized, captured on a flow cell, and amplified. The crucial difference from SBS is the decoupling of stepping along the DNA template from nucleotide identification, allowing for independent optimization and reduced reagent consumption. This method uses dye-labeled polymers (avidites) for base identification, resulting in highly specific multivalent binding and significantly reducing the concentration of reporting nucleotides.
The study compared lpWGS from the Element AVITI system (using avidity sequencing) and the Illumina NovaSeq 6000 (using SBS) on the same set of biological samples. The results showed dramatically lower optical duplication rates in avidity sequencing, leading to higher effective coverage with a fixed number of sequenced bases. Notably, the imputation accuracy across different genetic ancestries was comparable between the two sequencing methods.
Implications and Efficiency
The reduced duplication rate in avidity sequencing translates into a more uniform genome-wide sequencing coverage, crucial for accurate genotyping. This efficiency is especially relevant for large-scale genetic studies where cost and accuracy are paramount. Avidity sequencing, therefore, stands as a viable alternative to SBS, particularly for applications involving lpWGS followed by imputation.
Avidity sequencing not only provides a cost-effective alternative to traditional SBS but also improves data quality by reducing duplication rates. Lower duplication rates may be most relevant for ultralow (e.g., < 0.1x) coverage applications, where “every read counts.” For instance, in large-scale agricultural applications where hundreds of thousands of individuals are genotyped every year and where sequencing costs represent a nontrivial proportion of the total cost of a genomic prediction program. You can read the full study in G3 here.