Accuracy improvements in crop genome assembly using the Q20+ chemistry
About Alexander Wittenberg
Alexander graduated with an M.Sc. in plant breeding and crop protection at the Wageningen University and completed his Ph.D. at the Laboratory of Plant Breeding. In 2007, he joined KeyGene as a scientist, where he initially worked on the development and application of new molecular marker methods. Alexander has gained considerable experience in the field of next-generation sequencing, with expertise on a wide range of platforms and applications. Currently, he is responsible for scouting new technologies and is involved in the development of innovative sequence-based technologies in KeyGene’s Genome Insights crop innovation platform. In addition to his focus on innovation, he works closely with R&D and business development departments to translate these technologies to the market for KeyGene’s clients.
KeyGene is the technology innovation engine for crop improvement. Within KeyGene’s Genome Insights platform, cutting edge technologies are evaluated, developed, and applied that deliver a comprehensive genomic and genetic understanding of crops. High-quality, contiguous reference genomes are essential for effective marker development and gene discovery, comparative genomics analyses, dissecting the genetic architecture of important traits, and broadening trait discovery approaches beyond SNP-based analysis. Oxford Nanopore sequencing already provides highly contiguous, chromosome-level de novo reference genomes, in some cases stretching out from telomere-to-telomere. Increasing consensus accuracy has been relying on polishing using short reads, but omitting this step is highly desired, especially in heterozygous and/or polyploid species. Significant improvements at the level of raw, as well as consensus, accuracy have been made over the years and, in that respect, we have evaluated the Oxford Nanopore R10.3 and R10.4 pore types in combination with the Q20+ chemistry in a range of crop species. We have also evaluated the impact of a plant trained basecalling model on the raw and consensus accuracies of these species. I’ll provide an overview of the latest results and ongoing developments.