CiFi is a community-developed method enabling chromosome-scale haplotype-resolved genome assemblies from a single sequencing run
Sequencing technology developer PacBio and UC Davis researchers have introduced CiFi, a community-developed method enabling chromosome-scale haplotype-resolved genome assemblies from a single sequencing run, even when the sample material is limited.
“We developed CiFi to make high-accuracy, multi-contact chromatin capture accessible to researchers working with limited or challenging samples,” said associate professor at UC Davis Dr Megan Dennis. “By combining 3C with HiFi sequencing, we can resolve chromatin architecture across complex genomic regions and generate chromosome-scale assemblies with greater confidence and far less input.”
CiFi is a new method that addresses the limitations of short-read Hi-C by generating long and accurate reads that capture multiple chromatin interactions within a single molecule.
By integrating chromatin conformation capture (3C) with PacBio HiFi long-read sequencing, CiFi multi-contact reads and longer fragments that increase the information content of proximity ligation experiments in a single Revio sequencing run.
“CiFi expands our multiomics capabilities, increasing what we can do on HiFi sequencing systems without new hardware and unlocking new customer use cases,” said PacBio VP of global marketing David Miller. “The work from the Megan Dennis Lab at UC Davis shows what becomes possible when innovative chromatin capture methods are paired with the accuracy of HiFi sequencing.”
Traditional Hi-C approaches usually only capture two interacting genomic fragments per read pair and often struggle in repetitive or structurally complex regions. CiFi overcomes these limitations by producing long, concatemeric HiFi reads that can contain many interacting chromatin fragments, increasing contact density while maintaining the accuracy of PacBio HiFi sequencing.
When paired with Revio SPRQ chemistry, CiFi makes it possible to generate reference-quality assemblies using fewer cells, fewer libraries, and fewer sequencing runs. This lowers barriers for genome projects that have been limited by cost, complexity, or sample availability.
The method is particularly suitable for the needs of genome biology, biodiversity studies and functional genomics, offering improved mapping in repetitive regions, removed obstacles around low input performance and multi-contact resolution.
