On May 21st, Prof. Alberto Magi represented the COMBINE Lab at London Calling 2026, the major annual international conference hosted by Oxford Nanopore Technologies, delivering a presentation titled "Third-generation homozygosity analysis."
Runs of homozygosity (ROH) are extended chromosomal regions of consecutive homozygous genotypes arising from demographic history, parental relatedness, or mitotic recombination events. Detecting ROHs is critical in medical genetics, as these regions frequently harbor highly penetrant recessive variants responsible for Mendelian diseases. Traditionally, ROH analysis has relied heavily on standard SNP-array technologies.
To bridge the analytical gap in long-read sequencing data, our group developed a novel computational framework based on the H3M2 algorithm. Operating on a hidden Markov model (HMM) that measures genomic distances between consecutive SNPs, this pipeline enables precise ROH identification across a broad range of genomic scales using both low- and high-coverage nanopore datasets.
During his talk, Prof. Magi presented the evaluation of H3M2 on high-coverage (30x) and low-coverage (2x) nanopore datasets. The results demonstrate that the pipeline achieves an ROH detection resolution fully comparable to that of traditional SNP arrays. Remarkably, even when applied to ultra-low-coverage data, H3M2 maintains array-equivalent resolution.
These findings establish that our new framework successfully addresses a crucial challenge in long-read genomics. Furthermore, when combined with the native ability of low-coverage nanopore sequencing to accurately profile high-resolution copy number variations (CNVs), these results indicate that low-coverage nanopore sequencing can completely replace current SNP- and CGH-array technologies within a single, unified workflow.
Watch the Presentation
The full recording of Prof. Magi's presentation at London Calling is available online. You can watch his talk and explore the technical discussion on the official event platform.