Biomodal, an omics-based life sciences technology company, has announced that its duet multiomic solutions are now compatible with Element Biosciences' AVITI24 5D multiomics and AVITI sequencing instruments. The integration, validated at the University of Minnesota Genomics Center, aims to enhance sensitivity for cancer, ageing and neurodegenerative disease research. The collaboration combines biomodal's 5-base and 6-base sequencing solutions with Element's sequencing systems, enabling complete methylation detection and delivering actionable insights within a single streamlined process. AVITI users gain access to biomodal's software pipeline, creating an end-to-end workflow for next-generation sequencing. Biomodal's platform-agnostic technology integrates pre-sequencing workflow with post-sequencing informatics to generate genetic and epigenetic data from a single sample in one run.

CAMBRIDGE, England--(BUSINESS WIRE)--biomodal, an omics-based life sciences technology and analytics company, today announced it is delivering the 6-base genome to customers with the launch of duet multiomics solution evoC (duet evoC). The combinatorial genetic and epigenetic technology provides single-base-resolution sequencing data that reveals standard four-base sequencing (A, G, C, and T), and distinguishes between 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), on the same DNA molecule. This added resolution will allow greater power in detecting disease associations, identifying novel biomarkers, developing disease classifiers, and monitoring the progression of disease; even with limited samples such as cell-free DNA (cfDNA). The advanced 6-base genome data enables the exploration of epigenetic mechanisms of gene regulation through methylation and hydroxymethylation. Researchers now are able to obtain an accurate measurement of 5mC and 5hmC, integrated into local genetic context, with 95% of bases above Q30 and 50% with accuracy above Q40. By measuring multiple modes of biology from a single low-input DNA sample in a single experiment, researchers can use the comprehensive data to build predictive models of gene expression, chromatin accessibility, and enhancer status to better understand the biological mechanisms that link genotype to phenotype