PROJECT SUMMARY/ABSTRACT The genome is a critical factor in our health. However, the cost and performance of current sequencing technologies are limiting genomics from realizing its full potential in healthcare, including monitoring of cancer development and recurrence. The goal of the project is to develop a revolutionary sequencing platform that is superior to existing technologies across a range of metrics. Rather than reading one base or letter at a time, the proposed technology reads short segments of sequence or “words”, by measuring the kinetics of short oligonucleotide probe binding to their complementary sequence in the target using super-resolution fluorescence imaging. Each nucleotide is read multiple times during sequencing. Super-resolution imaging enables the sequencing of a high molecular density of targets. Advanced statistical and machine learning algorithms are used for image processing, base calling and sequence assembly. Once developed, this platform will surpass existing sequencing technology by one or more orders of magnitude in factors including accuracy and sequencing cost. XGenomes’ prior work has validated the fundamental approach. This Phase I project will develop a full-stack proof-of-concept through three specific aims. In Aim 1, we will apply our experience to expand the probe set to the 96 we will require for demonstrating sequencing in Aim 3. In Aim 2, the bioinformatics pipeline will be fully implemented and our prototype fluidics platform will be scaled up to deliver and image 96 probes. Finally, in Aim 3 we will construct the synthetic test targets and demonstrate Q50 sequencing of targeted variants of a clinically relevant loci. The successful completion of these aims will prove the technology works and position XGenomes to scale up to the complete platform.