Revealing the Genome's Hidden Signals

Throughout scientific history many discoveries involved luck. Scientists stumbled upon something important while engaged in blue skies research. Alexander Fleming observed an accidental mold contamination on a Petri dish killed surrounding bacteria. This led to his discovery of penicillin

However, discoveries do not immediately enable commercialization that benefits others. It was almost 15 years after penicillin was discovered before it was manufactured at scale

Even important discoveries have to compete with other ideas for recognition and acceptance. The frontier of scientific literature is written at an 18th grade level or above. Few have time to read and understand even a fraction of it. Scientists themselves may not even be aware of the significance of their discoveries. They operate at the edge of knowledge and even great discoveries contain uncertainty, misinterpretations and errors. Science is also plagued by findings that are correlation, not causation. There are over five million scientific publications per year to wade through, growing at an exponential rate

Barbara McClintock discovered "jumping genes", now known as retrotransposons, by looking at maize corn cells under a microscope. She looked at DNA and she saw it copy and paste parts from one place to another. It was decades before this was observed again by scientists. We now know, 75 years later, that retrotransposons are virus-like elements that also exist inside our genomes and can wake up under stress or in diseased cells

As the technology to sequence DNA gets cheaper, we can now see retrotransposons at an ever greater resolution. Every jump in scale is revealing how important they are in shaping the genome, throughout evolution and in disease

At L1 Therapeutics we are planning to sequence the genomes of diseased tissue at the resolution of a single cell. We're going to follow McClintock's path at a scale many orders of magnitude greater than she could. This matters because it enables us to prioritize diseases and match them to different therapeutic approaches depending on how retrotransposons are being activated. This is a core differentiator of our strategy

Even with today's technology, the mutations retrotransposons cause are one of the hardest things to detect in our genomes. Genomic data is massive and requires cloud computing, data engineering, bioinformatics & AI-driven algorithmic optimizations

Previously, scientists were stumbling in the dark. This still generated amazing discoveries, but also noise, and missed opportunities. Our genomes go to great lengths to suppress retrotransposons. They are both fundamental and targetable. There are diseases with a high unmet need where retrotransposons are activating and causally contributing to disease. We plan to generate the data necessary to determine who will benefit therapeutically from targeting them