Uncovering codon usage patterns during murine embryogenesis and tissue-specific developmental diseases

Sarah E Fumagalli¹Sean Smith²Brian Lin¹Rahul Paul²Collin Campbell²Luis Santana-Quintero²Anton Golikov²Juan Ibla³Haim Bar⁴Anton A Komar^5,6Ryan C Hunt⁷Michael Dicuccio⁸Chava Kimchi-Sarfaty^1*

• ¹Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research (CBER), United States Food and Drug Administration, Silver Spring, United States
• ²High-performance Integrated Virtual Environment (HIVE), Office of Biostatistics and Pharmacovigilance (OBPV), Center for Biologics Evaluation and Research (CBER), United States Food and Drug Administration, Silver Spring, United States
• ³Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, United States
• ⁴Department of Statistics, University of Connecticut, Storrs, CT, United States
• ⁵Center for Gene Regulation in Health and Disease, Department of Biological, Geological and Environmental Sciences, Cleveland State University, Cleveland, Georgia, United States
• ⁶Department of Biochemistry and Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH, United States
• ⁷Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies (OTAT), Center for Biologics Evaluation & Research, US Food and Drug Administration, Silver Spring, Maryland, United States
• ⁸Not Applicable, Rockville, MD, United States

Mouse models share significant genetic similarities with humans and have expanded our understanding of how embryonic tissue-specific genes influence disease states. By improved analyses of temporal, transcriptional data from these models, we can capture unique tissue codon usage patterns and determine how deviations from these patterns can influence developmental disorders. We analyzed transcriptomic-weighted data from four mouse strains across three different germ layer tissues (liver, heart, and eye) and through embryonic stages. Applying a multifaceted approach, we calculated relative synonymous codon usage, reduced the dimensionality, and employed machine learning clustering techniques. These techniques identified relative synonymous codon usage differences/similarities among strains and deviations in codon usage patterns between healthy and disease-linked genes. Original transcriptomic mouse data and RefSeq gene sequences can be found at the associated Mouse Embryo CoCoPUTs (codon and codon pair usage tables) website. Future studies can leverage this resource to uncover further insights into the dynamics of embryonic development and the corresponding codon usage biases that are paramount to understanding disease processes of embryologic origin.