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Abstract Cancer is a disease of multicellularity, observed across the tree of life. In principle, animals with larger body sizes and longer lifespans should be at increased risk of developing cancer. However, there is no strong relationship between these traits and cancer across mammals. Previous studies have proposed that increased copy number of cancer-related genes may enhance the robustness of cancer suppression pathways in long-lived mammals, but these studies have not extended beyond known cancer-related genes. In this study, we conducted a phylogenetic generalized least squares analysis to test for associations between copy number of all protein-coding genes and longevity, body size, and cancer prevalence across 94 species of mammals. In addition to investigating the copy number of individual genes, we tested sets of related genes for a relationship between the aggregated gene copy number of the set and these traits. We did not find strong evidence to support the hypothesis that adaptive changes in gene copy number contribute to the lack of correlation between cancer prevalence and body size or lifespan. However, we found several biological processes where aggregate copy number was associated with malignancy rate. The strongest association was for the gene set relating to transforming growth factor beta, a cytokine that plays a role in cancer progression. Overall, this study provides a comprehensive evaluation of the role of gene copy number in adaptation to body size and lifespan and sheds light on the contribution of gene copy number to variation in cancer prevalence across mammals. 

Abstract Global sequencing of genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to reveal new genetic variants that are the key to unraveling its early evolutionary history and tracking its global spread over time. Here we present the heretofore cryptic mutational history and spatiotemporal dynamics of SARS-CoV-2 from an analysis of thousands of high-quality genomes. We report the likely most recent common ancestor of SARS-CoV-2, reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient. This progenitor genome differs from genomes of the first coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the United States harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide months before and after the first reported cases of COVID-19 in China. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains that have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic in 2020. There have been multiple replacements of predominant coronavirus strains in Europe and Asia as well as continued presence of multiple high-frequency strains in Asia and North America. We have developed a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).