Computational genomic analysis of genomic variations in human tissues

Abstract Even though all somatic cells trace their developmental lineages traced back to a single fertilized egg, during the course of development and aging, various mutagenic exposures, DNA replication errors, and imperfect DNA repair lead to accumulation of somatic mutations – resulting in genetic variations among somatic cells in a tissue. While somatic mutations have primarily been investigated in the contexts of phenotypic conditions such as pigmentation patterns, diseases such as cancer, autoimmunity etc, or disease precursors such as field cancerization and clonal hematopoiesis, emerging evidence suggests that somatic mutations in apparently healthy tissues might be more common than previously anticipated, and that clonal makeups of somatic tissues continue to evolve throughout the lifetime. Nonetheless, our understanding of the patterns of ‘normal’ somatic variations in pathologically normal tissues remains limited –in terms of the types of tissues affected, classes of genomic alterations, and their etiologies – in part, due to technological barriers. In particular, many types of genomic alterations in mosaic somatic tissues remain poorly characterized. Recent technological developments have enabled examining complex patterns of genomic alterations and their significance in tissue contexts at unprecedented resolution and high accuracy. Here, utilizing emerging genomic technologies and computational genomics resources, and focusing on organs that have different types of exposure and regeneration abilities, we will ask two related questions: What are the prevalence and patterns of somatic genomic alterations in pathologically normal tissues? To what extent such genomic alterations contribute towards transcriptomic and phenotypic variations at the cellular and tissue-level? This research contributes towards understanding the landscape of somatic variations in pathologically normal tissues in human. Regularity of healthy tissues is taken for granted, which under-appreciates the genetic and non-genetic variations within. Our efforts have potentials to challenge the dogma, that have relevance for development, aging, and many disease types including cancer, immune and neurological disorders. Importantly, it will provide us with a baseline to compare the alterations observed in disease and pre-disease conditions, which would have implications for early detection, disease prevention, and minimizing over-diagnosis. We will also develop computational genomic resources contributing towards reproducible research and community-level resource sharing for advancing our understanding of somatic variations in human tissues.