Editorial: Towards genome interpretation: Computational methods to model the genotype-phenotype relationship

Daniele Raimondi, Gabriele Orlando, Nora Verplaetse, Piero Fariselli, Yves Moreau

Abstract: Genome Interpretation (GI) is an umbrella term for the scientific efforts oriented towards modelling and understanding the relationship between genotype and phenotype in living organisms [1,2,3]. Even temporarily setting epigenetic and environmental effects aside, untangling the complex relation between the complete set of genetic material of an individual organism (be it a human, other animals, plants, or microorganisms) and its observed phenotypes is an extremely ambitious and challenging endeavor, in particular for non-Mendelian traits. Being able to reliably model this genotype-phenotype relationship could revolutionize many aspects of genetics, biology, and medicine [4,2,5]. For example, it could warn us about late-onset genetic disorders, helping their prevention [6,7]. It could also lead to the design of medications and treatments tailored to each patient's genome, complementing environmental and medical-history data to improve patient prognosis [4,5]. Applied to cancer, it could bring a novel understanding of cancer development, helping devise highly specific cocktails of drugs and discover novel molecules to target each unique tumor [8]. Such personalized approaches to medicine, called Precision Medicine, are still largely out of our reach in many clinical settings [4,2,5].In the last decade, the avalanche of scientific results brought by Next Generation Sequencing (NGS) and big data technologies seemed almost unstoppable, and at times it seemed that finally crack...