Reimagining the Central Dogma

Summary

The identification of single gene alterations with large phenotypic effects elegantly explains many previously baffling phenomena: from the complex cellular choreography of embryonic development to particular disease predispositions. This, in addition to successful selective breeding of domestic plants and animals, has led to the idea (dogma) that many and perhaps most characteristics are largely genetically predetermined. However, most traits in human populations - from complex behavioral traits to simple and measurable characteristics such as height – have proven difficult to associate with small numbers of specific genes. It seems that most traits are determined by a multitude of genes, each with minuscule (sometimes indirect) effects, by interactions amongst specific gene alleles (epistasis), and/or by gene and environment interactions. Has the power of genetics to explain many phenomena caused us to overlook, miss, or ignore non-genetic mechanisms that would explain currently mysterious biological phenomena?

Given the technical complexity, costs, and ethical issues surrounding gene editing in humans, in which cases would it make more sense to identify environmental interventions to ameliorate deficiencies and/or improve outcomes for more people? In all organisms, are there understudied non-genetic mechanisms (cytoplasmic, mechanical, electrical, other?) that would explain currently mysterious biological phenomena? What are the blindspots in our current approaches to disentangling the relationship between genotype and phenotype? When it comes to the manner that genetic and genomic research is carried out, how do we know that we are asking the right questions? How would we know if we were doing it wrong?

We will assemble 7-10 of the top interdisciplinary scholars working in genetics, systems biology, and evolutionary biology to address the genotype to phenotype mapping problem. Our aim will be to envision the post-genome-sequencing era in order to launch a new field and to highlight the limitations of the current approach of accumulating ever more genome sequences while ignoring questions that such data have failed to answer.