Beyond the Gene

In an earlier post, I argued that the gene concept is in bad need of a makeover.  It turns out that Evelyn Fox Keller and David Harel feel the same way and have made an actual start of it in a paper titled Beyond the Gene.  In the paper they propose a new lexicon:

  • dene – “Like the gene, our notion of dene is intended to capture the essence of genetic transmission, but, rather than being confined to denoting a discrete chunk of DNA, it is far richer and more expressive.”
  • bene – “As with denes, our notion of bene will also be extremely rich, making it possible to express complex modal and temporal characteristics of the organism’s behavior over time, characteristics that go far beyond simple statements about, e.g., protein synthesis or transcription.”
  • genitor (aka genetic functor) – “…a genitor relates a particular dene to a particular bene, stating that whenever the organism’s DNA is seen to satisfy the property expressed by the dene, it’s behavior satisfies the property expressed by the bene.”  And later, “…A genitor, with its dene and bene, connects the static with the dynamic. It carries no expectation that its truth can be predicted on the basis of purely structural information.”

Putting this together,

…[a] genitor, G is defined as a triple G = (O, D, B), which groups together the organism O with a dene D and a bene B. The former is a statement about O’s DNA and the latter is a statement about O’s behavior.  …semantically, the dene D is a truth-valued function of O’s DNA sequence and the bene B is a truth valued function of O’s temporal life-span. Thus, a dene can be viewed as relating to a snapshot, taken with a still camera, of the organism’s most profound inherited artifact, and B can be viewed as relating to a movie, taken with a video camera, of the way the organism dynamically develops, lives, behaves, etc. A dene thus captures something tangible about what the organism inherently is, and a bene captures something about what it does, or what it is capable of doing, always of course in the context of its internal and external environment.

While the authors admit that their proposed formalism is only conceptual at this point and needs to be extended with a true calculus, it is a vast improvement over the current conceptual system used in genetics.  As other researchers have observed, “descriptions of proteins encoded in DNA know no borders — that each sequence reaches into the next and beyond” and “genomic architecture is not colinear, but is instead interleaved and modular, and that the same genomic sequences are multifunctional”; ”

The new formalism addresses these issues well by extending the concept of genetic information beyond just a linear sequence of the DNA.  For instance, “a dene may comprise the specification for one or more proteins, or it may serve as template for the production (transcription) of an RNA molecule that has a purely regulative function. It also might designate a binding site for a protein or RNA molecule, or it may comprise sequences that influence (shape or inform) the 3D structure of the DNA, its mutability, the location of nucleosomes, or even certain aspects of post-transcriptional regulation.”

Benes are formally described as follows: “…a sequence consisting of events and actions, either internal to the organism or cell, or external to them; reflecting changes in state, structure, value, shape, potential, location, etc.”  Thus, the phenotypic realm — as described by the bene — now has structure which can be analyzed and simulated with existing formalisms such as finite state machines, dynamically adaptive networks, etc.

An additional feature of the dene/bene/genitor model is that it can incorporate environment explicitly using familiar logic notation like so: “O(D & E & M) →B, stating that the behavior B must be true in organism O if its DNA has property D, it is endowed with mechanisms M, and its environment has property E.”  Working within a logical framework enables us to bring to bear well-understood computational techniques, including theorem provers.

Importantly too, the model now is able to account for aspects of complex systems that the standard genetic framework cannot.  Examples include virtual stability, epigenetic/lamarkian inheritance, organismal adaptation (e.g. Baldwin effect), and more.

There are some major gaps that I would like to see addressed, including multilevel evolution and emergence, as illustrated by Alex Ryan’s diagram.  But unlike the standard genetic model, the new one can be extended to include these aspects of complex system dynamics.  Which is another clue that the age of the gene is drawing to a close.

Hat tip: Carlo Maley