Definition of gene needs reveiwing ?

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    Definition Gene
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Discussion Overview

The discussion centers on the evolving definition of a gene in light of new genomic evidence, exploring the implications for developmental biology and genetic inheritance. Participants examine the complexities of gene definitions, the role of epigenetics, and the potential for new modeling frameworks in understanding genome expression and regulation.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Conceptual clarification

Main Points Raised

  • Some participants propose that recent genome analysis indicates the need to redefine what constitutes a gene, suggesting that traditional boundaries between genes are becoming less distinct.
  • Others argue that the variability in gene counts based on differing definitions highlights the complexity and ambiguity surrounding the concept of a gene.
  • One participant mentions that the process of gene expression is often not a straightforward one-to-one mapping with DNA sequences, complicating the definition of genes.
  • There is a suggestion that the future of developmental biology may involve a shift towards understanding gene networks and epigenetic inheritance, which could challenge current gene-centric models.
  • A later reply introduces a mathematical framework for modeling genome expression as dynamic systems, asserting that the traditional concept of a gene may be inadequate for such models.
  • Another participant cautions that current technologies may not yet provide the necessary data to develop accurate predictive models of cellular processes, indicating limitations in the proposed frameworks.

Areas of Agreement / Disagreement

Participants express multiple competing views regarding the definition of a gene and the implications for biological models. There is no consensus on a new definition or framework, and the discussion remains unresolved.

Contextual Notes

Limitations include the dependence on evolving definitions of genes, the unresolved nature of gene counting, and the current technological constraints in modeling genome expression accurately.

thorium1010
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According to this news article , genome analysis has shown that the understanding of what constitutes a gene has to reveiwed and redefined in light of new evidence. Btw there is no junk DNA in our genome.

http://medicalxpress.com/news/2012-09-encode-massive-genome-analysis-gene.html

"We see the boundaries of what were assumed to be the regions between genes shrinking in length," he says, "and genic regions making many overlapping RNAs." It appears, he continues, that the boundaries of conventionally described genes are melding together, challenging the notion that a gene is a discrete, localized region of a genome separated by inert DNA. "New definitions of a gene are needed".
 
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thorium1010 said:
According to this news article , genome analysis has shown that the understanding of what constitutes a gene has to reveiwed and redefined in light of new evidence. Btw there is no junk DNA in our genome.

http://medicalxpress.com/news/2012-09-encode-massive-genome-analysis-gene.html

At some point soon the entire idea of "genes" will have to be replaced with a more general concept. One sign that it is close to the end is that we can't precisely count genes in a genome. Small variations in the definition of a gene result in large differences between number of genes in the genome.
The number of genes in the human genome have varied between 10^4 to 10^6. Right now, the number seems to have settled down to 3×10^4. However, the definition chosen for this number is somewhat arbitrary.
One thing that complicates the definition of gene is that some contiguous sequences of RNA are transcripted from discontiguous segments of DNA in the chromosome. Another thing that complicates the definition of gene is that in eukaryotes, proteins are often synthesized in a two or three step process after the genes are translated into proteins. So enzymes do not always have one on one mapping to the corresponding sequence of DNA.
Developmental biology still has a revolution or two in its future. Although a "review" of the definition of gene would be helpful, there is no way to fix the concept of gene. I suspect that the theory of gene networks may be due for some breakthroughs. Furthermore, we have to find out more about epigenetic inheritance. By epigenetics, I mean inheritance through molecules other than DNA.
Don't get me wrong. The "gene centric" models of developmental biology will still continue to help evolutionary biology for a considerable amount of time in the future. Even while a new "synthesis" of biology is being developed, the gene centric approximation will be extremely useful for simplifying and clarifying evolution. However, there are some fundamental inconsistencies in the theory of genetic inheritance as we know it today.
I predict that in the future, "the gene" will have the same level of acceptance in biology as "the fluid element" has in classical mechanics. "The gene" will be recognized as a mathematical concept based on an approximation rather than a strictly physical concept based on the general theory.
 
I think (hope) that it will soon be a time for dynamical systems to play role in these definitions. There's a framework paper out in Biosystems called Mathematical modelling in the post-genome era: understanding genome expression and regulation— a system theoretic approach:

Abstract: This paper introduces a mathematical framework for modelling genome expression and regulation. Starting with a philosophical foundation, causation is identified as the principle of explanation of change in the realm of matter. Causation is, therefore, a relationship, not between components, but between changes of states of a system. We subsequently view genome expression (formerly known as ‘gene expression’) as a dynamic process and model aspects of it as dynamic systems using methodologies developed within the areas of systems and control theory. We begin with the possibly most abstract but general formulation in the setting of category theory. The class of models realized are state-space models, input–output models, autoregressive models or automata. We find that a number of proposed ‘gene network’ models are, therefore, included in the framework presented here. The conceptual framework that integrates all of these models defines a dynamic system as a family of expression profiles. It becomes apparent that the concept of a ‘gene’ is less appropriate when considering mathematical models of genome expression and regulation. The main claim of this paper is that we should treat (model) the organisation and regulation of genetic pathways as what they are: dynamic systems. Microarray technology allows us to generate large sets of time series data and is, therefore, discussed with regard to its use in mathematical modelling of gene expression and regulation.

BioSystems 65 (2002) 1–18
© 2002 Elsevier Science Ireland Ltd. All rights reserved.
 
Also, so that dynamical system's enthusiasts don't get too carried away, a caveat from the introduction:

It should be made clear from the start that this contribution is dealing with ‘science fiction’. Current technology, such as DNA microarrays, does not as yet deliver the data that would be required to identify accurate, predictive models of cellular processes realized by complex networks of chemical reactions. For a comprehensive model of genome expression, current microarray technology does not provide a sufficiently high resolution[...]
 

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