The biological inheritance mechanism is essentially an inter-generational digital data communications system. Organisms communicate information describing their designs to their descendents by means of nucleotide sequences on DNA molecules. Consequently, inheritance mechanisms share characteristics and constraints that are common to all digital data systems. This has implications for evolutionary mechanics theory, which in turn largely determines theories of biological aging, which in turn affect our approach to finding ways to treat age-related diseases and conditions.
Darwin specified that "natural variation" was essential to the evolution process. Local variation between individuals in a population creates differences that can then be selected by natural selection. Evolution would not be possible in a population in which all the members were genetically identical. Darwin lived in an analog world and had no reason to believe that biological inheritance was not an analog process. In particular, since variation is an inherent property of an analog system, Darwin had no reason to suspect that variation was not a fundamental "natural" property of living organisms that applied equally to all species. The first hints that this was not the case did not surface until later publication of Mendel's work on inheritance. We now know that organism design is specified by digital data carried by the sequence in which A, C, G, and T nucleotides are positioned on DNA molecules and that inheritance mechanisms must therefore follow rules that are common to any digital data construct.
Properties of digital information
All digital information including genetic information possesses common properties that distinguish it from analog communications methods:
- Synchronization: Since digital information is conveyed by the sequence in which symbols are ordered, all digital schemes have some method for determining the beginning of a sequence. In written or spoken human languages synchronization is typically provided by pauses (spaces), capitalization, and punctuation. Machine communications typically use special synchronization sequences. Genetic data contains synchronization features such as start and stop codons. Genes are independent internally synchronized data structures and are equivalent to packets in data terminology.
- Language: All digital communications require a language, which in this context consists of all the information that the sender and receiver of the digital communication must both possess, in advance, in order for the communication to be successful. Languages are generally arbitrary and specify the meaning to be assigned to particular symbol sequences, the allowed range of values, methods to be used for synchronization, etc. The genetic languages may also be largely arbitrary. There are major language differences (e.g. codon definitions, diploid organization, multiple chromosomes, etc.) between bacteria and more complex organisms.
- Errors: Disturbances (noise) in analog communications invariably introduce some, generally small deviation or error between the intended and actual communication. Disturbances in a digital communication do not result in errors unless the disturbance is so large as to result in a symbol being misinterpreted as another symbol or disturb the sequence of symbols. It is therefore generally possible to have an entirely error-free digital communication. Further, techniques such as check codes may be used to detect errors and guarantee error-free communications through redundancy or retransmission. Errors in digital communications can take the form of substitution errors in which a symbol is replaced by another symbol, or insertion/deletion errors in which an extra incorrect symbol is inserted into or deleted from a digital message. Uncorrected errors in digital communications have unpredictable and generally large impact on the information content of the communication.
- Copying: Because of the inevitable presence of noise, making many successive copies of an analog communication is infeasible because each generation adds to the noise. Because digital communications are generally error-free, copies of copies can be made indefinitely. Error characteristics of digital data are essential to life as we know it.
- Granularity: When a continuously variable analog value is represented in digital form there is always a decision as to the number of symbols to be assigned to that value. The number of symbols determines the precision or resolution of the resulting datum. The difference between the actual analog value and the digital representation is known as quantization error. Example: the actual temperature is 23.234456544453 degrees but if only two digits (23) are assigned to this parameter in a particular digital representation (e.g. digital thermometer or table in a printed report) the quantizing error is: 0.234456544453. This property of digital data is known as granularity. Granularity limits the precision with which an organism design parameter can be genetically specified.
- Combining sources: In an analog system signals from two or more sources can be easily combined by simple addition to create a composite that averages the character of both sources. Example: sounds from two singers add in the air to create a composite. Combining information from two or more digital data sources is very much more difficult. We would need to decode the incoming data streams, correctly locate and access each of the specified data items, convert to the same scale and format if necessary, perform the additions or other processes needed to create a meaningful composite, and then generate and produce the proper output format. Doing this requires a priori knowledge of the formats of the incoming data. There is no way to simply combine digital data. Very complex inheritance mechanisms handle merging of genetic data from two sources in sexual reproduction.
In an analog system, "mutations" to information specifying the design of something would be expected to cause minor variations. Progressively less frequently, larger changes could be expected. If inheritance was analog we could expect descendents to average the characteristics of their parents. We would expect to see variation that followed a bell-shaped curve. Actual observations of living organisms grossly approximate the analog expectations.
However, as described above, variation is not a natural property of digital information such as that conveyed by genetic codes. The natural state when copying digital information is exact duplicates. Instead, we now know that variation in complex (sexually reproducing) organisms is largely created by a series of very complex and obviously evolved mechanisms that act to handle and process digital genetic data in order to produce variation that is similar to that produced by an analog system. These mechanisms include paired chromosomes, random selection of chromosomes during meiosis, and unequal crossover of random segments of digital data within chromosomes in addition to other mechanisms associated with sexual reproduction. These mechanisms are much more complex and capable than the simpler inheritance mechanisms found in earlier organisms such as bacteria. Although mutations are the ultimate source of variation, observed variation between sexually reproducing individuals is almost entirely the result of inheritance mechanisms recombining digital data to result in different data sets and consequent different organism designs. Example: a single pair of individuals containing four genetic data sets can produce immediate descendents having a very wide range of design characteristics. These individuals represent particular combinations of design characteristics that never previously existed and can include specimens that are faster, slower, smarter, less smart, taller, shorter and that otherwise exceed the range of design parameters expressed by their parents.
The observation that evolved mechanisms produce a quality (local variation) that is essential to the evolution process directly supports the idea that organisms can evolve design characteristics that aid the process of evolution (the major premise of evolvability theory). This in turn has major implications for evolutionary mechanics theory and dependent theories such as theories of biological aging.
See Evolvability Theories and more discussion on Genetics Discoveries that Conflict with Classical Evolution Theory
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