An obvious speculation is that all that data sitting there may be readable in terms we also understand.
This then represents a decoding challenge. Statistical methods could plausibly unravel some of it.
Does this same junk exist in other mammals as well?
It is a real long shot..
It is also possible that all this data is data that is actually used once only such as the roadmap for growing out our whole body and all that.
.
Linguistic characteristics of Non-coding DNA: Modern Evidence for a Library of the Ancients
https://grahamhancock.com/meuccis1/
In chapter twenty of Graham Hancock’s Supernatural,
a fascinating question about the contents of “junk” DNA is brought to
light. At the time of publication, researchers had discovered that only
the non-coding sections of DNA had special properties of long range
ordering while the coding sections did not. This long range ordering
conforms to the pattern found in Zipf’s law which is also a pattern
found in spoken language.
While this is a remarkable finding in itself, there are many other processes in nature that have also been found to be Zipf compliant. What makes the findings of Eugene Stanley et al (1994) so amazing is that they also used information theory as a wholly separate test of the non-coding data. Using the theory which governs modern scientific treatments of data compression, storage and communication, they also found that non-coding DNA has the properties necessary for maintaining data integrity even in error prone conditions. This necessary form of redundancy, which is expressed in terms of “Shannon Entropy,” was not found in the coding portion of the DNA, nor was it found in random characters used as a control.
The fact that these two very different tests for linguistic characteristics are found in the non-coding sections leads very strongly to the conclusion that structured and useful information is contained within the non-coding sections of DNA. This initially led Hancock to posit that non-coding DNA, which makes up the vast majority (or at least around 90%) of the human genome, might actually be a repository of knowledge which could in some way be accessible. Recent science has added a great deal to this mind-blowing hypothesis.
“Junk” DNA? What are we talking about?
DNA is a set of molecules whose shape and configuration of charges allow them to interact with various other molecules in ways that ultimately result in building and operating the super-complex micro machines we call cells. One little section of DNA, therefore, is like some of those complex little machines full of gears that can do fascinating but specific things. Now imagine creating enough different little machines to populate a factory and that factory’s purpose was to create even more tools, gears, and machines. This is a basic description of a cell.
In this analogy the configuration of atoms which make up DNA are like specially shaped multi-pole magnets which self-assemble and fit together to make up the gears of the machinery. The specific way all these gears and machines fit together and how they are arranged is crucial to making the factory actually be able to create what it does. The sequence of events dictated by the arrangement of equipment can be said to be a sort of “program” and that is why we often refer to DNA this way. The simplest pieces are all pretty much the same so it’s the arrangement that makes the difference between “pieces of metal” and “a machine.” That configuration is information.
The problem is that when we look in at the super complex machinery of DNA, we can only really separate “machines” from “hunks of metal” by the fact that we can see certain components work together to create things. We call these sections of DNA “coding” sections because they take part in creating proteins. When we examined all we knew about DNA and its functioning, we found that only a small percentage of the DNA actually seemed to do anything at all.
While this is a remarkable finding in itself, there are many other processes in nature that have also been found to be Zipf compliant. What makes the findings of Eugene Stanley et al (1994) so amazing is that they also used information theory as a wholly separate test of the non-coding data. Using the theory which governs modern scientific treatments of data compression, storage and communication, they also found that non-coding DNA has the properties necessary for maintaining data integrity even in error prone conditions. This necessary form of redundancy, which is expressed in terms of “Shannon Entropy,” was not found in the coding portion of the DNA, nor was it found in random characters used as a control.
The fact that these two very different tests for linguistic characteristics are found in the non-coding sections leads very strongly to the conclusion that structured and useful information is contained within the non-coding sections of DNA. This initially led Hancock to posit that non-coding DNA, which makes up the vast majority (or at least around 90%) of the human genome, might actually be a repository of knowledge which could in some way be accessible. Recent science has added a great deal to this mind-blowing hypothesis.
“Junk” DNA? What are we talking about?
DNA is a set of molecules whose shape and configuration of charges allow them to interact with various other molecules in ways that ultimately result in building and operating the super-complex micro machines we call cells. One little section of DNA, therefore, is like some of those complex little machines full of gears that can do fascinating but specific things. Now imagine creating enough different little machines to populate a factory and that factory’s purpose was to create even more tools, gears, and machines. This is a basic description of a cell.
In this analogy the configuration of atoms which make up DNA are like specially shaped multi-pole magnets which self-assemble and fit together to make up the gears of the machinery. The specific way all these gears and machines fit together and how they are arranged is crucial to making the factory actually be able to create what it does. The sequence of events dictated by the arrangement of equipment can be said to be a sort of “program” and that is why we often refer to DNA this way. The simplest pieces are all pretty much the same so it’s the arrangement that makes the difference between “pieces of metal” and “a machine.” That configuration is information.
The problem is that when we look in at the super complex machinery of DNA, we can only really separate “machines” from “hunks of metal” by the fact that we can see certain components work together to create things. We call these sections of DNA “coding” sections because they take part in creating proteins. When we examined all we knew about DNA and its functioning, we found that only a small percentage of the DNA actually seemed to do anything at all.
This is like looking into a factory in which over 90% of what you see is machine parts in various states of configuration and assembly that don’t actually do anything and are never used at all in the production process. It’s just hanging around. Then, when the factory fully duplicates itself, it also duplicates all the seemingly pointless junk as well. The question we have to ask is if the non-coding DNA really is “junk” or not. Nature tends to get rid of superfluous things, so what is all the extra information for?
Ups and downs in the recent history of “junk” DNA
One of the first advances of note in examining this idea is the
recent finding that some of the non-coding areas of DNA previously
labelled “junk” have been reported to play a crucial role in modulating
gene expression. Some of the previously labeled “junk” is, therefore,
actually functional. In many reports on these findings, the very notion
of “Junk DNA” is strongly dissuaded, as though all of the non-coding DNA
has now been shown to have some purpose. This is the farthest thing
from the truth, however!
Upon closer examination, it has long been known (as early as 1951
through Barbara McClintock) that gene regulation exists within the
genome and that all of these regulators are not fully known or
understood. Furthermore, the idea of “junk” DNA has been held up as
support of an evolutionary development model and has been a hot-button
issue for creation science proponents. Much of the literature and
impetus to fight the idea of “junk” DNA has come through creation
science sources with a specific axe to grind.
Before
the completion of the human genome project, most arguments against
“junk” DNA were based upon comparative genomics. It was found that upon
comparing genes between species, a number of genes in non-coding areas
are shared. The further apart the species are genetically, the more
“highly conserved” an identical gene sequence found in both is
considered to be.
Some genes are considered “ultra conserved” because
they are found in widely divergent species such as rats, humans, and
cows. The first indication that these areas in particular may be useful
in some way was when over-expression of these ultraconserved regions was
linked with certain types of cancer (Calin et al 2007). This finding is
a special case which runs contrary to many other findings discussed
below.
Around the turn of the millennium, upon completion of the human
genome project, it was known that around a mere 1.5% of the DNA is
actually coding. But in September 2012 this same project group called
the Encyclopedia of DNA Elements Project (ENCODE) had published a series
of papers in Nature which showed that up to 76% of
non-coding DNA was being transcribed. This report – that around 80% of
genome is biologically active – also led to a great deal of conjecture
and presumption. Scientifically speaking however, these findings were
not direct evidence of real or direct biological functions, but evidence
of the possibility of them.
As early as 2011 however, the same project had identified that a
species of bladderwort was deleting the vast majority of non-coding DNA
such that only 3% of its total genome was non-coding DNA; this was in
opposition to the 98.5% found in humans. This extremely complex species
was functioning quite well with a miniscule number of regulatory genes.
While
some of the non-coding DNA in humans has been directly shown to have
regulatory action, the most recent findings now show that the amount of
the actual functioning non-coding DNA is still
extremely small. This conclusion fits well with the bladderwort findings
that only a small number of regulatory non-coding genes were necessary
to function. Most notably, the ENCODE group has reported that the total
functional DNA in humans is no greater than 8.2%. (Rands et al 2014)
This is, however, not proof of direct functioning of even that small
percentage, but an estimation made, once again, based upon comparative
genomics. Only a very, very small percentage of non coding DNA has been
directly shown to have regulatory action.
Comparative
genomics in this context relies predominantly upon the conservation of
genes between species, as mentioned above. It is automatically presumed
that the conservation of genes occurs because of selection pressures
acting upon the animal, meaning that the gene must either grant some
survival advantage or otherwise play some functional role that can
impact selection. Experimentation in deleting these genes, however, has
shown this presumption to be highly questionable.
It is important to note that one of the crucial aspects of regulatory
genes is that their placement near coding genes is considered the
mechanism by which they function. While the first experiments which
deleted highly conserved areas showed zero effect in the animals
(Nobrega, M.A. et al. 2004), these extremely unexpected results were
explained as perhaps related to the ease of lab conditions in keeping
the animals healthy and hiding possible frailties. In another experiment
however, researchers specifically chose ultra conserved areas in close
proximity to genes which are known to cause severe abnormalities when
not functioning normally. Once again, the deletion of these genes had
absolutely zero impact upon morphology, longevity, reproduction, or
metabolism (Ahituv, N. et al. 2007).
DNA data storage and information theory …again
In
the past decade and a half, the computer industry has delved deeply
into the use of DNA for developing long-term, space-saving data storage.
The first major proof of the concept emerged in 2012 with the writing
and reading of over 5 megabits of information in DNA storage (Church et
al 2012). While there have been simultaneous advancements in numerous
biological computation technologies (Shaji Varghese 2015), the most
telling example is the development of a DNA storage system for data
which is not only nearly as easily manipulated for editing etc. as an
electronic computer system, but has been shown to potentially last as
long as a million years in cold storage (Grass et al 2015). Even using
less than perfect data compression, all of the data on Wikipedia and
Facebook combined could fit in a couple of drops of liquid and all the
knowledge of mankind in the space of an elevator cabin.
The further breakthrough in this most recent development is the
application of information theory to maintain data integrity even in
conditions that might cause errors. DNA can be very unstable, so the
largest challenge is overcoming this limitation. By using error
correction codes, lost data can be reconstructed. This is accomplished
by duplicating information.
This methodology of redundancy results in precisely what was searched
for (and found) in non-coding DNA in the study mentioned at the
beginning of this article. With this insight, it seems as though we may
have come full circle with an ancient advanced civilization who had
previously discovered and used this technology.
In
the continued pursuit to design a data system which could eternally
store knowledge, it is inevitable that any singular storage place for a
library will be subject to destruction via simple mechanisms such as
bombing, to more long term concerns such as subsumption by tectonic
plates at large enough time scales. Our technology is already strongly
and quickly advancing from our manipulation of DNA, towards using it as a
form of wet nanotechnology (Zakeri et al 2015), which could accomplish
all of the tasks that our current technologies do with the added
advantage of self-assembling, self-healing and self-replicating devices.
An
obvious solution to the eternal storage problem would be to write our
knowledge into creatures that will grow, replicate and most importantly
adapt to an ever-changing environment through branching into every
possible species, to colonize every possible space and environmental
niche. It makes perfect sense to do again what might have been done
before.
We may decide to build an eternal library and fill it with our own
books. Chances are, as we excavate the location to build this library
that we will find, just under the surface, a library already built in
the same way and in the same place as before.
Data means nothing without an interpretation key
One of the most crucial aspects to consider when designing this eternal
library, however, is the leaving of a Rosetta stone, so that in a few
million years, when a wholly different species with no concept of our
language attempts to read it, it can be decoded. The Rosetta stone
itself must not only be hidden in the DNA with the information, but also
somehow cross language and culture barriers that are separated by an
alien mental gulf of time and circumstance.
One conceivable method for creating a Rosetta stone is to cause library
sections (non-coding) of the information to somehow also impact and
interact with the sections of DNA which do actually form the creature
(coding DNA). This could be a way of linking pure information with real
world actions and objects. By combining the method of action of this
“Rosetta stone” section of regulatory DNA with its location in
relationship to other non-coding sections, it might represent a word
within some larger statement. If this was combined with the component of
the animal that a particular section of DNA represents, one might
develop a seed for universal translation of the data through the
symbolic actions and actors found within the DNA itself.\
For instance, if the regulatory action causes a gene to “hide” or
“diminish” then that sequence of DNA could be interpreted to have that
meaning. If it “cuts” or “translates,” these might also give us a
meaning to particular sequences. Then if it affects “blood” or an “arm”
then we begin to have additional nouns to work with. All of these
actions and components might be used in a metaphorical sense to build a
language which can be unpacked through self-modification. Each
relationship might lead to other relationships by which a well designed
language might lead to ever more complex words based upon a system in
which few words act as modifiers upon each other to create ever greater
refinement and specificity of definition.
The discovery – that a small portion of our non-coding DNA does
directly regulate some genes – is a natural conclusion to, and in
further support of, the genetic library hypothesis.
Eliminating selection pressure impact on genetic information storage
One
of the other important design considerations in using animals and their
offspring to store crucial information, is the ability to somehow allow
the normal developmental process of species, but keep it from impacting
the passing on of the data to offspring. There would need to be a
selection mechanism within the genes that favors preservation of the
data even though the data provides no survival advantage.
Recent development in genetics has actually provided such a mechanism
and it’s called a “gene drive” or a Mutagenic Chain Reaction (MCR). In
applying the CRISPR gene editing technology with a targeting sequence,
researchers have created an auto-catalysing reaction that results in a
self-replicating gene editing system (Gantz & Bier 2015). This
system targets and edits all copies of the targeted gene and therefore
not only affects the genes of a given animal, but also the genes of
offspring. The editing system, passed down genetically, bypasses the
normal mendelian mechanics of dominant and recessive traits by
overwriting any other copy received from a normal donor parent with the
gene passed down from the gene drive parent. In the experiments, the
gene drive system resulted in passing down a recessive trait in fruit
flies with around 97% accuracy.
This
system so completely bypasses any selection pressures that it could
even result in preferentially passing down traits which directly lower
the survival rate of the offspring. This system, which is entirely
encapsulated within the molecular mechanics, could provide a means by
which DNA-based information storage is passed down preferentially in
animals completely regardless of natural selection processes.
The end result of storing information in this way would be that after
millions of years there would be ultra-conserved DNA which could be
directly deleted, with zero impact on the morphology or other traits of
the animals, precisely as was seen in the UCR deletion studies mentioned
above.
Epigenetics, Genetic Memory, and the Library of the Ancients
Epigenetics is another crucial component to this puzzle, the
knowledge of which has advanced a great deal in the past decade. We now
know that the events and influences within a single animal’s life can be
passed on to their offspring. Epigenetics is not a process that alters
the actual DNA code but works, instead, through regulation of gene
expression much like cell differentiation does. The reason we can have
all the various cells of different organs appear from the single stem
cell type is because of gene expression.
As one might expect, the sections of non-coding DNA which act in a
regulatory role and impact the coding DNA have been found to be a part
of the mechanism of epigenetics (Cao, J. 2014). These epigenetic changes
can also, however, alter the likelihood that a real genetic mutation
might occur in the affected area (Skinner 2015). The more short-term
mechanisms of epigenetic change, when transmitted over longer
trans-generational time scales, may, therefore, lead to direct genetic
change.\
The idea of genetic memory has been around for a very long time as an
anecdotal conjecture. The ability of savants to know things it seems
they have never learned has been explained in such a way, as have past
life regressions etc. While the idea that instincts must exist as
instructions hidden in genes which regulate brain morphology is widely
assumed, these general instructions have generally been postulated to
have formed purely through selection pressures.
With the recent understanding of epigenetics allowing for the
experiences of a single individual to become heritable, the possibility
of true genetic memory has become a scientifically viable area of
inquiry. As such, a study was performed on mice in which parental
traumatic exposure to cherry blossom scent passed down the fear
conditioning to future generations in which even the grandchildren
reacted very aversively toward the scent. Furthermore a gene was
identified with sensitivity to that scent and changes to the expression
of the gene had indeed been altered. Concurrent changes in brain
structure were also observed in offspring (Dias & Ressler 2014).
Now that genetically transmitted memory is a scientifically validated
concept, it is obvious that there is a data storage mechanism in DNA
which interacts with mental experiences and it seems no large
presumption that the interaction could possibly be two-way in nature.
Might we then suppose that our non-coding DNA may be comprised of
both trans-generational memories as well as a storehouse of more
directly inserted information from long ago? Might the directly inserted
older data play a role as a guiding principle for trans-generational
memory and might those memories, built upon that original key, provide a
sort of interpretational Rosetta stone for understanding that original
information?
From a programming and engineering perspective, it makes sense to integrate the interpretational system in such a fashion.
One final thought
In 2011 another new method of identifying spoken language emerged
from the application of information theory in a novel fashion. While the
“Shannon Entropy” (information density) of various languages differed,
one aspect remained almost exactly the same across all languages. The
amount of information carried by the structure of real communicative
language is higher than a word-salad mix of words. When we take any text
of any language and rearrange the words randomly, the amount of
information per word decreases by the same amount regardless of language
(Montemurro & Zanette 2011).
My personal opinion is that if non-coding DNA were subjected to this
test, it would probably fail because the language of memories is likely
more symbolic than syntax based. A reliance upon word ordering is
usually reserved only for spoken language and not general data storage.
Therefore a failure would not, in any way, falsify the library
hypothesis. However, if this test were to come back positive, not only
would the library hypothesis be utterly validated, but it would also
likely mean that all genetic memory is encoded directly into the
language once spoken by the ancients who created this library.
While this reliance upon syntax in the storage of genetic memory seems
unlikely, it is not completely unsupported by scientific discoveries.
Research at Carnegie Mellon has resulted in the discovery that language
is stored so similarly from one human to the next, that the physical
location in the brain for the data that represents nouns can be modeled
and predicted by a computer. Tests using fMRIs to read the blood flow
and activation of these areas in the brain resulted in the ability to
read a subject’s mind with between 70% and 94% accuracy when the subject
focused upon a noun. The accuracy was so great that this
computer-modeling-based “mind-reading” technique was able to distinguish
between thoughts of extremely similar objects like “pliers” and
“hammer.” (Mitchell et al 2008)
While this is not a reliance upon word ordering, it shows a
standardization of language storage from one human to the next.
Therefore the concept of storing additional information by the
relationships between words is not necessarily a large leap, but is a
worthy area of future inquiry. It does, however, lend itself to a
representational mechanism, based upon physical position, by which
genetic memory may be encoded. Specifically, it provides a structural
system by which one language may be translated into a different one.
References:
R. N. Mantegna, S. V. Buldyrev, A. L. Goldberger, S. Havlin, C.-K. Peng, M. Simons, and H. E. Stanley.
Linguistic Features of Non-coding DNA Sequences,
Phys. Rev. Lett. 73, 3169-3172 (1994)
Calin, George A. et al.
Ultraconserved Regions Encoding ncRNAs Are Altered in Human Leukemias and Carcinomas
Cancer Cell , Volume 12 , Issue 3 , 215 – 229, 2007
Ibarra-Laclette, E., Albert, V. A., Pérez-Torres, C. A.,
Zamudio-Hernández, F., Ortega-Estrada, M. de J., Herrera-Estrella, A.,
& Herrera-Estrella, L.
Transcriptomics and molecular evolutionary rate analysis of the
bladderwort (Utricularia), a carnivorous plant with a minimal genome.
BMC Plant Biology (2011), 11, 101. http://doi.org/10.1186/1471-2229-11-101
Rands CM, Meader S, Ponting CP, Lunter G.
8.2% of the Human Genome Is Constrained: Variation in Rates of Turnover across Functional Element Classes in the Human Lineage.
Schierup MH, ed. PLoS Genetics. 2014;10(7):e1004525. doi:10.1371/journal.pgen.1004525.
Nobrega, M.A. et al. (2004).
Megabase deletions of gene deserts result in viable mice.
Nature 431: 988-993.
Ahituv, N. et al. (2007).
Deletion of ultraconserved elements yields viable mice.
PLoS Biology 5(9): e234.
Church, G. M., Gao, Y. & Kosuri, S.
Next-generation digital information storage in dna.
Science 337, 1628–1628 (2012)
Shaji Varghese, Johannes A. A. W. Elemans, Alan E. Rowan, Roeland J. M. Nolte,
Molecular computing: paths to chemical Turing machines,
Chem. Sci., 2015, 6, 11, 6050
Grass, R. N., Heckel, R., Puddu, M., Paunescu, D. and Stark, W. J.
(2015), Robust Chemical Preservation of Digital Information on DNA in
Silica with Error-Correcting Codes.
Angew. Chem. Int. Ed., 54: 2552–2555. doi:10.1002/anie.201411378
Bijan Zakeri, Timothy K Lu,
DNA nanotechnology: new adventures for an old warhorse,
Current Opinion in Chemical Biology, 2015, 28, 9
Valentino M. Gantz, Ethan Bier
The mutagenic chain reaction: A method for converting heterozygous to homozygous mutations
Science 24 Apr 2015 : 442-444
Cao, J.
The functional role of long non-coding RNAs and epigenetics.
Biological Procedures Online (2014), 16, 11. http://doi.org/10.1186/1480-9222-16-11
Skinner MK
Environmental Epigenetics and a Unified Theory of the Molecular Aspects
of Evolution: A Neo-Lamarckian Concept that Facilitates Neo-Darwinian
Evolution.
Genome Biol Evol. 2015 Apr 26;7(5):1296-302. doi: 10.1093/gbe/evv073.
Brian G Dias & Kerry J Ressler
Parental olfactory experience influences behavior and neural structure in subsequent generations
Nature Neuroscience 17, 89–96 (2014) doi:10.1038/nn.3594
Marcelo A. Montemurro and Damián H. Zanette.
Universal Entropy of Word Ordering Across Linguistic Families.
PLoS ONE, Vol. 6, Issue 5, May 13, 2011. DOI: 10.1371/journal.pone.0019875.
Tom M. Mitchell, Svetlana V. Shinkareva, Andrew Carlson, Kai-Min Chang, Vicente L.. Malave, Robert A. Mason, Marcel Adam Just
Predicting Human Brain Activity Associated with the Meanings of Nouns
Science, 30 MAY 2008 : 1191-1195
No comments:
Post a Comment