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Inter-network protocols partition all bilaterians
Internet of Life Chapter 2
Eric Werner *
Oxford Advanced Research Foundation
eric.werner@oarf.org
https://www.ericwerner.com
https://www.oarf.com
Abstract
Previously, in Internet of Life, Chp 1 [137], it was shown that if the interaction protocol
between parental genome networks is random then there is a loss of bilateral symmetry.
Thus, a nonrandom meta-network, interaction protocol evolved as a precondition for the
evolution of the first bilaterally symmetric organisms in the Precambrian more than 570
million years ago. In this chapter we investigate some of the consequence of nonran-
dom interaction protocols for development and evolution. Computer simulations show
that any nonrandom interaction protocol dynamically partitions the organism into two
types of nonintersecting sections, one type controlled by the maternal and the other by the
paternal haploid genome network. Thus, at any given time, all cells in a given section
are exclusively controlled by only one of the two parental haploid genome networks. The
partition is dynamic with sections changing identity, splitting or merging as the organism
develops. The developmental effects of later partition states are superposed on earlier de-
velopmental states leading to complex mixtures of ancestrally inherited phenotypes. Each
protocol has an identifying meta-network signature. Different protocol signatures parti-
tion the developing organism differently leading to different morphologies and capacities
both mental and physical. As protocols and developmental networks diverge new species
and phyla can emerge. Protocols are the bedrock of social and sexual intercourse between
male and female genomes. For any diploid species their haploid protocols must cooper-
ate to generate a coherent, complete and consistent embryo. If the two haploid protocols
of potential sex partners diverge too much, network disfunction causes developmental
pathologies, miscarriage or unviability. Evidence for this new theory of development and
evolution comes from computational multicellular experiments, human and animal de-
velopment, malformations, teratology, hybrids and gynandromorphs. Developmental net-
works and their meta-network protocols provide a fundamentally new explanatory frame-
work for embryonic and post-embryonic development, developmental pathologies, animal
and plant hybrids, heterosis, and evolutionary dynamics.
Key words:embryo sectioning, embryo partitioning, haploid genome interaction protocols, maternal
genome, paternal genome, parental genomes, genome intercourse, morphogenesis, meta-network protocols,
meta-networks, meta-network signatures, evolution, species formation, evolution of species, cenes, cenome,
developmental control networks, brain development, brain evolution, social neurological evolution, commu-
nication capacity, language capacity, teratology, human malformations, gynandromorph, hybrids, heterosis,
hybrid vigor, 1st-order network, 2nd-order network, genome semantics, network completeness, network con-
sistency
*©Werner 2020. All rights reserved. Cite As: Werner, E., Inter-network protocols partition all bilaterians:
Internet of Life Chp 2, 2020, DOI: *insert DOI here*
Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 i
Contents
1 Introduction 2
1.1 Nonrandom protocols partition organisms bilaterally ............ 3
1.2 Protocols are the bedrock of social and sexual intercourse between male
and female genomes ............................... 3
1.3 Evidence and explanatory power ........................ 3
2 How network protocols partition bilaterians 4
2.1 Nonrandom protocols partition MCOs preserving bilateral symmetry . . . 4
2.2 Different protocol signatures partition organisms differently ......... 6
2.3 Protocol to partition correspondence ...................... 7
2.4 Same 1st-order genome networks but different 2nd-order networks gener-
ate different phenotypes ............................. 8
2.5 Functional segments versus sections of partitions ............... 8
3 Protocol partitioning is dynamic 8
3.1 Similarities and differences in brothers, sisters and grandparents . . . . . . 9
4 Each diploid genome has at least two execution pathways 9
4.1 One of Darwin’s puzzles solved ......................... 10
4.2 Imprinting and parent of origin effect ..................... 11
4.3 A fundamental question about male and female development ........ 11
4.4 Invisible twins: Genomically identical but phenotypically different ..... 12
4.5 False twins: Phenotypically identical but genomically different ....... 12
4.6 Hidden cancer networks ............................. 12
5 Mirror protocols generate inverse partitions 12
5.1 Mirror networks and duality of inverted partitioning ............. 13
5.2 Mirror networks generate dynamic inverted development .......... 14
5.3 Degrees of mirror inversion of partitions .................... 15
5.4 Mules and hinnies, a case of inverse development? .............. 15
6 The Null Protocol 15
6.1 The haploid genomes generate distinct MCOs ................. 15
6.2 Implementation of the Null Protocol in living systems ............ 16
7 Discussion 16
7.1 Properties of protocols .............................. 16
7.2 How are inter-network protocols implemented in living cells? ........ 17
7.3 Sex is complicated! Gynandromorphs and trans gender animals . . . . . . 17
7.4 Partitioning and the network paradigm ..................... 18
8 Conclusion 18
8.1 A Unifying theoretical framework ........................ 18
8.2 Evolutionary and developmental explanatory power ............. 18
8.3 Pragmatic import ................................. 18
8.4 Highlights of discoveries ............................. 19
8.5 Open questions .................................. 20
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Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 2
1 Introduction
Fig. 1: Partitioning Leonardo da Vinci’s Vitruvian Man For all bilaterians a nonrandom pro-
tocol between parental genomes partitions the body into sections controlled by either the maternal or
the paternal haploid genome network. The above is a hypothetical, figurative partition of the Vitruvian
Man (Leonardo da Vinci, ca. 1498) at the adult stage of development. Earlier in development, as the
man grew from a single fertilized egg, the partitions changed whenever the meta-network links of the
protocol activate the opposite sex parental genome network. These changes include both the body and
the brain with concomitant changes in physical, mental, emotional, behavioral, communicative, and
social capacities. Drawing adapted from Vitruvian Man, see [80] for the historical context.
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Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 3
1.1 Nonrandom protocols partition organisms bilaterally
Previously in Chapter 1 of this series[137] it was shown that if the interaction protocol between
the two parental haploid genome networks is random then there is a loss of bilateral symmetry
in the developing organism. Therefore, for all bilaterally symmetric organisms the interaction
protocol between the two parental genomes cannot be random. Moreover, it means that a
nonrandom ur-protocol must have evolved with the first diploid ur-bilaterians more than 570
million years ago.
The main result of this chapter:
Proposition 1 (Protocol Partitioning). For any bilaterian there exists a nonrandom inter-
network protocol between its two parental haploid genome networks that dynamically parti-
tions the developing body into sections where each section is separately controlled by either
the maternal or the paternal haploid genome network.
The partitioned Vitruvian man in Fig.1illustrates a main implication of Prop.1. The figure
shows two hypothetical, metaphorical partitions of Leonardo da Vinci’s classic Vitruvian man
at the adult stage of development. Earlier in his development, as the man grew from a single
fertilized egg, the partitioning changed whenever the meta-network links of the protocol ac-
tivated the opposite parental, haploid genome network. These changes include both the body
and the brain with concomitant changes in physical, mental, emotional, behavioral, commu-
nicative, and social capacities.
1.2 Protocols are the bedrock of social and sexual intercourse between male and
female genomes
The protocol mediates the familial interactions. If there is no coordination or cooperation
things fall apart.
"Happy families are all alike; every unhappy family is unhappy in its own
way." Leo Tolstoy, Anna Karenina.
So it is when two genomes cohabit in a cell. When the interaction protocol is not felicitous,
the possible pathologies are endless. A happy cohabitation places universal constraints on all
bilaterian genome interaction protocols.
The protocol is the bedrock of social and sexual intercourse between genomes. It is regulates
and implements the lowest level of interaction between the genomes of sexual beings. The
protocol was the precondition for the very existence and evolution of bilateral sexual organisms
in pre-Cambrian 570 million years ago[137].
1.3 Evidence and explanatory power
Evidence for this new theory of development and evolution comes from computational multi-
cellular experiments, human and animal development, malformations, teratology, hybrids and
gynandromorphs.
Cite As: Werner, E., Inter-network protocols partition all bilaterians: Internet of Life Chp. 2, 2020, DOI: *insert DOI here*
Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 4
Developmental networks and their meta-network protocols provide a fundamentally new ex-
planatory framework for embryonic and post-embryonic development, developmental patholo-
gies, animal and plant hybrids, heterosis, and evolutionary dynamics. The broad explanatory
and predictive scope shows the extraordinary power of the network theory of development.
(See Sec.8.4 for a list of new phenomena explained.)
Plan: In this chapter we investigate some of the consequences of nonrandom interaction proto-
cols for development and evolution. The focus is on the results of multicellular CAD modeling
and simulation where we study the properties and behavior of inter-genome protocols. In later
chapters we examine case studies and experiments that support these computational results.
The cases come from human and animal development, malformations, teratology, hybrids and
gynandromorphs.
2 How network protocols partition bilaterians
Using CAD software to design and run genomes in cells to generate bilateral multicellular
systems (Sec.10), computer simulations show that as a nonrandom protocol executes or runs,
it partitions the organism into nonintersecting sections or modules. The partitions are dynamic
varying over developmental time and space. Intuitively, at any instant, a partition covers an
MCO (Multi Cellular Organism) completely in such a way that none of the sections overlap1.
At any point in time in development, for any section in a partition, the cells in that section
are controlled by the same 1st-order, haploid genome network. However, the cells in a section
while controlled by the same haploid genome, will in general be in different regulatory 1st-
order network states[137].
2.1 Nonrandom protocols partition MCOs preserving bilateral symmetry
Any Turn-Taking protocol between two or more networks determines which network is in
control of a cell at any given time[137].
Principle 1 (Partitioning). Non-random Turn-Taking protocol dynamically partitions the de-
veloping bilateral embryo into sections exclusively controlled by one or the other haploid
genome 1st-order network.
When the protocol is nonrandom we get discrete combinations of maternal and paternal grand-
parent phenotypes, as is confirmed by the next series of computational experiments (Figs.2and
Fig.3).
1More formally, a partition P of a set Sis a set Pof non-empty, non-intersecting subsets sof Ssuch that the
union of the subsets sis equal to S, i.e., for all non-empty s∈P,⋃s∈P=S. Thus the sections cover Scompletely
but do not overlap each other. We will call these subsets of a partition sections or modules depending on the context.
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(a) Sig1 MCO
Network
Stained
(b) Protocol meta-network Signature 1 (c) Sig1 MCO
Differentiation
states
Fig. 2: Nonrandom protocol signatures generate bilateral partitioned organisms
A computationally modeled 3-segmented Multi-Cellular Organism (MCO) grown from a single cell
(zygote) under a nonrandom, Non-Null protocol. Each zygote contains both the paternal and maternal
haploid genomes. On the left Fig.2a is the MCO with cells stained Purple when the Paternal hap-
loid genome network is in control and Aquamarine when the Maternal haploid genome network is in
control. Note the partitioning of the MCO into type two types of sections. The center Fig.2b shows
protocol’s executed signature of meta-links (2nd-order or trans-links). The right MCO, Fig.2c, shows
the cell differentiation states of the Paternal and Maternal networks in various colors, greens for the
Paternal MCO. Note the difference between the segments of the organism versus the sectioning by the
protocol.
Definition 1 (Signature). The signature of a Turn-Taking protocol is the set of meta-network
links (also called trans-links,2nd-order links,inter-network links) between two haploid
genome 1st-order networks. (See Sec.9for definitions of protocols and protocol types.)
Fig.2shows an example signature (Fig.2b) and the multicellular organism (MCO) it gener-
ates. Using multicellular CAD software (see Materials and Methods Sect.10) one can select
a genome network view of developing cells to show which haploid genome is in control of
which cells at any given time. On the left side, in Fig.2a, Purple cells show where the paternal
haploid genome is active and Aquamarine cells show where the maternal haploid genome is
active.
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2.2 Different protocol signatures partition organisms differently
(a) Sig2 MCO
Network
Stained
(b) Protocol Network Signature 2 (c) Sig2 MCO
Differentiation
states
(d) Sig3 MCO
Network
Stained
(e) Protocol Network Signature 3 (f) Sig3 MCO
Differentiation
states
(g) Sig4 MCO
Network
Stained
(h) Protocol Network Signature 4 (i) Sig4 MCO
Differentiation
states
Fig. 3: Different protocol signatures generate differently sectioned organisms
Shown are different runs of the same MCO shown in Fig.2, but with protocols with different signatures.
On the left side, Purple cells in the MCOs show where the paternal haploid genome is active and
Aquamarine cells show where the maternal haploid genome is active. All have an identical pair of
haploid genomes. (See Sec.9for definitions of protocols, protocol types, executed signature.)
To generate the examples in Fig.3showing the relationship between Turn-Taking Protocols
and embryonic sectioning, we randomly generate protocols by randomly generating trans-links
(also called meta-links, or inter-network links) between two given parental genomes. This gen-
erates an interaction protocol or meta-network (2nd-order network) between the two parental
networks (1st-order networks). We then generate the embryo from a single cell and simultane-
ously show the resulting execution signature and its associated sectioned organism.
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2.3 Protocol to partition correspondence
Because the partition is generated by the meta-network protocol, there is a strong correspon-
dence of organism sections and meta-network link architecture. This meta-network architec-
ture contains the executed signature. As each different signature corresponds to a different
partitioning of the developing embryo.
(a) Partition stained human
skeleton via protocol 1
(b) Partition stained human
skeleton via protocol 2
Fig. 4: Two hypothetical partitions of human skeletons
Computer simulations confirm that any for any bilaterally symmetric diploid organism, a nonrandom
protocol adjudicates cellular control between its two haploid genomes. The protocol partitions the
organism into sections of two distinct types, one controlled by the mother’s haploid genome and the
other controlled by the father’s haploid genome. The figures show two possible partitions of a human
skeleton resulting from two different hypothetical protocols (meta-network signatures). Purple colored
sections are controlled by one parent’s haploid genome, while the brown colored sections are controlled
by the other parent’s haploid genome. The partition changes discreetly and sometimes dramatically over
the development of the organism from the embryo into its adult form.
A change in a signature that maintains consistency and completeness will, on execution, acti-
vate different 1st-order subnetworks leading to possible differences in morphology and func-
tion. Loss of a meta-link may lead to merging of two sections. Addition of a meta-link may
lead to additional maternal-paternal sections.
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2.4 Same 1st-order genome networks but different 2nd-order networks generate
different phenotypes
Note, all the organisms in Fig.2and Fig.3have identical genomes, except for their interaction
protocols. This illustrates that the very same genome can generate very different morphological
and functional phenotypes given changes in the interaction protocol. The networks in the
parental paternal and maternal genomes that generate the actual body parts and functions are
identical, just the protocols that determine how they cooperate are different.
2.5 Functional segments versus sections of partitions
Note the difference between partition sections generated by the protocol (Fig.2) and functional
segments of the MCO that refer to functionally distinct body parts, e.g., insects are segmented
but the segments themselves may be partitioned into further sections. The opposite can also
happen when the same section of a partition can contain more than one segment. Thus, the
relationship between functional segmenting of bilaterians and partitioning may be a complex
and indirect. The artificial MCO in Fig.2has three main segments (head, midsection and tail)
but it is partitioned variously in Fig.2and where protocol partition sections even cross segment
boundaries in Fig.3. This is also illustrated in the hypothetical example in Fig.4where the
thorax as segment is subdivided into partition sections. Thus, insects might have their segments
partitioned by their protocol leading to segment variation in the same species.
3 Protocol partitioning is dynamic
The protocol partition may change as the meta-links pass control to the other parental haploid
network. Thus, a section controlled by the maternal genome may switch to be under the control
of the paternal genome. Or a subset of the cells in a given section controlled by one haploid
network may flip and pass control to the opposite parental haploid network. Or a section may
expand its territory engulfing other cells into its sphere of control. And, of course, any section
may expand as its cells proliferate.
A salient feature of partitioning induced by meta-network protocols is that the partitions are
discrete and do not overlap at a given instant. However, partitions do change boundaries and
ownership over developmental time2. The sections in a partition can change their extent, merge
with other sections or split into two new partitions (see Fig.5). However the switch is not fluid.
It is a discrete event when a trans-link switches control to the other parental haploid genome
network. At the section or module level, some boundary changes of sections may appear to be
fluid because cells are small and the switching of ownership may be the result of cell signaling
or a chemical gradient.
2While a network is in control of the actions of a set (subset, section, module) of cells, the network is said to
own that set (subset, section, module) of cells in a partition. A partition consists of nonintersecting subsets each
exclusively owned by one or the other haploid network.
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(a) 2 Cells (b) 4 Cells (c) 8 Cells (d) 16 cells
(e) 32 Cells (f) 36 Cells (g) 40 Cells (h) 52 Cells (i) 80 Cells
Fig. 5: Protocol generated partitions change as the organism develops. As the simple mul-
ticellular organism (MCO) grows from a single cell, the haploid parental genome that controls which
parental network is active in any cell changes when the meta-control network switches to the opposite
haploid genome. The result is a dynamic sectioning of the embryo with sections reflecting the phe-
notype of either the paternal grandparents or the maternal grandparents. The developmental network
taken depends on which parental network initiates development. In this case the maternal genome starts
development. Compare with Fig.8j inverse development when execution starts at the paternal network.
3.1 Similarities and differences in brothers, sisters and grandparents
Protocol partitioning might explain the phenomenon of why some brothers and sisters can be
so alike and others be and look so different. Each child is a mixture of maternal and paternal
characteristics due to activation of different system-sectioned developmental networks. It also
explains why children often have the characteristics of their grandparents since developmental
networks that were inactive in the parent are now active in the child.
Thus, a commonly observed example is that of a developing child that looks very much like
the mother or grandmother at 8 years but then looks like the father’s family at 12, and so on.
Furthermore, since the previously established multicellular structures of sections in a partition
influences growth dynamics of the next phase of partitioning, mixtures that are not recognizable
as resulting from either parent become possible.
4 Each diploid genome has at least two execution pathways
A curious feature of any Turn-Taking protocol is that whichever player or haploid genome starts
first, changes the entire execution pathway (Def.4). The executed protocol instance (Def.2)
will, in general, depend on whether the execution starts on the Maternal genome network or on
the Paternal genome network. Let G be the complete genome of an MCO, GM the maternal
haploid genome in G and GP the paternal haploid genome in G. G=GM ⊗GP where ⊗
represents the protocol of interaction between the haploid genomes.
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Principle 2 (Dual Paths). For any diploid genome G =GM ⊗GP there are at least two
execution paths (maternal and paternal) through the global network NG. The maternal exe-
cution path starts from the root node of the 1st-order maternal developmental network GM.
The paternal execution path starts from the root node of the 1st-order paternal developmental
network GP.
Fig. 6: Two different protocol executions of the same genome
A diploid genome consisting a maternal haploid genome GM (Row 2) and a paternal haploid genome
GP (Row 4) and a protocol signature (Row 3). There are at least two execution pathways for any Turn-
Taking strategy. The execution pathway of the protocol depends on which haploid genome starts the
executing its network first. If it it starts at the Maternal haploid genome GM, then the executed network
path, is shown in Row 1. If the execution starts at the Paternal haploid genome GP then the executed
network path is shown in in Row 5. Caution, this is a highly abstracted, idealized example that does not
take into account the nonlinear, parallel nature of the execution of 1st and 2nd order reciprocal, dual
developmental control networks.
Principle 3 (Dual Partitions). Two different execution pathways result in two different parti-
tions of the developing organism.
Principle 2and Principle 3together imply that any diploid genome of bilaterians has at least
two different execution paths and these different execution paths can result in very different
developmental phenotypes.
4.1 One of Darwin’s puzzles solved
The Principles 2and 3solve and explain a long standing conundrum that puzzled Darwin [1]
and remained unresolved until now. It is the open question: Why do reciprocal hybrid crosses
have such distinct behavioral, physical and functional phenotypes?
The Solution: The difference in phenotype of hybrid crosses results from the different, recip-
rocal activation of parental haploid genomes.
More rigorously:
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Proposition 2 (Reciprocal Hybrid Crosses). Given two species S1 and S2 with Maternal
S1GM and Paternal S1GP and Maternal S2GM and Paternal S2GP haploid genomes,
1. If in reciprocal crosses the maternal genome is activated first, then the cross S1M x S2P
activates S1GM first and the reciprocal cross S2M x S1P activates S2GM first.
2. Or vice versa, if in reciprocal crosses the paternal genome is activated first, then the
cross S1M x S2P activates S2GP first and the reciprocal cross S2M x S1P activates
S1GP first.
Hence, by Principle 2, for each alternative, there are two different Execution Pathways through
the global developmental network. By Principle 3, this results in two different phenotypes of
reciprocal crosses.
Thus the different phenotype of reciprocal crosses is the result of the activation of opposite
haploid genomes by the two crosses. The reciprocal activation of G1 is the activation of the
opposite haploid genome G2. The difference in phenotype of a hybrid cross and its recipro-
cal cross results from the differential activation of two different, opposing, reciprocal haploid
protocols (meta-network signatures).
4.2 Imprinting and parent of origin effect
The standard explanation of the difference of reciprocal crosses is that it is the result of im-
printing, a parent of origin effect. This however says little more than that the phenotype of the
offsprings is different because the genomes are somehow marked by methylation or something
else. In contrast, Prop 2provides a precise explanation of the phenomenon. More on hybrids
and imprinting in a later chapter.
4.3 A fundamental question about male and female development
Given each genome has at least two execution pathways (Principles 2,3), could it be that males
and females develop reciprocally on different haploid genome execution pathways?
For example, if the child is female, development might activate the maternal haploid genome
and its ensuing maternal execution pathway. If the child is male, the reciprocal paternal haploid
genome might be activated and its resulting paternal execution pathway. Or the opposite, where
a female child first boots up the paternal execution pathway and the male starts the maternal
execution pathway.
If so, this would be consistent with hybrid reciprocal cross development (Prop.2) as well as
possible inverse development of diploid organisms (Prop.3) when the genomes and their pro-
tocols sufficiently mirror each other.
Interestingly, some supporting experimental results come from early mammalian development.
The early development of the mammalian embryo gives different roles to the paternal and
maternal haploid genomes[2,14,15,20–24,26,28,31,33,47,48]. More on this in coming
chapters.
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4.4 Invisible twins: Genomically identical but phenotypically different
Principles 2,3imply that it is theoretically possible to have two individuals that are genomi-
cally identical but morphologically and perhaps even functionally distinct. In any inter-network
protocol the execution path depends on which network is started first. Thus a given signature
has at least two different execution pathways. And since the two execution signatures are differ-
ent, they each partition the developing organism differently, which results in different emerging
phenotypes. Therefore, if one twin is the result of the maternal execution pathway while the
other is generated by the paternal execution pathway, such invisible twins can have, and usu-
ally will have, distinct appearances as well as different neurological, mental, behavioral and
physical functionality.
4.5 False twins: Phenotypically identical but genomically different
It is also possible that the executed network of two individuals is identical and thus they are
phenotypically identical, but their non-executed developmental subnetworks, i.e., their non-
activated segments of their otherwise identical genome, can be very different. If two individu-
als have an identical execution pathway through a dominant signature, they develop identically
into what appear to be identical twins. However, their genomes may differ in the 1st-order
networks that would be activated had the reciprocal signature that was not executed, been
executed. Hence, if these complementary 1st-order networks were skipped by the dominant
signature then two genomically different individuals can be phenotypically identical. There-
fore, it is possible to have false twins that are truly identical in all aspects of their development.
Just their genomes may differ up to 50%. This is possible because these divergent reciprocal
networks are never executed.
4.6 Hidden cancer networks
Since an execution pathway can skip whole networks, potential cancer networks[78] may ex-
ist in an organism that will not appear until they become part of the execution pathway in
a future offspring. Thus, one distinguishes 1st-order cancer networks from protocol induced
2nd-order cancer networks. More on this in the upcoming chapter on Pathologies and Malfor-
mations.
5 Mirror protocols generate inverse partitions
When the reciprocal, haploid protocols mirror each other the two execution pathways generate
inverse partitions of the developing organism. In other words, mirror protocols generate in-
verted partitions where the two section types of the partition are transposed, switching places
and ownership (Fig.7).
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5.1 Mirror networks and duality of inverted partitioning
Recall in Sec.4we showed that each protocol signature has at least two different execution
pathways through the network. When the two reciprocal 1st-order networks are sufficiently
homologous, and are in one-to-one correspondence, and the meta-links mirror each other, then
the two execution paths lead to reciprocal, inverted partitions where the ownership of sections
is inverted.
When haploid protocols do not mirror each other, reciprocal cross partitions would no longer be
inverted. However, there can be degrees of inverse partitioning 5.3. The extent of inversioning
of reciprocal partitions may vary with time as the embryo develops, as will be illustrated below
(Fig.8).
(a) Maternal genome start
(b) Paternal genome start
Fig. 7: Inverse development by the execution of the dual reciprocal mirror networks The
embryo develops as the inverse of the other mirror network. The top figure 7a shows the maternal
execution path and the corresponding developed MCO when development is started at the top maternal
haploid genome. The bottom fig. 7b shows the paternal execution path when development is initiated at
the reciprocal bottom paternal haploid genome network. The resulting MCOs have inverted partitions.
Proposition 3 (Inverse Partitions). If the reciprocal execution paths of two haploid networks
mirror each other, then the reciprocal generated multicellular systems are inversely parti-
tioned.
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5.2 Mirror networks generate dynamic inverted development
(a) 2 Cells (b) 4 Cells (c) 8 Cells (d) 16 cells
(e) 32 Cells (f) 36 Cells (g) 40 Cells (h) 52 Cells (i) 80 Cells
———————————————————————————–
(j) 2 Cells (k) 4 Cells (l) 8 Cells (m) 16 Cells
(n) 28 Cells (o) 36 Cells (p) 60 Cells (q) 90 Cells (r) 136 Cells
Fig. 8: Dynamic complementary development with partially inverted partitioning caused
by execution of partial mirroring reciprocal networks. The top development repeats Fig.5. The
bottom development result from execution of the reciprocal network. The network signatures (2nd-oder
networks) mirror each other. Hence, partitioning starts out as inverted and some body segments remain
inverted. However, while the 1st-order networks are homologous early in development, they are not
fully homologous downstream. The early network homology followed by later downstream separation
of network homology, results early inverse partitioned development followed by a gradual distancing of
inverted partition homology.
Given the haploid parental genomes are completely homologous and their signatures mirror
each other, then the reciprocal hybrid organisms have inverse, complementary partitions at each
stage of development, from the embryo to their adult form. In Fig.8we have an example where
the hybrids have inverse partitions early in development but then diverge later because the
genomes are not fully homologous. Their 1st-order developmental networks differ somewhat
downstream. Note, that some body segments, (e.g., head, midsection, tail) remain inverted
throughout development.
Cite As: Werner, E., Inter-network protocols partition all bilaterians: Internet of Life Chp. 2, 2020, DOI: *insert DOI here*
Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 15
5.3 Degrees of mirror inversion of partitions
The closer the hybrid species the more their signatures mirror one another and therefore the
greater the inverted development of the hybrids. This implies that reciprocal hybrids (see Prop.
2) undergo inverted mirror, complementary dual development to the extent that their networks
are homologous.
For the Null Protocol (Sec.6) the reciprocal, maternal and paternal execution path signatures
are null. And, thus, they trivially mirror each other. Therefore by Prop.3the generated MCOs
should be inversely partitioned. And, trivially, they are. Each is the total inverse partition of
the other, at least to the extent that the 1st-order networks are homologous.
5.4 Mules and hinnies, a case of inverse development?
Regarding reciprocal hybrids (Sec.4.1) an interesting, somewhat controversial, but thought pro-
voking example: Reciprocal horse and donkey crosses generate mules and hinnies. Generally,
the face and head of a mule is said to be more like the donkey, its body more like a horse, and
its legs like a donkey. In contrast, the head of the reciprocal hinny has a head is more like a
horse, the body more like donkey, and the legs like a horse. Indeed, the modules of the brains
of donkey’s and hinny’s appear to be inversely partitioned as well. The behavior of the mule
is more like that of a donkey (more intelligent, less docile) while the behavior of the hinny is
more like that of a horse (less intelligent, more docile). Granted these intellectual, emotional,
behavioral attributes may, in part, be due to the difference in maternal embryonic context and
later parenting, but the tendencies appear to support the inverse partitioning hypothesis.
Because of the great variation in phenotype, conformation and behavior in the parents of mules
and hinnies statistical averages of phenotype, conformation and behavior of hinnies and mule
would merge any overt differences when looking at each case. Each individual case could
support protocol principles while the statistical average may not. Thus, statistical averaging
can lead to false conclusions that hinnies and mules are not very different in phenotype.
6 The Null Protocol
For the sake of formal completeness, there is the special case of the Null Protocol: The Null
Protocol is a Turn-Taking Protocol where one side takes all the turns. Then only one of the
two parental haploid genome networks always has control of development. It is as if the other
genome network did not exist. Note, by definition a Null Protocol is nonrandom since there is
no interaction and hence no random interaction between genomes.
6.1 The haploid genomes generate distinct MCOs
A computational example of the Null Protocol is shown in Fig.9. Since there are no trans-links
and hence no interaction between parental genomes under the Null Protocol, two different
parental haploid networks generate two different multicellular organisms. Each develops sep-
arately, exclusively controlled by its own haploid genome.
Cite As: Werner, E., Inter-network protocols partition all bilaterians: Internet of Life Chp. 2, 2020, DOI: *insert DOI here*
Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 16
(a) Maternal Net
Stained
(b) Maternal
Segments
(c) Null Protocol Networks
top Maternal, bottom Paternal
(d) Paternal
Segments
(e) Paternal Net
Stained
Fig. 9: The Null Interaction Protocol (NP). Computationally designed, morphologically distinct, 3-
segmented maternal (M) and paternal (P) multicellular organisms (MCOs) grown from a single cell
(zygote). Each zygote contains both the maternal and paternal haploid genomes. In the Null Protocol
there is no interaction (no meta-links) between the top (Maternal) and bottom (Paternal) 1st-oder net-
works in Fig.9c. The cells controlled by the Maternal network are stained Aquamarine in the MCO
in Fig.9a and result from the execution of the top pure maternal haploid network in Fig.9c. Cells con-
trolled by the Paternal network are stained Purple in the MCO in Fig.9e and are generated by the
bottom paternal haploid genome network in Fig.9c. In the non-stained views of maternal Fig.9b and
paternal Fig.9d MCOs, different cell colors indicate distinct segment differentiation states.
In Fig.9the morphology and the differentiation states of the maternal and paternal offsprings
differ. With the Null Protocol if a haploid genome network is activated in a cell it runs sepa-
rately, independent of the other haploid genome. If run separately with no inter-network coor-
dination, then each haploid genome network generates a morphologically distinct organism to
the extent that the 1st-order networks differ.
6.2 Implementation of the Null Protocol in living systems
Whether the Null Protocol applied to a living organism actually develops to term, is an open
question, as there are difficulties for uniparental genome development for mammalians[2,14,
15,20–24,26,28,31,33,47,48]. In the case of mammalians the meta-network signature
would have to be reengineered to transform the given paternal or maternal haploid protocol
into the purely self-referential Null Protocol.
7 Discussion
7.1 Properties of protocols
Computer simulations show that any nonrandom interaction protocol dynamically partitions
the organism into nonintersecting sections exclusively controlled by either the maternal or the
paternal haploid genome network. At any given time, all cells in a given section are controlled
by one parental haploid genome network.
The partition is dynamic with sections changing identity, splitting or merging as the organism
develops. The developmental effects of later partition states are superposed on earlier develop-
mental states leading to complex mixtures of ancestrally inherited phenotypes.
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Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 17
The superposition of later on earlier developmental stages implies morphologies, functionali-
ties and capacities may appear to merge or even conflict. However, each change in the partition
state is the result of a discrete saltation of regulatory control.
Each protocol has an identifying meta-network signature. Different protocol signatures parti-
tion the developing organism differently leading to different morphologies and capacities both
mental and physical.
As protocols and developmental networks diverge new species and phyla can emerge. For any
diploid species their haploid protocols must cooperate to generate a coherent, complete and
consistent embryo. If the two haploid protocols of potential sex partners diverge too much,
network disfunction causes developmental pathologies, miscarriage or unviability.
7.2 How are inter-network protocols implemented in living cells?
Since the concepts introduced here and in Chapter 1 of this series are so new, readers have
suggested it would help to relate these concepts to the standard genetic model of development
and evolution. How are meta-network protocols molecularly implemented in genomes and
cells?
The trans-links in the meta-network protocol might be implemented as transcription factors
that jump from one parental genome to the other. Then the transcription factor activates the
1st-order network on the other parent’s genome.
Or they may be RNA sequences, or RNA-DNA structures, or a combination of protein car-
riers plus an RNA address, much like the Argonaute protein that cam carry RNA or DNA
addresses[66,71,87,104,132,134,135,138], or something similar to the CRISPR-Cas
protein-RNA address combination[85,90,105,108,109,123–127].
Yet another possibility is that chromosomes meet at trans-link points by physically connecting
and touching each other thereby allowing their networks to form a trans-link[50,99,122,130,
131]. Nature always has a way of surprising us with its creative solutions.
At present how protocols and their cis- and trans-links are realized molecularly is a fascinat-
ing open question awaiting experimental and theoretical research. See Sec.8.5 for further
open research questions, including higher-level questions of how protocols are encoded in
genomes.
7.3 Sex is complicated! Gynandromorphs and trans gender animals
As was shown in the gynandromorph paper [81], a kind of trans-link switch generates dual-
sex individuals. However, the sex of an organism appears to be orthogonal to the partitioning
protocol. Two individuals of different sex may be partitioned by the same protocol. They
may have the same developmentally induced partitioning but with sections having different sex
identities, induced by additionally activated, sex-based networks. Thus, sex is an additional
dimension of network control. Partitioned hybrids that are also gynandromorphs are fascinating
Cite As: Werner, E., Inter-network protocols partition all bilaterians: Internet of Life Chp. 2, 2020, DOI: *insert DOI here*
Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 18
special cases illustrating these complex relationships between partitioning protocols and sex
protocols. More on this in a later chapter on hybrids.
7.4 Partitioning and the network paradigm
The partitioning hypothesis is so radical, departing from all that we believe, that any scientist
will be tempted to disregard it, to stop reading, to turn away with incredulity or fear. Yet, I am
forced by logic to state it. It is the inference that one is forced to make if we accept the ex-
istence of such a universal protocol as defined by meta-networks between the complementary,
cooperating, competing developmental control networks in the parental genomes.
How could this have been missed all these years? It is so simple and yet has remained hidden
from our science. The reason, of course, is that the dogmatic gene-centered, molecular view of
development and evolution cannot even express it, and therefore, it cannot even be imagined.
So it is with major shifts in our understanding of ourselves and our world. While the hypothesis
itself may be astonishing, its fascinating implications and explanatory power may justify its
further investigation.
8 Conclusion
8.1 A Unifying theoretical framework
Intriguing is the similarity, the unity, of normal, pathological, hybrid and gynandromorph par-
titioning, all by way of a meta-network, trans-link architecture, namely, the protocol signature.
Thereby, we have a unified explanatory theoretical framework that accounts for a broad range
of seemingly unrelated phenomena.
8.2 Evolutionary and developmental explanatory power
Meta-network protocols provide a new, complimentary explanation and understanding of em-
bryonic and post-embryonic development, the inheritance of mental and physical capacities,
human pathologies and malformations, animal and plant hybrids, heterosis, gynandromorphs,
species formation and evolution.
This exhibits the extraordinary explanatory power of the network theory of development and
evolution. It opens new doors to a deeper understanding of developmental biology and the
evolution of species.
8.3 Pragmatic import
Moreover, it has potential pragmatic value. It allows for the modification and transformation
of protocols through manipulation of their trans-links. This opens the door for future biotech-
nological innovation for human and animal health, for animal and crop heterosis by design,
for corrective signature transformations for otherwise painful and/or debilitating human mal-
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Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 19
formations and for cancers caused by protocol inconsistencies[78]. This will be discussed in
greater detail in the chapter on protocol induced pathologies.
8.4 Highlights of discoveries
We have reported several fundamental, new discoveries that hold for all bilaterians which
have existed since the Cambrian Explosion. There are also applications to non-bilaterians
like plants.
1. Non-random protocols control bilaterian development: For ALL sexually reproduc-
ing bilaterally symmetric organisms, the interaction protocol between parental haploid
genomic networks must be non-random[137].
2. Embryos and adults are partitioned: At each point in time in development, any meta-
network between parental haploid 1st-order networks that implements a non-random
interaction protocol between those parental networks, partitions the resulting organism
into sections derived from one or the other parent (Sec.2.1 ).
3. Different protocol signatures generate different partitions:(Sec.2.2)
4. Fluctuating control makes partitioning dynamic: The parental ownership (origin) and
locus of such sections will in general vary over the spatial-temporal development of the
embryo into its adult form (Sec.3).
This gives a novel, detailed explanation of developmental pathologies as well as many
common phenomena: Thus a daughter will vary in appearance back and forth, from one
parent’s family to the other as she develops all the way to adulthood (Sec.3.1).
5. There are at least two execution pathways through a diploid genome: Two execution
paths lead to two different partitions of the developing organism. (Sec.4)
6. Darwin’ Puzzle Solved - Reciprocal hybrids, hybrid formation and heterosis: The
difference in phenotype of hybrid crosses results from the different, reciprocal activation
of parental haploid genomes.(Sec.4.1)
7. Heterosis by design: Heterosis or hybrid vigor and hybrid failure depends on how com-
patible, consistent and complete the 1st-order and 2nd-order networks are. The combina-
tion of two different species involves two distinct meta-network protocols and different
1st-order networks and with possibly different or incompatible sets of genes. Note, this
includes all sexually reproducing species, not just bilaterians. With the new genome
editing technology offered by Argonaute and CRISPR-like methods[66,71,87,104,
132,134,135,138], [85,90,105,108,109,123–127], the meta-network protocol model
has direct application to heterosis by design. More on this in an upcoming publication.
8. Invisible twins are possible developmental outcomes: Invisible twins are twins that
have the same genome but opposite, reciprocal execution pathways, will usually have
different phenotypes (Sec.4.4).
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Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 20
9. False twins are possible developmental outcomes: False twins have identical execu-
tion pathways, but their reciprocal networks (with non-activated execution paths) can
be very different. Hence, for false twins, their non-executed genome networks are non-
identical even though they are phenotypically identical. (Sec. 4.5)
10. Hidden cancer networks: Cancer network can exist in the non-active execution path-
way. Such cancer networks could be expressed in the next generation. (Sec.4.6 )
11. Mirror protocols generate inverse development:(Sec.5) We mentioned the mule -
hinny reciprocal hybrids as a possible example.
12. Species formation: Given the uncomfortable fact that we share many of our genes with
worms, fly’s and chimps, most species and even kingdoms are separated not by their
genes but by their 1st-order and 2nd-order developmental networks. As interaction pro-
tocols between potential sexual partners diverge the offspring becomes unviable at some
point in its development from egg to embryo to adult. This is a 1st-order network and
2nd-order meta-network barrier between species and phyla beyond their genetics.
13. Pathologies of development: Protocol disturbances present an entirely different way of
seeing pathologies of development. This will be the subject of another chapter.
8.5 Open questions
Any new theory should raise numerous new questions. Questions that have never been asked
before. Questions that have never been asked because the concepts have never been imagined.
Below are open questions that await cooperative research.
I am willing to cooperate with any researcher, research groups and research labs who
want to seek answers.
•How did the first ur-protocol form?
•What is the relationship of crossing over and the evolution of signature creation?
•To what extent is the signature in a species fixed?
•How are body plans and protocols related?
•Was the Cambrian Explosion a time of protocol fluidity and experimentation?
•To what extent are species and phylum boundaries determined by protocol incompatibil-
ities?
•What is the role of protocols in the evolution of species and phyla?
•To what extent does crossing over and independent assortment of homologous chromo-
somes during meiosis influence the structure of the signature?
•What is the nature of the 1st-order developmental network code in genomes?
Cite As: Werner, E., Inter-network protocols partition all bilaterians: Internet of Life Chp. 2, 2020, DOI: *insert DOI here*
Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 21
•What is the 2nd-order code that creates the meta-network protocol, the signature between
haploid genomes?3
•How do the codes interconnect to form a hierarchy of control in the developing organ-
ism?
The encoding of 1st-order and 2nd-order networks and the code hierarchy in genomes will be
a topic of further papers that discuss the informational architecture of genomes and cells (but
in the meantime see [61,79,86,103]).
9 Glossary of definitions and principles
Terminology: Aprotocol is implemented as a set of meta-network links (cis-links, trans-
links, 2nd-order links) between two haploid genome networks. Thus, a protocol is a 2nd-order
network between the 1st-order networks contained in the haploid genomes.
A protocol connecting two or more networks contains two types of meta-links: Cis-links and
trans-links. A trans-link connects two different networks, a source-network to a target-network.
Acis-link connects a network to itself. It is a self-link where the source-network and target-
network are the same. A cis-trans switch transforms a cis-link to a trans-link or vice versa
resulting in the potential activation of the reciprocal, opposite network.
A protocol between two haploid genome networks consists of two haploid protocols, one for
each haploid genome. The paternal haploid protocol consists of cis-links and trans-links going
from the paternal haploid genome to the maternal haploid genome. The maternal haploid
protocol consists of cis-links and trans-links going from the maternal haploid genome to the
paternal haploid genome. The haploid protocols interact to form the total protocol.
Principle 1(Partitioning) Non-random Turn-Taking protocol dynamically partitions the developing bilateral embryo into sec-
tions exclusively controlled by one or the other haploid genome 1st-order network.
Definition 1(Signature) The signature of a Turn-Taking protocol is the set of meta-network links (also called trans-links,2nd-
order links,inter-network links) between two haploid genome 1st-order networks.
Definition 2 (Execution Signature). The execution signature or protocol instance is the subset of possible 2nd-order, inter-
network links that are actually executed by any cell as the organism develops.
Definition 3 (Execution Pathway (Execution History, Run History)). The execution pathway of a network is the subset (sub-
network) of all 1st and 2nd-oder links and nodes (developmental histories) of the total network that are actually traversed by any
cell of the developing organism as that cell interprets and executes its copy of the total developmental network.
Definition 4 (Execution Potential). The execution potential of a network is the subset (subnetwork) of all possible 1st and
2nd-oder links and nodes of the total network that can possibly be traversed by any cell of the developing organism as that cell
interprets and executes its copy of the total developmental network4.
Principle 2(Dual Paths) For any diploid genome G =GM +GP there are at least two execution paths through the global network
NG. Starting from the root node of NGM leads to one execution path while starting from the root node NGP leads to the second
execution path. Other secondary and hidden execution paths are possible. Let GM be the maternal genome, GP the paternal
genome, G is the global genome (the union of GM and GP), NG is the global developmental network, NGP is the developmental
network of GP and NGM is the maternal developmental network.
3See Sec.7.2 for preliminary speculations on how trans-links of protocols might be implemented.
4The execution potential differs from the execution pathway when a link has multiple targets that are chosen
probabilistically.
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Eric Werner Protocols partition all bilaterians: Internet of Life Chp 2 22
Principle 3(Dual Partitions) Two different execution pathways result in two different partitions of the developing organ-
ism.
Proposition 2(Reciprocal Hybrid Crosses Given two species S1 and S2 with Maternal S1GM and Paternal S1GP and Maternal
S2GM and Paternal S2GP haploid genomes,
1. If in reciprocal crosses the maternal genome is activated first, then the cross S1M x S2P activates S1GM first and the
reciprocal cross S2M x S1P activates S2GM first.
2. Or vice versa, if in reciprocal crosses the paternal genome is activated first, then the cross S1M x S2P activates S2GP
first and the reciprocal cross S2M x S1P activates S1GP first.
Hence, by Principle 2, for each alternative, there are two different Execution Pathways through the global developmental network.
By Principle 3, this results in two different phenotypes of reciprocal crosses.
Principle 4 (Signature Partition Correspondence). Given the 1st-order parental genome networks remain constant, then there
is a correspondence between the execution signature and the sectioning of the growing organism.
Definition 5 (Ownership). The local haploid, parental developmental network that controls development of a set or section or
module of cells is said to own that cell, section or module.
Principle 5 (Partitioning Ownership). Non-random Turn-Taking protocols dynamically partition the developing embryo into
sections of varying network ownership while maintaining bilateral symmetry.
Proposition 3(Inverse Partitions) If the reciprocal execution paths of two haploid networks mirror each other, then the reciprocal
generated multicellular systems are inversely partitioned.
Definition 6 (Complement). The complement of an execution pathway is the set of all 1st and 2nd-order links in the global
network that are not in the execution pathway.
Proposition 4 (Inaccessible Hidden Networks). For any two execution pathways N1, N2, of a protocol π, the complement N0 of
N1 union N2, i.e., N0=N1∪N2, is never executed by either N1 or N2. Therefore, it has no phenotypic effect in normal or hybrid
reciprocal crosses. Let Ωbe the total genome network. N0=(Ω∖N1)∖N2=N1∪N2=N1∖N2 since Ω∖N1=Ω∩N1=N1.
Thus, if N0=N1∪N2 is nonempty, the potential networks it represents are never executed by either N1 or N2. It is effectively
inaccessible by N1 and N2. These are hidden assets or hidden liabilities that could be expressed by a different protocol π2.
10 Materials and Methods
All the computational experiments described here were designed and performed using genCADTM
multicellular modeling and simulation software. The software suite genCADTM allows the user to run
genomes of designed multicellular organism. Each run starts with a single cell which, once activated
by the user, develops into a 3-dimensional multicellular organism. Cell signaling, cell-cell physics can
be modeled in both discrete and continuous space-time. In concert with the developing cells, a window
shows the user graphically how genome network states change in a highly dynamic way. At any point
in development, growth can be stopped, continued or rebooted. Any particular cell state, the whole
multicellular state, or the genome state can be investigated or transformed graphically by the user. Then
development can be continued or restarted. For more about genCADTM email: contact@gencad.net
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