**4. A Systems Genomics Statistical Mechanics**

The heuristics leading to the here described consistent 3D genome organization has also resulted in another fundamental breakthrough besides merely clarifying the missing gap(s): the emergence of a multilistic systems statistical mechanics with uncertainty principles by reaching the fundamental resolution limits (see Section 2.1 above; [26]. Hence, this allows directly not only i) to extend the atomic theory based on ancient Greek philosophy and the notion of Theodor Schwann of cells being the fundamental atomic unit of tissues to the mesoscopic scale of genome architecture/dynamics, but also ii) to analyse and to describe how from the collective behaviour of these elements a holistic meta level, i.e. a phenotype, emerges. Thus, by reaching fundamental resolution limits now the statistical and uncertainty properties of each architectural/dynamic level can be determined both by experimental measurements as well as theoretical descriptions. Hence, from each of these "atomistic" basic units/elements their collective behaviour can be derived by a statistical mechanics on each individual level as wells as a complex interwoven scale-bridging, i.e. a hierarchic back referencing networked systems statistical mechanics - which obviously exists - can now be established in detail. This exceeds and is much more complex than establishing the statistical mechanics at the turn of the 20th century where from the individual components e.g. gas molecules a statistical mechanics established the collective properties of the entire system, e.g. the entire gas, because genome organization is not only a simple dualistic system of e.g. two levels but a complex multilistic network system with back references: In detail this means determining experimentally the behaviour of a genome structural/dynamic level precisely with its entire statistics and then doing the same on the level emerging from the underlying level. In principle this is what we have started already by setting up an experimental and theoretic framework over the past 20 years to elucidate genome organization [7, 18–24, 26, 27, 49, 50], although only now with the complete description of the general 3D genome architecture/ dynamics it is possible to fill the existing lack of knowledge in detail, determine the values for parameters with high precision, and in constant cycles of refinement adjust the description to an ever higher degree of approximation. Thus, the difference to the development of statistical mechanics in classical and later quantum physics at the turn to the 20th century is that in biology many and also much higher levels still are determined by and also act back even on the very first level to a much higher degree. This also immediately unites the at first sight contradicting theoretic descriptions of living systems of Ilia Prigogine [75], stating that living systems are far away from thermodynamic equilibrium, with those proposed by Georgi Gladyshev [76] stating that hierarchic substance stability is locally in thermodynamic equilibrium. Actually, these descriptions are even extended due to the multilistic statistical systems mechanics, i.e. manifold recursive hierarchically back-referencing, which are until now not described but e.g. envisioned in efforts to extend quantum mechanics to higher order complexities [77]. Consequently, a genomic multilistic statistical systems mechanics allows not only to describe and test basic properties of life, but also to answer perhaps the most fundamental questions of life as e.g. whether life time-wise can be extended beyond the currently obvious or thought of limits by manipulated engineering in one of its most central parts - the genome - a quest of epic dimensions appearing already at least between the lines in "What Is Life ?" by Erwin Schrödinger [78].

in terms of replication disentanglement it is. Consequently, replication origins can be situated and start replication everywhere in each chromatin loop with replication forks leading towards both directions until they hit a loop base (which is the reason for the bidirectional CTCF sites functioning as linear DNA markers for the directional oriented replication machinery). During this procedure even the twist and writhe are copied and need to be untangled as in the case of transcription. While hitting the loop bases then the two forks coming from two loops have to be joined and untangled, but no complex network of knots as they would appear even in a Random-Walk/Giant-Loop or even more so in a fractal globule like replication scenario would have to be cut and re-joined. Again here theoretical predictions for loop size and loop numbers are just fitting the experimental findings (see e.g. [39] and thereafter). Due to the two-dimensional topology of the multi-loop aggregates/rosettes, they can just be separated very easily in 3D space (this idea was proposed and illustrated to the author by his at the time 6 year old son Leander Aurelius!). And again the compaction and volume occupancy in the cell nucleus play an important role: the compaction into a chromatin fibre reduces not only the formation of DNA knots largely (perhaps almost to zero), but also provides with the volume occupancy in the cell nucleus the room for undisturbed replication, with the right flexibility provided by the intrinsic dynamics, allowing the disentanglement of replicated structures with minimal e.g. topoisomerase/decatenase driven active processes. In summary, the above proves even further and especially in a holistic combination with the presented new orthogonal approaches [26, 27] and including the heuristics of the field, that indeed the described 3D genome organization - DNA forming nucleosomes compacted into a quasi-fibre folded into stable loops, forming stable multi-loop aggregates/rosettes connected by linkers creating chromosome arms and entire chromosomes (**Figure 1**) - presents without doubt a consistent scale bridging systems statistical mechanics genomics fulfilling the functional conditions necessary for storage, transcription, and replication. Additionally, the actual values found for the various parameters involved are just found in those "regions" one would expect as the unavoidable outcome of Darwinian natural selection and Lamarkian

self-referenced manipulation (see below).

82 Chromatin and Epigenetics

**4. A Systems Genomics Statistical Mechanics**

The heuristics leading to the here described consistent 3D genome organization has also resulted in another fundamental breakthrough besides merely clarifying the missing gap(s): the emergence of a multilistic systems statistical mechanics with uncertainty principles by reaching the fundamental resolution limits (see Section 2.1 above; [26]. Hence, this allows directly not only i) to extend the atomic theory based on ancient Greek philosophy and the notion of Theodor Schwann of cells being the fundamental atomic unit of tissues to the mesoscopic scale of genome architecture/dynamics, but also ii) to analyse and to describe how from the collective behaviour of these elements a holistic meta level, i.e. a phenotype, emerges. Thus, by reaching fundamental resolution limits now the statistical and uncertainty properties of each architectural/dynamic level can be determined both by experimental
