When exploring statistical properties of genetic sequences two main features stand out: the existence of non-random structures at various scales (e. g., long-range correlations ) and the presence of symmetries (e.g., Chargaff parity rules). In the last decades, numerous studies investigated the origin and significance of each of these features separately . Here we show that both symmetry and structure have to be considered as the outcome of the same biological processes, whose cumulative effect can be quantitatively measured on extant genomes. We present a novel analysis (based on a minimal model) that not only explains and reproduces previous observations but also predicts the existence of a nested hierarchy of symmetries emerging at different structural scales. Our genome-wide analysis of H. Sapiens confirms the theoretical predictions .
Biologists have long sought a way to explain how statistical properties of genetic sequences emerged and are maintained through evolution. On the one hand, non-random structures at different scales indicate a complex URLanisation. On the other hand, single-strand symmetry has been scrutinised using neutral models in which correlations are not considered or irrelevant, contrary to empirical evidence. Different studies investigated these two statistical features separately, reaching minimal consensus despite sustained efforts . Here we unravel previously unknown symmetries in genetic sequences, which URLanized hierarchically through scales in which non-random structures are known to be present. These observations are confirmed through the statistical analysis of the human genome and explained through a simple domain model. These results suggest that domain models which account for the cumulative action of mobile elements can explain simultaneously non-random structures and symmetries in genetic sequences .
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When exploring
Biologists have long sought a way to explain how
R
two main features stand out: the existence of
emerged and are maintained through evolution. On the one hand,
R
various scales (e. g., long-range correlations ) and the presence of symmetries (e.g., Chargaff parity rules). In the last decades, numerous studies investigated the origin and significance of each of these features separately
different scales indicate a complex URLanisation. On the other hand, single-strand symmetry has been scrutinised using neutral models in which correlations are not considered or irrelevant, contrary to empirical evidence. Different studies investigated these two statistical features separately, reaching minimal consensus despite sustained efforts
R
show that both symmetry and structure have to be considered as the outcome of the same biological processes, whose cumulative effect can be quantitatively measured on extant genomes. We present a novel analysis (based on a minimal model) that not only explains and reproduces previous observations but also predicts the existence of a nested hierarchy of symmetries emerging at different structural scales. Our genome-wide analysis of H. Sapiens confirms the theoretical predictions
unravel previously unknown symmetries in genetic sequences, which URLanized hierarchically through scales in which non-random structures are known to be present. These observations are confirmed through the statistical analysis of the human genome and explained through a simple domain model. These results suggest that domain models which account for the cumulative action of mobile elements can explain simultaneously non-random structures and symmetries in genetic sequences