Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Biology >> Biological Evolution Subjects: Biology >> Biomathematics Subjects: Physics >> Interdisciplinary Physics and Related Areas of Science and Technology Subjects: Biology >> Genetics submitted time 2023-10-15
Zhang, Zecheng
Liu, Chunxiuzi
Zhu, Yingjun
Peng, Lu
Qiu, Weiyi
Tang, Qianyuan
Liu, He
Zhang, Ke
Di, Zengru
Liu, Yu
Abstract： Background: In bioinformatics, tools like multiple sequence alignment and entropy methods probe sequence information and evolutionary relationships between species. Although powerful, they might miss crucial hierarchical relationships formed by the reuse of repetitive subsequences like duplicons and transposable elements. Such relationships are governed by “evolutionary tinkering'', as described by Fran c{c}ois Jacob. The newly developed Ladderpath theory provides a quantitative framework to describe these hierarchical relationships.
Results: Based on this theory, we introduce two indicators: order-rate $ eta$, characterizing sequence pattern repetitions and regularities, and ladderpath-complexity $ kappa$, characterizing hierarchical richness within sequences, considering sequence length. Statistical analyses on real amino acid sequences showed: (1) Among the typical species analyzed, humans possess relatively more sequences with large $ kappa$ values. (2) Proteins with a significant proportion of intrinsically disordered regions exhibit increased $ eta$ values. (3) There are almost no super long sequences with low $ eta$. We hypothesize that this arises from varied duplication and mutation frequencies across different evolutionary stages, which in turn suggests a zigzag pattern for the evolution of protein complexity. This is supported by our simulations and examples from protein families such as Ubiquitin and NBPF.
Conclusions: Our method emphasizes “how objects are generated'', capturing the essence of evolutionary tinkering and reuse. The findings hint at a connection between sequence orderliness and structural uncertainty, and suggest that different species or those in varied environments might adopt distinct protein elongation strategies. These insights highlight our method's value for further in-depth evolutionary biology applications.
Peer Review Status:
Awaiting Review
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science Subjects: Physics >> Interdisciplinary Physics and Related Areas of Science and Technology submitted time 2022-08-15
Abstract： The notion of information and complexity are important concepts in many scientific fields such as molecular biology, evolutionary theory and exobiology. Many measures of these quantities are either difficult to compute, rely on the statistical notion of information, or can only be applied to strings. Based on assembly theory, we propose the notion of a ladderpath, which describes how an object can be decomposed into hierarchical structures using repetitive elements. From the ladderpath two measures naturally emerge: the ladderpath-index and the order-index, which represent two axes of complexity. We show how the ladderpath approach can be applied to both strings and spatial patterns and argue that all systems that undergo evolution can be described as ladderpaths. Further, we discuss possible applications to human language and the origin of life. The ladderpath approach provides an alternative characterization of the information that is contained in a single object (or a system) and could aid in our understanding of evolving systems and the origin of life in particular.
Hits
Hits
Downloads
Comment
YES