scholarly journals Ligation of random oligomers leads to emergence of autocatalytic sequence network

2020 ◽  
Author(s):  
Patrick W. Kudella ◽  
Alexei V. Tkachenko ◽  
Sergei Maslov ◽  
Dieter Braun
Keyword(s):  
Dna Sequences ◽  
Information Entropy ◽  
Theoretical Work ◽  
Temperature Oscillation ◽  
Temperature Cycling ◽  
Darwinian Evolution ◽  
Dependent Sequence ◽  
Sequence Patterns ◽  
Plausible Mechanism ◽  
Selection For

ABSTRACTThe emergence of longer information-carrying and functional nucleotide polymers from random short strands was a major stepping stone at the dawn of life. But the formation of those polymers under temperature oscillation required some form of selection. A plausible mechanism is template-based ligation where theoretical work already suggested a reduction in information entropy.Here, we show how nontrivial sequence patterns emerge in a system of random 12mer DNA sequences subject to enzyme-based templated ligation reaction and temperature cycling. The strands acted both as a template and substrates of the reaction and thereby formed longer oligomers. The selection for templating sequences leads to the development of a multiscale ligation landscape. A position-dependent sequence pattern emerged with a segregation into mutually complementary pools of A-rich and T-rich sequences. Even without selection for function, the base pairing of DNA with ligation showed a dynamics resembling Darwinian evolution.

scholarly journals IIMLP: integrated information-entropy-based method for LncRNA prediction

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Junyi Li ◽  
Huinian Li ◽  
Xiao Ye ◽  
Li Zhang ◽  
Qingzhe Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Dna Sequences ◽  
Information Entropy ◽  
Area Under The Curve ◽  
Prediction Method ◽  
Machine Learning Algorithms ◽  
Reading Frame ◽  
Non Coding Rna ◽  
The One ◽  
Long Non Coding Rna

Abstract Background The prediction of long non-coding RNA (lncRNA) has attracted great attention from researchers, as more and more evidence indicate that various complex human diseases are closely related to lncRNAs. In the era of bio-med big data, in addition to the prediction of lncRNAs by biological experimental methods, many computational methods based on machine learning have been proposed to make better use of the sequence resources of lncRNAs. Results We developed the lncRNA prediction method by integrating information-entropy-based features and machine learning algorithms. We calculate generalized topological entropy and generate 6 novel features for lncRNA sequences. By employing these 6 features and other features such as open reading frame, we apply supporting vector machine, XGBoost and random forest algorithms to distinguish human lncRNAs. We compare our method with the one which has more K-mer features and results show that our method has higher area under the curve up to 99.7905%. Conclusions We develop an accurate and efficient method which has novel information entropy features to analyze and classify lncRNAs. Our method is also extendable for research on the other functional elements in DNA sequences.

scholarly journals Onset of natural selection in auto-catalytic heteropolymers

2017 ◽  
Author(s):  
Alexei V. Tkachenko ◽  
Sergei Maslov
Keyword(s):  
Natural Selection ◽  
Theoretical Model ◽  
Information Entropy ◽  
Physical System ◽  
Driving Forces ◽  
Darwinian Evolution ◽  
Living Matter ◽  
Spontaneous Reduction ◽  
Nano Structures ◽  
Opening Up

Reduction of information entropy along with ever-increasing complexity are among the key signatures of living matter. Understanding the onset of such behavior in early prebiotic world is essential for solving the problem of origins of life. To elucidate this transition, we study a theoretical model of information-storing heteropolymers capable of template-assisted ligation and subjected to cyclic non-equilibrium driving forces. We discover that this simple physical system undergoes a spontaneous reduction of the information entropy due to the competition of chains for constituent monomers. This natural-selection-like process ultimately results in the survival of a limited subset of polymer sequences. Importantly, the number of surviving sequences remains exponentially large, thus opening up the possibility of further increase in complexity due to Darwinian evolution. We also propose potential experimental implementations of our model using either biopolymers or artificial nano-structures.

Maintenance of genetic variability by mutation–selection balance: a child's guide through the jungle

Genome ◽  
1989 ◽  
Vol 31 (2) ◽  
pp. 761-767 ◽  
Author(s):  
M. G. Bulmer
Keyword(s):  
Genetic Variability ◽  
Theoretical Work ◽  
Complex Problem ◽  
Recurrent Mutation ◽  
Mutation Rates ◽  
Stabilizing Selection ◽  
House Of Cards ◽  
Model Account ◽  
Optimal Value ◽  
Selection For

Metric characters closely connected with fitness have little additive genetic variability, presumably because it is quickly exhausted under continuous directional selection on fitness. Other metric characters have substantial additive genetic variability with a typical heritability of about 0.5. A popular model is that the second class of characters is subject to weak stabilizing selection for an optimal value, which depletes genetic variability, while recurrent mutation tends to restore it. Can this model account for the variability observed, given the evidence available about the strength of selection and mutation rates? Much theoretical work has been done on this complex problem. This work is reviewed, with the intention of simplifying it as much as possible.Key words: mutation–selection balance, genetic variability, continuum-of-alleles model, house-of-cards approximation.

scholarly journals Isolated clusters of paired tandemly repeated sequences in the Xenopus laevis genome.

1984 ◽  
Vol 4 (2) ◽  
pp. 254-259 ◽  
Author(s):  
D Carroll ◽  
J E Garrett ◽  
B S Lam
Keyword(s):  
Xenopus Laevis ◽  
Dna Sequences ◽  
Tandem Repeats ◽  
Genomic Organization ◽  
Evolutionary Conservation ◽  
Repeated Dna ◽  
Flanking Sequence ◽  
Base Pairs ◽  
Selection For ◽  
Tandemly Repeated Dna

There exist in the Xenopus laevis genome clusters of tandemly repeated DNA sequences, consisting of two types of 393-base-pair repeating unit. Each such cluster contains several units of one of these paired tandem repeats (PTR-1), followed by several units of the other repeat (PTR-2). The number of repeats of each type is variable from cluster to cluster and averages about seven of each type per cluster. Every cluster has ca. 1,000 base pairs of common left flanking sequence (adjacent to the PTR-1 repeats) and 1,000 base pairs of common right flanking sequence (adjacent to the PTR-2 repeats). Beyond these common flanks, the DNA sequences are different in the eight cloned genomic fragments we have studied. Thus, the hundreds of PTR clusters in the genome are dispersed at apparently unrelated sites. Nucleotide sequences of representative PTR-1 and PTR-2 repeats are 64% homologous. These sequences do not reveal an obvious function. However, the related species X. mulleri and X. borealis have sequences homologous to PTR-1 and PTR-2, which show the same repeat lengths and genomic organization. This evolutionary conservation suggests positive selection for the clusters. Maintenance of these sequences at dispersed sites imposes constraints on possible mechanisms of concerted evolution.

Isolated clusters of paired tandemly repeated sequences in the Xenopus laevis genome

1984 ◽  
Vol 4 (2) ◽  
pp. 254-259
Author(s):  
D Carroll ◽  
J E Garrett ◽  
B S Lam
Keyword(s):  
Xenopus Laevis ◽  
Dna Sequences ◽  
Tandem Repeats ◽  
Genomic Organization ◽  
Evolutionary Conservation ◽  
Repeated Dna ◽  
Flanking Sequence ◽  
Base Pairs ◽  
Selection For ◽  
Tandemly Repeated Dna

There exist in the Xenopus laevis genome clusters of tandemly repeated DNA sequences, consisting of two types of 393-base-pair repeating unit. Each such cluster contains several units of one of these paired tandem repeats (PTR-1), followed by several units of the other repeat (PTR-2). The number of repeats of each type is variable from cluster to cluster and averages about seven of each type per cluster. Every cluster has ca. 1,000 base pairs of common left flanking sequence (adjacent to the PTR-1 repeats) and 1,000 base pairs of common right flanking sequence (adjacent to the PTR-2 repeats). Beyond these common flanks, the DNA sequences are different in the eight cloned genomic fragments we have studied. Thus, the hundreds of PTR clusters in the genome are dispersed at apparently unrelated sites. Nucleotide sequences of representative PTR-1 and PTR-2 repeats are 64% homologous. These sequences do not reveal an obvious function. However, the related species X. mulleri and X. borealis have sequences homologous to PTR-1 and PTR-2, which show the same repeat lengths and genomic organization. This evolutionary conservation suggests positive selection for the clusters. Maintenance of these sequences at dispersed sites imposes constraints on possible mechanisms of concerted evolution.

scholarly journals KIS: An automated attribute induction method for classification of DNA sequences

2012 ◽  
Vol 22 (3) ◽  
pp. 711-721 ◽  
Author(s):  
Rafał Biedrzycki ◽  
Jarosław Arabas
Keyword(s):  
Dna Sequences ◽  
Splice Sites ◽  
Induction Method ◽  
Sequence Recognition ◽  
Iron Responsive Element ◽  
Reference Methods ◽  
Donor And Acceptor ◽  
Sequence Patterns ◽  
Responsive Element

Abstract This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites. We also show how to use the algorithm to find a human readable model of the IRE (Iron-Responsive Element) and to find IRE sequences. The method, although universal, yields results which are of quality comparable to those obtained by reference methods. In contrast to reference methods, this approach uses models that operate on sequence patterns, which facilitates interpretation of the results by humans.

scholarly journals Self-Reproduction and Darwinian Evolution in Autocatalytic Chemical Reaction Systems

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 308
Author(s):  
Sandeep Ameta ◽  
Yoshiya J. Matsubara ◽  
Nayan Chakraborty ◽  
Sandeep Krishna ◽  
Shashi Thutupalli
Keyword(s):  
Experimental Evolution ◽  
Experimental Studies ◽  
Theoretical Work ◽  
Living System ◽  
Darwinian Evolution ◽  
Chemical System ◽  
Chemical Systems ◽  
Open Questions ◽  
Scientific Questions ◽  
Emergence Of Life

Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as “a self-sustaining chemical system capable of Darwinian evolution”. It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.

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