The RNA World is currently the most plausible hypothesis for explaining the origins of life on Earth. The supporting body of evidence is growing and it comes from multiple areas, including astrobiology, chemistry, biology, mathematics, and, in particular, from computer simulations. Such methods frequently assume the existence of a hypothetical species on Earth, around three billion years ago, with a base sequence probably dissimilar from any in known genomes. However, it is often hard to verify whether or not a hypothetical sequence has the characteristics of biological sequences, and is thus likely to be functional. The primary objective of the presented research was to verify the possibility of building a computational `life probe' for determining whether a given genetic sequence is biological, and assessing the sensitivity of such probes to the signatures of life present in known biological sequences. We have proposed decision algorithms based on the normalized compression distance (NCD) and Levenshtein distance (LD). We have validated the proposed method in the context of the RNA World hypothesis using short genetic sequences shorter than the error threshold value (i.e., 100 nucleotides). We have demonstrated that both measures can be successfully used to construct life probes that are significantly better than a random decision procedure, while varying from each other when it comes to detailed characteristics. We also observed that fragments of sequences related to replication have better discriminatory power than sequences having other molecular functions. In a broader context, this shows that the signatures of life in short RNA samples can be effectively detected using relatively simple means.
@ARTICLE { JTB2019,
ABSTRACT = { The RNA World is currently the most plausible hypothesis for explaining the origins of life on Earth. The supporting body of evidence is growing and it comes from multiple areas, including astrobiology, chemistry, biology, mathematics, and, in particular, from computer simulations. Such methods frequently assume the existence of a hypothetical species on Earth, around three billion years ago, with a base sequence probably dissimilar from any in known genomes. However, it is often hard to verify whether or not a hypothetical sequence has the characteristics of biological sequences, and is thus likely to be functional. The primary objective of the presented research was to verify the possibility of building a computational `life probe' for determining whether a given genetic sequence is biological, and assessing the sensitivity of such probes to the signatures of life present in known biological sequences. We have proposed decision algorithms based on the normalized compression distance (NCD) and Levenshtein distance (LD). We have validated the proposed method in the context of the RNA World hypothesis using short genetic sequences shorter than the error threshold value (i.e., 100 nucleotides). We have demonstrated that both measures can be successfully used to construct life probes that are significantly better than a random decision procedure, while varying from each other when it comes to detailed characteristics. We also observed that fragments of sequences related to replication have better discriminatory power than sequences having other molecular functions. In a broader context, this shows that the signatures of life in short RNA samples can be effectively detected using relatively simple means. },
AUTHOR = { Szymon Wasik and Natalia Szostak and Mateusz Kudla and Michal Wachowiak and Krzysztof Krawiec and Jacek Blazewicz },
DOI = { https://doi.org/10.1016/j.jtbi.2018.12.018 },
ISSN = { 0022-5193 },
JOURNAL = { Journal of Theoretical Biology },
KEYWORDS = { Genetic sequence, Normalized compression distance, Edit distance, Compression, RNA World, },
PAGES = { 110 - 120 },
TITLE = { Detecting life signatures with RNA sequence similarity measures },
URL = { http://www.sciencedirect.com/science/article/pii/S0022519318306155 },
VOLUME = { 463 },
YEAR = { 2019 },
1 = { http://www.sciencedirect.com/science/article/pii/S0022519318306155 },
2 = { https://doi.org/10.1016/j.jtbi.2018.12.018 },
}