The determinants of the rarity of nucleic and peptide short sequences in nature

Author:

Chantzi Nikol1,Mareboina Manvita1,Konnaris Maxwell A123,Montgomery Austin1,Patsakis Michail1,Mouratidis Ioannis13,Georgakopoulos-Soares Ilias1ORCID

Affiliation:

1. Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine , Hershey , PA , 17033,  USA

2. Department of Statistics, Penn State University , University Park , PA , 16802,  USA

3. Huck Institutes of the Life Sciences, Penn State University , University Park , PA , 16802,  USA

Abstract

Abstract The prevalence of nucleic and peptide short sequences across organismal genomes and proteomes has not been thoroughly investigated. We examined 45 785 reference genomes and 21 871 reference proteomes, spanning archaea, bacteria, eukaryotes and viruses to calculate the rarity of short sequences in them. To capture this, we developed a metric of the rarity of each sequence in nature, the rarity index. We find that the frequency of certain dipeptides in rare oligopeptide sequences is hundreds of times lower than expected, which is not the case for any dinucleotides. We also generate predictive regression models that infer the rarity of nucleic and proteomic sequences across nature or within each domain of life and viruses separately. When examining each of the three domains of life and viruses separately, the R² performance of the model predicting rarity for 5-mer peptides from mono- and dipeptides ranged between 0.814 and 0.932. A separate model predicting rarity for 10-mer oligonucleotides from mono- and dinucleotides achieved R² performance between 0.408 and 0.606. Our results indicate that the mono- and dinucleotide composition of nucleic sequences and the mono- and dipeptide composition of peptide sequences can explain a significant proportion of the variance in their frequencies in nature.

Funder

Huck Innovative and Transformational Seed Grant

Publisher

Oxford University Press (OUP)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A survey of k-mer methods and applications in bioinformatics;Computational and Structural Biotechnology Journal;2024-12

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