Range-limited Heaps' law for functional DNA words in the human genome
Wentian Li1, Yannis Almirantis2, Astero Provata3
1Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA(1); The Robert S. Boas Center for Genomics and Human Genetics, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
Journal of Theoretical Biology
|June 20, 2024
Summary
Heaps' law, a linguistic principle, is demonstrated in the human genome by defining DNA words as protein-coding regions. This study confirms its existence in genomes, offering insights into protein domain evolution.
Area of Science:
- Genomics
- Computational Biology
- Bioinformatics
Background:
- Heaps' law describes the relationship between vocabulary size (types) and word count (tokens) as a power-law function.
- Its application to genomes is debated due to differing definitions of 'DNA words' and smaller dictionary sizes compared to human language.
Purpose of the Study:
- To investigate the applicability of Heaps' law to the human genome.
- To define 'DNA words' as protein-coding regions and analyze their relationship with Heaps' law.
- To explore the implications for understanding protein domain evolution and genomic linguistics.
Main Methods:
- Defined 'DNA words' as genomic coding regions for protein domains.
- Analyzed human chromosomes and chromosome arms as individual samples.
- Applied Heaps' law analysis and quadratic regression on log-log type-token plots.
- Examined several animal genomes for comparative analysis.
Main Results:
- Established the existence of a range-limited Heaps' law in the human genome using the defined 'DNA words'.
- Observed deviations from Heaps' law at maximum sample sizes, but quadratic regression provided an excellent fit.
- Demonstrated similar range-limited Heaps' law in various animal genomes, with differing exponents.
Conclusions:
- Heaps' law is applicable to the human genome when DNA words are defined as protein-coding regions.
- The study provides a novel linguistic perspective on protein domain reusage, redundancy, and creation.
- Genomic analysis of Heaps' law offers insights into evolutionary processes and the structure of biological information.
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