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Using Evolutionary Analyses to Refine Whole-Genome Sequence Match Criteria.
Arthur W Pightling1, Hugh Rand1, James Pettengill1
1Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD, United States.
Frontiers in Microbiology
|July 25, 2022
Summary
Whole-genome sequencing data is expanding, prompting new evolutionary analyses. For Salmonella enterica, an evolutionary rate of 1.97 single-nucleotide polymorphisms per year is proposed for genome sequence matching.
Area of Science:
- Microbiology
- Genomics
- Evolutionary Biology
Background:
- Whole-genome sequence databases are rapidly expanding.
- Increasing time between sample collections presents challenges for comparing recent and historical genomic data.
- This temporal data offers opportunities for evolutionary analyses to refine matching criteria.
Purpose of the Study:
- To measure evolutionary rates for 22 Salmonella enterica serotypes.
- To propose a standardized evolutionary rate for genome sequence matching.
Main Methods:
- Analysis of whole-genome sequence data from 22 Salmonella enterica serotypes.
- Calculation of evolutionary rates based on single-nucleotide polymorphism (SNP) accumulation over time.
Main Results:
- Evolutionary rates were determined for 22 Salmonella enterica serotypes.
- A proposed evolutionary rate of 1.97 single-nucleotide polymorphisms (SNPs) per year was established.
Conclusions:
- The proposed evolutionary rate can enhance the accuracy of matching Salmonella enterica genome sequences.
- Utilizing evolutionary rates is crucial for interpreting genomic data in the context of sample collection timing.
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