Unknown

Dataset Information

0

Using Evolutionary Analyses to Refine Whole-Genome Sequence Match Criteria.


ABSTRACT: Whole-genome sequence databases continue to grow. Collection times between samples are also growing, providing both a challenge for comparing recently collected sequence data to historical samples and an opportunity for evolutionary analyses that can be used to refine match criteria. We measured evolutionary rates for 22 Salmonella enterica serotypes. Based upon these measurements, we propose using an evolutionary rate of 1.97 single-nucleotide polymorphisms (SNPs) per year when determining whether genome sequences match.

SUBMITTER: Pightling AW 

PROVIDER: S-EPMC9301902 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

altmetric image

Publications

Using Evolutionary Analyses to Refine Whole-Genome Sequence Match Criteria.

Pightling Arthur W AW   Rand Hugh H   Pettengill James J  

Frontiers in microbiology 20220616


Whole-genome sequence databases continue to grow. Collection times between samples are also growing, providing both a challenge for comparing recently collected sequence data to historical samples and an opportunity for evolutionary analyses that can be used to refine match criteria. We measured evolutionary rates for 22 <i>Salmonella enterica</i> serotypes. Based upon these measurements, we propose using an evolutionary rate of 1.97 single-nucleotide polymorphisms (SNPs) per year when determini  ...[more]

Similar Datasets

| S-EPMC10055830 | biostudies-literature
| S-EPMC5740155 | biostudies-literature
| S-EPMC10584648 | biostudies-literature
| S-EPMC3927822 | biostudies-literature
| S-EPMC6768097 | biostudies-literature
| S-EPMC2801616 | biostudies-literature
| S-EPMC5772158 | biostudies-literature
| S-EPMC5572866 | biostudies-literature
| S-EPMC7253450 | biostudies-literature
| S-EPMC6485071 | biostudies-literature