Different Resolution Power of Multilocus Variable-Number Tandem Repeat Analysis and Whole-Genome Sequencing in the Characterization of S. 1,4,[5],12:i:- Isolates

2019 ◽  
Vol 16 (8) ◽  
pp. 558-561
Author(s):  
Sara Petrin ◽  
Alessandra Longo ◽  
Lisa Barco ◽  
Enzo Cortini ◽  
Arianna Peruzzo ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Tandem Repeat ◽  
Variable Number Tandem Repeat ◽  
Variable Number ◽  
Whole Genome ◽  
Resolution Power ◽  
Repeat Analysis

scholarly journals Comparison of inferred relatedness based on multilocus variable-number tandem-repeat analysis and whole genome sequencing ofVibrio choleraeO1

2016 ◽  
Vol 363 (12) ◽  
pp. fnw116 ◽  
Author(s):  
Mahamud-ur Rashid ◽  
Mathieu Almeida ◽  
Andrew S. Azman ◽  
Brianna R. Lindsay ◽  
David A. Sack ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Tandem Repeat ◽  
Variable Number Tandem Repeat ◽  
Variable Number ◽  
Whole Genome ◽  
Repeat Analysis

scholarly journals Genetic Characterization of Brucella spp.: Whole Genome Sequencing-Based Approach for the Determination of Multiple Locus Variable Number Tandem Repeat Profiles

2021 ◽  
Vol 12 ◽  
Author(s):  
Ana Pelerito ◽  
Alexandra Nunes ◽  
Teresa Grilo ◽  
Joana Isidro ◽  
Catarina Silva ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
In Silico ◽  
Variable Number Tandem Repeat ◽  
Epidemiological Studies ◽  
Variable Number ◽  
Epidemiological Surveillance ◽  
Future Application ◽  
Whole Genome

Brucellosis is an important zoonosis that is emerging in some regions of the world, gaining increased relevance with the inclusion of the causing agent Brucella spp. in the class B bioterrorism group. Until now, multi-locus VNTR Analysis (MLVA) based on 16 loci has been considered as the gold standard for Brucella typing. However, this methodology is laborious, and, with the rampant release of Brucella genomes, the transition from the traditional MLVA to whole genome sequencing (WGS)-based typing is on course. Nevertheless, in order to avoid a disruptive transition with the loss of massive genetic data obtained throughout the last decade and considering that the transition timings will vary considerably among different countries, it is important to determine WGS-based MLVA alleles of the nowadays sequenced genomes. On this regard, we aimed to evaluate the performance of a Python script that had been previously developed for the rapid in silico extraction of the MLVA alleles, by comparing it to the PCR-based MLVA procedure over 83 strains from different Brucella species. The WGS-based MLVA approach detected 95.3% of all possible 1,328 hits (83 strains×16 loci) and showed an agreement rate with the PCR-based MLVA procedure of 96.4% for MLVA-16. According to our dataset, we suggest the use of a minimal depth of coverage of ~50x and a maximum number of ~200 contigs as guiding “boundaries” for the future application of the script. In conclusion, the evaluated script seems to be a very useful and robust tool for the in silico determination of MLVA profiles of Brucella strains, allowing retrospective and prospective molecular epidemiological studies, which are important for maintaining an active epidemiological surveillance of brucellosis.

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