Dataset Information

Whole-Genome Sequence of Streptococcus agalactiae Strain S13, Isolated from a Fish Eye from a Nile Tilapia Farm in Southern Brazil.

ABSTRACT: Streptococcus agalactiae is an important pathogen to world aquaculture due to its high mortality rates in fish farms and consequent economic losses. Our study presents the complete genome sequence of strain S13, isolated from a tilapia farm outbreak in southern Brazil.

SUBMITTER: Facimoto CT

PROVIDER: S-EPMC5578858 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Publications

Whole-Genome Sequence of <i>Streptococcus agalactiae</i> Strain S13, Isolated from a Fish Eye from a Nile Tilapia Farm in Southern Brazil.

Facimoto César T CT Chideroli Roberta T RT Gonçalves Daniela D DD Carmo Anderson O do AOD Kalaphotakis Evanguedes E Pereira Ulisses de Pádua UP

Genome announcements 20170831 35

<i>Streptococcus agalactiae</i> is an important pathogen to world aquaculture due to its high mortality rates in fish farms and consequent economic losses. Our study presents the complete genome sequence of strain S13, isolated from a tilapia farm outbreak in southern Brazil. ...[more]

PMID: 28860260

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Project description:BackgroundStreptococcosis is a major bacterial disease in Nile tilapia that is caused by Streptococcus agalactiae infection, and development of resistant strains of Nile tilapia represents a sustainable approach towards combating this disease. In this study, we performed a controlled disease trial on 120 full-sib families to (i) quantify and characterize the potential of genomic selection for survival to S. agalactiae infection in Nile tilapia, and (ii) identify the best genomic model and the optimal density of single nucleotide polymorphisms (SNPs) for this trait.MethodsIn total, 40 fish per family (15 fish intraperitoneally injected and 25 fish as cohabitants) were used in the challenge test. Mortalities were recorded every 3 h for 35 days. After quality control, genotypes (50,690 SNPs) and phenotypes (0 for dead and 1 for alive) for 2472 cohabitant fish were available. Genetic parameters were obtained using various genomic selection models (genomic best linear unbiased prediction (GBLUP), BayesB, BayesC, BayesR and BayesS) and a traditional pedigree-based model (PBLUP). The pedigree-based analysis used a deep 17-generation pedigree. Prediction accuracy and bias were evaluated using five replicates of tenfold cross-validation. The genomic models were further analyzed using 10 subsets of SNPs at different densities to explore the effect of pruning and SNP density on predictive accuracy.ResultsModerate estimates of heritabilities ranging from 0.15 ± 0.03 to 0.26 ± 0.05 were obtained with the different models. Compared to a pedigree-based model, GBLUP (using all the SNPs) increased prediction accuracy by 15.4%. Furthermore, use of the most appropriate Bayesian genomic selection model and SNP density increased the prediction accuracy up to 71%. The 40 to 50 SNPs with non-zero effects were consistent for all BayesB, BayesC and BayesS models with respect to marker id and/or marker locations.ConclusionsThese results demonstrate the potential of genomic selection for survival to S. agalactiae infection in Nile tilapia. Compared to the PBLUP and GBLUP models, Bayesian genomic models were found to boost the prediction accuracy significantly.

Dataset Information

Whole-Genome Sequence of Streptococcus agalactiae Strain S13, Isolated from a Fish Eye from a Nile Tilapia Farm in Southern Brazil.

Publications

Whole-Genome Sequence of <i>Streptococcus agalactiae</i> Strain S13, Isolated from a Fish Eye from a Nile Tilapia Farm in Southern Brazil.

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