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High-Throughput Single Nucleotide Polymorphism (SNP) Discovery and Validation Through Whole-Genome Resequencing in Nile Tilapia (Oreochromis niloticus)

Abstract

Nile tilapia (Oreochromis niloticus) is the second most important farmed fish in the world and a sustainable source of protein for human consumption. Several genetic improvement programs have been established for this species in the world. Currently, the estimation of genetic merit of breeders is typically based on genealogical and phenotypic information. Genome-wide information can be exploited to efficiently incorporate traits that are difficult to measure into the breeding goal. Thus, single nucleotide polymorphisms (SNPs) are required to investigate phenotype–genotype associations and determine the genomic basis of economically important traits. We performed de novo SNP discovery in three different populations of farmed Nile tilapia. A total of 29.9 million non-redundant SNPs were identified through Illumina (HiSeq 2500) whole-genome resequencing of 326 individual samples. After applying several filtering steps, including removing SNP based on genotype and site quality, presence of Mendelian errors, and non-unique position in the genome, a total of 50,000 high-quality SNPs were selected for the development of a custom Illumina BeadChip SNP panel. These SNPs were highly informative in the three populations analyzed showing between 43,869 (94%) and 46,139 (99%) SNPs in Hardy-Weinberg Equilibrium; 37,843 (76%) and 45,171(90%) SNPs with a minor allele frequency (MAF) higher than 0.05; and 43,450 (87%) and 46,570 (93%) SNPs with a MAF higher than 0.01. The 50K SNP panel developed in the current work will be useful for the dissection of economically relevant traits, enhancing breeding programs through genomic selection, as well as supporting genetic studies in farmed populations of Nile tilapia using dense genome-wide information.

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Data Availability

The sequence data used for SNP discovery and the 50K SNP chip developed here belongs to Aquainnovo/AquaChile, and it can be available upon reasonable request.

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Acknowledgments

We would like to acknowledge the Aqua America and Aquacorporación Internacional for kindly providing the samples used in this work, and Gabriel Rizzato and Natalí Kunita from Aqua America and Diego Salas and José Soto from Aquacorporación International for their contribution of the samples from Brazil and Costa Rica, respectively.

Funding Information

This study was partially funded from CORFO grant number 14EIAT-28667 from the Government of Chile. This work was supported by the Basal grant of the Center for Mathematical Modeling AFB170001 (UMI2807 UCHILE-CNRS) and the Center for Genome Regulation Fondap Grant 15090007 Powered@NLHPC. This research was partially supported by the supercomputing infrastructure of the NLHPC (ECM-02).

Author information

J.M.Y. conceived of and designed the study, contributed to the analysis, and drafted the manuscript. G.Y. contributed to the analysis and writing. A.B. drafted the first version of the manuscript. G.C., M.E.L., and A.J. participated in the data collection, purification, and management of the samples for sequencing and genotyping. R.P., D.D., D.T., and A.M. assisted with the bioinformatics analysi and contributed to writing. J.P.L. participated in the design of the study and writing. JS and DS contributed to the collection of the samples and managmenent of populations from Costa Rica. All authors have reviewed and approved the manuscript.

Correspondence to José M. Yáñez.

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Conflict of Interest

Two commercial organizations (Aquainnovo and Illumina) were involved in the SNP identification and preparation of the manuscript. GMY and JPL were employed by Benchmark Genetics Chile during the course of the study.

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Yáñez, J.M., Yoshida, G., Barria, A. et al. High-Throughput Single Nucleotide Polymorphism (SNP) Discovery and Validation Through Whole-Genome Resequencing in Nile Tilapia (Oreochromis niloticus). Mar Biotechnol (2020) doi:10.1007/s10126-019-09935-5

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Keywords

  • SNP
  • Oreochromis niloticus
  • Next-generation sequencing
  • Illumina
  • Genomic selection