Status and future perspectives of single nucleotide polymorphisms (SNPs) markers in farmed fishes: Way ahead using next generation sequencing

Abstract

The progress in the sequencing technology has significantly augmented single nucleotide polymorphism (SNPs) discovery and genotyping in fish genetic research. The affordable cost, development in Next Generation Sequencing (NGS) technology and computational tool has rationalized SNPs discovery in various model and non-model aquaculture species. The SNPs linked with biological part on a genomic scale is expected to provide new insights into the fish biology, evolution and physiology. Alongside, recently developed SNPs arrays are a powerful tool for understanding genomic patterns of fish diversity, phylogeny in fish populations and marker–trait associations. These SNPs arrays or chips are a valuable for genetic studies in fish species like genomic selection, Quantitative Trait Locus (QTL) detection, and genetic diversity studies. Here, we have discussed for SNPs discovery using advanced sequencing techniques for understanding genomic level information in fishes and provide a future perspective. We have speculated the impact analysis of SNPs on the genes/proteins, which rationalize further experimental study. This review focuses on high-throughput sequencing technologies has used for SNPs identification studies in fishes with evidence. This review will simplify process for mining SNPs from important genes associated with the production/performance traits for conducting genomic selection program in aquaculture.

Introduction

Now a day, molecular biology field has been progressing from sequencing and mapping of fish genomes towards understanding genomic functions specifically (Li et al., 2011). Also, this progress significantly heightened the single nucleotide polymorphism (SNP) discovery in non-model fish species. The use of molecular markers, single nucleotide polymorphism (SNP) and Simple Sequence Repeats is becoming marker of choice for genetic studies in fishes (Garvin et al., 2010, Sundaray et al., 2016). For exploring a large number of SNPs linked to economically important traits associated with disease, stress and other traits, high-throughput sequencing technologies provides a reasonable platform.

The SNPs are the most abundant type of the DNA sequence polymorphism or variants which has significant role in genetic studies (Hinds, 2005, Danzmann et al., 2016). Thus, SNPs is becoming the marker of choice because of their large numbers in almost all populations of individuals for genome-wide association studies as well as QTL mapping (Baranski et al., 2014, Qi et al., 2014, Robinson et al., 2014, Zhong et al., 2014). The SNPs are enormous in number, bi-allelic in nature as well as co-dominant, and scattered along the genome. Besides, identified SNPs can be used as markers to distinguish allelic-transcripts while studying the allele-specific expression (Ulloa et al., 2015). Many SNPs markers have been identified in plants, humans and mammals, which are evenly scattered along the genome. Also, in aquaculture species, SNPs are being used as a genomic resource such as development genetic linkage map for fish species such as in Atlantic cod (Hubert et al., 2010).

The transcriptome data will be serve as source for SNPs detection, whenever lack of genome map of non-model species (Bester et al., 2008, Chakrapani et al., 2016). This NGS and Bioinformatics field made it possible to screen the genome of many non-model species followed by large-scale SNPs discovery associated with the genome (Garvin and Gharrett, 2010, Garvin et al., 2010). Also, SNP markers are most popular molecular markers because of the possibility of being linked with different phenotypes or genotypes of interest. Now a day high-density SNP genotyping platforms are available Sheep (Clarke et al., 2014), Pig (Ramos et al., 2009), Catfish (Liu et al., 2014), and Atlantic salmon (Houston et al., 2014, Tsai et al., 2016, Yanez et al., 2016). Among those identified SNPs, nonsynonymous SNPs which are present in the coding region of gene could have impact on its gene function. These predictions can be done using advanced computational algorithms based on sequence-structure evolution (Rasal et al., 2016).

In this review, we have speculated the use of high-throughput sequencing technologies in genomic research specifically for SNPs identification. We also deliberated the use of computational algorithms/tools for variant or SNP characterization. Therefore, integrative analysis of biological systems of fishes carries forward with the help of advanced sequencing technologies and computational tools. The identified SNPs in genes associated with performance and production traits allows geneticists to select fish with superior genetic material for future generations by genomic selection. Thus, SNPs discovery useful for genome wide investigation and development of high-density SNP panels or array by high-throughput genotyping in fish to impose genomic selection program.