De novo Assembly and Characterization of Patagonian Toothfish Transcriptome and Develop of EST-SSR Markers for Population Genetics

2019 
Patagonian toothfish (Dissostichus eleginoides) is a hefty notothenioid fish and a key species within the marine ecosystem with a high migratory capacity across sub-Antarctic and south American Pacific oceans. Transcriptome characterization and molecular markers associated with micro and macro-evolutionary studies are not available, which in turn limits the gain of knowledge about the genetic basis of this species. Therefore, in the present study, a de novo transcriptome from eight tissue and an embryonic state of Patagonian toothfish was developed, using the Illumina Hiseq 4000 platform. A total of 233,424 superTranscripts were assembled and 37,446 annotated against public databases. Moreover, we identified 71,107 expressed sequence tag-simple sequence repeats (EST-SSRs), with an average number of 0.3 SSRs per superTranscripts and one SSR per 1.12kB. The most abundant SSR type was repeated dinucleotide (53.67%), followed by trinucleotide (13.73%) repeats. From the total of EST-SSRs identified, 34,196 primer pairs were properly designed and a subset of twenty-five immune loci were selected for its evaluation as potential EST-SSR population markers. Of this subset, eleven proved to have good technical features and were evaluated in 64 animals from four Patagonian toothfish populations. A number of 63 alleles were identified, with a mean of 4.9 alleles per locus and a polymorphism information content ranging from 0.224 to 0.591, with a mean of 0.50. Significant (FST, range 0.082-0.117 and G´ST, range 0.069-0.291) genetic differentiation (P<0.05) was determined among the populations analyzed. Therefore, the results presented here represent a relevant genetic resource for biological studies on evolution, conservation, genetic diversity, population structure and genetic management of breeding stocks of this important species.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    68
    References
    3
    Citations
    NaN
    KQI
    []