Background Atlantic salmon (Salmo Salar) is a key aquaculture species in several countries. Since its critical role in economic sector and scientific research, this species has been relatively extensively investigated, in comparison with other farmed and wild aquatic species. However, the genetic components associated with growth and fillet-related traits are lack consistency, and the issue of sea louse disease in both wild and famed salmon is still unsolved. Objectives Overall aim of this project was to understand the genetic basis of growth-related traits and host resistance to sea lice using three large commercial farmed salmon populations. Specifically, the method of quantitative trait loci (QTL) mapping, genome-wide association study (GWAS), and genomic prediction (GS) were utilized to dissect the genetic architectures associated with traits of interest in our experimental populations. Prior to this, linkage mapping was performed to construct a high-density linkage map for Atlantic salmon. Results Linkage map A linkage map was firstly constructed underlying a SNP array containing 132 K validated SNPs. 96,396 SNPs were successfully assigned to 29 chromosomes that correspond to the linkage group number of European Atlantic salmon. 6.5 % of unassigned contigs, which was equal to 1 % of recent whole genome reference assembly (GCA_000233375.4) anchored to exist chromosomes by referring to linkage mapping result. Genetic components associated with growth traits Heritabilities of growth-related traits were about 0.5 to 0.6 in adult and juvenile farmed salmon. The QTL mapping and GWAS suggested the growth-related traits are likely a polygenic genetic architecture with no major QTL segregating. The prediction accuracy estimated by genomic prediction showed that approximately 5,000 SNP markers could achieve the highest accuracy in body weight and length in juvenile salmon within population. Genetic components associated with lice resistance The heritability of lice resistance was 0.22 to 0.33 using pedigree and genetic relationship matrices respectively. GWAS indicated that the host resistance to sea lice was likely polygenic with no individual SNP surpassed the genome-wide significance threshold. Genomic prediction showed that about 5 to 10 K SNPs was able to achieve the asymptote of accuracy in closely related animals, while the greatest advantage of genomic prediction was observed in non-sibling test within population. Conclusions As the growth-related traits and lice resistance are both likely polygenic and population-specific, the genomic prediction is an efficient approach to capture the genetic variances of the traits in selection candidates in experimental population, especially for traits with low heritability such as flesh colour and lice resistance. Family-based selection method is the better choice than mass selection to accumulate the genetic effects in corresponding SNP platform. Given the high cost of genotyping and field data collection, the genotyping-by-sequencing and genotype imputation are likely the way to make significant improvements in relevant research.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:738840 |
| Date | January 2017 |
| Creators | Tsai, Hsin Yuan |
| Contributors | Houston, Ross |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/28918 |
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