Large yellow croaker (Larimichthys crocea) is an important economic fish in China and Eastern Asia. Because of the exhaustive fishing and overdense aquaculture, the wild population and the mariculture of the species are facing serious challenges on germplasm degeneration and susceptibility to infectious disease agents. However, a comprehensive transcriptome from multi-tissues of the species has not been reported and functional molecular markers have not yet been detected and analyzed. In this work, we applied RNA-seq with the Illumina Hiseq2000 platform for a multi-tissue sample of large yellow croaker and assembled the transcriptome into 88,103 transcripts. Of them, 52,782 transcripts have been successfully annotated by nt/nr, InterPro, GO and KEGG database. Comparing with public fish proteins, we have found that 34,576 protein coding transcripts are shared in large yellow croaker with zebrafish, medaka, pufferfish, and stickleback. For functional markers, we have discovered 1,276 polymorphic SSRs and 261, 000 SNPs. The functional impact analysis of SNPs showed that the majority (~75%) of small variants cause synonymous mutations in proteins, followed by variations in 3' UTR region. The functional enrichment analysis illuminated that transcripts involved in DNA bindings, enzyme activities, and signal pathways prominently exhibit less single-nucleotide variants but genes for the constituent of the muscular tissue, the cytoskeleton, and the immunity system contain more frequent SNP mutations, which may reflect the structural and functional selections of the translated proteins. This is the first work for the high-throughput detection and analysis of functional polymorphic SSR and SNP markers in a comprehensive transcriptome of large yellow croaker. Our study provides valuable transcript sequence and functional marker resources for the quantitative trait locus (QTL) identification and molecular selection of the species in the research community.

The advances of sequencing technology accelerate the development of theory of molecular quantitative genetics such as QTL mapping, genome-wide association study and genomic selection. This paper was designed to study genomic selection in large yellow croaker breeding. The aims of this study were: (i) to estimate heritability values of traits in large yellow croaker; (ii) to assess feasibility of genomic selection in the traits of growth rate and meat quality; (iii) to compare predictive accuracies affected by different algorithms and training sizes, and to find what training sizes could reach ideal accuracies; (iv) to compare results of GWAS with genomic prediction, and to assess feasibility of pre-selection of significant SNPs in genomic selection. 500 individuals were tested in the trait of body weight and body length, while 176 were tested in the percentage of n-3 highly unsaturated fatty acids (n-3HUFA) in muscle. GBLUP and emBayesB were used to perform genomic prediction. Genotyping-By-Sequencing method was used to construct the libraries for the NGS sequencing and find ~30,000 SNPs. Heritability estimates were 0.604, 0.586 and 0.438 for trait of body weight, body length and n-3HUFA, respectively. The predictive abilities estimated by GBLUP showed higher than that by emBayesB in traits of body weight and body length. However, the result was just the opposite in n-3HUFA. According to fit the curve of predictive accuracy, we estimated that at least 1000 individuals in training set could reach an accuracy of 0.8 in body weight and body length. GBLUP, emBayesB and GWAS could not always find significant SNPs associated with phenotypes consistently. Significant SNPs were selected by emBayesB could obtain the largest proportions to explain total additive genetic variances. This research showed that genomic selection was feasible in large yellow croaker breeding. We suggest doing a test before deciding to use which algorithm in specific trait in genomic prediction. We estimated required training sizes to reach ideal predictive accuracies and assessed feasibility of pre-selection of SNPs successfully. Because of high mortality rate of fish and high cost in genomic sequencing, genomic selection may be more suitable for applying on some traits which cannot be measured on candidates directly.