Mitotic gene regulation by the N-MYC-WDR5-PDPK1 nexus.

BACKGROUND: During mitosis the cell depends on proper attachment and segregation of replicated chromosomes to generate two identical progeny. In cancers defined by overexpression or dysregulation of the MYC oncogene this process becomes impaired, leading to genomic instability and tumor evolution. Recently it was discovered that the chromatin regulator WDR5-a critical MYC cofactor-regulates expression of genes needed in mitosis through a direct interaction with the master kinase PDPK1. However, whether PDPK1 and WDR5 contribute to similar mitotic gene regulation in MYC-overexpressing cancers remains unclear. Therefore, to characterize the influence of WDR5 and PDPK1 on mitotic gene expression in cells with high MYC levels, we performed a comparative transcriptomic analysis in neuroblastoma cell lines defined by MYCN-amplification, which results in high cellular levels of the N-MYC protein. RESULTS: Using RNA-seq analysis, we identify the genes regulated by N-MYC and PDPK1 in multiple engineered CHP-134 neuroblastoma cell lines and compare them to previously published gene expression data collected in CHP-134 cells following inhibition of WDR5. We find that as expected N-MYC regulates a multitude of genes, including those related to mitosis, but that PDPK1 regulates specific sets of genes involved in development, signaling, and mitosis. Analysis of N-MYC- and PDPK1-regulated genes reveals a small group of commonly controlled genes associated with spindle pole formation and chromosome segregation, which overlap with genes that are also regulated by WDR5. We also find that N-MYC physically interacts with PDPK1 through the WDR5-PDPK1 interaction suggesting regulation of mitotic gene expression may be achieved through a N-MYC-WDR5-PDPK1 nexus. CONCLUSIONS: Overall, we identify a small group of genes highly enriched within functional gene categories related to mitotic processes that are commonly regulated by N-MYC, WDR5, and PDPK1 and suggest that a tripartite interaction between the three regulators may be responsible for setting the level of mitotic gene regulation in N-MYC amplified cell lines. This study provides a foundation for future studies to determine the exact mechanism by which N-MYC, WDR5, and PDPK1 converge on cell cycle related processes.

Coding and Noncoding Genes Involved in Atrophy and Compensatory Muscle Growth in Nile Tilapia.

Improvements in growth-related traits reduce fish time and production costs to reach market size. Feed deprivation and refeeding cycles have been introduced to maximize aquaculture profits through compensatory growth. However, the molecular compensatory growth signature is still uncertain in Nile tilapia. In this study, fish were subjected to two weeks of fasting followed by two weeks of refeeding. The growth curve in refed tilapia was suggestive of a partial compensatory response. Transcriptome profiling of starved and refed fish was conducted to identify genes regulating muscle atrophy and compensatory growth. Pairwise comparisons revealed 5009 and 478 differentially expressed (differential) transcripts during muscle atrophy and recovery, respectively. Muscle atrophy appears to be mediated by the ubiquitin-proteasome and autophagy/lysosome systems. Autophagy-related 2A, F-box and WD repeat domain containing 7, F-box only protein 32, miR-137, and miR-153 showed exceptional high expression suggesting them as master regulators of muscle atrophy. On the other hand, the muscle compensatory growth response appears to be mediated by the continuous stimulation of muscle hypertrophy which exceeded normal levels found in control fish. For instance, genes promoting ribosome biogenesis or enhancing the efficiency of translational machinery were upregulated in compensatory muscle growth. Additionally, myogenic microRNAs (e.g., miR-1 and miR-206), and hypertrophy-associated microRNAs (e.g., miR-27a-3p, miR-29c, and miR-29c) were reciprocally expressed to favor hypertrophy during muscle recovery. Overall, the present study provided insights into the molecular mechanisms regulating muscle mass in fish. The study pinpoints extensive growth-related gene networks that could be used to inform breeding programs and also serve as valuable genomic resources for future mechanistic studies.

Weighted Single-Step GWAS Identifies Genes Influencing Fillet Color in Rainbow Trout.

The visual appearance of the fish fillet is a significant determinant of consumers' purchase decisions. Depending on the rainbow trout diet, a uniform bright white or reddish/pink fillet color is desirable. Factors affecting fillet color are complex, ranging from the ability of live fish to accumulate carotenoids in the muscle to preharvest environmental conditions, early postmortem muscle metabolism, and storage conditions. Identifying genetic markers of fillet color is a desirable goal but a challenging task for the aquaculture industry. This study used weighted, single-step GWAS to explore the genetic basis of fillet color variation in rainbow trout. We identified several SNP windows explaining up to 3.5%, 2.5%, and 1.6% of the additive genetic variance for fillet redness, yellowness, and whiteness, respectively. SNPs are located within genes implicated in carotenoid metabolism (ß,ß-carotene 15,15'-dioxygenase, retinol dehydrogenase) and myoglobin homeostasis (ATP synthase subunit ß, mitochondrial (ATP5F1B)). These genes are involved in processes that influence muscle pigmentation and postmortem flesh coloration. Other identified genes are involved in the maintenance of muscle structural integrity (kelch protein 41b (klh41b), collagen α-1(XXVIII) chain (COL28A1), and cathepsin K (CTSK)) and protection against lipid oxidation (peroxiredoxin, superoxide dismutase 2 (SOD2), sestrin-1, Ubiquitin carboxyl-terminal hydrolase-10 (USP10)). A-to-G single-nucleotide polymorphism in ß,ß-carotene 15,15'-dioxygenase, and USP10 result in isoleucine-to-valine and proline-to-leucine non-synonymous amino acid substitutions, respectively. Our observation confirms that fillet color is a complex trait regulated by many genes involved in carotenoid metabolism, myoglobin homeostasis, protection against lipid oxidation, and maintenance of muscle structural integrity. The significant SNPs identified in this study could be prioritized via genomic selection in breeding programs to improve fillet color in rainbow trout.

Integrated Analyses of DNA Methylation and Gene Expression of Rainbow Trout Muscle under Variable Ploidy and Muscle Atrophy Conditions.

Rainbow trout, Oncorhynchus mykiss, is an important cool, freshwater aquaculture species used as a model for biological research. However, its genome reference has not been annotated for epigenetic markers affecting various biological processes, including muscle growth/atrophy. Increased energetic demands during gonadogenesis/reproduction provoke muscle atrophy in rainbow trout. We described DNA methylation and its associated gene expression in atrophying muscle by comparing gravid, diploid females to sterile, triploid females. Methyl Mini-seq and RNA-Seq were simultaneously used to characterize genome-wide DNA methylation and its association with gene expression in rainbow trout muscle. Genome-wide enrichment in the number of CpGs, accompanied by depleted methylation levels, was noticed around the gene transcription start site (TSS). Hypermethylation of CpG sites within ±1 kb on both sides of TSS (promoter and gene body) was weakly/moderately associated with reduced gene expression. Conversely, hypermethylation of the CpG sites in downstream regions of the gene body +2 to +10 kb was weakly associated with increased gene expression. Unlike mammalian genomes, rainbow trout gene promotors are poor in CpG islands, at <1% compared to 60%. No signs of genome-wide, differentially methylated (DM) CpGs were observed due to the polyploidy effect; only 1206 CpGs (0.03%) were differentially methylated, and these were primarily associated with muscle atrophy. Twenty-eight genes exhibited differential gene expression consistent with methylation levels of 31 DM CpGs. These 31 DM CpGs represent potential epigenetic markers of muscle atrophy in rainbow trout. The DM CpG-harboring genes are involved in apoptosis, epigenetic regulation, autophagy, collagen metabolism, cell membrane functions, and Homeobox proteins. Our study also identified genes explaining higher water content and modulated glycolysis previously shown as characteristic biochemical signs of rainbow trout muscle atrophy associated with sexual maturation. This study characterized DNA methylation in the rainbow trout genome and its correlation with gene expression. This work also identified novel epigenetic markers associated with muscle atrophy in fish/lower vertebrates.

Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels.

BACKGROUND: One of the most important goals for the rainbow trout aquaculture industry is to improve fillet yield and fillet quality. Previously, we showed that a 50 K transcribed-SNP chip can be used to detect quantitative trait loci (QTL) associated with fillet yield and fillet firmness. In this study, data from 1568 fish genotyped for the 50 K transcribed-SNP chip and ~ 774 fish phenotyped for fillet yield and fillet firmness were used in a single-step genomic BLUP (ssGBLUP) model to compute the genomic estimated breeding values (GEBV). In addition, pedigree-based best linear unbiased prediction (PBLUP) was used to calculate traditional, family-based estimated breeding values (EBV). RESULTS: The genomic predictions outperformed the traditional EBV by 35% for fillet yield and 42% for fillet firmness. The predictive ability for fillet yield and fillet firmness was 0.19-0.20 with PBLUP, and 0.27 with ssGBLUP. Additionally, reducing SNP panel densities indicated that using 500-800 SNPs in genomic predictions still provides predictive abilities higher than PBLUP. CONCLUSION: These results suggest that genomic evaluation is a feasible strategy to identify and select fish with superior genetic merit within rainbow trout families, even with low-density SNP panels.

Genome-wide scan for common variants associated with intramuscular fat and moisture content in rainbow trout.

BACKGROUND: Genetic improvement of fillet quality attributes is a priority of the aquaculture industry. Muscle composition impacts quality attributes such as flavor, appearance, texture, and juiciness. Fat and moisture make up about ~ 80% of the tissue weight. The genetic architecture underlying the fat and moisture content of the muscle is still to be fully explored in fish. A 50 K gene transcribed SNP chip was used for genotyping 789 fish with available phenotypic data for fat and moisture content. Genotyped fish were obtained from two consecutive generations produced in the National Center for Cool and Cold Water Aquaculture (NCCCWA) growth-selective breeding program. Estimates of SNP effects from weighted single-step GBLUP (WssGBLUP) were used to perform genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with the studied traits. RESULTS: Using genomic sliding windows of 50 adjacent SNPs, 137 and 178 SNPs were identified as associated with fat and moisture content, respectively. Chromosomes 19 and 29 harbored the highest number of SNPs explaining at least 2% of the genetic variation in fat and moisture content. A total of 61 common SNPs on chromosomes 19 and 29 affected the aforementioned traits; this association suggests common mechanisms underlying intramuscular fat and moisture content. Additionally, based on single-marker GWA analyses, 8 and 24 SNPs were identified in association with fat and moisture content, respectively. CONCLUSION: SNP-harboring genes were primarily involved in lipid metabolism, cytoskeleton remodeling, and protein turnover. This work provides putative SNP markers that could be prioritized and used for genomic selection in breeding programs.

A lipidome-wide association study of the lipoprotein insulin resistance index.

BACKGROUND: The lipoprotein insulin resistance (LPIR) score was shown to predict insulin resistance (IR) and type 2 diabetes (T2D) in healthy adults. However, the molecular basis underlying the LPIR utility for classification remains unclear. OBJECTIVE: To identify small molecule lipids associated with variation in the LPIR score, a weighted index of lipoproteins measured by nuclear magnetic resonance, in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 980). METHODS: Linear mixed effects models were used to test the association between the LPIR score and 413 lipid species and their principal component analysis-derived groups. Significant associations were tested for replication with homeostatic model assessment-IR (HOMA-IR), a phenotype correlated with the LPIR score (r = 0.48, p <  0.001), in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 590). RESULTS: In GOLDN, 319 lipids were associated with the LPIR score (false discovery rate-adjusted p-values ranging from 4.59 × 10- 161 to 49.50 × 10- 3). Factors 1 (triglycerides and diglycerides/storage lipids) and 3 (mixed lipids) were positively (ß = 0.025, p = 4.52 × 10- 71 and ß = 0.021, p = 5.84 × 10- 41, respectively) and factor 2 (phospholipids/non-storage lipids) was inversely (ß = - 0.013, p = 2.28 × 10- 18) associated with the LPIR score. These findings were replicated for HOMA-IR in the HAPI Heart Study (ß = 0.10, p = 1.21 × 10- 02 for storage, ß = - 0.13, p = 3.14 × 10- 04 for non-storage, and ß = 0.19, p = 8.40 × 10- 07 for mixed lipids). CONCLUSIONS: Non-storage lipidomics species show a significant inverse association with the LPIR metabolic dysfunction score and present a promising focus for future therapeutic and prevention studies.

Genome-wide identification of loci associated with growth in rainbow trout.

BACKGROUND: Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. RESULTS: A previously developed 50 K gene-transcribed SNP chip, containing ~ 21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~ 6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R2 = 0.09). CONCLUSION: The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

Genome-Wide Association Study Identifies Genomic Loci Affecting Filet Firmness and Protein Content in Rainbow Trout.

Filet quality traits determine consumer satisfaction and affect profitability of the aquaculture industry. Soft flesh is a criterion for fish filet downgrades, resulting in loss of value. Filet firmness is influenced by many factors, including rate of protein turnover. A 50K transcribed gene SNP chip was used to genotype 789 rainbow trout, from two consecutive generations, produced in the USDA/NCCCWA selective breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform genome-wide association (GWA) analyses to identify quantitative trait loci affecting filet firmness and protein content. Applying genomic sliding windows of 50 adjacent SNPs, 212 and 225 SNPs were associated with genetic variation in filet shear force and protein content, respectively. Four common SNPs in the ryanodine receptor 3 gene (RYR3) affected the aforementioned filet traits; this association suggests common mechanisms underlying filet shear force and protein content. Genes harboring SNPs were mostly involved in calcium homeostasis, proteolytic activities, transcriptional regulation, chromatin remodeling, and apoptotic processes. RYR3 harbored the highest number of SNPs (n = 32) affecting genetic variation in shear force (2.29%) and protein content (4.97%). Additionally, based on single-marker analysis, a SNP in RYR3 ranked at the top of all SNPs associated with variation in shear force. Our data suggest a role for RYR3 in muscle firmness that may be considered for genomic- and marker-assisted selection in breeding programs of rainbow trout.

Genome-Wide Association Analysis With a 50K Transcribed Gene SNP-Chip Identifies QTL Affecting Muscle Yield in Rainbow Trout.

Detection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. This study has two-fold objectives, first to develop, and validate a 50K transcribed gene SNP-chip using RNA-Seq data. To achieve this objective, two bioinformatics pipelines, GATK and SAMtools, were used to identify ~21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs ere identified from pooled RNA-Seq data collected from ~620 fish, representing 98 families from growth- and 54 families from BCWD-selected lines with divergent phenotypes. In addition, ~29K transcribed SNPs without allelic-imbalances were strategically added to build a 50K Affymetrix SNP-chip. SNPs selected included two SNPs per gene from 14K genes and ~5K non-synonymous SNPs. The SNP-chip was used to genotype 1728 fish. The average SNP calling-rate for samples passing quality control (QC; 1,641 fish) was ≥ 98.5%. The second objective of this study was to test the feasibility of using the new SNP-chip in GWA (Genome-wide association) analysis to identify QTL explaining muscle yield variance. GWA study on 878 fish (representing 197 families from 2 consecutive generations) with muscle yield phenotypes and genotyped for 35K polymorphic markers (passing QC) identified several QTL regions explaining together up to 28.40% of the additive genetic variance for muscle yield in this rainbow trout population. The most significant QTLs were on chromosomes 14 and 16 with 12.71 and 10.49% of the genetic variance, respectively. Many of the annotated genes in the QTL regions were previously reported as important regulators of muscle development and cell signaling. No major QTLs were identified in a previous GWA study using a 57K genomic SNP chip on the same fish population. These results indicate improved detection power of the transcribed gene SNP-chip in the target trait and population, allowing identification of large-effect QTLs for important traits in rainbow trout.

Integrated analysis of lncRNA and mRNA expression in rainbow trout families showing variation in muscle growth and fillet quality traits.

Muscle yield and quality traits are important for the aquaculture industry and consumers. Genetic selection for these traits is difficult because they are polygenic and result from multifactorial interactions. To study the genetic architecture of these traits, phenotypic characterization of whole body weight (WBW), muscle yield, fat content, shear force and whiteness were measured in ~500 fish representing 98 families from a growth-selected line. RNA-Seq was used to sequence the muscle transcriptome of different families exhibiting divergent phenotypes for each trait. We have identified 240 and 1,280 differentially expressed (DE) protein-coding genes and long noncoding RNAs (lncRNAs), respectively, in fish families exhibiting contrasting phenotypes. Expression of many DE lncRNAs (n = 229) was positively correlated with overlapping, neighboring or distantly located protein-coding genes (n = 1,030), resulting in 3,392 interactions. Three DE antisense lncRNAs were co-expressed with sense genes known to impact muscle quality traits. Forty-four DE lncRNAs had potential sponge functions to miRNAs that affect muscle quality traits. This study (1) defines muscle quality associated protein-coding and noncoding genes and (2) provides insight into non-coding RNAs involvement in regulating growth and fillet quality traits in rainbow trout.

Crosstalk among lncRNAs, microRNAs and mRNAs in the muscle 'degradome' of rainbow trout.

In fish, protein-coding and noncoding genes involved in muscle atrophy are not fully characterized. In this study, we characterized coding and noncoding genes involved in gonadogenesis-associated muscle atrophy, and investigated the potential functional interplay between these genes. Using RNA-Seq, we compared expression pattern of mRNAs, long noncoding RNAs (lncRNAs) and microRNAs of atrophying skeletal muscle from gravid females and control skeletal muscle from age-matched sterile individuals. A total of 852 mRNAs, 1,160 lncRNAs and 28 microRNAs were differentially expressed (DE) between the two groups. Muscle atrophy appears to be mediated by many genes encoding ubiquitin-proteasome system, autophagy related proteases, lysosomal proteases and transcription factors. Transcripts encoding atrogin-1 and mir-29 showed exceptional high expression in atrophying muscle, suggesting an important role in bulk muscle proteolysis. DE genes were co-localized in the genome with strong expression correlation, and they exhibited extensive 'lncRNA-mRNA', 'lncRNA-microRNA', 'mRNA-microRNA' and 'lncRNA-protein' physical interactions. DE genes exhibiting potential functional interactions comprised the highly correlated 'lncRNA-mRNA-microRNA' gene network described as 'degradome'. This study pinpoints extensive coding and noncoding RNA interactions during muscle atrophy in fish, and provides valuable resources for future mechanistic studies.

RNA-Seq reveals MicroRNA expression signature and genetic polymorphism associated with growth and muscle quality traits in rainbow trout.

The role of microRNA expression and genetic variation in microRNA-binding sites of target genes on growth and muscle quality traits is poorly characterized. We used RNA-Seq approach to investigate their importance on 5 growth and muscle quality traits: whole body weight (WBW), muscle yield, muscle crude-fat content, muscle shear force and whiteness. Phenotypic data were collected from 471 fish, representing 98 families (~5 fish/family) from a growth-selected line. Muscle microRNAs and mRNAs were sequenced from 22 families showing divergent phenotypes. Ninety microRNAs showed differential expression between families with divergent phenotypes, and their expression was strongly associated with variation in phenotypes. A total of 204 single nucleotide polymorphisms (SNPs) present in 3' UTR of target genes either destroyed or created novel illegitimate microRNA target sites; of them, 78 SNPs explained significant variation in the aforementioned 5 muscle traits. Majority of the phenotype-associated SNPs were present in microRNA-binding sites of genes involved in energy metabolism and muscle structure. These findings suggest that variation in microRNA expression and/or sequence variation in microRNA binding sites in target genes play an important role in mediating differences in fish growth and muscle quality phenotypes.

Identification of SNPs associated with muscle yield and quality traits using allelic-imbalance analyses of pooled RNA-Seq samples in rainbow trout.

BACKGROUND: Coding/functional SNPs change the biological function of a gene and, therefore, could serve as "large-effect" genetic markers. In this study, we used two bioinformatics pipelines, GATK and SAMtools, for discovering coding/functional SNPs with allelic-imbalances associated with total body weight, muscle yield, muscle fat content, shear force, and whiteness. Phenotypic data were collected for approximately 500 fish, representing 98 families (5 fish/family), from a growth-selected line, and the muscle transcriptome was sequenced from 22 families with divergent phenotypes (4 low- versus 4 high-ranked families per trait). RESULTS: GATK detected 59,112 putative SNPs; of these SNPs, 4798 showed allelic imbalances (>2.0 as an amplification and <0.5 as loss of heterozygosity). SAMtools detected 87,066 putative SNPs; and of them, 4962 had allelic imbalances between the low- and high-ranked families. Only 1829 SNPs with allelic imbalances were common between the two datasets, indicating significant differences in algorithms. The two datasets contained 7930 non-redundant SNPs of which 4439 mapped to 1498 protein-coding genes (with 6.4% non-synonymous SNPs) and 684 mapped to 295 lncRNAs. Validation of a subset of 92 SNPs revealed 1) 86.7-93.8% success rate in calling polymorphic SNPs and 2) 95.4% consistent matching between DNA and cDNA genotypes indicating a high rate of identifying SNPs with allelic imbalances. In addition, 4.64% SNPs revealed random monoallelic expression. Genome distribution of the SNPs with allelic imbalances exhibited high density for all five traits in several chromosomes, especially chromosome 9, 20 and 28. Most of the SNP-harboring genes were assigned to important growth-related metabolic pathways. CONCLUSION: These results demonstrate utility of RNA-Seq in assessing phenotype-associated allelic imbalances in pooled RNA-Seq samples. The SNPs identified in this study were included in a new SNP-Chip design (available from Affymetrix) for genomic and genetic analyses in rainbow trout.

Aquaculture genomics, genetics and breeding in the United States: current status, challenges, and priorities for future research.

Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, high-density and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries.Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States.

Differential expression of long non-coding RNAs in three genetic lines of rainbow trout in response to infection with Flavobacterium psychrophilum.

Bacterial cold-water disease caused by Flavobacterium psychrophilum is one of the major causes of mortality of salmonids. Three genetic lines of rainbow trout designated as ARS-Fp-R (resistant), ARS-Fp-C (control) and ARS-Fp-S (susceptible) have significant differences in survival rate following F. psychrophilum infection. Previous study identified transcriptome differences of immune-relevant protein-coding genes at basal and post infection levels among these genetic lines. Using RNA-Seq approach, we quantified differentially expressed (DE) long non-coding RNAs (lncRNAs) in response to F. psychrophilum challenge in these genetic lines. Pairwise comparison between genetic lines and different infection statuses identified 556 DE lncRNAs. A positive correlation existed between the number of the differentially regulated lncRNAs and that of the protein-coding genes. Several lncRNAs showed strong positive and negative expression correlation with their overlapped, neighboring and distant immune related protein-coding genes including complement components, cytokines, chemokines and several signaling molecules involved in immunity. The correlated expressions and genome-wide co-localization suggested that some lncRNAs may be involved in regulating immune-relevant protein-coding genes. This study provides the first evidence of lncRNA-mediated regulation of the anti-bacterial immune response in a commercially important aquaculture species and will likely help developing new genetic markers for rainbow trout disease resistance.

Genome-Wide Discovery of Long Non-Coding RNAs in Rainbow Trout.

The ENCODE project revealed that ~70% of the human genome is transcribed. While only 1-2% of the RNAs encode for proteins, the rest are non-coding RNAs. Long non-coding RNAs (lncRNAs) form a diverse class of non-coding RNAs that are longer than 200 nt. Emerging evidence indicates that lncRNAs play critical roles in various cellular processes including regulation of gene expression. LncRNAs show low levels of gene expression and sequence conservation, which make their computational identification in genomes difficult. In this study, more than two billion Illumina sequence reads were mapped to the genome reference using the TopHat and Cufflinks software. Transcripts shorter than 200 nt, with more than 83-100 amino acids ORF, or with significant homologies to the NCBI nr-protein database were removed. In addition, a computational pipeline was used to filter the remaining transcripts based on a protein-coding-score test. Depending on the filtering stringency conditions, between 31,195 and 54,503 lncRNAs were identified, with only 421 matching known lncRNAs in other species. A digital gene expression atlas revealed 2,935 tissue-specific and 3,269 ubiquitously-expressed lncRNAs. This study annotates the lncRNA rainbow trout genome and provides a valuable resource for functional genomics research in salmonids.

Transcriptome assembly, gene annotation and tissue gene expression atlas of the rainbow trout.

Efforts to obtain a comprehensive genome sequence for rainbow trout are ongoing and will be complemented by transcriptome information that will enhance genome assembly and annotation. Previously, transcriptome reference sequences were reported using data from different sources. Although the previous work added a great wealth of sequences, a complete and well-annotated transcriptome is still needed. In addition, gene expression in different tissues was not completely addressed in the previous studies. In this study, non-normalized cDNA libraries were sequenced from 13 different tissues of a single doubled haploid rainbow trout from the same source used for the rainbow trout genome sequence. A total of ~1.167 billion paired-end reads were de novo assembled using the Trinity RNA-Seq assembler yielding 474,524 contigs > 500 base-pairs. Of them, 287,593 had homologies to the NCBI non-redundant protein database. The longest contig of each cluster was selected as a reference, yielding 44,990 representative contigs. A total of 4,146 contigs (9.2%), including 710 full-length sequences, did not match any mRNA sequences in the current rainbow trout genome reference. Mapping reads to the reference genome identified an additional 11,843 transcripts not annotated in the genome. A digital gene expression atlas revealed 7,678 housekeeping and 4,021 tissue-specific genes. Expression of about 16,000-32,000 genes (35-71% of the identified genes) accounted for basic and specialized functions of each tissue. White muscle and stomach had the least complex transcriptomes, with high percentages of their total mRNA contributed by a small number of genes. Brain, testis and intestine, in contrast, had complex transcriptomes, with a large numbers of genes involved in their expression patterns. This study provides comprehensive de novo transcriptome information that is suitable for functional and comparative genomics studies in rainbow trout, including annotation of the genome.