Identification of single-nucleotide polymorphism markers associated with cortisol response to crowding in rainbow trout

Genomic Selection for Dairy Cattle Behaviour Considering Novel Traits in a Changing Technical Production Environment

Cow behaviour is a major factor influencing dairy herd profitability and is an indicator of animal welfare and disease. Behaviour is a complex network of behavioural patterns in response to environmental and social stimuli and human handling. Advances in agricultural technology have led to changes in dairy cow husbandry systems worldwide. Increasing herd sizes, less time availability to take care of the animals and modern technology such as automatic milking systems (AMSs) imply limited human-cow interactions. On the other hand, cow behaviour responses to the technical environment (cow-AMS interactions) simultaneously improve production efficiency and welfare and contribute to simplified "cow handling" and reduced labour time. Automatic milking systems generate objective behaviour traits linked to workability, milkability and health, which can be implemented into genomic selection tools. However, there is insufficient understanding of the genetic mechanisms influencing cow learning and social behaviour, in turn affecting herd management, productivity and welfare. Moreover, physiological and molecular biomarkers such as heart rate, neurotransmitters and hormones might be useful indicators and predictors of cow behaviour. This review gives an overview of published behaviour studies in dairy cows in the context of genetics and genomics and discusses possibilities for breeding approaches to achieve desired behaviour in a technical production environment.

Genomic Predictions of Phenotypes and Pseudo-Phenotypes for Viral Nervous Necrosis Resistance, Cortisol Concentration, Antibody Titer and Body Weight in European Sea Bass

Simple Summary

Selective breeding programs based on genomic data are still not a common practice in aquaculture, although genomic selection has been widely demonstrated to be advantageous when trait phenotyping is a difficult task. In this study, we investigated the accuracy of predicting the phenotype and the estimated breeding value (EBV) of three Bayesian models and a Random Forest algorithm exploiting the information of a genome-wide SNP panel for European sea bass. The genomic predictions were developed for mortality caused by viral nervous necrosis, post-stress cortisol concentration, antibody titer against nervous necrosis virus and body weight. Selective breeding based on genomic data is a possible option for improving these traits while overcoming difficulties related to individual phenotyping of the investigated traits. Our results evidenced that the EBV used as a pseudo-phenotype enhances the predictive performances of genomic models, and that EBV can be predicted with satisfactory accuracy. The genomic prediction of the EBV for mortality might also be used to classify the phenotype for the same trait.

Abstract

In European sea bass (Dicentrarchus labrax L.), the viral nervous necrosis mortality (MORT), post-stress cortisol concentration (HC), antibody titer (AT) against nervous necrosis virus and body weight (BW) show significant heritability, which makes selective breeding a possible option for their improvement. An experimental population (N = 650) generated by a commercial broodstock was phenotyped for the aforementioned traits and genotyped with a genome-wide SNP panel (16,075 markers). We compared the predictive accuracies of three Bayesian models (Bayes B, Bayes C and Bayesian Ridge Regression) and a machine-learning method (Random Forest). The prediction accuracy of the EBV for MORT was approximately 0.90, whereas the prediction accuracies of the EBV and the phenotype were 0.86 and 0.21 for HC, 0.79 and 0.26 for AT and 0.71 and 0.38 for BW. The genomic prediction of the EBV for MORT used to classify the phenotype for the same trait showed moderate classification performance. Genome-wide association studies confirmed the polygenic nature of MORT and demonstrated a complex genetic structure for HC and AT. Genomic predictions of the EBV for MORT could potentially be used to classify the phenotype of the same trait, though further investigations on a larger experimental population are needed.

Effect of long-term confinement on metabolic and physiological parameters in mice

Long-term and mild confinement or isolation in an enclosed environment can occur in situations such as disasters, specific political, economic or social events, nuclear shelters, seabed exploration, polar expeditions, and space travel. To investigate the effects of stress caused by long-term confinement in an enclosed environment in mammals, we divided 8-week-old C57BL/6J mice into four groups that were housed in a closed environment with a narrow metabolic cage (stress group), normal metabolic cage (control group), conventional cage (conventional group) or conventional cage with wire mesh floor (wire mesh group). The phenotypes of the mice were examined for four weeks, followed by behavioral tests. Weight gain suppression was observed in the stress group. Continuous analysis of these mice every two minutes for four weeks using an implanted measuring device showed a significantly decreased amount of spontaneous activity and subcutaneous temperature in the stress group. After housing in each environment for four weeks, the behavioral tests of mice in the stress group also revealed a shorter latency to fall off in the rotarod test and shorter stride length and interstep distance in the footprint test. Interestingly, the lower spontaneous activity of mice in the stress group was rescued by housing in conventional cages. These results suggest a temporary effect of long-term confinement in an enclosed environment as a chronic and mild stress on homeostasis in mammals.

The genetic basis of animal behavioural diversity in natural populations

Individual differences in animal behaviour influence ecological and evolutionary processes. Much behavioural variation has a heritable component, suggesting that genetics may play a role in its development. Yet, the study of the mechanistic description linking genes to behaviour in nature remains in its infancy, and such research is considered a challenge in contemporary biology. Here, we performed a literature review and meta-analysis to assess trends in analytical approaches used to investigate the relationship between genes and behaviour in natural systems, specifically candidate gene approaches, quantitative trait locus (QTL) mapping, and genome-wide association studies (GWAS). We aimed to determine the efficacy and success of each approach, while also describing which behaviours and species were examined by researchers most often. We found that the majority of QTL mapping and GWAS results revealed a significant or suggestive effect (Zr = 0.3 [95% CI: 0.25:0.35] and Zr = 0.39 [0.33:0.46], respectively) between the trait of interest and genetic marker(s) tested, while over half of candidate gene accounts (Zr = 0.16 [0.11:0.21]) did not find a significant association. Approximately a third of all study estimates investigated animal personality traits; though, reproductive and migratory behaviours were also well-represented. Our findings show that despite widespread accessibility of molecular approaches given current sequencing technologies, efforts to elucidate the genetic basis of behaviour in free-ranging systems has been limited to relatively few species. We discuss challenges encountered by researchers, and recommend integration of novel genomic methods with longitudinal studies to usher in the next wave of behavioural genomic research.

Genetic and genomic analysis for cocoon yield traits in silkworm

Domestic species provides a powerful model for examining genetic mechanisms in the evolution of yield traits. The domestic silkworm (Bombyx mori) is an important livestock species in sericulture. While the mechanisms controlling cocoon yield are largely unknown. Here, using B. mori and its wild relative B. mandarina as intercross parents, 100 BC₁ individuals were sequenced by restriction site-associated DNA sequencing (RAD-Seq). The linkage map contained 9,632 markers was constructed. We performed high-resolution quantitative trait locus (QTL) mapping for four cocoon yield traits. A total of 11 QTLs were identified, including one yield-enhancing QTL from wild silkworm. By integrating population genomics and transcriptomic analysis with QTLs, some favourable genes were revealed, including 14 domestication-related genes and 71 differentially expressed genes (DEGs) in the fifth-instar larval silk gland transcriptome between B. mori and B. mandarina. The relationships between the expression of two important candidate genes (KWMTBOMO04917 and KWMTBOMO12906) and cocoon yield were supported by quantitative real-time PCR (qPCR). Our results provide some new insights into the molecular mechanisms of complex yield traits in silkworm. The combined method might be an efficient approach for identifying putative causal genes in domestic livestock and wild relatives.

Quantitative Trait Loci (QTL) Mapping

Quantitative trait loci (QTL) are genetic regions that influence phenotypic variation of a complex trait, often through genetic interactions with each other and the environment. These are commonly identified through a statistical genetic analysis known as QTL mapping. Here, I present a step-by-step, practical approach to QTL mapping along with a sample data file. I focus on methods commonly used and discoveries that have been made in fishes, and utilize a multiple QTL mapping (MQM) approach in the free software package R/qtl.

GWAS Analysis Indicated Importance of NF-κB Signaling Pathway in Host Resistance Against Motile Aeromonas Septicemia Disease in Catfish

Motile Aeromonas septicemia (MAS) disease caused by a bacterial pathogen, Aeromonas hydrophila, is an emerging but severe disease of catfish. Genetic enhancement of disease resistance is considered to be effective to control the disease. To provide an insight into the genomic basis of MAS disease resistance, in this study, we conducted a genome-wide association study (GWAS) to identify quantitative trait loci (QTL). A total of 1820 interspecific backcross catfish of 7 families were challenged with A. hydrophila, and 382 phenotypic extremes were selected for genotyping with the catfish 690 K SNP arrays. Three QTL on linkage group (LG) 2, 26 and 29 were identified to be significantly associated with MAS resistance. Within these regions, a total of 24 genes had known functions in immunity, 10 of which were involved in NF-κB signaling pathway, suggesting the importance of NF-κB signaling pathway in MAS resistance. In addition, three suggestively significant QTL were identified on LG 11, 17, and 20. The limited numbers of QTL involved in MAS resistance suggests that marker-assisted selection may be a viable approach for catfish breeding.

Major Histocompatibility Complex (MHC) Genes and Disease Resistance in Fish

Fascinating about classical major histocompatibility complex (MHC) molecules is their polymorphism. The present study is a review and discussion of the fish MHC situation. The basic pattern of MHC variation in fish is similar to mammals, with MHC class I versus class II, and polymorphic classical versus nonpolymorphic nonclassical. However, in many or all teleost fishes, important differences with mammalian or human MHC were observed: (1) The allelic/haplotype diversification levels of classical MHC class I tend to be much higher than in mammals and involve structural positions within but also outside the peptide binding groove; (2) Teleost fish classical MHC class I and class II loci are not linked. The present article summarizes previous studies that performed quantitative trait loci (QTL) analysis for mapping differences in teleost fish disease resistance, and discusses them from MHC point of view. Overall, those QTL studies suggest the possible importance of genomic regions including classical MHC class II and nonclassical MHC class I genes, whereas similar observations were not made for the genomic regions with the highly diversified classical MHC class I alleles. It must be concluded that despite decades of knowing MHC polymorphism in jawed vertebrate species including fish, firm conclusions (as opposed to appealing hypotheses) on the reasons for MHC polymorphism cannot be made, and that the types of polymorphism observed in fish may not be explained by disease-resistance models alone.

Genome-Scale Association Study of Abnormal Scale Pattern in Yellow River Carp Identified Previously Known Causative Gene in European Mirror Carp

Common carp (Cyprinus carpio) is one of the most widely studied fish species due to its great economic value and strong environmental adaptability. Scattered scale, a typical phenotype of the mirror carp that is derived from Europe, has never been observed in the Yellow River carp previously. We recently identified approximately one fourth of the F1 progenies displaying scattered scale in a full-sib Yellow River carp family in our breeding program, despite both parents that showed wild type with normal scale patterns. This family provides us unique materials to investigate the genetic basis underlying the abnormal scale mutant in Yellow River carp population. Genome-wide association study (GWAS) and association mapping were performed based on genome-wide single nucleotide polymorphisms (SNP) genotyped with common carp 250 K SNP genotyping array in 82 samples of the Yellow River carp family. We identified a 1.4 Mb genome region that was significantly associated with abnormal scattered scale patterns. We further identified a deletion mutation in fibroblast growth factor receptor 1 a1 (fgfr1a1) gene within this genome region. Amplification and sequencing analysis of this gene revealed a 311-bp deletion in intron 10 and exon 11, which proved that fgfr1a1 could be the causal gene responsible for abnormal scattered scale in the Yellow River carp family. Since similar fragment mutation with 306-bp and 310-bp deletions had been previously reported as causal mutation of scattered scale patterns in the mirror carp, we speculate that either the deletion mutation was introduced from Europe-derived mirror carp or the deletion independently occurred in the mutation hotspot in fgfr1a1 gene. The results provided insights into the genetic basis of scale pattern mutant in Yellow River carp population, which would help us to eliminate the recessive allele of the abnormal scale patterns in Yellow River carp population by molecular marker-assisted breeding.

Applications of genotyping by sequencing in aquaculture breeding and genetics

Selective breeding is increasingly recognized as a key component of sustainable production of aquaculture species. The uptake of genomic technology in aquaculture breeding has traditionally lagged behind terrestrial farmed animals. However, the rapid development and application of sequencing technologies has allowed aquaculture to narrow the gap, leading to substantial genomic resources for all major aquaculture species. While high-density single-nucleotide polymorphism (SNP) arrays for some species have been developed recently, direct genotyping by sequencing (GBS) techniques have underpinned many of the advances in aquaculture genetics and breeding to date. In particular, restriction-site associated DNA sequencing (RAD-Seq) and subsequent variations have been extensively applied to generate population-level SNP genotype data. These GBS techniques are not dependent on prior genomic information such as a reference genome assembly for the species of interest. As such, they have been widely utilized by researchers and companies focussing on nonmodel aquaculture species with relatively small research communities. Applications of RAD-Seq techniques have included generation of genetic linkage maps, performing genome-wide association studies, improvements of reference genome assemblies and, more recently, genomic selection for traits of interest to aquaculture like growth, sex determination or disease resistance. In this review, we briefly discuss the history of GBS, the nuances of the various GBS techniques, bioinformatics approaches and application of these techniques to various aquaculture species.

Genetically influenced resistance to stress and disease in salmonids in relation to present-day breeding practice - a short review

While intensive fish production has many advantages, it also has a number of drawbacks as regards disease and stress. To date, there has been no conclusive review of disease resistance at Czech fish farms. The aim of the study was to describe briefly the existing salmonid breeding practice in the Czech Republic and to point out the trends and new possibilities gaining ground around Europe. However, the present situation in the Czech stocks is not rare at all and therefore it is used here as a model example representing numerous breeding practices in Europe. Stress and disease resistance in fish is polygenic and quantitative, making selection for such traits difficult. In recent years, however, fish breeding methods have developed rapidly, with the use of genetic analysis tools, for example, now allowing much greater selection accuracy. Gradual progress in understanding the importance of individual genetic markers offers many new options that can be utilised in breeding practice. New selection methods, such as quantitative trait loci (QTLs) and genomic selection, are increasingly employed in European aquaculture. Next generation sequencing techniques now help in the finding of new and promising QTLs that can be used in assisted selection. This review maps the current progress in improving salmonid resistance to stress and disease in aquaculture and at the same time provides the breeders with a short overview of the latest tools of genetically controlled breeding and of the newest products available at the European market.

Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect quantitative trait loci (QTL) for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57 K SNP array and a reference genome assembly have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57 K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57 K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

QTL Mapping for Resistance to Iridovirus in Asian Seabass Using Genotyping-by-Sequencing

Identifying quantitative trait loci (QTL) for viral disease resistance is of particular importance in selective breeding programs of fish species. Genetic markers linked to QTL can be useful in marker-assisted selection (MAS) for elites resistant to specific pathogens. Here, we conducted a genome scan for QTL associated with Singapore grouper iridovirus (SGIV) resistance in an Asian seabass (Lates calcarifer) family, using a high-density linkage map generated with genotyping-by-sequencing. One genome-wide significant and three suggestive QTL were detected at LG21, LG6, LG13, and LG15, respectively. The phenotypic variation explained (PVE) by the four QTL ranged from 7.5 to 15.6%. The position of the most significant QTL at LG21 was located between 31.88 and 36.81 cM. The SNP marker (SNP130416) nearest to the peak of this QTL was significantly associated with SGIV resistance in an unrelated multifamily population. One candidate gene, MECOM, close to the peak of this QTL region, was predicted. Evidence of alternative splicing was observed for MECOM and one specific category of splicing variants was differentially expressed at 5 days post-SGIV infection. The QTL detected in this study are valuable resources and can be used in the selective breeding programs of Asian seabass with regard to resistance to SGIV.

Construction of the First High-Density Genetic Linkage Map and Analysis of Quantitative Trait Loci for Growth-Related Traits in Sinonovacula constricta

The razor clam (Sinonovacula constricta) is an important aquaculture species, for which a high-density genetic linkage map would play an important role in marker-assisted selection (MAS). In this study, we constructed a high-density genetic map and detected quantitative trait loci (QTLs) for Sinonovacula constricta with an F₁ cross population by using the specific locus amplified fragment sequencing (SLAF-seq) method. A total of 315,553 SLAF markers out of 467.71 Mreads were developed. The final linkage map was composed of 7516 SLAFs (156.60-fold in the parents and 20.80-fold in each F₁ population on average). The total distance of the linkage map was 2383.85 cM, covering 19 linkage groups with an average inter-marker distance of 0.32 cM. The proportion of gaps less than 5.0 cM was on average 96.90%. A total of 16 suggestive QTLs for five growth-related traits (five QTLs for shell height, six QTLs for shell length, three QTLs for shell width, one QTL for total body weight, and one QTL for soft body weight) were identified. These QTLs were distributed on five linkage groups, and the regions showed overlapping on LG9 and LG13. In conclusion, the high-density genetic map and QTLs for S. constricta provide a valuable genetic resource and a basis for MAS.

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.

Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss)

Fillet yield (FY, %) is an economically-important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has received little attention in breeding programs because it is difficult to measure on a large number of fish and cannot be directly measured on breeding candidates. The recent development of a high-density SNP array for rainbow trout has provided the needed tool for studying the underlying genetic architecture of this trait. A genome-wide association study (GWAS) was conducted for FY, body weight at 10 (BW10) and 13 (BW13) months post-hatching, head-off carcass weight (CAR), and fillet weight (FW) in a pedigreed rainbow trout population selectively bred for improved growth performance. The GWAS analysis was performed using the weighted single-step GBLUP method (wssGWAS). Phenotypic records of 1447 fish (1.5 kg at harvest) from 299 full-sib families in three successive generations, of which 875 fish from 196 full-sib families were genotyped, were used in the GWAS analysis. A total of 38,107 polymorphic SNPs were analyzed in a univariate model with hatch year and harvest group as fixed effects, harvest weight as a continuous covariate, and animal and common environment as random effects. A new linkage map was developed to create windows of 20 adjacent SNPs for use in the GWAS. The two windows with largest effect for FY and FW were located on chromosome Omy9 and explained only 1.0-1.5% of genetic variance, thus suggesting a polygenic architecture affected by multiple loci with small effects in this population. One window on Omy5 explained 1.4 and 1.0% of the genetic variance for BW10 and BW13, respectively. Three windows located on Omy27, Omy17, and Omy9 (same window detected for FY) explained 1.7, 1.7, and 1.0%, respectively, of genetic variance for CAR. Among the detected 100 SNPs, 55% were located directly in genes (intron and exons). Nucleotide sequences of intragenic SNPs were blasted to the Mus musculus genome to create a putative gene network. The network suggests that differences in the ability to maintain a proliferative and renewable population of myogenic precursor cells may affect variation in growth and fillet yield in rainbow trout.

Evaluation of Genome-Enabled Selection for Bacterial Cold Water Disease Resistance Using Progeny Performance Data in Rainbow Trout: Insights on Genotyping Methods and Genomic Prediction Models

Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic breeding values (GEBVs) for BCWD resistance in 10 families from the first generation of the NCCCWA BCWD resistance breeding line, compared the predictive ability (PA) of GEBVs to pedigree-based estimated breeding values (EBVs), and compared the impact of two SNP genotyping methods on the accuracy of GEBV predictions. The BCWD phenotypes survival days (DAYS) and survival status (STATUS) had been recorded in training fish (n = 583) subjected to experimental BCWD challenge. Training fish, and their full sibs without phenotypic data that were used as parents of the subsequent generation, were genotyped using two methods: restriction-site associated DNA (RAD) sequencing and the Rainbow Trout Axiom® 57 K SNP array (Chip). Animal-specific GEBVs were estimated using four GS models: BayesB, BayesC, single-step GBLUP (ssGBLUP), and weighted ssGBLUP (wssGBLUP). Family-specific EBVs were estimated using pedigree and phenotype data in the training fish only. The PA of EBVs and GEBVs was assessed by correlating mean progeny phenotype (MPP) with mid-parent EBV (family-specific) or GEBV (animal-specific). The best GEBV predictions were similar to EBV with PA values of 0.49 and 0.46 vs. 0.50 and 0.41 for DAYS and STATUS, respectively. Among the GEBV prediction methods, ssGBLUP consistently had the highest PA. The RAD genotyping platform had GEBVs with similar PA to those of GEBVs from the Chip platform. The PA of ssGBLUP and wssGBLUP methods was higher with the Chip, but for BayesB and BayesC methods it was higher with the RAD platform. The overall GEBV accuracy in this study was low to moderate, likely due to the small training sample used. This study explored the potential of GS for improving resistance to BCWD in rainbow trout using, for the first time, progeny testing data to assess the accuracy of GEBVs, and it provides the basis for further investigation on the implementation of GS in commercial rainbow trout populations.

Genome-Wide Mapping of Growth-Related Quantitative Trait Loci in Orange-Spotted Grouper (Epinephelus coioides) Using Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq)

Mapping of quantitative trait loci (QTL) is essential for the discovery of genetic structures that related to complex quantitative traits. In this study, we identified 264,072 raw SNPs (single-nucleotide polymorphisms) by double digest restriction site associated DNA sequencing (ddRADseq), and utilized 3029 of these SNPs to construct a genetic linkage map in orange-spotted grouper (Epinephelus coioides) using a regression mapping algorithm. The genetic map contained 24 linkage groups (LGs) spanning a total genetic distance of 1231.98 cM. Twenty-seven significant growth-related QTLs were identified. Furthermore, we identified 17 genes (fez2, alg3, ece2, arvcf, sla27a4, sgk223, camk2, prrc2b, mchr1, sardh, pappa, syk, tert, wdrcp91, ftz-f1, mate1 and notch1) including three (tert, ftz-f1 and notch1) that have been reported to be involved in fish growth. To summarize, we mapped growth-related QTLs in the orange-spotted grouper. These QTLs will be useful in marker-assisted selection (MAS) efforts to improve growth-related traits in this economically important fish.

Mapping QTL for Resistance Against Viral Nervous Necrosis Disease in Asian Seabass

Viral nervous necrosis disease (VNN), caused by nervous necrosis virus (NNV), leads to mass mortality in mariculture. However, phenotypic selection for resistance against VNN is very difficult. To facilitate marker-assisted selection (MAS) for resistance against VNN and understanding of the genetic architecture underlying the resistance against this disease, we mapped quantitative trait loci (QTL) for resistance against VNN in Asian seabass. We challenged fingerlings at 37 days post-hatching (dph), from a single back-cross family, with NNV at a concentration of 9 × 10(6) TCID50/ml for 2 h. Daily mortalities were recorded and collected. A panel of 330 mortalities and 190 surviving fingerlings was genotyped using 149 microsatellites with 145 successfully mapped markers covering 24 linkage groups (LGs). Analysis of QTL for both resistance against VNN and survival time was conducted using interval mapping. Five significant QTL located in four LGs and eight suggestive QTL in seven LGs were identified for resistance. Another five significant QTL in three LGs and five suggestive QTL in three LGs were detected for survival time. One significant QTL, spanning 3 cM in LG20, was identified for both resistance and survival time. These QTL explained 2.2-4.1% of the phenotypic variance for resistance and 2.2-3.3% of the phenotypic variance for survival time, respectively. Our results suggest that VNN resistance in Asian seabass is controlled by many loci with small effects. Our data provide information for fine mapping of QTL and identification of candidate genes for a better understanding of the mechanism of disease resistance.

Transcriptome profiling in fast versus slow-growing rainbow trout across seasonal gradients

Background

Circannual rhythms in vertebrates can influence a wide variety of physiological processes. Some notable examples include annual reproductive cycles and for poikilotherms, seasonal changes modulating growth. Increasing water temperature elevates growth rates in fishes, but increases in photoperiod regime can have similar influences even at constant temperature. Therefore, in order to understand the dynamics of growth in fish it is important to consider the background influence of photoperiod regime on gene expression differences. This study examined the influence of a declining photoperiod regime (winter solstice) compared to an increasing photoperiod regime (spring equinox) on white muscle transcriptome profiles in fast and slow-growing rainbow trout from a commercial aquaculture strain.

Results

Slow-growing fish could be characterized as possessing transcriptome profiles that conform in many respects to an endurance training regime in humans. They have elevated mitochondrial and cytosolic creatine kinase expression levels and appear to suppress mTOR-signaling as evidenced by elevated TSC2 expression, and they also have elevated p53 levels. Large fish display a physiological repertoire that may be consistent with strength/resistance physiology having elevated cytoskeletal gene component expression and glycogen metabolism cycling along with higher PI3K levels. In many respects small vs. large fish match eccentric vs. concentric muscle expression patterns, respectively. Lipid metabolic genes are also more elevated in larger fish, the most notable being the G0S2 switch gene. M and Z-line sarcomere remodelling appears to be more prevalent in large fish. Twenty-three out of 26 gene families with previously reported significant SNP-based growth differences were detected as having significant expression differences.

Conclusions

Larger fish display a broader array of genes showing higher expression, and their profiles are more similar to those observed in December lot fish (i.e., an accelerated growth period). Conversely, small fish display gene profiles more similar to seasonal growth decline phases (i.e., September lot fish). Overall, seasonal timing was coupled to greater differences in gene expression compared to differences associated with fish size.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2363-5) contains supplementary material, which is available to authorized users.

Identification of single nucleotide polymorphism markers associated with bacterial cold water disease resistance and spleen size in rainbow trout

Bacterial cold water disease (BCWD) is one of the frequent causes of elevated mortality in salmonid aquaculture. Previously, we identified and validated microsatellites on chromosome Omy19 associated with QTL (quantitative trait loci) for BCWD resistance and spleen size in rainbow trout. Recently, SNPs (single nucleotide polymorphism) have become the markers of choice for genetic analyses in rainbow trout as they are highly abundant, cost-effective and are amenable for high throughput genotyping. The objective of this study was to identify SNP markers associated with BCWD resistance and spleen size using both genome-wide association studies (GWAS) and linkage-based QTL mapping approaches. A total of 298 offspring from the two half-sib families used in our previous study to validate the significant BCWD QTL on chromosome Omy19 were genotyped with RAD-seq (restriction-site-associated DNA sequencing), and 7,849 informative SNPs were identified. Based on GWAS, 18 SNPs associated with BCWD resistance and 20 SNPs associated with spleen size were identified. Linkage-based QTL mapping revealed three significant QTL for BCWD resistance. In addition to the previously validated dam-derived QTL on chromosome Omy19, two significant BCWD QTL derived from the sires were identified on chromosomes Omy8 and Omy25, respectively. A sire-derived significant QTL for spleen size on chromosome Omy2 was detected. The SNP markers reported in this study will facilitate fine mapping to identify positional candidate genes for BCWD resistance in rainbow trout.

Detection and Validation of QTL Affecting Bacterial Cold Water Disease Resistance in Rainbow Trout Using Restriction-Site Associated DNA Sequencing

Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. Using microsatellite markers in a genome scan, we previously detected significant and suggestive QTL affecting phenotypic variation in survival following challenge with Flavobacterium psychrophilum, the causative agent of BCWD in rainbow trout. In this study, we performed selective genotyping of SNPs from restriction-site associated DNA (RAD) sequence data from two pedigreed families (2009070 and 2009196) to validate the major QTL from the previous work and to detect new QTL. The use of RAD SNPs in the genome scans increased the number of mapped markers from ~300 to ~5,000 per family. The significant QTL detected in the microsatellites scan on chromosome Omy8 in family 2009070 was validated explaining up to 58% of the phenotypic variance in that family, and in addition, a second QTL was also detected on Omy8. Two novel QTL on Omy11 and 14 were also detected, and the previously suggestive QTL on Omy1, 7 and 25 were also validated in family 2009070. In family 2009196, the microsatellite significant QTL on Omy6 and 12 were validated and a new QTL on Omy8 was detected, but none of the previously detected suggestive QTL were validated. The two Omy8 QTL from family 2009070 and the Omy12 QTL from family 2009196 were found to be co-localized with handling and confinement stress response QTL that our group has previously identified in a separate pedigreed family. With the currently available data we cannot determine if the co-localized QTL are the result of genes with pleiotropic effects or a mere physical proximity on the same chromosome segment. The genetic markers linked to BCWD resistance QTL were used to query the scaffolds of the rainbow trout reference genome assembly and the QTL-positive scaffold sequences were found to include 100 positional candidate genes. Several of the candidate genes located on or near the two Omy8 QTL detected in family 2009070 suggest potential linkages between stress response and the regulation of immune response in rainbow trout.

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.