Genomic prediction using DArT-Seq technology for yellowtail kingfish Seriola lalandi.
ABSTRACT: Genomic prediction using Diversity Arrays Technology (DArT) genotype by sequencing platform has not been reported in yellowtail kingfish (Seriola lalandi). The principal aim of this study was to address this knowledge gap and to assess predictive ability of genomic Best Linear Unbiased Prediction (gBLUP) for traits of commercial importance in a yellowtail kingfish population comprising 752 individuals that had DNA sequence and phenotypic records for growth traits (body weight, fork length and condition index). The gBLUP method was used due to its computational efficiency and it showed similar predictive performance to other approaches, especially for traits whose variation is of polygenic nature, such as body traits analysed in this study. The accuracy or predictive ability of the gBLUP model was estimated for three growth traits: body weight, folk length and condition index.The prediction accuracy was moderate to high (0.44 to 0.69) for growth-related traits. The predictive ability for body weight increased by 17.0% (from 0.69 to 0.83) when missing genotype was imputed. Within population prediction using five-fold across validation approach showed that the gBLUP model performed well for growth traits (weight, length and condition factor), with the coefficient of determination (R2) from linear regression analysis ranging from 0.49 to 0.71.Collectively our results demonstrated, for the first time in yellowtail kingfish, the potential application of genomic selection for growth-related traits in the future breeding program for this species, S. lalandi.
Project description:The genetic resources available for the commercially important fish species Yellowtail kingfish (YTK) (Seriola lalandi) are relative sparse. To overcome this, we aimed (1) to develop a linkage map for this species, and (2) to identify markers/variants associated with economically important traits in kingfish (with an emphasis on body weight). Genetic and genomic analyses were conducted using 13,898 single nucleotide polymorphisms (SNPs) generated from a new high-throughput genotyping by sequencing platform, Diversity Arrays Technology (DArTseqTM) in a pedigreed population comprising 752 animals. The linkage analysis enabled to map about 4,000 markers to 24 linkage groups (LGs), with an average density of 3.4 SNPs per cM. The linkage map was integrated into a genome-wide association study (GWAS) and identified six variants/SNPs associated with body weight (P < 5e-8) when a multi-locus mixed model was used. Two out of the six significant markers were mapped to LGs 17 and 23, and collectively they explained 5.8% of the total genetic variance. It is concluded that the newly developed linkage map and the significantly associated markers with body weight provide fundamental information to characterize genetic architecture of growth-related traits in this population of YTK S. lalandi.
Project description:Fish skin and gut microbiomes contribute to host health and growth and are often significantly different in aquaculture-reared fish compared to wild fish. Determining how factors associated with aquaculture, including altered diet and abiotic conditions, affect the microbiome will assist with optimizing farming practices and non-invasively assessing fish health. Here, juvenile yellowtail kingfish (Seriola lalandi) housed at optimal (22 °C) and non-optimal (26 °C) water temperature were fed a fishmeal control diet or the same diet substituted with 30% soy-protein concentrate (SPC) in order to investigate impacts on host health and the microbial community composition of the skin mucosa, gut mucosa and digesta. Each of these sites was observed to have a distinct microbiome composition. The combination of SPC and housing at 26 °C significantly reduced weight gain in yellowtail kingfish and affected immune parameters. The overall microbial composition and relative abundance of specific operational taxonomic units (OTUs) was also significantly altered by inclusion of SPC at 26 °C, with a notable increase in an OTU identified as Photobacterium in the skin mucosa and digesta. Increased relative abundance of Photobacterium sp. was significantly correlated with reduced levels of digesta myeloperoxidase in yellowtail kingfish; a recognized innate immunity defense mechanism. The changes in the microbial communities of yellowtail kingfish fed a diet containing 30% SPC at 26 °C highlights the importance of considering the interactive effects of diet and environmental factors on microbiome health in farmed yellowtail kingfish.
Project description:The supply of quality juveniles via land-based larviculture represents a major bottleneck to the growing finfish aquaculture industry. As the microbiome plays a key role in animal health, this study aimed to assess the microbial community associated with early larval development of commercially raised Yellowtail Kingfish (Seriola lalandi). We used qPCR and 16S rRNA gene amplicon sequencing to monitor changes in the microbiome associated with the development of S. lalandi from larvae to juveniles. We observed an increase in the bacterial load during larval development, which consisted of a small but abundant core microbiota including taxa belonging to the families Rhodobacteraceae, Lactobacillaceae and Vibrionaceae. The greatest change in the microbiome occurred as larvae moved from a diet of live feeds to formulated pellets, characterized by a transition from Proteobacteria to Firmicutes as the dominant phylum. A prediction of bacterial gene functions found lipid metabolism and secondary metabolite production were abundant in the early larval stages, with carbohydrate and thiamine metabolism functions increasing in abundance as the larvae age and are fed formulated diets. Together, these results suggest that diet is a major contributor to the early microbiome development of commercially raised S. lalandi.
Project description:Genomic selection is a promising breeding strategy that has been used in considerable numbers of breeding projects due to its highly accurate results. Yak are rare mammals that are remarkable because of their ability to survive in the extreme and harsh conditions predominantly at the so-called "roof of the world"-the Qinghai-Tibetan Plateau. In the current study, we conducted an exploration of the feasibility of genomic evaluation and compared the predictive accuracy of early growth traits with five different approaches. In total, four growth traits were measured in 354 yaks, including body weight, withers height, body length, and chest girth in two early stages of development (weaning and yearling). Genotyping was implemented using the Illumina BovineHD BeadChip. The predictive accuracy was calculated through five-fold cross-validation in five classical statistical methods including genomic best linear unbiased prediction (GBLUP) and four Bayesian methods. Body weights at 30 months in the same yak population were also measured to evaluate the prediction at 6 months. The results indicated that the predictive accuracy for the early growth traits of yak ranged from 0.147 to 0.391. Similar performance was found for the GBLUP and Bayesian methods for most growth traits. Among the Bayesian methods, Bayes B outperformed Bayes A in the majority of traits. The average correlation coefficient between the prediction at 6 months using different methods and observations at 30 months was 0.4. These results indicate that genomic prediction is feasible for early growth traits in yak. Considering that genomic selection is necessary in yak breeding projects, the present study provides promising reference for future applications.
Project description:Genomic prediction has been widely utilized to estimate genomic breeding values (GEBVs) in farm animals. In this study, we conducted genomic prediction for 20 economically important traits including growth, carcass and meat quality traits in Chinese Simmental beef cattle. Five approaches (GBLUP, BayesA, BayesB, BayesC? and BayesR) were used to estimate the genomic breeding values. The predictive accuracies ranged from 0.159 (lean meat percentage estimated by BayesC?) to 0.518 (striploin weight estimated by BayesR). Moreover, we found that the average predictive accuracies across 20 traits were 0.361, 0.361, 0.367, 0.367 and 0.378, and the averaged regression coefficients were 0.89, 0.86, 0.89, 0.94 and 0.95 for GBLUP, BayesA, BayesB, BayesC? and BayesR respectively. The genomic prediction accuracies were mostly moderate and high for growth and carcass traits, whereas meat quality traits showed relatively low accuracies. We concluded that Bayesian regression approaches, especially for BayesR and BayesC?, were slightly superior to GBLUP for most traits. Increasing with the sizes of reference population, these two approaches are feasible for future application of genomic selection in Chinese beef cattle.
Project description:Captive breeding programs and aquaculture production have commenced worldwide for the globally distributed yellowtail kingfish (Seriola lalandi), and captive bred fingerlings are being shipped from the Southern Hemisphere to be farmed in the Northern Hemisphere. It was recently proposed that Pacific S. lalandi comprise at least three distinct species that diverged more than 2 million years ago. Here, we tested the hypothesis of different "species" in the Pacific using novel genomic data (namely single nucleotide polymorphisms and diversity array technology markers), as well as mtDNA and DNA microsatellite variation. These new data support the hypothesis of population subdivision between the Northeast Pacific, Northwest Pacific and South Pacific, and genetic divergence indicates restriction to the gene flow between hemispheres. However, our estimates of maximum mtDNA and nuclear DNA divergences of 2.43% and 0.67%, respectively, were within the ranges more commonly observed for populations within species than species within genera. Accordingly our data support the more traditional view that S. lalandi in the Pacific comprises three distinct populations rather than the subdivisions into several species.
Project description:The influence of sea-cage aquaculture on wildfish assemblages has received little attention outside of Europe. Sea-cage aquaculture of finfish is a major focus in South Australia, and while the main species farmed is southern bluefin tuna (Thunnus maccoyii), there is also an important yellowtail kingfish (Seriola lalandi) industry. Yellowtail kingfish aquaculture did not appear to have any local or regional effects on demersal assemblages (primarily fish, but also some crustaceans) surveyed by baited remote underwater video (BRUV) in Fitzgerald Bay. We did, however, detect small scale spatial variations in assemblages within the bay. The type of bait used strongly influenced the assemblage recorded, with significantly greater numbers of fish attracted to deployments where sardines were used as the bait to compared to those with no bait. The pelleted feed used by the aquaculture industry was just as attractive as sardines at one site, and intermediate between sardines and no bait at the other. There was significant temporal variability in assemblages at both farm sites and one control site, while the second control site was temporally stable (over the 9 weeks of the study). Overall, the results suggested that aquaculture was having little if any impact on the abundance and assemblage structure of the demersal macrofauna in Fitzgerald Bay.
Project description:Three cohorts of farmed yellowtail kingfish (Seriola lalandi) from South Australia were examined for Chlamydia-like organisms associated with epitheliocystis. To characterize the bacteria, 38 gill samples were processed for histopathology, electron microscopy, and 16S rRNA amplification, sequencing, and phylogenetic analysis. Microscopically, the presence of membrane-enclosed cysts was observed within the gill lamellae. Also observed was hyperplasia of the epithelial cells with cytoplasmic vacuolization and fusion of the gill lamellae. Transmission electron microscopy revealed morphological features of the reticulate and intermediate bodies typical of members of the order Chlamydiales. A novel 1,393-bp 16S chlamydial rRNA sequence was amplified from gill DNA extracted from fish in all cohorts over a 3-year period that corresponded to the 16S rRNA sequence amplified directly from laser-dissected cysts. This sequence was only 87% similar to the reported "Candidatus Piscichlamydia salmonis" (AY462244) from Atlantic salmon and Arctic charr. Phylogenetic analysis of this sequence against 35 Chlamydia and Chlamydia-like bacteria revealed that this novel bacterium belongs to an undescribed family lineage in the order Chlamydiales. Based on these observations, we propose this bacterium of yellowtail kingfish be known as "Candidatus Parilichlamydia carangidicola" and that the new family be known as "Candidatus Parilichlamydiaceae."
Project description:Anthropogenic CO2 emissions are causing global ocean warming and ocean acidification. The early life stages of some marine fish are vulnerable to elevated ocean temperatures and CO2 concentrations, with lowered survival and growth rates most frequently documented. Underlying these effects, damage to different organs has been found as a response to elevated CO2 in larvae of several species of marine fish, yet the combined effects of acidification and warming on organ health are unknown. Yellowtail kingfish, Seriola lalandi, a circumglobal subtropical pelagic fish of high commercial and recreational value, were reared from fertilization under control (21 °C) and elevated (25 °C) temperature conditions fully crossed with control (500 µatm) and elevated (1,000 µatm) pCO2 conditions. Larvae were sampled at 11 days and 21 days post hatch for histological analysis of the eye, gills, gut, liver, pancreas, kidney and liver. Previous work found elevated temperature, but not elevated CO2, significantly reduced larval kingfish survival while increasing growth and developmental rate. The current histological analysis aimed to determine whether there were additional sublethal effects on organ condition and development and whether underlying organ damage could be responsible for the documented effects of temperature on survivorship. While damage to different organs was found in a number of larvae, these effects were not related to temperature and/or CO2 treatment. We conclude that kingfish larvae are generally vulnerable during organogenesis of the digestive system in their early development, but that this will not be exacerbated by near-future ocean warming and acidification.
Project description:Genomic selection has been widely used for complex quantitative trait in farm animals. Estimations of breeding values for slaughter traits are most important to beef cattle industry, and it is worthwhile to investigate prediction accuracies of genomic selection for these traits. In this study, we assessed genomic predictive abilities for average daily gain weight (ADG), live weight (LW), carcass weight (CW), dressing percentage (DP), lean meat percentage (LMP) and retail meat weight (RMW) using Illumina Bovine 770K SNP Beadchip in Chinese Simmental cattle. To evaluate the abilities of prediction, marker effects were estimated using genomic BLUP (GBLUP) and three parallel Bayesian models, including multiple chains parallel BayesA, BayesB and BayesC? (PBayesA, PBayesB and PBayesC?). Training set and validation set were divided by random allocation, and the predictive accuracies were evaluated using 5-fold cross validations. We found the accuracies of genomic predictions ranged from 0.195±0.084 (GBLUP for LMP) to 0.424±0.147 (PBayesB for CW). The average accuracies across traits were 0.327±0.085 (GBLUP), 0.335±0.063 (PBayesA), 0.347±0.093 (PBayesB) and 0.334±0.077 (PBayesC?), respectively. Notably, parallel Bayesian models were more accurate than GBLUP across six traits. Our study suggested that genomic selections with multiple chains parallel Bayesian models are feasible for slaughter traits in Chinese Simmental cattle. The estimations of direct genomic breeding values using parallel Bayesian methods can offer important insights into improving prediction accuracy at young ages and may also help to identify superior candidates in breeding programs.