Family differences on triploid induction, sexual maturation and its contribution to sea cage performance of Atlantic cod, Gadus morhua

Early maturation has been one of the biological bottlenecks of commercializing Atlantic cod culture. To overcome the bottleneck, production of sterile fish through triploidy and other molecular techniques have been suggested and attempted. Although studies have been carried out on triploid performance of Atlantic cod, no studies have been conducted to see the performance of triploid fish at family level. We produced 29 triploid sibling families using standard hydrostatic pressure technique of newly fertilized eggs with parallel, untreated diploid families. Larvae were reared in separate tanks using standard rearing protocols until reaching 20 g and were PIT tagged. PIT tagged juveniles were transferred to sea cages in duplicate. At 34 months post-hatch, all the fish were sampled and body weight, liver weight and gonadal weight were recorded. Results showed that significant family differences exist between diploid and triploid families in gonadal development, especially for the females. Fish from triploid families had significantly smaller gonadosomatic index than fish from diploid families, but diploid families were heavier than the triploid families. Our result highlight the need for considering a parallel strategy for triploid family selection within the conventional diploid breeding program to exploit the existing variation in triploid performance.acceptedVersio

Genetic variation among full-sib families and the effect of non-genetic factors on growth traits at harvest in Clarias magur (Hamilton, 1822)

Magur (Clarias magur) is an Indian catfish species with a good potential for aquaculture. The expansion of magur aquaculture is hindered because of low reproductive and survival rates. Furthermore, males need to be sacrificed to collect milt for artificial fertilization. At present, magur seed production mainly depends on the wild-caught juveniles and to a smaller extent, from broodfish whose genetic potential is unknown. The availability of high-quality seeds in a sustainable way can be ensured through the selective breeding program for magur. The knowledge of factors influencing growth traits and their genetic parameters is a pre-requisite for implementing a genetic selection program. The present study aimed to quantify the performance of C.magur reared in a two-year class and estimate their heritabilities at stocking and harvest and also to estimate the genetic and phenotypic correlations among them. The growth traits such as Body Weight (BW), Total Length (TL), Body Depth (BD), Head Width (HW), and Average Daily Gain (ADG) were recorded from 1413 animals belonging to 78 fullsib families produced by adopting single pair mating design, after one year of pond culture (traits at harvest). Genetic parameters were also estimated for body weight (BW0) and total length (TL0) measured from 2328 fish from 78 fullsib families at the time of stocking. Magur attained an average BW of 135 g and 24.5 cm TL after one year culture period. The heritabilities of BW, TL, and ADG were 0.44 ± 0.07, 0.32 ± 0.06, and 0.42 ± 0.07, respectively and may be biased upwardly due to the single pair mating design. Genetic correlations between harvest traits were all positive and varied in magnitude between traits (0.74 to 0.99). The results obtained from the current study indicate the presence of genetic variation in magur population for growth traits and selection based on genetic merit can produce improvement in these traits

Genotype by environment interaction for growth in Atlantic Cod (Gadus morhua L.) in four farms of Norway

We studied genotype by environment interaction (G × E) for body weight (BW) of Atlantic cod (Gadus morhua L.) from the National cod breeding program in Norway. Records of 13,811 fish in a nucleus farm (NUC) and two test farms (PENorth, PESouth) in year-class (YC) 2007, and for 9149 fish in NUC and one test farm in YC 2010 were available. Heterogeneity of variances and heritabilities ( ) were estimated using a univariate animal model with environmental effects common to full-sibs (full-model). Genetic correlations ( ) between farms were estimated using a multivariate full-model and a reduced-model (without ) for each YC. Heterogeneity of  was observed in both YC 2007 (0.10 to 0.16) and YC 2010 (0.08 to 0.26). The estimates of  between NUC and test farms were relatively high for both models (0.81 ± 0.19 to 0.96 ± 0.17) and (0.81 ± 0.08 to 0.86 ± 0.04), suggesting low re-ranking of genotypes. Strong re-ranking of genotypes between PESouth and PENorth may be less important because most cod producers are situated close to the breeding nucleus. In conclusion, G × E between NUC and test farms were low and at present there is no need for separate breeding programs for BW in cod

Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar)

© 2017 The Author(s). Background: Salmon Rickettsial Syndrome (SRS) caused by Piscirickettsia salmonis is a major disease affecting the Chilean salmon industry. Genomic selection (GS) is a method wherein genome-wide markers and phenotype information of full-sibs are used to predict genomic EBV (GEBV) of selection candidates and is expected to have increased accuracy and response to selection over traditional pedigree based Best Linear Unbiased Prediction (PBLUP). Widely used GS methods such as genomic BLUP (GBLUP), SNPBLUP, Bayes C and Bayesian Lasso may perform differently with respect to accuracy of GEBV prediction. Our aim was to compare the accuracy, in terms of reliability of genome-enabled prediction, from different GS methods with PBLUP for resistance to SRS in an Atlantic salmon breeding program. Number of days to death (DAYS), binary survival status (STATUS) phenotypes, and 50 K SNP array genotypes were obtained from 2601 smolts challenged with P. salmonis. The reliability o

Evaluation of alternative methods for estimating the precision of REML-based estimates of variance components and heritability

Residual Maximum Likelihood (REML) analysis is the most widely used method to estimate variance components and heritability. This method is based on large sample theory under the assumption that the parameter estimates are asymptotically multivariate normally distributed with covariance matrix given by the inverse of the information matrix. Hence, these sampling variances could be biased if the assumption of asymptotic approximation is incorrect, especially when the sample size is small. Though it is difficult to assess the impact of sample size, an alternative option is to generate a full distribution of the parameters to determine the uncertainty of estimates. In this study, we compared the REML estimates of variance components, heritability and sampling variances of body-weight (BW), body-depth (BD), and condition-factor (K) with those obtained from four sampling-based methods viz., parametric and nonparametric bootstrap, asymptotic sampling and Bayesian estimation. The aim was to understand if a sample size of order 1413 was sufficient to contain adequate information for a reliable asymptotic approximation. The REML solution was close to values obtained from different sampling-based methods indicating that the present sample size was sufficient to estimate reliable genetic variation in different traits with varying heritability. The variance and heritability estimated by a nonparametric bootstrap estimate based on randomization of family effects gave comparable results as evaluated by REML for different traits. Hence, the nonparametric bootstrap estimate can be effectively used to understand whether the sample size is large enough to contain sufficient information under likelihood estimation assumptions

Correlated response of flesh color to selection for harvest weight in coho salmon (Oncorhynchus kisutch)

Chilean coho salmon (Oncorhynchus kisutch) represents about 90% of the worldwide production. From a commercial perspective rapid growth to market weights and product quality are important aspects of profitability. The objective of this study was to determine genetic parameters, genetic trends and correlated response of flesh color (FC) after eight generations of selection for harvest weight (HW) in two coho salmon populations spawning independently in even and odd years. A total of 41,597 and 37,319 records for HW and 4946 and 6731 for FCwere included in the analysis for the even and odd populations, respectively. A linear bivariate animal modelwas used to estimate genetic parameters and compute breeding values for both traits. Estimated heritabilities for HWand FCwere 0.41 +/- 0.03 and 0.08 +/- 0.02 in the even population and 0.22 +/- 0.03 and 0.04 +/- 0.01 the in odd population, respectively. Genetic and phenotypic correlations betweenHW and FC were 0.15 +/- 0.11 and 0.07 +/- 0.02 in the even population and 0.25 +/- 0.14 and 0.12 +/- 0.02 in odd population, respectively. Response to selection was measured as the slope of the linear regression fitted on the mean breeding values per generation per trait. We found a positive genetic trend for both traits after eight generations of selection for HW. The increase in HW per generation was 0.31 +/- 0.01 and 0.26 +/- 0.02 kg for the even and odd populations, respectively. The correlated increase in FC was 0.04 +/- 0.01 and 0.04 +/- 0.00 fan units per generation in the even and odd population, respectively, showing that selection for HWcan increase FC. Statement of relevance. Correlated response in color to selection for growth in cohoU-inicia Grant, from VID, Universidad de Chile Canada through Genome Canada Genome British Columbia Genome Quebe

Genetic parameters for Piscirickettsia salmonis resistance, sea lice (Caligus rogercresseyi) susceptibility and harvest weight in rainbow trout (Oncorhynchus mykiss)

Piscirickettsiosis caused by the intracellular bacterium Piscirickettsia salmonis and caligidosis produced by the ectoparasite Caligus rogercresseyi, are important diseases which generate great economic losses in salmonid farming in Chile. Selective breeding for pathogen resistance has been proposed as an alternative tool for the control of diseases. The objective of the present study is to determine the levels of genetic variation for resistance to P. salmonis and susceptibility to C. rogercresseyi, in addition to investigating the levels of genetic co-variation between these traits and harvest weight in rainbow trout. Resistance to P. salmonis was defined as individual day of death (SRS_DD) and as binary survival (SRS_BS) after an experimental challenge carried out by intraperitoneal injection of an inoculum based on LF89 strain. Susceptibility to C. rogercresseyi (CAL) was measured as the sum of the parasitic load on the pectoral and caudal fins per fish after an experimental challenge. Harvest weight (HW) was recorded in individuals genetically related to challenged fish and analyzed to determine the genetic correlations between this trait and the previous ones. A linear multi-trait animal model was used to estimate (co)variance components for SRS_DD, CAL and HW. A single-trait probit threshold animal model was used to estimate variance components for SRS_BS on the underlying scale. Bivariate linear animal models were used to estimate genetic correlations between SRS_BS on the observed scale and all other traits. The heritabilities for SRS_DD, CAL and HW were 0.45 ± 0.06, 0.08 ± 0.02 and 0.35 ± 0.06, respectively. The heritabilities for SRS_BS were 0.28 ± 0.03 and 0.38 ± 0.05 on the underlying and observed scale, respectively. The genetic correlation between SRS_DD and CAL and between SRS_BS and CAL were 0.39 ± 0.14 and −0.34 ± 0.15, respectively. All other genetic correlations assessed were not significant. We concluded that there is significant additive genetic variation for P. salmonis resistance and C. rogercresseyi susceptibility, which indicates that it is possible to genetically improve these traits in rainbow trout. In addition, there is an unfavorable genetic correlation between P. salmonis resistance and C. rogercresseyi susceptibility and a null genetic correlation between growth and these traits. These results suggest that resistance to P. salmonis or C. rogercresseyi can be simultaneously improved with harvest weight. However, simultaneous selection for P. salmonis and C. rogercresseyi resistance must account for the unfavorable genetic relationship between both traits in this rainbow trout breeding population

Genomic prediction accuracy for resistance against piscirickettsia salmonis in farmed rainbow trout

Salmonid rickettsial syndrome (SRS), caused by the intracellular bacterium Piscirickettsia salmonis, is one of the main diseases affecting rainbow trout (Oncorhynchus mykiss) farming. To accelerate genetic progress, genomic selection methods can be used as an effective approach to control the disease. The aims of this study were: (i) to compare the accuracy of estimated breeding values using pedigree-based best linear unbiased prediction (PBLUP) with genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), Bayes C, and Bayesian Lasso (LASSO); and (ii) to test the accuracy of genomic prediction and PBLUP using different marker densities (0.5, 3, 10, 20, and 27 K) for resistance against P. salmonis in rainbow trout. Phenotypes were recorded as number of days to death (DD) and binary survival (BS) from 2416 fish challenged with P. salmonis. A total of 1934 fish were genotyped using a 57 K single-nucleotide polymorphism (SNP) array. All genomic prediction methods achieved higher accuracies than PBLUP. The relative increase in accuracy for different genomic models ranged from 28 to 41% for both DD and BS at 27 K SNP. Between different genomic models, the highest relative increase in accuracy was obtained with Bayes C (approximate to 40%), where 3 K SNP was enough to achieve a similar accuracy to that of the 27 K SNP for both traits. For resistance against P. salmonis in rainbow trout, we showed that genomic predictions using GBLUP, ssGBLUP, Bayes C, and LASSO can increase accuracy compared with PBLUP. Moreover, it is possible to use relatively low-density SNP panels for genomic prediction without compromising accuracy predictions for resistance against P. salmonis in rainbow trout.Aguas Claras S.A. Corporacion de Fomento de la Produccion 11IEI-12843 Fondo Nacional de Desarrollo Cientifico y Tecnologico Regular 1171720 Nucleo Milenio de Salmonidos Invasores Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) 2014/20626-4 2015/25232-7 National Council for Scientific and Technological Development fellowship 308636/2014-

Additional file 2: of Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar)

Reliability from five-fold cross validation steps for PBLUP and different GS models for DAYS and STATUS at different marker densities; Mean reliability table for BLUP and all GS models for DAYS and STATUS at different marker densities and corresponding plots; Increase in reliability (in percentage) for all GS models for DAYS and STATUS at different marker densities compared to PBLUP and corresponding plots. (XLSX 74 kb

Additional file 1: Figure S1. of Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar)

The Kaplan-Meier curves of the survival function was plotted for the test period to show the cumulative mortality across the challenge. (PDF 5 kb