Heritability of harvest growth traits and genotype–environment interactions in barramundi, Lates calcarifer (Bloch)

Domingos, Jose A.; Smith-Keune, Carolyn; Robinson, Nick; Loughnan, Shannon R.; Harrison, Paul J.; Jerry, Dean R.

doi:10.1016/j.aquaculture.2013.03.029

Cited by 62 publications

(29 citation statements)

References 41 publications

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“…Recently, Thodesen et al (2013) reported, in a different population of red tilapia, that the genetic correlation between body weight in freshwater earthen ponds and floating cages was high (0.92 ± 0.06), while that between freshwater earthen ponds and brackish water tanks was low (0.33 ± 0.14). The G × E interaction effect was reported for a range of fish species, including Nile tilapia (Bentsen et al, 2012; Trọng et al, 2013), rainbow trout (Kause et al, 2003), Atlantic cod (Kolstad et al, 2006), Asian and European sea bass (Dupont-Nivet et al, 2010; Domingos et al, 2013; Le Boucher et al, 2013). A synthesis of the literature review across farmed aquaculture species indicates that when the environments are similar (e.g., pond vs. cage), the G × E effect is not of commercial importance for body traits (e.g., Nguyen, 2016; Sae-Lim et al, 2016).…”

Section: Introductionmentioning

confidence: 93%

Effects of Genotype by Environment Interaction on Genetic Gain and Genetic Parameter Estimates in Red Tilapia (Oreochromis spp.)

Nguyen

Hamzah²,

Thoa

2017

Front. Genet.

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The extent to which genetic gain achieved from selection programs under strictly controlled environments in the nucleus that can be expressed in commercial production systems is not well-documented in aquaculture species. The main aim of this paper was to assess the effects of genotype by environment interaction on genetic response and genetic parameters for four body traits (harvest weight, standard length, body depth, body width) and survival in Red tilapia (Oreochromis spp.). The growth and survival data were recorded on 19,916 individual fish from a pedigreed population undergoing three generations of selection for increased harvest weight in earthen ponds from 2010 to 2012 at the Aquaculture Extension Center, Department of Fisheries, Jitra in Kedah, Malaysia. The pedigree comprised a total of 224 sires and 262 dams, tracing back to the base population in 2009. A multivariate animal model was used to measure genetic response and estimate variance and covariance components. When the homologous body traits in freshwater pond and cage were treated as genetically distinct traits, the genetic correlations between the two environments were high (0.85–0.90) for harvest weight and square root of harvest weight but the estimates were of lower magnitudes for length, width and depth (0.63–0.79). The heritabilities estimated for the five traits studied differed between pond (0.02 to 0.22) and cage (0.07 to 0.68). The common full-sib effects were large, ranging from 0.23 to 0.59 in pond and 0.11 to 0.31 in cage across all traits. The direct and correlated responses for four body traits were generally greater in pond than in cage environments (0.011–1.561 vs. −0.033–0.567 genetic standard deviation units, respectively). Selection for increased harvest body weight resulted in positive genetic changes in survival rate in both pond and cage culture. In conclusion, the reduced selection response and the magnitude of the genetic parameter estimates in the production environment (i.e., cage) relative to those achieved in the nucleus (pond) were a result of the genotype by environment interaction and this effect should be taken into consideration in the future breeding program for Red tilapia.

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Section: Introductionmentioning

confidence: 93%

Effects of Genotype by Environment Interaction on Genetic Gain and Genetic Parameter Estimates in Red Tilapia (Oreochromis spp.)

Nguyen

Hamzah²,

Thoa

2017

Front. Genet.

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“…Quantitative genetic approaches have shown that significant amounts of additive genetic variation underlie the observed phenotypic variation (Domingos et al 2013;Fuller et al 2013). In addition, quantitative trait locus (QTL) analyses have located multiple chromosomal regions that control the phenotypic variation (Laine et al 2013;Laghari et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Co-localization of growth QTL with differentially expressed candidate genes in rainbow trout

Kocmarek

Ferguson

Danzmann

2015

Genome

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Abstract:We tested whether genes differentially expressed between large and small rainbow trout co-localized with familial QTL regions for body size. Eleven chromosomes, known from previous work to house QTL for weight and length in rainbow trout, were examined for QTL in half-sibling families produced in September (1 XY male and 1 XX neomale) and December (1 XY male). In previous studies, we identified 108 candidate genes for growth expressed in the liver and white muscle in a subset of the fish used in this study. These gene sequences were BLASTN aligned against the rainbow trout and stickleback genomes to determine their location (rainbow trout) and inferred location based on synteny with the stickleback genome. Across the progeny of all three males used in the study, 63.9% of the genes with differential expression appear to co-localize with the QTL regions on 6 of the 11 chromosomes tested in these males. Genes that co-localized with QTL in the mixed-sex offspring of the two XY males primarily showed up-regulation in the muscle of large fish and were related to muscle growth, metabolism, and the stress response.Key words: rainbow trout, QTL, neomale, growth.Résumé : Les auteurs ont voulu vérifier si des gènes montrant une expression différentielle chez des grandes et des petites truites arc-en-ciel étaient situés au même endroit dans le génome que des QTL pour la taille. Onze chromosomes, connus comme étant porteurs de QTL pour la masse et la longueur des truites, ont été examinés pour des QTL au sein de familles de demi-frères produits en septembre (1 mâle XY et 1 néo-mâle XX) et en décembre (1 mâle XY). Dans des travaux antérieurs, les auteurs avaient identifié 108 gènes candidats pour la croissance qui sont exprimés chez le foie et les muscles lisses chez un sous-ensemble des poissons analysés dans ce travail. Les séquences de ces gènes ont été alignées (BLASTN) sur les génomes de la truite arc-en-ciel et de l'épinoche pour déterminer leur position (truite arc-en-ciel) ou position inférée sur la base de la synténie avec le génome de l'épinoche. Parmi les progénitures des trois mâles employés dans ce travail, 63,9 % des gènes affichant une expression différentielle ont semblé présenter une co-localisation avec des QTL sur 6 des 11 chromosomes testés chez ces mâles. Les gènes qui co-localisaient avec les QTL au sein des progénitures des deux sexes des deux mâles XY étaient principalement surexprimés chez le muscle des grands poissons et étaient impliqués dans la croissance musculaire, le métabolisme et la réponse aux stress. [Traduit par la Rédaction]

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“…Genetic correlations for weight (0.96-0.99) have been observed across different environments in European sea bass (Dicentrarchus labrax L.) (Dupont-Nivet et al, 2008). No significant G × E interactions were detected for the growth-related traits (weight, standard length, and body depth) in barramundi [Lates calcarifer (Bloch)] reared in fresh or seawater cages 62 days post-hatch (r g ≥ 0.97) or commercially reared in freshwater until harvest size (343-469 days post-hatch) in an intensive recirculating aquaculture system vs. a semi-intensive pond (r g approximately 0.99) (Domingos et al, 2013).…”

Section: Tablementioning

confidence: 97%

“…Moreover, Sae-Lim et al (2010) also reported that estimates of genetic correlations can be biased downward with larger standard error when heritability is low (approximately 0.10) compared with higher heritability, as for K in our study. Therefore, the population at harvest could be used to study G × E interactions for HW and BL; however, the estimate of the genetic correlation for K across environments may be biased downward by the population, which also occurred in the study by Domingos et al (2013).…”

Section: Genotype-by-environment Interactionmentioning

confidence: 99%

Estimating genetic parameters and genotype-by-environment interactions in body traits of turbot in two different rearing environments

Guan

Wang

et al. 2016

Aquaculture

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Heritability of harvest growth traits and genotype–environment interactions in barramundi, Lates calcarifer (Bloch)

Cited by 62 publications

References 41 publications

Effects of Genotype by Environment Interaction on Genetic Gain and Genetic Parameter Estimates in Red Tilapia (Oreochromis spp.)

Effects of Genotype by Environment Interaction on Genetic Gain and Genetic Parameter Estimates in Red Tilapia (Oreochromis spp.)

Co-localization of growth QTL with differentially expressed candidate genes in rainbow trout

Estimating genetic parameters and genotype-by-environment interactions in body traits of turbot in two different rearing environments

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