Designing aquaculture mass selection programs to avoid high inbreeding rates

Bentsen, Hans B.; Olesen, Ingrid

doi:10.1016/s0044-8486(01)00846-8

Cited by 128 publications

(56 citation statements)

References 14 publications

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“…For instance, to maximize genetic diversity in captive broodstocks, the number of founders may be selected so that the captive population is diverse enough to adequately represent the wild source population while taking into account the capacity of the hatchery (Crow and Kimura 1970;Bentsen and Olesen 2002;Frankham 2010;Witzenberger and Hochkirch 2011). Managers can estimate the proportion of expected heterozygosity in a wild population that will be captured by a given number of founders using the following equation: where H f is the mean expected heterozygosity in the N founders and H w is the mean expected heterozygosity in the wild population (Crow and Kimura 1970).…”

Section: Application To Hatchery Managementmentioning

confidence: 99%

Fish Hatchery Genetic Management Techniques: Integrating Theory with Implementation

et al. 2015

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Artificial propagation of fish species in hatcheries has been conducted on a large scale for several decades. In recent years, however, there has been an increase in conservation hatcheries, which aim not only to produce fish for supplementing wild populations but also to preserve the genetic diversity and integrity of threatened or endangered species. Important considerations for the latter are maximizing genetic diversity and effective population size while minimizing inbreeding and adaptation to captivity. Several studies document the theoretical implementation of captive management strategies designed to achieve these goals. However, the practical application of many of these strategies to conservation hatcheries remains challenging, as the majority of the guidelines were developed for small zoo populations. The aims of this review are (1) to survey current fish conservation hatchery managers in order to assess current hatchery practices and goals; (2) to present available management strategies for conservation hatcheries that may minimize the genetic effects of artificial propagation; and (3) to present genetic management options and their trade‐offs to managers developing fish conservation hatcheries. The results of the survey suggest that the majority of the responding conservation and nonconservation hatcheries use random broodstock selection and pairing techniques while valuing the importance of maintaining genetic diversity and effective population size and minimizing inbreeding. This article reviews the application of small‐population management techniques to conservation hatcheries in an effort to increase their utility in recovery plans for endangered fish species.

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Section: Application To Hatchery Managementmentioning

confidence: 99%

Fish Hatchery Genetic Management Techniques: Integrating Theory with Implementation

et al. 2015

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“…In a recent study, Abd-el-kader et al (2013) observed a relatively high level of genetic diversity within and between three Tilapia species namely Tilapia zilli, Oreochromis aureus and Oreochromis niloticus in Egypt. In Nigeria and many other West African countries, T. guineensis is one of the dominant Tilapia species; in view of the importance of genetic variability in selective breeding, it is necessary to assess genetic variability of T. guineensis for sustainable fish improvement in Nigeria and many other African countries (Bentsen and Olesen, 2002).…”

Section: Introductionmentioning

confidence: 99%

Molecular characterization and genetic diversity assessment of Tilapia guineensis from some coastal rivers in Nigeria

Ukenye¹,

Taiwo²,

Oguntade³

et al. 2016

Afr. J. Biotechnol.

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Tilapia guineensis is an important economically and nutritionally important fish commonly found in Nigerian coastal waters. Genetic diversity of the fish was assessed to obtain information that may help in developing appropriate conservation and breeding programmes for improving the economic and nutritional quality of the fish. Twelve (12) Nigerian coastal populations and nine microsatellite loci were considered. All the loci were multi-allelic giving an average of 3.1 alleles per locus. The number of alleles (Na) ranged from two to four alleles per locus while the effective number of expected alleles (Ne) ranged from 1.087 to 2.612. Buguma, Badagry and Brass populations had the highest genetic diversity as was revealed by heterozygosity (observed and expected) and shannon index of the populations. The longest pairwise genetic distance of 0.30 was between Brass in Bayelsa State and River Ethiope in Delta State. Clustering using simple sequence repeat (SSR) data gave four major clusters which did not concur with geographical location clustering. We conclude that although genetic diversity is low in some populations of T. guineensis in Nigerian coastal waters, some populations (Buguma, Badagry and Brass) still retain some genetic variability which may be explored for fish improvement through appropriate breeding and conservation programmes.

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“…Factorial designs with higher densities in the off diagonals lead to reductions in inbreeding if rearing and mating resources for specific full-sib groups are unlimited (Leitch et al, 1994;Dupont-Nivet et al, 2006), but when the number of full-sib families is constrained, factorial designs result in a smaller effective population size and hence much higher rates of inbreeding. Bentsen and Olesen (2002) considered the design of mass selection programmes with TS and RM and recommended at least 50 mating pairs of individuals be established with the number of progeny tested per pair standardised to be not less than 30 to 50. In this study, we have found that OPS and MIM can facilitate breeding designs with smaller numbers of parents selected (i.e.…”

Section: Discussionmentioning

confidence: 99%

Optimised parent selection and minimum inbreeding mating in small aquaculture breeding schemes: a simulation study

Hely¹,

Amer²,

Walker

et al. 2013

Animal

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The effectiveness of low cost breeding scheme designs for small aquaculture breeding programmes were assessed for their ability to achieve genetic gain while managing inbreeding using stochastic simulation. Individuals with trait data were simulated over 15 generations with selection on a single trait. Combinations of selection methods, mating strategies and genetic evaluation options were evaluated with and without the presence of common environmental effects. An Optimal Parent Selection (OPS) method using semi-definite programming was compared with a truncation selection (TS) method. OPS constrains the rate of inbreeding while maximising genetic gain. For either selection method, mating pairs were assigned from the selected parents by either random mating (RM) or Minimum Inbreeding Mating (MIM), which used integer programming to determine mating pairs. Offspring were simulated for each mating pair with equal numbers of offspring per pair and these offspring were the candidates for selection of parents of the next generation. Inbreeding and genetic gain for each generation were averaged over 25 replicates. Combined OPS and MIM led to a similar level of genetic gain to TS and RM, but inbreeding levels were around 75% lower than TS and RM after 15 generations. Results demonstrate that it would be possible to manage inbreeding over 15 generations within small breeding programmes comprised of 30 to 40 males and 30 to 40 females with the use of OPS and MIM. Selection on breeding values computed using Best Linear Unbiased Prediction (BLUP) with all individuals genotyped to obtain pedigree information resulted in an 11% increase in genetic merit and a 90% increase in the average inbreeding coefficient of progeny after 15 generations compared with selection on raw phenotype. Genetic evaluation strategies using BLUP wherein elite individuals by raw phenotype are genotyped to obtain parentage along with a range of different samples of remaining individuals did not increase genetic progress in comparison to selection on raw phenotype. When common environmental effects on full-sib families were simulated, performance of small breeding scheme designs was little affected. This was because the majority of selection must anyway be applied within family due to inbreeding constraints.

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Designing aquaculture mass selection programs to avoid high inbreeding rates

Cited by 128 publications

References 14 publications

Fish Hatchery Genetic Management Techniques: Integrating Theory with Implementation

Fish Hatchery Genetic Management Techniques: Integrating Theory with Implementation

Molecular characterization and genetic diversity assessment of Tilapia guineensis from some coastal rivers in Nigeria

Optimised parent selection and minimum inbreeding mating in small aquaculture breeding schemes: a simulation study

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