Literature DB >> 22141902

Quantitative genetic analysis of the physiological stress response in three strains of brook charr Salvelinus fontinalis and their hybrids.

A Crespel1, L Bernatchez, D Garant, C Audet.   

Abstract

Three strains [domestic (D), Laval (L) and Rupert (R)] of brook charr Salvelinus fontinalis and their reciprocal hybrids were submitted to transport stress to measure stress resistance. Primary (cortisol) and secondary (glucose, osmolality and haematocrit) stress responses were measured for each cross. Significant heritabilities were observed for both levels of stress response, with mean ± S.E. heritability (h(2)) = 0.60 ± 0.20 for plasma cortisol and 0.61 ± 0.20 for plasma glucose. There were strain differences whereby the R strain was the least sensitive to stress at the primary and secondary levels. No heterosis was detected, and only one case of outbreeding depression was present. The outbreeding depression was observed in the D(♀) R(♂) hybrid, which had a 27% increase of plasma glucose compared to parental strains. The D(♀) R(♂) and R(♀) L(♂) hybrids had more pronounced variations (increase or decrease) in plasma osmolality than their respective parental strains, but these variations were difficult to relate definitively with the potential secondary stress response. These results indicate a strong potential for genetic improvement in the stress response to transport with the use of purebred crosses while hybridization has little value in this regard.
© 2011 The Authors. Journal of Fish Biology © 2011 The Fisheries Society of the British Isles.

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Year:  2011        PMID: 22141902     DOI: 10.1111/j.1095-8649.2011.03149.x

Source DB:  PubMed          Journal:  J Fish Biol        ISSN: 0022-1112            Impact factor:   2.051


  7 in total

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6.  Thermal regime during parental sexual maturation, but not during offspring rearing, modulates DNA methylation in brook charr (Salvelinus fontinalis).

Authors:  Clare J Venney; Kyle W Wellband; Eric Normandeau; Carolyne Houle; Dany Garant; Céline Audet; Louis Bernatchez
Journal:  Proc Biol Sci       Date:  2022-05-04       Impact factor: 5.530

7.  Network analysis highlights complex interactions between pathogen, host and commensal microbiota.

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  7 in total

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