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Comparison of single- and multi-trait approaches to identify best wild candidates for aquaculture shows that the simple way fails.

Authors :
Toomey L
Lecocq T
Bokor Z
Espinat L
Ferincz Á
Goulon C
Vesala S
Baratçabal M
Barry MD
Gouret M
Gouron C
Staszny Á
Mauduit E
Mean V
Muller I
Schlick N
Speder K
Thumerel R
Piatti C
Pasquet A
Fontaine P
Source :
Scientific reports [Sci Rep] 2020 Jul 14; Vol. 10 (1), pp. 11564. Date of Electronic Publication: 2020 Jul 14.
Publication Year :
2020

Abstract

In agriculture, diversifying production implies picking up, in the wild biodiversity, species or populations that can be domesticated and fruitfully produced. Two alternative approaches are available to highlight wild candidate(s) with high suitability for aquaculture: the single-trait (i.e. considering a single phenotypic trait and, thus, a single biological function) and multi-trait (i.e. considering multiple phenotypic traits involved in several biological functions) approaches. Although the former is the traditional and the simplest method, the latter could be theoretically more efficient. However, an explicit comparison of advantages and pitfalls between these approaches is lacking to date in aquaculture. Here, we compared the two approaches to identify best candidate(s) between four wild allopatric populations of Perca fluviatilis in standardised aquaculture conditions. Our results showed that the single-trait approach can (1) miss key divergences between populations and (2) highlight different best candidate(s) depending on the trait considered. In contrast, the multi-trait approach allowed identifying the population with the highest domestication potential thanks to several congruent lines of evidence. Nevertheless, such an integrative assessment is achieved with a far more time-consuming and expensive study. Therefore, improvements and rationalisations will be needed to make the multi-trait approach a promising way in the aquaculture development.

Details

Language :
English
ISSN :
2045-2322
Volume :
10
Issue :
1
Database :
MEDLINE
Journal :
Scientific reports
Publication Type :
Academic Journal
Accession number :
32665568
Full Text :
https://doi.org/10.1038/s41598-020-68315-5