Acronym NA
Category
Aquaculture
Title Efficient combination of QTL detection and introgression schemes in aquaculture Programme National Programme
Instrument (FP6)
Contact Type (FP7)
Strand (Interreg)
NA
Theme (FP7)
Activity Area (FP6)
Regional Area (Interreg)
Action (COST)
NA
Specific Programme (FP7)
NA
Funding source National Coordinator Anna Sonesson Coordinator email anna.sonesson@nofima.no
Coordinator institution
NOFIMA - Norwegian Institute of Food, Fisheries and Aquaculture Research (Norway)
Institutions involved
NA
Start year 2005 End year 2009 Funding (€) € 357,080 Website https://prosjektbanken.forskningsradet.no/en/project/FORISS/165046?Kilde=FORISS&Kilde=EU&distribution=Ar&chart=bar&calcType=funding&Sprak=no&sortBy=date&sortOrder=desc&resultCount=30&offset=4260<P.1=LTP2+Hav Summary The commercial Norwegian fish production constantly needs to optimise and improve all parts of the system to continue to be in the forefront of growing international competition. One vital part of the production system is the genetics of the breeding material that it utilises. Most fish populations still have wild ancestors, which make it possible to introgress valuable traits/genes from these populations to commercial breeding populations. The aim of this project is to develop and validate DNA marker based strategies to simultaneously detect and introgress valuable genes from wild fish populations into the genomes of cultured fish populations, while minimising the genetic lag between top nucleus breeding stock and stocks that come from the introgression programme. Only the desired part of the genome of the wild population should be introgressed into that of the commercial population, whilst the remaining genome of the commercial population should be kept as much as possible intact, and whilst the genetic lag for other economically important traits should be minimal. We will develop a method that combines detection of quantitative trait loci (QTLs) and introgression schemes in order to shorten the time between the detection of the QTL and introgression. This approach will save genotyping costs, monitor the gene effects continuously, and minimise the genetic lag with the very best nucleus breeding stocks. The method will be tested in computer simulations of fish genomes.
Keywords
Engineering;
Fish;
Genomic sequencing;
Genetic;
Marine Region
76
Not associated to marine areas
0
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