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Open Access Research article

Search for QTL affecting the shape of the egg laying curve of the Japanese quail

Francis Minvielle1*, Boniface B Kayang23, Miho Inoue-Murayama2, Mitsuru Miwa2, Alain Vignal3, David Gourichon4, André Neau5, Jean-Louis Monvoisin1 and Shin' ichi Ito2

Author Affiliations

1 Génétique et Diversité Animales, Institut National de la Recherche Agronomique, Centre de Jouy, 78352 Jouy-en-Josas, France

2 Faculty of Applied Biological Sciences, Gifu University, Gifu 501–1193, Japan

3 Génétique Cellulaire, Institut National de la Recherche Agronomique, Centre de Toulouse, 31326 Castanet-Tolosan, France

4 Unité Expérimentale de Génétique Avicole, Institut National de la Recherche Agronomique, Centre de Tours, 37380 Nouzilly, France

5 Département de Génétique Animale, Institut National de la Recherche Agronomique, Centre de Jouy, 78352 Jouy-en-Josas, France

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BMC Genetics 2006, 7:26  doi:10.1186/1471-2156-7-26

Published: 5 May 2006

Abstract

Background

Egg production is of critical importance in birds not only for their reproduction but also for human consumption as the egg is a highly nutritive and balanced food. Consequently, laying in poultry has been improved through selection to increase the total number of eggs laid per hen. This number is the cumulative result of the oviposition, a cyclic and repeated process which leads to a pattern over time (the egg laying curve) which can be modelled and described individually. Unlike the total egg number which compounds all variations, the shape of the curve gives information on the different phases of egg laying, and its genetic analysis using molecular markers might contribute to understand better the underlying mechanisms. The purpose of this study was to perform the first QTL search for traits involved in shaping the egg laying curve, in an F2 experiment with 359 female Japanese quail.

Results

Eight QTL were found on five autosomes, and six of them could be directly associated with egg production traits, although none was significant at the genome-wide level. One of them (on CJA13) had an effect on the first part of the laying curve, before the production peak. Another one (on CJA06) was related to the central part of the curve when laying is maintained at a high level, and the four others (on CJA05, CJA10 and CJA14) acted on the last part of the curve where persistency is determinant. The QTL for the central part of the curve was mapped at the same position on CJA06 than a genome-wide significant QTL for total egg number detected previously in the same F2.

Conclusion

Despite its limited scope (number of microsatellites, size of the phenotypic data set), this work has shown that it was possible to use the individual egg laying data collected daily to find new QTL which affect the shape of the egg laying curve. Beyond the present results, this new approach could also be applied to longitudinal traits in other species, like growth and lactation in ruminants, for which good marker coverage of the genome and theoretical models with a biological significance are available.