Breeding strategies to improve the egg's natural defence

I. C. Dunn*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The risk posed by food borne pathogens in eggs has taken on a high priority for government and consumer. In Europe there has been concern that plans to move from battery cages may increase the risk from eggs. For this reason there is some pressure to demonstrate progress in reducing risk from eggs. At the level of the egg the approach has been to improve resistance of the eggshell to breakage using selection for quasi-static compression or specific gravity. The review will consider phenotypic measurement and developments in genetics and genomics that can place new tools in the hands of poultry breeders, should they want to use them. New phenotypic measurements that better describe the physical and antibacterial properties of the egg and eggshell need to be developed which accurately measure the egg's natural defence characteristics to complement the developments in chicken genomics. Acoustic resonance analysis to measure the stiffness of the eggshell and ultra-structural measurements using electron microscopy in pedigree populations are methods which have been examined. Also organic matrix measurements, antimicrobial properties and bacterial penetration measurements that have only been of academic interest may be used in test populations. Genetics and genomics can be used with these phenotypic measurements to identify genetic markers that can be used in selection programmes, rather than the measurements themselves, using whole genome scans for quantitative trait loci and association analysis with candidate genes. The availability of the chicken genome sequence and EST resources has made carrying out these analyses easier in pedigree breeding flocks.

Original languageEnglish
Pages (from-to)458-468
Number of pages11
JournalWorld's Poultry Science Journal
Issue number4
Publication statusPublished - 1 Dec 2004


  • Egg-quality
  • EST
  • Genetics
  • Genomics
  • SNP


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