In 2004 the chicken genome sequence and more than 2.8 million single nucleotide polymorphisms (SNPs) were reported. This information greatly enhanced the ability of poultry scientists to understand chicken biology, especially with respect to identification of quantitative trait loci (QTL) and genes that control simple and complex traits. To validate and address the quality of the reported SNPs, assays for 3072 SNPS were developed and used to genotype 2576 DNAs isolated from commercial and experimental birds. Over 90% of the SNPs were valid based on the criterion used for segregating, and over 88% had a minor allele frequency of 2% or greater. As the East Lansing (EL) and Wageningen University (WAU) reference panels were genotyped, 1933 SNPs were added to the chicken genetic map, which was used in the second chicken genome sequence assembly. It was also discovered that linkage disequilibrium varied considerably between commercial layers and broilers; with the latter having haplotype blocks averaging 10 to 50 kb in size. Finally, it was estimated that commercial lines have lost 70% or more of their genetic diversity, with the majority of allele loss attributable to the limited number of chicken breeds used.

Characterisation of genetic diversity in a large number of European pig populations has been undertaken with EC support. The populations sampled included local (rare) breeds, national varieties of the major international breeds, commercial lines and the Chinese Meishan breed. A second phase of the project will sample a further 50 Chinese breeds. Neutral genetic markers (AFLP and microsatellites), with individual or bulk typing, were used and compared.

DNA from 59 European pig populations was extracted on samples of about 50 individuals per population. Individuals were typed for 50 microsatellites and for 148 AFLP bands. A subset of 25 populations was typed for 20 microsatellites on pools of DNA. Allele frequencies were estimated by direct allele counting for the co-dominant markers. Frequencies of AFLP negative alleles (absent bands) were obtained by taking the square root of absent band frequencies. Within-breed variability was summarised using standard statistics: expected and observed heterozygosity, mean observed and effective numbers of alleles, and F statistics. Between-breed diversity analysis was based on a bootstrapped Neighbor-Joining (NJ) tree derived from Reynolds distances (DR). The standard distance of Nei (DS) was also calculated.

The use of genetic markers to identify regions of the genome associated with variation in quantitative traits (QTL) is now widespread. Several studies have attempted to find QTLs for growth and fatness in pigs. Since the first published study (Andersson et al., 1994) many groups have found effects on chromosome 4, albeit with different breeds. In theory, joint analysis offers considerable potential to extract additional information from the data. This study aims to investigate the benefits and drawbacks of joint analysis.

Data on birth weight (BWT), growth rate to end of test or slaughter (GRE) and average backfat depth (BF) were supplied from seven different pig populations in six countries. The data from Scotland, France, USA, Netherlands and half of the data from Germany were Meishan (MS) x commercial F2 populations. Data from Sweden and the remaining German data were from wild boar (WB) x commercial F2 populations. A total of 31 different markers were used, all on chromosome 4.