No abstract

Twenty-five single nucleotide polymorphisms (SNPs) were analyzed in 20 distinct chicken breeds. The SNPs, each located in a different gene and mostly on different chromosomes, were chosen to examine the use of SNPs in or close to genes (g-SNPs), for biodiversity studies. Phylogenetic trees were constructed from these data. When bootstrap values were used as a criterion for the tree repeatability, doubling the number of SNPs from 12 to 25 improved tree repeatability more than doubling the number of individuals per population, from five to ten. Clustering results of these 20 populations, based on the software STRUCTURE, are in agreement with those previously obtained from the analysis of microsatellites. When the number of clusters was similar to the number of populations, affiliation of birds to their original populations was correct (>95%) only when at least the 22 most polymorphic SNP loci (out of 25) were included. When ten populations were clustered into five groups based on STRUCTURE, we used membership coefficient (Q) of the major cluster at each population as an indicator for clustering success level. This value was used to compare between three marker types; microsatellites, SNPs in or close to genes (g-SNPs) and SNPs in random fragments (r-SNPs). In this comparison, the same individuals were used (five to ten birds per population) and the same number of loci (14) used for each of the marker types. The average membership coefficients (Q) of the major cluster for microsatellites, g-SNPs and r-SNPs were 0.85, 0.7, and 0.64, respectively. Analysis based on microsatellites resulted in significantly higher clustering success due to their multi-allelic nature. Nevertheless, SNPs have obvious advantages, and are an efficient and cost-effective genetic tool, providing broader genome coverage and reliable estimates of genetic relatedness.

Genetic relationships among 50 fruiting-mei (Prunus mume Sieb. et Zucc.) cultivars from China and Japan were investigated, using 767 amplified fragment length polymorphism (AFLP) and 103 single nucleotide polymorphism (SNP) markers. The polymorphism among the cultivars was found to be 69.77%, based on EcoR I + Mse I AFLP primer pairs. The sequence alignment of 11 group sequences, derived from 50 samples, yielded 103 SNPs; the total length of genomic sequences was 3683 bp. Among these SNPs, 73 were heterozygous in the loci of different cultivars. The SNP distribution was 58% transition, 40% transversion, and 2% InDels. There was also 1 trinucleotide deletion. AFLP and SNP markers allowed us to evaluate the genetic diversity of these 50 fruiting-mei cultivars. The 2 derived cladograms did display some differences: all cultivars formed 2 subclusters (1A and 1B) in the cladogram based on AFLP polymorphisms, and formed 3 subclusters (2A, 2B, and 2C) in the cladogram based on SNP polymorphisms; and, in the cladogram based on AFLP polymorphisms, most cultivars from the Guangdong to Fujian provinces (G-F) in China, from the Yunnan, Hunan, and Sichuan provinces (Y-S-H) in China, and from Japan grouped in cluster 1A, and 18 (78.26%) of 23 cultivars from Jiangsu to Zhejiang provinces in China (J-Z) grouped in cluster 1B. The results demonstrate that mei cultivars from Japan are clustered with cultivars from China, and support the hypothesis that mei in Japan were introduced from China. Cultivars from the J-Z region of China have more genetic similarities. Cultivars from the G-F and Y-S-H regions have fewer genetic similarities and suggest more germplasm exchanges in the past.