Background Since domestication, chickens did not only disperse into the different parts of the world but they have also undergone significant genomic changes in this process. Many breeds, strains or lines have been formed and those represent the diversity of the species. However, other than the natural evolutionary forces, management practices (including those that threaten the persistence of genetic diversity) following domestication have shaped the genetic make-up of and diversity between today’s chicken breeds. As part of the SYNBREED project, samples from a wide variety of chicken populations have been collected across the globe and were genotyped with a high density SNP array. The panel consists of the wild type, commercial layers and broilers, indigenous village/local type and fancy chicken breeds. The SYNBREED chicken diversity panel (SCDP) is made available to serve as a public basis to study the genetic structure of chicken diversity. In the current study we analyzed the genetic diversity between and within the populations in the SCDP, which is important for making informed decisions for effective management of farm animal genetic resources. Results Many of the fancy breeds cover a wide spectrum and clustered with other breeds of similar supposed origin as shown by the phylogenetic tree and principal component analysis. However, the fancy breeds as well as the highly selected commercial layer lines have reduced genetic diversity within the population, with the average observed heterozygosity estimates lower than 0.205 across their breeds’ categories and the average proportion of polymorphic loci lower than 0.680. We show that there is still a lot of genetic diversity preserved within the wild and less selected African, South American and some local Asian and European breeds with the average observed heterozygosity greater than 0.225 and the average proportion of polymorphic loci larger than 0.720 within their breeds’ categories. Conclusions It is important that such highly diverse breeds are maintained for the sustainability and flexibility of future chicken breeding. This diversity panel provides opportunities for exploitation for further chicken molecular genetic studies. With the possibility to further expand, it constitutes a very useful community resource for chicken genetic diversity research. Electronic supplementary material The online version of this article (10.1186/s12864-019-5727-9) contains supplementary material, which is available to authorized users.

BackgroundSingle nucleotide polymorphism (SNP) panels have been widely used to study genomic variations within and between populations. Methods of SNP discovery have been a matter of debate for their potential of introducing ascertainment bias, and genetic diversity results obtained from the SNP genotype data can be misleading. We used a total of 42 chicken populations where both individual genotyped array data and pool whole genome resequencing (WGS) data were available. We compared allele frequency distributions and genetic diversity measures (expected heterozygosity (He), fixation index (FST) values, genetic distances and principal components analysis (PCA)) between the two data types. With the array data, we applied different filtering options (SNPs polymorphic in samples of two Gallus gallus wild populations, linkage disequilibrium (LD) based pruning and minor allele frequency (MAF) filtering, and combinations thereof) to assess their potential to mitigate the ascertainment bias.ResultsRare SNPs were underrepresented in the array data. Array data consistently overestimated He compared to WGS data, however, with a similar ranking of the breeds, as demonstrated by Spearman’s rank correlations ranging between 0.956 and 0.985. LD based pruning resulted in a reduced overestimation of He compared to the other filters and slightly improved the relationship with the WGS results. The raw array data and those with polymorphic SNPs in the wild samples underestimated pairwise FST values between breeds which had low FST (<0.15) in the WGS, and overestimated this parameter for high WGS FST (>0.15). LD based pruned data underestimated FST in a consistent manner. The genetic distance matrix from LD pruned data was more closely related to that of WGS than the other array versions. PCA was rather robust in all array versions, since the population structure on the PCA plot was generally well captured in comparison to the WGS data.ConclusionsAmong the tested filtering strategies, LD based pruning was found to account for the effects of ascertainment bias in the relatively best way, producing results which are most comparable to those obtained from WGS data and therefore is recommended for practical use.Electronic supplementary materialThe online version of this article (doi: 10.1186/s12864-017-4416-9) contains supplementary material, which is available to authorized users.

Background Migration of a population from its founder population is expected to cause a reduction of its genetic diversity and facilitates differentiation between the population and its founder population, as predicted by the theory of genetic isolation by distance. Consistent with that theory, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be explained well by their geographic expansion from their founders, which is correlated with genetic differentiation. Methods To investigate this in chicken, we estimated the relationship between the genetic diversity of 160 domesticated chicken populations and their genetic distances to wild chicken populations. Results Our results show a strong inverse relationship, i.e. 88.6% of the variation in the overall genetic diversity of domesticated chicken populations was explained by their genetic distance to the wild populations. We also investigated whether the patterns of genetic diversity of different types of single nucleotide polymorphisms (SNPs) and genes are similar to that of the overall genome. Among the SNP classes, the non-synonymous SNPs deviated most from the overall genome. However, genetic distance to the wild chicken still explained more variation in domesticated chicken diversity across all SNP classes, which ranged from 83.0 to 89.3%. Conclusions Genetic distance between domesticated chicken populations and their wild relatives can predict the genetic diversity of the domesticated populations. On the one hand, genes with little genetic variation across populations, regardless of the genetic distance to the wild population, are associated with major functions such as brain development. Changes in such genes may be detrimental to the species. On the other hand, genetic diversity seems to change at a faster rate within genes that are associated with e.g. protein transport and protein and lipid metabolic processes. In general, such genes may be flexible to changes according to the populations’ needs. These results contribute to the knowledge of the evolutionary patterns of different functional genomic regions in the chicken.

Body weight and weight of body parts are of economic importance. It is difficult to directly predict body weight from highly correlated morphological traits through multiple regression. Factor analysis was carried out to examine the relationship between body weight and five linear body measurements (body length, body girth, wing length, shank thickness, and shank length) in South African Venda (VN), Naked neck (NN), and Potchefstroom koekoek (PK) indigenous chicken breeds, with a view to identify those factors that define body conformation. Multiple regression was subsequently performed to predict body weight, using orthogonal traits derived from the factor analysis. Measurements were obtained from 210 chickens, 22 weeks of age, 70 chickens per breed. High correlations were obtained between body weight and all body measurements except for wing length in PK. Two factors extracted after varimax rotation explained 91, 95, and 83% of total variation in VN, NN, and PK, respectively. Factor 1 explained 73, 90, and 64% in VN, NN, and PK, respectively, and was loaded on all body measurements except for wing length in VN and PK. In a multiple regression, these two factors accounted for 72% variation in body weight in VN, while only factor 1 accounted for 83 and 74% variation in body weight in NN and PK, respectively. The two factors could be used to define body size and conformation of these breeds. Factor 1 could predict body weight in all three breeds. Body measurements can be better selected jointly to improve body weight in these breeds.

26Migration of populations from their founder population is expected to cause a reduction in 27 genetic diversity and facilitates population differentiation between the populations and their 28 founder population as predicted by the theory of genetic isolation by distance. Consistent with 29 that, a model of expansion from a single founder predicts that patterns of genetic diversity in 30 populations can be well explained by their geographic expansion from the founders, which is 31 correlated to the genetic differentiation. To investigate this in the chicken, we have estimated the 32 relationship between the genetic diversity in 172 domesticated chicken populations and their 33 genetic distances to wild populations. We have found a strong inverse relationship whereby 34 87.5% of the variation in the overall genetic diversity of domesticated chicken can be explained 35 by the genetic distance to the wild populations. We also investigated if different types of SNPs 36 and genes present similar patterns of genetic diversity as the overall genome. Among different 37 SNP classes, the non-synonymous ones were the most deviating from the overall genome. 38However, the genetic distances to wild populations still explained more variation in domesticated 39 chicken diversity in all SNP classes ranging from 81.7 to 88.7%. The genetic diversity seemed to 40 change at a faster rate within the chicken in genes that are associated with transmembrane 41 transport, protein transport and protein metabolic processes, and lipid metabolic processes. In 42 general, such genes are flexible to be manipulated according to the population needs. On the 43 other hand, genes which the genetic diversity hardly changes despite the genetic distance to the 44 wild populations are associated with major functions e.g. brain development. Therefore, changes 45 in the genes may be detrimental to the chickens. These results contribute to the knowledge of 46 different evolutionary patterns of different functional genomic regions in the chicken.47 48Author summary 49 The chicken was first domesticated about 6000 B.C. in Asia from the jungle fowl. Following 50 domestication, chickens were taken to different parts of the world mainly by humans. 51Evolutionary forces such as selection and genetic drift have shaped diversification within the 52 chicken species. In addition, new breeds or strains have been developed from crossbreeding 53 programs facilitated by man. These events, together with other breeding practices, have led to 54 genomic alterations causing genetic differentiation between the domesticated chickens and their 55 ancestral/wild population as well as manipulation of the genetic diversity within the 56 domesticated chickens. We investigated the relationship between 172 domesticated chicken 57 populations from different selection, breeding and management backgrounds and their genetic 58 distance to the wild type chickens. We found that the genetic diversity within the populations 59 decreases with the increasing genetic distances to the wil...