Genetic Characteristics of the Ostrich Population Using Molecular Methods

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1 Genetic Characteristics of the Ostrich Population Using Molecular Methods M. Kawka,* 1 J. O. Horbańczuk,* M. Sacharczuk,* G. Zięba, M. Łukaszewicz,* K. Jaszczak,* and R. Parada* *Polish Academy of Sciences, Institute of Genetics and Animal Breeding, Jastrzębiec, Poland; and Department of Biological Bases for Animal Production, University of Agriculture, Lublin, Poland ABSTRACT A genetic analysis was performed on Polish lyzed. The diversity within breeds, obtained on the basis ostriches from the 3 principal ostrich breeds: of the DNA fingerprinting analysis, proved to be low. red-, blue-, and black-necks. The analysis was based on 2 molecular methods: DNA fingerprinting and microsatellites. The DNA fingerprinting patterns were obtained Among the ostrich populations analyzed, the highest variability potential was observed for black-necked ostriches (the mean diversity of patterns amounted to using the restriction enzyme HinfI and Jeffrey s %, whereas the mean heterozygosity was 0.30) and probe. The second method consisted of a PCR procedure, the lowest was observed for the red-necks. The largest for which 5 VIAS-OS primers specific to the ostrich were genetic similarity was recorded between red- and bluenecked ostriches, but the greatest genetic distance was used. The PCR products were separated on polyacrylamide gel using ALFexpress (Authomated Laser Fluores- between the red- and black-necks. This means that the use of birds of those breeds in crosses should result in cent DNA Sequencer). The study aimed at assessing the the highest heterotic effect. Both of these methods measured the genetic distance between the analyzed ostrich genetic variability within and among the 3 ostrich breeds as well as evaluating the genetic distance between them, breeds that was expected from the geographic origin of and represents the first report on the genetic characteristics these birds. The results obtained in the present study of the ostrich breeds. The results obtained by both methods showed considerable compatibility, especially with regard to the relationship among the breeds anashowed that both analytic methods used can be successfully applied when elaborating on the genetic characteristics of the ostrich. Key words: microsatellite analysis, DNA fingerprinting, genetic variability, genetic distance, ostrich 2007 Poultry Science 86: INTRODUCTION Over the past several years, ostrich farming and breeding have been gaining popularity throughout the world as a new agricultural activity. In Poland the first ostrich farm was founded in 1993, and currently this country is one of the leaders of the European ostrich industry, keeping 3 main ostrich breeds: red-, blue-, and black-necks (Horbańczuk, 2003). Intensive ostrich breeding is a new branch compared with mainstream livestock production. In Poland, breeding work has proved to be difficult because of the relatively short ostrich reproduction period and small mean flock size, which is one of the most important aspects of animal breeding. This means that the possibility of applying traditional breeding methods is very limited. However, because of the development in the last decade of molecular tools (e.g., mini- and microsatellite se Poultry Science Association Inc. Received August 23, Accepted October 11, Corresponding author: m.kawka@ighz.pl quences), new opportunities have arisen making it possible to genetically analyze the ostrich population. For example, highly polymorphic microsatellite markers, which may be detected quickly and easily and disseminated among laboratories, are used for linkage mapping, parentage testing, or population genetic studies (Cheng et al., 1995; Primmer et al., 1997). The genetic information on microsatellite markers of ratites is scarce when compared with the chicken genome (International Chicken Genome Sequencing Consortium, 2004). For genetic analyses of the ostrich, DNA fingerprinting has been used more often, because with this method no specific knowledge about the genome is necessary. Minisatellite markers would be useful in identifying individuals, families, or breeds (Dunnington et al., 1990), in establishing parentage, for studying the relationships between subspecies, and also for conducting breeding programs. Some of these DNA fingerprinting pattern (DFP) applications were used by Sacharczuk et al. (2001) to identify the dizygosity and monozygosity of ostrich twins. Thus, the aim of the present study was to elaborate on the genetic characteristics of the ostrich population by 277

2 278 KAWKA ET AL. Table 1. Characteristics of the 5 ostrich microsatellite loci used in the current study Number of Length of Microsatellite Sequence of microsatellite Repeat motif alleles alleles (bp) VIAS-OS4 CTCCTGGATGTTCTAGCAGT (GTGTAT) 2 (GT) to 268 CTCCTTGTCCAGCCATATAC (GCGT) 4 (GT) 17 VIAS-OS8 ACTAAACTCCTCGCTGCTGG to 140 CTAAGATGCAAGGGTGAATTGAG (AC) 11 VIAS-OS14 CACTTCTCCGAATTTTAAAAGG to 245 AGGAAGAGATGTGGAGTCCC (AC) 21 VIAS-OS22 AAGTAGGAGAATGGTTCTGC (TG) 2 TA(TG) to 164 TCATACACACACATGCACAC TTTA(TG) 4 CA (TG) 4 VIAS-OS29 TTTTCGTCTTCCACCCACTG (AC) 13 GG(AC) to 173 CTGCTTCTTCCGTGTGTGTC GG(AC) 4 using 2 molecular methods: DNA fingerprinting and 5 tested ostrich microsatellites (VIAS-OS4, VIAS-OS8, VIAS-OS14, VIAS-OS22, and VIAS-OS29 loci; Ward et al., 1998). The analysis included an evaluation of the genetic variability within and between the 3 breeds (red-, blue-, and black-necked ostriches) and of the genetic distances among them. MATERIALS AND METHODS The 3 main ostrich breeds (red-, blue-, and black-necks) were obtained from the oldest Polish farms in Garczyn and Płużnica (north of the country), which maintain the birds in conditions compliant with EU directives (Horbańczuk, 2002, 2003). The experimental population consisted of 66 individuals descended from 66 cocks and hens, maintained in unrelated reproduction pairs for 2 generations. Analysis of Minisatellites The DNA fingerprinting analysis was performed according to the methods of Sambrook et al. (1989). Ostrich genomic DNA samples were isolated from feathers and incubated overnight at 56 C with proteinase K (Taberlet and Bouvet, 1991). The DNA was purified by 2 phenolchloroform-isoamyl-alcohol extractions. Because DNA fingerprints can be obtained only from the undegraded DNA, each sample was examined by a spectrophotometer and electrophoresis. The DNA samples (10 g) were digested with the HinfI restriction enzyme for 16 h. The DNA fragments were separated by electrophoresis in 0.8% agarose gel for 48 h and visualized by staining with ethidium bromide. The DNA fragments were then transferred onto standard Hybond-Npf nylon filters (membrane optimized for nucleic acid transfer; Amersham Life Science, Buckinghamshire, UK) in 20 SSC buffer (1.5 M NaCl and 0.15 M sodium citrate) using the standard capillary method and left overnight. Next, the filters were prehybridized for 40 min at 50 C and hybridized to probe (Jeffreys et al., 1985) for 30 min at the same temperature. The chemiluminescent signal was detected using Lumi-Phose 530 solution (Cellmark Diagnostics, Germantown, MD). Selection of restriction enzymes and probes (33.15 or 33.6) was performed on the basis of the authors research and was based on the number of bands. In the case of the Struthio camelus species, probe was found to be highly polymorphic. A combination of the HinfI enzyme and probe has been effective in many studies, principally in phylogenetic studies (Zawadzka, 1999; Wan et al., 2003). The DFP analysis included only bands representing fragments larger than 2 kb. For control, all paths on the autoradiogram were related to paths on the DNA size standard. The bands were accepted as the same for both paths, were compared if the difference in migration between the 2 bands exceeded 0.5 mm (Hau et al., 1997), and were compared if the intensity of one band was not more than double that of the other. Two types of DFP were made: those of individual DNA samples and those of DNA pools, obtained from each animal within each breed (animals used for the pool analysis were not analyzed as individuals). The DFP of individual DNA samples were used to determine the degree of band sharing (BS) and the band frequencies within the ostrich populations. Pooled DNA from different breeds was used to produce DFP patterns that were representative of the populations analyzed. Banding patterns were compared between lines to classify shared and nonshared bands. Bands were regarded as nonshared if they differed in their position by more than half of the bandwidth and if the intensity ratio was less than 1:2. Statistical Analysis Statistical analyses were performed using the procedure in the SAS statistical package (SAS Institute, 1989). The significance of differences between means was tested using the Duncan multiple-range test of the GLM procedure. The principal statistical parameter of band patterns, that is, BS based on the number of common bands between 2 individual samples, was used to describe the similarity between DFP profiles. On the basis of BS parameters, the probability of identity (Wetton et al., 1987), the total number of distinct and recombinationally sepa-

3 GENETIC ANALYSIS OF THE OSTRICH POPULATION 279 Table 2. Mean values 1 of DNA fingerprinting parameters for ostrich breeds obtained using the HinfI enzyme and probe Mean number Mean band of line sharing Probability Breed (LSM ± SE) (LSM ± SE) of identity Black-necks 34.3 a ± c ± Blue-necks 37.0 b ± b ± Red-necks 32.6 a ± a ± a c Means within a column with no common superscript are different (P 0.05). 1 LSM = Least squares mean. rable hypervariable loci (Lynch, 1990), heterozygosity (Stephens et al., 1992), and genetic distance (Lynch, 1990) were determined to compare the individuals analyzed within and between breeds. Microsatellite Analysis The analysis of microsatellite sequences was carried out using 5 selected ostrich microsatellite loci, as described in Table 1. The analysis of microsatellite sequence polymorphism was performed using the PCR method. The PCR was carried out in a total volume of 8.63 ml comprising 100 ng of template DNA, 2.5 pmol of each primer, 100 mm of each deoxynucleoide triphosphate, 0.5 units of DNA polymerase, 10 mm Tris-HCl (ph 8.9), 1.5 mm MgCl 2,50mM KCl, and 0.1% Triton X-100. One primer for each locus was labeled with fluorescein (Cy5). The PCR conditions were optimized for all 5 primer pairs. The following thermal cycling (on a PTC-200 Programmable Thermal Controller; MJ Research, Watertown, MA) amplification conditions were adopted: 5 min of denaturation at 94 C, followed by 30 to 33 cycles of denaturation at 94 C for 30 s, annealing at 55 to 65 C, and extension at 72 C for 90 s. The fluorescent PCR products were separated on 6% denaturing polyacrylamide gels by using an Automated Laser Fluorescent (ALFexpress) DNA Sequencer (Pharmacia Biotech, Uppsala, Sweden). The PCR products were analyzed after 5 min of denaturation in a 50% formamide solution containing blue dextran. The results were visualized and the genotyping was completed with Allele Links 1.01 (Pharmacia Biotech). After automated allele calling and binning within the Allele Links 1.01 software, individual genotypes were manually inspected before exporting the genotype database to Excel (Microsoft Corp., Redmond, WA). Statistical Analysis Allelic frequencies (i.e., the number of alleles per locus) were estimated by direct counting from the genotype observed. The values for genetic distance were calculated using the DISPAN (Ota, 1993) and Microsat (Minch, 1998) programs. RESULTS AND DISCUSSION Genetic Diversity Within Breeds The DFP of individual DNA samples were identified from 29 to 42 bands. The highest number of bands was obtained for the blue-necked ostrich (37) and the lowest number was for the red-necked ostrich (32.6). Another important parameter in the genetic characterization of animal populations is BS. The BS values obtained within the ostrich populations analyzed ranged from to The highest level of BS, and thus the lowest variability of DFP was obtained for the red-necked ostrich. The probability that 2 randomly selected, unrelated individuals had an identical pattern of DNA fingerprints was very low and ranged from for red-necks to for black-necks (Table 2). On the basis of the number of bands, an assessment was made of the mean number of variable loci detected in the DFP, which ranged from (red-necks) to (blue-necks). The level of genetic variability within the 3 ostrich breeds analyzed was determined on the basis of the mean pattern diversity (APD) and mean heterozygosity (Table 3). Based on band frequencies of the DFP, the heterozygosity ranged from 0.23 (red-necks) to 0.30 (black-necks, i.e., was low in all the breeds analyzed). The mean values of the parameters analyzed showed a high level of homozygosity within the ostrich breeds, especially among red-necks, where the APD was and the mean heterozygosity was Analysis of Microsatellites Genotypic and allelic frequencies were calculated on the basis on all 5 microsatellite loci. The genetic diversity within the ostrich populations analyzed was described by the mean number of alleles per locus and the mean expected and observed heterozygosity or total gene diversity (Nei, 1978). Genetic differentiation between populations was assessed by an analysis of molecular variance. For all 3 ostrich populations, the mean number of alleles detected per locus was 10.2, although the actual number of observable alleles at each locus ranged from 2 at locus VIAS-OS8 to 11 at locus VIAS-OS29. The most specific Table 3. Mean values for genetic variability parameters within ostrich breeds obtained by DNA fingerprinting using the HinfI enzyme and probe Mean diversity Mean Breed of patterns (%) heterozygosity Black-necks Blue-necks Red-necks

4 280 KAWKA ET AL. Table 4. Observed heterozygosity (H o ) and expected heterozygosity (H e ) within the ostrich breeds analyzed Black-necks Blue-necks Red-necks Locus H o H e H o H e H o H e VIAS-OS VIAS-OS VIAS-OS VIAS-OS VIAS-OS Mean H (SE) (0.046) (0.046) (0.138) (0.138) (0.144) (0.144) alleles were found in the black-necked ostrich population. No specific alleles were observed in the population of red-necked ostriches. The highest mean heterozygosity was observed in black-necks (Table 4). Microsatellites provided higher heterozygosity values than did the DFP (from to 0.831), but both those markers showed that black-necks had the highest and red-necks the lowest heterozygosity. In total, the results of both marker systems (micro- and minisatellites) were highly correlated. Genetic Diversity Among Breeds Among the ostrich populations analyzed, the highest variability potential was demonstrated by the blacknecked ostrich, whereas the lowest was demonstrated by the red-necked ostrich. Genetic variability among the ostrich breeds analyzed was described on the basis of the mean BS, APD, and genetic distance (Table 5). The closest genetic similarity was recorded between red- and bluenecks. However, the largest genetic distance was observed between red- and black-necks. This implies that the highest heterosis effect could potentially be obtained when crossing birds of those breeds. The breed structure observed in the ostrich populations examined seems to reflect the geographic origin of individual ostrich breeds. The genetic distance, calculated on the basis of the microsatellite analysis, was largest between red- and black-necked ostriches (0.561), whereas the lowest values were observed between red-necks and blue-necks (0.119). This analysis showed that the populations of red-necks were more closely related to the blue-necks than to the black-necks. The highest genetic diversity was observed between the red-necked and black-necked ostriches, and was identical to that obtained by DNA fingerprinting. Also, the dendrograms based on DFP and microsatellite analyses demonstrated the same dependences between the ostrich Table 5. Parameter values describing the genetic distance between 3 ostrich breeds obtained by using the HinfI enzyme and probe Mean diversity Genetic Breed comparison of patterns distance Black- vs. blue-necks Blue- vs. red-necks Black- vs. red-necks populations analyzed. In total, the concordance between the 2 dendrograms was very high. One tree was constructed on the basis of genetic distance by a cluster analysis, using the unweighted pairgroup method (using arithmetic averages), and the second tree was constructed from genetic distance based on the microsatellite analysis, using the neighbor-joining method of Saitou and Nei (1987). Within these trees, the populations were sorted according to their geographic origin. Red-necked ostriches (S. camelus massaicus) live in east-central Africa (eastern Kenya) and blue-necks (S. camelus australis) range from south of the Zambezi River (including Zimbabwe and Namibia), but black-necks live principally in the south of the continent (Republic of South Africa). Moreover, the physical distance between Central and South Africa is several thousand kilometers; thus, the distance separating red- and blue-necked ostriches is smaller than that separating red- and blacknecks. With regard to the estimation of genetic variability and genetic distance between the populations analyzed, both molecular methods were shown to be acceptable, but the microsatellite method was quicker and more economical, and was therefore competitive with the use of DNA fingerprints. On the other hand, the use of DNA fingerprints together with a microsatellite analysis provided more detailed information, and the strategy of linking using both methods was preferred. The present study showed the value of both the DFP and microsatellite analysis for estimating genetic variation. Both of these methods were effective tools for evaluating genetic distance and genetic variation in S. camelus and also for generating large numbers of polymorphic DNA markers in the ostrich. The results described here represent the first molecular genetic analysis of ostrich populations and should be of value for crossbreeding programs. ACKNOWLEDGMENTS This work was supported by a grant from the Polish Ministry of Education, State Committee for Scientific Research, 0656/P06/2003/25, project no. 3 P06D REFERENCES Cheng, H. H., I. Levin, R. L. Vallejo, H. Khatib, J. B. Dodgson, L. B. Crittenden, and J. Hillel Development of a genetic

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