The usefulness of microsatellite markers in pedigree analysis of the sika deer (Cervus nippon) was tested in a herd in which the maternal lineages were recorded. Eighteen sets of microsatellite primers originally designed for bovine, ovine, and cervine loci successfully amplified polymorphic DNA in the deer. The numbers of alleles per locus ranged from two to seven, and the observed heterozygosity ranged from 0.350 to 0.900. The resolution power of the markers in paternity testing was then determined by calculating exclusion probabilities and paternity indices. Parentages of the study population were efficiently discriminated by genotyping 17 microsatellite loci. The microsatellite data were also used to calculate the genetic relatedness between individuals, which significantly correlated with coancestry coefficients for the pairs. Our results demonstrate that the microsatellite markers are efficient tools in studying the social structure and behavior of the sika deer, as well as in monitoring the inbreeding status.
INTRODUCTION
Natural populations of the Japanese sika deer (Cervus nippon) have a promiscuous mating system at high population densities (Minami, personal communication). Because hinds at estrus usually mate with more than one stag, the paternity of calves cannot be easily determined by a behavioral study alone. Such ambiguous paternity of calves has been an obstacle for studying the reproductive success of males and the pedigree structure of the sika deer. This problem, however, can be solved if discrete genetic markers are available to examine the genetic profiles of dams, calves, and alleged sires. Recent studies have utilized microsatellite DNA analysis to obtain the genetic profiles of individuals in mainly species of wild animals. These microsatellite DNA are non-coding, short, and tandemly repeated simple nucleotide sequences. They are highly variable in the number of tandem repeats inherited in a simple Mendelian fashion (Tautz and Renz, 1984; Tautz et al., 1986; Tautz, 1989; Litt and Luty, 1989; Weber and May, 1989). Because of the high variability, microsatellite DNA markers have been successfully used in the pedigree analyses of primates (Takenaka et al., 1993, Deka et al., 1994), carnivores (Fredholm et al., 1995) and many avian species (Ellegren, 1992).
In recent studies, a number of microsatellite markers have been screened for red deer and sika deer, some of which have been found to be diagnostic for detecting variations within a population as well as between different populations (Abernethy, 1994; Slate et al., 1998; Nagata et al., 1998, Tamate et al., in press). These studies have demonstrated the usefulness of microsatellite markers in a population-based study of deer species. For individual-based study, on the other hand, the potential applicability of the microsatellite markers to pedigree analysis has only been inferred (Talbot et al., 1996; Mommens et al., 1998), and the reliability, efficiency, and appropriateness of this technique has not been evaluated in practice. In the present study, therefore, we carried out a pedigree analysis of sika deer in a captive population in which individual histories had been recorded, and tested the usefulness of the microsatellite markers in individual-based studies of the sika deer.
MATERIALS AND METHODS
Animals
A study population of sika deer was kept in an enclosure from 1980 in Nogeyama Zoological Garden, Yokohama, Japan. This population was originally established with five founder animals, two stags, and three hinds. They are captured or introduced in Kanto area, Japan, and unrelated to each other except a stag and a hind introduced from a zoo. The coancestry coefficient (θ) between these individuals were unknown, so the θ between founders was regarded to be zero. The founders subsequently gave birth to 33 offspring during this period. For each newborn, the mother was identified but father was ambiguous. The maternal lineage of this population is shown in Fig. 1. Among 22 males in the study population, only two adult stags over the age of 3 were likely to have sired all the calves; nevertheless, we included all males above 1 year old as candidate males in the paternity analysis. The number of candidate males varied from two to nine for each year. Incestuous breeding was likely to have occurred because mating was not controlled in the study population.
Blood was collected from 20 sika deer of 17 pedigrees, and whole blood or white cell pellets were preserved in ethanol. DNA was extracted by the Phenol-Chloroform method as described in Sambrook et al. (1989).
Microsatellite analysis
Microsatellite primers were tested to amplify 50 ng of template DNA with the internal labeling method (Iwahana et al., 1996). PCR was performed in a total volume of 10 μl reaction mixture with 0.5 μM of each primer, 200 μM of each dNTP, 0.4 μM of [F]-dCTP, and 0.025 unit of TaKaRa Taq DNA polymerase (Takara, Japan) in buffer consisting of 10 mM Tris-HCl (pH 8.3), 50 mM KCl, and 1.5 mM MgCl2. For some primers, 2.5 mM of MgCl2 was added with DMSO for denaturation (Slate et al., 1998). The [F]-dCTPs were obtained from PE Applied Biosystems (PE-ABI). Amplification of microsatellite DNA was carried out with 37 cycles of a series of reactions for 30 sec at 96°C for denaturation, for 1 min for annealing, and for 30 sec at 72°C for elongation. For some primers, PCR was performed by a two-step PCR method, first with an amplification step of seven cycles, followed by a second step of 30 cycles, as described by Slate et al. (1998). Primer-specific annealing temperatures and modifications for the reaction mixture are shown in Table 1. A 0.5 μl sample of each PCR product was mixed with formamide and an internal size marker, ROX350 (PE-ABI), and then electrophoresed in an ABI-PRISM™ 310 Genetic Analyzer for 30 min as described previously (Tamate et al., in press). The fragment length was analyzed with GeneScan™ (PEABI).
Table 1
Microsatellite information and amplification conditions.
Paternity testings was performed using the Cervus computation program (Marshall et al. 1998) with an error rate of 1%. The effectiveness of microsatellite markers for the parentage analyses was tested by calculating the exclusion probability (PE) according to formulae by Chakraborty et al. (1988). The individual's paternity was then determined by calculating the paternity index (PI) according to Evett and Weir (1998) and Essen-Möller (1938), with the prior probability of paternity being set to 0.5. The PI of each candidate male was determined separately for three different cases. Case 1 included six pedigrees in which the mothers were known, and all candidate fathers were included in the analysis. Case 2 included seven pedigrees in which the mothers were known, but not all of the possible fathers were sampled. Case 3 included four offspring, for whom the mothers were not sampled and the fathers were unknown. The paternity was judged to be resolved if the probability of the first candidate was above 0.900, while the probability of the second candidate was below 0.100. By using the Cervus program, we also calculated the polymorphic information content (PIC) according to a formula by Bostein et al. (1980).
Relatedness and coancestry coefficient
Based on the genotype data for the 17 loci, we calculated Queller and Goodnight's genetic relatedness (r) between individuals by using the Kinship computation program. The index is defined as:
where P* is the population frequency of each allele excluding the compared individuals and Px and Py are the frequencies of each allele in the compared indivicuals, respectively (Queller and Goodnight, 1989).The coancestry coefficient (θ) between a pair of individuals was calculated by the path analysis as described (Weir, 1996). This genetic measure is a consequence of sharing identical alleles in different individuals, and equivalent to an inbreeding coefficient of putative offspring of the pair.
RESULTS
Fifteen bovine, 1 ovine, 1 cervine primers successfully amplified polymorphic PCR products under the conditions shown in Table 1. Departure from Hardy-Weinberg equilibrium was not detected in any of those loci when more than 200 samples of the sika deer were genotyped in a separate experiment (data not shown), suggesting that the effect of null alleles is negligible in our analysis.
All individuals were genotyped at all 17 microsatellite loci except for an individual in which the alleles at the TGLA53 locus were not amplified. Each deer had a unique individual genotype. There was no conflict in matching the genotypes of mother and offspring. The number of alleles per locus, the observed heterozygosities, PIC, and the size-ranges of the alleles are summarized in Table 2. The most polymorphic locus, TGLA53, has seven alleles, and was found to be the most informative because of the highest PIC value 0.812. The average heterozygosity for the 17 loci was 0.656.
Table 2
Information of polymorphic markers for analysis of sika deer population.
The exclusion probability for each locus (Pe) and the cumulative power of exclusion for the 17 loci (PE) are shown in Table 2. The PE reached 0.9997 for the two-parent test, and even for one-parent test, the PE exceeded 0.9889.
The genotype data of the 20 individuals were further subjected to paternity testing - the paternity index (PI) of each male was calculated to quantify individual's likelihood of being the true sire. In the two-parent test where the mothers were identified, paternity was resolved clearly with a high confidence level (>0.90) in all pedigrees. Table 3 shows the distribution of PIs of the first candidate (the individual having the highest PI among the possible sires in a test of a certain pedigree) and of the second candidate (an individual that has the second highest PI in the same test). In all pedigrees in cases 1 and 2, where the mothers were sampled, the PI values for the first candidates were above 0.90, while those of the second candidates were below 0.10. In the one-parent test, on the other hand, the PI values of the first candidates ranged from 0.5559 to 0.9998 (Table 3). According to the standard for the confident parentage above, three of four parentages were judged to be resolved.
Table 3
PI for the first and the second candidate of parentage
Figure 2 shows the pedigrees of the Nogeyama deer population reconstructed from the data of the parentage analysis. These results indicate that the two founder stags sired all the calves sampled. The results also suggest that there was incestuous breeding in the study population as was anticipated.
Based on the resolved pedigrees, pairwise coancestry coefficients (θ) from path analysis were calculated. θ ranged from 0 to 0.375, while r ranged from −0.741 to 0.712. Relatedness between the founders was lower than −0.349 in any combination, supporting our assumption that all the founders were unrelated. We then tested the correlation between θ and r. The two indices showed strong and significant corrrelation with the coefficient 0.844 (Fig. 3, Pearson's correlation coefficient, p<0.001).
DISCUSSION
Resolution power of the microsatellite markers in paternity testing
Genetic analysis using microsatellite markers provides useful information in studying the social structure of animals, although its resolution power is fully dependent on the number of available markers. In a behavioral study of the sika deer, which is promiscuous at least at high population densities, a number of diagnostic microsatellite markers will be required to clarify even a simple aspects of their society such as the father-offspring relationship. In the present study, we demonstrated that genotyping 17 loci of the microsatellite markers provides sufficient data to determine the paternity at a high confidence level in relation to the exclusion probabilities and the paternity index. Theoretically, in a one parent test where the mothers are not sampled, as in case 3, the resolution power is not superior to that of the two-parent test. In the present study, however, we were able to determine some of the paternity relationship by means of one-parent testing through the use of a set of markers. The genotyping system described in the present paper has been successfully applied to the study of a wild population of the sika deer in the Kinkazan Island (Tamate et al., in press).
Use of microsatellite markers in estimating relatedness
Microsatellite data are also utilized in estimating genetic relatedness (r) between individuals in wild populations. Theoretically, r is a measure of the genetic similarity between a pair of individuals, which corresponds directly to the proportion of shared alleles in the genomes of the pair. The genetic relatedness has been a powerful tool in dissecting the social structures of many mammalian species (Girman et al., 1997), although, its relationship with classic genetic measures, such as the coancestry coefficient (θ), has not been studied well.
In a population starting from a few founders, microsatellite alleles of the same size are likely to have originated from a single ancestral allele. Under this condition, r can be an alternative genetic measure to θ, because θ is a measure that quantifies the proportion of alleles that are identical by descent in a pair of individuals. The assumption was supported by our data —we demonstrated a strong correlation between θ and r. These results suggested that even without pedigree structure, we can assess the level of inbreeding (or outbreeding) of the sika deer populations by the genetic relatedness calculated from microsatellite data. Moreover, in a captive population, the inbreeding status may be monitored by measuring the genetic relatedness between individuals.
Incestuous breeding, which may lead to an inbreeding depression, may occur in many captive populations where mating is not controlled. In our study population, among 16 calves for whom the paternity was resolved, six calves were found to be inbred to some extent because of the incestuous mating. The microsatellite analysis described in the present paper should be an efficient tool not only in behavioral studies of wild deer populations, but in creating precise breeding programs and monitoring the genetic status of the population.
Acknowledgments
We would like to thank Yoshinobu Nomura, Toshio Shiraishi of Nogeyama Zoological Gardens, Yokohama for providing samples and information regarding the captive deer population, and Hitoshi Suzuki for his advice and encouragement in all aspects of this research.