Laboratory of Comparative Genomics, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
Human Genetics Center, University of TexasHouston
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Abstract |
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Introduction |
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Genetic variation in a sample is informative in studying population DNA history. Patterns of mismatch distribution and phylogenetic analyses among genes have been utilized to delineate population processes (Slatkin and Hudson 1991
; Rogers and Harpending 1992
; Nee et al. 1994
; Moritz 1995
; Glenn, Stephan, and Braun 1999
). In addition, several methods were also developed to estimate population parameters and to test biological hypotheses (Watterson 1975
; Tajima 1983, 1989
; Fu and Li 1993
; Fu 1994, 1996, 1997
). Compared with its relative the giant panda, the red panda has not received sufficient attention in population genetic studies, partly due to the difficulty in obtaining large samples for such studies, a difficulty which is also common for many other endangered species. Here, we report the first study of mitochondrial DNA sequence variations in a large sample of red pandas.
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Materials and Methods |
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Phylogenetic Analysis and Statistical Tests of Neutrality
For phylogenetic analysis, parsimony (PAUP, version 3.1.1; Swofford 1993
) and median-joining network analyses (Bandelt, Forster, and Röhl 1999
) were used. The homologous sequence of the raccoon (Procyon lotor), the closest living relative of the red panda, was included as an outgroup. The pairwise mismatch distribution was generated using Arlequin, version 2.000 (Schneider, Roessli, and Excoffier 2000). The essential population parameter
was estimated using Watterson's (1975)
estimate, Tajima's (1983)
estimate, and Fu's (1994)
UPBLUE estimate. Watterson's estimate is based on the number of segregating sites among the sequences. Tajima's estimate is based on the calculation of the mean number of pairwise differences of the sequences, while Fu's UPBLUE estimate is done by incorporating the genealogical information of the sequences. A statistical test of neutrality was carried out using Fu's (1997)
FS test. Strictly speaking, all three of these estimators of
are based on the infinite-sites model (Watterson 1975
; Tajima 1983
; Fu 1997
). Since the sequences generated in this study are from the D-loop region that has mutation hot spots, the infinite-sites model is violated to some extent. To minimize the effect of violation of the model on the estimation of
, as well as statistical tests of neutrality, we inferred all the required information for parameter estimation and neutrality testing from the parsimony analysis. This was done by first reconstructing a parsimony tree from the sequences and then inferring the required information from the tree. For example, to infer the total number of mutations in the sample, we counted the total number of steps in the parsimony tree. For each pair of sequences, the distance needed for UPBLUE could easily be computed from the parsimony tree as well.
Fu's FS test of neutrality was used to infer the population history of the red panda. The FS value tends to be negative when there is an excess of recent mutations, and therefore a large negative value of FS will be taken as evidence against the neutrality of mutations, an indication of deviation caused by population growth and/or selection.
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Results and Discussion |
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It is interesting to note that different estimators of put different weights on mutations occurring in different time periods. The UPBLUE puts heavy emphasis on recent mutations, thus revealing relatively recent population process, while Tajima's estimator put more weights on ancient mutations, therefore reflecting ancient population events (Fu 1997
). Hence, a comparison of the two estimates could give some clues as to how population size has changed over time. Since
= 2Nµ for the mitochondrial genome, the ratio of population size change is positively correlated with the
values given a constant mutation rate. Table 4
shows that for the total population, the UPBLUE estimate is about two times as large as that of the Tajima estimate, indicating that the population size has been at least doubled recently. A similar situation was also seen in the Yunnan population (UPBLUE
/Tajima's
= 1.889), but not in the Sichuan population (UPBLUE
/Tajima's
= 1.105).
According to the fossil record, the red panda diverged from its common ancestor with bears about 40 MYA (Mayr 1986
). With this divergence, by comparing the sequence difference between the red panda and the raccoon, the observed mutation rate for the red panda was calculated to be on the order of 10-9 for the D-loop region, which is apparently an underestimate compared with the average rate in mammals (Li 1997
). This underestimation is probably due to multiple recurrent mutations in the D-loop region, as the divergence between the red panda and the raccoon is extremely deep.
It should be noted that population expansion may not be the only explanation for a significant FS test (Fu 1997
). Other evolutionary forces, e.g., genetic hitchhiking and background selection, can also lead to similar patterns of variation. However, we did not observe any obvious population subdivision in the phylogenetic analysis, and we have not seen any data showing selection pressure on the mitochondrial DNA genome of the red panda, especially considering the noncoding nature of the D-loop region. Furthermore, selection would likely produce similar polymorphism patterns in the Sichuan and Yunnan populations, which is not the case in our observations. Therefore, the data presented in this study suggest that population expansion is the most likely cause of the significant FS test for the red panda.
It should also be noted that no shared haplotypes were observed between the Sichuan and Yunnan populations. This is probably due to either the sample size in this study or an implication of limited genetic divergence between these two populations, even though it was not observed in the phylogenetic analysis. The Yangtze River, the second largest river in China, lining between the Sichuan and Yunnan provinces could serve as a natural barrier in recent history (fig. 1 ). However, how complete the separation could be is unclear. According to the FS tests shown above, the effective population size of the Sichuan population is larger and more stable than that of the Yunnan population. Therefore, historically, Sichuan might be the homeland of the red panda, and population growth might have led to a southward expansion to Yunnan.
It is well known that genetic diversity exists in natural populations and is considered the raw material of evolution. When a population grows rapidly, genetic variations will be accumulated and maintained and in the long run will be beneficial to the success of this species. It has been reported that rare and endangered animal species usually show extremely low levels of genetic variation, which were interpreted as one of the critical reasons leading to extinction (O'Brien et al. 1985
; Su et al. 1994
; Wayne 1994
). In this study, we showed that the red panda harbors a considerable amount of genetic variation resulting from both a relatively large effective population size and a recent population expansion, although its population size has been decreasing in the past several decades due to human activity. For the conservation of this endangered species, our results are encouraging. With a high level of genetic variation, the red panda would be more viable than its relative the giant panda, a well-known species with extremely low genetic variation (Su et al. 1994
). This comparison coincides with the field observation and the ex situ breeding of both endangered animals, for which the newborn death rate is much higher for the giant panda than that for the red panda in the field, and the breeding of the red panda is much more successful than that of the giant panda (Hu 1990a, 1990b
). Therefore, as long as efforts are made to protect the natural habitats, the recovery of red panda populations should be expected.
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Supplementary Material |
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Acknowledgements |
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Footnotes |
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1 Keywords: red panda
mitochondrial DNA
D-loop
sequence diversity
neutrality test
population expansion
2 Address for correspondence and reprints: Bing Su, Human Genetics Center, University of TexasHouston, 6901 Bertner Avenue, Houston, Texas 77030. bsu{at}sph.uth.tmc.edu
.
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