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Published on: October 15, 2019
Low major histocompatibility complex class II DQA diversity in the Giant Panda (Ailuropoda melanoleuca)
Liang Zhu1, Xiang-Dong Ruan, Yun-Fa Ge
1College of Life Sciences, Zhejiang University, Hangzhou, PR China. imzl@eyou.com <imzl@eyou.com>
Background:
The giant panda (Ailuropoda melanoleuca) is one of the most endangered animals due to habitat fragmentation and loss. Although the captive breeding program for this species is now nearly two decades old, researches on the genetic background of such captive populations, especially on adaptive molecular polymorphism of major histocompatibility complex (MHC), are still limited. In this study, we characterized adaptive variation of the giant panda's MHC DQA gene by PCR amplification of its antigen-recognizing region (i.e. the exon 2) and subsequent single-strand conformational polymorphism (SSCP) and sequence analyses.
Results:
The results revealed a low level of DQA exon 2 diversity in this rare animal, presenting 6 alleles from 61 giant panda individuals. The observed polymorphism was restricted to 9 amino acid substitutions, all of which occurred at and adjacent to positions forming the functionally important antigen-binding sites. All the samples were in Hardy-Weinberg proportions. A significantly higher rate of non-synonymous than synonymous substitutions at the antigen-binding sites indicated positive selection for diversity in the locus.
Conclusion:
The DQA allelic diversity of giant pandas was low relative to other vertebrates. Nonetheless, the pandas exhibited more alleles in DQA than those in DRB, suggesting the alpha chain genes would play a leading role when coping with certain pathogens and thus should be included in conservation genetic investigation. The microsatellite and MHC loci might predict long-term persistence potential and short-term survival ability, respectively. Consequently, it is recommended to utilize multiple suites of microsatellite markers and multiple MHC loci to detect overall genetic variation in order to design unbiased conservation strategies.
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