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Highland adaptation of birds on the Qinghai-Tibet Plateau via gut microbiota.

Gang LiuChao LiYan LiuChang-Ming ZhengYu NingHong-Guo YangLang SuoXin-Zhang QiHui-Xin LiWan-Yu WenYu-Hang WangHong-Yun QiPing CaiMing-Hao Gong
Published in: Applied microbiology and biotechnology (2022)
Highland birds evolve multiple adaptive abilities to cope with the harsh environments; however, how they adapt to the high-altitude habitats via the gut microbiota remains understudied. Here we integrated evidences from comparative analysis of gut microbiota to explore the adaptive mechanism of black-necked crane, a typical highland bird in the Qinghai-Tibet Plateau. Firstly, the gut microbiota diversity and function was compared among seven crane species (one high-altitude species and six low-altitude species), and then among three populations of contrasting altitudes for the black-necked crane. Microbiota community diversity in black-necked crane was significantly lower than its low-altitude relatives, but higher microbiota functional diversity was observed in black-necked crane, suggesting that unique bacteria are developed and acquired due to the selection pressure of high-altitude environments. The functional microbial genes differed significantly between the low- and high-altitude black-necked cranes, indicating that altitude significantly impacted microbial communities' composition and structure. Adaptive changes in microbiota diversity and function are observed in response to high-altitude environments. These findings provide us a new insight into the adaptation mechanism to the high-altitude environment for birds via the gut microbiota. KEY POINTS: • The diversity and function of gut microbiota differed significantly between the low- and high-altitude crane species. • Black-necked crane adapts to the high-altitude environment via specific gut microbiota. • Altitude significantly impacted microbial communities' composition and structure.
Keyphrases
  • healthcare
  • mental health
  • genetic diversity
  • genome wide analysis
  • bioinformatics analysis