Whole-genome sequencing of giant pandas provides insights into demographic history and local adaptation

Shancen Zhao;Pingping Zheng;Shanshan Dong;Xiangjiang Zhan;Qi Wu;Xiaosen Guo;Yibo Hu;Weiming He;Shanning Zhang;Wei Fan;Lifeng Zhu;Dong Li;Xuemei Zhang;Quan Chen;Hemin Zhang;Zhihe Zhang;Xuelin Jin;Jinguo Zhang;焕明 杨;Jian Wang;军 王;辅文 魏

CAS - Institute of Zoology;Shenzhen Key Laboratory of Transomics Biotechnologies;University of Chinese Academy of Sciences;Wildlife Conservation Society China Program;China Conservation and Research Center for the Giant Panda;Chengdu Res. Base Giant Panda Breed.;Shaanxi Wild Animal Research Center;Beijing Zoo;University of Copenhagen

发表时间:2013-1

期 刊:Nature Genetics

语 言:English

U R L: http://www.scopus.com/inward/record.url?scp=84871986062&partnerID=8YFLogxK

摘要

The panda lineage dates back to the late Miocene and ultimately leads to only one extant species, the giant panda (Ailuropoda melanoleuca). Although global climate change and anthropogenic disturbances are recognized to shape animal population demography their contribution to panda population dynamics remains largely unknown. We sequenced the whole genomes of 34 pandas at an average 4.7-fold coverage and used this data set together with the previously deep-sequenced panda genome to reconstruct a continuous demographic history of pandas from their origin to the present. We identify two population expansions, two bottlenecks and two divergences. Evidence indicated that, whereas global changes in climate were the primary drivers of population fluctuation for millions of years, human activities likely underlie recent population divergence and serious decline. We identified three distinct panda populations that show genetic adaptation to their environments. However, in all three populations, anthropogenic activities have negatively affected pandas for 3,000 years.

相关科学

生物化学、遗传学和分子生物学
遗传学

被引量

期刊度量

Scopus度量

年份 CiteScore SJR SNIP
1996
1997
1998
1999 14.31 5.209
2000 14.412 5.509
2001 15.204 5.69
2002 13.168 5.248
2003 13.523 4.987
2004 13.814 5.292
2005 14.345 5.183
2006 14.302 4.991
2007 17.931 4.885
2008 20.87 5.153
2009 24.768 6.295
2010 28.013 6.717
2011 60.4 25.298 7.218
2012 57.2 25.621 7.088
2013 50.9 24.193 6.227
2014 48.9 23.98 6.262
2015 50.1 24.157 6.62
2016 52.3 21.979 6.79
2017 45.4 22.243 5.98
2018 45.1 21.508 5.648
2019 45.2 19.795 6.001
2020 49.3
2021

相似文献推荐