bioRxiv preprint doi: https://doi.org/10.1101/2021.03.27.436702; this version posted March 27, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Structural variant selection for high-altitude adaptation using single-molecule 2 long-read sequencing 3 Jinlong Shi1,2,4*, Zhilong Jia1,2,3*, Xiaojing Zhao2*, Jinxiu Sun4*, Fan Liang5*, Minsung Park5*, Chenghui Zhao1, 4 Xiaoreng Wang2, Qi Chen4, Xinyu Song2,3, Kang Yu1, Qian Jia2, Depeng Wang5, Yuhui Xiao5, Yinzhe Liu5, Shijing 5 Wu1, Qin Zhong2, Jue Wu2, Saijia Cui2, Xiaochen Bo6, Zhenzhou Wu7, Manolis Kellis8,9, Kunlun He1,2# 6 1. Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information 7 Technology, Chinese PLA General Hospital, Beijing, China. 8 2. Beijing Key Laboratory for Precision Medicine of Chronic Heart Failure, Chinese PLA General Hospital, Beijing, 9 China. 10 3. Research Center of Medical Artificial Intelligence, Chinese PLA General Hospital, Beijing, China. 11 4. Research Center of Medical Big Data, Chinese PLA General Hospital, Beijing, China. 12 5. GrandOmics Biosciences Inc, Beijing, China. 13 6. Beijing Institute of Radiation Medicine, Beijing, China. 14 7. BioMind Inc, Beijing, China. 15 8. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, 16 MA, USA. 17 9. Broad Institute of MIT and Harvard, Cambridge, MA, USA. 18 *These authors contributed equally to this work. 19 #Corresponding author:
[email protected] 20 21 Abstract: (150 words) 22 Structural variants (SVs) can be important drivers of human adaptation with strong effects, but previous studies 23 have focused primarily on common variants with weak effects.