Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference
Summary: The genome of the most recent common ancestor is generally not available but can greatly facilitate the inference of demographic history and the detection of local adaptations. Here, we present a protocol for applying local ancestry inference in present-day samples to reconstruct ancestral...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | STAR Protocols |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666166724007457 |
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| author | Xiaoxi Zhang Baonan Wang Jia Wen Yang Gao Yuwen Pan Shuhua Xu |
| author_facet | Xiaoxi Zhang Baonan Wang Jia Wen Yang Gao Yuwen Pan Shuhua Xu |
| author_sort | Xiaoxi Zhang |
| collection | DOAJ |
| description | Summary: The genome of the most recent common ancestor is generally not available but can greatly facilitate the inference of demographic history and the detection of local adaptations. Here, we present a protocol for applying local ancestry inference in present-day samples to reconstruct ancestral genomes. We describe steps for estimating haplotypes, inferring local ancestry, and assembling ancestral haplotypes. This protocol describes the analytic steps of reconstructing ancestral genomes using the example data of the Miao and She target populations.For complete details on the use and execution of this protocol, please refer to Gao et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. |
| format | Article |
| id | doaj-art-029e34f9323843ccb97fe912ac24947d |
| institution | Kabale University |
| issn | 2666-1667 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | STAR Protocols |
| spelling | doaj-art-029e34f9323843ccb97fe912ac24947d2025-01-18T05:05:14ZengElsevierSTAR Protocols2666-16672025-03-0161103580Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inferenceXiaoxi Zhang0Baonan Wang1Jia Wen2Yang Gao3Yuwen Pan4Shuhua Xu5Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China; State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, ChinaKey Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, ChinaState Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China; Corresponding authorSummary: The genome of the most recent common ancestor is generally not available but can greatly facilitate the inference of demographic history and the detection of local adaptations. Here, we present a protocol for applying local ancestry inference in present-day samples to reconstruct ancestral genomes. We describe steps for estimating haplotypes, inferring local ancestry, and assembling ancestral haplotypes. This protocol describes the analytic steps of reconstructing ancestral genomes using the example data of the Miao and She target populations.For complete details on the use and execution of this protocol, please refer to Gao et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.http://www.sciencedirect.com/science/article/pii/S2666166724007457BioinformaticsGeneticsGenomicsEvolutionary biology |
| spellingShingle | Xiaoxi Zhang Baonan Wang Jia Wen Yang Gao Yuwen Pan Shuhua Xu Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference STAR Protocols Bioinformatics Genetics Genomics Evolutionary biology |
| title | Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference |
| title_full | Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference |
| title_fullStr | Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference |
| title_full_unstemmed | Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference |
| title_short | Protocol for reconstructing ancestral genomes from present-day samples by applying local ancestry inference |
| title_sort | protocol for reconstructing ancestral genomes from present day samples by applying local ancestry inference |
| topic | Bioinformatics Genetics Genomics Evolutionary biology |
| url | http://www.sciencedirect.com/science/article/pii/S2666166724007457 |
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