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      Whole-genome sequencing of 128 camels across Asia reveals origin and migration of domestic Bactrian camels

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      1 , 2 , 3 , 4 , 1 , 3 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 8 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 1 , 1 , 1 , 3 , 2 , 2 , 8 , 3 , 4 , 23 , 24 , , 3 , , 1 , 2 , 10 ,
      Communications Biology
      Nature Publishing Group UK
      Evolutionary genetics, Molecular evolution, Population genetics, Genome evolution

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          Abstract

          The domestic Bactrian camels were treated as one of the principal means of locomotion between the eastern and western cultures in history. However, whether they originated from East Asia or Central Asia remains elusive. To address this question, we perform whole-genome sequencing of 128 camels across Asia. The extant wild and domestic Bactrian camels show remarkable genetic divergence, as they were split from dromedaries. The wild Bactrian camels also contribute little to the ancestry of domestic ones, although they share close habitat in East Asia. Interestingly, among the domestic Bactrian camels, those from Iran exhibit the largest genetic distance and the earliest split from all others in the phylogeny, despite evident admixture between domestic Bactrian camels and dromedaries living in Central Asia. Taken together, our study support the Central Asian origin of domestic Bactrian camels, which were then immigrated eastward to Mongolia where native wild Bactrian camels inhabit.

          Abstract

          Ming, Yuan et al. performed whole-genome sequencing on 128 wild and domesticated Bactrian camels across Asia. They show that wild and domestic Bactrian camels are genetically diverged from dromedaries, and that wild camels contributed little to domestic camel ancestry despite sharing a habitat in East Asia.

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          Testing for ancient admixture between closely related populations.

          One enduring question in evolutionary biology is the extent of archaic admixture in the genomes of present-day populations. In this paper, we present a test for ancient admixture that exploits the asymmetry in the frequencies of the two nonconcordant gene trees in a three-population tree. This test was first applied to detect interbreeding between Neandertals and modern humans. We derive the analytic expectation of a test statistic, called the D statistic, which is sensitive to asymmetry under alternative demographic scenarios. We show that the D statistic is insensitive to some demographic assumptions such as ancestral population sizes and requires only the assumption that the ancestral populations were randomly mating. An important aspect of D statistics is that they can be used to detect archaic admixture even when no archaic sample is available. We explore the effect of sequencing error on the false-positive rate of the test for admixture, and we show how to estimate the proportion of archaic ancestry in the genomes of present-day populations. We also investigate a model of subdivision in ancestral populations that can result in D statistics that indicate recent admixture.
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            Evaluating the Use of ABBA–BABA Statistics to Locate Introgressed Loci

            Several methods have been proposed to test for introgression across genomes. One method tests for a genome-wide excess of shared derived alleles between taxa using Patterson’s D statistic, but does not establish which loci show such an excess or whether the excess is due to introgression or ancestral population structure. Several recent studies have extended the use of D by applying the statistic to small genomic regions, rather than genome-wide. Here, we use simulations and whole-genome data from Heliconius butterflies to investigate the behavior of D in small genomic regions. We find that D is unreliable in this situation as it gives inflated values when effective population size is low, causing D outliers to cluster in genomic regions of reduced diversity. As an alternative, we propose a related statistic f ^ d , a modified version of a statistic originally developed to estimate the genome-wide fraction of admixture. f ^ d is not subject to the same biases as D, and is better at identifying introgressed loci. Finally, we show that both D and f ^ d outliers tend to cluster in regions of low absolute divergence (dXY ), which can confound a recently proposed test for differentiating introgression from shared ancestral variation at individual loci.
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              Bayesian inference of ancient human demography from individual genome sequences

              Besides their value for biomedicine, individual genome sequences are a rich source of information about human evolution. Here we describe an effort to estimate key evolutionary parameters from sequences for six individuals from diverse human populations. We use a Bayesian, coalescent-based approach to extract information about ancestral population sizes, divergence times, and migration rates from inferred genealogies at many neutrally evolving loci from across the genome. We introduce new methods for accommodating gene flow between populations and integrating over possible phasings of diploid genotypes. We also describe a custom pipeline for genotype inference to mitigate biases from heterogeneous sequencing technologies and coverage levels. Our analysis indicates that the San of Southern Africa diverged from other human populations 108–157 thousand years ago (kya), that Eurasians diverged from an ancestral African population 38–64 kya, and that the effective population size of the ancestors of all modern humans was ~9,000.
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                Author and article information

                Contributors
                yxli@sibs.ac.cn
                zwang01@sibs.ac.cn
                yeluotuo1999@vip.163.com
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                7 January 2020
                7 January 2020
                2020
                : 3
                : 1
                Affiliations
                [1 ]ISNI 0000 0004 1756 9607, GRID grid.411638.9, Key Laboratory of Dairy Biotechnology and Engineering, Ministry of Education, College of Food Science and Engineering, , Inner Mongolia Agricultural University, ; Huhhot, China
                [2 ]Inner Mongolia Institute of Camel Research, West Alax, Inner Mongolia China
                [3 ]ISNI 0000000119573309, GRID grid.9227.e, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, , Chinese Academy of Sciences, ; Shanghai, China
                [4 ]ISNI 0000000119573309, GRID grid.9227.e, Bio-Med Big Data Center, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, , Chinese Academy of Sciences, ; Shanghai, China
                [5 ]ISNI 0000000119573309, GRID grid.9227.e, Gui’an Bio-Med Big Data Center, Shanghai Institutes for Biological Sciences, , Chinese Academy of Sciences, ; Guiyang, China
                [6 ]ISNI 0000 0004 1756 9607, GRID grid.411638.9, Key Laboratory of Clinical Diagnosis and Treatment Technology in Animal Disease, Ministry of Agriculture, College of Veterinary Medicine, , Inner Mongolia Agricultural University, ; Huhhot, China
                [7 ]Bactrian Camel Academe of Altai, Xingjiang Wangyuan Camel Milk Limited Company, Fuhai County, Xijiang, China
                [8 ]GRID grid.440461.3, College of Industrial Technology, , Mongolian University of Science and Technology, ; Ulaanbaater, Mongolia
                [9 ]ISNI 0000 0004 1762 5445, GRID grid.413026.2, University of Mohaghegh Arabili, ; Ardabil, Iran
                [10 ]China-Mongolia Joint Laboratory for Biomacromolecule Research, Ulaanbaatar, Mongolia
                [11 ]Mongolian Wild Camel Protection Area, Ministry of Nature and Environment, Ulaanbaatar, Mongolia
                [12 ]Kirovski Plant, Non-Public Joint-Stock Company, Republic of Kalmykia, Russia
                [13 ]ISNI 0000 0004 0587 3863, GRID grid.425564.4, Institute of Chemistry and Chemical Technology, , Mongolian Academy of Sciences, ; Ulaanbaatar, Mongolia
                [14 ]Bactrian Camel Institute of Alxa, Inner Mongolia, China
                [15 ]ISNI 0000 0004 1763 4106, GRID grid.410754.3, Animal Science Institute, , Xinjiang Academy of Animal Science, ; Urumqi, China
                [16 ]Animal Husbandry Bureau of North Urad, Bayannuur, Inner Mongolia China
                [17 ]Animal Husbandry Workstation of West Sunid, Xiliingol, Inner Mongolia China
                [18 ]GRID grid.446296.b, Agrarian Faculty, , Kalmyk State University, ; Republic of Kalmykia, Russia
                [19 ]ISNI 0000 0004 0606 4849, GRID grid.171588.2, Kazakh National Agrarian University, ; Almaty, Kazakhstan
                [20 ]ISNI 0000 0004 1756 9607, GRID grid.411638.9, College of Animal Science, , Inner Mongolia Agricultural University, ; Huhhot, China
                [21 ]ISNI 0000 0004 1757 7666, GRID grid.413375.7, Department of Pharmacy, , Affiliated Hospital of Inner Mongolia Medical University, ; Huhhot, China
                [22 ]Institute of Technology, Ulaanbaatar, Mongolia
                [23 ]GRID grid.495809.9, Shanghai Center for Bioinformation Technology, , Shanghai Industrial Technology Institute, ; Shanghai, China
                [24 ]ISNI 0000 0001 0125 2443, GRID grid.8547.e, Collaborative Innovation Center for Genetics and Development, , Fudan University, ; Shanghai, China
                Author information
                http://orcid.org/0000-0001-8108-627X
                Article
                734
                10.1038/s42003-019-0734-6
                6946651
                31925316
                628de401-add8-4f2a-9ba7-ef3ba767ef97
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 July 2019
                : 10 December 2019
                Funding
                Funded by: National Key R&D Program of China (2017YFC0907505, 2017YFC0908405), the Chinese Academy of Sciences (KFJ-STS-QYZD-126, ZDBS-SSW-DQC-02)
                Funded by: FundRef https://doi.org/10.13039/501100004739, Youth Innovation Promotion Association of the Chinese Academy of Sciences (Youth Innovation Promotion Association CAS);
                Award ID: 2017325
                Award Recipient :
                Funded by: National Key R&D Program of China (2017YFA0505500, 2016YFC0901704)
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 31360397
                Award ID: 31560710
                Award Recipient :
                Funded by: International S&T Cooperation Program of China (2015DFR30680, ky201401002), Special Project of the Inner Mongolia Autonomous Region
                Categories
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                © The Author(s) 2020

                evolutionary genetics,molecular evolution,population genetics,genome evolution

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