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Agdzhoyan A, Ponomarev G, Pylev V, Autleva (Kagazezheva) Z, Gorin I, Evsyukov I, Pocheshkhova E, Koshel S, Kuleshov V, Adamov D, Kuznetsova N. The Finnic Peoples of Russia: Genetic Structure Inferred from Genome-Wide and Y-Chromosome Data. Genes (Basel) 2024; 15:1610. [PMID: 39766877 PMCID: PMC11675159 DOI: 10.3390/genes15121610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2024] [Revised: 11/22/2024] [Accepted: 12/12/2024] [Indexed: 01/11/2025] Open
Abstract
Background: Eastern Finnic populations, including Karelians, Veps, Votes, Ingrians, and Ingrian Finns, are a significant component of the history of Finnic populations, which have developed over ~3 kya. Yet, these groups remain understudied from a genetic point of view. Methods: In this work, we explore the gene pools of Karelians (Northern, Tver, Ludic, and Livvi), Veps, Ingrians, Votes, and Ingrian Finns using Y-chromosome markers (N = 357) and genome-wide autosomes (N = 67) and in comparison with selected Russians populations of the area (N = 763). The data are analyzed using statistical, bioinformatic, and cartographic methods. Results: The autosomal gene pool of Eastern Finnic populations can be divided into two large categories based on the results of the PCA and ADMIXTURE modeling: (a) "Karelia": Veps, Northern, Ludic, Livvi, and Tver Karelians; (b) "Ingria": Ingrians, Votes, Ingrian Finns. The Y-chromosomal gene pool of Baltic Finns is more diverse and is composed of four genetic components. The "Northern" component prevails in Northern Karelians and Ingrian Finns, the "Karelian" in Livvi, Ludic, and Tver Karelians, the "Ingrian-Veps" in Ingrians and Veps (a heterogeneous cluster occupying an intermediate position between the "Northern" and the "Karelian" ones), and the "Southern" in Votes. Moreover, our phylogeographic analysis has found that the Y-haplogroup N3a4-Z1927 carriers are frequent among most Eastern Finnic populations, as well as among some Northern Russian and Central Russian populations. Conclusions: The autosomal clustering reflects the major areal groupings of the populations in question, while the Y-chromosomal gene pool correlates with the known history of these groups. The overlap of the four Y-chromosomal patterns may reflect the eastern part of the homeland of the Proto-Finnic gene pool. The carriers of the Y-haplogroup N3a4-Z1927, frequent in the sample, had a common ancestor at ~2.4 kya, but the active spread of N3a4-Z1927 happened only at ~1.7-2 kya, during the "golden" age of the Proto-Finnic culture (the archaeological period of the "typical" Tarand graves). A heterogeneous Y-chromosomal cluster containing Ingrians, Veps, and Northern Russian populations, should be further studied.
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Affiliation(s)
- Anastasia Agdzhoyan
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
| | - Georgy Ponomarev
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
| | - Vladimir Pylev
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
- Biobank of Northern Eurasia, 115201 Moscow, Russia
| | - Zhaneta Autleva (Kagazezheva)
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
- Department of Faculty Therapy, Faculty of Medicine, Maykop State Technological University, 385000 Maykop, Russia
| | - Igor Gorin
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
| | - Igor Evsyukov
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
| | - Elvira Pocheshkhova
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
- Department of Biology with the Course of Medical Genetics, Pharmaceutical Faculty, Kuban State Medical University, Mitrofana Sedina Str., 4, 350063 Krasnodar, Russia
| | - Sergey Koshel
- Department of Cartography and Geoinformatics, Faculty of Geography, Lomonosov Moscow State University, 119991 Moscow, Russia;
| | - Viacheslav Kuleshov
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
- Institute for the History of Material Culture, Russian Academy of Sciences, Dvortsovaya Naberezhnaya, 18A, 191186 Saint-Petersburg, Russia
| | - Dmitry Adamov
- Research Centre for Medical Genetics, 115522 Moscow, Russia; (G.P.); (V.P.); (Z.A.); (I.G.); (I.E.); (E.P.); (V.K.); (D.A.)
| | - Natalia Kuznetsova
- Dipartimento di Scienze Linguistiche e Letterature Straniere, Università Cattolica del Sacro Cuore, Largo Gemelli 1, 20123 Milan, Italy;
- Department of the Languages of Russia, Institute for Linguistic Studies, Russian Academy of Sciences, Tuchkov Per. 9, 199004 Saint-Petersburg, Russia
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Chen H, Xu S. Population genomics advances in frontier ethnic minorities in China. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-024-2659-2. [PMID: 39643831 DOI: 10.1007/s11427-024-2659-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/18/2024] [Indexed: 12/09/2024]
Abstract
China, with its large geographic span, possesses rich genetic diversity across vast frontier regions in addition to the Han Chinese majority. Importantly, demographic events and various natural and cultural environments in Chinese frontier regions have shaped the genomic diversity of ethnic minorities via local adaptations. Thus, insights into the genetic diversity and adaptive evolution of these under-represented ethnic groups are crucial for understanding evolutionary scenarios and biomedical implications in East Asian populations. Here, we focus on ethnic minorities in Chinese frontier regions and review research advances regarding genomic diversity, genetic structure, population history, genetic admixture, and local adaptation. We first provide an overview of the extensive genetic diversity across populations in different Chinese frontier regions. Next, we summarize research progress regarding genetic ancestry, demographic history, the adaptive process, and the archaic identification of multiple ethnic minorities in different Chinese frontier regions. Finally, we discuss the gaps and opportunities in genomic studies of Chinese populations and the need for a more comprehensive understanding of genomic diversity and the evolution of populations of East Asian ancestry in the post-genomic era.
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Affiliation(s)
- Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Shuhua Xu
- Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, 200438, China.
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Ayupova G, Litvinov S, Akhmetova V, Minniakhmetov I, Mokrysheva N, Khusainova R. Population Characteristics of the Spectrum and Frequencies of CFTR Gene Mutations in Patients with Cystic Fibrosis from the Republic of Bashkortostan (Russia). Genes (Basel) 2024; 15:1335. [PMID: 39457459 PMCID: PMC11507265 DOI: 10.3390/genes15101335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Revised: 10/04/2024] [Accepted: 10/15/2024] [Indexed: 10/28/2024] Open
Abstract
BACKGROUND/OBJECTIVES Cystic fibrosis (CF) is one of the most common autosomal-recessive disorders worldwide. The incidence of CF depends on the prevalence of cystic fibrosis transmembrane conductance regulator gene (CFTR) mutations in the population, which is determined by genetic diversity and ethnicity. METHODS The search for the causes of mutations in the transmembrane conductance regulator gene (CFTR) was carried out using targeted next-generation sequencing (NGS) on the Illumina platform in patients with cystic fibrosis from the Republic of Bashkortostan (Russia), taking into account the ethnic structure of the sample. RESULTS A total of 35 distinct causal variants were found in 139 cases from 129 families. Five (F508del, E92K, 3849+10kbC>T, CFTRdele2.3, L138ins) explain 78.7% of identified CF causal alleles. Variants N13103K and 394delTT were found in four families each. Variants 2143delT, S1196X, W1282X, Y84X, G194R, and 1525-1G>A, as well as the two previously described complex alleles-c. [S466X; R1070Q] and str.[G509D;E217G]-were found in two or three families each. Twenty additional variants occurred only once. Variant c.3883_3888dup has not been described previously. Thus, regional and ethnic features were identified in the spectrum of frequencies of pathogenic variants of the CFTR gene in the three major sub-groups of patients-Russians, Tatars, and Bashkirs. CONCLUSIONS Taking into account these results, highlighting the genetic specificity of the region, a more efficient search for CFTR mutations in patients can be performed. In particular it is possible to choose certain test kits for quick and effective genetic screening before use of NGS sequencing.
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Affiliation(s)
- Guzel Ayupova
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, 450008 Ufa, Russia;
| | - Sergey Litvinov
- Institute of Biochemistry and Genetics, 450000 Ufa, Russia; (S.L.); (V.A.)
| | - Vita Akhmetova
- Institute of Biochemistry and Genetics, 450000 Ufa, Russia; (S.L.); (V.A.)
| | | | | | - Rita Khusainova
- Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, 450008 Ufa, Russia;
- Institute of Biochemistry and Genetics, 450000 Ufa, Russia; (S.L.); (V.A.)
- Endocrinology Research Centre, 117292 Moscow, Russia; (I.M.); (N.M.)
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Balinova N, Hudjašov G, Pankratov V, Pennarun E, Reidla M, Metspalu E, Batyrov V, Khomyakova I, Reisberg T, Parik J, Dzhaubermezov M, Aiyzhy E, Balinova A, El'chinova G, Spitsyna N, Khusnutdinova E, Metspalu M, Tambets K, Villems R, Kushniarevich A. Gene pool preservation across time and space In Mongolian-speaking Oirats. Eur J Hum Genet 2024; 32:1150-1158. [PMID: 38605123 PMCID: PMC11369229 DOI: 10.1038/s41431-024-01588-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/27/2024] [Accepted: 03/04/2024] [Indexed: 04/13/2024] Open
Abstract
The Oirats are a group of Mongolian-speaking peoples residing in Russia, China, and Mongolia, who speak Oirat dialects of the Mongolian language. Migrations of nomadic ethnopolitical formations of the Oirats across the Eurasian Steppe during the Late Middle Ages/early Modern times resulted in a wide geographic spread of Oirat ethnic groups from present-day northwestern China in East Asia to the Lower Volga region in Eastern Europe. In this study, we generate new genome-wide and mitochondrial DNA data for present-day Oirat-speaking populations from Kalmykia in Eastern Europe, Western Mongolia, and the Xinjiang region of China, as well as Issyk-Kul Sart-Kalmaks from Central Asia, and historically related ethnic groups from Altai, Tuva, and Northern Mongolia to study the genetic structure and history of the Oirats. Despite their spatial and temporal separation, small current population census, both the Kalmyks of Eastern Europe and the Oirats of Western Mongolia in East Asia are characterized by strong genetic similarity, high effective population size, and low levels of interpopulation structure. This contrasts the fine genetic structure observed today at a smaller geographic scale in traditionally sedentary populations, and is conditioned by high mobility and marriage practices (traditional strict exogamy) in nomadic groups. Conversely, the genetic profile of the Issyk-Kul Sart-Kalmaks suggests a distinct source(s) of genetic ancestry, along with indications of isolation and genetic drift compared to other Oirats. Our results also show that there was limited gene flow between the ancestors of the Oirats and the Altaians during the late Middle Ages. Source of the yurt image: https://www.vecteezy.com/free-vector/yurt .
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Affiliation(s)
- Natalia Balinova
- Research Centre for Medical Genetics, Moskvorechye Str. 1, 115522, Moscow, Russia.
| | - Georgi Hudjašov
- Core Facility of Genomics, Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Vasili Pankratov
- Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Erwan Pennarun
- Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Maere Reidla
- Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Ene Metspalu
- Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Valery Batyrov
- Kalmyk State University named after B. B. Gorodovikov, Pushkina Str. 11, 358000, Elista, Russia
| | - Irina Khomyakova
- Anuchin Research Institute and Museum of Anthropology, Lomonosov Moscow State University, Mokhovaya Str., 11, 125009, Moscow, Russia
| | - Tuuli Reisberg
- Core Facility of Genomics, Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Jüri Parik
- Core Facility of Genomics, Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Murat Dzhaubermezov
- Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences, 71 Prospekt Oktyabrya Str., 450054, Ufa, Russia
- Federal State Educational Institution of Higher Education "Ufa University of Science and Technology", 32 Zaki Validi Str., 450076, Ufa, Russia
| | - Elena Aiyzhy
- Tuvan State University, Kyzyl, Russian Federation, Lenina Str., 36, 667000, Kyzyl, Republiс of Tuva, Russia
| | - Altana Balinova
- Institute of Linguistics, Russian Academy of Sciences, Bolshoi Kislovsky Pereulok, 1, 125009, Moscow, Russia
| | - Galina El'chinova
- Research Centre for Medical Genetics, Moskvorechye Str. 1, 115522, Moscow, Russia
| | - Nailya Spitsyna
- Institute of Ethnology and Anthropology, Russian Academy of Sciences, Leninsky Prospekt, 32 А, 119334, Moscow, Russia
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences, 71 Prospekt Oktyabrya Str., 450054, Ufa, Russia
- Federal State Educational Institution of Higher Education "Ufa University of Science and Technology", 32 Zaki Validi Str., 450076, Ufa, Russia
| | - Mait Metspalu
- Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Kristiina Tambets
- Estonian Biocentre, Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Richard Villems
- Estonian Biocentre, Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia
| | - Alena Kushniarevich
- Estonian Biocentre, Institute of Genomics, University of Tartu, Riia 23B, 51010, Tartu, Estonia.
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Lei C, Liu J, Zhang R, Pan Y, Lu Y, Gao Y, Ma X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Ancestral Origins and Admixture History of Kazakhs. Mol Biol Evol 2024; 41:msae144. [PMID: 38995236 PMCID: PMC11272102 DOI: 10.1093/molbev/msae144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/29/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024] Open
Abstract
Kazakh people, like many other populations that settled in Central Asia, demonstrate an array of mixed anthropological features of East Eurasian (EEA) and West Eurasian (WEA) populations, indicating a possible scenario of biological admixture between already differentiated EEA and WEA populations. However, their complex biological origin, genomic makeup, and genetic interaction with surrounding populations are not well understood. To decipher their genetic structure and population history, we conducted, to our knowledge, the first whole-genome sequencing study of Kazakhs residing in Xinjiang (KZK). We demonstrated that KZK derived their ancestries from 4 ancestral source populations: East Asian (∼39.7%), West Asian (∼28.6%), Siberian (∼23.6%), and South Asian (∼8.1%). The recognizable interactions of EEA and WEA ancestries in Kazakhs were dated back to the 15th century BCE. Kazakhs were genetically distinctive from the Uyghurs in terms of their overall genomic makeup, although the 2 populations were closely related in genetics, and both showed a substantial admixture of western and eastern peoples. Notably, we identified a considerable sex-biased admixture, with an excess of western males and eastern females contributing to the KZK gene pool. We further identified a set of genes that showed remarkable differentiation in KZK from the surrounding populations, including those associated with skin color (SLC24A5, OCA2), essential hypertension (HLA-DQB1), hypertension (MTHFR, SLC35F3), and neuron development (CNTNAP2). These results advance our understanding of the complex history of contacts between Western and Eastern Eurasians, especially those living or along the old Silk Road.
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Affiliation(s)
- Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University, Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
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Masila EM, Ogada SO, Ogali IN, Kennedy GM, Too EK, Ommeh CS. Mitochondrial DNA D-Loop Polymorphisms among the Galla Goats Reveals Multiple Maternal Origins with Implication on the Functional Diversity of the HSP70 Gene. Genet Res (Camb) 2024; 2024:5564596. [PMID: 38348366 PMCID: PMC10861283 DOI: 10.1155/2024/5564596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/12/2024] [Accepted: 01/18/2024] [Indexed: 02/15/2024] Open
Abstract
Despite much attention given to the history of goat evolution in Kenya, information on the origin, demographic history, dispersal route, and genetic diversity of Galla goats remains unclear. Here, we examined the genetic background, diversity, demographic history, and population genetic variation of Galla goats using mtDNA D-loop and HSP70 single-nucleotide polymorphism markers. The results revealed 90 segregating sites and 68 haplotypes in a 600-bp mtDNA D-loop sequence. The overall mean mitochondrial haplotype diversity was 0.993. The haplotype diversities ranged between 0.8939 ± 0.0777 and 1.0000 ± 0.0221 in all populations supporting high genetic diversity. Mitochondrial phylogenetic analysis revealed three Galla goat haplogroups (A, G, and D), supporting multiple maternal ancestries, of which haplogroup A was the most predominant. Analysis of molecular variance (AMOVA) showed considerable variation within populations at 94.39%, evidence of high genetic diversity. Bimodal mismatch distribution patterns were observed while most populations recorded negative results for Tajima and Fu's Fs neutrality tests supporting population expansion. Genetic variation among populations was also confirmed using HSP70 gene fragment sequences, where six polymorphic sites which defined 21 haplotypes were discovered. Analysis of molecular variance revealed a significant FST index value of 0.134 and a high FIS index value of 0.746, an indication of inbreeding. This information will pave the way for conservation strategies and informed breeding to improve Galla or other goat breeds for climate-smart agriculture.
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Affiliation(s)
- Ednah M. Masila
- Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Juja, Kenya
- Veterinary Science Research Institute (VSRI), Kenya Agricultural Livestock and Research Organization (KALRO), P.O. Box 32-00902, Nairobi, Kenya
| | - Stephen O. Ogada
- Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Juja, Kenya
| | - Irene N. Ogali
- Veterinary Science Research Institute (VSRI), Kenya Agricultural Livestock and Research Organization (KALRO), P.O. Box 32-00902, Nairobi, Kenya
| | - Grace M. Kennedy
- Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Juja, Kenya
| | - Eric K. Too
- Veterinary Science Research Institute (VSRI), Kenya Agricultural Livestock and Research Organization (KALRO), P.O. Box 32-00902, Nairobi, Kenya
| | - Cecily S. Ommeh
- Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000-00200, Juja, Kenya
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Alinaghi S, Mohseni M, Fattahi Z, Beheshtian M, Ghodratpour F, Zare Ashrafi F, Arzhangi S, Jalalvand K, Najafipour R, Khorram Khorshid HR, Kahrizi K, Najmabadi H. Genetic Analysis of 27 Y-STR Haplotypes in 11 Iranian Ethnic Groups. ARCHIVES OF IRANIAN MEDICINE 2024; 27:79-88. [PMID: 38619031 PMCID: PMC11017261 DOI: 10.34172/aim.2024.13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/23/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND The study of Y-chromosomal variations provides valuable insights into male susceptibility in certain diseases like cardiovascular disease (CVD). In this study, we analyzed paternal lineage in different Iranian ethnic groups, not only to identify developing medical etiology, but also to pave the way for gender-specific targeted strategies and personalized medicine in medical genetic research studies. METHODS The diversity of eleven Iranian ethnic groups was studied using 27 Y-chromosomal short tandem repeat (Y-STR) haplotypes from Y-filer® Plus kit. Analysis of molecular variance (AMOVA) based on pair-wise RST along with multidimensional scaling (MDS) calculation and Network phylogenic analysis was employed to quantify the differences between 503 unrelated individuals from each ethnicity. RESULTS Results from AMOVA calculation confirmed that Gilaks and Azeris showed the largest genetic distance (RST=0.35434); however, Sistanis and Lurs had the smallest considerable genetic distance (RST=0.00483) compared to other ethnicities. Although Azeris had a considerable distance from other ethnicities, they were still close to Turkmens. MDS analysis of ethnic groups gave the indication of lack of similarity between different ethnicities. Besides, network phylogenic analysis demonstrated insignificant clustering between samples. CONCLUSION The AMOVA analysis results explain that the close distance of Azeris and Turkmens may be the effect of male-dominant expansions across Central Asia that contributed to historical and demographics of populations in the region. Insignificant differences in network analysis could be the consequence of high mutation events that happened in the Y-STR regions over the years. Considering the ethnic group affiliations in medical research, our results provided an understanding and characterization of Iranian male population for future medical and population genetics studies.
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Affiliation(s)
- Somayeh Alinaghi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Marzieh Mohseni
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Zohreh Fattahi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Maryam Beheshtian
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Fatemeh Ghodratpour
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Farzane Zare Ashrafi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Sanaz Arzhangi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Khadijeh Jalalvand
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Reza Najafipour
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Kimia Kahrizi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hossein Najmabadi
- Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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He G, Wang P, Chen J, Liu Y, Sun Y, Hu R, Duan S, Sun Q, Tang R, Yang J, Wang Z, Yun L, Hu L, Yan J, Nie S, Wei L, Liu C, Wang M. Differentiated genomic footprints suggest isolation and long-distance migration of Hmong-Mien populations. BMC Biol 2024; 22:18. [PMID: 38273256 PMCID: PMC10809681 DOI: 10.1186/s12915-024-01828-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 01/12/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND The underrepresentation of Hmong-Mien (HM) people in Asian genomic studies has hindered our comprehensive understanding of the full landscape of their evolutionary history and complex trait architecture. South China is a multi-ethnic region and indigenously settled by ethnolinguistically diverse HM, Austroasiatic (AA), Tai-Kadai (TK), Austronesian (AN), and Sino-Tibetan (ST) people, which is regarded as East Asia's initial cradle of biodiversity. However, previous fragmented genetic studies have only presented a fraction of the landscape of genetic diversity in this region, especially the lack of haplotype-based genomic resources. The deep characterization of demographic history and natural-selection-relevant genetic architecture of HM people was necessary. RESULTS We reported one HM-specific genomic resource and comprehensively explored the fine-scale genetic structure and adaptative features inferred from the genome-wide SNP data of 440 HM individuals from 33 ethnolinguistic populations, including previously unreported She. We identified solid genetic differentiation between HM people and Han Chinese at 7.64‒15.86 years ago (kya) and split events between southern Chinese inland (Miao/Yao) and coastal (She) HM people in the middle Bronze Age period and the latter obtained more gene flow from Ancient Northern East Asians. Multiple admixture models further confirmed that extensive gene flow from surrounding ST, TK, and AN people entangled in forming the gene pool of Chinese coastal HM people. Genetic findings of isolated shared unique ancestral components based on the sharing alleles and haplotypes deconstructed that HM people from the Yungui Plateau carried the breadth of previously unknown genomic diversity. We identified a direct and recent genetic connection between Chinese inland and Southeast Asian HM people as they shared the most extended identity-by-descent fragments, supporting the long-distance migration hypothesis. Uniparental phylogenetic topology and network-based phylogenetic relationship reconstruction found ancient uniparental founding lineages in southwestern HM people. Finally, the population-specific biological adaptation study identified the shared and differentiated natural selection signatures among inland and coastal HM people associated with physical features and immune functions. The allele frequency spectrum of cancer susceptibility alleles and pharmacogenomic genes showed significant differences between HM and northern Chinese people. CONCLUSIONS Our extensive genetic evidence combined with the historical documents supported the view that ancient HM people originated from the Yungui regions associated with ancient "Three-Miao tribes" descended from the ancient Daxi-Qujialing-Shijiahe people. Then, some have recently migrated rapidly to Southeast Asia, and some have migrated eastward and mixed respectively with Southeast Asian indigenes, Liangzhu-related coastal ancient populations, and incoming southward ST people. Generally, complex population migration, admixture, and adaptation history contributed to the complicated patterns of population structure of geographically diverse HM people.
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Affiliation(s)
- Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
| | - Peixin Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Medical Information, Chongqing Medical University, Chongqing, 400331, China
| | - Jing Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Yuntao Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Institute of Forensic Medicine, West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Rong Hu
- School of Sociology and Anthropology, Xiamen University, Xiamen, 361005, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Renkuan Tang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Junbao Yang
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Libing Yun
- Institute of Forensic Medicine, West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Liping Hu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Shengjie Nie
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Lanhai Wei
- School of Ethnology and Anthropology, Inner Mongolia Normal University, Inner Mongolia, 010028, China
| | - Chao Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
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9
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Halili B, Yang X, Wang R, Zhu K, Hai X, Wang CC. Inferring the population history of Kyrgyz in Xinjiang, Northwest China from genome-wide array genotyping. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2023; 181:611-625. [PMID: 37310136 DOI: 10.1002/ajpa.24794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 04/29/2023] [Accepted: 05/26/2023] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Xinjiang plays a vital role in the trans-Eurasian population migration, language diffusion, and culture and technology exchange. However, the underrepresentation of Xinjiang's genomes has hindered a more comprehensive understanding of Xinjiang's genetic structure and population history. MATERIALS AND METHODS We collected and genotyped 70 southern Xinjiang's Kyrgyz (SXJK) individuals and combined the data with modern and ancient Eurasians published. We used allele-frequency methods, including PCA, ADMIXTURE, f-statistics, qpWave/qpAdm, ALDER, Treemix, and haplotype-shared methods including shared-IBD segments, fineSTRUCTURE, and GLOBETROTTER to unveil the fine-scale population structure and reconstruct admixture history. RESULTS We identified genetic substructure within the SXJK population with subgroups showing different genetic affinities to West and East Eurasians. All SXJK subgroups were suggested to have close genetic relationships with surrounding Turkic-speaking groups that is, Uyghur, Kyrgyz from north Xinjiang and Tajikistan, and Chinese Kazakh, suggesting a shared ancestry among those populations. Outgroup-f3 and symmetrical f4 statistics showed a high genetic affinity of SXJK to present-day Tungusic, Mongolic-speaking populations and Ancient Northeast Asian (ANA) related groups. Allele sharing and haplotype sharing profiles revealed the east-west admixture pattern of SXJK. The qpAdm-based admixture models showed that SXJK derived ancestry from East Eurasian (ANA and East Asian, 42.7%-83.3%) and West Eurasian (Western Steppe herders and Central Asian, 16.7%-57.3%), the recent east-west admixture event could be traced to 1000 years ago based on ALDER and GLOBETROTTER analysis. DISCUSSION The high genetic affinity of SXJK to present-day Tungusic and Mongolic-speaking populations and short-shared IBD segments indicated their shared common ancestry. SXJK harbored a close genetic affinity to ANA-related populations, indicating the Northeast Asian origin of SXJK. The West and East Eurasian admixture models observed in SXJK further provided evidence of the dynamic admixture history in Xinjiang. The east-west admixture pattern and the identified ancestral makeup of SXJK suggested a genetic continuity from some Iron Age Xinjiang populations to present-day SXJK.
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Affiliation(s)
- Bubibatima Halili
- Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China
| | - Xiaomin Yang
- Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China
| | - Rui Wang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Kongyang Zhu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Xiangjun Hai
- Key Laboratory of Environmental Ecology and Population Health in Northwest Minority Areas, Northwest Minzu University, Lanzhou, China
| | - Chuan-Chao Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, China
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
- State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
- Institute of Artificial Intelligence, Xiamen University, Xiamen, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
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10
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Wilke F, Herrick N, Matthews H, Hoskens H, Singh S, Shaffer JR, Weinberg SM, Shriver MD, Claes P, Walsh S. Exploring regional aspects of 3D facial variation within European individuals. Sci Rep 2023; 13:3708. [PMID: 36879022 PMCID: PMC9988837 DOI: 10.1038/s41598-023-30855-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Facial ancestry can be described as variation that exists in facial features that are shared amongst members of a population due to environmental and genetic effects. Even within Europe, faces vary among subregions and may lead to confounding in genetic association studies if unaccounted for. Genetic studies use genetic principal components (PCs) to describe facial ancestry to circumvent this issue. Yet the phenotypic effect of these genetic PCs on the face has yet to be described, and phenotype-based alternatives compared. In anthropological studies, consensus faces are utilized as they depict a phenotypic, not genetic, ancestry effect. In this study, we explored the effects of regional differences on facial ancestry in 744 Europeans using genetic and anthropological approaches. Both showed similar ancestry effects between subgroups, localized mainly to the forehead, nose, and chin. Consensus faces explained the variation seen in only the first three genetic PCs, differing more in magnitude than shape change. Here we show only minor differences between the two methods and discuss a combined approach as a possible alternative for facial scan correction that is less cohort dependent, more replicable, non-linear, and can be made open access for use across research groups, enhancing future studies in this field.
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Affiliation(s)
- Franziska Wilke
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA
| | - Noah Herrick
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA
| | - Harold Matthews
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Hanne Hoskens
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Sylvia Singh
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA
| | - John R Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Seth M Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Anthropology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark D Shriver
- Department of Anthropology, The Pennsylvania State University, University Park, PA, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Susan Walsh
- Department of Biology, Indiana University-Purdue University Indianapolis, 723 W Michigan St, Indianapolis, IN, 46202, USA.
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11
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Albert EA, Kondratieva OA, Baranova EE, Sagaydak OV, Belenikin MS, Zobkova GY, Kuznetsova ES, Deviatkin AA, Zhurov AA, Karpulevich EA, Volchkov PY, Vorontsova MV. Transferability of the PRS estimates for height and BMI obtained from the European ethnic groups to the Western Russian populations. Front Genet 2023; 14:1086709. [PMID: 36726807 PMCID: PMC9885218 DOI: 10.3389/fgene.2023.1086709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/05/2023] [Indexed: 01/17/2023] Open
Abstract
Genetic data plays an increasingly important role in modern medicine. Decrease in the cost of sequencing with subsequent increase in imputation accuracy, and the accumulation of large amounts of high-quality genetic data enable the creation of polygenic risk scores (PRSs) to perform genotype-phenotype associations. The accuracy of phenotype prediction primarily depends on the overall trait heritability, Genome-wide association studies cohort size, and the similarity of genetic background between the base and the target cohort. Here we utilized 8,664 high coverage genomic samples collected across Russia by "Evogen", a Russian biomedical company, to evaluate the predictive power of PRSs based on summary statistics established on cohorts of European ancestry for basic phenotypic traits, namely height and BMI. We have demonstrated that the PRSs calculated for selected traits in three distinct Russian populations, recapitulate the predictive power from the original studies. This is evidence that GWAS summary statistics calculated on cohorts of European ancestry are transferable onto at least some ethnic groups in Russia.
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Affiliation(s)
- E. A. Albert
- National Medical Research Center for Endocrinology, Moscow, Russia,Life Sciences Research Center, Moscow Institute of Physics and Technology, Dolgoprudniy, Russia,*Correspondence: E. A. Albert,
| | - O. A. Kondratieva
- Department of Information Systems, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia
| | | | | | | | | | | | - A. A. Deviatkin
- National Medical Research Center for Endocrinology, Moscow, Russia,Life Sciences Research Center, Moscow Institute of Physics and Technology, Dolgoprudniy, Russia
| | - A. A. Zhurov
- National Medical Research Center for Endocrinology, Moscow, Russia
| | - E. A. Karpulevich
- Department of Information Systems, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia
| | - P. Y. Volchkov
- National Medical Research Center for Endocrinology, Moscow, Russia,Life Sciences Research Center, Moscow Institute of Physics and Technology, Dolgoprudniy, Russia
| | - M. V. Vorontsova
- National Medical Research Center for Endocrinology, Moscow, Russia
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12
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Bánfai Z, Kövesdi E, Sümegi K, Büki G, Szabó A, Magyari L, Ádám V, Pálos F, Miseta A, Kásler M, Melegh B. Characterization of Danube Swabian population samples on a high-resolution genome-wide basis. BMC Genomics 2023; 24:9. [PMID: 36624381 PMCID: PMC9830925 DOI: 10.1186/s12864-022-09092-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 12/20/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND German-derived ethnicities are one of the largest ethnic groups in Hungary, dating back to the formation of the Kingdom of Hungary, which took place at the beginning of the 11th century. Germans arrived in Hungary in many waves. The most significant immigration wave took place following the collapse of the Ottoman Empire in East-Central Europe which closed the 150 year long Ottoman occupation. To date, there are no comprehensive genome-wide studies investigating the genetic makeup of the Danube Swabians. Here we analyzed 47 Danube Swabian samples collected from elderly Swabian individuals living in the Dunaszekcső-Bár area, in Danube side villages of Southwest Hungary. These Swabians, according to self-declaration, did not admix with other ethnic groups for 3-6 succeeding generations. Using Illumina Infinium 720 K Beadchip genotype data, we applied allele frequency-based and haplotype-based genome-wide marker data analyses to investigate the ancestry and genetic composition of the collected Danube Swabian samples. RESULTS Haplotype-based analyses like identity by descent segment analysis show that the investigated Danube Swabians possess significant German and other West European ancestry, but their Hungarian ancestry is also prominent. Our results suggest that their main source of ancestry can be traced back to Western Europe, presumably to the region of Germany. CONCLUSION This is the first analysis of Danube Swabian population samples based on genome-wide autosomal data. Our results establish the basis for conducting further comprehensive research on Danube Swabians and on other German ethnicities of the Carpathian basin, which can help reconstruct their origin, and identify their major archaic genomic patterns.
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Affiliation(s)
- Zsolt Bánfai
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary
| | - Erzsébet Kövesdi
- grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Institute of Physiology, Medical School, Hungary, University of Pécs, Ifjúság út 12, H-7624 Pécs, Hungary
| | - Katalin Sümegi
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Department of Biochemistry and Medical Chemistry, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary
| | - Gergely Büki
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary
| | - András Szabó
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary
| | - Lili Magyari
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary
| | - Valerián Ádám
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary
| | - Ferenc Pálos
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary
| | - Attila Miseta
- grid.9679.10000 0001 0663 9479Department of Laboratory Medicine, Medical School, University of Pécs, Ifjúság út 13, H-7624 Pécs, Hungary
| | - Miklós Kásler
- grid.419617.c0000 0001 0667 8064National Institute of Oncology, Ráth György u. 7-9, H-1122 Budapest, Hungary
| | - Béla Melegh
- grid.9679.10000 0001 0663 9479Department of Medical Genetics, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary ,grid.9679.10000 0001 0663 9479Szentágothai Research Centre, University of Pécs, Ifjúság út 20, H-7624 Pécs, Hungary
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13
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Rodríguez-Varela R, Moore KHS, Ebenesersdóttir SS, Kilinc GM, Kjellström A, Papmehl-Dufay L, Alfsdotter C, Berglund B, Alrawi L, Kashuba N, Sobrado V, Lagerholm VK, Gilbert E, Cavalleri GL, Hovig E, Kockum I, Olsson T, Alfredsson L, Hansen TF, Werge T, Munters AR, Bernhardsson C, Skar B, Christophersen A, Turner-Walker G, Gopalakrishnan S, Daskalaki E, Omrak A, Pérez-Ramallo P, Skoglund P, Girdland-Flink L, Gunnarsson F, Hedenstierna-Jonson C, Gilbert MTP, Lidén K, Jakobsson M, Einarsson L, Victor H, Krzewińska M, Zachrisson T, Storå J, Stefánsson K, Helgason A, Götherström A. The genetic history of Scandinavia from the Roman Iron Age to the present. Cell 2023; 186:32-46.e19. [PMID: 36608656 DOI: 10.1016/j.cell.2022.11.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/14/2022] [Accepted: 11/22/2022] [Indexed: 01/07/2023]
Abstract
We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.
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Affiliation(s)
- Ricardo Rodríguez-Varela
- Centre for Palaeogenetics, 106 91 Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden.
| | | | - S Sunna Ebenesersdóttir
- deCODE Genetics/AMGEN, Inc., 102 Reykjavik, Iceland; Department of Anthropology, University of Iceland, 102 Reykjavik, Iceland
| | - Gulsah Merve Kilinc
- Department of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, 06100 Ankara, Turkey
| | - Anna Kjellström
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | | | - Clara Alfsdotter
- Department of Archaeology, Bohusläns Museum, Museigatan 1, 451 19 Udevalla, Sweden
| | - Birgitta Berglund
- Department of Archaeology and Cultural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Loey Alrawi
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Natalija Kashuba
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden; Department of Archaeology and Ancient History, Archaeology, Uppsala University, 752 38 Uppsala, Sweden; Department of Organismal Biology, Human Evolution, and SciLife Lab, Uppsala University, 75236 Uppsala, Sweden
| | - Verónica Sobrado
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Vendela Kempe Lagerholm
- Centre for Palaeogenetics, 106 91 Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Edmund Gilbert
- School of Pharmacy and Biomolecular Sciences, RCSI, D02 YN77 Dublin, Ireland; FutureNeuro SFI Research Centre, RCSI, D02 YN77 Dublin, Ireland
| | - Gianpiero L Cavalleri
- School of Pharmacy and Biomolecular Sciences, RCSI, D02 YN77 Dublin, Ireland; FutureNeuro SFI Research Centre, RCSI, D02 YN77 Dublin, Ireland
| | - Eivind Hovig
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, 166 0450 Oslo, Norway
| | - Ingrid Kockum
- Center for Molecular Medicine, Department of Clinical Neuroscience, Neuroimmunology Unit, Karolinska Institutet, 171 76 Stockholm, Sweden
| | - Tomas Olsson
- Center for Molecular Medicine, Department of Clinical Neuroscience, Neuroimmunology Unit, Karolinska Institutet, 171 76 Stockholm, Sweden
| | - Lars Alfredsson
- Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Thomas F Hansen
- Institute of Biological Psychiatry, Copenhagen Mental Health Services, 4000 Roskilde, Denmark; Danish Headache Center, Department of Neurology, Copenhagen University Hospital, 2600 Glostrup, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Copenhagen Mental Health Services, 4000 Roskilde, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen 2200, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, 8210 Aarhus, Denmark
| | - Arielle R Munters
- Department of Organismal Biology, Human Evolution, and SciLife Lab, Uppsala University, 75236 Uppsala, Sweden
| | - Carolina Bernhardsson
- Department of Organismal Biology, Human Evolution, and SciLife Lab, Uppsala University, 75236 Uppsala, Sweden
| | - Birgitte Skar
- Department of Archaeology and Cultural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Axel Christophersen
- Department of Archaeology and Cultural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Gordon Turner-Walker
- Department of Archaeology and Anthropology National Museum of Natural Science, 404023 Taichung City, Taiwan
| | - Shyam Gopalakrishnan
- Center for Evolutionary Hologenomics, the GLOBE Institute, University of Copenhagen, 1353 Copenhagen, Denmark
| | - Eva Daskalaki
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Ayça Omrak
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Patxi Pérez-Ramallo
- isoTROPIC Research Group, Department of Archaeology, Max Planck Institute for Geoanthropology, 07745 Jena, Germany; Department of Medical and Surgical Specialities, Faculty of Medicine and Nursing, University of the Basque Country (EHU), Donostia-San Sebastián 20014, Spain
| | | | - Linus Girdland-Flink
- Department of Archaeology, School of Geosciences, University of Aberdeen, AB24 3FX Aberdeen, UK; School of Biological and Environmental Sciences, Liverpool John Moores University, L3 3AF Liverpool, UK
| | - Fredrik Gunnarsson
- Department of Museum Archaeology, Kalmar County Museum, Box 104, Kalmar 39121, Sweden
| | | | - M Thomas P Gilbert
- Center for Evolutionary Hologenomics, the GLOBE Institute, University of Copenhagen, 1353 Copenhagen, Denmark; Department of Natural History, NTNU University Museum, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
| | - Kerstin Lidén
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Mattias Jakobsson
- Department of Organismal Biology, Human Evolution, and SciLife Lab, Uppsala University, 75236 Uppsala, Sweden
| | - Lars Einarsson
- Kronan, Marine Archaeological Department, Kalmar County Museum, Box 104, Kalmar S-39121, Sweden
| | - Helena Victor
- Department of Museum Archaeology, Kalmar County Museum, Box 104, Kalmar 39121, Sweden
| | - Maja Krzewińska
- Centre for Palaeogenetics, 106 91 Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | | | - Jan Storå
- Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden
| | - Kári Stefánsson
- deCODE Genetics/AMGEN, Inc., 102 Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Agnar Helgason
- deCODE Genetics/AMGEN, Inc., 102 Reykjavik, Iceland; Department of Anthropology, University of Iceland, 102 Reykjavik, Iceland.
| | - Anders Götherström
- Centre for Palaeogenetics, 106 91 Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, 10691 Stockholm, Sweden.
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14
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Arrieta-Bolaños E, Hernández-Zaragoza DI, Barquera R. An HLA map of the world: A comparison of HLA frequencies in 200 worldwide populations reveals diverse patterns for class I and class II. Front Genet 2023; 14:866407. [PMID: 37035735 PMCID: PMC10076764 DOI: 10.3389/fgene.2023.866407] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/13/2023] [Indexed: 04/11/2023] Open
Abstract
HLA frequencies show widespread variation across human populations. Demographic factors as well as selection are thought to have shaped HLA variation across continents. In this study, a worldwide comparison of HLA class I and class II diversity was carried out. Multidimensional scaling techniques were applied to 50 HLA-A and HLA-B (class I) as well as 13 HLA-DRB1 (class II) first-field frequencies in 200 populations from all continents. Our results confirm a strong effect of geography on the distribution of HLA class I allele groups, with principal coordinates analysis closely resembling geographical location of populations, especially those of Africa-Eurasia. Conversely, class II frequencies stratify populations along a continuum of differentiation less clearly correlated to actual geographic location. Double clustering analysis revealed finer intra-continental sub-clusters (e.g., Northern and Western Europe vs. South East Europe, North Africa and Southwest Asia; South and East Africa vs. West Africa), and HLA allele group patterns characteristic of these clusters. Ancient (Austronesian expansion) and more recent (Romani people in Europe) migrations, as well as extreme differentiation (Taiwan indigenous peoples, Native Americans), and interregional gene flow (Sámi, Egyptians) are also reflected by the results. Barrier analysis comparing DST and geographic location identified genetic discontinuities caused by natural barriers or human behavior explaining inter and intra-continental HLA borders for class I and class II. Overall, a progressive reduction in HLA diversity from African to Oceanian and Native American populations is noted. This analysis of HLA frequencies in a unique set of worldwide populations confirms previous findings on the remarkable similarity of class I frequencies to geography, but also shows a more complex development for class II, with implications for both human evolutionary studies and biomedical research.
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Affiliation(s)
- Esteban Arrieta-Bolaños
- Institute for Experimental Cellular Therapy, University Hospital Essen, Essen, Germany
- German Cancer Consortium (DKTK), partner site Essen/Düsseldorf, Heidelberg, Germany
- *Correspondence: Esteban Arrieta-Bolaños,
| | | | - Rodrigo Barquera
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology (MPI-EVA), Leipzig, Germany
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15
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Fedorova SA, Khusnutdinova EK. Genetic Structure and Genetic History of the Sakha (Yakuts) Population. RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422120031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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16
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Kaneva K, Schurr TG, Tatarinova TV, Buckley J, Merkurjev D, Triska P, Liu X, Done J, Maglinte DT, Deapen D, Hwang A, Schiffman JD, Triche TJ, Biegel JA, Gai X. Mitochondrial DNA haplogroup, genetic ancestry, and susceptibility to Ewing sarcoma. Mitochondrion 2022; 67:6-14. [PMID: 36115539 PMCID: PMC9997094 DOI: 10.1016/j.mito.2022.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/30/2022] [Accepted: 09/09/2022] [Indexed: 01/11/2023]
Abstract
Based on current studies, the incidence of Ewing sarcoma (ES) varies significantly by race and ethnicity, with the disease being most common in patients of European ancestry. However, race/ethnicity has generally been self-reported rather than formally evaluated at a population level using DNA evidence. Additionally, mitochondrial dysfunction is a hallmark of ES, yet there have been no reported studies of mitochondrial genetics in ES. Thus, we evaluated both the mitochondrial and nuclear ancestries of 420 pediatric ES patients in the United States using whole-genome sequencing. We found that the mitochondrial DNA (mtDNA) genomes of only six (1.4 %) patients belonged to African L haplogroups, while those of 90 % of the patients belonged to macrohaplogroup R, which includes haplogroup H, the most common maternal lineage in Europe. Compared to the general US population, European haplogroups were significantly enriched in ES patients (p < 2.2e-16) and the African haplogroups are significantly impoverished (p < 4.6e-16). Using the ancestry informative markers defined in a National Genographic study, the vast majority of patients exhibited significant nuclear ancestry originating from the Mediterranean, Northern Europe, and Southwest Asia, including all six patients with African L mtDNAs. Very few had primarily African nuclear ancestry. This is the first genomic epidemiology study to simultaneously interrogate the mitochondrial and nuclear ancestries of ES patients. While supporting previous findings of enriched European ancestry in ES patients, these results also suggest alternative hypotheses for the significant contribution of mitochondrial ancestry in ES patients, as well as the protective role of African ancestry.
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Affiliation(s)
- Kristiyana Kaneva
- Division of Hematology, Oncology, and Blood and Marrow Transplant Program, Children's Center for Cancer and Blood Diseases, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Theodore G Schurr
- Department of Anthropology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jonathan Buckley
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Daria Merkurjev
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Petr Triska
- Department of Pediatric Hematology and Oncology, Charles University, Prague, Czech Republic
| | - Xiyu Liu
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - James Done
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Dennis T Maglinte
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Dennis Deapen
- Cancer Surveillance Program, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Amie Hwang
- Cancer Surveillance Program, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Joshua D Schiffman
- Department of Pediatrics and Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA; PEEL Therapeutics, Inc., Salt Lake City, UT, USA
| | - Timothy J Triche
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jaclyn A Biegel
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xiaowu Gai
- Center for Personalized Medicine, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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17
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Dai SS, Sulaiman X, Isakova J, Xu WF, Abdulloevich NT, Afanasevna ME, Ibrohimovich KB, Chen X, Yang WK, Wang MS, Shen QK, Yang XY, Yao YG, Aldashev AA, Saidov A, Chen W, Cheng LF, Peng MS, Zhang YP. The genetic echo of the Tarim mummies in modern Central Asians. Mol Biol Evol 2022; 39:6675590. [PMID: 36006373 PMCID: PMC9469894 DOI: 10.1093/molbev/msac179] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The diversity of Central Asians has been shaped by multiple migrations and cultural diffusion. Although ancient DNA studies have revealed the demographic changes of the Central Asian since the Bronze Age, the contribution of the ancient populations to the modern Central Asian remains opaque. Herein, we performed high-coverage sequencing of 131 whole genomes of Indo-European-speaking Tajik and Turkic-speaking Kyrgyz populations to explore their genomic diversity and admixture history. By integrating the ancient DNA data, we revealed more details of the origins and admixture history of Central Asians. We found that the major ancestry of present-day Tajik populations can be traced back to the admixture of the Bronze Age Bactria–Margiana Archaeological Complex and Andronovo-related populations. Highland Tajik populations further received additional gene flow from the Tarim mummies, an isolated ancient North Eurasian–related population. The West Eurasian ancestry of Kyrgyz is mainly derived from Historical Era populations in Xinjiang of China. Furthermore, the recent admixture signals detected in both Tajik and Kyrgyz are ascribed to the expansions of Eastern Steppe nomadic pastoralists during the Historical Era.
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Affiliation(s)
- Shan Shan Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Xierzhatijiang Sulaiman
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Department of Pharmacology, School of Pharmacy, Xinjiang Medical University, Urumqi 830054, China
| | - Jainagul Isakova
- Institute of Molecular Biology and Medicine, Bishkek 720040, Kyrgyzstan
| | - Wei Fang Xu
- Shenzhen Hospital of Guangzhou University of Chinese Medicine, Shenzhen 518034, China
| | - Najmudinov Tojiddin Abdulloevich
- E.N. Pavlovsky Institute of Zoology and Parasitology, Academy of Sciences of Republic of Tajikistan, Dushanbe 734025, Tajikistan
| | - Manilova Elena Afanasevna
- E.N. Pavlovsky Institute of Zoology and Parasitology, Academy of Sciences of Republic of Tajikistan, Dushanbe 734025, Tajikistan
| | - Khudoidodov Behruz Ibrohimovich
- E.N. Pavlovsky Institute of Zoology and Parasitology, Academy of Sciences of Republic of Tajikistan, Dushanbe 734025, Tajikistan
| | - Xi Chen
- Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China.,State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Wei Kang Yang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Ming Shan Wang
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Quan Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Xing Yan Yang
- Key Laboratory of Chemistry in Ethnic Medicinal Resource, Yunnan Minzu University, Kunming 650504, China.,School of Chemistry and Environment, Yunnan Minzu University, Kunming 650504, China
| | - Yong Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,KIZ/CUHK Joint Laboratory of Bio-resources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Almaz A Aldashev
- Institute of Molecular Biology and Medicine, Bishkek 720040, Kyrgyzstan
| | - Abdusattor Saidov
- E.N. Pavlovsky Institute of Zoology and Parasitology, Academy of Sciences of Republic of Tajikistan, Dushanbe 734025, Tajikistan
| | - Wei Chen
- College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650224, China.,State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming 650224, China
| | - Lu Feng Cheng
- Department of Pharmacology, School of Pharmacy, Xinjiang Medical University, Urumqi 830054, China
| | - Min Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,KIZ/CUHK Joint Laboratory of Bio-resources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Ya Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,KIZ/CUHK Joint Laboratory of Bio-resources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China.,State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
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18
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Huang X, Xia ZY, Bin X, He G, Guo J, Adnan A, Yin L, Huang Y, Zhao J, Yang Y, Ma F, Li Y, Hu R, Yang T, Wei LH, Wang CC. Genomic Insights Into the Demographic History of the Southern Chinese. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.853391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Southern China is the birthplace of rice-cultivating agriculture and different language families and has also witnessed various human migrations that facilitated cultural diffusions. The fine-scale demographic history in situ that forms present-day local populations, however, remains unclear. To comprehensively cover the genetic diversity in East and Southeast Asia, we generated genome-wide SNP data from 211 present-day Southern Chinese and co-analyzed them with ∼1,200 ancient and modern genomes. In Southern China, language classification is significantly associated with genetic variation but with a different extent of predictability, and there is strong evidence for recent shared genetic history particularly in Hmong–Mien and Austronesian speakers. A geography-related genetic sub-structure that represents the major genetic variation in Southern East Asians is established pre-Holocene and its extremes are represented by Neolithic Fujianese and First Farmers in Mainland Southeast Asia. This sub-structure is largely reduced by admixture in ancient Southern Chinese since > ∼2,000 BP, which forms a “Southern Chinese Cluster” with a high level of genetic homogeneity. Further admixture characterizes the demographic history of the majority of Hmong–Mien speakers and some Kra-Dai speakers in Southwest China happened ∼1,500–1,000 BP, coeval to the reigns of local chiefdoms. In Yellow River Basin, we identify a connection of local populations to genetic sub-structure in Southern China with geographical correspondence appearing > ∼9,000 BP, while the gene flow likely closely related to “Southern Chinese Cluster” since the Longshan period (∼5,000–4,000 BP) forms ancestry profile of Han Chinese Cline.
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19
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Assessing temporal and geographic contacts across the Adriatic Sea through the analysis of genome-wide data from Southern Italy. Genomics 2022; 114:110405. [PMID: 35709925 DOI: 10.1016/j.ygeno.2022.110405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/01/2022] [Accepted: 06/09/2022] [Indexed: 11/22/2022]
Abstract
Southern Italy was characterised by a complex prehistory that started with different Palaeolithic cultures, later followed by the Neolithization and the demic dispersal from the Pontic-Caspian Steppe during the Bronze Age. Archaeological and historical evidences point to a link between Southern Italians and the Balkans still present in modern times. To shed light on these dynamics, we analysed around 700 South Mediterranean genomes combined with informative ancient DNAs. Our findings revealed high affinities of South-Eastern Italians with modern Eastern Peloponnesians, and a closer affinity of ancient Greek genomes with those from specific regions of South Italy than modern Greek genomes. The higher similarity could be associated with a Bronze Age component ultimately originating from the Caucasus with high Iranian and Anatolian Neolithic ancestries. Furthermore, extremely differentiated allele frequencies among Northern and Southern Italy revealed putatively adapted SNPs in genes involved in alcohol metabolism, nevi features and immunological traits.
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20
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Elliott KS, Haber M, Daggag H, Busby GB, Sarwar R, Kennet D, Petraglia M, Petherbridge LJ, Yavari P, Heard-Bey FU, Shobi B, Ghulam T, Haj D, Al Tikriti A, Mohammad A, Antony S, Alyileili M, Alaydaroos S, Lau E, Butler M, Yavari A, Knight JC, Ashrafian H, Barakat MT. Fine-Scale Genetic Structure in the United Arab Emirates Reflects Endogamous and Consanguineous Culture, Population History, and Geography. Mol Biol Evol 2022; 39:msac039. [PMID: 35192718 PMCID: PMC8911814 DOI: 10.1093/molbev/msac039] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The indigenous population of the United Arab Emirates (UAE) has a unique demographic and cultural history. Its tradition of endogamy and consanguinity is expected to produce genetic homogeneity and partitioning of gene pools while population movements and intercontinental trade are likely to have contributed to genetic diversity. Emiratis and neighboring populations of the Middle East have been underrepresented in the population genetics literature with few studies covering the broader genetic history of the Arabian Peninsula. Here, we genotyped 1,198 individuals from the seven Emirates using 1.7 million markers and by employing haplotype-based algorithms and admixture analyses, we reveal the fine-scale genetic structure of the Emirati population. Shared ancestry and gene flow with neighboring populations display their unique geographic position while increased intra- versus inter-Emirati kinship and sharing of uniparental haplogroups, reflect the endogamous and consanguineous cultural traditions of the Emirates and their tribes.
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Affiliation(s)
- Katherine S Elliott
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Marc Haber
- Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom
| | - Hinda Daggag
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | - George B Busby
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Rizwan Sarwar
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Derek Kennet
- Department of Archaeology, Durham University, Durham, United Kingdom
| | - Michael Petraglia
- Max Planck Institute for the Science of Human History, Jena, Germany
| | | | - Parisa Yavari
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Bindu Shobi
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | - Tariq Ghulam
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | - Dalia Haj
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | | | | | - Suma Antony
- Imperial College London Diabetes Centre, Abu Dhabi, UAE
| | | | | | - Evelyn Lau
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Mark Butler
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Arash Yavari
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Julian C Knight
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Houman Ashrafian
- Experimental Therapeutics, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
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21
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Ashirbekov Y, Abaildayev A, Neupokoyeva A, Sabitov Z, Zhabagin M. Genetic polymorphism of 27 Y-STR loci in Kazakh populations from Northern Kazakhstan. Ann Hum Biol 2022; 49:87-89. [PMID: 35132894 DOI: 10.1080/03014460.2022.2039292] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
BACKGROUND Previous studies of the genetic polymorphism of the Y-chromosome of Kazakhs were focused on the Eastern, Central, Southern, and Western regions of Kazakhstan. In addition, many of these studies were limited to 17 Y-STR loci from the Yfiler. AIM To enrich the existing Kazakhstan Y-chromosome Haplotype Reference Database from the Northern Kazakh population data by a wide set of 27 Y-STR and investigate the population genetic relationships with previously published data. SUBJECTS AND METHODS 27 Y-STR loci from the Yfiler Plus PCR Amplification Kit were analysed in 382 healthy unrelated Kazakh males from Northern Kazakhstan. Genetic polymorphism was analysed using Arlequin software. RESULTS A total of 326 distinct haplotypes of the 27 Y-STR loci were observed in 382 individuals. The discrimination capacity (0.9982) and haplotype diversity (0.8534) were computed. A total of 168 alleles at single-copy loci were observed, and their frequencies ranged from 0.003 to 0.843. The pairwise genetic distance (RST) showed that the Northern Kazakh population is genetically distinct from the Chinese Kazakh population. CONCLUSIONS Genetic polymorphism shows that the potential value of 27 Y-STR loci for forensic casework in the Northern Kazakh population, and the current findings, might be beneficial for paternal lineages in the study of population genetics.
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Affiliation(s)
- Yeldar Ashirbekov
- M. Aitkhozhin Institute of Molecular Biology and Biochemistry, Republic of Kazakhstan
| | - Arman Abaildayev
- M. Aitkhozhin Institute of Molecular Biology and Biochemistry, Republic of Kazakhstan
| | | | - Zhaxylyk Sabitov
- National Center for Biotechnology, Republic of Kazakhstan.,L.N. Gumilyov Eurasian National University, Republic of Kazakhstan
| | - Maxat Zhabagin
- National Center for Biotechnology, Republic of Kazakhstan.,Young Researchers Alliance, Republic of Kazakhstan
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22
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Cardinali I, Bodner M, Capodiferro MR, Amory C, Rambaldi Migliore N, Gomez EJ, Myagmar E, Dashzeveg T, Carano F, Woodward SR, Parson W, Perego UA, Lancioni H, Achilli A. Mitochondrial DNA Footprints from Western Eurasia in Modern Mongolia. Front Genet 2022; 12:819337. [PMID: 35069708 PMCID: PMC8773455 DOI: 10.3389/fgene.2021.819337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 12/14/2021] [Indexed: 11/15/2022] Open
Abstract
Mongolia is located in a strategic position at the eastern edge of the Eurasian Steppe. Nomadic populations moved across this wide area for millennia before developing more sedentary communities, extended empires, and complex trading networks, which connected western Eurasia and eastern Asia until the late Medieval period. We provided a fine-grained portrait of the mitochondrial DNA (mtDNA) variation observed in present-day Mongolians and capable of revealing gene flows and other demographic processes that took place in Inner Asia, as well as in western Eurasia. The analyses of a novel dataset (N = 2,420) of mtDNAs highlighted a clear matrilineal differentiation within the country due to a mixture of haplotypes with eastern Asian (EAs) and western Eurasian (WEu) origins, which were differentially lost and preserved. In a wider genetic context, the prevalent EAs contribution, larger in eastern and central Mongolian regions, revealed continuous connections with neighboring Asian populations until recent times, as attested by the geographically restricted haplotype-sharing likely facilitated by the Genghis Khan’s so-called Pax Mongolica. The genetic history beyond the WEu haplogroups, notably detectable on both sides of Mongolia, was more difficult to explain. For this reason, we moved to the analysis of entire mitogenomes (N = 147). Although it was not completely possible to identify specific lineages that evolved in situ, two major changes in the effective (female) population size were reconstructed. The more recent one, which began during the late Pleistocene glacial period and became steeper in the early Holocene, was probably the outcome of demographic events connected to western Eurasia. The Neolithic growth could be easily explained by the diffusion of dairy pastoralism, as already proposed, while the late glacial increase indicates, for the first time, a genetic connection with western Eurasian refuges, as supported by the unusual high frequency and internal sub-structure in Mongolia of haplogroup H1, a well-known post-glacial marker in Europe. Bronze Age events, without a significant demographic impact, might explain the age of some mtDNA haplogroups. Finally, a diachronic comparison with available ancient mtDNAs made it possible to link six mitochondrial lineages of present-day Mongolians to the timeframe and geographic path of the Silk Route.
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Affiliation(s)
- Irene Cardinali
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Perugia, Italy
| | - Martin Bodner
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Christina Amory
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Edgar J Gomez
- Sorenson Molecular Genealogy Foundation, Salt Lake City, UT, United States.,FamilySearch Int., Salt Lake City, UT, United States
| | - Erdene Myagmar
- Department of Anthropology and Archaeology, National University of Mongolia, Ulaanbaatar, Mongolia
| | - Tumen Dashzeveg
- Department of Anthropology and Archaeology, National University of Mongolia, Ulaanbaatar, Mongolia
| | - Francesco Carano
- Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Scott R Woodward
- Sorenson Molecular Genealogy Foundation, Salt Lake City, UT, United States
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria.,Forensic Science Program, The Pennsylvania State University, State College, PA, United States
| | - Ugo A Perego
- Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia, Italy.,Sorenson Molecular Genealogy Foundation, Salt Lake City, UT, United States.,Department of Math and Science, Southeastern Community College, Burlington, IA, United States
| | - Hovirag Lancioni
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Perugia, Italy
| | - Alessandro Achilli
- Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia, Italy
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23
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Genetic continuity of Indo-Iranian speakers since the Iron Age in southern Central Asia. Sci Rep 2022; 12:733. [PMID: 35031610 PMCID: PMC8760286 DOI: 10.1038/s41598-021-04144-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 12/14/2021] [Indexed: 12/14/2022] Open
Abstract
Since prehistoric times, southern Central Asia has been at the crossroads of the movement of people, culture, and goods. Today, the Central Asian populations are divided into two cultural and linguistic groups: the Indo-Iranian and the Turko-Mongolian groups. Previous genetic studies unveiled that migrations from East Asia contributed to the spread of Turko-Mongolian populations in Central Asia and the partial replacement of the Indo-Iranian populations. However, little is known about the origin of the latters. To shed light on this, we compare the genetic data on two current-day Indo-Iranian populations — Yaghnobis and Tajiks — with genome-wide data from published ancient individuals. The present Indo-Iranian populations from Central Asia display a strong genetic continuity with Iron Age samples from Turkmenistan and Tajikistan. We model Yaghnobis as a mixture of 93% Iron Age individual from Turkmenistan and 7% from Baikal. For the Tajiks, we observe a higher Baikal ancestry and an additional admixture event with a South Asian population. Our results, therefore, suggest that in addition to a complex history, Central Asia shows a remarkable genetic continuity since the Iron Age, with only limited gene flow.
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Yang X, Sarengaowa, He G, Guo J, Zhu K, Ma H, Zhao J, Yang M, Chen J, Zhang X, Tao L, Liu Y, Zhang XF, Wang CC. Genomic Insights Into the Genetic Structure and Natural Selection of Mongolians. Front Genet 2021; 12:735786. [PMID: 34956310 PMCID: PMC8693022 DOI: 10.3389/fgene.2021.735786] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 11/02/2021] [Indexed: 11/13/2022] Open
Abstract
Mongolians dwell at the Eastern Eurasian Steppe, where is the agriculture and pasture interlaced area, practice pastoral subsistence strategies for generations, and have their own complex genetic formation history. There is evidence that the eastward expansion of Western Steppe herders transformed the lifestyle of post-Bronze Age Mongolia Plateau populations and brought gene flow into the gene pool of Eastern Eurasians. Here, we reported genome-wide data for 42 individuals from the Inner Mongolia Autonomous Region of North China. We observed that our studied Mongolians were structured into three distinct genetic clusters possessing different genetic affinity with previous studied Inner Mongolians and Mongols and various Eastern and Western Eurasian ancestries: two subgroups harbored dominant Eastern Eurasian ancestry from Neolithic millet farmers of Yellow River Basin; another subgroup derived Eastern Eurasian ancestry primarily from Neolithic hunter-gatherers of North Asia. Besides, three-way/four-way qpAdm admixture models revealed that both north and southern Western Eurasian ancestry related to the Western Steppe herders and Iranian farmers contributed to the genetic materials into modern Mongolians. ALDER-based admixture coefficient and haplotype-based GLOBETROTTER demonstrated that the former western ancestry detected in modern Mongolian could be recently traced back to a historic period in accordance with the historical record about the westward expansion of the Mongol empire. Furthermore, the natural selection analysis of Mongolians showed that the Major Histocompatibility Complex (MHC) region underwent significantly positive selective sweeps. The functional genes, alcohol dehydrogenase (ADH) and lactase persistence (LCT), were not identified, while the higher/lower frequencies of derived mutations were strongly correlated with the genetic affinity to East Asian/Western Eurasian populations. Our attested complex population movement and admixture in the agriculture and pasture interlaced area played an important role in the formation of modern Mongolians.
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Affiliation(s)
- Xiaomin Yang
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Sarengaowa
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China
| | - Guanglin He
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Jianxin Guo
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Kongyang Zhu
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Hao Ma
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Jing Zhao
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Meiqing Yang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Jing Chen
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Xianpeng Zhang
- Institute of Biological Anthropology, Jinzhou Medical University, Liaoning, China
| | - Le Tao
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Yilan Liu
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| | - Xiu-Fang Zhang
- Department of Pediatrics, Xiang'an Hospital of Xiamen University, Xiamen, China
| | - Chuan-Chao Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Sociology and Anthropology, Xiamen University, Xiamen, China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
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25
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Balanovsky O, Petrushenko V, Mirzaev K, Abdullaev S, Gorin I, Chernevskiy D, Agdzhoyan A, Balanovska E, Kryukov A, Temirbulatov I, Sychev D. Variation of Genomic Sites Associated with Severe Covid-19 Across Populations: Global and National Patterns. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021; 14:1391-1402. [PMID: 34764675 PMCID: PMC8575442 DOI: 10.2147/pgpm.s320609] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 10/04/2021] [Indexed: 01/10/2023]
Abstract
Background Information about the distribution of clinically significant genetic markers in different populations may be helpful in elaborating personalized approaches to the clinical management of COVID-19 in the absence of consensus guidelines. Aim Analyze frequencies and distribution patterns of two markers associated with severe COVID-19 (rs11385942 and rs657152) and look for potential correlations between these markers and deaths from COVID-19 among populations in Russia and across the world. Methods We genotyped 1883 samples from 91 ethnic groups pooled into 28 populations representing Russia and its neighbor states. We also compiled a dataset on 32 populations from other regions using genotypes extracted or imputed from the available databases. Geographic maps showing the frequency distribution of the analyzed markers were constructed using the obtained data. Results The cartographic analysis revealed that rs11385942 distribution follows the West Eurasian pattern: the marker is frequent among the populations of Europe, West Asia and South Asia but rare or absent in all other parts of the globe. Notably, the transition from high to low rs11385942 frequencies across Eurasia is not abrupt but follows the clinal variation pattern instead. The distribution of rs657152 is more homogeneous. The analysis of correlations between the frequencies of the studied markers and the epidemiological characteristics of COVID-19 in a population revealed that higher frequencies of both risk alleles correlated positively with mortality from this disease. For rs657152, the correlation was especially strong (r = 0.59, p = 0.02). These reasonable correlations were observed for the "Russian" dataset only: no such correlations were established for the "world" dataset. This could be attributed to the differences in methodology used to collect COVID-19 statistics in different countries. Conclusion Our findings suggest that genetic differences between populations make a small yet tangible contribution to the heterogeneity of the pandemic worldwide.
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Affiliation(s)
- Oleg Balanovsky
- Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia.,Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia.,Biobank of North Eurasia, Moscow, Russia
| | - Valeria Petrushenko
- Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia.,Department of Bioinformatics Moscow Institute of Physics and Technology, Moscow, Russia
| | - Karin Mirzaev
- Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia.,Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - Sherzod Abdullaev
- Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - Igor Gorin
- Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia.,Department of Bioinformatics Moscow Institute of Physics and Technology, Moscow, Russia
| | - Denis Chernevskiy
- Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia
| | - Anastasiya Agdzhoyan
- Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia.,Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia
| | - Elena Balanovska
- Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia.,Biobank of North Eurasia, Moscow, Russia
| | - Alexander Kryukov
- Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - Ilyas Temirbulatov
- Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia.,Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - Dmitriy Sychev
- Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, Russia
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26
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Mitogenomics of modern Mongolic-speaking populations. Mol Genet Genomics 2021; 297:47-62. [PMID: 34757478 DOI: 10.1007/s00438-021-01830-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 10/27/2021] [Indexed: 10/19/2022]
Abstract
Here, we present a comprehensive data set of 489 complete mitogenomes (211 of which are new) from four Mongolic-speaking populations (Mongols, Barghuts, Khamnigans, and Buryats) to investigate their matrilineal genetic structure, ancestry and relationship with other ethnic groups. We show that along with very high levels of genetic diversity and lack of genetic differentiation, Mongolic-speaking populations exhibit strong genetic resemblance to East Asian populations of Chinese, Japanese, and Uyghurs. Phylogeographic analysis of complete mitogenomes reveals the presence of different components in the gene pools of modern Mongolic-speaking populations-the main East Eurasian component is represented by mtDNA lineages of East Asian, Siberian and autochthonous (the Baikal region/Mongolian) ancestry, whereas the less pronounced West Eurasian component can be ascribed to Europe and West Asia/Caucasus. We also observed that up to one third of the mtDNA subhaplogroups identified in Mongolic-speaking populations can be considered as Mongolic-specific with the coalescence age of most of them not exceeding 1.7 kya. This coincides well with the population size growth which started around 1.1 kya and is detectable only in the Bayesian Skyline Plot constructed based on Mongolic-specific mitogenomes. Our data suggest that the genetic structure established during the Mongol empire is still retained in present-day Mongolic-speaking populations.
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27
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Scheidel W. Fitness and Power: The Contribution of Genetics to the History of Differential Reproduction. EVOLUTIONARY PSYCHOLOGY 2021; 19:14747049211066599. [PMID: 34918580 PMCID: PMC10303451 DOI: 10.1177/14747049211066599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 11/28/2021] [Indexed: 11/16/2022] Open
Abstract
Textual evidence from pre-modern societies supports the prediction that status differences among men translate to variance in reproductive success. In recent years, analysis of genetic data has opened up new ways of studying this relationship. By investigating cases that range over several millennia, these analyses repeatedly document the replacement of local men by newcomers and reveal instances of exceptional reproductive success of specific male lineages. These findings suggest that violent population transfers and conquests could generate considerable reproductive advantages for male dominants. At the same time, this does not always seem to have been the case. Moreover, it is difficult to link such outcomes to particular historical characters or events, or to identify status-biased reproductive inequalities within dominant groups. The proximate factors that mediated implied imbalances in reproductive success often remain unclear. A better understanding of the complex interplay between social power and genetic fitness will only arise from sustained transdisciplinary engagement.
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28
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Warshauer EM, Brown A, Fuentes I, Shortt J, Gignoux C, Montinaro F, Metspalu M, Youssefian L, Vahidnezhad H, Jacków J, Christiano AM, Uitto J, Fajardo-Ramírez ÓR, Salas-Alanis JC, McGrath JA, Consuegra L, Rivera C, Maier PA, Runfeldt G, Behar DM, Skorecki K, Sprecher E, Palisson F, Norris DA, Bruckner AL, Kogut I, Bilousova G, Roop DR. Ancestral patterns of recessive dystrophic epidermolysis bullosa mutations in Hispanic populations suggest sephardic ancestry. Am J Med Genet A 2021; 185:3390-3400. [PMID: 34435747 DOI: 10.1002/ajmg.a.62456] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 07/11/2021] [Accepted: 07/14/2021] [Indexed: 11/11/2022]
Abstract
Recessive dystrophic epidermolysis bullosa (RDEB) is a rare genodermatosis caused by mutations in the gene coding for type VII collagen (COL7A1). More than 800 different pathogenic mutations in COL7A1 have been described to date; however, the ancestral origins of many of these mutations have not been precisely identified. In this study, 32 RDEB patient samples from the Southwestern United States, Mexico, Chile, and Colombia carrying common mutations in the COL7A1 gene were investigated to determine the origins of these mutations and the extent to which shared ancestry contributes to disease prevalence. The results demonstrate both shared European and American origins of RDEB mutations in distinct populations in the Americas and suggest the influence of Sephardic ancestry in at least some RDEB mutations of European origins. Knowledge of ancestry and relatedness among RDEB patient populations will be crucial for the development of future clinical trials and the advancement of novel therapeutics.
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Affiliation(s)
- Emily Mira Warshauer
- Department of Dermatology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA.,Charles C. Gates Center for Regenerative Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Adam Brown
- Avotaynu Research Partnership LLC, Englewood, New Jersey, USA
| | - Ignacia Fuentes
- Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago, Chile.,Fundación DEBRA Chile, Santiago, Chile
| | - Jonathan Shortt
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Chris Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Francesco Montinaro
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Biology and Genetics, University of Bari, Bari, Italy
| | - Mait Metspalu
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Leila Youssefian
- Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College and Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Hassan Vahidnezhad
- Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College and Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Joanna Jacków
- Department of Dermatology, Columbia University, New York, New York, USA.,St. John's Institute of Dermatology, King's College London (Guy's Campus), London, UK
| | - Angela M Christiano
- Department of Dermatology, Columbia University, New York, New York, USA.,Department of Genetics and Development, Columbia University, New York, New York, USA
| | - Jouni Uitto
- Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College and Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Óscar R Fajardo-Ramírez
- DEBRA Mexico, Azteca Guadalupe, Mexico.,Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Mexico
| | - Julio C Salas-Alanis
- DEBRA Mexico, Azteca Guadalupe, Mexico.,Instituto Dermatologico de Jalisco, Zapopan, Mexico
| | - John A McGrath
- St. John's Institute of Dermatology, King's College London (Guy's Campus), London, UK
| | | | - Carolina Rivera
- Fundación DEBRA Colombia, Bogotá, Colombia.,Department of Medical Genetics, Pediatric Hospital, Fundacion Cardioinfantil-Universidad del Rosario, Bogotá, Colombia
| | - Paul A Maier
- Gene by Gene, Genomic Research Center, Houston, Texas, USA
| | - Goran Runfeldt
- Gene by Gene, Genomic Research Center, Houston, Texas, USA
| | - Doron M Behar
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia.,Gene by Gene, Genomic Research Center, Houston, Texas, USA
| | - Karl Skorecki
- Azrieli Faculty of Medicine of the Galilee, Bar-Ilan University, Safed, Israel
| | - Eli Sprecher
- Department of Dermatology, Tel-Aviv Sourasky Medical Center, Tel Aviv, Israel.,Department of Human Molecular Genetics, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel
| | - Francis Palisson
- Fundación DEBRA Chile, Santiago, Chile.,Facultad de Medicina Clínica Alemana Universidad del Desarrollo, Santiago, Chile
| | - David A Norris
- Department of Dermatology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA.,Charles C. Gates Center for Regenerative Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Anna L Bruckner
- Department of Dermatology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Igor Kogut
- Department of Dermatology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA.,Charles C. Gates Center for Regenerative Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Ganna Bilousova
- Department of Dermatology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA.,Charles C. Gates Center for Regenerative Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Dennis R Roop
- Department of Dermatology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA.,Charles C. Gates Center for Regenerative Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, Colorado, USA
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29
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Kumar V, Bennett EA, Zhao D, Liang Y, Tang Y, Ren M, Dai Q, Feng X, Cao P, Yang R, Liu F, Ping W, Zhang M, Ding M, Yang MA, Amridin B, Muttaliu H, Wang J, Fu Q. Genetic continuity of Bronze Age ancestry with increased Steppe-related ancestry in Late Iron Age Uzbekistan. Mol Biol Evol 2021; 38:4908-4917. [PMID: 34320653 PMCID: PMC8557446 DOI: 10.1093/molbev/msab216] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Although Uzbekistan and Central Asia are known for the well-studied Bronze Age civilization of the Bactria–Margiana Archaeological Complex (BMAC), the lesser-known Iron Age was also a dynamic period that resulted in increased interaction and admixture among different cultures from this region. To broaden our understanding of events that impacted the demography and population structure of this region, we generated 27 genome-wide single-nucleotide polymorphism capture data sets of Late Iron Age individuals around the Historical Kushan time period (∼2100–1500 BP) from three sites in South Uzbekistan. Overall, Bronze Age ancestry persists into the Iron Age in Uzbekistan, with no major replacements of populations with Steppe-related ancestry. However, these individuals suggest diverse ancestries related to Iranian farmers, Anatolian farmers, and Steppe herders, with a small amount of West European Hunter Gatherer, East Asian, and South Asian Hunter Gatherer ancestry as well. Genetic affinity toward the Late Bronze Age Steppe herders and a higher Steppe-related ancestry than that found in BMAC populations suggest an increased mobility and interaction of individuals from the Northern Steppe in a Southward direction. In addition, a decrease of Iranian and an increase of Anatolian farmer-like ancestry in Uzbekistan Iron Age individuals were observed compared with the BMAC populations from Uzbekistan. Thus, despite continuity from the Bronze Age, increased admixture played a major role in the shift from the Bronze to the Iron Age in southern Uzbekistan. This mixed ancestry is also observed in other parts of the Steppe and Central Asia, suggesting more widespread admixture among local populations.
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Affiliation(s)
- Vikas Kumar
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China.,Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Beijing, 100044, China
| | - E Andrew Bennett
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Dongyue Zhao
- School of Cultural Heritage, Northwest University, Xi'an, 710069, China
| | - Yun Liang
- School of Cultural Heritage, Northwest University, Xi'an, 710069, China
| | - Yunpeng Tang
- School of Cultural Heritage, Northwest University, Xi'an, 710069, China
| | - Meng Ren
- School of Cultural Heritage, Northwest University, Xi'an, 710069, China
| | - Qinyan Dai
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Xiaotian Feng
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Peng Cao
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Ruowei Yang
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Feng Liu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Wanjing Ping
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China
| | - Ming Zhang
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Manyu Ding
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Melinda A Yang
- Department of Biology, University of Richmond, Richmond, VA, 23173, USA
| | - Berdimurodov Amridin
- Institute of Archaeology, Academy of Sciences of Uzbekistan, Samarkand, Uzbekistan
| | - Hasanov Muttaliu
- Institute of Archaeology, Academy of Sciences of Uzbekistan, Samarkand, Uzbekistan
| | - Jianxin Wang
- School of Cultural Heritage, Northwest University, Xi'an, 710069, China
| | - Qiaomei Fu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, 100044, China.,Center for Excellence in Life and Paleoenvironment, Chinese Academy of Sciences, Beijing, 100044, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
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30
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Moosanezhad Khabisi M, Asadi Foozi M, Lv FH, Esmailizadeh A. Genome-wide DNA arrays profiling unravels the genetic structure of Iranian sheep and pattern of admixture with worldwide coarse-wool sheep breeds. Genomics 2021; 113:3501-3511. [PMID: 34293474 DOI: 10.1016/j.ygeno.2021.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 05/18/2021] [Accepted: 07/17/2021] [Indexed: 10/20/2022]
Abstract
Archaeological and genetic evidence show that sheep were originally domesticated in area around the North of Zagros mountains, North-west of Iran. The Persian plateau exhibits a variety of native sheep breeds with a common characteristic of coarse-wool production. Therefore, knowledge about the genetic structure and diversity of Iranian sheep and genetic connections with other sheep breeds is of great interest. To this end, we genotyped 154 samples from 11 sheep breeds distributed across Iran with the Ovine Infinium HD SNP 600 K BeadChip array, and analyzed this dataset combined with the retrieved data of 558 samples from 19 worldwide coarse-wool sheep breeds. The average genetic diversity ranged from 0.315 to 0.354, while the FST values ranged from 0.016 to 0.177 indicating a low differentiation of Iranian sheep. Analysis of molecular variance showed that 90.21 and 9.79% of the source of variation were related to differences within and between populations, respectively. Our results indicated that the coarse-wool sheep from Europe were clearly different from those of the Asia. Accordingly, the Asiatic mouflon was positioned between Asian and European countries. In addition, we found that the genetic background of Iranian sheep is present in sheep from China and Kyrgyzstan, as well as India. The revealed admixture patterns of the Iranian sheep and other coarse-wool sheep breeds probably resulted from the expansion of nomads and through the Silk Road trade network.
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Affiliation(s)
- Mozhdeh Moosanezhad Khabisi
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, PB 76169-133 Kerman, Iran
| | - Masood Asadi Foozi
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, PB 76169-133 Kerman, Iran
| | - Feng-Hua Lv
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, PB 76169-133 Kerman, Iran.
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Chen J, He G, Ren Z, Wang Q, Liu Y, Zhang H, Yang M, Zhang H, Ji J, Zhao J, Guo J, Zhu K, Yang X, Wang R, Ma H, Wang CC, Huang J. Genomic Insights Into the Admixture History of Mongolic- and Tungusic-Speaking Populations From Southwestern East Asia. Front Genet 2021; 12:685285. [PMID: 34239544 PMCID: PMC8258170 DOI: 10.3389/fgene.2021.685285] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 05/05/2021] [Indexed: 12/17/2022] Open
Abstract
As a major part of the modern Trans-Eurasian or Altaic language family, most of the Mongolic and Tungusic languages were mainly spoken in northern China, Mongolia, and southern Siberia, but some were also found in southern China. Previous genetic surveys only focused on the dissection of genetic structure of northern Altaic-speaking populations; however, the ancestral origin and genomic diversification of Mongolic and Tungusic-speaking populations from southwestern East Asia remain poorly understood because of the paucity of high-density sampling and genome-wide data. Here, we generated genome-wide data at nearly 700,000 single-nucleotide polymorphisms (SNPs) in 26 Mongolians and 55 Manchus collected from Guizhou province in southwestern China. We applied principal component analysis (PCA), ADMIXTURE, f statistics, qpWave/qpAdm analysis, qpGraph, TreeMix, Fst, and ALDER to infer the fine-scale population genetic structure and admixture history. We found significant genetic differentiation between northern and southern Mongolic and Tungusic speakers, as one specific genetic cline of Manchu and Mongolian was identified in Guizhou province. Further results from ADMIXTURE and f statistics showed that the studied Guizhou Mongolians and Manchus had a strong genetic affinity with southern East Asians, especially for inland southern East Asians. The qpAdm-based estimates of ancestry admixture proportion demonstrated that Guizhou Mongolians and Manchus people could be modeled as the admixtures of one northern ancestry related to northern Tungusic/Mongolic speakers or Yellow River farmers and one southern ancestry associated with Austronesian, Tai-Kadai, and Austroasiatic speakers. The qpGraph-based phylogeny and neighbor-joining tree further confirmed that Guizhou Manchus and Mongolians derived approximately half of the ancestry from their northern ancestors and the other half from southern Indigenous East Asians. The estimated admixture time ranged from 600 to 1,000 years ago, which further confirmed the admixture events were mediated via the Mongolians Empire expansion during the formation of the Yuan dynasty.
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Affiliation(s)
- Jing Chen
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Guanglin He
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Zheng Ren
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Qiyan Wang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Yubo Liu
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Hongling Zhang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Meiqing Yang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Han Zhang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Jingyan Ji
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
| | - Jing Zhao
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Jianxin Guo
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Kongyang Zhu
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Xiaomin Yang
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Rui Wang
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Hao Ma
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Chuan-Chao Wang
- State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Marine Environmental Science, Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
- School of Basic Medical Sciences, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiang Huang
- Department of Forensic Medicine, Guizhou Medical University, Guiyang, China
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Abstract
The peopling of Siberia and the Americas is intriguing for archaeologists, linguists, and human geneticists, but despite significant recent developments, many details remain controversial. Here, we provide insights based on genetic diversity within Helicobacter pylori, a bacterium that infects 50% of all humans. H. pylori strains were collected from across eastern Eurasia and the Americas. Sequence analyses indicated that Siberia contains both anciently diverged and recently admixed bacteria, supporting both human persistence over the last glacial maximum and more recent human recolonization. We inferred a single migration across the Bering land bridge, accompanied by a dramatic reduction in effective population size, followed by bidirectional Holocene gene flow between Asia and the Americas. The gastric bacterium Helicobacter pylori shares a coevolutionary history with humans that predates the out-of-Africa diaspora, and the geographical specificities of H. pylori populations reflect multiple well-known human migrations. We extensively sampled H. pylori from 16 ethnically diverse human populations across Siberia to help resolve whether ancient northern Eurasian populations persisted at high latitudes through the last glacial maximum and the relationships between present-day Siberians and Native Americans. A total of 556 strains were cultivated and genotyped by multilocus sequence typing, and 54 representative draft genomes were sequenced. The genetic diversity across Eurasia and the Americas was structured into three populations: hpAsia2, hpEastAsia, and hpNorthAsia. hpNorthAsia is closely related to the subpopulation hspIndigenousAmericas from Native Americans. Siberian bacteria were structured into five other subpopulations, two of which evolved through a divergence from hpAsia2 and hpNorthAsia, while three originated though Holocene admixture. The presence of both anciently diverged and recently admixed strains across Siberia support both Pleistocene persistence and Holocene recolonization. We also show that hspIndigenousAmericas is endemic in human populations across northern Eurasia. The evolutionary history of hspIndigenousAmericas was reconstructed using approximate Bayesian computation, which showed that it colonized the New World in a single migration event associated with a severe demographic bottleneck followed by low levels of recent admixture across the Bering Strait.
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Liu Y, Yang J, Li Y, Tang R, Yuan D, Wang Y, Wang P, Deng S, Zeng S, Li H, Chen G, Zou X, Wang M, He G. Significant East Asian Affinity of the Sichuan Hui Genomic Structure Suggests the Predominance of the Cultural Diffusion Model in the Genetic Formation Process. Front Genet 2021; 12:626710. [PMID: 34194465 PMCID: PMC8237860 DOI: 10.3389/fgene.2021.626710] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 04/28/2021] [Indexed: 11/13/2022] Open
Abstract
The ancestral origin and genomic history of Chinese Hui people remain to be explored due to the paucity of genome-wide data. Some evidence argues that an eastward migration of Central Asians gave rise to modern Hui people, which is referred to as the demic diffusion hypothesis; other evidence favors the cultural diffusion hypothesis, which posits that East Asians adopted Muslim culture to form the modern culturally distinct populations. However, the extent to which the observed genetic structure of the Huis was mediated by the movement of people or the assimilation of Muslim culture also remains highly contentious. Analyses of over 700 K SNPs in 109 western Chinese individuals (49 Sichuan Huis and 60 geographically close Nanchong Hans) together with the available ancient and modern Eurasian sequences allowed us to fully explore the genomic makeup and origin of Hui and neighboring Han populations. The results from PCA, ADMIXTURE, and allele-sharing-based f-statistics revealed a strong genomic affinity between Sichuan Huis and Neolithic-to-modern Northern East Asians, which suggested a massive gene influx from East Asians into the Sichuan Hui people. Three-way admixture models in the qpWave/qpAdm analyses further revealed a small stream of gene influx from western Eurasians into the Sichuan Hui people, which was further directly confirmed via the admixture event from the temporally distinct Western sources to Sichuan Hui people in the qpGraph-based phylogenetic model, suggesting the key role of the cultural diffusion model in the genetic formation of the Sichuan Huis. ALDER-based admixture date estimation showed that this observed western Eurasian admixture signal was introduced into the Sichuan Huis during the historic periods, which was concordant with the extensive western-eastern communication along the Silk Road and historically documented Huis' migration history. In summary, although significant cultural differentiation exists between Hui people and their neighbors, our genomic analysis showed their strong genetic affinity with modern and ancient Northern East Asians. Our results support the hypothesis that the Sichuan Huis arose from a mixture of minor western Eurasian ancestry and predominant East Asian ancestry.
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Affiliation(s)
- Yan Liu
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China
| | - Junbao Yang
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China
| | | | - Renkuan Tang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Didi Yuan
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Yicheng Wang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Peixin Wang
- College of Medical Information, Chongqing Medical University, Chongqing, China
| | - Shudan Deng
- School of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Simei Zeng
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China
| | - Hongliang Li
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, China
| | - Gang Chen
- Hunan Key Lab of Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
| | - Xing Zou
- Department of Forensic Genetics, Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, China
| | - Mengge Wang
- Department of Forensic Genetics, Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, China
| | - Guanglin He
- Department of Forensic Genetics, Institute of Forensic Medicine, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu, China
- Department of Anthropology and Ethnology, Institute of Anthropology, National Institute for Data Science in Health and Medicine, School of Life Sciences, Xiamen University, Xiamen, China
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Bose A, Platt DE, Parida L, Drineas P, Paschou P. Integrating Linguistics, Social Structure, and Geography to Model Genetic Diversity within India. Mol Biol Evol 2021; 38:1809-1819. [PMID: 33481022 PMCID: PMC8097304 DOI: 10.1093/molbev/msaa321] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
India represents an intricate tapestry of population substructure shaped by geography, language, culture, and social stratification. Although geography closely correlates with genetic structure in other parts of the world, the strict endogamy imposed by the Indian caste system and the large number of spoken languages add further levels of complexity to understand Indian population structure. To date, no study has attempted to model and evaluate how these factors have interacted to shape the patterns of genetic diversity within India. We merged all publicly available data from the Indian subcontinent into a data set of 891 individuals from 90 well-defined groups. Bringing together geography, genetics, and demographic factors, we developed Correlation Optimization of Genetics and Geodemographics to build a model that explains the observed population genetic substructure. We show that shared language along with social structure have been the most powerful forces in creating paths of gene flow in the subcontinent. Furthermore, we discover the ethnic groups that best capture the diverse genetic substructure using a ridge leverage score statistic. Integrating data from India with a data set of additional 1,323 individuals from 50 Eurasian populations, we find that Indo-European and Dravidian speakers of India show shared genetic drift with Europeans, whereas the Tibeto-Burman speaking tribal groups have maximum shared genetic drift with East Asians.
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Affiliation(s)
- Aritra Bose
- Computational Genomics, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Daniel E Platt
- Computational Genomics, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Laxmi Parida
- Computational Genomics, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Petros Drineas
- Computer Science Department, Purdue University, West Lafayette, IN, USA
| | - Peristera Paschou
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
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Population genetic data for 21 autosomal STR loci in the Azerbaijani population using the Globalfiler™ kit. Int J Legal Med 2021; 135:1789-1791. [PMID: 33907867 DOI: 10.1007/s00414-021-02610-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 04/20/2021] [Indexed: 09/29/2022]
Abstract
The Republic of Azerbaijan is located in the southern Caucasus mountains, a region which is linguistically and ethnically diverse. We report allele frequency data for 21 autosomal loci from the Globalfiler™ kit in the Azerbaijani population using 467 individuals from Baku. Exact tests for Hardy Weinberg Equilibrium and Linkage Equilibrium were conducted, and all forensic parameters were estimated. High levels of Expected Heterozygosity HE were seen, with a minimum of 0.637 for TPOX and a maximum of 0.949 for SE33. Polymorphism Information Content (PIC) values for all STR loci were high, ranging from 0.587 for TPOX to 0.947 for SE33. Matching probability (MP) estimates ranged from 0.006 for SE33 to 0.178 for TPOX. Power of Discrimination (PD) values for most of the tested loci (17/21) were ≥ 0.9. The Combined Matching Probability (CMP) and the Combined Power of Discrimination (CPD) for all 21 loci were 7.84 × 10-27 and 1.0 respectively. Exact tests for population differentiation using all available Globalfiler™ datasets from across Europe and Asia reveal a general trend of higher differentiation with increasing geographical separation, but there is a need for additional population data from neighboring regions of Azerbaijan.
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Yelmen B, Marnetto D, Molinaro L, Flores R, Mondal M, Pagani L. Improving Selection Detection with Population Branch Statistic on Admixed Populations. Genome Biol Evol 2021; 13:6151747. [PMID: 33638983 PMCID: PMC8046333 DOI: 10.1093/gbe/evab039] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2021] [Indexed: 12/16/2022] Open
Abstract
Detecting natural selection signals in admixed populations can be problematic since the source of the signal typically dates back prior to the admixture event. On one hand, it is now possible to study various source populations before a particular admixture thanks to the developments in ancient DNA (aDNA) in the last decade. However, aDNA availability is limited to certain geographical regions and the sample sizes and quality of the data might not be sufficient for selection analysis in many cases. In this study, we explore possible ways to improve detection of pre-admixture signals in admixed populations using a local ancestry inference approach. We used masked haplotypes for population branch statistic (PBS) and full haplotypes constructed following our approach from Yelmen et al. (2019) for cross-population extended haplotype homozygosity (XP-EHH), utilizing forward simulations to test the power of our analysis. The PBS results on simulated data showed that using masked haplotypes obtained from ancestry deconvolution instead of the admixed population might improve detection quality. On the other hand, XP-EHH results using the admixed population were better compared with the local ancestry method. We additionally report correlation for XP-EHH scores between source and admixed populations, suggesting that haplotype-based approaches must be used cautiously for recently admixed populations. Additionally, we performed PBS on real South Asian populations masked with local ancestry deconvolution and report here the first possible selection signals on the autochthonous South Asian component of contemporary South Asian populations.
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Affiliation(s)
- Burak Yelmen
- Institute of Genomics, University of Tartu, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Estonia
| | | | - Ludovica Molinaro
- Institute of Genomics, University of Tartu, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Estonia
| | | | | | - Luca Pagani
- Institute of Genomics, University of Tartu, Estonia.,Department of Biology, University of Padova, Italy
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Jain A, Sharma D, Bajaj A, Gupta V, Scaria V. Founder variants and population genomes-Toward precision medicine. ADVANCES IN GENETICS 2021; 107:121-152. [PMID: 33641745 DOI: 10.1016/bs.adgen.2020.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Human migration and community specific cultural practices have contributed to founder events and enrichment of the variants associated with genetic diseases. While many founder events in isolated populations have remained uncharacterized, the application of genomics in clinical settings as well as for population scale studies in the recent years have provided an unprecedented push towards identification of founder variants associated with human health and disease. The discovery and characterization of founder variants could have far reaching implications not only in understanding the history or genealogy of the disease, but also in implementing evidence based policies and genetic testing frameworks. This further enables precise diagnosis and prevention in an attempt towards precision medicine. This review provides an overview of founder variants along with methods and resources cataloging them. We have also discussed the public health implications and examples of prevalent disease associated founder variants in specific populations.
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Affiliation(s)
- Abhinav Jain
- CSIR-Institute of Genomics and Integrative Biology, New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Disha Sharma
- CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Anjali Bajaj
- CSIR-Institute of Genomics and Integrative Biology, New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Vishu Gupta
- CSIR-Institute of Genomics and Integrative Biology, New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Vinod Scaria
- CSIR-Institute of Genomics and Integrative Biology, New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India.
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Huang X, Wang S, Jin L, He Y. Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation. Biol Open 2021; 10:bio056523. [PMID: 33495209 PMCID: PMC7888712 DOI: 10.1242/bio.056523] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Accepted: 12/21/2020] [Indexed: 01/05/2023] Open
Abstract
Human pigmentation is a highly diverse and complex trait among populations and has drawn particular attention from both academic and non-academic investigators for thousands of years. Previous studies detected selection signals in several human pigmentation genes, but few studies have integrated contribution from multiple genes to the evolution of human pigmentation. Moreover, none has quantified selective pressures on human pigmentation over epochs and between populations. Here, we dissect dynamics and differences of selective pressures during different periods and between distinct populations with new approaches. We use genotype data of 19 genes associated with human pigmentation from 17 publicly available datasets and obtain data for 2346 individuals of six representative population groups from across the world. Our results quantify the strength of natural selection on light pigmentation not only in modern Europeans (0.0259/generation) but also in proto-Eurasians (0.00650/generation). Our results also suggest that several derived alleles associated with human dark pigmentation may be under positive directional selection in some African populations. Our study provides the first attempt to quantitatively investigate the dynamics of selective pressures during different time periods in the evolution of human pigmentation.This article has an associated First Person interview with the first author of the article.
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Affiliation(s)
- Xin Huang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sijia Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Li Jin
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences-Max Planck Society Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Yungang He
- Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
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Balanovska EV, Petrushenko VS, Koshel SM, Pocheshkhova EA, Chernevskiy DK, Mirzaev KB, Abdullaev S, Balanovsky OP. Cartographic atlas of frequency variation for 45 pharmacogenetic markers in populations of Russia and its neighbor states. BULLETIN OF RUSSIAN STATE MEDICAL UNIVERSITY 2020. [DOI: 10.24075/brsmu.2020.080] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The lack of information about the frequency of pharmacogenetic markers in Russia impedes the adoption of personalized treatment algorithms originally developed for West European populations. The aim of this paper was to study the distribution of some clinically significant pharmacogenetic markers across Russia. A total of 45 pharmacogenetic markers were selected from a few population genetic datasets, including ADME, drug target and hemostasis-controlling genes. The total number of donors genotyped for these markers was 2,197. The frequencies of these markers were determined for 50 different populations, comprised of 137 ethnic and subethnic groups. A comprehensive pharmacogenetic atlas was created, i.e. a systematic collection of gene geographic maps of frequency variation for 45 pharmacogenetic DNA markers in Russia and its neighbor states. The maps revealed 3 patterns of geographic variation. Clinal variation (a gradient change in frequency along the East-West axis) is observed in the pharmacogenetic markers that follow the main pattern of variation for North Eurasia (13% of the maps). Uniform distribution singles out a group of markers that occur at average frequency in most Russian regions (27% of the maps). Focal variation is observed in the markers that are specific to a certain group of populations and are absent in other regions (60% of the maps). The atlas reveals that the average frequency of the marker and its frequency in individual populations do not indicate the type of its distribution in Russia: a gene geographic map is needed to uncover the pattern of its variation.
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Affiliation(s)
- EV Balanovska
- Bochkov Research Center for Medical Genetics, Moscow, Russia; Biobank of North Eurasia, Moscow, Russia
| | - VS Petrushenko
- Bochkov Research Center for Medical Genetics, Moscow, Russia; Vavilov Institute of General Genetics, Moscow, Russia
| | - SM Koshel
- Bochkov Research Center for Medical Genetics, Moscow, Russia; Lomonosov Moscow State University, Moscow, Russia
| | - EA Pocheshkhova
- Bochkov Research Center for Medical Genetics, Moscow, Russia; Kuban State Medical Institute, Krasnodar, Russia
| | - DK Chernevskiy
- Bochkov Research Center for Medical Genetics, Moscow, Russia
| | - KB Mirzaev
- Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - ShP Abdullaev
- Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - OP Balanovsky
- Bochkov Research Center for Medical Genetics, Moscow, Russia; Biobank of North Eurasia, Moscow, Russia; Vavilov Institute of General Genetics, Moscow, Russia
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Tham YC, Tao Y, Zhang L, Rim THT, Thakur S, Lim ZW, Chee ML, Bikbov MM, Kazakbaeva GM, Wang N, Cao K, Hao J, Nangia V, Panda-Jonas S, Wang YX, Wong IY, Chan JCH, Meng Q, Sabanayagam C, Wong TY, Jonas JB, Zhong H, Cheng CY. Is kidney function associated with primary open-angle glaucoma? Findings from the Asian Eye Epidemiology Consortium. Br J Ophthalmol 2020; 104:1298-1303. [PMID: 31959588 DOI: 10.1136/bjophthalmol-2019-314890] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 10/25/2019] [Accepted: 12/02/2019] [Indexed: 11/03/2022]
Abstract
AIM To comprehensively examine the association between kidney function and primary open angle glaucoma (POAG) in a large consortium of multiple Asian population-based studies. METHODS 28 925 participants (57 340 eyes) from 9 population-based studies (from China, Hong Kong, India, Korea, Russia, Singapore) of the Asian Eye Epidemiology Consortium were included. Across all studies, POAG was defined based on the International Society of Geographical and Epidemiological Ophthalmology criteria. Estimated glomerular filtration rate (eGFR) was calculated from serum creatinine. Chronic kidney disease (CKD) was defined as eGFR<60 mL/min/1.73 m2. Eye-specific data were pooled from each study. Multivariable regression analysis with generalised estimating equation models was performed to evaluate the associations between kidney function with POAG and intraocular pressure (IOP). RESULTS After adjusting for age, gender, study group, hypertension, diabetes, hyperlipidaemia, body mass index, smoking status and IOP, lower eGFR (per 10 mL/min/1.73 m2 decrease) was not significantly associated with POAG (OR=1.01; p=0.77). Presence of CKD was also not significantly associated with POAG (OR=1.01; p=0.739). Furthermore, lower eGFR and presence of CKD were not associated with IOP (all p≥0.12), However, in the subgroup of combined Korean and Chinese individuals, significant associations between lower eGFR (OR=1.09; 95% CI 1.00 to 1.18; p=0.048) and severe kidney function decline (<45 mL/min/1.73 m2; OR=2.57; 95% CI 1.34 to 4.93; p=0.004) with POAG, were observed. CONCLUSION In this large pooled-analysis of multiple Asian population-based studies, our findings suggest that the association between CKD and POAG may only be present in East Asians specifically but not in the overall Asian population. Further evaluation in Japanese population is warranted to confirm this observation.
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Affiliation(s)
- Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Yijin Tao
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Tyler Hyung Taek Rim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, Severance Hospital, Institute of Vision Research, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sahil Thakur
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Zhi Wei Lim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Miao Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | | | | | - Ningli Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Kai Cao
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jie Hao
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | | | - Songhomitra Panda-Jonas
- Department of Ophthalmology, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ian Y Wong
- Department of Ophthalmology, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
- Department of Ophthalmology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Jonathan Cheuk Hung Chan
- Department of Ophthalmology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Qianli Meng
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangzhou, Guangdong, China
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Tien Y Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jost B Jonas
- Department of Ophthalmology, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Hua Zhong
- Department of Ophthalmology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Science Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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41
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Ádám V, Bánfai Z, Maász A, Sümegi K, Miseta A, Melegh B. Investigating the genetic characteristics of the Csangos, a traditionally Hungarian speaking ethnic group residing in Romania. J Hum Genet 2020; 65:1093-1103. [PMID: 32653894 DOI: 10.1038/s10038-020-0799-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/23/2020] [Accepted: 06/27/2020] [Indexed: 11/09/2022]
Abstract
Csango people are an East-Central European ethnographic group living mostly in the historical region of Moldavia, Romania. Their traditional language, the Csango is an old Hungarian dialect, which is a severely endangered language due to language shift. Their origin is still disputed among experts and there are many hypotheses since the 19th century. Previous genetic studies found connection with ethnic groups living in Hungary and provided evidence which might support their Hungarian origin. Another study found Inner Asian Altaic ancestry in their genetic makeup. The goal of this study was to analyze the genetic characteristics of the Csango people by comparing their genetic characteristics to contemporary Eurasian populations based on genome-wide autosomal marker data. Our findings suggest that genetic affinity of Csangos to Hungarians is more significant than to Romanians. They also have a detectable connection with Central-Asian and Siberian Turkic ethnic groups. Besides the presumable Middle Eastern/Central-Asian Turkic ancestry, Csangos show ~4% Turkic ancestry from Central Asia/Siberia, which makes them unique in comparison to all other East-Central European populations investigated in this study. The admixture that resulted in this Turkic ancestry could have occurred 30-40 generations ago, which date interval corresponds to Hungarian historical events regarding their migration and the conquest of the Carpathian basin.
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Affiliation(s)
- Valerián Ádám
- Department of Medical Genetics, Clinical Centre, University of Pécs, Pécs, Hungary.,Szentágothai Research Centre, University of Pécs, Pécs, Hungary
| | - Zsolt Bánfai
- Department of Medical Genetics, Clinical Centre, University of Pécs, Pécs, Hungary. .,Szentágothai Research Centre, University of Pécs, Pécs, Hungary.
| | - Anita Maász
- Department of Medical Genetics, Clinical Centre, University of Pécs, Pécs, Hungary.,Szentágothai Research Centre, University of Pécs, Pécs, Hungary
| | - Katalin Sümegi
- Department of Medical Genetics, Clinical Centre, University of Pécs, Pécs, Hungary.,Szentágothai Research Centre, University of Pécs, Pécs, Hungary
| | - Attila Miseta
- Department of Laboratory Medicine, Medical School, University of Pécs, Pécs, Hungary
| | - Béla Melegh
- Department of Medical Genetics, Clinical Centre, University of Pécs, Pécs, Hungary. .,Szentágothai Research Centre, University of Pécs, Pécs, Hungary.
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42
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Mirzaev K, Abdullaev S, Akmalova K, Sozaeva J, Grishina E, Shuev G, Bolieva L, Sozaeva M, Zhuchkova S, Gimaldinova N, Sidukova E, Serebrova S, Asoskova A, Shein A, Poptsova M, Suleymanov S, Burashnikova I, Shikaleva A, Kachanova A, Fedorinov D, Sychev D. Interethnic differences in the prevalence of main cardiovascular pharmacogenetic biomarkers. Pharmacogenomics 2020; 21:677-694. [DOI: 10.2217/pgs-2020-0005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Background: The aim of this study was to determine the prevalence of CYP2C9, VKORC1, CYP2C19, ABCB1, CYP2D6 and SLCO1B1 genes polymorphisms among residents of the Volga region (Chuvash and Mari) and northern Caucasus (Kabardins and Ossetians). Materials & methods: The study involved 845 apparently healthy volunteers of both sexes of the four different ethnic groups living in the Russian Federation: 238 from the Chuvash ethnic group, 206 Mari, 157 Kabardins and 244 Ossetians. Results: Significant differences were identified in allele frequency of CYP2C9, VKORC1, CYP2C19, ABCB1, CYP2D6 and SLCO1B1 genes polymorphisms between the Chuvash and Kabardins, Chuvash and Ossetians, Mari and Kabardians, Mari and Ossetians.
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Affiliation(s)
- Karin Mirzaev
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Sherzod Abdullaev
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Kristina Akmalova
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Jeannette Sozaeva
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Elena Grishina
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Gregory Shuev
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Laura Bolieva
- Federal State Budgetary Educational Institution of Higher Education “North Ossetia State Medical Academy” of The Ministry of Healthcare of the Russian Federation, Pushkinskaya Str., 40, Vladikavkaz, Republic of North Ossetia–Alania, 362019, Russian Federation
| | - Mariam Sozaeva
- State Budgetary Healthcare Institution “Republican Clinical Hospital” of The Ministry of Healthcare of The Russian Federation, Nogmova Str., 91, Nalchik, Kabardino–Balkarian Republic, 360003, Russian Federation
| | - Svetlana Zhuchkova
- Autonomous Institution “Republican Clinical Oncology Center” of the Ministry of Health of The Chuvash Republic, Gladkov Str., 31, Cheboksary, Chuvash Republic, 428020, Russian Federation
| | - Natalya Gimaldinova
- Federal State Budgetary Educational Institution of Higher Education “I. N. Ulianov Chuvash State University”, Moskovskiy Pr., 15, Cheboksary, Chuvash Republic, 428015, Russian Federation
| | - Elena Sidukova
- State Budgetary Institution of The Republic of Mari El ‘Kozmodemyansk interdistrict hospital”, 3rd microdistrict, 25, Kozmodemyansk, Republic of Mari El, 425350, Russian Federation
| | - Svetlana Serebrova
- Department of Clinical Pharmacology & Propaedeutic of Internal Diseases of The Faculty of General Medicine of Sechenov First Moscow State Medical University of The Ministry of Health of The Russian Federation, Trubetskaya Str., 8, bld., Moscow, 2119991, Russian Federation
| | - Anastasia Asoskova
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Alexander Shein
- Laboratory of Bioinformatics, Big Data & Information Retrieval School, Faculty of Computer Science, National Research University Higher School of Economics, 3 Kochnovsky Proezd, Moscow, 109028, Russian Federation
| | - Maria Poptsova
- Laboratory of Bioinformatics, Big Data & Information Retrieval School, Faculty of Computer Science, National Research University Higher School of Economics, 3 Kochnovsky Proezd, Moscow, 109028, Russian Federation
| | - Salavat Suleymanov
- Russian–Japanese Medical Center “SAIKO”, Komsomolskaya St., 104, Khabarovsk, Khabarovsk Territory, 680000, Russian Federation
| | - Irina Burashnikova
- Kazan State Medical Academy, Kazan State Medical University, Mushtari st., 11, Kazan, Republic of Tatarstan, 420012, Russian Federation
| | - Anastasia Shikaleva
- Kazan State Medical Academy, Kazan State Medical University, Mushtari st., 11, Kazan, Republic of Tatarstan, 420012, Russian Federation
| | - Anastasia Kachanova
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Denis Fedorinov
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
| | - Dmitry Sychev
- Federal State Budgetary Educational Institution of Further Professional Education “Russian Medical Academy of Continuous Professional Education” of The Ministry of Healthcare of The Russian Federation, Barrikadnaya Str., 2/1, Bldg. 1, Moscow, 125993, Russian Federation
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43
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Zubair M, Hemphill BE, Schurr TG, Tariq M, Ilyas M, Ahmad H. Mitochondrial DNA diversity in the Khattak and Kheshgi of the Peshawar Valley, Pakistan. Genetica 2020; 148:195-206. [PMID: 32607672 DOI: 10.1007/s10709-020-00095-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 05/12/2020] [Indexed: 11/29/2022]
Abstract
The strategic location of Pakistan and its presence at the crossroads of Asia has resulted in it playing a central role in both prehistoric and historic human migratory events, thereby linking and facilitating contacts between the inhabitants of the Middle East, Central Asia, China and South Asia. Despite the importance of this region and its inhabitants for our understanding of modern human origins and population dispersals, the nature of mitochondrial DNA (mtDNA) variation among members of the myriad populations of this area has largely been unexplored. Here, we report mtDNA control region sequences in 58 individuals from the Khattak and the Kheshgi, two major Pakhtun tribes residing within the Peshawar Valley of northwestern Pakistan. The results reveal that these ethnic groups are genetically heterogeneous, having 55.7% West Eurasian, 33.9% South Asian and 10.2% East Asian haplogroups. The genetic diversity observed for the Kheshgi was somewhat higher than that of the Khattak. A multidimensional scaling plot based on haplogroup frequencies for the Khattak, Kheshgi and neighboring populations indicates that the Khattak have close affinities with Baluch, Uzbek and Kazak populations but are only distantly related to the Kheshgi and other Pakistani populations. By contrast, the Kheshgi cluster closely with other Pakhtun or Pathan populations of Pakistan, suggesting a possible common maternal gene pool shared amongst them. These mtDNA data allow us to begin reconstructing the origins of the Khattak and Kheshgi and describe their complex interactions with populations from the surrounding regions.
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Affiliation(s)
- Muhammad Zubair
- Department of Zoology, Hazara University Mansehra, Mansehra, 21120, Pakistan.,Department of Genetics, Hazara University Mansehra, Mansehra, 21120, Pakistan
| | - Brian E Hemphill
- Department of Anthropology, University of Alaska, Fairbanks, AK, 99775, USA
| | - Theodore G Schurr
- Department of Anthropology, University of Pennsylvania, Philadelphia, 19104, USA
| | - Muhammad Tariq
- Centre for Omic Sciences, Islamia College Peshawar, Peshawar, 25120, Pakistan
| | - Muhammad Ilyas
- Centre for Omic Sciences, Islamia College Peshawar, Peshawar, 25120, Pakistan
| | - Habib Ahmad
- Department of Genetics, Hazara University Mansehra, Mansehra, 21120, Pakistan. .,Centre for Omic Sciences, Islamia College Peshawar, Peshawar, 25120, Pakistan.
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44
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Recent effective population size in Eastern European plain Russians correlates with the key historical events. Sci Rep 2020; 10:9729. [PMID: 32546820 PMCID: PMC7298007 DOI: 10.1038/s41598-020-66734-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 05/12/2020] [Indexed: 11/13/2022] Open
Abstract
Effective population size reflects the history of population growth, contraction, and structuring. When the effect of structuring is negligible, the inferred trajectory of the effective population size can be informative about the key events in the history of a population. We used the IBDNe and DoRIS approaches, which exploit the data on IBD sharing between genomes, to reconstruct the recent effective population size in two population datasets of Russians from Eastern European plain: (1) ethnic Russians sampled from the westernmost part of Russia; (2) ethnic Russians, Bashkirs, and Tatars sampled from the Volga-Ural region. In this way, we examined changes in effective population size among ethnic Russians that reside in their historical area at the West of the plain, and that expanded eastward to come into contact with the indigenous peoples at the East of the plain. We compared the inferred demographic trajectories of each ethnic group to written historical data related to demographic events such as migration, war, colonization, famine, establishment, and collapse of empires. According to IBDNe estimations, 200 generations (~6000 years) ago, the effective size of the ancestral populations of Russians, Bashkirs, and Tatars hovered around 3,000, 30,000, and 8,000 respectively. Then, the ethnic Russians exponentially grew with increasing rates for the last 115 generations and become the largest ethnic group of the plain. Russians do not show any drop in effective population size after the key historical conflicts, including the Mongol invasion. The only exception is a moderate drop in the 17th century, which is well known in Russian history as The Smuta. Our analyses suggest a more eventful recent population history for the two small ethnic groups that came into contact with ethnic Russians in the Volga-Ural region. We found that the effective population size of Bashkirs and Tatars started to decrease during the time of the Mongol invasion. Interestingly, there is an even stronger drop in the effective population size that coincides with the expansion of Russians to the East. Thus, 15–20 generations ago, i.e. in the 16–18th centuries in the trajectories of Bashkirs and Tatars, we observe the bottlenecks of four and twenty thousand, respectively. Our results on the recent effective population size correlate with the key events in the history of populations of the Eastern European plain and have importance for designing biomedical studies in the region.
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45
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Recently lost connectivity in the Western Palaearctic steppes: the case of a scarce specialist butterfly. CONSERV GENET 2020. [DOI: 10.1007/s10592-020-01271-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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46
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Uchiyama J, Gillam JC, Savelyev A, Ning C. Populations dynamics in Northern Eurasian forests: a long-term perspective from Northeast Asia. EVOLUTIONARY HUMAN SCIENCES 2020; 2:e16. [PMID: 37588381 PMCID: PMC10427466 DOI: 10.1017/ehs.2020.11] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The 'Northern Eurasian Greenbelt' (NEG) is the northern forest zone stretching from the Japanese Archipelago to Northern Europe. The NEG has created highly productive biomes for humanity to exploit since the end of the Pleistocene. This research explores how the ecological conditions in northern Eurasia contributed to and affected human migrations and cultural trajectories by synthesizing the complimentary viewpoints of environmental archaeology, Geographic Information Science (GIS), genetics and linguistics. First, the environmental archaeology perspective raises the possibility that the NEG functioned as a vessel fostering people to develop diverse cultures and engage in extensive cross-cultural exchanges. Second, geographical analysis of genomic data on mitochondrial DNA using GIS reveals the high probability that population dynamics in the southeastern NEG promoted the peopling of the Americas at the end of the Pleistocene. Finally, a linguistic examination of environmental- and landscape-related vocabulary of the proto-Turkic language groups enables the outline of their original cultural landscape and natural conditions, demonstrating significant cultural spheres, i.e. from southern Siberia to eastern Inner Mongolia during Neolithization. All of these results combine to suggest that the ecological complex in the southern edge of the NEG in northeast Asia played a significant role in peopling across the continents during prehistory.
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Affiliation(s)
- Junzo Uchiyama
- The Sainsbury Institute for the Study of Japanese Arts and Cultures, University of East Anglia, 64 The Close, NorwichNR1 4DH, UK
- Center for Cultural Resource Studies, Kanazawa University, Kakuma-machi, Kanazawa-shi, 920-1192, Japan
| | - J. Christopher Gillam
- Department of Sociology, Criminology and Anthropology, Winthrop University, 319 Kinard Hall, Rock Hill, SC29733, USA
| | - Alexander Savelyev
- Max Planck Institute for the Science of Human History, 07745Jena, Germany
- Institute of Linguistics, Russian Academy of Sciences, Bolshoy Kislovsky Pereulok 1/1, 125009Moscow, Russia
| | - Chao Ning
- Max Planck Institute for the Science of Human History, 07745Jena, Germany
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47
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Abstract
Geographic patterns in human genetic diversity carry footprints of population history and provide insights for genetic medicine and its application across human populations. Summarizing and visually representing these patterns of diversity has been a persistent goal for human geneticists, and has revealed that genetic differentiation is frequently correlated with geographic distance. However, most analytical methods to represent population structure do not incorporate geography directly, and it must be considered post hoc alongside a visual summary of the genetic structure. Here, we estimate "effective migration" surfaces to visualize how human genetic diversity is geographically structured. The results reveal local patterns of differentiation in detail and emphasize that while genetic similarity generally decays with geographic distance, the relationship is often subtly distorted. Overall, the visualizations provide a new perspective on genetics and geography in humans and insight to the geographic distribution of human genetic variation.
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Affiliation(s)
- Benjamin M Peter
- Department of Human Genetics, University of Chicago, Chicago, IL
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Desislava Petkova
- Wellcome Trust Center for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, IL
- Department of Ecology & Evolution, University of Chicago, Chicago, IL
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48
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Yelmen B, Mondal M, Marnetto D, Pathak AK, Montinaro F, Gallego Romero I, Kivisild T, Metspalu M, Pagani L. Ancestry-Specific Analyses Reveal Differential Demographic Histories and Opposite Selective Pressures in Modern South Asian Populations. Mol Biol Evol 2020; 36:1628-1642. [PMID: 30952160 PMCID: PMC6657728 DOI: 10.1093/molbev/msz037] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Genetic variation in contemporary South Asian populations follows a northwest to southeast decreasing cline of shared West Eurasian ancestry. A growing body of ancient DNA evidence is being used to build increasingly more realistic models of demographic changes in the last few thousand years. Through high-quality modern genomes, these models can be tested for gene and genome level deviations. Using local ancestry deconvolution and masking, we reconstructed population-specific surrogates of the two main ancestral components for more than 500 samples from 25 South Asian populations and showed our approach to be robust via coalescent simulations. Our f3 and f4 statistics–based estimates reveal that the reconstructed haplotypes are good proxies for the source populations that admixed in the area and point to complex interpopulation relationships within the West Eurasian component, compatible with multiple waves of arrival, as opposed to a simpler one wave scenario. Our approach also provides reliable local haplotypes for future downstream analyses. As one such example, the local ancestry deconvolution in South Asians reveals opposite selective pressures on two pigmentation genes (SLC45A2 and SLC24A5) that are common or fixed in West Eurasians, suggesting post-admixture purifying and positive selection signals, respectively.
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Affiliation(s)
- Burak Yelmen
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Mayukh Mondal
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Ajai K Pathak
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Francesco Montinaro
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Irene Gallego Romero
- Melbourne Integrative Genomics and School of BioSciences, University of Melbourne, Parkville, Australia
| | - Toomas Kivisild
- Institute of Genomics, University of Tartu, Tartu, Estonia.,Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Mait Metspalu
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Luca Pagani
- Institute of Genomics, University of Tartu, Tartu, Estonia.,APE Lab, Department of Biology, University of Padova, Padova, Italy
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49
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Balanovska EV, Skhalyakho RA, Kagazezheva ZA, Zaporozhchenko VV, Urasin VM, Agdzhoyan AT, Koshel SM, Pocheshkhova EA, Balanovsky OP. Inferring the Genetic Ancestry of Ubykh People from North Caucasus. RUSS J GENET+ 2020. [DOI: 10.1134/s1022795419090035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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50
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Mallory J, Dybo A, Balanovsky O. The Impact of Genetics Research on Archaeology and Linguistics in Eurasia. RUSS J GENET+ 2020. [DOI: 10.1134/s1022795419120081] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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