Search

Your search keyword '"Balanovsky, O."' showing total 200 results
Start Over Author "Balanovsky, O."
200 results on '"Balanovsky, O."'

2. Variation of Genomic Sites Associated with Severe Covid-19 Across Populations: Global and National Patterns

Author

Balanovsky O, Petrushenko V, Mirzaev K, Abdullaev S, Gorin I, Chernevskiy D, Agdzhoyan A, Balanovska E, Kryukov A, Temirbulatov I, and Sychev D

Subjects
severe covid-19, genetic markers, ab0, rs11385942, rs657152, gene geography, Therapeutics. Pharmacology, RM1-950
Abstract

Oleg Balanovsky,1– 3 Valeria Petrushenko,1,4 Karin Mirzaev,2,5 Sherzod Abdullaev,5 Igor Gorin,1,4 Denis Chernevskiy,2 Anastasiya Agdzhoyan,1,2 Elena Balanovska,2,3 Alexander Kryukov,5 Ilyas Temirbulatov,2,5 Dmitriy Sychev5 1Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia; 2Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia; 3Biobank of North Eurasia, Moscow, Russia; 4Department of Bioinformatics Moscow Institute of Physics and Technology, Moscow, Russia; 5Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, RussiaCorrespondence: Elena BalanovskaLaboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, RussiaTel +7 499 612-81-79Email balanovska@mail.ruDmitriy SychevDepartment of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, RussiaTel +7 495 680-05-99Email dmitry.alex.sychev@gmail.comBackground: 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.Keywords: severe COVID-19, genetic markers, AB0, rs11385942, rs657152, gene geography

Published
2021

8. Demographic and Genetic Portraits of the Ulchi Population

Author

Balanovska, E. V., Bogunov, Y. V., Kamenshikova, E. N., Balaganskaya, O. A., Agdzhoyan, A. T., Bogunova, A. A., Skhalyakho, R. A., Alborova, I. E., Zhabagin, M. K., Koshel, S. M., Daragan, D. M., Borisova, E. B., Galakhova, A. A., Maltceva, O. V., Mustafin, Kh. Kh., Yankovsky, N. K., and Balanovsky, O. P.

Published
2018
Full Text
View/download PDF

12. Population biobanks: Organizational models and prospects of application in gene geography and personalized medicine

Author

Balanovska, E. V., Zhabagin, M. K., Agdzhoyan, A. T., Chukhryaeva, M. I., Markina, N. V., Balaganskaya, O. A., Skhalyakho, R. A., Yusupov, Yu. M., Utevska, O. M., Bogunov, Yu. V., Asilguzhin, R. R., Dolinina, D. O., Kagazezheva, Zh. A., Damba, L. D., Zaporozhchenko, V. V., Romanov, A. G., Dibirova, Kh. D., Kuznetsova, M. A., Lavryashina, M. B., Pocheshkhova, E. A., and Balanovsky, O. P.

Published
2016
Full Text
View/download PDF

19. Ten millennia of hepatitis B virus evolution

Author

Kocher, A, Papac, L, Barquera, R, Key, FM, Spyrou, MA, Hubler, R, Rohrlach, AB, Aron, F, Stahl, R, Wissgott, A, van Bommel, F, Pfefferkorn, M, Mittnik, A, Villalba-Mouco, V, Neumann, GU, Rivollat, M, van de Loosdrecht, MS, Majander, K, Tukhbatova, R, Musralina, L, Ghalichi, A, Penske, S, Sabin, S, Michel, M, Gretzinger, J, Nelson, EA, Ferraz, T, Nagele, K, Parker, C, Keller, M, Guevara, EK, Feldman, M, Eisenmann, S, Skourtanioti, E, Giffin, K, Gnecchi-Ruscone, GA, Friederich, S, Schimmenti, V, Khartanovich, V, Karapetian, MK, Chaplygin, MS, Kufterin, VV, Khokhlov, AA, Chizhevsky, AA, Stashenkov, DA, Kochkina, AF, Tejedor-Rodriguez, C, Garcia-Martinez de Lagran, I, Arcusa-Magallon, H, Garrido-Pena, R, Ignacio Royo-Guillen, J, Novacek, J, Rottier, S, Kacki, S, Saintot, S, Kaverzneva, E, Belinskiy, AB, Veleminsky, P, Limbursky, P, Kostka, M, Loe, L, Popescu, E, Clarke, R, Lyons, A, Mortimer, R, Sajantila, A, Chinique de Armas, Y, Hernandez Godoy, ST, Hernandez-Zaragoza, D, Pearson, J, Binder, D, Lefranc, P, Kantorovich, AR, Maslov, VE, Lai, L, Zoledziewska, M, Beckett, JF, Langova, M, Ingman, T, Garcia Atienzar, G, de Miguel Ibanez, MP, Romero, A, Sperduti, A, Beckett, S, Salter, SJ, Zilivinskaya, ED, Vasil, DV, von Heyking, K, Burger, RL, Salazar, LC, Amkreutz, L, Navruzbekov, M, Rosenstock, E, Alonso-Fernandez, C, Slavchev, V, Kalmykov, AA, Atabiev, BC, Batieva, E, Alvarez Calmet, M, Llamas, B, Schultz, M, Krauss, R, Jimenez-Echevarria, J, Francken, M, Shnaider, S, de Knijff, P, Altena, E, Van de Vijver, K, Fehren-Schmitz, L, Tung, TA, Losch, S, Dobrovolskaya, M, Makarov, N, Read, C, Van Twest, M, Sagona, C, Ramsl, PC, Akar, M, Yener, KA, Carmona Ballestero, E, Cucca, F, Mazzarello, V, Utrilla, P, Rademaker, K, Fernandez-Dominguez, E, Baird, D, Semal, P, Marquez-Morfin, L, Roksandic, M, Steiner, H, Carlos Salazar-Garcia, D, Shishlina, N, Erdal, YS, Hallgren, F, Boyadzhiev, Y, Boyadzhiev, K, Kuessner, M, Sayer, D, Onkamo, P, Skeates, R, Rojo-Guerra, M, Buzhilova, A, Khussainova, E, Djansugurova, LB, Beisenov, AZ, Samashev, Z, Massy, K, Mannino, M, Moiseyev, V, Mannermaa, K, Balanovsky, O, Deguilloux, M-F, Reinhold, S, Hansen, S, Kitov, EP, Dobes, M, Ernee, M, Meller, H, Alt, KW, Prufer, K, Warinner, C, Schiffels, S, Stockhammer, PW, Bos, K, Posth, C, Herbig, A, Haak, W, Krause, J, Kuehnert, D, Kocher, A, Papac, L, Barquera, R, Key, FM, Spyrou, MA, Hubler, R, Rohrlach, AB, Aron, F, Stahl, R, Wissgott, A, van Bommel, F, Pfefferkorn, M, Mittnik, A, Villalba-Mouco, V, Neumann, GU, Rivollat, M, van de Loosdrecht, MS, Majander, K, Tukhbatova, R, Musralina, L, Ghalichi, A, Penske, S, Sabin, S, Michel, M, Gretzinger, J, Nelson, EA, Ferraz, T, Nagele, K, Parker, C, Keller, M, Guevara, EK, Feldman, M, Eisenmann, S, Skourtanioti, E, Giffin, K, Gnecchi-Ruscone, GA, Friederich, S, Schimmenti, V, Khartanovich, V, Karapetian, MK, Chaplygin, MS, Kufterin, VV, Khokhlov, AA, Chizhevsky, AA, Stashenkov, DA, Kochkina, AF, Tejedor-Rodriguez, C, Garcia-Martinez de Lagran, I, Arcusa-Magallon, H, Garrido-Pena, R, Ignacio Royo-Guillen, J, Novacek, J, Rottier, S, Kacki, S, Saintot, S, Kaverzneva, E, Belinskiy, AB, Veleminsky, P, Limbursky, P, Kostka, M, Loe, L, Popescu, E, Clarke, R, Lyons, A, Mortimer, R, Sajantila, A, Chinique de Armas, Y, Hernandez Godoy, ST, Hernandez-Zaragoza, D, Pearson, J, Binder, D, Lefranc, P, Kantorovich, AR, Maslov, VE, Lai, L, Zoledziewska, M, Beckett, JF, Langova, M, Ingman, T, Garcia Atienzar, G, de Miguel Ibanez, MP, Romero, A, Sperduti, A, Beckett, S, Salter, SJ, Zilivinskaya, ED, Vasil, DV, von Heyking, K, Burger, RL, Salazar, LC, Amkreutz, L, Navruzbekov, M, Rosenstock, E, Alonso-Fernandez, C, Slavchev, V, Kalmykov, AA, Atabiev, BC, Batieva, E, Alvarez Calmet, M, Llamas, B, Schultz, M, Krauss, R, Jimenez-Echevarria, J, Francken, M, Shnaider, S, de Knijff, P, Altena, E, Van de Vijver, K, Fehren-Schmitz, L, Tung, TA, Losch, S, Dobrovolskaya, M, Makarov, N, Read, C, Van Twest, M, Sagona, C, Ramsl, PC, Akar, M, Yener, KA, Carmona Ballestero, E, Cucca, F, Mazzarello, V, Utrilla, P, Rademaker, K, Fernandez-Dominguez, E, Baird, D, Semal, P, Marquez-Morfin, L, Roksandic, M, Steiner, H, Carlos Salazar-Garcia, D, Shishlina, N, Erdal, YS, Hallgren, F, Boyadzhiev, Y, Boyadzhiev, K, Kuessner, M, Sayer, D, Onkamo, P, Skeates, R, Rojo-Guerra, M, Buzhilova, A, Khussainova, E, Djansugurova, LB, Beisenov, AZ, Samashev, Z, Massy, K, Mannino, M, Moiseyev, V, Mannermaa, K, Balanovsky, O, Deguilloux, M-F, Reinhold, S, Hansen, S, Kitov, EP, Dobes, M, Ernee, M, Meller, H, Alt, KW, Prufer, K, Warinner, C, Schiffels, S, Stockhammer, PW, Bos, K, Posth, C, Herbig, A, Haak, W, Krause, J, and Kuehnert, D

Abstract

Hepatitis B virus (HBV) has been infecting humans for millennia and remains a global health problem, but its past diversity and dispersal routes are largely unknown. We generated HBV genomic data from 137 Eurasians and Native Americans dated between ~10,500 and ~400 years ago. We date the most recent common ancestor of all HBV lineages to between ~20,000 and 12,000 years ago, with the virus present in European and South American hunter-gatherers during the early Holocene. After the European Neolithic transition, Mesolithic HBV strains were replaced by a lineage likely disseminated by early farmers that prevailed throughout western Eurasia for ~4000 years, declining around the end of the 2nd millennium BCE. The only remnant of this prehistoric HBV diversity is the rare genotype G, which appears to have reemerged during the HIV pandemic.

Published
2021

28. Characterizing the genetic history of admixture across inner Eurasia

Author

Jeong, C., Balanovsky, O., Lukianova, E., Kahbatkyzy, N., Flegontov, P., Zaporozhchenko, V., Immel, A., Wang, C., Ixan, O., Khussainova, E., Bekmanov, B., Zaibert, V., Lavryashina, M., Pocheshkhova, E., Yusupov, Y., Agdzhoyan, A., Sergey, K., Bukin, A., Nymadawa, P., Churnosov, M., Skhalyakho, R., Daragan, D., Bogunov, Y., Bogunova, A., Shtrunov, A., Dubova, N., Zhabagin, M., Yepiskoposyan, L., Churakov, V., Pislegin, N., Damba, L., Saroyants, L., Dibirova, K., Artamentova, L., Utevska, O., Idrisov, E., Kamenshchikova, E., Evseeva, I., Metspalu, M., Robbeets, M., Djansugurova, L., Balanovska, E., Schiffels, S., Haak, W., Reich, D., and Krause, J.

Abstract

The indigenous populations of inner Eurasia, a huge geographic region covering the central Eurasian steppe and the northern Eurasian taiga and tundra, harbor tremendous diversity in their genes, cultures and languages. In this study, we report novel genome-wide data for 763 individuals from Armenia, Georgia, Kazakhstan, Moldova, Mongolia, Russia, Tajikistan, Ukraine, and Uzbekistan. We furthermore report genome-wide data of two Eneolithic individuals (~5,400 years before present) associated with the Botai culture in northern Kazakhstan. We find that inner Eurasian populations are structured into three distinct admixture clines stretching between various western and eastern Eurasian ancestries. This genetic separation is well mirrored by geography. The ancient Botai genomes suggest yet another layer of admixture in inner Eurasia that involves Mesolithic hunter-gatherers in Europe, the Upper Paleolithic southern Siberians and East Asians. Admixture modeling of ancient and modern populations suggests an overwriting of this ancient structure in the Altai-Sayan region by migrations of western steppe herders, but partial retaining of this ancient North Eurasian-related cline further to the North. Finally, the genetic structure of Caucasus populations highlights a role of the Caucasus Mountains as a barrier to gene flow and suggests a post-Neolithic gene flow into North Caucasus populations from the steppe.

Published
2018

29. The genetic prehistory of the Greater Caucasus

Author

Wang, C., Reinhold, S., Kalmykov, A., Wissgott, A., Brandt, G., Jeong, C., Cheronet, O., Ferry, M., Harney, E., Keating, D., Mallick, S., Rohland, N., Stewardson, K., Kantorovich, A., Maslov, V., Petrenko, V., Erlikh, V., Atabiev, B., Magomedov, R., Kohl, P., Alt, K., Pichler, S., Gerling, C., Meller, H., Vardanyan, B., Yeganyan, L., Rezepkin, A., Mariaschk, D., Berezina, N., Gresky, J., Fuchs, K., Knipper, C., Schiffels, S., Balanovska, E., Balanovsky, O., Mathieson, I., Higham, T., Berezin, Y., Buzhilova, A., Trifonov, V., Pinhasi, R., Belinskiy, A., Reich, D., Hansen, S., Krause, J., and Haak, W.

Abstract

Archaeogenetic studies have described the formation of Eurasian ’}steppe ancestry{’ as a mixture of Eastern and Caucasus hunter-gatherers. However, it remains unclear when and where this ancestry arose and whether it was related to a horizon of cultural innovations in the 4th millennium BCE that subsequently facilitated the advance of pastoral societies likely linked to the dispersal of Indo-European languages. To address this, we generated genome-wide SNP data from 45 prehistoric individuals along a 3000-year temporal transect in the North Caucasus. We observe a genetic separation between the groups of the Caucasus and those of the adjacent steppe. The Caucasus groups are genetically similar to contemporaneous populations south of it, suggesting that - unlike today - the Caucasus acted as a bridge rather than an insurmountable barrier to human movement. The steppe groups from Yamnaya and subsequent pastoralist cultures show evidence for previously undetected Anatolian farmer-related ancestry from different contact zones, while Steppe Maykop individuals harbour additional Upper Palaeolithic Siberian and Native American related ancestry.

Published
2018

30. Ancient Fennoscandian genomes reveal origin and spread of Siberian ancestry in Europe

Author

Lamnidis, T., Majander, K., Jeong, C., Salmela, E., Wessman, A., Moiseyev, V., Khartanovich, V., Balanovsky, O., Ongyerth, M., Weihmann, A., Sajantila, A., Kelso, J., Pääbo, S., Onkamo, P., Haak, W., Krause, J., and Schiffels, S.

Abstract

European history has been shaped by migrations of people, and their subsequent admixture. Recently, evidence from ancient DNA has brought new insights into migration events that could be linked to the advent of agriculture, and possibly to the spread of Indo-European languages. However, little is known so far about the ancient population history of north-eastern Europe, in particular about populations speaking Uralic languages, such as Finns and Saami. Here we analyse ancient genomic data from 11 individuals from Finland and Northwest Russia. We show that the specific genetic makeup of northern Europe traces back to migrations from Siberia that began at least 3,500 years ago. This ancestry was subsequently admixed into many modern populations in the region, in particular populations speaking Uralic languages today. In addition, we show that ancestors of modern Saami inhabited a larger territory during the Iron Age than today, which adds to historical and linguistic evidence for the population history of Finland.

Published
2018

32. Aboriginal Australian mitochondrial genome variation – an increased understanding of population antiquity and diversity

Author

Nagle, N, Van Oven, M, Wilcox, S, Van Holst Pellekaan, S, Tyler-Smith, C, Xue, Y, Ballantyne, KN, Wilcox, L, Papac, L, Cooke, K, Van Oorschot, RAH, McAllister, P, Williams, L, Kayser, M, Mitchell, RJ, Adhikarla, S, Adler, CJ, Balanovska, E, Balanovsky, O, Bertranpetit, J, Clarke, AC, Comas, D, Cooper, A, Der Sarkissian, CSI, Dulik, MC, Gaieski, JB, Kumar, A, Prasad, G, Haak, W, Haber, M, Hobbs, A, Javed, A, Jin, L, Kaplan, ME, Li, S, Martinez-Cruz, B, Matisoo-Smith, EA, Mele, M, Merchant, NC, Owings, AC, Parida, L, Pitchappan, R, Platt, DE, Quintana-Murci, L, Renfrew, C, Royyuru, AK, Santhakumari, AV, Santos, FR, Schurr, TG, Soodyall, H, Soria Hernanz, DF, Swamikrishnan, P, Vilar, MG, Wells, RS, Zalloua, PA, Ziegle, JS, Martinez Cruz, B, Genetic Identification, La Trobe University [Melbourne], Erasmus University Medical Center [Rotterdam] (Erasmus MC), Australian Genome Research Facility, University of Queensland [Brisbane], University of New South Wales [Canberra Campus] (UNSW), The University of Sydney, The Wellcome Trust Sanger Institute [Cambridge], Griffith University [Brisbane], The Genographic Project was supported by National Geographic Society, IBM and the Waitt Family Foundation. Y.L.X. and C.T.-S. were supported by The Wellcome Trust (098051). M.K., M.v.O., and K.N.B. were supported by Erasmus M.C., and We gratefully acknowledge the participation of Aboriginal Australians from Victoria, Queensland, the Northern Territory, South Australia, Western Australia and Tasmania whose collaboration made this study possible. We owe Tammy Williams and Jason Tatipata many thanks for their support throughout this study.

Subjects
0301 basic medicine, Mitochondrial DNA, Native Hawaiian or Other Pacific Islander, [SDV]Life Sciences [q-bio], Population, Evolutionary biology, Biology, Article, Haplogroup, 03 medical and health sciences, 0302 clinical medicine, Phylogenetics, Genetics, Humans, Clade, education, QH426, Phylogeny, [SDV.GEN]Life Sciences [q-bio]/Genetics, education.field_of_study, Multidisciplinary, Phylogenetic tree, Haplotype, Australia, Genetic Variation, Sequence Analysis, DNA, 030104 developmental biology, Haplotypes, Genome, Mitochondrial, 030217 neurology & neurosurgery, Human mitochondrial DNA haplogroup
Abstract

Aboriginal Australians represent one of the oldest continuous cultures outside Africa, with evidence indicating that their ancestors arrived in the ancient landmass of Sahul (present-day New Guinea and Australia) ~55 thousand years ago. Genetic studies, though limited, have demonstrated both the uniqueness and antiquity of Aboriginal Australian genomes. We have further resolved known Aboriginal Australian mitochondrial haplogroups and discovered novel indigenous lineages by sequencing the mitogenomes of 127 contemporary Aboriginal Australians. In particular, the more common haplogroups observed in our dataset included M42a, M42c, S, P5 and P12, followed by rarer haplogroups M15, M16, N13, O, P3, P6 and P8. We propose some major phylogenetic rearrangements, such as in haplogroup P where we delinked P4a and P4b and redefined them as P4 (New Guinean) and P11 (Australian), respectively. Haplogroup P2b was identified as a novel clade potentially restricted to Torres Strait Islanders. Nearly all Aboriginal Australian mitochondrial haplogroups detected appear to be ancient, with no evidence of later introgression during the Holocene. Our findings greatly increase knowledge about the geographic distribution and phylogenetic structure of mitochondrial lineages that have survived in contemporary descendants of Australia’s first settlers.

Published
2017
Full Text
View/download PDF

33. The genetic history of Northern Europe

Author

Mittnik, A., Wang, C., Pfrengle, S., Daubaras, M., Zariņa, G., Hallgren, F., Allmäe, R., Khartanovich, V., Moiseyev, V., Furtwängler, A., Andrades Valtueña, A., Feldman, M., Economou, C., Oinonen, M., Vasks, A., Tõrv, M., Balanovsky, O., Reich, D., Jankauskas, R., Haak, W., Schiffels, S., and Krause, J.

Published
2017

35. Estimating the impact of the Mongol expansion upon the gene pool of Tuvans

Author

Damba, L. D., primary, Balanovskaya, Е. V., additional, Zhabagin, M. K., additional, Yusupov, Y. М., additional, Bogunov, Y. V., additional, Sabitov, Z. M., additional, Agdzhoyan, A. T., additional, Korotkova, N. A., additional, Lavryashina, M. B., additional, Mongush, B. B., additional, Kavai-ool, U. N., additional, and Balanovsky, O. P., additional

Published
2018
Full Text
View/download PDF

36. Gene pool of the Novgorod population: Between the north and the south

Author

Balanovska, E. V., primary, Agdzhoyan, A. T., additional, Skhalyakho, R. A., additional, Balaganskaya, O. A., additional, Freydin, G. S., additional, Chernevskii, K. G., additional, Chernevskii, D. K., additional, Stepanov, G. D., additional, Kagazezheva, Z. A., additional, Zaporozhchenko, V. V., additional, Markina, N. V., additional, Palipana, D., additional, Koshel, S. M., additional, Kozlov, S. A., additional, and Balanovsky, O. P., additional

Published
2017
Full Text
View/download PDF

37. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

Author

Mallick, S, Li, H, Lipson, M, Mathieson, I, Gymrek, M, Racimo, F, Zhao, M, Chennagiri, N, Nordenfelt, S, Tandon, A, Skoglund, P, Lazaridis, I, Sankararaman, S, Fu, Q, Rohland, N, Renaud, G, Erlich, Y, Willems, T, Gallo, C, Spence, JP, Song, YS, Poletti, G, Balloux, F, van Driem, G, de Knijff, P, Romero, IG, Jha, AR, Behar, DM, Bravi, CM, Capelli, C, Hervig, T, Moreno-Estrada, A, Posukh, OL, Balanovska, E, Balanovsky, O, Karachanak-Yankova, S, Sahakyan, H, Toncheva, D, Yepiskoposyan, L, Tyler-Smith, C, Xue, Y, Abdullah, MS, Ruiz-Linares, A, Beall, CM, Di Rienzo, A, Jeong, C, Starikovskaya, EB, Metspalu, E, Parik, J, Villems, R, Henn, BM, Hodoglugil, U, Mahley, R, Sajantila, A, Stamatoyannopoulos, G, Wee, JTS, Khusainova, R, Khusnutdinova, E, Litvinov, S, Ayodo, G, Comas, D, Hammer, MF, Kivisild, T, Klitz, W, Winkler, CA, Labuda, D, Bamshad, M, Jorde, LB, Tishkoff, SA, Watkins, WS, Metspalu, M, Dryomov, S, Sukernik, R, Singh, L, Thangaraj, K, Paeaebo, S, Kelso, J, Patterson, N, Reich, D, Mallick, S, Li, H, Lipson, M, Mathieson, I, Gymrek, M, Racimo, F, Zhao, M, Chennagiri, N, Nordenfelt, S, Tandon, A, Skoglund, P, Lazaridis, I, Sankararaman, S, Fu, Q, Rohland, N, Renaud, G, Erlich, Y, Willems, T, Gallo, C, Spence, JP, Song, YS, Poletti, G, Balloux, F, van Driem, G, de Knijff, P, Romero, IG, Jha, AR, Behar, DM, Bravi, CM, Capelli, C, Hervig, T, Moreno-Estrada, A, Posukh, OL, Balanovska, E, Balanovsky, O, Karachanak-Yankova, S, Sahakyan, H, Toncheva, D, Yepiskoposyan, L, Tyler-Smith, C, Xue, Y, Abdullah, MS, Ruiz-Linares, A, Beall, CM, Di Rienzo, A, Jeong, C, Starikovskaya, EB, Metspalu, E, Parik, J, Villems, R, Henn, BM, Hodoglugil, U, Mahley, R, Sajantila, A, Stamatoyannopoulos, G, Wee, JTS, Khusainova, R, Khusnutdinova, E, Litvinov, S, Ayodo, G, Comas, D, Hammer, MF, Kivisild, T, Klitz, W, Winkler, CA, Labuda, D, Bamshad, M, Jorde, LB, Tishkoff, SA, Watkins, WS, Metspalu, M, Dryomov, S, Sukernik, R, Singh, L, Thangaraj, K, Paeaebo, S, Kelso, J, Patterson, N, and Reich, D

Abstract

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.

Published
2016

38. Population distribution and ancestry of the cancer protective MDM2 SNP285 (rs117039649)

Author

Knappskog, S., Gansmo, L. B., Dibirova, K., Metspalu, A., Ozcelik, T., Zalloua, P., Mouzaya, F., Bliznetz, E., Balanovsky, O., and Lonning, P. E.

Subjects
Mdm2, Promoter, Snp285, Polymorphism, Snp309
Abstract

Cataloged from PDF version of article. The MDM2 promoter SNP285C is located on the SNP309G allele. While SNP309G enhances Sp1 transcription factor binding and MDM2 transcription, SNP285C antagonizes Sp1 binding and reduces the risk of breast-, ovary- and endometrial cancer. Assessing SNP285 and 309 genotypes across 25 different ethnic populations (>10.000 individuals), the incidence of SNP285C was 6-8% across European populations except for Finns (1.2%) and Saami (0.3%). The incidence decreased towards the Middle-East and Eastern Russia, and SNP285C was absent among Han Chinese, Mongolians and African Americans. Interhaplotype variation analyses estimated SNP285C to have originated about 14,700 years ago (95% CI: 8,300 - 33,300). Both this estimate and the geographical distribution suggest SNP285C to have arisen after the separation between Caucasians and modern day East Asians (17,000 - 40,000 years ago). We observed a strong inverse correlation (r = -0.805; p < 0.001) between the percentage of SNP309G alleles harboring SNP285C and the MAF for SNP309G itself across different populations suggesting selection and environmental adaptation with respect to MDM2 expression in recent human evolution. In conclusion, we found SNP285C to be a pan-Caucasian variant. Ethnic variation regarding distribution of SNP285C needs to be taken into account when assessing the impact of MDM2 SNPs on cancer risk.

Published
2014

39. A recent bottleneck of Y chromosome diversity coincides with a global change in culture

Author

Karmin, M., Saag, L., Vicente, M., Wilson Sayres, M.A., Jarve, M., Talas, U.G., Rootsi, S., Ilumae, A.M., Magi, R., Mitt, M., Pagani, L., Puurand, T., Faltyskova, Z., Clemente, F., Cardona, A., Metspalu, E., Sahakyan, H., Yunusbayev, B., Hudjashov, G., DeGiorgio, M., Loogvali, E.L., Eichstaedt, C., Eelmets, M., Chaubey, G., Tambets, K., Litvinov, S., Mormina, M., Xue, Y., Ayub, Q., Zoraqi, G., Korneliussen, T.S., Akhatova, F., Lachance, J., Tishkoff, S., Momynaliev, K., Ricaut, F.X., Kusuma, P., Razafindrazaka, H., Pierron, D., Cox, M.P., Sultana, G.N., Willerslev, R., Muller, C., Westaway, M., Lambert, D., Skaro, V., Kovacevic, L., Turdikulova, S., Dalimova, D., Khusainova, R., Trofimova, N., Akhmetova, V., Khidiyatova, I., Lichman, D.V., Isakova, J., Pocheshkhova, E., Sabitov, Z., Barashkov, N.A., Nymadawa, P., Mihailov, E., Seng, J.W., Evseeva, I., Migliano, A.B., Abdullah, S., Andriadze, G., Primorac, D., Atramentova, L., Utevska, O., Yepiskoposyan, L., Marjanovic, D., Kushniarevich, A., Behar, D.M., Gilissen, C., Vissers, L., Veltman, J.A., Balanovska, E., Derenko, M., Malyarchuk, B., Metspalu, A., Fedorova, S., Eriksson, A., Manica, A., Mendez, F.L., Karafet, T.M., Veeramah, K.R., Bradman, N., Hammer, M.F., Osipova, L.P., Balanovsky, O., Khusnutdinova, E.K., Johnsen, K., Remm, M., Thomas, M.G., Tyler-Smith, C., Underhill, P.A., Willerslev, E., Nielsen, R., Metspalu, M., Villems, R., Kivisild, T., Karmin, M., Saag, L., Vicente, M., Wilson Sayres, M.A., Jarve, M., Talas, U.G., Rootsi, S., Ilumae, A.M., Magi, R., Mitt, M., Pagani, L., Puurand, T., Faltyskova, Z., Clemente, F., Cardona, A., Metspalu, E., Sahakyan, H., Yunusbayev, B., Hudjashov, G., DeGiorgio, M., Loogvali, E.L., Eichstaedt, C., Eelmets, M., Chaubey, G., Tambets, K., Litvinov, S., Mormina, M., Xue, Y., Ayub, Q., Zoraqi, G., Korneliussen, T.S., Akhatova, F., Lachance, J., Tishkoff, S., Momynaliev, K., Ricaut, F.X., Kusuma, P., Razafindrazaka, H., Pierron, D., Cox, M.P., Sultana, G.N., Willerslev, R., Muller, C., Westaway, M., Lambert, D., Skaro, V., Kovacevic, L., Turdikulova, S., Dalimova, D., Khusainova, R., Trofimova, N., Akhmetova, V., Khidiyatova, I., Lichman, D.V., Isakova, J., Pocheshkhova, E., Sabitov, Z., Barashkov, N.A., Nymadawa, P., Mihailov, E., Seng, J.W., Evseeva, I., Migliano, A.B., Abdullah, S., Andriadze, G., Primorac, D., Atramentova, L., Utevska, O., Yepiskoposyan, L., Marjanovic, D., Kushniarevich, A., Behar, D.M., Gilissen, C., Vissers, L., Veltman, J.A., Balanovska, E., Derenko, M., Malyarchuk, B., Metspalu, A., Fedorova, S., Eriksson, A., Manica, A., Mendez, F.L., Karafet, T.M., Veeramah, K.R., Bradman, N., Hammer, M.F., Osipova, L.P., Balanovsky, O., Khusnutdinova, E.K., Johnsen, K., Remm, M., Thomas, M.G., Tyler-Smith, C., Underhill, P.A., Willerslev, E., Nielsen, R., Metspalu, M., Villems, R., and Kivisild, T.

Abstract

Contains fulltext : 153022.pdf (publisher's version ) (Open Access), It is commonly thought that human genetic diversity in non-African populations was shaped primarily by an out-of-Africa dispersal 50-100 thousand yr ago (kya). Here, we present a study of 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Applying ancient DNA calibration, we date the Y-chromosomal most recent common ancestor (MRCA) in Africa at 254 (95% CI 192-307) kya and detect a cluster of major non-African founder haplogroups in a narrow time interval at 47-52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck. In contrast to demographic reconstructions based on mtDNA, we infer a second strong bottleneck in Y-chromosome lineages dating to the last 10 ky. We hypothesize that this bottleneck is caused by cultural changes affecting variance of reproductive success among males.

Published
2015

40. The GenoChip: A New Tool for Genetic Anthropology

Author

Elhaik, E, Greenspan, E, Staats, S, Krahn, T, Tyler-Smith, C, Xue, Y, Tofanelli, S, Francalacci, P, Cucca, F, Pagani, Luca, Jin, L, Li, H, Schurr, Tg, Greenspan, B, Spencer Wells, R, Acosta, O, Adhikarla, S, Adler, Cj, Balanovska, E, Balanovsky, O, Bertranpetit, J, Clarke, Ac, Comas, D, Cooper, A, Dulik, Mc, Gaieski, Jb, Ganesh Prasad AK, Haak, W, Haber, M, Kaplan, Me, Lacerda, Dr, Li, S, Martinez-Cruz, B, Matisoo-Smith, Ea, Merchant, Nc, Mitchell, Jr, Owings, Ac, Parida, L, Pitchappan, R, Platt, De, Quintana-Murci, L, Renfrew, C, Royyuru, Ak, Sandoval, Jr, Santhakumari, Av, Santos, Fr, Der Sarkissian CSI, Soodyall, S, Soria Hernanz DF, Swamikrishnan, P, Vieira, Pp, Vilar, Mg, Zalloua, Pa, and Ziegle, Js

Subjects
Letter, Anthropology, Human Migration, Population genetics, Genética de población, Ancestry-informative marker, Human genetic variation, MED/03 Genetica medica, Genética humana, DNA, Mitochondrial, Polymorphism, Single Nucleotide, Haplogroup, genetic anthropology, AimsFinder, 03 medical and health sciences, 0302 clinical medicine, Genes, Y-Linked, Human Genome Project, Genetics, Humans, Quantitative Biology - Genomics, Genographic Project, Quantitative Biology - Populations and Evolution, Genotyping, Denisovan, Antropologia, Ecology, Evolution, Behavior and Systematics, Anthropology, Cultural, History, Ancient, 030304 developmental biology, GenoChip, Oligonucleotide Array Sequence Analysis, Genomics (q-bio.GN), 0303 health sciences, Genètica humana, Genètica de poblacions, biology, BIO/18 Genetica, Populations and Evolution (q-bio.PE), population genetics, Especiación genética, biology.organism_classification, FOS: Biological sciences, haplogroups, Haplotipos, 030217 neurology & neurosurgery, Human mitochondrial DNA haplogroup
Abstract

The Genographic Project is an international effort using genetic data to chart human migratory history. The project is non-profit and non-medical, and through its Legacy Fund supports locally led efforts to preserve indigenous and traditional cultures. In its second phase, the project is focusing on markers from across the entire genome to obtain a more complete understanding of human genetic variation. Although many commercial arrays exist for genome-wide SNP genotyping, they were designed for medical genetic studies and contain medically related markers that are not appropriate for global population genetic studies. GenoChip, the Genographic Project's new genotyping array, was designed to resolve these issues and enable higher-resolution research into outstanding questions in genetic anthropology. We developed novel methods to identify AIMs and genomic regions that may be enriched with alleles shared with ancestral hominins. Overall, we collected and ascertained AIMs from over 450 populations. Containing an unprecedented number of Y-chromosomal and mtDNA SNPs and over 130,000 SNPs from the autosomes and X-chromosome, the chip was carefully vetted to avoid inclusion of medically relevant markers. The GenoChip results were successfully validated. To demonstrate its capabilities, we compared the FST distributions of GenoChip SNPs to those of two commercial arrays for three continental populations. While all arrays yielded similarly shaped (inverse J) FST distributions, the GenoChip autosomal and X-chromosomal distributions had the highest mean FST, attesting to its ability to discern subpopulations. The GenoChip is a dedicated genotyping platform for genetic anthropology and promises to be the most powerful tool available for assessing population structure and migration history., Comment: 11 pages, 5 Figures, 2 supplementary notes

Published
2013

43. Ancient human genomes suggest three ancestral populations for present-day Europeans

Author

Lazaridis, I, Patterson, N, Mittnik, A, Renaud, G, Mallick, S, Kirsanow, K, Sudmant, Ph, Schraiber, Jg, Castellano, S, Lipson, M, Berger, B, Economou, C, Bollongino, R, Fu, Q, Bos, Ki, Nordenfelt, S, Li, H, De Filippo, C, Prüfer, K, Sawyer, S, Posth, C, Haak, W, Hallgren, F, Fornander, E, Rohland, N, Delsate, D, Francken, M, Guinet, Jm, Wahl, J, Ayodo, G, Babiker, Ha, Bailliet, G, Balanovska, E, Balanovsky, O, Bedoya, G, Ben Ami, H, Bene, J, Berrada, F, Bravi, Cm, Brisighelli, Francesca, Busby, Gb, Cali, F, Churnosov, M, Cole, De, Corach, D, Damba, L, Van Driem, G, Dryomov, S, Fedorova, Sa, Gallego Romero, I, Gubina, M, Hammer, M, Henn, Bm, Hervig, T, Hodoglugil, U, Jha, Ar, Karachanak Yankova, S, Khusainova, R, Khusnutdinova, E, Kittles, R, Kivisild, T, Kučinskas, V, Kushniarevich, A, Laredj, L, Litvinov, S, Loukidis, T, Mahley, Rw, Melegh, B, Metspalu, E, Molina, J, Mountain, J, Näkkäläjärvi, K, Nesheva, D, Nyambo, T, Osipova, L, Platonov, F, Posukh, O, Romano, V, Rothhammer, F, Rudan, I, Ruizbakiev, R, Sahakyan, H, Sajantila, A, Salas, A, Starikovskaya, Eb, Tarekegn, A, Toncheva, D, Turdikulova, S, Utevska, O, Vasquez, R, Villena, M, Voevoda, M, Winkler, Ca, Yepiskoposyan, L, Zalloua, P, Zemunik, T, Cooper, A, Capelli, C, Ruiz Linares, A, Tishkoff, Sa Et Al, Brisighelli, Francesca (ORCID:0000-0001-5469-4413), Lazaridis, I, Patterson, N, Mittnik, A, Renaud, G, Mallick, S, Kirsanow, K, Sudmant, Ph, Schraiber, Jg, Castellano, S, Lipson, M, Berger, B, Economou, C, Bollongino, R, Fu, Q, Bos, Ki, Nordenfelt, S, Li, H, De Filippo, C, Prüfer, K, Sawyer, S, Posth, C, Haak, W, Hallgren, F, Fornander, E, Rohland, N, Delsate, D, Francken, M, Guinet, Jm, Wahl, J, Ayodo, G, Babiker, Ha, Bailliet, G, Balanovska, E, Balanovsky, O, Bedoya, G, Ben Ami, H, Bene, J, Berrada, F, Bravi, Cm, Brisighelli, Francesca, Busby, Gb, Cali, F, Churnosov, M, Cole, De, Corach, D, Damba, L, Van Driem, G, Dryomov, S, Fedorova, Sa, Gallego Romero, I, Gubina, M, Hammer, M, Henn, Bm, Hervig, T, Hodoglugil, U, Jha, Ar, Karachanak Yankova, S, Khusainova, R, Khusnutdinova, E, Kittles, R, Kivisild, T, Kučinskas, V, Kushniarevich, A, Laredj, L, Litvinov, S, Loukidis, T, Mahley, Rw, Melegh, B, Metspalu, E, Molina, J, Mountain, J, Näkkäläjärvi, K, Nesheva, D, Nyambo, T, Osipova, L, Platonov, F, Posukh, O, Romano, V, Rothhammer, F, Rudan, I, Ruizbakiev, R, Sahakyan, H, Sajantila, A, Salas, A, Starikovskaya, Eb, Tarekegn, A, Toncheva, D, Turdikulova, S, Utevska, O, Vasquez, R, Villena, M, Voevoda, M, Winkler, Ca, Yepiskoposyan, L, Zalloua, P, Zemunik, T, Cooper, A, Capelli, C, Ruiz Linares, A, Tishkoff, Sa Et Al, and Brisighelli, Francesca (ORCID:0000-0001-5469-4413)

Abstract

We sequenced the genomes of a ∼7,000-year-old farmer from Germany and eight ∼8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations' deep relationships and show that early European farmers had ∼44% ancestry from a 'basal Eurasian' population that split before the diversification of other non-African lineages.

Published
2014

44. The western and eastern roots of the Saami - The story of genetic 'outliers' told by mitochondrial DNA and Y chromosomes

Author

Tambets, K Rootsi, S Kivisild, T Help, H Serk, P and Loogvali, EL Tolk, HV Reidla, M Metspalu, E Pliss, L and Balanovsky, O Pshenichnov, A Balanovska, E Gubina, M and Zhadanov, S Osipova, L Damba, L Voevoda, M Kutuev, I and Bermisheva, M Khusnutdinova, E Gusar, V Grechanina, E and Parik, J Pennarun, E Richard, C Chaventre, A Moisan, JP and Barac, L Pericic, M Rudan, P Terzic, R Mikerezi, I and Krumina, A Baumanis, V Koziel, S Rickards, O De Stefano, GF Anagnou, N Pappa, KI Michalodimitrakis, E and Ferak, V Furedi, S Komel, R Beckman, L Villems, R

Abstract

The Saami are regarded as extreme genetic outliers among European populations. In this study, a high-resolution phylogenetic analysis of Saami genetic heritage was undertaken in a comprehensive context, through use of maternally inherited mitochondrial DNA ( mtDNA) and paternally inherited Y-chromosomal variation. DNA variants present in the Saami were compared with those found in Europe and Siberia, through use of both new and previously published data from 445 Saami and 17,096 western Eurasian and Siberian mtDNA samples, as well as 127 Saami and 2,840 western Eurasian and Siberian Y-chromosome samples. It was shown that the “Saami motif” variant of mtDNA haplogroup U5b is present in a large area outside Scandinavia. A detailed phylogeographic analysis of one of the predominant Saami mtDNA haplogroups, U5b1b, which also includes the lineages of the “Saami motif,” was undertaken in 31 populations. The results indicate that the origin of U5b1b, as for the other predominant Saami haplogroup, V, is most likely in western, rather than eastern, Europe. Furthermore, an additional haplogroup (H1) spread among the Saami was virtually absent in 781 Samoyed and Ob-Ugric Siberians but was present in western and central European populations. The Y-chromosomal variety in the Saami is also consistent with their European ancestry. It suggests that the large genetic separation of the Saami from other Europeans is best explained by assuming that the Saami are descendants of a narrow, distinctive subset of Europeans. In particular, no evidence of a significant directional gene flow from extant aboriginal Siberian populations into the haploid gene pools of the Saami was found.

Published
2004

45. Recombination networks as genetic markers in a human variation study of the Old World.

Author

Javed, A., Mele, M., Pybus, M., Zalloua, P., Haber, M., Comas, D., Netea, M.G., Balanovsky, O., Balanovska, E., Jin, L., Yang, Y, Arunkumar, G., Pitchappan, R., Bertranpetit, J., Calafell, F., Parida, L., Javed, A., Mele, M., Pybus, M., Zalloua, P., Haber, M., Comas, D., Netea, M.G., Balanovsky, O., Balanovska, E., Jin, L., Yang, Y, Arunkumar, G., Pitchappan, R., Bertranpetit, J., Calafell, F., and Parida, L.

Abstract

1 april 2012, Item does not contain fulltext, We have analyzed human genetic diversity in 33 Old World populations including 23 populations obtained through Genographic Project studies. A set of 1,536 SNPs in five X chromosome regions were genotyped in 1,288 individuals (mostly males). We use a novel analysis employing subARG network construction with recombining chromosomal segments. Here, a subARG is constructed independently for each of five gene-free regions across the X chromosome, and the results are aggregated across them. For PCA, MDS and ancestry inference with STRUCTURE, the subARG is processed to obtain feature vectors of samples and pairwise distances between samples. The observed population structure, estimated from the five short X chromosomal segments, supports genome-wide frequency-based analyses: African populations show higher genetic diversity, and the general trend of shared variation is seen across the globe from Africa through Middle East, Europe, Central Asia, Southeast Asia, and East Asia in broad patterns. The recombinational analysis was also compared with established methods based on SNPs and haplotypes. For haplotypes, we also employed a fixed-length approach based on information-content optimization. Our recombinational analysis suggested a southern migration route out of Africa, and it also supports a single, rapid human expansion from Africa to East Asia through South Asia.

Published
2012

46. Recombination gives a new insight in the effective population size and the history of the old world human populations.

Author

Mele, M., Javed, A., Pybus, M., Zalloua, P., Haber, M., Comas, D., Netea, M.G., Balanovsky, O., Balanovska, E., Jin, L., Yang, Y., Pitchappan, R.M., Arunkumar, G., Parida, L., Calafell, F., Bertranpetit, J., Mele, M., Javed, A., Pybus, M., Zalloua, P., Haber, M., Comas, D., Netea, M.G., Balanovsky, O., Balanovska, E., Jin, L., Yang, Y., Pitchappan, R.M., Arunkumar, G., Parida, L., Calafell, F., and Bertranpetit, J.

Abstract

01 januari 2012, Item does not contain fulltext, The information left by recombination in our genomes can be used to make inferences on our recent evolutionary history. Specifically, the number of past recombination events in a population sample is a function of its effective population size (Ne). We have applied a method, Identifying Recombination in Sequences (IRiS), to detect specific past recombination events in 30 Old World populations to infer their Ne. We have found that sub-Saharan African populations have an Ne that is approximately four times greater than those of non-African populations and that outside of Africa, South Asian populations had the largest Ne. We also observe that the patterns of recombinational diversity of these populations correlate with distance out of Africa if that distance is measured along a path crossing South Arabia. No such correlation is found through a Sinai route, suggesting that anatomically modern humans first left Africa through the Bab-el-Mandeb strait rather than through present Egypt.

Published
2012

47. Characteristics of Populations of the Russian Federation over the Panel of Fifteen Loci Used for DNA Identification and in Forensic Medical Examination

Author

Stepanov, V A, primary, Balanovsky, O P, additional, Melnikov, A V, additional, Lash-Zavada, A Yu, additional, Khar'kov, V N, additional, Tyazhelova, T V, additional, Akhmetova, V L, additional, Zhukova, O V, additional, Shneider, Yu V, additional, Shil'nikova, I N, additional, Borinskaya, S A, additional, Marusin, A V, additional, Spiridonova, M G, additional, Simonova, K V, additional, Khitrinskaya, I Yu, additional, Radzhabov, M O, additional, Romanov, A G, additional, Shtygasheva В, O V, additional, Koshel', S M, additional, Balanovskaya, E V, additional, Rybakova, A V, additional, Khusnutdinova, E K, additional, Puzyrev, V P, additional, and Yankovsky, N K, additional

Published
2011
Full Text
View/download PDF

48. Allele frequency distributions of - 174G/ C polymorphism in regulatory region of interleukin 6 gene ( IL6) in Russian and worldwide populations.

Author

Borinskaya, S., Gureev, A., Orlova, A., Sanina, E., Kim, A., Gasemianrodsari, F., Shirmanov, V., Balanovsky, O., Rebrikov, D., Koshechkin, A., and Yankovsky, N.

Subjects
GENE frequency, GENETIC polymorphisms, GENETIC regulation, INTERLEUKIN-6 genetics, POPULATION genetics, CYTOKINES
Abstract

Allele and genotype frequencies of the − 174G/ C polymorphism (rs1800795) in the regulatory region of the IL6 gene, which encode anti-inflammatory cytokine interleukin 6, were determined in seven populations representing five ethnic groups from the European part of Russia (440 individuals), as well as in small cohorts that represent populations from 24 countries of Africa and Eurasia (365 individuals). The maps of the geographic distribution of the − 174G/ C allele frequencies were constructed based on personal (22 populations) and the literature data (66 populations), and the data from dbSNP database obtained by the HapMap project (10 populations). The frequency of the − 174G allele varied from 45 to 100% and was characterized by nonrandom geographic distribution. These data could reflect the adaptive load of the alleles examined, which was different in different regions of the world. It is suggested that the level of pathogen prevalence is one of the environmental factors that determine different adaptive values of the IL6*-174G/ C alleles. This suggestion is supported by a positive correlation between the − 174G allele frequency and level of pathogen prevalence calculated based on historical data ( R = 0.768; p < 0.0001). [ABSTRACT FROM AUTHOR]

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results