Computer-aided comparison of folk music from different nations is one of the newest research areas. We were intrigued to have identified some important similarities between phylogenetic studies and modern folk music. First of all, both of them use similar concepts and representation tools such as multidimensional scaling for modelling relationship between populations. This gave us the idea to investigate whether these connections are merely accidental or if they mirror population migrations from the past. We raised the question; does the complex structure of musical connections display a clear picture and can this system be interpreted by the genetic analysis? This study is the first to systematically investigate the incidental genetic background of the folk music context between different populations. Paternal (42 populations) and maternal lineages (56 populations) were compared based on Fst genetic distances of the Y chromosomal and mtDNA haplogroup frequencies. To test this hypothesis, the corresponding musical cultures were also compared using an automatic overlap analysis of parallel melody styles for 31 Eurasian nations. We found that close musical relations of populations indicate close genetic distances (<0.05) with a probability of 82%. It was observed that there is a significant correlation between population genetics and folk music; maternal lineages have a more important role in folk music traditions than paternal lineages. Furthermore, the combination of these disciplines establishing a new interdisciplinary research field of "music-genetics" can be an efficient tool to get a more comprehensive picture on the complex behaviour of populations in prehistoric time.
Genetic studies noted that the Hungarian Y-chromosomal gene pool significantly differs from other Uralic-speaking populations. Hungarians show very limited or no presence of haplogroup N-Tat, which is frequent among other Uralic-speaking populations. We proposed that some genetic links need to be observed between the linguistically related Hungarian and Mansi populations.This is the first attempt to divide haplogroup N-Tat into subhaplogroups by testing new downstream SNP markers L708 and L1034. Sixty Northern Mansi samples were collected in Western Siberia and genotyped for Y-chromosomal haplotypes and haplogroups. We found 14 Mansi and 92 N-Tat samples from 7 populations. Comparative results showed that all N-Tat samples carried the N-L708 mutation. Some Hungarian, Sekler, and Uzbek samples were L1034 SNP positive, while all Mongolians, Buryats, Khanty, Finnish, and Roma samples yielded a negative result for this marker. Based on the above, L1034 marker seems to be a subgroup of N-Tat, which is typical for Mansi and Hungarian-speaking ethnic groups so far. Based on our time to most recent common ancestor data, the L1034 marker arose 2,500 years before present. The overall frequency of the L1034 is very low among the analyzed populations, thus it does not necessarily mean that proto-Hungarians and Mansi descend from common ancestors. It does provide, however, a limited genetic link supporting language contact. Both Hungarians and Mansi have much more complex genetic population history than the traditional tree-based linguistic model would suggest.
Hungarians who live in Central Europe today are one of the westernmost Uralic speakers. Despite of the proposed Volga-Ural/West Siberian roots of the Hungarian language, the present-day Hungarian gene pool is highly similar to that of the surrounding Indo-European speaking populations. However, a limited portion of specific Y-chromosomal lineages from haplogroup N, sometimes associated with the spread of Uralic languages, link modern Hungarians with populations living close to the Ural Mountain range on the border of Europe and Asia. Here we investigate the paternal genetic connection between these spatially separated populations. We reconstruct the phylogeny of N3a4-Z1936 clade by using 33 high-coverage Y-chromosomal sequences and estimate the coalescent times of its sub-clades. We genotype close to 5000 samples from 46 Eurasian populations to show the presence of N3a4-B539 lineages among Hungarians and in the populations from Ural Mountain region, including Ob-Ugric-speakers from West Siberia who are geographically distant but linguistically closest to Hungarians. This sub-clade splits from its sister-branch N3a4-B535, frequent today among Northeast European Uralic speakers, 4000–5000 ya, which is in the time-frame of the proposed divergence of Ugric languages.
Haplogroup R1a1-M198 is a major clade of Y chromosomal haplogroups which is distributed all across Eurasia. To this date, many efforts have been made to identify large SNP-based subgroups and migration patterns of this haplogroup. The origin and spread of R1a1 chromosomes in Eurasia has, however, remained unknown due to the lack of downstream SNPs within the R1a1 haplogroup. Since the discovery of R1a1-M458, this is the first scientific attempt to divide haplogroup R1a1-M198 into multiple SNP-based sub-haplogroups. We have genotyped 217 R1a1-M198 samples from seven different population groups at M458, as well as the Z280 and Z93 SNPs recently identified from the "1000 Genomes Project". The two additional binary markers present an effective tool because now more than 98% of the samples analyzed assign to one of the three sub-haplogroups. R1a1-M458 and R1a1-Z280 were typical for the Hungarian population groups, whereas R1a1-Z93 was typical for Malaysian Indians and the Hungarian Roma. Inner and Central Asia is an overlap zone for the R1a1-Z280 and R1a1-Z93 lineages. This pattern implies that an early differentiation zone of R1a1-M198 conceivably occurred somewhere within the Eurasian Steppes or the Middle East and Caucasus region as they lie between South Asia and Eastern Europe. The detection of the Z93 paternal genetic imprint in the Hungarian Roma gene pool is consistent with South Asian ancestry and amends the view that H1a-M82 is their only discernible paternal lineage of Indian heritage.
similarity of haplogroup composition. The results obtained represented a genetically, geographically and historically well-interpretable picture of 10 genetic clusters of populations mirroring the early spread of populations from the Fertile Crescent to the Caucasus, Central Asia, Arabia and Southeast Europe. The results show that a parallel clustering of populations using SOC and MRP methods can be an efficient tool for studying the demographic history of populations sharing common genetic footprints.
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