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The goal of this study is to show two new clustering and visualising techniques developed to find the most typical clusters of 18-dimensional Y chromosomal haplogroup frequency distributions of 90 Western Eurasian populations. The first technique called "self-organizing cloud (SOC)" is a vector-based self-learning method derived from the Self Organising Map and non-metric Multidimensional Scaling algorithms. The second technique is a new probabilistic method called the "maximal relation probability" (MRP) algorithm, based on a probability function having its local maximal values just in the condensation centres of the input data. This function is calculated immediately from the distance matrix of the data and can be interpreted as the probability that a given element of the database has a real genetic relation with at least one of the remaining elements. We tested these two new methods by comparing their results to both each other and the k-medoids algorithm. By means of these new algorithms, we determined 10 clusters of populations based on the 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.

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 (

According to written sources, Roma (Romanies, Gypsies) arrived in the Balkans around 1,000 years ago from India and have subsequently spread through several parts of Europe. Genetic data, particularly from the Y chromosome, have supported this model, and can potentially refine it. We now provide an analysis of Y-chromosomal markers from five Roma and two non-Roma populations (N 5 787) in order to investigate the genetic relatedness of the Roma popula- tion groups to one another, and to gain further under- standing of their likely Indian origins, the genetic contri- bution of non-Roma males to the Roma populations, and the early history of their splits and migrations in Europe. The two main sources of the Roma paternal gene pool were identified as South Asian and European. The reduced diversity and expansion of H1a-M82 lineages in all Roma groups imply shared descent from a single paternal ancestor in the Indian subcontinent. The Roma paternal gene pool also contains a specific subset of E1b1b1a-M78 and J2a2-M67 lineages, implying admixture during early settlement in the Balkans and the subsequent influx into the Carpathian Basin. Additional admixture, evident in the low and moderate frequencies of typical European haplogroups I1-M253, I2a-P37.2, I2b-M223, R1b1-P25, and R1a1- M198, has occurred in a more population-specific manner. Am J Phys Anthropol 000:000-000, 2011. V C 2011 Wiley-Liss, Inc.

Haplotype frequencies for 11 Y-STR markers (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS385, DYS437, DYS438 and DYS439) in a Romani population (n=63) from Slovakia, Jats of Haryana (n=84) and Jat Sikhs (n=80) from India were determined. The Slovakian Romani, the Haryana and Sikh populations were endogamous based on their unique haplotype ratio and haplotype diversity values, although the Sikh population appeared to be more diverse. AMOVA revealed non-significant differences between the Romanies and significant differences with non-Romani populations. The Macedonian Romani population differed from all Romani populations examined. Frequent haplotypes observed in Romani populations were sporadic in northwest Indian populations. Thirteen out of 316 populations worldwide were found to share the six most frequent haplotypes of the Slovakian Romanies when the screening conditions were narrowed based on the population size to be over 40, the occurrence of the haplotypes was more than one and the sum frequencies of the most frequent haplotypes was at least 0.02. The most common haplotypes were also observed in other Romani groups. When searching with two Indian (Malbar and Malaysian Indian) most frequent haplotypes under the same conditions matches could be detected in all Romani populations except for the Macedonian Romanies. The search with the Jat Sikhs and Jats of Haryana most frequent haplotypes resulted no matches in Romani populations.

Testing of thirty autosomal single nucleotide polymorphisms were performed in 218 independent Hungarian male and female samples. We applied this system to 24 paternity testing cases including 14 inclusions and 10 exclusions.

Testing of 49 Y-SNP loci with TaqMan assays were completed in 119 independent Hungarian, 61 Hungarian Romani and 29 Tiszavasvari Hungarian Romani male samples. Haplogroup diversity values were calculated and the populations were compared to each other with G-test. The two Romani populations were not significantly different from each other, when their haplogroup frequencies were compared ( p =0.01). The Hungarian population was significantly different from both Romani populations. Genetic distances of the above populations to South Indian, Northwest Indian (Punjab) and East Asian populations were calculated based on haplogroup frequencies with AMOVA implemented in Arlequin2.0. The major Hungarian Y chromosomal haplogroups were R1a1-M198, R1b-P25 and I1b-P37. In the Hungarian Romani population the most frequent haplogroups were H1-M82, R1a1-M198 and J2f-M67, while in the Tiszavasvari Hungarian Romani population also the H1-M82 haplogroup was the most frequent with the frequency as high as 60%. Preliminary haplogroup data of the Malaysian Indian population indicate that the Romanies might come from South India, since one of their major haplogroups was H1-M82 with the frequency of 19.7%, and based on haplogroup frequencies the genetic distances between the Malaysian Indian and the Romani populations were similar to that of the Hungarian population, regardless of the large geographic distance.

Romanies constitute the largest minority group belonging to different subgroups in Hungary. Vlax Romanies are one of these Romani subgroups. The Gypsies came to Hungary from the Balkans in two large migrations. The Carpathian Romanies arrived in the 15th century and the Vlax Romanies came in the 19th century. The Carpathian Gypsies speak Hungarian and the Vlax Romanies speak Hungarian and Romani languages. Only a limited number of genetic studies of Y-chromosomal haplotypes/haplogroups have been done before, moreover most studies did not contain information regarding the investigated Roma populations which subgroups belong to. In the present study, we analyzed a wide set of Y-chromosomal markers to do comparable studies of the Vlax Roma in eastern Hungarian regions. The results can be compared in the context of previously published data on other Romani groups, Indian and Hungarian reference populations. Haplogroups H1a-M82 and J2a2-M67 were most common in the investigated population groups. A median-joining network of haplogroup H1a-M82 has demonstrated the sharing of identical Indian specific Y-chromosomal lineages between all Romani populations including Malaysian Indians as well as the Vlax Romanies. This common lineage of haplogroup H1a-M82 represents a common descent from a single ancestor provides a strong genetic link to the ancestral geographical origin of the proto-Gypsies. The detected haplogroups in the Vlax Romani population groups can be classified into two different Y-chromosomal lineages based on their putative origin. These lineages include ancestral Indian (H1a-M82), present-day Eurasian (J2a2-M67, J2*-M172, E1b1b1a-M78, I1-M253, R1a1-M198 and R1b1-P25) Y-chromosome lineages. Presence of these lineages in the paternal gene pool of the Roma people is illustrative of the Gypsy migration route from India through the Balkan to the Carpathian Basin.

The Madjars are a previously unstudied population from Kazakhstan who practice a form of local exogamy in which wives are brought in from neighboring tribes, but husbands are not, so the paternal lineages remain genetically isolated within the population. Their name bears a striking resemblance to the Magyars who have inhabited Hungary for over a millennium, but whose previous history is poorly understood. We have now carried out a genetic analysis of the population structure and relationships of the Madjars, and in particular have sought to test whether or not they show a genetic link with the Magyars. We concentrated on paternal lineages because of their isolation within the Madjars and sampled males representing all extant male lineages unrelated for more than eight generations (n = 45) in the Torgay area of Kazakhstan. The Madjars show evidence of extensive genetic drift, with 24/45 carrying the same 12-STR haplotype within haplogroup G. Genetic distances based on haplogroup frequencies were used to compare the Madjars with 37 other populations and showed that they were closest to the Hungarian population rather than their geographical neighbors. Although this finding could result from chance, it is striking and suggests that there could have been genetic contact between the ancestors of the Madjars and Magyars, and thus that modern Hungarians may trace their ancestry to Central Asia, instead of the Eastern Uralic region as previously thought.

49 Y-chromosomal single nucleotide polymorphisms (SNPs) with TaqMan assay and 11 Y-chromosomal STR loci were tested in 215 independent Hungarian male samples. Genetic distances to 23 other populations were calculated based on haplogroup frequencies with AMOVA implemented in Arlequin2.0. Based on distances phylogenetic tree was constructed with Neighbor-joining method using Phylip 3.66. Haplotype and haplogroup diversity values were calculated.

The X chromosomal STR markers DXS10135 and DXS8378 in linkage group 1, DXS7132 and DXS10074 in linkage group 2, HPRTB and DXS10101 in linkage group 3, and DXS10134 and DXS7423 in linkage group 4 were studied in the Hungarian population. After genotyping unrelated men (219) and women (165), forensic efficiency parameters were calculated. Deviations from Hardy-Weinberg equilibrium could not be detected. There were several microvariant and rare alleles were sequenced: four in locus DXS10135 (alleles 17.1, 18.1, 20.1 and 26.1), one in locus DXS10074 (alleles 11), three in locus DXS10101 (alleles 26, 34.2 and 35) and five in locus DXS10134 (alleles 35.3, 37.2, 38.2, 39.2, 41).

DXS8378, DXS7132, HPRTB, and DXS7423 microsatellite markers located in four different X-chromosomal linkage groups were studied in the Hungarian population. After genotyping unrelated men (219) and women (165), forensic efficiency parameters showing that the four X-linked short tandem repeats are informative for forensic applications were calculated. With fragment and sequence analysis, one microvariant allele (11.2) was identified in the HPRTB locus. A deviation from the Hardy-Weinberg equilibrium could not be detected. Investigations of 96 father-child meioses revealed one mutation in the DXS7132 locus. For comparison of 22 different populations, G-tests were carried out.

Martínez-Cruz, Begoña et al., The Roma, also known as ‘Gypsies’, represent the largest and the most widespread ethnic minority of Europe. There is increasing evidence, based on linguistic, anthropological and genetic data, to suggest that they originated from the Indian subcontinent, with subsequent bottlenecks and undetermined gene flow from/to hosting populations during their diaspora. Further support comes from the presence of Indian uniparentally inherited lineages, such as mitochondrial DNA M and Y-chromosome H haplogroups, in a significant number of Roma individuals. However, the limited resolution of most genetic studies so far, together with the restriction of the samples used, have prevented the detection of other non-Indian founder lineages that might have been present in the proto-Roma population. We performed a high-resolution study of the uniparental genomes of 753 Roma and 984 non-Roma hosting European individuals. Roma groups show lower genetic diversity and high heterogeneity compared with non-Roma samples as a result of lower effective population size and extensive drift, consistent with a series of bottlenecks during their diaspora. We found a set of founder lineages, present in the Roma and virtually absent in the non-Roma, for the maternal (H7, J1b3, J1c1, M18, M35b, M5a1, U3, and X2d) and paternal (I-P259, J-M92, and J-M67) genomes. This lineage classification allows us to identify extensive gene flow from non-Roma to Roma groups, whereas the opposite pattern, although not negligible, is substantially lower (up to 6.3%). Finally, the exact haplotype matching analysis of both uniparental lineages consistently points to a Northwestern origin of the proto-Roma population within the Indian subcontinent., This study was partly supported by the Spanish Ministerio de Economía y Competitividad Grant CGL2013-44351-P.