Monday, January 29, 2024

Shahr-e-Sokhte 2 samples and nearness

 




Finding closer to the Shahr-e-Sokhte2 samples. Looking at a generic PCA of my FTDNA sample and the Iyer samples and the Patel sample, these look closest to the Shahr-e-Sokhte2 samples and mine looks closest to the Shahr-e-Sokhte3 sample.



Now doing one on one against the Iyer-1-14 sample that is closest to the Shahr-e-Sokhte2 samples with my Dante sample shows mine Dante sample is 1.22 more nearby than the Iyer-1-14 sample.



running NMONTE on my and Iyer-1-14 sample shows it prefers more Yana and Ust-Ishim while mine prefers little bit Hoabinh but overall higher Shahr-e-Sokhte2


Checking the actual SNPs matched shows my sample matches close to 1024 SNPs on Shahr-e-Sokhte2 I11456 sample and chunks of > 20cM segments


Similarly on Shahr-e-Sokhte3 I8728 sample My Dante sample matches 269SNP


The overall Shahr-e-Sokhte 2 matches on my file are atleast 5-10% more than the nearest Indian samples.


The Bronze age time line on my FTDNA+Myheritage sample shows 20+ cM chunks on Shahr-e-Sokhte2 and 2.27cM on Helmand samples. The ancient Greek BA samples (probably outliers) show big chunks of 20, 30 and 40cMs on many samples. There is also matches with Gonur samples, BA Bulgaria, Ebla and Anatolia BA, Copper age Italy etc...



Running few samples showing current day mixtures, shows following. The Punjabi Lahore is high among Nambudri, Iyer samples and Kamma. Velamas have Punjabi Lahore but high of Brahmin mixed input from TN. Reddy have Pallan and Patel like mix. 


adding additional Kerala samples decreases the Punjabi Lahore of Iyers but Nambudri and Kamma stays same




Thursday, September 21, 2023

West Ugric ancient language family

 The Carian alphabet is a script evolutionary missing link that was conjectured by Revesz [32] to have existed somewhere in western Anatolia as a common ancestor of the Cypriot syllabary and the Old Hungarian alphabet. This situation is illustrated in Fig. 1






Minoan is an Ugric Language In this section we consider the relationship between the Minoan language as recorded in Linear A [14, 41] and Cretan Hieroglyphs [26, 42] and the Uralic language family. The Uralic language family consists of a Finno-Ugric branch and a Samoyedic branch. The Finno-Ugric branch is further divided into a Finno-Permic and an Ugric branch [18]. The Ugric branch is composed of the Hungarian, Khanty and Mansi languages [18]. Linguists have studied the Uralic languages for over two hundred years and identified sets of words that characterize the nodes of this family tree (see Honti [17]). Minoan, the language of Linear A, is an unknown language. Nevertheless, ancient Greek preserves many words from the Minoan language. Beekes [4] collected in a dictionary all the non-Indo-European vocabulary of ancient Greek. While Beekes [4] often identifies the non-Indo-European words of ancient Greek as having unknown origin, we have found corresponding cognate words within the Uralic language family for many of them. We give some examples of these cognate pairs in Tables 7, 8 and 9, which show some apparent cognate ancient Greek and Uralic, Finno-Ugric and Ugric word pairs. In Tables 7, 8, and 9 the similar consonant sounds are highlighted by red, inserted glide consonants are highlighted by blue, and omitted sounds are indicated by underscores. The Hungarian words and their cognates in Tables 7 and 8 are based on the Hungarian etymological dictionary of Zaicz [43]. The Hungarian words and most of their Khanty and Mansi cognates in Table 9 are based on Honti [17]


The ancient Greek words are from the ancient Greek etymological dictionary of Beekes [3, 4]. The associations of the ancient Greek and the Uralic cognates are our work. There were some earlier dictionaries of Greek and Hungarian by J. Aczél in 1926 and more recently by Varga [37], but they completely ignored Finno-Ugric linguistics. Their dictionaries lack any etymological considerations and list words that are not true cognates but medieval or later borrowings. Their dictionaries also contain several false cognates. Nevertheless, they deserve some credit for bringing the issue of larger than expected similarities between the Greek and the Hungarian vocabularies to attention. Tables 7, 8 and 9 have some striking implications. Clearly, the Ugric word cognates are the most remarkable because the Ugric words are unique to the Ugric branch according to Honti [17]. While there are strong Greek and Hungarian connections because Greek missionaries and merchants frequently visited Hungary, there is no similar relationship between Greek and Khanty or Mansi. Hence we have to suppose that Minoan is a previously overlooked Ugric language. The only logical assumption can be that Minoan separated from the Ugric branch and came to Crete before the arrival of proto-Greek speakers sometime around 1450 BC, when the Linear B supplanted the Linear A writing according to the archeological record. The author’s previous decipherments of the Phaistos Disk [30] and Cretan Hieroglyph inscriptions [31] also suggest that the Minoan language was Finno-Ugric. That proposal was received with some skepticism on a geographic ground because it was difficult to imagine how the Minoans could have arrived to Crete from any previously proposed Finno-Ugric homeland. This situation has led us to the consideration of the Hattic language of Anatolia, as described below.





Hattic is an Ugric Language Usually a language family spreads over a connected area. Hence it looks strange that Minoan culture existed primarily in Crete, while Khanty and Mansi live on the eastern side of the Ural Mountains. However, the gap between these two areas can be explained if Minoans migrated to Crete from the north, probably the eastern or northern costal areas of the Black Sea via Anatolia, that is, present day Turkey. If there was such a migration through Turkey, then it also had to occur in very ancient times. According to archeologists in those ancient times, the Hattic culture occupied most of northern and central Turkey [29]. This naturally raises the question whether Hattic is also related to Minoan and whether it could also be an Ugric language. In this section, we consider this issue because if there is a relation between Minoan and Hattic, then Hattic could also help to reconstruct the Minoan language. Linguists generally consider Hattic to be an language isolate. The only exception that we are aware of is that recently, Alexey Kassian [29] suggested some of the following language similarities between Hattic and the Yeniseian languages, Ket and Kott  

from


Establishing the West-Ugric Language Family with Minoan, Hattic and Hungarian by a Decipherment of Linear A PETER Z. REVESZ Department of Computer Science and Engineering University of Nebraska-Lincoln Lincoln, NE 68588-0115 USA revesz@cse.unl.edu, cse.unl.edu/~revesz/

www.researchgate.net/publication/333816923_Establishing_the_West-Ugric_Language_Family_with_Minoan_Hattic_and_Hungarian_by_a_Decipherment_of_Linear_A



This old language family might have had some input into Dravidian based on analysis by the same author and some influence on Sumerian. The existence of words in Dravidian probably from LBA due to ocean trade etc.. might have had a massive influence on Dravidian people 


WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402

Volume 16, 2019

Sumerian Contains Dravidian and Uralic Substrates Associated with the Emegir and Emesal Dialects

Author: Peter Z. Revesz

Abstract: Data mining the Sumerian vocabulary reveals a dichotomy of the cognate associations of the Emeĝir and the Emesal dialects, with the former having mostly Dravidian and the later mostly Uralic cognates, indicating that Sumerian arose by the combination of two languages from those language families. The data mining also reveals a distribution pattern of Proto-Uralic, Proto-Finno-Ugric, Proto-Ugric and Proto-Hungarian cognates that indicates that Sumerian is farther than Minoan from Hungarian, although all are West-Ugric.


Dr Peter Z Revesz also published another datamining paper that showed Sumerian is the main language influence into Minoan and later Uralic and Hungarian. Also Dravidian shares some input from these too.


It is massive coincidence since I share the West Ugric lactose persistence and also some ancient Greek/Minoan chunks of DNA not found widely in the present Greeks

Thursday, September 14, 2023

G25 Simple Analysis of South Indian castes

 Our aim is to provide a simple analysis that uses the existing public aDNA. For that source I have used the 

Russia_Srubnaya:I0232
Russia_Srubnaya:I0234
Russia_Srubnaya:I0235
Russia_Srubnaya:I0358
Russia_Srubnaya:I0359
Russia_Srubnaya:I0361
Russia_Srubnaya:I0422
Russia_Srubnaya:I0423
Russia_Srubnaya:I0424
Russia_Srubnaya:I0430
Russia_Srubnaya:I0431
Iran_ShahrISokhta_BA2:I8728_enhanced
Saharawi:SAH10
Saharawi:SAH12
Saharawi:SAH13
Saharawi:SAH14
Saharawi:SAH18
Saharawi:SAH2
Saharawi:SAH21
Saharawi:SAH22
Saharawi:SAH24
Saharawi:SAH27
Saharawi:SAH3
Saharawi:SAH31
Saharawi:SAH34
Saharawi:SAH40
Saharawi:SAH41
Saharawi:SAH44
Saharawi:SAH48
Saharawi:SAH49
Saharawi:SAH58
Saharawi:SAH59
Saharawi:SAH6,
Saharawi:SAH7
Saharawi:SAH8
Saharawi:SAH9
Uzbekistan_Bustan_Eneolithic:I11028
Poland_Viking.SG:VK154_noUDG.SG
Poland_Viking.SG:VK156_noUDG.SG
Poland_Viking.SG:VK157_noUDG.SG
Poland_Viking.SG:VK212_noUDG.SG
Poland_Viking.SG:VK494_noUDG.SG
Russia_Steppe_Maikop_o:IV3002
Russia_Steppe_Maikop_o:SA6013
Russia_Steppe_Maikop_o:AY2001
Russia_Steppe_Maikop_o:MK5005.C0101
I have used the South Indian Brahmin and Agri castes from the latest Eurogenes spreadsheet and ran the analysis





The following shows that the Brahmin samples have a 10-20% pull towards Srubna and Steppe Maikop, Whereas certain other group such as Myself and Nambudri Brahmins and few Telugu Brahmins and includes one Vellalar have close to 10% towards Polish Viking group. Also Brahmins have 5-10% pull towards North African Saharawi. There is Mesolithic part which is the excess on top of Shahr-e-Sokhte 8728 that shows up in few Vellalars.

Tuesday, September 12, 2023

Big impacts of H-M82 from Persian Greek wars of 5th Cen BCE

 The discovery of H-M82 samples in the Bronze Age (2000-3000BCE) Indus Valley Periphery cities of Shahr-e-Sokhte and Gonur which are within the sphere of ancient Persian Influence was probably shattered when Achaemenid rulers (705-330 b.c.e.) took over these cities and destroyed them and created their own rural form of society and iron based culture. These thriving cities were a urban oasis for many millennia harboring diverse population. Destruction of such huge cities caused these Indus periphery population to move into India and other places until Greek armies took over these ancient cities hundred years later.

"In 520 b.c.e., after Darius had reunited dissident factions in Persia, Darius commissioned a massive trilingual inscription to commemorate his triumph. It still stands today on a cliff at Bisitun, high above the road from Babylon to Ecbatana (now Hamadan, Iran), one of the ancient capitals of Persia. The list of subject provinces at the end includes Gandhara as the easternmost province. The inscription carved to commemorate Darius’s building of a wall around Persepolis in 518 b.c.e. contains Gandhara and a new eastern province, Hindush. This province, whose name reproduces the Persian pronunciation of “Indus” (from which derives the word “Hindu”), must have been acquired sometime between 520 and 518 b.c.e.

A book titled Periplus (voyage around by sea) written by Scylax, a member of Darius’s exploratory expedition down the Indus River, became the foundation for two new genres of Greek writing, geography and ethnography. The book influenced all later Greek historians, including Herodotus, and through them later historical writing. It remained the source for all Greek knowledge about India until the time of Alexander the Great."

The H-M82 branch probably got split into multiple branches during this time of major wars. 


A look at the minimum spanning tree of the PCA component 1 and 2 of the SNPs of the H-M82 in the FTDNA database shows that there are deep divergences with samples from Turkey, Israel, Arabia, Romani, Kashmir, Gangetic plains, Tamils forming major nodes. The approximate time of divergence is probably 2500 years to 1500 years. These are the time of the Persian and Greek occupation of the cities around Indus Valley. The split of some these ancient individuals into Turkey, Arabia and Israel could be explained by Greek occupation and movement of these people along with the Greek armies during that time. The further split of Romani after the fall of the Greek cities in Medieval times probably caused the groups supporting the Greeks to move into Europe as Romanis.




Saturday, September 2, 2023

C677T mutation of MTHFR gene

 People with MTHFR mutation have elevated homocysteine levels. 

The mutations can lead to high levels of homocysteine in the blood, which may contribute to several health conditions, including:


Mutations in the MTHFR gene can affect the body’s ability to process amino acids — namely, homocysteine — which can lead to some adverse health outcomes.

Conditions that researchers have associated with MTHFR gene mutations include:

  • homocysteinemia, which is the term for abnormally high levels of homocysteine in the blood or urine
  • ataxia, which is a neurological condition that affects coordination
  • peripheral neuropathy, which is a neurological condition that damages the nerves
  • microcephaly, which is a condition present at birth in which the head is smaller than usual
  • scoliosis, which refers to an abnormal curvature of the spine
  • anemia, which means that there is a lack of healthy red blood cells in the body
  • cardiovascular diseases, such as blood clotsstroke, and heart attack
  • mental health conditions, such as depression, schizophrenia, Alzheimer
  • behavior disorders, such as attention deficit hyperactivity disorder
  • recurrent pregnancy loss
  • myocardial infraction

677C>T mutation (rs1801133)  and A1298C>T mutation are the major MTHFR gene mutations that cause these issue. The below map shows the distribution of these mutations world wide. As you can see the mutations values are very high (50+%) among certain Mexican, Tuscans, Bosnian, Czechs, Ukrainian, Norwegian, Swedish, certain Chinese and Japanese population world wide. 



certain American Indian groups had very high percent of these mutations making them high susceptible to the different health conditions.



 Remarkably, the frequency of the 677T in Mexican individuals and particularly in MA people, was the highest worldwide. In contrast, the frequency of the 1298C risk allele in Mexicans was the lowest in the world. In addition, the frequency of 677T allele showed an increasing gradient from northern to southern Mexico in both populations; while the 1298C allele frequency showed the opposite gradient (Fig 3). This finding demonstrates the great ethnic diversity and heterogeneity of the genetic background in the country. Consistent with previous studies [7, 8, 13, 16], our findings suggest that one of the major contributions of the 677T allele in MEZ was the Indian admixture; while, the 1298C allele is mainly derived from European genomes. Some ethnic groups had the highest frequencies in the country for the 677T allele. Mocho, Kaqchiquel, and Chuj, belonging to the Mayan linguistic family inhabiting the SE region, had frequencies >80%, and Mazateco, Mixteco, Zapoteco, Totonaco, and Mazahua from the S and CE regions had frequencies >70% (Fig 1). Notably, some ethnic groups showed particularities; for example, the Seris (N), Pame (CE), and Huave (S) had lower 677T allele frequencies than other groups that co-inhabited the same regions (13% vs. 32–47%; 35% vs. 57–74%; and 33% vs. 59–81%, respectively) (Fig 1). Also, we found seven ethnic groups that were monomorphic for the A allele of the A1298C polymorphism (Seri, Pame, Chuj, Kanjobal, Mocho, Mazahua, and Zapoteco) (Fig 2). In contrast to the 677T allele, the MA groups from the N (32–47%), with the exception of the Seris, had the highest 1298C allele frequencies (11–22%). These findings may reflect the particular features and history of migration and isolation throughout the centuries of each ethnic group, including the 5 Nahuatl groups, where heterogeneity was also observed among them.



Among Jewish, the frequency of the C677T MTHFR mutation in healthy Israeli ethnic groups. The frequency of the mutation was determined in 897 young healthy Jewish and Muslim Arab Israelis of eight different ethnic groups. Marked ethnic differences in the frequency of mutant homozygotes were found, ranging from 2% in Yemenite Jews, 4% in Sephardic Jews, 9% in Oriental Jews, 10% in Muslim Arabs, 16% in North African Jews, and 19% in Ashkenazi Jews. The frequency of mutant homozygotes was significantly higher in Ashkenazi Jews compared to Yemenites Oriental Jews, Sephardic Jews, and Muslim Arabs (χ2 = 12.35 p < 0.001, χ2 = 8.17 p = 0.004, χ2 = 6.04 p = 0.01, χ2 = 6.54 p = 0.01, respectively)

Among Arabs, significant differences in groups such as Lebanon Vs Bahrain are noticed. The C677T mutation was present in 169/408 Lebanese and 30/152 Bahraini participants, giving an overall carrier frequency of 41.4% for Lebanese and 19.7% for Bahraini participants [P < 0.001; odds ratio (OR) = 2.83; 95% confidence interval (CI) 1.81, 4.42]. Of the carriers, 159/408 (38.97%) Lebanese and 26/152 (17.11%) Bahraini carriers were heterozygotes (OR = 3.03; 95% CI 1.92, 5.00), while 10/408 (2.45%) Lebanese and 4/152 (2.63%) Bahraini carriers were in the homozygous state (OR = 1.25; 95% CI 0.39, 4.00) . No difference in the MTHFR C677T mutation frequency was seen with respect to gender.

In Iran, The prevalence of MTHFR (C677T) mutation was 17.9% of which 7.1% had the TT mutant allele in homozygous and 10.8% had CT allele in heterozygous state.

In Turkey, a study showed a genotypic distribution CC: CT: TT = 40.0%: 47.3%: 12.7% in 243 coronary patients. In a Chinese study, the genotypic distribution in 106 patients was CC: CT: TT = 63.8%: 25.7%: 10.5%. In a Tunisian study the genotypic distribution in patients was respectively CC: CT: TT = 42.2%: 38.9%: 18.9%. A Tunisian study of 185 apparently healthy subjects in 2005 showed an allele frequency of 17.8% and a genotypic frequency of 5.4%

Among South Asians, T-allele frequency for C677T mutation of MTHFR gene in the South Indian population (0.10) established by this study is lower compared to UK (0.186) and USA (0.322) and much higher when compared to Sri Lanka (0.049)12 . Similar findings were observed among case-control studies conducted in Mumbai and Pune. This shows certain urban groups in India harbor very high C677T mutations making them susceptible to different health conditions. There is no big study to find out more on these. Given high ANE based risk for this gene no wonder the newer groups who came post MLBA might have these higher risks from the mutations.

One of the Indian studies showed that Women have higher C677T mutations in India than Male. Overall Indian percentage is less compared to other major groups in China, Japan, Mexico, Peru, Italy, Bosnia, Scandinavia, Ukraine etc... However Indian probably harbor more localized such mutations in certain urban places like Pune, Mumbai, Chennai, Delhi etc... which requires more investigation and remedies


That probably shows that the Indian mtDNA has more ANE and UP based origin. However the deep Indian HGs like H and F are probable low on this gene and so low on such risk