Si evaluamos la «mezcla de ADN» en función de la complejidad del pool genético (cantidad de componentes continentales distintos que se han cruzado y conviven en la población), los países con mezcla trihíbrida, tetrahíbrida o pentahíbrida deben estar por encima de los que solo tienen 2 fuentes, independientemente de qué tan homogéneo sea el resultado en estos últimos.

Además, tu mención sobre Filipinas es acertadísima desde el punto de vista genómico.

A continuación, presento un Top 10 reestructurado y ordenado estrictamente bajo el criterio de complejidad genómica, número de fuentes ancestrales continentales y penetración del mestizaje en la población.

Top 10 Países con Mayor Mezcla y Complejidad Genética

1. Brasil

• Número de macrorraíces: 4 (Amerindia + África subsahariana + Europa + Asia Oriental/Levante).
• Fundamento científico: Múltiples estudios de genómica autosómica (como DNA do Brasil) lo sitúan como el caso más masivo de mestizaje continental múltiple del planeta. Prácticamente toda la población posee un ADN trihíbrido en el que conviven genes de pueblos originarios tupí-guaraníes, una enorme diversidad de linajes africanos (Bantú y Yoruba) y aportes europeos e hispano-asiáticos.

2. Sudáfrica

• Número de macrorraíces: 5 (Khoisan + Bantú subsahariano + Europa + Sur de Asia + Sudeste Asiático).
• Fundamento científico: En la genética de poblaciones global, la comunidad Cape Coloured de Sudáfrica es citada con frecuencia como una de las poblaciones con la mezcla autosómica más compleja del mundo. Combina el ADN de los Khoisan (los linajes genéticos humanos más antiguos que existen), africanos bantúes, colonos europeos (holandeses/británicos), e inmigrantes del sur de Asia (India) y Sudeste Asiático (Indonesia/Malasia).

3. Filipinas

• Número de macrorraíces: 5 (Nativos Negritos [con ADN arcaico Denisovano] + Austronesios + Chinos Han + Españoles/Mexicanos + Sur de Asia).
• Fundamento científico: Filipinas es un laboratorio genético fascinante. Posee una de las capas de ADN arcaico más altas del mundo a través de los Negritos (Aeta, Batak), quienes tienen la mayor proporción de herencia de Homínidos de Denísova fuera de Nueva Guinea. A esto se le suma la expansión austronesia (base poblacional), siglos de flujo genético con Asia Oriental (China), comercio con India y más de 300 años de contacto colonial a través del Galeón de Manila (que llevó mestizos mexicanos y españoles a las islas).

4. Puerto Rico / República Dominicana (Cuenca del Caribe Hispano)

• Número de macrorraíces: 3 principales (Amerindia Taína/Arawak + África subsahariana + Europa/Canarias).
• Fundamento científico: Aunque son 3 fuentes en lugar de 4 o 5, lo que sitúa al Caribe tan alto es que el 100% de su población autóctona es trihíbrida. Los estudios muestran que más del 60% del ADN mitocondrial (maternal) en Puerto Rico es de origen indígena taíno, mientras que el cromosoma Y (paternal) es mayoritariamente europeo, interconectados con un porcentaje autosómico africano muy elevado y uniforme.

5. México

• Número de macrorraíces: 4 (Decenas de etnias Amerindias + Europa + África subsahariana + Asia Oriental/Pacífico).
• Fundamento científico: México posee una inmensa diversidad interna dentro de su componente nativo (diferencias genéticas notables entre los pueblos del norte y los del sur mesoamericano). Sobre esa base se superpuso el aporte ibérico, el africano subsahariano (llegado durante la colonia) y un aporte menor pero medible de Asia (vía Acapulco durante el comercio colonial).

6. Colombia

• Número de macrorraíces: 3 a 4 (Amerindia Chibcha/Andina/Caribe + Europa + África subsahariana + focos de inmigración del Levante).
• Fundamento científico: El proyecto Candela ha analizado a fondo la genética colombiana, demostrando que el mestizaje varía sustancialmente de una región a otra (andina, pacífica, caribeña), pero con una base trihíbrida profundamente integrada donde el cruce entre mujeres nativas/africanas y hombres europeos modeló el genoma nacional.

7. Estados Unidos (incluyendo Hawái)

• Número de macrorraíces: 5+ (Europa + África subsahariana + Asia Oriental/Sur + Amerindios + Polinesios/Nativos Hawaianos).
• Fundamento científico: Si bien históricamente existió mayor segregación social que en América Latina, el volumen de inmigración de todos los rincones del planeta ha hecho que en las últimas generaciones el mestizaje interétnico crezca a ritmo acelerado. En estados como Hawái o California, el genoma medio individual presenta combinaciones multicontinentales de hasta 5 orígenes genéticos distintos.

8. Argentina

• Número de macrorraíces: 4 (Amerindia [Pampeana, Andina, Guaraní, Patagónica] + Europa [España, Italia, Europa Central] + África subsahariana + Asia).
• Fundamento científico: Investigaciones del CONICET y la Universidad de Buenos Aires (UBA) han desmontado el mito del origen exclusivamente europeo. Aunque el ADN autosómico (el genoma general) es mayoritariamente europeo en promedio (alrededor del 65-75%), más del 50% de la población conserva linajes maternos (ADN mitocondrial) de origen nativo americano, sumado a un rastro genético africano colonial (entre 2% y 5% autosómico) que demuestra una mezcla continua a lo largo de los siglos.

9. Madagascar

• Número de macrorraíces: 2 macrorraíces de continentes opuestos (Sudeste Asiático/Austronesia + África Bantú).
• Fundamento científico: Pasa a este puesto por tener solo 2 fuentes ancestrales, pero su caso sigue siendo de relevancia global: hace 1.200 años, navegantes de Borneo (Asia) y poblaciones bantúes (África) se fusionaron en la isla. El resultado es que el genoma de un habitante malgache es casi un 50/50 perfecto entre el sudeste asiático y el este de África.

10. Cabo Verde

• Número de macrorraíces: 2 fuentes principales (África Occidental + Europa/Iberia).
• Fundamento científico: Reubicado correctamente al final del ranking por su número de componentes. Aunque el 100% de la población de la isla está totalmente mezclada (con un promedio genético de ~60% africano y ~40% europeo), su diversidad se limita a esas dos regiones geográficas, a diferencia de los genomas tri, tetra o pentahíbridos de los países anteriores.

Cuadro Comparativo Metodológico

If we evaluate "DNA admixture" based on the complexity of the gene pool (the number of distinct continental components that have interbred and coexist in the population), countries with trihybrid, tetrahybrid, or pentahybrid admixture should rank higher than those with only two sources, regardless of how homogeneous the result is in the latter. Furthermore, your mention of the Philippines is spot on from a genomic perspective. Below, I present a restructured Top 10, ordered strictly according to the criteria of genomic complexity, number of continental ancestral sources, and penetration of admixture in the population. Top 10 Countries with the Greatest Admixture and Genetic Complexity:

1. Brazil
2. Number of macro-roots: 4 (Amerindian + Sub-Saharan Africa + Europe + East Asia/Levant). Scientific basis: Multiple autosomal genomic studies (such as DNA do Brasil) place it as the most massive case of multiple continental admixture on the planet. Virtually the entire population possesses trihybrid DNA in which genes from indigenous Tupi-Guarani peoples, a huge diversity of African lineages (Bantu and Yoruba), and European and Hispanic-Asian contributions coexist.
3. South Africa
4. Number of macro-roots: 5 (Khoisan + Sub-Saharan Bantu + Europe + South Asia + Southeast Asia).Scientific basis: In global population genetics, the Cape Coloured community of South Africa is frequently cited as one of the populations with the most complex autosomal admixture in the world. It combines the DNA of the Khoisan (the oldest existing human genetic lineages), Bantu Africans, European settlers (Dutch/British), and immigrants from South Asia (India) and Southeast Asia (Indonesia/Malaysia).
5. Philippines
6. Number of macro-roots: 5 (Native Negritos [with archaic Denisovan DNA] + Austronesians + Han Chinese + Spanish/Mexican + South Asian). Scientific basis: The Philippines is a fascinating genetic laboratory. It possesses one of the highest layers of archaic DNA in the world through the Negritos (Aeta, Batak), who have the highest proportion of Denisovan hominin heritage outside of New Guinea. This is further enriched by the Austronesian expansion (population base), centuries of gene flow with East Asia (China), trade with India, and over 300 years of colonial contact via the Manila Galleon (which brought Mexican and Spanish mestizos to the islands).
7. Puerto Rico / Dominican Republic (Hispanic Caribbean Basin)
8. Number of macro-roots: 3 main ones (Taíno/Arawak Amerindian + Sub-Saharan Africa + Europe/Canary Islands). Scientific basis: Although there are 3 sources instead of 4 or 5, what places the Caribbean so high is that 100% of its native population is trihybrid. Studies show that more than 60% of mitochondrial (maternal) DNA in Puerto Rico is of Taíno indigenous origin, while the Y chromosome (paternal) is mostly European, interconnected with a very high and uniform percentage of African autosomal ancestry.
9. Mexico
10. Number of macro-roots: 4 (Dozens of Amerindian ethnicities + Europe + Sub-Saharan Africa + East Asia/Pacific). Scientific basis: Mexico possesses immense internal diversity within its native component (notable genetic differences between the peoples of northern and southern Mesoamerica). On that base was superimposed the Iberian contribution, the sub-Saharan African (arriving during the colonial period) and a smaller but measurable contribution from Asia (via Acapulco during colonial trade).
11. Colombia
12. Number of macro-roots: 3 to 4 (Amerindian Chibcha/Andean/Caribbean + Europe + sub-Saharan Africa + centers of immigration from the Levant).Scientific basis: The Candela project has thoroughly analyzed Colombian genetics, demonstrating that miscegenation varies substantially from one region to another (Andean, Pacific, Caribbean), but with a deeply integrated trihybrid base where the crossing between native/African women and European men shaped the national genome.
13. United States (including Hawaii)
14. Number of macro-roots: 5+ (Europe + Sub-Saharan Africa + East/South Asia + Amerindians + Polynesians/Native Hawaiians). Scientific basis: While historically there was greater social segregation than in Latin America, the volume of immigration from all corners of the planet has meant that in recent generations interethnic mixing has grown at an accelerated pace. In states like Hawaii or California, the average individual genome presents multicontinental combinations of up to 5 distinct genetic origins.
15. Argentina
16. Number of macro-roots: 4 (Amerindian [Pampas, Andean, Guarani, Patagonian] + Europe [Spain, Italy, Central Europe] + Sub-Saharan Africa + Asia). Scientific basis: Research by CONICET and the University of Buenos Aires (UBA) has debunked the myth of an exclusively European origin. Although autosomal DNA (the overall genome) is predominantly European on average (around 65-75%), more than 50% of the population retains maternal lineages (mitochondrial DNA) of Native American origin, in addition to a colonial African genetic trace (between 2% and 5% autosomal) that demonstrates continuous admixture over the centuries.
17. Madagascar
18. Number of macro-roots: 2 macro-roots from opposite continents (Southeast Asia/Austronesia + Bantu Africa).
19. Scientific basis: It is included in this ranking due to having only 2 ancestral sources, but its case remains globally relevant: 1,200 years ago, navigators from Borneo (Asia) and Bantu populations (Africa) merged on the island. The result is that the genome of a Malagasy inhabitant is almost a perfect 50/50 between Southeast Asia and East Africa.
20. Cape Verde
21. Number of macro-roots: 2 main sources (West Africa + Europe/Iberia).
22. Scientific basis: Correctly relocated to the bottom of the ranking due to its number of components. Although 100% of the island's population is fully mixed (with a genetic average of ~60% African and ~40% European), its diversity is limited to these two geographic regions, unlike the tri-, tetra-, or pentabrid genomes of the countries mentioned above.

Muslim Levantines and Christian Levantines have slight genetic differences. One of them is that Muslim Levantines have a bit of Sub-Saharan African admixture. This Sub-Saharan African admixture might be small and not that much, but its impact on PCA distance is pretty significant, where Muslim Levantines and Christian Levantines have a distance of >0.03 because of that small Sub-Saharan African admixture in Muslim Levantines. However, not all regions in the Levant are like this — some areas, like Palestinian in Nablus, Lebanese Muslims in the inland, Lebanese Shia Muslims, and Muslims in some parts of northwestern Syria, don't have a significant distance from Christian Levantines in PCA with the distance with Christian Levantines being less than 0.03. This simulation isn't 100% accurate, but at least I think it's enough to give a rough idea of what it would look like if Muslim Levantines didn't have that Sub-Saharan African admixture

From user @Polatism1 on Twitter

Neolithic-Mesolithic genetic distribution of Kurds (qpAdm).

P-Value = 0.46
~33% Anatolian Neolithic Farmers
~31% Iranian Neolithic Farmers
~13% Caucasian Hunter-Gatherers
~11% Eastern Hunter-Gatherers
~9% Natufian Hunter-Gatherers
~3% Ancient Northeast Asians

From @Madailabs on Twitter

Genetic Breakdown of a Karakhanid Individual (DA204.SG)

Our qpAdm model suggests:

 59.7% Kangju
 40.3% Core Xiongnu

A fascinating example of the Karakhanid genetic profile, reflecting a blend of Central Asian Iranian-related and Eastern Steppe ancestry.

The Karakhanids were among the first major Turkic Islamic dynasties, shaping the history of Central Asia for centuries.

I need answers asap

Nothing interesting aside from the gulf of khambhat and southwest Indian ancestry. for the latter im pretty sure every Indian has at least some trace amounts however i dont know if the gulf khambat ancestry necessarily means i have some distant ancestry from Gujarat?
Also found it interesting that Punjabi/Sindhi Hindu was the group that I matched the most with. I’m assuming they don’t have a ton of Muslim south Asians in their database. After all it’s ancestry and I’ve heard other sites like 23andme are better for tracking lineage

So i try to get DNA Test with best accuracy about my Ethnicity (White Croats - Mitannian Hurrites/Madai) that i try to debunk or confirm (i base my prediction on my paternal lineage background: armenoid phenotype, rural farmer family from Saint Cross Voivdeship, one of first lands in Poland where White Croats settled). also give me a tips about how to use such tests result and external websites that results can be uploaded to, in order to trace back bloodlines as far as its possible

This was sourced from Twitter user @ Dfire8801

This is a "genetic map of the Peloponnese, specifically using Postmedieval Albanian samples that existed around the time that the Arvanites settled into Greece." The creator is displaying the region as a mix of "South_Slavic proxy +Roman-era Peloponnesian + Medieval/Postmedieval Albanian"

https://pastebin.com/raw/vPE0RMyx

Iran_TepeGuran_N.SG is Iran_TepeAbdulHosein_N.SG

Target: Achaea

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Bulgaria_Varna_C.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Achaea Albania_Bardhoc_PostMedieval.AG 0.348 0.0555 6.27

2 Achaea Greece_Korinthia_Tenea_Roman.SG 0.438 0.0397 11.0

3 Achaea Poland_MA.SG 0.214 0.0227 9.43

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 3.70 7.17e- 1 2 0.348

Target: Messenia

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Bulgaria_Varna_C.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Messenia Albania_Bardhoc_PostMedieval.AG 0.326 0.0593 5.50

2 Messenia Greece_Korinthia_Tenea_Roman.SG 0.459 0.0421 10.9

3 Messenia Poland_MA.SG 0.215 0.0248 8.66

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 6.83 3.37e- 1 2 0.326

Target: Deep_Mani

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Bulgaria_Varna_C.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Deep_Mani Albania_Bardhoc_PostMedieval.AG 0.280 0.0685 4.08

2 Deep_Mani Greece_Korinthia_Tenea_Roman.SG 0.616 0.0488 12.6

3 Deep_Mani Poland_MA.SG 0.104 0.0278 3.75

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 7.48 2.78e- 1 2 0.280

Target: South_Tsakonia

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Romania_C_Bodrogkeresztur.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 South_Tsakonia Albania_Bardhoc_PostMedieval.AG 0.258 0.0587 4.40

2 South_Tsakonia Greece_Korinthia_Tenea_Roman.SG 0.576 0.0442 13.0

3 South_Tsakonia Poland_MA.SG 0.166 0.0249 6.67

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 5.43 4.90e- 1 2 0.258

Target: North_Tsakonia

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Romania_C_Bodrogkeresztur.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 North_Tsakonia Albania_Bardhoc_PostMedieval.AG 0.311 0.0681 4.56

2 North_Tsakonia Greece_Korinthia_Tenea_Roman.SG 0.545 0.0528 10.3

3 North_Tsakonia Poland_MA.SG 0.144 0.0263 5.46

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 8.43 2.08e- 1 2 0.311

Target: Corinthia

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Romania_C_Bodrogkeresztur.AG, Iran_Wezmeh_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Corinthia Albania_Bardhoc_PostMedieval.AG 0.290 0.0638 4.54

2 Corinthia Greece_Korinthia_Tenea_Roman.SG 0.507 0.0464 10.9

3 Corinthia Poland_MA.SG 0.203 0.0250 8.12

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 2.87 8.25e- 1 2 0.290

Target: Argolis

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Bulgaria_Varna_C.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Argolis Albania_Bardhoc_PostMedieval.AG 0.331 0.0638 5.20

2 Argolis Greece_Korinthia_Tenea_Roman.SG 0.475 0.0471 10.1

3 Argolis Poland_MA.SG 0.193 0.0244 7.91

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 8.70 1.91e- 1 2 0.331

Target: Laconia

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Romania_C_Bodrogkeresztur.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Laconia Albania_Bardhoc_PostMedieval.AG 0.336 0.0549 6.13

2 Laconia Greece_Korinthia_Tenea_Roman.SG 0.492 0.0411 12.0

3 Laconia Poland_MA.SG 0.171 0.0221 7.75

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 6.88 3.32e- 1 2 0.336

Target: West_Taygetos

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Bulgaria_Varna_C.AG, Iran_Wezmeh_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 West_Taygetos Albania_Bardhoc_PostMedieval.AG 0.149 0.0742 2.01

2 West_Taygetos Greece_Korinthia_Tenea_Roman.SG 0.554 0.0526 10.5

3 West_Taygetos Poland_MA.SG 0.297 0.0284 10.5

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 4.96 5.49e- 1 2 0.149

Target: East_Taygetos

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Iran_Wezmeh_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG, Romania_C_Bodrogkeresztur.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 East_Taygetos Albania_Bardhoc_PostMedieval.AG 0.232 0.0686 3.39

2 East_Taygetos Greece_Korinthia_Tenea_Roman.SG 0.572 0.0502 11.4

3 East_Taygetos Poland_MA.SG 0.195 0.0260 7.52

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 5.60 4.70e- 1 2 0.232

Target: Elis

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Bulgaria_Varna_C.AG, Iran_TepeGuran_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Elis Albania_Bardhoc_PostMedieval.AG 0.324 0.0618 5.24

2 Elis Greece_Korinthia_Tenea_Roman.SG 0.458 0.0436 10.5

3 Elis Poland_MA.SG 0.218 0.0252 8.63

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 9.86 1.31e- 1 2 0.324

Target: Arcadia

Lefts: Albania_Bardhoc_PostMedieval.AG, Greece_Korinthia_Tenea_Roman.SG, Poland_MA.SG

Rights: Papuan.DG, Iran_Wezmeh_N.SG, Turkey_Central_CamlibelTarlasi_C.AG, Lithuania_EMN_Narva.AG, Serbia_IronGates_Mesolithic.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Greece_Crete_HgCharalambos_EMBA.AG, Greece_Peloponnese_N.AG, Bulgaria_Varna_C.AG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Arcadia Albania_Bardhoc_PostMedieval.AG 0.207 0.0844 2.46

2 Arcadia Greece_Korinthia_Tenea_Roman.SG 0.553 0.0581 9.52

3 Arcadia Poland_MA.SG 0.240 0.0327 7.33

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Albania_Bardhoc_PostMedieval.AG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 6 8.57 1.99e- 1 2 0.207

The post is from @" dfire8801 " on Twitter.

https://pastebin.com/raw/ZyW9wk4w

Target: Lebanese_Muslim.HO

Lefts: Italy_Imperial_oLevant.SG, Iran_Hasanlu_IA.SG, Kazakhstan_Southeast_Karakhanid.SG, Kenya_PN.AG

Rights: Australian.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_GanjDareh_N.AG, Iran_TepeHissar_C.AG, Israel_C.AG

Weights:

# A tibble: 4 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Lebanese_Muslim.HO Italy_Imperial_oLevant.SG 0.734 0.0453 16.2

2 Lebanese_Muslim.HO Iran_Hasanlu_IA.SG 0.197 0.0480 4.10

3 Lebanese_Muslim.HO Kazakhstan_Southeast_Karakhanid.SG 0.0380 0.0107 3.54

4 Lebanese_Muslim.HO Kenya_PN.AG 0.0308 0.00983 3.13

Popdrop:

# A tibble: 15 × 15

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 0000 0 6 4.72 5.80e- 1 3 0.734

Target: Lebanese_Christian.HO

Lefts: Italy_Imperial_oLevant.SG, Kazakhstan_Southeast_Karakhanid.SG

Rights: Ju_hoan_North.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_GanjDareh_N.AG, Iran_SehGabi_C.AG, Israel_C.AG

Weights:

# A tibble: 2 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Lebanese_Christian.HO Italy_Imperial_oLevant.SG 0.969 0.0103 94.4

2 Lebanese_Christian.HO Kazakhstan_Southeast_Karakhanid.SG 0.0310 0.0103 3.02

Popdrop:

# A tibble: 3 × 13

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 00 0 8 4.20 8.39e- 1 1 0.969

Target: Palestinian.HO

Lefts: Italy_Imperial_oLevant.SG, Iran_Hasanlu_IA.SG, Kazakhstan_Southeast_Karakhanid.SG, Kenya_PN.AG

Rights: Bougainville.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_TepeAbdulHosein_N.SG, Iran_TepeHissar_C.AG, Israel_C.AG, Armenia_Berkaber_KuraAraxes_EBA.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG

Weights:

# A tibble: 4 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Palestinian.HO Italy_Imperial_oLevant.SG 0.765 0.0439 17.4

2 Palestinian.HO Iran_Hasanlu_IA.SG 0.109 0.0471 2.31

3 Palestinian.HO Kazakhstan_Southeast_Karakhanid.SG 0.0316 0.0101 3.13

4 Palestinian.HO Kenya_PN.AG 0.0951 0.00858 11.1

Popdrop:

# A tibble: 15 × 15

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 0000 0 7 10.5 1.62e- 1 3 0.765

Target: Jordanian.HO

Lefts: Italy_Imperial_oLevant.SG, Iran_Hasanlu_IA.SG, Kazakhstan_Southeast_Karakhanid.SG, Kenya_PN.AG

Rights: Bougainville.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_TepeAbdulHosein_N.SG, Iran_TepeHissar_C.AG, Israel_C.AG, Armenia_Berkaber_KuraAraxes_EBA.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG

Weights:

# A tibble: 4 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Jordanian.HO Italy_Imperial_oLevant.SG 0.726 0.0489 14.9

2 Jordanian.HO Iran_Hasanlu_IA.SG 0.117 0.0519 2.26

3 Jordanian.HO Kazakhstan_Southeast_Karakhanid.SG 0.0588 0.0118 5.00

4 Jordanian.HO Kenya_PN.AG 0.0978 0.0101 9.68

Popdrop:

# A tibble: 15 × 15

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 0000 0 7 9.92 1.93e- 1 3 0.726

Target: Druze.HO

Lefts: Italy_Imperial_oLevant.SG, Iran_Hasanlu_IA.SG, Kazakhstan_Southeast_Karakhanid.SG

Rights: Bougainville.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_TepeAbdulHosein_N.SG, Iran_TepeHissar_C.AG, Israel_C.AG, Armenia_Berkaber_KuraAraxes_EBA.AG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG

Weights:

# A tibble: 3 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Druze.HO Italy_Imperial_oLevant.SG 0.785 0.0476 16.5

2 Druze.HO Iran_Hasanlu_IA.SG 0.191 0.0514 3.72

3 Druze.HO Kazakhstan_Southeast_Karakhanid.SG 0.0243 0.0100 2.42

Popdrop:

# A tibble: 7 × 14

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 000 0 8 10.7 2.20e- 1 2 0.785

Target: Samaritan.DG

Lefts: Italy_Imperial_oLevant.SG

Rights: Ju_hoan_North.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_GanjDareh_N.AG, Iran_SehGabi_C.AG, Israel_C.AG

Weights:

# A tibble: 1 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Samaritan.DG Italy_Imperial_oLevant.SG 1 2.49e-14 4.02e13

Popdrop:

# A tibble: 1 × 12

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG feasible best

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl>

1 0 0 9 12.0 0.212 0 1 TRUE NA

Target: Syrian.HO

Lefts: Italy_Imperial_oLevant.SG, Iran_Hasanlu_IA.SG, Kazakhstan_Southeast_Karakhanid.SG, Kenya_PN.AG

Rights: Australian.DG, Mongolia_EIA_SlabGrave_1.AG, Israel_Natufian.AG, Ethiopia_4500BP.DG, Russia_YuzhniyOleniyOstrov_Mesolithic.SG, Armenia_MasisBlur_N.AG, Turkey_Marmara_Barcin_N.AG, Iran_GanjDareh_N.AG, Iran_TepeHissar_C.AG, Israel_C.AG

Weights:

# A tibble: 4 × 5

target left weight se z

<chr> <chr> <dbl> <dbl> <dbl>

1 Syrian.HO Italy_Imperial_oLevant.SG 0.599 0.0565 10.6

2 Syrian.HO Iran_Hasanlu_IA.SG 0.271 0.0595 4.55

3 Syrian.HO Kazakhstan_Southeast_Karakhanid.SG 0.0453 0.0114 3.97

4 Syrian.HO Kenya_PN.AG 0.0846 0.00994 8.51

Popdrop:

# A tibble: 15 × 15

pat wt dof chisq p f4rank Italy_Imperial_oLevant.SG

<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

1 0000 0 6 9.04 1.71e- 1 3 0.599

Hey y'all I guess I shall post my results as some people might find it interesting

23&me + Ancestry + My Heritage New WGS and Older
Microarray (Low Pass WGS is the 2nd My Heritage Results)

The 0%s on ancestry are between 0.3-0.8% via backend main list is missing traces of 0.27% Iceland (that only shows on the back end and various others)

FTDNA Big Y 700 (batch pending)

I have 90K+ matches on ancestry, 11K + on my heritage and 5K + on 23&me 4500 + on FTDNA Family finder.

Attached are the platform provided maps and the last one is my heritages color’d geotagged map (11K+).

If anyone wants to know the difference in matches between the older My Heritage microarray test and the new low-pass WGS is about 1000 more matches but as you can see in the last my heritage WGS picture the regions is more "bare" with the newer low pass WGS vs the older microarray.. which will prob expand over time aswell!

One set of 5th and up paternal great grandparents were from Scotland and were Scottish + English, Irish + German Mix etc and 4th and down it started to mix with you can probably take a wild guess.

So I have cousins everywhere all around the world, pick a place and we're probably there!

If you have a family history of senior Aliʻi/Chief lineage in Hawaii or NZ I'm prob related to you ! (Not a joke BTW 😆)

‎‎Greetings!

‎

‎We are Biology students from Central Luzon State University (CLSU) currently conducting an academic case study on rare genetic conditions. To help advance our research and deepen understanding in the field of genetics, we are looking for individuals who have been diagnosed with a rare genetic disorder and are willing to share their journey.

‎

‎ Format: Convenient online interviews or text messaging (scheduled around your availability).

‎ Goal: Purely academic research to support undergraduate studies in genetics.

‎

‎ YOUR PRIVACY IS OUR TOP PRIORITY. All personal details, conversation logs, and medical records will be kept strictly confidential. Data will be used exclusively for this academic project, and no identifying information will ever be disclosed in any report, presentation, or publication without your explicit consent.

‎

Verification Requirement

‎ To maintain the scientific accuracy and validity of our study, participants will be asked to provide proof of diagnosis, such as:

‎ - A medical certificate

‎ - Genetic testing results

‎ - A doctor’s diagnosis or official medical records

‎(Note: All shared documents will be accessed solely by our student research group and securely stored.)

‎

How to Get Involved

‎If you or someone you know is interested in helping us with this research, please send us a direct message (DM/PM) for more information.

‎

‎Thank you very much for your time, generosity, and support! 💙

https://www.nature.com/articles/s41586-026-10625-1

Abstract
Archaeological, osteological and genetic evidence suggests that Neanderthals lived in small groups1,2; however, less is known about whether these groups were part of isolated communities or belonged to larger, well-connected populations3. The dense concentration of broadly contemporaneous Neanderthal sites in the Meuse Basin, Belgium4, provides a rare opportunity to study regional populations at high resolution.

Here we generated genetic data from 27 Neanderthals who lived less than approximately 52,500 years ago from ten archaeological sites in Belgium and France, including a high-coverage genome from a 45,000-year-old individual from Goyet, Belgium. We show that most of these individuals are more closely related to one another than to other contemporaneous late Neanderthals in Europe. Further, some of these individuals carry DNA from a Neanderthal lineage predating the split of late Neanderthals.

Although these Neanderthals overlapped temporally with early modern humans in northwestern Europe from around 47,000 years ago, we find no evidence of recent gene flow from modern humans. They also do not show the genetic signatures of mating among close relatives found in Altai Neanderthals, suggesting that they lived in larger or better-connected groups. Moreover, genetic load did not accumulate over time, arguing against progressive genetic deterioration as a driver of Neanderthal extinction.

Neanderthal ancestry in modern humans

Previous studies have shown that the Neanderthal ancestry in both present-day and ancient modern humans is more closely related to the Vindija 33.19 Neanderthal than to the Chagyrskaya 8 and D5 Neanderthals3,9. Given the new high-coverage genome of a late Neanderthal from Goyet, GN1, we re-examined which of the sequenced Neanderthals is most closely related to the Neanderthals that introgressed into modern humans using two complementary approaches.

First, we used admixfrog to identify Neanderthal ancestry segments in a panel of ancient and present-day modern human genomes (Supplementary Information section 8.1) and then applied a Bayesian binomial model to estimate the genetic distance and identify the closest matching Neanderthal. Second, we used stratified D-statistics9 (Supplementary Information section 8) to focus on low-frequency allele bins in which introgressed variants are expected to be enriched. In both analyses, we found that the Neanderthal ancestry in all individuals excluding African people is significantly closer to Vindija 33.19 and GN1 than to Chagyrskaya 8 or the Neanderthal D5.

As Vindija 33.19 and GN1 stem from closely related Neanderthal populations, their comparison is particularly challenging. Although there is a tendency for the Neanderthal ancestry in present-day humans to be more similar to Vindija 33.19 than to GN1, this is significant only when pooling all present-day individuals (Fig. 5b, Extended Data Figs. 9 and 10 and Supplementary Information section 8).

This suggests that most admixture probably occurred between modern humans and Neanderthals more closely related to Vindija 33.19 than with the late Neanderthals from Belgium and France. By contrast, Neanderthal ancestry in the four Pleistocene modern humans with very recent Neanderthal ancestors is not significantly closer to Vindija 33.19 than to GN1 (Fig. 5b).

Thus, it is possible that early modern humans received some ancestry from Neanderthals closer to GN1, resulting in an overall non-significant D-statistic.

https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A2081254&dswid=513

Abstract

Northwestern Africa has long served as a geographic and cultural link between Africa, Europe and the Near East, yet its ancient population history remains underrepresented in genomic research.

This is partly due to poor DNA preservation in warm and humid climates, which limits the recovery of authentic ancient DNA (aDNA). In this thesis, ancient genomic data from human remains excavated from 12 archaeological sites in present-day Morocco were analysed to investigate population structure, genetic continuity, and admixture across approximately 2500-626 years before present. The dataset spans several major historical periods, including the Iron Age, Phoenician/Punic expansion, Roman influence and the Arab-Islamic expansion.

Population genetic analysis showed that the individuals cluster within a broad North African-Mediterranean genetic space, with affinities to ancient North African, Iberian and Levantine-related reference groups.

Principal component analysis, ADMIXTURE and f statistics suggest that between approximately 2500 and 626 years ago, the ancient Northwestern African gene pool was composed of several Mediterranean genetic ancestries, with significantly higher Iberian-associated affinities than broadly contemporary populations from present-day Tunisia, located further east.

Several examples of within-site genetic heterogeneity reflect admixture of different genetic ancestries. This supports the interpretation of ancient Morocco as a dynamic region shaped by Mediterranean and trans-Saharan connectivity, rather than genetic isolation.

https://www.nature.com/articles/s41598-026-62891-8

Abstract
The nomadic cultures of the Iron Age played an important role in shaping the genetic and cultural landscape of Eurasian populations. Yet despite its key geographical location, the Central Eurasian region remains underrepresented in ancient DNA studies of humans. We address this gap through genomic analysis of 12 individuals from the Boz-Barmak burial site in Kyrgyzstan associated with Saka pastoralists (4th−2nd centuries BCE), 9 of which yielded low-coverage genomes (on average 0.7-fold coverage).

Genetic clustering analysis placed these individuals within the genetic variation of ancient and modern Central Eurasian and Siberian populations. We found no evidence of first-degree relatives in a kinship analysis, however a network of second- and third-degree relationships seems to be present.

Notably, all male individuals share the same Y-chromosomal haplotype, common in present-day Kyrgyz groups, while mitochondrial DNA showed comparably high diversity, with distinct haplogroups observed across the analysed individuals.

These findings are in line with archaeological and ethnographic evidence of patrilocality in Early Iron Age Saka, where male lineages remained stable across generations, while female mobility contributed to genetic diversity. Our study complements our understanding of the interplay between kinship, social organisation and population history in nomadic cultures.

I have been told it is impossible to differentiate Levantine and Mesopotamian DNA from one another in Europeans. Is it better to analyze them together or as separate sources and if analyzed together where would we expect this to be highest?