For the greater parts of a century archaeologists have wrestled with the identity of ancient samples. None more controversial than ancient Egyptians in the last few centuries. Just to add more to the controversial nature of this field of study, there was research published late 2023 by Wurst and colleagues.1 This study sought to look at diseases in mummified individuals from around the globe. Here I’ll report a preliminary analysis on some of their samples that were pulled from Egypt. One ancient individual in particular from Gebelein dated to and culturally associated with the first Naqada period will be emphasized foremost. I also would like to freely discuss methods in processing ancient data in a series of posts forthcoming.
About the Pre-Dynastic
Before the pyramids in Egypt were built, settlers said to be escaping the desiccation of the dessert had settled into areas around the Nile. Neolithic settlements along the river dating to around 6.4Kya were referred to as the ‘pre-dyanastic’, for those proto-cultures had set the foundations for what we observe as pharonic Egypt today.2,3 The earliest attestation of farming in upper Egypt is labeled the Badarian, after the area (el-Badari) in which their first site was discovered. Their settlements were semi-sedentary and recognizable by rippled motifs on their black top pottery.4,5 After, what followed was the Naqada, which was split into three main phases. The first phase, Naqada I was quite similar to the Badarian with minor differences such as changes in burial practices and more distinct pottery. The burials were still shallow narrow pits however the dead would be more decorated with jewelry and craft and the pottery would be less spherical and more conical and possibly colored during Naqada I. The second phase introduced more elaborate burials and wider variation in pottery and tools. It comes as having possibly the most numerous sites for pre-dynastic findings. The third phase leads into the dawn of dynastic Egypt and is hallmarked by the presence of writing and wealthier burials.2,3,6,7
Site map for Egypt and Lower Nubia
(Click to hide)
What’s in the DNA? – Population Genomics
This analysis points to this pre-dynastic sample being similar to Epipaleolithic and early Neolithic Moroccans in that they posses a genetic profile vaguely related to both West Eurasians and Sub-Saharan Africans.8 More so, they typically fail to yield statistically significant results from two way admixture models of any modern Sub-Saharan and ancient West Eurasian source and the percentages of each cohort vary depending on the comparative samples or method of analysis.9,10 Though these North African samples can at times be used interchangeably as an “autochthonous” North African proxy, the two regions (North-West and North-East Africa ) seem to prefer different ancestral proxies themselves. For instance, 8,10–12 While North-West Africans like Taforalt can be modeled most significantly with Natufians, AM14590 (the sample ID) of Naqada’s west Eurasian related DNA is most similar to Neolithic Iranians.13 In fact, it seems that the individual unearthed from one of the Belt Caves, Hotu, shares the most similarity with the “Non-African” portion of this pre-dynastic sample. Though, it could be the case that Hotu’s relatively low SNP count yielded high P values and ancestry estimates due to ascertainment bias, the overwhelming preference of this sample to model the bulk of the pre-dynastic samples ancestry should still be noted. When using the Natufian and Yoruba to model NaqadaI the proportions are more or less identical to that of Epipaleolithic and Early Neolithic Moroccans though the p-values are close to null.
While all two way models tested failed to show a p-value of more than 0.01 or 1% probability, there were some working three way models. The sources of Eurasian ancestry are quite strict requiring a minor WHG-like source and a Neolithic Iranian source. The Sub-Saharan source of ancestry while not as strict, shows some variation in percentages and likelihood. There are some nuances to be mindful of when calculating via academic programs.14–16 There was a tendency to undermine Sub-Saharan ancestry in all samples when making these predictions even at the expense of lowering statistical significance. This is an issue with the qpAdm software available in the admixtools software package.16 However nonetheless some insightful results were yielded with the help of an updated more faster performing set of tools.15 See methods. I was able to discover that the single modern population along with Ganj Dareh of Iran to model AM14590’s ancestry and show the greatest p-value consistently were the Bakola hunter-gatherers from modern day Cameroon. Interestingly, not only did they yield significant results, but so did the Mbuti pygmies, the Aka pygmies and the Bedzan. This came as a bit of a surprise as Mbuti have been used as an outgroup for the great majority of ADNA studies and therefore much of the diversity captured in their gene-pool when relating to populations of North Africa and Eurasia is not accounted for in those analysis.9,17–23 The modern African population to cover the highest proportion of pre-Dynastic ancestry are the Laka of Chad and the Mada of Cameroon though, the probability that they were ancestral seem pretty low unsurprisingly. What seems to be the case here is that a grand majority of pre-dynastic ancestry is extinct and not directly related to populations who haven’t directly inherited their lineage, like the modern Egyptians, Copts and other neighbors. Moreover it becomes even more obvious when we take into account that the actual best 3-way admixture model includes Ganj Dareh, Villabruna (a West Eurasian Huntergatherer from Sicily) and a 7 thousand year old East African Hunter-Gatherer from Tanzania’s Kisese rockshelter.50 (actual Best statistics are achieved with hunter-gatherers similar to Kisese II from Nyarindi, Kenya, Hotu and WHG/Villabruna but the former two samples both maintain a fraction of the SNP count.) These East African Hunter-Gatherers have an extinct genetic profile which was modeled as a mixture of Ancient East, South and Central African related ancestries.49
Great Variation During the Dynastic Period?
To see how Pre-Dynastic ancestry was inherited, I calculated potential admixture proportions in East Africans and a few Egyptian samples gathered from outside of Africa. 1,24–26 Unfortunately, site information for all samples of the dynastic periods were not available. Therefore I left the Identifiers as “unknown.” Within the other samples I included ancient and modern Nubians27–29 as well as Somalians and an ancient Kenyan30 who had previously shown evidence of having high Ancestral North African related ancestry. The results were not too surprising though not entirely predictable on all fronts. For one, it should be expected that individuals such as the Sudanese Copts would score among the highest amount of this ancestry given their history and genetic profile.28,31–33 For example, though they are dominated by paternal haplogroup J, their culture and genetics are linked to ancient populations of the region and was preserved by their endogamous practices. And given what’s being suggested by the autosomal result of NaqadaI, their frequency of macro-haplogroup B33 shouldn’t be undermined as well. An overall general trend is that later samples, particularly those of the Roman Era show more dilution of pre-dyanastic ancestry despite modern individuals from North East Africa showing signs of recurring pre-dynastic ancestry. The variation is alarming given that such high levels of the indigenous component likely could have been maintained in individuals through out time in the region. This phenomena which incurred a possible event of demic diffusion was also seen during the neolithic of North-West Africa, 12,34,35 Samples such as those from lower Egypt’s Fayum during the Ptolemaic era26, could seem to have had heavy dilution possibly by a near eastern source of some kind. And could have been living side by side with more indigenous people possibly living a bit further south.
Note that for the sake of time and simplicity, models here were selected on least chi-square. This is to preserve as much admixture weights feasible. Comparative Neolithic samples from regions surrounding Egypt were included to measure admixture weights. The Aegean Neolithic grouping includes pre-pottery Neolithic samples from Cyprus,36 Early Neolithic individuals from Nea Nikomedeia37 and three commonly used Neolithic samples from Greece.38 The ‘Caucus Neolithic’ group contains pre-pottery samples from Mesopotamia and Nemrik sites36 and the Levant Neolithic groups pre-pottery Neolithic individuals from modern day Israel and Jordan.39
Table 2: Admixture Proportions and Standard Errors for Select Populations (click to expand)
Thoughts and Methods
Samples were downloaded from the European Nucleotide archive identified by accession ID’s disclosed in their respective publications. Fastq files were aligned to using Burrows Wheeler alignment protocols; aln, samse, and mem.40 The latter algorithm was used to produce the ultimate binary alignment files (bam’s) for paired end reads and the former two were used to align both single and paired end reads, where; single end reads were to be prepped for downstream analysis and paired end reads were aligned this way for diagnostic purposes. Diagnostics were ran using ATLAS,41 to where read length and sequencing depth information was taken into account per bam. As expected optical duplicate reads were marked by GATK42 and were removed with VariantBAM (for single end reads) or MergeReads an algorithm provided by ATLAS which clips overlapping segments of paired end reads. For bams of paired end reads, the read sequences longer than their insert sizes were removed as they were likely present due to contamination. Post mortem damage (PMD) was also assessed using ATLAS, with length parameters variably based on the average read length per paired end read, and the read length with the greatest amount reads for singe end data. Base quality re-calibration was done incorporating PMD for all bams processed. To incorporate post mortem damage into recalibration, I had to use ATLAS for BQSR and for the NaqadaI sample, the bam was copied and updated with new base quality scores using updateBam and then psuedohalploid calls were generated with ATLAS by ‘allelePresence’. All samples had genotype likelihoods generated in GLF and VCF formats. The former initiated by ATLAS’s GLF caller and the later called with MLE. VCF’s were genotyped and phased with beagle derivatives. 43–45
Admixture analysis was done using qpAdm from both admixtools16 and admixtools215 packages. All runs in the former is replicable (albeit with minor variance in statistical scores) in the latter variation of the program. However the same could not be said vice verse. The original admixtools package had a tendency to reduce estimates of ancestry coming from more basal samples. I took advantage of this restriction to constrain the models possible given the populations at hand. Because the programs in the updated version (admixtools2) run much quicker, I created scripts to permute various population combinations in modeling ancestry of the samples above. The runs with the highest p-Value (for NaqadaI ancestry) or lowesr chi-square estimates (for East and North Africans ) had their models co-analyzed by the original program. The successful outputs were reported above.
I took a “semi-heuristic” approach to working with twelve right/reference populations. I used Tian Yuan46 man from China as the outgroup. This was done under the a-prioric assumption that he isn’t related to any of the populations being tested or modeled as ancestors. For Naqada’s ancestry estimates I did not follow the methods seen in either Lazaridis 201910 or Loosdrect 20178 to where they excluded African populations in the reference grouping. This is because I wanted to further test with better accuracy which region of Africa would have the greatest statistical probability of being related to the ancestors of predynatic Egyptians. This is opposed to just checking if there is deep or basal ancestry. With that in mind, four ancient African individuals each representing a quadrant of the continent was selected. Ifri Ouberrid; North Africa, Mota from 4.5kya Ethiopia; East Africa, Shum Laka (individual I10871 from 8kya, Cameroon); Western Africa, and an ancient hunter-gather from Faroaskop rock shelter; South Africa. Non Africans included, Ust Ishim, Romania IronGates Mesolithic, Russia Afanasievo, Luxembourg_Loschbour; ANE, EHG and WHG peoples as per convention. The last three populations were carefully selected and cycled out based on the population being used as sources. For example, for populations with a strong draw towards European farmers, the Epipaleolithic individual from Pınarbaşı was cycled out of the reference group. The other two references were Caucus hunter gathers (CHG) and Natufians, where more modern Iranian and Levantine groups would cycle the two aforementioned Epipaleolithic groups out respectively. After finding best fits per model, all populations were returned to the right group to further see if the model would break in which case the scores can be seen above.
More research is yet to come. This was mainly a quick look into what’s possibly the case as far as North East African ancestry is concerned. Along with more analysis, better methods for phasing accuracy and contamination filtering is on the way. Phenotype predictions using the imputed data processed as pointed out above have been investigated. Though most of the major alleles for skin and hair color has been included in the reference data set (1000 genomes project) more alleles can be scanned to better predict skin, hair and especially eye color, as well as other genes focused on disease and lactase persistence. Phasing power was described in recent studies to be accurate for most populations around 0.5% coverage and above. 47,48 As a result I chose to work with only a handful of samples with coverage approaching said percentage. Kadruka was included as a negative control, for their coverage is far too low for imputation. In which case reference bias was likely the determining factor in predicting their haplotype. KDR001’s standout results serves as supports the accuracy of imputation for the haplotypes of the others. Check them out below.
Phenotype calls for ancient North East Africans.
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Very good as always. I assume the yellow is predynastic ancestry?
Awesome findings! Now all we need is more predynastic samples to see how representative this one is.
Hi,
What is the accession number of the Used Naqada sample and where it was originally published?!
Best
Prof. Amr Saeb
Hey, thanks for your reply.
https://www.ebi.ac.uk/ena/browser/view/ERR11600030 <- Direct link for the Naqada Sequence.
Be interesting if they dna test the mesolithic remains of wadi halfa that’s 8k years old located at border of egypt and sudan
”
Abstract
The dentition of a Mesolithic population (8,000–11,000 years old) from Wadi Halfa, Sudan, can be characterized as morphologically complex, massive and relatively free from pathology except that associated with extreme wear.
Maxillary incisors show shoveling. All of the maxillary molars show some development of the hypocone. Supernumerary cusps appear frequently. Almost one-half of the second lower molars observed show distally located third cusps. Over one-half of the maxillary third molars show an extra cusp. A high percentage of mandibular molars show six cusps.
Overall the teeth from this population compare favorably in size with those of an Australian aborigine tribe and are slightly larger than the teeth of the Neanderthaloids from Skūhl.
The teeth show wear of a degree greater than that found in present day Eskimo or Australian aborigine groups.
This data may be interpreted as indicating that this Mesolithic group was subjected to rigorous selective pressures favoring large and/or morphologically complex teeth. This pressure was apparently intensive wear, presumably caused by the inclusion of large amounts of grit in the diet through the eating of vegetable food macerated on coarse grinding stones.
”
https://onlinelibrary.wiley.com/doi/abs/10.1002/ajpa.1330270107
https://www.sciencedirect.com/science/article/abs/pii/S0047248481800139
https://www.researchgate.net/publication/289506027_The_Wadi_Halfa_Mesolithic_Population
Yes It would be quite interesting. See these earlier posts to get a view at what I expect from Mesolithic populations of the region! West_Afr ancestry and ANA ancestry in Africa?
I’m suprised that Horn of Africans don’t score any of this pre-dynastic Egyptian. It seems to be their Eurasian ancestry is mostly PPNB and Chalcolithic Iranian. Does Dinka really suffice for the SSA admixture in Somalis, since Dinka has excess West African?
What do you mean by excess West African?
Well you see often times in admix analyses theres a component that peaks in Dinka people, usually makes up about 70% of their ancestry and the rest is something that peaks in West Africans and Mbuti Pygmies, Somalis and other Horners except maybe Gumuz and other close grouos usually never score the West African/Mbuti stuff.
Beni Amer score it, they live in Eritrea and Sudan, personally i think Somalis do have Naqadan-like ancestry but maybe due to the low coverage it messes up the model who knows
160 SNPs ? This is a joke of a “sample”
Hello, Zerger. Within both readgroups, (target-metagenomic) this sample has reads covering more than 13 million base pairs. Roughly 30,000 variants conventionally overlaps with the 1240K before QC and filtering and ~13.6 million reads is decent for imputation of missing genotypes. After filtering I was able to keep 13,000 psuedo-haploid reads as per convention and 900,000 SNP’s following imputation. See Methods. You can refine your methodology if you’re struggling to get any reads from any of these individuals. Thanks for commenting.
BTW, could you possibly look into how much predynastic Egyptian-like ancestry is in ancient Levantines? I wonder how much of that ancestry ancient Hebrews or Canaanites might have had given their interactions with Egypt.
Hey!
I was wondering for the predynastic samples, and old kingdom samples, if you could run them through the typical standard ancient Eurasian calculator that shows the breakdown of these ancestries: Natufian, Anatolian Neolithic farmers, Irn Neolithic, CHG , ANA, SSA, steppe, etc. it would be very interesting to know their ancient Eurasian dna breakdown and compare them to later samples to see continuity, as this is the easiest method. It would also give us good insight, as there isn’t any known old kingdom/ predynastic samples that were run this way. If they were already run, what was their breakdown like using this format? From what time period and where in Egypt? This information would be very valuable due to the limited sources.
Thanks Alot!
Is it also possible to identify the “late period unknown” and “MK_ Rifeh” samples as they have heavy predynastic DNA. Is there G25s for them or any sample numbers or ID numbers?
Hello Mazin. The middle Kingdom samples are probably on G25. However I’m not affiliated with nor employ any of those tools for core analysis. They are of the individuals Nakht Ankh and Khnum Nakht.
Oh ok, I figured, just was making sure. And about the ancestry of old kingdom samples, are they possible to run in different types of calculators like standard Eurasian. Also, I was wondering for the predynastic samples, and old kingdom samples, if you could run them through the typical standard ancient Eurasian calculator that shows the breakdown of these ancestries: Natufian, Anatolian Neolithic farmers, Irn Neolithic, CHG , ANA, SSA, steppe, etc. it would be very interesting to know their ancient Eurasian dna breakdown and compare them to later samples to see continuity, as this is the easiest method. It would also give us good insight, as there isn’t any known old kingdom/ predynastic samples that were run this way. If they were already run, what was their breakdown like using this format? From what time period and where in Egypt? This information would be very valuable due to the limited sources.
If it isn’t possible to do it’s fine, I’m just curious as there is not much sampling from those areas, and our knowledge is very limited.
Sincerely
Mazin Abdel-Kerim
Hello, I was curious: did you use the HIrisPlex to Predict phenotypes if so, that category of dark to black skin is highly misleading it can mean anything from a Uyghurs skin complexion to someone from South Sudan this is not a great way to analyze ancient phenotypes also were the genomes low coverage and also would you be open to redoing the phenotype prediction with this model https://andreikh.itch.io/trait-predictor by this guy https://www.youtube.com/@-andreiDNA/videos its is much more accurate at predicting phenotypes
Might you be able to provide the links which shows the Uyghurs predicted phenotypes under Hirisplex? If they show novel genes for skin lightening and tanning I can investigate directly for the presence of said mutations. As for relatedness to modern populations I believe that the basis of comparison should first and foremost be established with extant people in the investigated regions possibly including descendants (of Predynastic and Dynastic Egyptians) in modern day Egypt and North East Africa. The diversity of skin tones both genotypically and phenotypically is well captured in these regions today.
Uighurs are largely East Asian in ancestry IIRC, so they probably have East Eurasian rather than West Eurasian alleles for skin lightening (since East and West Eurasians appear to have evolved lighter skin independently). I notice that when people try to discredit HirisPlex predictions, they always bring up East Eurasian or Native American populations, which makes me think the program was made for West rather than East Eurasian samples. I really doubt predynastic Egyptians would have East Eurasian skin-lightening alleles