Friday, April 3, 2015

Revised Timeline and Distribution of the Earliest Diverged Human Maternal Lineages in Southern Africa


The oldest extant human maternal lineages include mitochondrial haplogroups L0d and L0k found in the southern African click-speaking forager peoples broadly classified as Khoesan. Profiling these early mitochondrial lineages allows for better understanding of modern human evolution. In this study, we profile 77 new early-diverged complete mitochondrial genomes and sub-classify another 105 L0d/L0k individuals from southern Africa. We use this data to refine basal phylogenetic divergence, coalescence times and Khoesan prehistory.
Our results confirm L0d as the earliest diverged lineage (~172 kya, 95%CI: 149–199 kya), followed by L0k (~159 kya, 95%CI: 136–183 kya) and a new lineage we name L0g (~94 kya, 95%CI: 72–116 kya). We identify two new L0d1 subclades we name L0d1d and L0d1c4/L0d1e, and estimate L0d2 and L0d1 divergence at ~93 kya (95%CI:76–112 kya). We concur the earliest emerging L0d1’2 sublineage L0d1b (~49 kya, 95%CI:37–58 kya) is widely distributed across southern Africa. Concomitantly, we find the most recent sublineage L0d2a (~17 kya, 95%CI:10–27 kya) to be equally common. While we agree that lineages L0d1c and L0k1a are restricted to contemporary inland Khoesan populations, our observed predominance of L0d2a and L0d1a in non-Khoesan populations suggests a once independent coastal Khoesan prehistory. The distribution of early-diverged human maternal lineages within contemporary southern Africans suggests a rich history of human existence prior to any archaeological evidence of migration into the region. For the first time, we provide a genetic-based evidence for significant modern human evolution in southern Africa at the time of the Last Glacial Maximum at between ~21–17 kya, coinciding with the emergence of major lineages L0d1a, L0d2b, L0d2d and L0d2a.

Link (Open Access) 

Tuesday, March 17, 2015

New NGS study of the Y DNA

A new Y-DNA study has appeared using Next Generation Sequencing, where ~9 Mb of the Y Chromosome was sequenced for 456 samples (299 of which were new) some preliminary observations are outlined below:

(1) Mutation Rate:

This is the second published study to calibrate the substitution mutation rate for the YDNA based on fossil evidence, to do this, they used a combination of derived mutation rates from 2 separate fossils; the 12.6 KY old Anzick fossil from Montana belonging to haplogroup Q1b and the 4 KY old Saqqaq fossil from Greenland belonging to haplogroup Q2b. The first study, Fu (2014) used the 45 KY old Ust-Ishim fossil from Siberia belonging to haplogroup K(xLT). Interestingly, despite the big difference in age of these fossils of ~ 36 KYA (on average), the derived mutation rates were quite close to each other, with the current study's central estimate only ~8% slower than the rates derived from the Ust-Ishim fossil. The 95% CI bounds for this study were however less tight than the 95% CI bounds of Fu (2014). I have already incorporated these new rates into the TMRCA calculator under Karmin (2015).

(2) Coalescence of Non-African YDNA chromosomes:

The authors report :
....... a cluster of major non-African founder haplogroups in a narrow time interval at 47–52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck
Which aligns almost perfectly with the recent find in Manot, Israel of the 49.2 - 60.2 KY old non-African AMH fossil believed of being closely related to the ancestors of all extant non-Africans, i.e. the first OOA migrants.

(3) A "New" E1b1b (E-M215) topology:

The "new" topology of E-M215 they outline below is in-fact over 3 years old, actually, we knew more back then than what they show in this paper today (see here)
E-M215 Karmin (2015)
Compared with what we knew 3 years ago (note: CTS8288 above is equivalent to E-Z830 below):

The unanswered questions with respect to the major topology of E-M215 remain:
  • What is the relationship, if any,  of E-V92 with respect to E-Z827, E-Z830 or E-V68
  • What is the relationship, if any, of E-V6 with respect to E-Z827, E-Z830 or E-V68

A recent bottleneck of Y chromosome diversity coincides with a global change in culture


It is commonly thought that human genetic diversity in non-African populations was shaped primarily by an out-of-Africa dispersal 50–100 thousand yr ago (kya). Here, we present a study of 456 geographically diverse high-coverage Y chromosome sequences, including 299 newly reported samples. Applying ancient DNA calibration, we date the Y-chromosomal most recent common ancestor (MRCA) in Africa at 254 (95% CI 192–307) kya and detect a cluster of major non-African founder haplogroups in a narrow time interval at 47–52 kya, consistent with a rapid initial colonization model of Eurasia and Oceania after the out-of-Africa bottleneck. In contrast to demographic reconstructions based on mtDNA, we infer a second strong bottleneck in Y-chromosome lineages dating to the last 10 ky. We hypothesize that this bottleneck is caused by cultural changes affecting variance of reproductive success among males.

Link (Closed Access)

Tuesday, February 3, 2015

SNP based module added to the Y TMRCA calculator

The solely STR based Y TMRCA calculator now also can accept SNP based input to compute the TMRCA of a node. Instructions and methodology can be found within the app at the link below:

For now, it uses 7 separate mutation rates that all come from different publications, but not all necessarily using differing methods to derive the rates. I will look to expand these as more substitution mutation rates become available.

Below I have run some quick verifications for 3 separate mutation rate sources:

Poznick (2013) rates via Underhill (2014)

The following is stated in Underhill (2014):
A consensus has not yet been reached on the rate at which Y-chromosome SNPs accumulate within this 9.99Mb sequence. Recent estimates include one SNP per: ~100 years,⁵⁸ 122 years,⁴ 151 years⁵ (deep sequencing reanalysis rate), and 162 years.⁵⁹ Using a rate of one SNP per 122 years, and based on an average branch length of 206 SNPs from the common ancestor of the 13 sequences, we estimate the bifurcation of R1 into R1a and R1b to have occurred ~25,100 ago (95% CI: 21,300–29,000). Using the 8 R1a lineages, with an average length of 48 SNPs accumulated since the common ancestor, we estimate the splintering of R1a-M417 to have occurred rather recently, B5800 years ago (95% CI: 4800–6800). The slowest mutation rate estimate would inflate these time estimates by one third, and the fastest would deflate them by 17%.
Putting in the variables for the R1 node from above into the calculator,
We get an output of:

 R1 - Underhill (2014)
which for the mutation rate they used , i.e. Poznick (2013), the calculator gives 25.15 KYA, close enough to their estimate of 25.1 KYA.
Similarliy for the R1a-M417 node , we get:

R1a-M417 - Underhill (2014)
Again, looking @ the calculator's Poznick TMRCA of 5.86 KYA, we can see it is close enough to their estimate of 5.8 KYA.

Wednesday, January 28, 2015

'Smoking gun' found for the Out of Africa Theory

An Israeli anthropologist, Israel Hershkovitz, claims that he and his team have found the archaeological smoking gun for the Out of Africa theory, a theory which has been genetically reinforced for the past couple of decades,
"This is the smoking gun that confirms what geneticists have been predicting," he said. "We had finds from Africa and from Europe but we were missing the connection between them; it's like finishing a puzzle and finding that a piece is missing: it drives you crazy. This is the missing connection between the older African populations and the later European populations."
The evidence, a 55,000 year old partial skull found in a cave called Manot in Northern Israel, also disqualifies the popular Bab-el-mandeb route that modern humans may have took as they were leaving Africa, and strengthens a Nile valley route according to the same Anthropologist,
Hershkovitz told Haaretz that the presence of modern humans at Manot also supports the idea that Homo sapiens sapiens left Africa through the Nile valley, Sinai and what is today known as Israel,

Obviously, a scenario of multiple exits out of Africa, first via Bab-el-mandeb and then via the Nile valley, can not be necessarily discounted by this find.

Levantine cranium from Manot Cave (Israel) foreshadows the first European modern humans

A key event in human evolution is the expansion of modern humans of African origin across Eurasia between 60 and 40 thousand years (kyr) before present (bp), replacing all other forms of hominins1. Owing to the scarcity of human fossils from this period, these ancestors of all present-day non-African modern populations remain largely enigmatic. Here we describe a partial calvaria, recently discovered at Manot Cave (Western Galilee, Israel) and dated to 54.7 ± 5.5 kyr bp (arithmetic mean ± 2 standard deviations) by uranium–thorium dating, that sheds light on this crucial event. The overall shape and discrete morphological features of the Manot 1 calvaria demonstrate that this partial skull is unequivocally modern. It is similar in shape to recent African skulls as well as to European skulls from the Upper Palaeolithic period, but different from most other early anatomically modern humans in the Levant. This suggests that the Manot people could be closely related to the first modern humans who later successfully colonized Europe. Thus, the anatomical features used to support the ‘assimilation model’ in Europe might not have been inherited from European Neanderthals, but rather from earlier Levantine populations. Moreover, at present, Manot 1 is the only modern human specimen to provide evidence that during the Middle to Upper Palaeolithic interface, both modern humans and Neanderthals contemporaneously inhabited the southern Levant, close in time to the likely interbreeding event with Neanderthals2, 3.

Link ( Closed Access) 

Tuesday, January 20, 2015

Genes & Language, Impact of Oldest Butchering Tools on Communication, Lalibela Archaeology

A comparison of worldwide phonemic and genetic variation in human populations


Worldwide patterns of genetic variation are driven by human demographic history. Here, we test whether this demographic history has left similar signatures on phonemes—sound units that distinguish meaning between words in languages—to those it has left on genes. We analyze, jointly and in parallel, phoneme inventories from 2,082 worldwide languages and microsatellite polymorphisms from 246 worldwide populations. On a global scale, both genetic distance and phonemic distance between populations are significantly correlated with geographic distance. Geographically close language pairs share significantly more phonemes than distant language pairs, whether or not the languages are closely related. The regional geographic axes of greatest phonemic differentiation correspond to axes of genetic differentiation, suggesting that there is a relationship between human dispersal and linguistic variation. However, the geographic distribution of phoneme inventory sizes does not follow the predictions of a serial founder effect during human expansion out of Africa. Furthermore, although geographically isolated populations lose genetic diversity via genetic drift, phonemes are not subject to drift in the same way: within a given geographic radius, languages that are relatively isolated exhibit more variance in number of phonemes than languages with many neighbors. This finding suggests that relatively isolated languages are more susceptible to phonemic change than languages with many neighbors. Within a language family, phoneme evolution along genetic, geographic, or cognate-based linguistic trees predicts similar ancestral phoneme states to those predicted from ancient sources. More genetic sampling could further elucidate the relative roles of vertical and horizontal transmission in phoneme evolution. 

See Also: 

A Novel Solution For Dating The Origin Of Language. Response to Comments on “Phonemic Diversity Supports a Serial Founder Effect Model of Language Expansion from Africa”

Experimental evidence for the co-evolution of hominin tool-making teaching and language


Hominin reliance on Oldowan stone tools—which appear from 2.5 mya and are believed to have been socially transmitted—has been hypothesized to have led to the evolution of teaching and language. Here we present an experiment investigating the efficacy of transmission of Oldowan tool-making skills along chains of adult human participants (N=184) using five different transmission mechanisms. Across six measures, transmission improves with teaching, and particularly with language, but not with imitation or emulation. Our results support the hypothesis that hominin reliance on stone tool-making generated selection for teaching and language, and imply that (i) low-fidelity social transmission, such as imitation/emulation, may have contributed to the ~700,000 year stasis of the Oldowan technocomplex, and (ii) teaching or proto-language may have been pre-requisites for the appearance of Acheulean technology. This work supports a gradual evolution of language, with simple symbolic communication preceding behavioural modernity by hundreds of thousands of years.

Link (Closed Access)

The Lalibela Rock Hewn Site and its Landscape (Ethiopia): An Archaeological Analysis


This article presents the methods employed at the site of Lalibela, Ethiopia during the 2009, 2010, 2011 and part of the 2012 campaigns, as well as the first results obtained. This site consists of a group of rock-cut churches attributed to the sovereign of the same name, King Lalibela, who we know to have reigned in the late 12th century and in the first third of the 13th century. Cut out of solid rock, Lalibela is an exceptional archaeological site since most of the traces of its early phases were eliminated in the process of its transformation. The site thus presents a significant challenge for historians and archaeologists. How is it possible to write its history without excavation? Geomorphological observations of the region offer new keys for understanding Lalibela; identification of the spoil heap, in which we discovered a clear stratigraphy confirming the existence of different cutting phases; the topographic and taphonomic analysis of the remains, and investigations in the cemetery of Qedemt, revealed that the site was formed in multiple phases, probably reflecting a long occupation sequence spanning at least eleven centuries (from the 10th to the 21st century).

Monday, December 8, 2014

SNP vs. STR YDNA TMRCA Estimation

An interesting comparison of YDNA TMRCA estimates using the SNP counting method and STRs (with both pedigree and Zhivotovsky rates as well as rho and ASD methods) can be found in a recently published study.

The Y-chromosome tree bursts into leaf: 13,000 high-confidence SNPs covering the majority of known clades

Many studies of human populations have used the male-specific region of the Y chromosome (MSY) as a marker, but MSY sequence variants have traditionally been subject to ascertainment bias. Also, dating of haplogroups has relied on Y-specific short tandem repeats (STRs), involving problems of mutation rate choice, and possible long-term mutation saturation. Next-generation sequencing can ascertain single nucleotide polymorphisms (SNPs) in an unbiased way, leading to phylogenies in which branch-lengths are proportional to time, and allowing the times-to-most-recent-common-ancestor (TMRCAs) of nodes to be estimated directly. Here we describe the sequencing of 3.7 Mb of MSY in each of 448 human males at a mean coverage of 51 ×, yielding 13,261 high-confidence SNPs, 65.9% of which are previously unreported. The resulting phylogeny covers the majority of the known clades, provides date estimates of nodes, and constitutes a robust evolutionary framework for analysing the history of other classes of mutation. Different clades within the tree show subtle but significant differences in branch lengths to the root. We also apply a set of 23 Y-STRs to the same samples, allowing SNP- and STR-based diversity and TMRCA estimates to be systematically compared. Ongoing purifying selection is suggested by our analysis of the phylogenetic distribution of non-synonymous variants in 15 MSY single-copy genes. 

Link (Open Access)

(iii) The evolutionary STR mutation rate consistently overestimates, and the pedigree rate underestimates, the TMRCAs of nodes (Figure 4a).As expected, the pedigree mutation rate performs better for young nodes (<10 KYA; Table S6 ), while the evolutionary rate performs better for older nodes.

Off course "overestimation" and "underestimation"in this case are both relative to the particular mutation rate used by the authors for the SNP counting method in the first place, the authors used the Xue (2009) mutation rate estimate of 1 X 10^-9/bp/year , therefore, a slower mutation rate choice (like from Poznick (2013) or Francalacci (2013) for instance ) would obviously reduce the "overestimation" of the evolutionary STR mutation rate performance and conversely, a faster mutation rate choice would reduce the "underestimation" of the pedigree mutation rate performance, also important to note is that there is quite a bit of variance within the pedigree rates themselves, the authors chose to use a mean pedigree rate from YHRD (see the YTMRCA Calculator to see how pedigree rates from different sources impact TMRCA estimation). All in all however this was an interesting exercise, I hope we can get to see more of these types of comparisons, especially with fossil calibrated mutation rate estimates used for the SNP counting method.

Figure4: Relationship between SNP-and STR-based TMRCA estimates.SNP-based node estimates are plotted against   STR-based estimates for (a) 21 STRs (b) 17 STRs and (c) 13 STRs, here using ASD with the ‘ancestral haplotype’ root specification. The black dashed linein each case indicates x=y.U nderlying data and correlation coefficients are given in Tables S6 and S7.

For further insight in the current understanding of substitution rates used for the SNP counting method, I direct readers to the Wang (2014) article which enumerates on the 4 primary methods that have been used to calculate the substitution rate:
  1. Human - Chimp Comparisons : Thompson (2000) , Kuroki (2006)
  2. Deep Rooting Pedigree: Xue (2009)
  3. Autosomal Mutation Rate Adjustment: Mendez (2013)
  4. Founding Migrations Based Inference:  Poznick (2013), Francalacci (2013)  
In terms of inferences based on the Y Chromosome TMRCA and the Out Of Africa migrations the authors suggest that Xue (2009) and Poznick (2013) give the most reasonable estimates. 

Comparison of different Y chromosomal substitution rates in time estimation using Y chromosome dataset of 1000 Genome dataset. Time estimations are performed in BEAST. (a) TMRCA of 526 Y chromosomes (including haplogroup A1b1b2b-M219 to T). (b) Time of Out-of-Africa migration, the age of macro-haplogroup CT. HCR- Thomson and HCR-Kuroki: Y chromosome base-substitution rate measured from human-chimpanzee comparison by Thomson et al. [6] and Kuroki et al. [7], respectively. Pedigree rate: Y chromosome base-substitution rate measured in a deep-rooting pedigree by Xue et al. [8]. Autosomal Rate Adjusted: Y chromosome substitution rate adjusted from autosomal mutation rates by Mendez et al. [9]. AEFM-America and AEFM-Sardinian: Y chromosome base-substitution rate based on archaeological evidence of founding migrations using initial peopling of Americas [10] and initial Sardinian expansion [11], respectively. Different reported mutation rates are given at the log scale. Confidence intervals for some of the mutation rates are very wide, and time calculations here use only the point estimate. The times would overlap more if all the uncertainties were taken into account. Figure was drawn using boxplot in R 3.0.2.

However a fifth method , entirely sequencing Y chromosomes from verifiable ancient individuals , a method which is still at its infancy but gaining momentum, should refine the substitution rate to a level of precision that as of yet has not been available. It stands to be seen if it will corroborate the rates from the front runners (Xue (2009), Poznick (2013) ) or maybe even yield unforeseen results.

Thursday, November 13, 2014

Novel genomic signals of recent selection in an Ethiopian population

Fasil Tekola-Ayele, Adebowale Adeyemo, Guanjie Chen, Elena Hailu, Abraham Aseffa, Gail Davey, Melanie J Newport and Charles N Rotimi
The recent feasibility of genome-wide studies of adaptation in human populations has provided novel insights into biological pathways that have been affected by adaptive pressures. However, only a few African populations have been investigated using these genome-wide approaches. Here, we performed a genome-wide analysis for evidence of recent positive selection in a sample of 120 individuals of Wolaita ethnicity belonging to Omotic-speaking people who have inhabited the mid- and high-land areas of southern Ethiopia for millennia. Using the 11 HapMap populations as the comparison group, we found Wolaita-specific signals of recent positive selection in several human leukocyte antigen (HLA) loci. Notably, the selected loci overlapped with HLA regions that we previously reported to be associated with podoconiosis–a geochemical lymphedema of the lower legs common in the Wolaita area. We found selection signals in PPARA, a gene involved in energy metabolism during prolonged food deficiency. This finding is consistent with the dietary use of enset, a crop with high-carbohydrate and low-fat and -protein contents domesticated in Ethiopia subsequent to food deprivation 10000 years ago, and with metabolic adaptation to high-altitude hypoxia. We observed novel selection signals in CDKAL1 and NEGR1, well-known diabetes and obesity susceptibility genes. Finally, the SLC24A5 gene locus known to be associated with skin pigmentation was in the top selection signals in the Wolaita, and the alleles of single-nucleotide polymorphisms rs1426654 and rs1834640 (SLC24A5) associated with light skin pigmentation in Eurasian populations were of high frequency (47.9%) in this Omotic-speaking indigenous Ethiopian population.

Link (Closed Access)

Wednesday, October 8, 2014

Assumptions on the genesis of artistic expression in humans shattered by Indonesian find.

Hand stencils and paintings of pigs found in Indonesian caves are cause for experts to rethink the genesis of artistic expression in humans according to a new publication in nature.

Archaeologists have long been puzzled by the appearance in Europe ~40–35 thousand years (kyr) ago of a rich corpus of sophisticated artworks, including parietal art (that is, paintings, drawings and engravings on immobile rock surfaces)1, 2 and portable art (for example, carved figurines)3, 4, and the absence or scarcity of equivalent, well-dated evidence elsewhere, especially along early human migration routes in South Asia and the Far East, including Wallacea and Australia5, 6, 7, 8, where modern humans (Homo sapiens) were established by 50 kyr ago9, 10. Here, using uranium-series dating of coralloid speleothems directly associated with 12 human hand stencils and two figurative animal depictions from seven cave sites in the Maros karsts of Sulawesi, we show that rock art traditions on this Indonesian island are at least compatible in age with the oldest European art11. The earliest dated image from Maros, with a minimum age of 39.9 kyr, is now the oldest known hand stencil in the world. In addition, a painting of a babirusa (‘pig-deer’) made at least 35.4 kyr ago is among the earliest dated figurative depictions worldwide, if not the earliest one. Among the implications, it can now be demonstrated that humans were producing rock art by ~40 kyr ago at opposite ends of the Pleistocene Eurasian world.
Link (Closed Access)

Watch Video:

From the Press (BBC):
But the discovery of paintings of a similar age in Indonesia shatters this view, according to Prof Chris Stringer of the Natural History Museum in London.
"It is a really important find; it enables us to get away from this Euro-centric view of a creative explosion that was special to Europe and did not develop in other parts of the world until much later," he said.
The discovery of 40,000-year-old cave paintings at opposite ends of the globe suggests that the ability to create representational art had its origins further back in time in Africa, before modern humans spread across the rest of the world.
"That's kind of my gut feeling," says Prof Stringer. "The basis for this art was there 60,000 years ago; it may even have been there in Africa before 60,000 years ago and it spread with modern humans".

Thursday, October 2, 2014

Statisitics on African born immigrants in the U.S.

I stumbled upon an interesting article in the WP that led me to a recently released brief by the US Census Bureau outlining some interesting stats on the growing demography of Africans in America.

The article can be freely accessed here.

Some figures and highlights I found interesting follows:

According to the 2008–2012 American Community Survey (ACS), 39.8 million foreign-born people resided in the United States, including 1.6 million from Africa, or about 4 percent of the total foreign-born population. In 1970, there were about 80,000 African foreign born, representing less than 1 percent of the total foreign-born population (Figure 1). During the following four decades, the number of foreign born from Africa grew rapidly, roughly doubling each decade.
About three-fourths of the foreign-born population from Africa came to live in the United States after 1990. The timing of this movement was driven in part by historical changes. Outmigration from Africa increased rapidly after World War II, as migrants responded to.....

Of the 1.6 million foreign born from Africa in the United States, 36 percent were from Western Africa, 29 percent were from Eastern Africa, and 17 percent were from Northern Africa, followed by Southern Africa (5 percent), Middle Africa (5 percent), and other Africa (7 percent)

...Of these seven, the four largest were Nigeria (221,000 or 14 percent of the African-born population), Ethiopia (164,000 or 10 percent), Egypt (143,000 or 9 percent), and Ghana (121,000 or 8 percent), together constituting 41 percent of the African-born total....

.....Forty-one percent of the African-born population had a bachelor’s degree or higher in 2008–2012, compared with 28 percent of the overall foreign born. Egypt (64 percent) and Nigeria (61 percent) were among the African countries of birth with the highest proportion of bachelor’s and higher degrees. 

 ^ I was surprised (and slightly disappointed) by the relatively lower attainment of Bachelor's degrees by Ethiopians in the US. According to the report, 26% of Ethiopians attained a Bachelor's degree or higher, which is lower than both the foreign born (28%) and the National (30%) attainment levels.

The article attempts at explaining the disparity in educational attainment levels by stating:

The difference in educational attainment among the populations from different African countries in part reflects how they immigrated to the United States. A relatively high proportion of immigrants from Africa entered the United States on diversity visas (24 percent as compared with 5 percent of the overall foreign born), which require a high school diploma or equivalent work experience.The foreign born from Somalia, who mostly entered the United States as refugees or asylees (82 percent in 2010), not as diversity migrants (1 percent in 2010), were an exception to this overall pattern. Forty percent of the Somali born had less than a high school education.

On the bright side, Nigerians and Egyptians have attained Bachelor's degrees (or higher) at a level 2 times than that of the whole nation, which is impressive.

Tuesday, August 19, 2014

East African Climate on Hominin Evolution , Archaelogical evidence for African Homo Sapiens Substructure (pre-OOA)

East African climate pulses and early human evolution


Current evidence suggests that all of the major events in hominin evolution have occurred in East Africa. Over the last two decades, there has been intensive work undertaken to understand African palaeoclimate and tectonics in order to put together a coherent picture of how the environment of East Africa has varied in the past. The landscape of East Africa has altered dramatically over the last 10 million years. It has changed from a relatively flat, homogenous region covered with mixed tropical forest, to a varied and heterogeneous environment, with mountains over 4 km high and vegetation ranging from desert to cloud forest. The progressive rifting of East Africa has also generated numerous lake basins, which are highly sensitive to changes in the local precipitation-evaporation regime. There is now evidence that the presence of precession-driven, ephemeral deep-water lakes in East Africa were concurrent with major events in hominin evolution. It seems the unusual geology and climate of East Africa created periods of highly variable local climate, which, it has been suggested could have driven hominin speciation, encephalisation and dispersal out of Africa. One example is the significant hominin speciation and brain expansion event at ∼1.8 Ma that seems to have been coeval with the occurrence of highly variable, extensive, deep-water lakes. This complex, climatically very variable setting inspired first the variability selection hypothesis, which was then the basis for the pulsed climate variability hypothesis. The newer of the two suggests that the long-term drying trend in East Africa was punctuated by episodes of short, alternating periods of extreme humidity and aridity. Both hypotheses, together with other key theories of climate-evolution linkages, are discussed in this paper. Though useful the actual evolution mechanisms, which led to early hominins are still unclear and continue to be debated. However, it is clear that an understanding of East African lakes and their palaeoclimate history is required to understand the context within which humans evolved and eventually left East Africa.

Link (Open Access)

Earliest evidence for the structure of Homo sapiens populations in Africa


Understanding the structure and variation of Homo sapiens populations in Africa is critical for interpreting multiproxy evidence of their subsequent dispersals into Eurasia. However, there is no consensus on early H. sapiens demographic structure, or its effects on intra-African dispersals. Here, we show how a patchwork of ecological corridors and bottlenecks triggered a successive budding of populations across the Sahara. Using a temporally and spatially explicit palaeoenvironmental model, we found that the Sahara was not uniformly ameliorated between ∼130 and 75 thousand years ago (ka), as has been stated. Model integration with multivariate analyses of corresponding stone tools then revealed several spatially defined technological clusters which correlated with distinct palaeobiomes. Similarities between technological clusters were such that they decreased with distance except where connected by palaeohydrological networks. These results indicate that populations at the Eurasian gateway were strongly structured, which has implications for refining the demographic parameters of dispersals out of Africa.

Link (Closed Access)

Monday, June 9, 2014

Mutation rate of the nuclear genome is getting a fossil calibration

The SMBE 2014 conference is showcasing a presentation where a 45,000 year old genome is being fully sequenced by Fu et al. and where the sequence will be used to calibrate, to my knowledge for the first time, the mutation rate of the nuclear genome.

Previously, Fu et al. (2013) had calibrated the Mitochondrial genome's mutation rate by using some 10 non-African fossils as a reference, with results by and large in compliance with previously established mutation rate estimates.

The rate of accumulation of SNPs on the YDNA, will thus be the last remaining thing to get a fossil calibration. Once we get that, temporal based analysis using these calibrated mutation rates should gain a much more solid basis.

The complete genome sequence of a 45,000-year-oldmodern human from Eurasia
Qiaomei Fu 1 ,2, Bence Viola1 ,3, Heng Li5 ,6, Priya Moorjani6, Flora Jay4, Aximu Ayinuer-Petri1, Susan Keates8, Yaroslav V. Kuzmin7, Montgomery Slatkin4, David Reich5 ,6, Janet Kelso1, Svante Pääbo1  
1Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, 2Key Laboratory of Vertebrate Evolution and Human Origins of Chinese Academy of Sciences, Beijing, China, 3Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, 4Department of Integrative Biology, University of California, Berkeley, USA, 5Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA, 6Department of Genetics,Harvard Medical School, Boston, USA, 7Institute of Geology & Mineralogy, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia, 8University Village, Columbia, USA

We have sequenced to high coverage the genome of a femur recently discovered near Ust-Ishim in Siberia. The bone was directly carbon-dated to 45,000 years before present. Analyses of the relationship of the Ust-Ishim individual to present-day humans show that he is closely related to the ancestral population shared between present-day Europeans and present-day Asians. The over-all amount of genomic admixture from Neandertals is similar to that in present-day non-Africans and there is no evidence for admixture from Denisovans. However, the size of the genomic segments of Neandertal ancestry in the Ust-Ishim individual is substantially larger than in present-day individuals. From the size distribution of these segments we estimated that this individual lived about 200-400 generations after the admixture with Neandertals occurred. The age of this genome allows us to directly assess the mutation rate in the different compartments of the human genome. These results will be presented and discussed.


Monday, April 21, 2014

Genomic and cranial phenotype data support multiple modern human dispersals from Africa and a southern route into Asia


Current consensus indicates that modern humans originated from an ancestral African population between ∼100–200 ka. The ensuing dispersal pattern is controversial, yet has important implications for the demographic history and genetic/phenotypic structure of extant human populations. We test for the first time to our knowledge the spatiotemporal dimensions of competing out-of-Africa dispersal models, analyzing in parallel genomic and craniometric data. Our results support an initial dispersal into Asia by a southern route beginning as early as ∼130 ka and a later dispersal into northern Eurasia by ∼50 ka. Our findings indicate that African Pleistocene population structure may account for observed plesiomorphic genetic/phenotypic patterns in extant Australians and Melanesians. They point to an earlier out-of-Africa dispersal than previously hypothesized. 


Despite broad consensus on Africa as the main place of origin for anatomically modern humans, their dispersal pattern out of the continent continues to be intensely debated. In extant human populations, the observation of decreasing genetic and phenotypic diversity at increasing distances from sub-Saharan Africa has been interpreted as evidence for a single dispersal, accompanied by a series of founder effects. In such a scenario, modern human genetic and phenotypic variation was primarily generated through successive population bottlenecks and drift during a rapid worldwide expansion out of Africa in the Late Pleistocene. However, recent genetic studies, as well as accumulating archaeological and paleoanthropological evidence, challenge this parsimonious model. They suggest instead a “southern route” dispersal into Asia as early as the late Middle Pleistocene, followed by a separate dispersal into northern Eurasia. Here we test these competing out-of-Africa scenarios by modeling hypothetical geographical migration routes and assessing their correlation with neutral population differentiation, as measured by genetic polymorphisms and cranial shape variables of modern human populations from Africa and Asia. We show that both lines of evidence support a multiple-dispersals model in which Australo-Melanesian populations are relatively isolated descendants of an early dispersal, whereas other Asian populations are descended from, or highly admixed with, members of a subsequent migration event. 

Link (Closed Access) 

Friday, April 4, 2014

Median Joining Networks

This post will be dedicated to YSTR median joining networks I will be creating using the Fluxus Network Software©

The  Y TMRCA calculator now also has the capability to create the input file necessary to create median joining networks using the Fluxus Network Software, see here for more details.

This blog-post will be updated routinely with network diagrams as I make more of them, since I do not have access to the Network Publisher  add-on, it takes a considerable amount of time to properly format the diagrams.

I will start with Ethiopian E-M34 data from the Plaster thesis, see also the following post for more detail on Ethiopian E-M34: YDNA E-M123; A closer look 

Monday, March 24, 2014

Modeling 3D Facial Shape from DNA

While still at its infancy, this technology is quite fascinating


Human facial diversity is substantial, complex, and largely scientifically unexplained. We used spatially dense quasi-landmarks to measure face shape in population samples with mixed West African and European ancestry from three locations (United States, Brazil, and Cape Verde). Using bootstrapped response-based imputation modeling (BRIM), we uncover the relationships between facial variation and the effects of sex, genomic ancestry, and a subset of craniofacial candidate genes. The facial effects of these variables are summarized as response-based imputed predictor (RIP) variables, which are validated using self-reported sex, genomic ancestry, and observer-based facial ratings (femininity and proportional ancestry) and judgments (sex and population group). By jointly modeling sex, genomic ancestry, and genotype, the independent effects of particular alleles on facial features can be uncovered. Results on a set of 20 genes showing significant effects on facial features provide support for this approach as a novel means to identify genes affecting normal-range facial features and for approximating the appearance of a face from genetic markers.

Link (Open Access) 

......Since both categorical and continuous variables can be modeled using BRIM, this approach might be used to test for relationships between facial features and other factors, e.g., age, adiposity, and temperament. The methods illustrated here also provide for the development of diagnostic tools by modeling validated cases of overt craniofacial dysmorphology. Most directly, our methods provide the means of identifying the genes that affect facial shape and for modeling the effects of these genes to generate a predicted face. Although much more work is needed before we can know how many genes will be required to estimate the shape of a face in some useful way and many more populations need to be studied before we can know how generalizable the results are, these results provide both the impetus and analytical framework for these studies.....

Some interesting figures:

Figure 1: Workflow for 3D face scan processing.
A) original surface, B) trimmed to exclude non-face parts, C) reflected to make mirror image, D) anthropometric mask of quasi-landmarks, E) remapped, F) reflected remapped, G) symmetrized, H) reconstructed.
Figure 3: Transformations and heat maps showing how face shape is affected by (A) RIP-A and (B) RIP-S.
The top row of each panel shows the shape transformations three standard deviations below and above the mean of the RIPs in this sample. The second row shows the R2 (proportion of the total variation in each quasi-landmark) and the three primary facial shape change parameters: area ratio, curvature difference, and normal displacement. The bottom row shows in yellow the regions of the face that are statistically significantly different (p<0.001) between the two transformations. The max R2 values for RIP-A and RIP-S are 40.83% and 38.21%, respectively. 
Figure 4: Relationships between the ancestry and sex RIP variables and their initial predictor variables.
(A) RIP-A with genomic ancestry; genomic ancestry is calculated using the core panel of 68 AIMs and RIP-A is calculated using this ancestry estimate on the set of three populations combined (N = 592). Populations are indicated as shown in the legend with United States participants shown with black circles, Brazilians with red circles, and Cape Verdeans with blue circles. (B) Histograms of RIP-S by self-reported sex.
Figure 6: Transformations and heat maps showing how face shape is affected by three particular RIP-G variables.
The initial predictor variables are SNPs in the genes (A) SLC35D1 (B) FGFR1, and (C) LRP6. The top row of each panel shows the shape transformations near the extreme values of the particular RIP-G shown. The second row shows the R2 (proportion of the facial total variation), the three primary facial shape change parameters: area ratio, curvature difference, and normal displacement. The max R2 values for A, B, and C are 11.68%, 15.16% and 10.10%, respectively.

Sunday, March 23, 2014

The $1,000 genome

.................The price of sequencing an average human genome has plummeted from about US$10 million to a few thousand dollars in just six years (see ‘Falling fast’). That does not just outpace Moore's law — it makes the once-powerful predictor of unbridled progress look downright sedate. And just as the easy availability of personal computers changed the world, the breakneck pace of genome-technology development has revolutionized bioscience research. It is also set to cause seismic shifts in medicine...........

Read More Here:

Wednesday, February 26, 2014

Was skin cancer a selective force for black pigmentation in early hominin evolution?

Some excerpts from a very interesting read, I suggest reading the whole article here:

Dark or black skin lowers the risk of ultraviolet radiation (UVR)-induced skin cancer by several orders of magnitude and, while this might be considered an incidental benefit, here I make a case for lethal skin cancer—in reproductive, young, early humans, as a potent selective force underlying the emergence of black skin as the ancestral pigmentation state.

Were it not for the efficacy of DNA repair of UV-induced DNA damage, those with white skin would all have cancer, and at a very young age, as evidenced by the impact of the inherited disorder of nucleotide excision DNA repair, xeroderma pigmentosum (XP) [25,26]. Black- or dark-skinned ethnic groups are substantially less at risk but when they do have a diagnosis of skin cancer, it is often on soles and palms—less pigmented regions of the body [27,28].

In black-skinned individuals, melanocytes synthesize brown/black eumelanin which is then packaged into peri-nuclear distributed, ellipsoid melanosomes of keratinocytes (figure 1). This appears to be a near optimal arrangement for UV filtration and DNA protection. In white skin, melanocytes synthesize a higher proportion of yellow and/or red pheomelanin and this is then assembled into clustered small, circular melanosomes in keratinocytes. The compound effect is minimal UV filtration.

Whatever the evolutionary logic, the acquisition of pale skin has become a liability. But only so because pale-skinned Europeans have been subject to either voluntary or enforced migration to much sunnier climes (e.g. Queensland, Australia, and other subtropical zones) and, more recently, have availed themselves of youthful opportunities for intermittent high level sun exposure via inexpensive air travel and recreational holidays in the sun. In this context, skin cancer arises as the consequence of a mismatch between the ancestral environmental conditions that shaped our genetics and skin properties and our current behavioural and social activities [3]. This narrative is reasonably well established. What I address here is another and, in a sense, reciprocal evolutionary aspect of skin coloration and cancer risk.

Early hominin evolution in East Africa at some 2–3 Ma was associated with a dramatic loss of the body hair development that is retained by our primate cousins [68,69]. Hair growth was retained on the head—the most UVR-exposed part of the body of a bipedal hominin. Some exotic explanations have been entertained for this dramatic phenotypic shift, including avoidance of fur parasites or of catching fire, a response to wearing clothes or an adaptation to an aquatic way of life [68–72]. But the most likely major adaptive advantage would have been for thermoregulation or facilitation of sweating and heat loss for physically active, hunter–gatherers in the savannah [69,73,74]. But what colour was the exposed skin of the first hairless hominins? Not black it would seem. The skin of our nearest primate relative, the chimpanzee, is, under the fur, essentially pale or white with melanocytes restricted to hair follicles [67]. The exposed and relatively hairless face and hands are also white in infant chimpanzees of three Pan subspecies (but black in Pan paniscus) and they become facultatively pigmented with age [75]. It has therefore been considered very likely, albeit not unambiguously so [76], that the first African hominins to discard hirsutism were also white- or pale-skinned [7,43,50].

There are no population-based databases that provide for accurate age incidence rates of skin cancer in African albinos. However, multiple clinical reports testify to the fact that the prevalence of skin cancer in African albinos, though variable according to geographical region, is exceptionally high in low-latitude (5–10°) regions with high year-round UVB exposures, including Tanzania [97,109–111], Cameroon [112] and Nigeria [93,113,114]. In South Africa, skin cancer rates in albinos vary with latitude and altitude, being relatively high in Soweto and the Transvaal and lower in the Transkei [107,115]. The risk of developing skin cancer in Soweto albinos was estimated to be some 1000 times that of pigmented blacks [116]. Erythema and burns occur in infant albinos and focal skin lesions develop as early as 5 years of age [97]. By the age of 20 years, most albino individuals in low-latitude regions have multiple actinic keratoses (figure 3) [97], the precursor lesions for SCC [117,118]. Many of these regress spontaneously but most, if not all albinos, have overt skin cancer in their twenties or thirties [97,115,119,120], with occasional presentation even in childhood [97]. 

8. Concluding remarks
Extrapolation from the current risk of skin cancer in OCA2 albinos to that of early hominins in equatorial Africa is clearly speculative but if early humans were indeed pale-skinned, they would most probably have similarly suffered substantial affliction during reproductively active years from non-melanoma skin cancers. That skin cancer in African albinos might be germane to considerations of the adaptive significance of dark skin has been noted before [7,11,138,139], but never explored.

The age-related incidence and mortality from skin cancer, both historically and in contemporary albinos, have been modulated by many factors, including lifestyle, occupation and varying degrees of awareness, preventive measures and medical intervention [91]. In these cultural respects, the lethal impact of skin cancer would have been more severe in naked, pale-skinned and outdoor living hominins, dwelling in a habitat with the highest levels of year-round UVB radiation—in open and arid equatorial savannah. It is difficult to imagine a more potent prescription for cancer: maximum, sustained, whole-body carcinogenic exposure (UVB) coupled with minimal attenuation capacity (via melanin). Young hunter–gatherer males might have suffered the greatest UV exposure and risk of cancer. Death would have ensued at a young age from either metastases or localized invasion, ulceration, bleeding and infection. The detrimental impact on reproductive fitness would then have been severe, providing potent pressure for both the selective sweep of the highly stable African MC1R variant, promoting eumelanin synthesis and black skin and its subsequent stable maintenance for more than a million years. This critical gene clearly did diversify in sequence and function in the descendents of most of those migrants that left Africa to populate the rest of the world. In those, the selective pressures via UVR were both relaxed and different.

Tuesday, February 25, 2014

mtDNA from Southern Africa

Reference mtDNA from Southern Africa from the pre-print "Migration and interaction in a contact zone: mtDNA variation among Bantu-speakers in southern Africa" (Thanks to Maju for the referral)

Friday, February 21, 2014

YDNA E-M123; A closer look

E-M123 (as well as E-M34) was first discovered by Underhill(2000) and is found with a low to medium frequency distribution in East Africa and the Middle East, while it has a low frequency distribution in North Africa and Europe.

Figure 1 - Current and previous E-M215 phylogenetic structure 

Figure 1 shows a comparison of the basic phylogeny of E-M215/M35 as was known before 2011 (a) and after (b), with a 'who and when' key for the Discovery of the UEPs. Notice the impact the rearrangement has on the phylogenetic placement of E-M123, specifically the fact that E-M123 is shown to have a more recent common ancestor with the East and Southern African variants of E-M35, i.e. E-V42 and E-M293, before it does with any of the other variants of E-M35.

Previous publications:

While it is unfortunate that all of the research that has previously been published on E-M123 was done under the consideration of the older (and rather out of date) configuration of the basic structure of E-M35, it is still worth while to look at articles that have tried to untangle the origins and history of this lineage, of these, 3 come to mind:

Friday, February 14, 2014

Comprehensive Ethiopian YDNA TMRCA Estimates

Find below a comprehensive list for all central TMRCA estimates calculated from the Plaster thesis for 6 UEPs (look at this post under Interactive Chart of Figure 3.2 for the frequencies of the UEPs). P*(x R1a) & Y*(x BT,A3b2)  are not included due to their minimal frequency and very sporadic distribution. 

There were a total of 5,756 haplotypes reported with the paper for the markers DYS19, DYS388, DYS390, DYS391, DYS392 and DYS393.  30 of those haplotypes belonged to P*(x R1a) & Y*(x BT,A3b2), leaving a total of 5,726 haplotypes. These remaining haplotypes, were then categorized with the criteria of Cultural ID + Generic Language Group* + UEP, any group of haplotypes that conformed to this criteria with N >1 and with a coalescent not equal to 0 (meaning non-identical haplotypes) were processed for their TMRCA and reported, accounting for 5,668 or 98% of the total haplotypes reported for the paper.

The tables are ordered according to the frequencies of the tested UEPs in Ethiopia, i.e. E*(x E1b1a), 3985 Haplotypes  > J,  689 Haplotypes  > A3b2, 601 Haplotypes  > K*(xL,N1c,O2b,P) , 154 Haplotypes > BT*(xDE,JT), 193 Haplotypes  and E1b1a7, 46 Haplotypes .

Note that both the mean TMRCA's for Zhivotovsky (Z-TMRCA) and the pedigree rates (P-TMRCA), some times also known as germline rates, are in units of generations, the suitable length of a generation for the Z-TMRCA is 25 years, while for the P-TMRCA it may range from 28 to 33 years.

If detail of the TMRCA analysis for any of the populations listed below maybe required, go to the table here, and upload the necessary file into the Y TMRCA calculator and filter for the specific population in question.

Tuesday, February 11, 2014

Ethiopian YDNA J STR Analysis - An addendum

In the past, I had carried out a TMRCA (STR) analysis of YDNA haplogroup J haplotypes from Ethiopia using the primary dataset from the Plaster thesis that was discussed here. While that particular dataset had a large number of haplotypes, it also had a low number of Markers (6). However there was supplementary data that had Y-STR Haplotypes from haplogroup J supplied with the paper. While it only had data for a select few of the populations found in the main paper, it however had better resolution typing at 14 markers. Below are the TMRCA results for those haplotypes. The Dataset can be found in this table in .csv format under "Ethiopian_JM267.csv".
In total, 54 haplotypes were found in the supplementary dataset, nevertheless the total number of haplotypes among the population groups sum up to 53 above, the reason is because one haplotype that belonged to the Anuak dataset was not included.

The results are quite consistent with the results I got from the dataset with less resolution, even if the sample sizes are quite small. For instance, although the Afar had the J Haplogroup in excess of 25%, their haplotypes show the least amount of diversity, conversely the high diversity of Haplogroup J in the other populations is still maintained. 

While the Zhivotovsky TMRCA (Z-TMRCA) for all the 691 YDNA J haplotypes found in Ethiopia in the lower resolution dataset was previously calculated to 595 generations, the Z-TMRCA for the higher resolution dataset for all 54 haplotypes, as seen above, was calculated to 705 generations, if only the markers that were used in the lower resolution data set were used to compute the Z-TMRCA in these 54 haplotypes we would get a Z-TMRCA of 631 Generations. Furthermore, if we intersected the 14 markers from this dataset with the recommended Zhivotovsky markers, the resulting markers of '19', '393', '392', '391', '390', '439', '388', '389-1' and '389-2' , would yield a Z-TMRCA of 920 generations, implicating  an introduction of YDNA J-M267 in Ethiopia well into the Upper Paleolithic.

Update: With respect to the low resolution haplotypes from the plaster thesis; I have added 5,726 YDNA str haplotypes  in *.csv format compatible with the calculator and tabulated according to the UEPs tested, in the Table at this link below as well:

Monday, January 27, 2014

Y TMRCA Calculator as a Web App

The Y DNA (STR) TMRCA calculator can now be accessed as a web application with full functionality here:

It is also embedded in this blog in a new page (above)

UPDATE (02/11/2014)

Another series of updates for the calculator:

  • User now able to utilize the previously idle first column in the csv file to group haplotypes together and thus compute the TMRCA for a specified group (see example below)
  • The application now also accepts Locus names in NIST format as well.
  • It also now automatically deletes any haplotype with a non-integer value given for any locus in the *.csv file. (instead of producing an error for that scenario)