Mycenaeans and Italians

We don't have Ancient Roman DNA yet, but now we have the next closest thing: Ancient Mycenaean Greek DNA. This new study shows that Mycenaeans, like their Peloponnesean descendants, are genetically similar to modern Italians (and other Southern Europeans) because both are similar mixes of Neolithic farmers and Indo-Europeans, and also because of Ancient Greek settlements in Southern Italy.

We estimated the fixation index, F_ST, of Bronze Age populations with present-day West Eurasians, finding that Mycenaeans were least differentiated from populations from Greece, Cyprus, Albania, and Italy (Fig. 2), part of a general pattern in which Bronze Age populations broadly resembled present-day inhabitants from the same region (Extended Data Fig. 7). [...] Other proposed migrations, such as settlement by Egyptian or Phoenician colonists, are not discernible in our data, as there is no measurable Levantine or African influence in the Minoans and Mycenaeans, thus rejecting the hypothesis that the cultures of the Aegean were seeded by migrants from the old civilizations of these regions.

[...]

The Mycenaeans settled all of mainland Greece up to Thessaly, and throughout the Aegean islands. There is evidence of extensive Mycenaean acculturation in Western Anatolia, Italy and Cyprus and trading relations with Egypt and the Near East. The Mycenaeans were literate and used for accounting purposes a syllabic script, Linear B, written in an early form of the Greek. They introduced this script into Crete after they occupied the island.

Lazaridis et al. "Genetic origins of the Minoans and Mycenaeans". Nature, 2017.

Complex Spread of Indo-European Languages

In this recent post, I talked about how ancestry clines in Italy could be due to the way Indo-European languages spread, and a new study suggests the same thing. Italy and the Balkans, especially the southern parts, differ from the rest of Europe by having a lot of the Caucasus Hunter-Gatherer (CHG) component of Yamnaya, but not much of the Eastern Hunter-Gatherer (EHG) component. The authors conclude that Italic, Greek and Balkan branches of Indo-European may have spread directly from the Caucasus through Anatolia and not via the Russian Steppe.

The most recent literature demonstrated significant impact of Caucasus-related ancestry in the Central European Late-Neolithic and Bronze-Age through the migrations of Yamnaya/Pontic-Steppe herders. Accordingly, our results confirm that Caucasus-related admixture via Yamnaya is present in Eastern and Central-Western European clusters (i.e. Continental Europe; Supplementary Table S8, Supplementary Information). However, among our Mediterranean groups, evidence of Yamnaya (and EHG) introgression seems to be present at a lesser extent and was detected mainly in Balkan-related groups (Supplementary Table S8, Supplementary Information), which in turn display traces of admixture with Eastern Europe (Fig. 4, Supplementary Fig. S2). In addition, outgroup-f3 values for Late Neolithic/Bronze Age samples (especially Yamnaya) appear lower in all our newly analysed Mediterranean populations (Supplementary Fig. S9). These results suggest that the genetic history of Southern Italian and Balkan populations may have been, at least in part, independent from that of Eastern and Central Europe, involving specific migratory events that carried Caucasian and Levantine genetic contributes along the Mediterranean shores (see Supplementary Information). This picture may bring important implications for our understanding of the cultural history of Europe, and in particular for the diffusion of Indo-European languages. The Steppe in the Early Bronze Age has been supported as a source of at least some Indo-European languages entering North-Central Europe at that time. In southern Mediterranean Europe, however, our results suggest lower impacts. Any significant Steppe/northern component may have arrived in the south Balkan mainland and southern Italy only later, by which time Indo-European languages of the Italic, Greek and various Balkan branches had already established themselves there. This would suggest that a Bronze Age Steppe source may be not highly consistent with all branches of the Indo-European family (see also Broushaki et al.).

[...]

Summing it up, our analyses show that a Caucasus-related ancestry is observed in both Southern Italian and Southern Balkan populations. Nevertheless, these populations do not seem to reveal such significant evidence of Bronze-Age Yamanya-like introgressions, which have been interpreted as the most probable vectors of CHG-like ancestry in Central-Eastern and Northern Europe and were also linked with the demographic diffusion of some Indo-European languages. These results may suggest that Caucasus-related ancestry reached our Mediterranean populations through migratory events at least partly independent from those postulated for Central Europe, most likely through Anatolia. If so, the spread of Indo-European languages in Europe may be envisaged as a more complex multi-way phenomenon, rather than the one-way result of a single diffusion process.

Sarno et al. "Ancient and recent admixture layers in Sicily and Southern Italy trace multiple migration routes along the Mediterranean". Scientific Reports, 2017.

Genetically Southern European

Genetic studies on Italians often say that Northerners are "closer" to Central and Northern Europeans while Southerners are "closer" to Middle Easterners and North Africans. Technically that's true because of simple geography, but it's misleading because it makes it seem like they cluster with those distant populations, which is false. All Italians cluster with other populations from Southern Europe.

This new study is mainly about Peloponnesean Greeks and how they haven't changed much since ancient times, but they also happen to be the group of Greeks who are genetically closest to Southern Italians. In addition to 5 Italian samples from all over the country, the study also has a large sample of Spaniards (including Andalusians from the south), who are genetically closest to Northern Italians.

Confirming many other studies, this PCA plot shows that the Italian samples — Lombards (labeled "Italians"), Venetians, Tuscans (including "TSI"), and Sicilians — cluster in a North-to-South cline between the Spanish and Greek samples, i.e. Southwestern and Southeastern Europe on the map. (Sardinians, as always, are outliers because of their almost purely Neolithic farmer ancestry.)


In these plots, with the Peloponnesean Greeks (in red) acting as a proxy for the southernmost Italians (and therefore all Italians and Southern Europeans in general), we can see that they're genetically distinct from all non-European populations of Western Eurasia, North Africa and beyond.

Supplementary Figure 2: Comparisons of Peloponneseans with non-European populations. PCA analysis of Peloponneseans and A. Near East. B. Caucasus. C. North Africa. D. East Africa. E. Arabia. F. West Siberia populations.

Stamatoyannopoulos et al. "Genetics of the peloponnesean populations and the theory of extinction of the medieval peloponnesean Greeks". Eur J Hum Genet, 2017.

Much Better Population Structure

This new study confirms the results of previous studies by Di Gaetano et al. (2012) and Fiorito et al. (2016) but has much better geographical coverage of samples, with 737 individuals from 20 locations in 15 different regions being tested, making the earlier genetic "gap" between North-Central and Southern Italians disappear, filled in by an intermediate Central Italian cluster, creating a continuous cline of variation down the peninsula (with Sardinians as outliers) that mirrors geography.



The four new Italian samples from this study (N_ITA, C_ITA, S_ITA and SARD) cluster right on top of older Italian samples from Bergamo, Tuscany, Abruzzo, Sicily and Sardinia used in earlier studies, which are barely visible underneath, showing that the results are consistent. Northern Italians once again cluster with Spaniards, and there's a small Greek sample this time, but it's not from the areas closest to Southern Italians, clustering more with the Central Italians instead.


The study also for the first time includes a formal admixture test that models the ancestry of Italians by inferring admixture events using all of the Western Eurasian samples. The results are very interesting in light of the ancient DNA evidence that has come out in the last couple years.

When top 1% of most significant f3 values were retained according to computed Z-scores, 85% of tested population trios actually involved Italian clusters (Supplementary Table S2). In addition to the pattern described in the main text, the SARD sample seemed to have played a major role as source of admixture for most of the examined populations, especially Italian ones, rather than as recipient of migratory processes. In fact, the most significant f3 scores for trios including SARD indicated peninsular Italians as plausible results of admixture between SARD and populations from Iran, Caucasus and Russia. This scenario could be interpreted as further evidence that Sardinians retain high proportions of a putative ancestral genomic background that was considerably widespread across Europe at least until the Neolithic and that has been subsequently erased or masked in most of present-day European populations.

It's known that Sardinians are almost identical to Early European Farmers from the Neolithic, and that the Indo-Europeans who spread their languages all across Europe in the Bronze Age were a mix of Eastern Hunter-Gatherers from the Russian Steppe and either Caucasus Hunter-Gatherers or Chalcolithic Iranians (who are very similar).

So it looks like Italians resemble other Europeans in being a mix of early European farmers and later Indo-European invaders. The farmer ancestry (which is ultimately from Anatolia) has an expected southeast to northwest cline in Europe, but surprisingly not within Italy. According to the study's estimates, it's about the same amount in the North as it is in the South. The two regions actually differ in their Indo-European related ancestries, caused by inverse clines of the "Caucasus/Iran" and "Russian Steppe" components.

The purple component was predominant in Southern European groups and equally distributed along the peninsula (average frequency of 46%), almost reaching fixation in Sardinians (85%) plausibly due to their long-term isolation especially to Post-Neolithic processes. [...] The green component was considerably represented in samples from Caucasus and Middle East, being also evident in some Southern European populations (e.g. Greeks) and, especially, in Southern Italy (28%), progressively decreasing towards the northern part of the peninsula (12%). [...] The red component characterized most of Central and Eastern European populations, being reduced in Sardinia (7.4%) and showing a decreasing north-south gradient in peninsular Italy (from 39% in N_ITA to 20% in S_ITA).

This difference could be explained by the fact that Ancient Italy was home to a variety of Indo-European speakers: Italic languages spread everywhere, Celtic languages were spoken in the North, and Greek and Illyrian languages in the South. It's likely that some of these arrived via southern route through the Balkans while others took a northern route over the Alps, and the people who brought them thus had different levels of "Caucasus" and "Russian" ancestry.

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Sazzini et al. "Complex interplay between neutral and adaptive evolution shaped differential genomic background and disease susceptibility along the Italian peninsula". Scientific Reports, 2016.

Related: Complex Spread of Indo-European Languages

More Italian Population Structure

This new study is a follow-up to Di Gaetano et al. (2012) by the same team. It increases the number of SNPs, improves the sample selection criteria, and incorporates some newer methods, but it has a lot of the same problems. The main findings are that genetic variation in Italy is clinal going from the Western to the Eastern Mediterranean (with Sardinians as outliers) and that all Italians are made up of the same ancestral components, in different proportions, related to Paleolithic, Neolithic and Bronze Age settlements of Europe (with minor recent Lombard/Norman and Moorish admixture).

We hypothesize two simple historical scenarios leading to the observed genetic variability across Italy: (a) continuous ancient gene flow amplified by isolation-by-distance in recent times; (b) different ancestral origins of the main Italian macroareas whose distinguishability has been attenuated by genetic exchange in recent times.

Monmonier's algorithm revealed no evidence of the presence of genetic barriers across the peninsula. Instead, results from the Mantel test provide evidence of a correlation between genetics and geographical distance. The observed higher average length of the segments with shared IBD within regions compared with those shared between regions (Supplementary Table S2B) suggests recent isolation-by-distance across the wide range of latitude of the Italian peninsula. Moreover, a North to South gradient of increasing ancestral N_e was inferred for the three main macroareas (Northern, Central and Southern), coinciding with increased heterozygosity in Southern Italy. A similar trend was previously described for the rate of inbreeding and genome-wide similarity across Central Europe, and could be interpreted as a signature of the 'Out of Africa' migration during Palaeolithic expansions from refugia after the ice age and of ancient South-to-North migratory waves that occurred at the times of European colonization by Neolithic farmers. The ancestry and IBD analyses provided evidence of admixture in Italy with three major ancestries detected, most represented in Northern Europeans, Southern Europeans and Middle Eastern, respectively (with a small percentage of a North African component found in South Italy and Sardinia), with different prevalence across the peninsula. None of these components is fixed in any population, meaning that there is a poor fit with a strict admixture model, as assumed by the algorithm used, and supporting a process of continuous gene flow in multiple directions (migratory waves to and from Italy). According to previous studies on the Y chromosome and mtDNA, the Middle Eastern ancestry in Southern Italians most likely originated at the time of the Greek colonization and, with a smaller percentage, of the subsequent Arabic domination, whereas in Central-Northern Italy it is possibly because of the admixture of the indigenous residents with Middle Eastern populations spreading from the Caucasus to Central Europe. Our results agree with previously published reports describing a possible maritime route of colonization across Europe, including Italy, although we cannot exclude the occurrence of more recent demographic events leading to a similar scenario. Finally, the homogenous ancestral effective population size across Italian regions could be interpreted as reflecting common genetic origins, taking also into account previous considerations, although the same results might also occur in comparing populations without common origins.

Our study supports the notion that genetic variability across Italy is likely to represent continuous gene flow leading to differences in the proportion of ancestry from different sources, along with genetic exchange among neighbouring populations (eg, Northern Italian with European countries, Southern Italian with Middle Eastern and North African ones). Previous studies, analysing uniparental markers, found Y-chromosome genetic discontinuity across Italy. This contrasts with a general lack of structure for mitochondrial DNA, and with a higher homogeneity for maternal than paternal genetic contributions, suggesting different demographic and historical dynamics for females and males in Italy.

One issue is that the samples are still unevenly distributed, with a big gap between North-Center and South — which is reflected in the PCAs — and almost nothing from the eastern part of the country. (Note: the genetic gap between Aosta Valley and its very close neighbor regions is due to some of it being ethnically French).

Principal component analysis based on the coancestry matrix including Sardinians (b) and excluding Sardinians (c); x and y axes were inverted to emphasize similarity to the geographical map of Italy.

This time they do include a few Iberians for comparison, and that's who Northern Italians cluster with. But besides a few Cypriots, there are still no Greeks, which Paschou et al. (2014) and many other studies show Southern Italians clustering with. Sardinians, as always, are the closest to Ötzi the Iceman.


Fiorito et al. "The Italian genome reflects the history of Europe and the Mediterranean basin". Eur J Hum Genet, 2016.

Related: Much Better Population Structure

Italian Clustering vs. German Clustering

Some people with a Nordicist agenda will use the fact that Northern Italians are a little bit closer than Southern Italians to Northern Europeans as evidence supporting the myth of racial differences between Northern and Southern Italy resulting from Germanic and Arab/African invasions. But there's no reason to expect all Italians to form a tight cluster. Genetic distance is largely a product of geographic distance, and Italy is long and curved, stretching from the Western Alps in the North to the Eastern Mediterranean in the South. So it's normal that Italians would be spread out in a broad cluster that mimics the shape of the country. Tian et al. (2009), which sampled Lombards, Tuscans, Southern Italians and Sardinians, noted exactly this pattern:

To further explore the relationship among European population groups and examine population substructure, PCA was performed using the genotype results from a set of ~300,000 autosomal SNPs that was common to each of the populations examined. For most individuals with self-reported ethnic identities, there was a general correspondence with the geographical location of origin (Figure 1A). For example, the relationship of Italian groups and the subjects from the island country of Sardinia shows a striking resemblance to maps of Europe. In addition, genotypes from the same or related population groups typed in different laboratories showed similar PCA results (for example, north Italian and Tuscan groups genotyped as part of HGDP overlapped with Italian American subjects).

The same thing can be seen in other large countries, like Germany for example. Below is a detail of Figure S2 from Nelis et al. (2009). The Germans are spread out over an even greater area than the Italians, with Northern Germans (from Schleswig-Holstein) tending to the right and Southern Germans (from Bavaria) tending to the left, similar to the pattern observed with the Northern Italians (from Piedmont) and Southern Italians (from Puglia):


The distance between the Northern and Southern locations in each country is about 430 miles (690 km), and accordingly, the median values of PCs for the corresponding sample sets are about the same genetic distance:


In addition, Germany has East-West differences that seem to be even more prominent. The cities of Munich and Dresden are only 223 miles (359 km) apart, yet according to Heath et al. (2008), their populations form two distinct genetic clusters connecting Eastern and Western Europeans, just like on the map:



All of this is ultimately related to the clinal distribution of Mesolithic hunter-gatherer and Neolithic farmer ancestry, which shifts Northern and Eastern Europeans slightly toward Siberia, and Southern and Western Europeans slightly toward the Middle East, and can also have an effect within nations. Indeed, even smaller and less populous Germanic nations have noticeable population structure that follows the same pattern seen in Italy, Germany and Europe as a whole.

Lao et al. (2013) observed it in the Netherlands:

We detected a subtle but clearly noticeable genomic population substructure in the Dutch population, allowing differentiation of a north-eastern, central-western, central-northern and a southern group. Furthermore, we observed a statistically significant southeast to northwest cline in the distribution of genomic diversity across the Netherlands, similar to earlier findings from across Europe. [...] This genetic diversity cline is traditionally explained by several major prehistoric demographic events in Europe: the first colonization of Europe by anatomically modern humans together with a postglacial re-expansion from the southern European refugee areas in Palaeolithic times, and the introduction of the Neolithic agricultural lifestyle by people from the Near East.

And Humphreys et al. (2011) observed it in Sweden:

In a comparison of extended homozygous segments, we detected a clear divide between southern and northern Sweden with small differences between the southern counties and considerably more segments in northern Sweden. [...] The first principal component showed the presence of a north-south genetic gradient that was mainly driven by each northern county being different from other counties. Systematic variation was present in the south of Sweden although to a markedly smaller degree than in the north of Sweden. [...] The overall North-South axis of variation is consistent with previous studies that have shown axes of variation on a European scale that closely line up with geographical axes.

Overestimated Admixture in Brisighelli (2012)

This study tries to quantify individual ancestry in Italians by using a small panel of autosomal markers that are known to produce errors and overestimate admixture compared with using the full SNP data set, and as a result it comes up with estimates of Sub-Saharan African admixture in Italy and elsewhere in Europe that are much higher than in any other study:

A panel of 52 AIMs was genotyped in 435 Italian individuals in order to estimate the proportion of ancestry from a three-way differentiation: sub-Saharan Africa, Europe and Asia. Structure analyses allowed us to infer membership proportions in population samples, and these proportions can be graphically displayed, as in Figure 2. This analysis indicated that Italians have a basal proportion of sub-Saharan ancestry that is higher (9.2%, on average) than other central or northern European populations (1.5%, on average). The amount of African ancestry in Italians is however more comparable to (but slightly higher than) the average in other Mediterranean countries (7.1%).

The authors go on to say that Sub-Saharan African admixture in Italy is also evident in uniparental markers, but they should've been suspicious of their high AIM-based estimate when they found only 1.2% mtDNA haplogroup L and no A, B or E(xE3b) Y-DNA, which leads to an admixture estimate (0.6%) that's 15 times lower.

They also should've been puzzled by other bizarre results in their structure analysis, like African admixture appearing higher in Northern and Central Italy than in Southern Italy, with an equally high amount in Britain and Japan, and a very high Asian component in Central and Southern Italians that other Europeans don't have:

52 AIMs

Indeed, when we look at many of the same and similar populations tested using 291,184 SNPs in Lazaridis et al. (2014), we can see that the pattern is totally different and fits much better with the uniparental data and known reality. Italians only have a drop (<1%) of African admixture, which is highest in the south, while the British and Japanese don't have any at all, and Asian admixture is expectedly higher in Northern and Eastern Europe than it is in Southern Europe:

291,184 SNPs

These two very different results highlight the importance of using all genome-wide data when estimating individual ancestry and admixture proportions.

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Brisighelli et al. "Uniparental Markers of Contemporary Italian Population Reveals Details on Its Pre-Roman Heritage". PLoS One, 2012.

Mediterranean Sea as Genetic Barrier

This new study confirms that the Mediterranean Sea has acted as a strong barrier to gene flow through geographic isolation following initial settlements. Samples from (Northern) Italy, Tuscany, Sicily and Sardinia are closest to other Southern Europeans from Iberia, the Balkans and Greece, who are in turn closest to the Neolithic migrants that spread farming throughout Europe, represented here by the Cappadocian sample from Anatolia. But there hasn't been any significant admixture from the Middle East or North Africa into Southern Europe since then.

Genes Mirror Geography Across the Mediterranean Basin

We first used principal components analysis (PCA) to visualize the genotypic distances between studied populations. Populations on the southern and northern coasts of the Mediterranean appear to be separated by the geographic barrier of the Mediterranean Sea. The role of the Mediterranean Sea as a barrier for gene flow among populations was also supported by our analysis using the BARRIER software, which implements Monmonier's maximum difference algorithm. In accordance with this finding...the PCA distribution of the populations closely resembles the geographic map of the countries circling the Mediterranean Sea. On this PCA "map" of populations, the east coast of the Mediterranean Sea is appropriately occupied by the Palestinians and the Lebanese Druze. Yemenites and Bedouins branch out from the Mediterranean populations and are closer to the populations of the Near East.

[...]

Seljuk Turks settled in Anatolia in the 12th century AD; however, the Anatolian Cappadocians we included in this study belong to the population that have kept the religion and the language of the pre-Seljuk Cappadocians and, therefore, most likely carry the genetic makeup of the ancient Anatolians. The only important gene flows from Near East to Europe must have occurred in prehistoric times and, as genetic evidence suggests, the most prominent migrations should have occurred during the Neolithic.

[...]

Although the Southeastern Mediterranean islands seem to have acted as a bridge from Anatolia to Southern Europe, the relatively small degree of gene flow between the African and the European coasts shows that the Mediterranean Sea also had a barrier function as also suggested with studies of mtDNA polymorphisms. Thus, the Mediterranean seems to have facilitated the migrations of Neolithic farmers along its Southern European coast but it mostly acted as an isolating factor between its European and African coasts.

Paschou et al. "Maritime route of colonization of Europe". PNAS, 2014.

Related: Moors Expelled from Sicily and Southern Italy

Italian Ancestry of Ashkenazi Jews

Genetic similarities between Italians and Ashkenazi Jews are due to the fact that about half of Jews' ancestry is European, a lot of which came from Italy when diaspora males migrated to Rome and found wives among local women who then converted to Judaism. The same process happened again to a lesser degree in other parts of Europe as Jews migrated further north, west and then east, but according to genome-wide autosomal DNA, their highest European admixture is Italian.

Overall, it seems that at least 80% of Ashkenazi maternal ancestry is due to the assimilation of mtDNAs indigenous to Europe, most likely through conversion. The phylogenetic nesting patterns suggest that the most frequent of the Ashkenazi mtDNA lineages were assimilated in Western Europe, ~2 ka or slightly earlier. Some in particular, including N1b2, M1a1b, K1a9 and perhaps even the major K1a1b1, point to a north Mediterranean source. It seems likely that the major founders were the result of the earliest and presumably most profound wave of founder effects, from the Mediterranean northwards into central Europe, and that most of the minor founders were assimilated in west/central Europe within the last 1,500 years. The sharing of rarer lineages with Eastern European populations may indicate further assimilation in some cases, but can often be explained by exchange via intermarriage in the reverse direction.

The Ashkenazim therefore resemble Jewish communities in Eastern Africa and India, and possibly also others across the Near East, Caucasus and Central Asia, which also carry a substantial fraction of maternal lineages from their 'host' communities. Despite widely differing interpretations of autosomal data, these results in fact fit well with genome-wide studies, which imply a significant European component, with particularly close relationships to Italians. As might be expected from the autosomal picture, Y-chromosome studies generally show the opposite trend to mtDNA (with a predominantly Near Eastern source) with the exception of the large fraction of European ancestry seen in Ashkenazi Levites.

Evidence for haplotype sharing with non-Ashkenazi Jews for each of the three main haplogroup K founders may imply a partial common ancestry in Mediterranean Europe for Ashkenazi and Spanish-exile Sephardic Jews, but may also, at least in part, be due to subsequent gene flow, especially into Bulgaria and Turkey, both of which witnessed substantial immigration from Ashkenazi communities in the fourteenth and fifteenth centuries. Gene flow could have been substantial in some cases—ongoing intermarriage is likely when these communities began living in closer proximity after the Spanish exile. A partial common ancestry for all European Jews—both Ashkenazi and Sephardic—is again strongly supported by the autosomal results.

Jewish communities were already spread across the Graeco-Roman and Persian world >2,000 years ago. It is thought that a substantial Jewish community was present in Rome from at least the mid-second century BCE, maintaining links to Jerusalem and numbering 30,000-50,000 by the first half of the first century CE. By the end of the first millennium CE, Ashkenazi communities were historically visible along the Rhine valley in Germany. After the wave of expulsions in Western Europe during the fifteenth century, they began to disperse once more, into Eastern Europe.

These analyses suggest that the first major wave of assimilation probably took place in Mediterranean Europe, most likely in the Italian peninsula ~2 ka, with substantial further assimilation of minor founders in west/central Europe. There is less evidence for assimilation in Eastern Europe, and almost none for a source in the North Caucasus/Chuvashia, as would be predicted by the Khazar hypothesis—rather, the results show strong genetic continuities between west and east European Ashkenazi communities, albeit with gradual clines of frequency of founders between east and west.

Costa et al. "A substantial prehistoric European ancestry amongst Ashkenazi maternal lineages". Nature Communications, 2013.

Admixture between previously diverged populations yields patterns of genetic variation that can aid in understanding migrations and natural selection. An understanding of individual admixture (IA) is also important when conducting association studies in admixed populations. However, genetic drift, in combination with shallow allele frequency differences between ancestral populations, can make admixture estimation by the usual methods challenging. We have, therefore, developed a simple but robust method for ancestry estimation using a linear model to estimate allele frequencies in the admixed individual or sample as a function of ancestral allele frequencies. The model works well because it allows for random fluctuation in the observed allele frequencies from the expected frequencies based on the admixture estimation. We present results involving 3,366 Ashkenazi Jews (AJ) who are part of the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort and genotyped at 674,000 SNPs, and compare them to the results of identical analyses for 2,768 GERA African Americans (AA). For the analysis of the AJ, we included surrogate Middle Eastern, Italian, French, Russian, and Caucasus subgroups to represent the ancestral populations. For the African Americans, we used surrogate Africans and Northern Europeans as ancestors. For the AJ, we estimated mean ancestral proportions of 0.380, 0.305, 0.113, 0.041 and 0.148 for Middle Eastern, Italian, French, Russian and Caucasus ancestry, respectively. For the African Americans, we obtained estimated means of 0.745 and 0.248 for African and European ancestry, respectively. We also noted considerably less variation in the individual admixture proportions for the AJ (s.d. = .02 to .05) compared to the AA (s.d.= .15), consistent with an older age of admixture for the former. From the linear model regression analysis on the entire population, we also obtain estimates of goodness of fit by r2. For the analysis of AJ, the r2 was 0.977; for the analysis of the AA, the r2 was 0.994, suggesting that genetic drift has played a more prominent role in determining the AJ allele frequencies. This was confirmed by examination of the distribution of differences for the observed versus predicted allele frequencies. As compared to the African Americans, the AJ differences were significantly larger, and presented some outliers which may have been the target of selection (e.g. in the HLA region on chromosome 6p).

Banda et al. "Admixture Estimation in a Founder Population". Am Soc Hum Genet, 2013.

Two major differences among the populations in this study were the high degree of European admixture (30%-60%) among the Ashkenazi, Sephardic, Italian, and Syrian Jews and the genetic proximity of these populations to each other compared to their proximity to Iranian and Iraqi Jews. This time of a split between Middle Eastern Iraqi and Iranian Jews and European/Syrian Jews, calculated by simulation and comparison of length distributions of IBD segments, is 100–150 generations, compatible with a historical divide that is reported to have occurred more than 2500 years ago. The Middle Eastern populations were formed by Jews in the Babylonian and Persian empires who are thought to have remained geographically continuous in those locales. In contrast, the other Jewish populations were formed more recently from Jews who migrated or were expelled from Palestine and from individuals who were converted to Judaism during Hellenic-Hasmonean times, when proselytism was a common Jewish practice. During Greco-Roman times, recorded mass conversions led to 6 million people practicing Judaism in Roman times or up to 10% of the population of the Roman Empire. Thus, the genetic proximity of these European/Syrian Jewish populations, including Ashkenazi Jews, to each other and to French, Northern Italian, and Sardinian populations favors the idea of non-Semitic Mediterranean ancestry in the formation of the European/Syrian Jewish groups and is incompatible with theories that Ashkenazi Jews are for the most part the direct lineal descendants of converted Khazars or Slavs. The genetic proximity of Ashkenazi Jews to southern European populations has been observed in several other recent studies.

Atzmon et al. "Abraham's Children in the Genome Era: Major Jewish Diaspora Populations Comprise Distinct Genetic Clusters with Shared Middle Eastern Ancestry". Am J Hum Genet, 2010.

Population Structure Within Italy

The good news is there's a new study on population structure in Italy. The bad news is that it's not very well done. The authors failed to sample populations from elsewhere in Southern Europe (like Iberia and the Balkans), which Italians are most related to in other studies, and they didn't collect 4-grandparental information on each individual, resulting in several outliers apparently with recent origins in different parts of the country. They also describe genetic components that are probably very old and have a wide distribution as "Northern European ancestry" and "Middle Eastern ancestry" as if they came from modern populations. Besides all that, the results aren't too surprising.

According to the study, Italians have similar proportions of the same genetic components, varying slightly from North to South, but distinct from both Northern/ Central Europe and the Middle East/North Africa. The island of Sardinia is unique in having an excess amount of one of those components.


In terms of PCA, Italians plot expectedly according to geography between the Western and Eastern Mediterranean (the authors say "France" and "the Middle East" because of the lack of Southern European reference samples), with Sardinians out to the side.

The position of the Italian population samples suggests that genetic distances between these populations and other European and Middle East populations has a good correlation with geographic distances. At the same time, Sardinia was confirmed to be a genetic "outlier".

[...]

The relative position of the samples reflected their geographic location: the close correlation between PC and geography was previously reported by several authors. When compared to other European populations, Sardinia was confirmed to be a genetic "outlier", whereas the Northern Italian population was genetically close to the French population, and the Southern Italians had some similarities with other Mediterranean populations such as those from Middle East. Unfortunately, lack of data from other relevant reference populations from the South-East Europe, e.g. from the Balkan peninsula, made it impossible to fully analyze the extent of the Eastern contribution in Italian populations.

Our main goal was to investigate the genetic structure of the Italian population considering four main macro-areas (Northern, Central, Southern Italy and Sardinia). We carried out PC analysis on the Italian samples and plotted the eigenvectors 1 and 2 in Figure 2. Most samples fell within a main cluster which seems to be indicative of Italian peninsula individuals. The first PC divided Italian populations in two clusters, one for Sardinia and the other for the remaining three Italian macro-areas. The Sardinian population is highly dispersed along the first eigenvector.

The second PC divided Italian mainland population into two clusters, with a certain degree of overlapping between Northern and Central Italy, and a separate cluster for Southern Italy, suggesting that genetic variation is generally continuous rather than discrete, at least within Italian mainland.

The overlap of Northern and Central Italy, and the gap between Central and Southern Italy, is explained by the uneven distribution of the samples.

ADMIXTURE analysis confirms that there was no clear separation between Northern and Central Italy, at least as considered as macro-areas. Additional comparison of the distribution of pair-wise identity-by-state within each of the four populations and ADMIXTURE analysis clarified that this is not an artifact of the PC analysis. However, the PC and ADMIXTURE analysis results could be due to the sparse geographical coverage of our samples, especially for the Central and Northern macro-areas. In fact, many of the individuals (N = 413) in the North Italian sample analyzed in this study were from Piedmont — a North West Italian region that has historically been affected by intense migration. At the same time, many individuals in the Central Italy macro-area (113 samples) are settled in Tuscany, an administrative region which is at the border with northern regions.

Within each macro-area, there isn't much substructure, meaning that a Sicilian, e.g., is not particularly differentiated from a Campanian or a Puglian.

A finer view of the Italian substructure, can be seen in Figure S2 where the hidden population structure within the Italian dataset is appreciable. Subjects are labeled by municipality, or in the case of the Sardinian samples, by the main linguistic area. In this figure we can appreciate the lack of clustering at the municipality level, also within Sardinia. Individuals seem to cluster within the main macro-area, but the geographic patterning is less obvious for the municipality (or in the case of Sardinia, linguistic) division, and in our opinion this pattern indicates no substructure within regions among municipalities, while the structuring between regions can be easily detected. It is also possible to appreciate a certain genetic homogeneity within Sardinia.

Di Gaetano et al. "An Overview of the Genetic Structure within the Italian Population from Genome-Wide Data". PLoS One, 2012.

Related: More Italian Population Structure, Much Better Population Structure

Affinity of Ancient and Modern Italians

Ancient DNA analysis reveals that Ötzi the Iceman clusters with modern Southern Europeans and closest to Italians (the orange "Europe S" dots in the plots below), especially those from the island of Sardinia. Other Italians pull away toward Southeastern and Central Europe consistent with geography and some post-Neolithic gene flow from those areas (e.g. Italics, Greeks, Etruscans, Celts), but despite that and centuries of history, they're still very similar to their prehistoric ancestor.

The first analysis was to determine if the Iceman's autosomal DNA shows an affinity to any specific population or if he remains an outlier among contemporary samples. We intersected...his genome with the population reference sample consisting of more than 1,300 Europeans...125 individuals from seven North African populations ranging from Egypt to Morocco...and 20 Qatari samples from the Arabian Peninsula. When plotting the Iceman's genotype along the first two major axes of variation in Principal Component space (PC1 versus PC2), PC1 is driven by a north-to-south gradient differentiating North Africans from Europeans, and PC2 aligns individuals along north-to-south gradient within Europe (Fig. 3a). The Iceman clusters nearest to southern European samples, suggesting no greater genetic affinity with the North African or Middle Eastern components of variation than present day southern Europeans (Fig. 3a).

When considering only European populations, however, we observe that the Iceman clusters closest with five outlier contemporary samples from south-western Europe. In particular, the Iceman abuts the Italian samples originating from geographically isolated regions such as Sardinia (Fig. 3b). Analysis of a larger set of samples, including Sardinians from HGDP across a smaller subset of SNPs, further supports the clustering of the Iceman with samples from Sardinia based on autosomal SNPs (Fig. 3f). [...] The affinity of the Iceman's genome to modern Sardinian groups may reflect relatively recent common ancestry between the ancient Sardinian and Alpine populations, possibly due to the diffusion of Neolithic peoples.

Keller et al. "New insights into the Tyrolean Iceman's origin and phenotype as inferred by whole-genome sequencing". Nature Communications, 2012.

Moors Expelled from Sicily and Southern Italy

It's often claimed that Italians south of Rome are mostly descended from Moors who invaded in the Middle Ages. But according to historian Julie Anne Taylor, the large scale presence of Muslims in medieval Italy was restricted to just two southern locations (first Sicily and then the area around Lucera) and in both cases ended with mass expulsions. Her narrative is consistent with the available genetic data, which estimates only low levels (2-4%) of gene flow from Arabs and Berbers into those two locations, and even lower levels (0-1%) in the rest of the country.

When tensions between the Christians and Muslims in Sicily in the first decades of the thirteenth century disrupted life on Frederick II's island, the emperor did what the Christian rulers of Iberia had done in the eleventh century: he removed the Muslims from his kingdom. Instead of expelling them, however, he deported them to Lucera, a town previously inhabited by Christians in Apulia, forty miles or so from the Adriatic Sea in the southern Italian peninsula. The first deportations began in the 1220s and continued for twenty years. By mid-century, Sicily's Muslim population no longer existed. Some had fled to North Africa while the majority had been settled in Lucera and small villages in the same region.

[...]

Rebellions of Muslims in villages around the island prompted Frederick to find ways to rid Sicily of them, but not to the point of depriving himself completely of their talents and uses. He shipped them off to Apulia, forced them to settle in Lucera, and put them to work in the service of the kingdom.

[...]

When Charles I of Anjou took possession of the colony in 1265, life became increasingly difficult for the inhabitants until, in 1300, Charles II decided to liquidate the colony entirely. He had all the Muslims in southern Italy sold into slavery, took the gold from their sale, and confiscated all of their property. Officials took inventory of all the grain and agricultural products stored there before carting them off to feed the Christian populations of southern Italy.

Sally McKee. "Review: Muslims in Medieval Italy: The Colony at Lucera, by Julie Taylor". The American Historical Review, October 2004.

Our estimates of NW African chromosome frequencies were highest in Iberia and Sicily, in accordance with the long-term Arab rule in these two areas. The chromosome frequencies in the two samples were not significantly different from each other (Fisher's exact test P=0.83) but were both significantly different from the peninsular Italy sample (P<0.01). An inspection of Table 1 reveals a non-random distribution of MNA [medieval North African] types in the Italian peninsula, with at least a twofold increase over the Italian average estimate in three geographically close samples across the southern Apennine mountains (East Campania, Northwest Apulia, Lucera). When pooled together, these three Italian samples displayed a local frequency of 4.7%, significantly different from the North and the rest of South Italy (P<0.01), but not from Iberia and Sicily (P=0.12 and P=0.33, respectively). Arab presence is historically recorded in these areas following Frederick II's relocation of Sicilian Arabs.

SAMPLE	% TOTAL ADMIXTURE
Val Badia	0.0
Veneto	0.9
Central Emilia	0.0
Central Tuscany	1.2
Tuscany-Latium border	0.0
Northeast Latium	0.9
Marche	0.7
South Latium	0.0
East Campania	2.4
Northwest Apulia	3.3
Lucera	1.7
West Calabria	0.0
South Apulia	0.7
Sicily	3.8
Colonized locations	2.8
Rest of country	0.4
Whole country	1.1

Capelli et al. "Moors and Saracens in Europe: estimating the medieval North African male legacy in southern Europe". Eur J Hum Genet, 2009.

Related: Mediterranean Sea as Genetic Barrier

Another Richard Lynn Refutation

They just keep coming. The others can be found here.

As stated at the outset, the aim of this analysis is not to demonstrate that IQ in Southern Italy is the same or higher than that in the North. On the other hand, a simple statistical exercise, based on correlations among variables, such as that by Lynn, is far from conclusive. Recent studies have shown a significant statistical relationship (p-value = 0.008) between the presence of storks in the European continent and the birth rate (Matthews, 2000); an association which seems particularly remarkable in the case of Germany (Höfer et al. 2004). We know how hard it is to explain causality by means of statistical exercises and certainly causal relationships are not captured by simple statistical correlations.

Our previous discussion suggests a different relationship among the variables analyzed by R. Lynn and those collected in the present article. Allowing that school tests are representative of differences in IQ, we have seen that:

• they clearly show how the North-South difference in cognitive ability does not exist at the age of 7. The correlation between regional educational achievement (INVALSI) and regional per capita income becomes positive (0.44) at the age of 10, but is, however, considerably lower than that found through PISA test scores;
• the IQ-average income relationship did not exist in the past, although if it had derived from a genetic difference, it would consequently have done so;
• knowledge of genetic differences in Italy does not support Lynn's opinion that peoples from North Africa and the Near East strongly influenced the genetic structure of the Southern Italian population. Genetically, the influence of the Phoenicians and the Near East populations accounts for a very small fraction, while the predominant genetic influence derives from the long phase of Greek colonization.

The existence of differences in IQ, as revealed by school tests and other tests (supposing that these actually reveal "fundamental" diversities in intelligence), seems much better explained as being socially, economically and historically influenced rather than being genetically determined. Capabilities in problem solving are enhanced by a developing and stimulating environment, according to the so-called "Flynn effect".

In the past, the Southern Italian economy has at times been more advanced than the Northern one; for example during both the Roman antiquity and the high Middle Ages. Perhaps the North and the Centre were more advanced than the South in the late Middle Ages; although nothing certain can be said on the matter. The following decline of the Italian economy as a whole, from the late Middle Ages until the end of the 19th century, probably cancelled the existing economic differences. When per capita GDP diminishes and approaches the level of bare subsistence, differences among regions disappear. In the 19th century, Italy was a relatively backward country both in the North and the South. The statistical material available from the end of the 19th century onwards, does not actually indicate a deep North-South divide, in economic terms. The start of modern growth from then on affected the North much more than the South and economic disparity began to exist between the two parts of the country. In 1891 the North-South difference in per capita GDP was less than 10 percent; it was 20 percent on the eve of World War 1, and 45 per cent after World War 2. In 2010, per capita GDP in the South is about 60 percent that of the North. As ordinarily happens, relative backwardness implies the accumulation of adverse influences. While literacy and years of education grew in the North with respect to the South, infant mortality diminished much more quickly in the North than the South. Institutions, including families and schools, work much better in prosperity than backwardness. Estimates of IQ are likely to be higher where families, municipalities, provinces and regions invest more in education. Remarkable emigration from the South to the North, especially between 1950 and 1975, increased the North-South diversity since emigration, in Italy as elsewhere, is always selective. Since IQ registers education and years of schooling to a greater extent than intelligence, the relative position of the South compared to the North deteriorated in both the cultural environment and the economy more or less contemporaneously.

Daniele and Malanima. "Are people in the South less intelligent than in the North? IQ and the North-South disparity in Italy". Journal of Socio-Economics, 2011.

Clarifying Bauchet et al. (2007)

This was among the first in the recent spate of genome-wide population structure studies, and better ones have been done since then that paint a clearer picture. Here, the sampled populations are divided into broad "northern" and "southern" clusters, and the authors conclude the following about Italians:

Conversely, Italy appears to be a zone of sharp differentiation over small distances. Some Italians cluster with the northern Europeans, whereas others fall into the southeastern grouping (fig. 4A).

Even though the text says no such thing, everyone automatically assumes that it's Northern Italians who are clustering with Northern Europeans, and that the observed pattern is representative of Italy's genetic structure. But in fact, the three individuals in question are Southern Italians, and the North-Central Italians (two Tuscans from the Coriell database) cluster even farther to the "south" than Sicilians:


Either way, the authors' conclusion is unfounded, because those few individuals are outliers that don't represent the average. In subsequent studies that have used larger sample populations and more genetic markers, all Italians cluster with other Southern Europeans according to geographical location, and are clearly distinguished from both Northern Europeans and Ashkenazi Jews. Even in a similar study from the year before, Seldin et al. (2006), there was no overlap between a sample of 86 Northern, Central and Southern Italians and various samples from farther north in Europe.

Although it is a bit surprising to find so many outliers in such a small sample, they're not unusual in and of themselves, and more often than not they're Northern and Central Europeans. In fact, in Bauchet's Figure 4A, you can see a German individual in the "southern" cluster, and different studies have shown similar outliers from Britain, France, Belgium, Scandinavia and Austria, among other places.

On a side note, it's also worth mentioning that non-Caucasoid admixture from Africa (Negroid) and Asia (Mongoloid) is as negligible in Bauchet's Italian samples as it is in the other European samples.

---------------
Bauchet et al. "Measuring European Population Stratification with Microarray Genotype Data". Am J Hum Genet, 2007.

Italians Are Genetically Distinct from Jews

It's often claimed that Italians, especially Southern Italians, cluster with Ashkenazi Jews. At the very least, that's backwards because it's Jews who have mixed origins, pulling them away from West Asia and toward Europe. That, and the correspondence between geographic and genetic distance, puts them closest to Southern Europeans. However, when enough markers are used (or the right kinds of markers) the two groups can be distinguished, just as each can be distinguished from others. Indeed, Ashkenazi Jews form their own unique cluster, while Italians belong to a broader Southern European cluster, expectedly plotting between Spaniards and Greeks.

Tian et al. (2009) sampled Lombards (ITN_N), Tuscans (TUSC), Sardinians (SARD) and Southern Italian-Americans from New York (ITN), as well as Ashkenazi Jews (AJA), and genotyped them for 300,000 autosomal SNPs:

The current study extends the analysis of European population genetic structure to include additional southern European groups and Arab populations. Even within Italy, the relative position of northern Italians compared with subjects from Tuscany is consistent with the general geographic correspondence of PCA results. Interestingly, the majority of Italian Americans (NYCP four grandparents defined) appear to derive from southern Italy and overlap with subjects of Greek heritage. Both of these observations are consistent with previous historical information.

Possible exceptions to this observation of geographic correspondence include the Ashkenazi Jewish population. While the Ashkenazi are clearly of southern origin based on both PCA and STRUCTURE studies, in our analyses of diverse European populations, this group appears to have a unique genotypic pattern that may not reflect geographic origins.

Price et al. (2008) sampled Southern Italians and Sicilians, and isolated the genetic markers that are most accurate for distinguishing between European groups, achieving results comparable to those from genome-wide analyses:

Important work has already shown that northwest and southeast Europeans can be distinguished using as few as 800-1,200 ancestry-informative markers mined from datasets of 6,000-10,000 markers. Here we mine much larger datasets (more markers and more samples) to identify a panel of 300 highly ancestry-informative markers which accurately distinguish not just northwest and southeast European, but also Ashkenazi Jewish ancestry. [...] Our results are consistent with a previous study in which Ashkenazi Jewish and southeast European samples occupied similar positions on the northwest-southeast axis, although there was insufficient data in that study to separate these two populations.

Tian et al. (2008) provide an additional example of the same clustering pattern, using samples and markers similar to those in their other study:

European population genetic substructure was examined in a diverse set of >1,000 individuals of European descent, each genotyped with >300 K SNPs. Both STRUCTURE and principal component analyses (PCA) showed the largest division/principal component (PC) differentiated northern from southern European ancestry. A second PC further separated Italian, Spanish, and Greek individuals from those of Ashkenazi Jewish ancestry as well as distinguishing among northern European populations. In separate analyses of northern European participants other substructure relationships were discerned showing a west to east gradient.

Minimal Demographic Impact of Roman Slavery

It's commonly thought that slaves made up a huge percentage of Italy's population during the Roman Empire, and that most were of foreign origin, eventually replacing the native Italians. Historian Nathan Rosenstein turns this conventional notion on its head by showing that previous estimates of slaves' numbers are all wrong, and that increases in urban populations were caused instead by migrants from rural areas of Italy. These findings are supported by DNA evidence that detects no significant change in Italy's gene pool from the Iron Age.

Recent studies of Italian demography have further increased doubts about a rapid expansion of the peninsula's servile population in this era. No direct evidence exists for the number of slaves in Italy at any time. Brunt has little trouble showing that Beloch's estimate of 2 million during the reign of Augustus is without foundation. Brunt himself suggests that there were about 3 million slaves out of a total population in Italy of about 7.5 million at this date, but he readily concedes that this is no more than a guess. As Lo Cascio has cogently noted, that guess in effect is a product of Brunt's low estimate of the free population in Italy in A.D. 14. That is, Brunt must assume that the slave population had come to comprise nearly 40 percent of the population of Italy by the time of Augustus because he believes that the nonservile population of Italy had only managed to stay even between 225 B.C. and A.D. 14. At the same time, however, the number of residents of cities and towns throughout the peninsula and especially of Rome itself was skyrocketing. Consequently, without the supposition that slaves made up a very high percentage of the total population, not enough people would have been left in the countryside to produce the food needed to feed those in the towns. The basis for the supposition that slaves in Italy numbered as many as 3 million by the reign of Augustus in other words really consists of nothing more than a kind of elaborate circular argument in which the low free population "explains" the high number of slaves, which in turn "explains" how there could be so few free men and women in Italy.

Brunt also advances the claim that the Romans owned about 500,000 slaves circa 212, which suggests that, in his opinion, the slave population of Italy might have seen an average annual net gain between then and the end of the first century B.C. of perhaps 12,500 individuals. But the starting point for postulating such a rapid rate of increase is also based on a similar piece of guesswork. After noting that, by his reckoning, the Romans had mobilized about 11 percent of their free population in that year and mentioning the comparisons that other scholars had made to the 10 percent of their populations that some Balkan states in 1913 and Germany in 1914 had mobilized, Brunt continues, "We have only to suppose that the Romans owned not far short of half a million slaves to reduce the proportion of men in the armies and fleets far below 10 percent, even after allowing that 20,000-30,000 slaves may have been used after 214 as rowers." In other words, a slave population of 500,000 is necessary to bring the ratio of men under arms to the civilian population down into a range that Brunt finds acceptable. He makes no attempt to discover what might constitute a maximum rate of mobilization for a society such as Rome's in this period except to state that productivity per person was lower than in Germany and the war lasted longer than the modern conflicts. Of course, the cost of equipping and maintaining an army was much lower for the Romans as were the economic requirements of the civilian population. And one might suppose that more men could be spared from a simple agrarian economy like ancient Rome's than from a complex industrial one like early twentieth-century Germany's.

Consequently, Brunt's figures offer no basis for assuming that a dramatic rise in the number of Roman slaves — and hence in the number of the plantations that employed them — was getting under way during the early second century. To be sure, Livy records a depressing litany of enslavements by Roman armies in the course of their conquests in this period. But it does not necessarily follow that these would have helped bring about the sixfold increase in the Roman slave population by the reign of Augustus that Brunt postulates. Given the usual assumption in modern scholarship that male slaves significantly outnumbered females, the slave population would have been incapable of reproducing itself at full replacement level. As a result, the Romans regularly had to import substantial numbers of new slaves just to keep the slave population from shrinking. Scheidel has shown that on the assumption that slaves in 225 numbered 500,000 and were declining by only 1 or 2 percent per year, far more new slaves would have been required simply to replace current slaves who died than to generate a net increase of 2.5 million in the total slave population by 25 B.C. As large as the enslavements of this period were, therefore, they cannot in and of themselves demonstrate a rapid rise in Italy's slave population along the lines Brunt supposes. It is also worth bearing in mind that not all of those whom Rome's armies captured will have wound up in Italy, for this by no means constituted the only market for slaves in the early second century. Agriculture and manufacture in Carthage, Sicily, and elsewhere in the Hellenistic world made extensive use of slave labor, and the same factors of imbalanced sex-ratios and low birthrates that created a very high demand for replacement slaves in Italy may well have been operating in these areas also.

However, one piece of negative evidence, to which Scheidel has also drawn attention, provides an intriguing hint that conventional estimates of slaves making up as much as 40 percent of Italy's population by the late first century B.C. may be far too high. An analysis of the genetic makeup of Italy's modern population argues that the various distinctive genetic combinations currently found in different regions within the peninsula by and large track the linguistic distribution that resulted from the migrations of the Iron Age. No data indicate the subsequent large-scale infusion of new genetic material into the populations of these regions except in the case of southern Italy and eastern Sicily, which is explained by the well-documented Greek migrations there. If this finding is correct, then the slave population of Italy even at its greatest extent must have been far smaller than Brunt imagined, perhaps no more than a million. Otherwise, one must suppose that a very large number of slaves existed but made no contribution to the peninsula's genetic composition because they simply failed to reproduce themselves. Yet a very large number of slaves, on the order of 3 million, presupposes that this population was fairly successful at reproducing itself because it could never have reached that size in the first place and then maintained those numbers for centuries through imports alone. As already noted, the majority of new slaves brought into a servile population that was not reproducing itself completely would only have replaced old slaves who had died. But if a population of 3 million slaves, representing as much as 40 percent of Italy's inhabitants in the first century B.C., was successfully reproducing itself, it would surely have left its mark on the genetic makeup of contemporary Italians. That it did not argues strongly for a very low rate of natural reproduction among Italy's slaves, which in turn is difficult to reconcile with the hypothesis that the number of slaves ever grew large enough to comprise 40 percent of the Italian population.

If a dramatic rise in Italy's servile population during the second and first centuries is beginning to appear increasingly questionable, the decline in the numbers of free men and women that is supposed to have been its corollary is also being viewed with a growing skepticism. The census returns of 70 and 28 B.C. represent the linchpin for this pessimistic assessment of the condition of Italy's smallholders. For many years Brunt's powerful defense in Italian Manpower of Beloch's view that these totals demonstrate a drop in the free population of Italy remained unchallenged, even though the numbers themselves, around 900,000 in 70 and over 4 million in 28, would seem to reflect precisely the reverse. But Beloch and Brunt argue that the latter figure represents free men, women, and children, whereas the censors in 70 had counted only adult male citizens. When the totals are adjusted and allowances made for enfranchisements between 70 and 28 and citizens overseas, the result is a net decline in the free population. When these figures are in turn compared with the census returns of 225, the general regression in Italy's free population becomes patent, a regression that Brunt traces to the damage that Rome's wars and the importation of slaves inflicted on Italy's farmers.

In a provocative article, Lo Cascio has asked how it is possible to make demographic sense out of the Beloch-Brunt thesis. The argument they advance must assume that the population between 70 and 28 was declining annually by .5 percent, and the implications of such a decline, Lo Cascio believes, are unacceptable. Beyond question, the urban population of Italy increased dramatically during the middle of the first century, and any rise in urban numbers, with the possible exception of Rome itself, had to come from the rural population. In the preindustrial world, however, an urban population does not grow without a sustained growth in the rural free population whose economic products support it. Thus Lo Cascio argues that unless we are prepared to suppose that the ratio of urban to rural dwellers in Italy between 70 and 28 was far in excess of preindustrial norms — and there is no good reason to do so — the Beloch-Brunt interpretation of the census total for 28 cannot be made plausible. For it must assume that a dramatic and unparalleled drop in Italy's nonurban population was occurring at a time of unprecedented urban growth. Consequently, the figure of 4 million must represent only adult, male citizens just as had been the case in earlier republican censuses. If that is so, then as Tenny Frank long ago argued, the free population of Italy must have been growing vigorously during the second and first centuries.

Lo Cascio's article certainly will not be the final word on the controversy surrounding Beloch's and Brunt's thesis, but the mere fact that this critical prop is now being challenged renders claims about a crisis among Italy's small farmers due to war and the introduction of plantation agriculture all the more open to question. From a different perspective, Morley, too, has raised additional doubts about the conventional view. He notes that the populations of early modern cities generally could not reproduce themselves; they depended instead upon a large, steady influx of immigrants from the countryside to reach and then to maintain their size. Rome, he believes, would have been no different. Therefore the swelling of the city's inhabitants to nearly a million over the course of the second and first centuries B.C. and the stability of their numbers at roughly that level over the ensuing centuries cannot be attributed to a single, discrete event like the displacement of smallholders after the Hannibalic War. Such an episode would create a temporary increase, but then the process would slow, perhaps even reverse course, and the city would shrink as its population gradually died off.

Nathan Rosenstein. Rome at War: Farms, Families, and Death in the Middle Republic. Chapel Hill: University of North Carolina Press, 2004.

Refuting Richard Lynn's Italian "IQ" Study

Controversial psychologist Richard Lynn, who looks at IQ and its correlates, has published a study claiming to show regional (North-South) differences in intelligence within Italy, which he attempts to correlate with achievement and attribute to admixture. The guy's been called just about every name in the book, and he can now add Padanian Nordicist to that list.

Intelligence

Generally speaking, Lynn is not to be trusted. He's been caught numerous times falsifying and manipulating data to fit his conclusions (e.g. here, here, here, here, here and here), and it looks like he's up to his old tricks again.

This time around, he's not even using actual IQ data, but the proxy of scores on reading, math and science tests administered to 15-year-olds (PISA 2006). So he's attempting to quantify innate general intelligence by looking at the academic performance of school kids, a measure that to a large extent involves learned knowledge and other factors. Indeed, while some researchers report a strong correlation between general intelligence and educational attainment, one of Lynn's own sources, Deary et al. (2007), addressing two of his other sources, suggests that caution should be exercised when attempting to equate the two:

There are various possible causes of the cognitive ability-educational achievement association. Bartels et al. (2002b) found a strong genetic correlation between cognitive ability (measured at 5, 7, 10, and 12 years) and educational achievement at age 12. In an overview, Petrill and Wilkerson (2000) concluded that genetics and shared and non-shared environmental factors all influence intelligence and education, with genetics being important in the correlation between them, and non-shared environment being important in discrepancies between intelligence and educational attainments.

Whereas the correlations indicate that around 50% to 60% of the variance in GCSE [General Certificate of Secondary Education] examination points score can be statistically explained by the prior g [general intelligence] factor, by the same token a large proportion of the variance is not accounted for by g. Some of the remaining variance in GCSE scores will be measurement error, but some will be systematic. Thus, non-g factors have a substantial impact on educational attainment. These may include: school attendance and engagement; pupils' personality traits, motivation and effort; the extent of parental support; and the provision of appropriate learning experiences, teaching quality, school ethos, and structure among other possible factors (Petrides, Chamorro-Premuzic, Frederickson, & Furnham, 2005; Strand, 2003).

But Lynn already knows the pitfalls of his approach. Finland had the highest score in Europe on the 2006 PISA tests, and using his method leads to a calculated IQ of 107, yet he reports Finns' IQ as being just 97. Romanians' PISA score is near the very bottom of Europe, leading to an estimate of 85, though their measured IQ is in fact 94 according to Lynn, just three points lower than that of Finns. With discrepancies like that, there's absolutely no reason to trust his calculated IQs of around 100 and 90 for Northern and Southern Italians. Clearly, PISA scores are not a good substitute for IQ.

Then, to try to prove that disparities in intelligence are long-standing, and therefore genetically based, he uses literacy as another (questionable) proxy for IQ. But whereas for other correlates like stature and infant mortality he includes data from the past and present to show that the North-South gap has remained fairly stable, for literacy he only includes data from 1880, when it was extremely large (55% vs. 20%, on average). Obviously, he wants to hide the fact that the gap has been closing steadily since then, and by the 21st century, literacy among Italians under the age of sixty-five was 99.7% in the North and 99% in the South (Istat 2001).

Achievement

Lynn goes on to attempt to correlate his fake IQs with achievement. The primary measure he uses is per capita income, which is double in the North what it is in the South. His source is the Italian Statistical Office, but he should be aware that figures for the South's economic performance are greatly underestimated because the official statistics fail to take into account a large underground economy there, according to Burnett and Vaccara (1999):

But the third factor, somewhat alleviating the second, is the existence of a far vaster private sector than ever shows up in the economic statistics. The size of the lavoro nero sector and the black market in the South clearly exceeds that of any other EU region.... In Calabria, with its dire employment figures, 84 percent of the families own their own home. What such anomalies must mean is that real income in Calabria is far higher than what is "on the books." Many among the vast numbers of officially unemployed are, in fact, partly or fully employed. They are earning no social benefits, but they are earning the daily lire that keep their families afloat. [...] A very large part of the South's hidden labor is made up of entrepreneurs, sometimes also employing black labor, and existing themselves outside official recognition, taxation, protection, control, or counting. A recent analysis concludes that "there exists in several zones of the Mezzogiorno [Southern Italy] a whole fabric of small and very small businesses that escape every census, but that work and make profits, share among themselves a serious level of production, export to other regions [of Italy] and abroad." [...] This massive sector skews all the statistics. It means that the GDP for the Italian South (and for Italy as a whole) is far from accurate. And the unemployment figures do not reflect reality.

Then, with the same goal of establishing a pattern that extends far back in time, he also looks at historical achievement, citing Charles Murray's Human Accomplishment. But here again he plays fast and loose with the data. He adds up Murray's "significant figures" for Italy from 1400-1950 and divides them into "North", "Center" and "South" based on their origins. Almost all of them (187 out of 236) come from the "North". However, he explains that he uses the 42nd and 41st lines of latitude as borders, which are, respectively, just north of Rome and just north of Naples. So more than half of the country is put into the "North" category, while the "Center" gets flattened down and pushed into the territory of the "South" (click here to see what that looks like). This is a shameless and transparent ploy by Lynn to hugely inflate the number of significant figures from the "North" and reduce the number elsewhere in the country.

But perhaps even worse, he ignores the main finding of Murray's book, which is that achievement has been concentrated in just a few places, and Southern Italy is but one of many "low-achievement" areas throughout Europe, along with some of the northernmost regions in Italy:


As you can see — and as Murray points out in his book — the highest ranking region is Tuscany, which would normally be considered part of Central Italy. Ironically, Lynn doesn't even have PISA/IQ data for Tuscany, though its 1880 literacy rate isn't particularly high. So he's basically attributing the unique genius of that region to the brainpower of regions that have not produced the same level of genius.

Admixture

Finally, Lynn offers his "explanation" for the disparities in fake IQ, which, unsurprisingly, turns out to be admixture from the Middle East and North Africa, where (according to him) IQs are in the range of 80-84. As you might expect from someone with an agenda and little knowledge of genetics, he references a lot of old studies that use single or small numbers of loci and don't directly address the question of admixture. One of them has "Neolithic demic diffusion in Europe" in its title, yet he stupidly follows the citation with references to historical groups like Phoenicians and Arabs.

Recent genome-wide studies have been able to detect and quantify admixture like never before. Li et al. (2008), using more than 600,000 autosomal SNPs, identify seven global population clusters, including European, Middle Eastern and Central/South Asian. Contrary to Lynn's claims, it's actually the overachieving Tuscans who have a small amount of non-European admixture and not the underachieving Sardinians:


López Herráez et al. (2009) typed the same samples at close to 1 million SNPs and analyzed them in a Western Eurasian context, identifying a number of subclusters. This time, all of the European samples show some minor admixture. Among the Italians, Tuscany still has the most, and Sardinia has a bit too, but so does Lombardy (Bergamo), which is even farther north:

Conclusion

The bottom line is, we don't know the average IQs for different regions in Italy, which is why Richard Lynn had to resort to making them up. And while Southern Italians are likely to be a few points lower than Northern Italians — as the Irish and Scottish are a few points lower than the English — there's absolutely no reason to believe that North and South would be separated at their extremes by almost a full standard deviation. Lynn certainly hasn't proven anything of the kind with this ridiculous study, nor has he provided any valid explanations for such a disparity.

Updates

Since I wrote this article, a number of studies have been published that refute Lynn and confirm what I've said:

• Cornoldi et al. (2010) and Beraldo (2010)
• Felice and Giugliano (2011)
• Daniele and Malanima (2011)
• Robinson et al. (2011)
• D'Amico et al. (2012)
• Templer (2012)
• Cornoldi et al. (2013)

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Richard Lynn. "In Italy, north-south differences in IQ predict differences in income, education, infant mortality, stature, and literacy". Intelligence, 2010.