The Genetic Origin of Daunians and the Pan-Mediterranean Southern

Home , Daunians, David Reich (geneticist), Iapygians, Italian Peninsula, Messapians, Ordona

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1 The genetic origin of Daunians and the Pan-Mediterranean

2 southern Italian Iron Age context

3 Serena Aneli1§*, Tina Saupe2§, Francesco Montinaro3, Anu Solnik4, Ludovica Molinaro2, Cinzia

4 Scaggion5, Nicola Carrara6, Alessandro Raveane7, Toomas Kivisild2,8, Mait Metspalu2, Christiana

5 L Scheib2,9†, Luca Pagani1,2†

6 Summary

7 The geographical location and shape of Apulia, a narrow land stretching out in the sea at

8 the South of Italy, made this region a Mediterranean crossroads connecting Western Europe and

9 the Balkans. Such movements culminated at the beginning of the Iron Age with the Iapygian

10 civilization which consisted of three cultures: Peucetians, Messapians and Daunians. Among them,

11 the Daunians left a peculiar cultural heritage, with one-of-a-kind stelae and pottery, but, despite

12 the extensive archaeological literature, their origin has been lost to time. In order to shed light on

13 this and to provide a genetic picture of Iron Age Southern Italy, we collected and sequenced human

14 remains from three archaeological sites geographically located in Northern Apulia (the area

1 Department of Biology, University of Padua, Via Ugo Bassi, 58b, Padova 35121, Italy 2 Estonian Biocentre, Institute of Genomics, University of Tartu, Riia 23B, Tartu 51010, Estonia 3 Department of Biology-Genetics, University of Bari, Via E. Orabona, 4, Bari 70124, Italy 4 Core Facility, Institute of Genomics, University of Tartu, Riia 23B, Tartu, 51010 Estonia 5 Department of Geosciences, University of Padua, Via Giovanni Gradenigo, 6, Padova 35131, Italy 6 Anthropology Museum, University of Padova,Via Giotto, 1, Padova 35121, Italy 7 Laboratory of Hematology-Oncology, European Institute of Oncology IRCCS, Milan, Italy. 8 Department of Human Genetics, KU Leuven, Leuven, Herestraat 49, B-3000, Belgium 9 St John’s College, Cambridge, CB2 1TP, United Kingdom § These authors contributed equally † Senior Author *Lead Contact: Serena Aneli ([email protected]) Corresponding author: [email protected] 1

15 historically inhabited by Daunians) and radiocarbon dated between 1157 and 275 calBCE. We find

16 that Iron Age Apulian samples are still distant from the genetic variability of modern-day Apulians,

17 they show a remarkable genetic heterogeneity, even though a few kilometers and centuries separate

18 them, and they are well inserted into the Iron Age Pan-Mediterranean genetic landscape. Our study

19 provides for the first time a window on the genetic make-up of pre-imperial Southern Italy, whose

20 increasing connectivity within the Mediterranean landscape, would have contributed to laying the

21 foundation for modern genetic variability. In this light, the genetic profile of Daunians may be

22 compatible with an autochthonous origin, with plausible contributions from the Balkan peninsula.

23 Introduction

24 The Mediterranean’s Iron Age populations, between 1100 and 600 BCE, lived in a time of

25 previously unprecedented connectivity1. Although the technological advances in seafaring had

26 allowed great opportunities for long-distance mobility just a few millennia earlier, it was during

27 the Iron Age that the cosmopolitan role of Mare Nostrum arose, by promoting the spreading of

28 cultures, goods, languages, technical advances as well as heterogeneous ancestral genetic

29 components coming from far and wide1,2. Notable examples of such distant connections are the

30 Greek and Phoenician settlements across the Central and Western Mediterranean shores beginning

31 from the ninth and eighth centuries3,4.

32 The Italian peninsula and its Tyrrenian islands, where the Iron Age is conventionally

33 marked as beginning 950 BCE1,5, joined as well the cosmopolitan wave sweeping across Southern

34 Europe, by hosting numerous trading posts along its shores. A patchwork of communities appeared

35 in this period within the Italian borders, each characterized by unique and well-defined cultures

36 and identities, which were later encapsulated and blurred by the Roman colonization. The shift

37 from Republican to Imperial Rome, with the consequent inclusion of non-Roman civilizations

38 from and beyond the Italian peninsula, has already been shown to be connected with a major

39 eastward genetic shift in Central Italian samples6. Genetic material from Imperial Romans from

40 Central Italy is indeed the first to co-localize with contemporary Italians in a Principal Component

41 space, pointing to this time period (~200 BCE) as a crucial one in shaping contemporary Italian

42 genetic makeup. Whether such a shift can also be observed in the rest of the Italian peninsula and

43 how the Republic to Imperial transition may have impacted on the genetic landscape of local, pre-

44 Roman populations remains an open question.

45 Despite the numerous written records and archaeological findings, questions about Iron

46 Age populations, their origins and mutual relationships remain. Among the many groups

47 occupying Italy in the Iron Age, the Daunians, a Iapygian population from northern Apulia, were

48 first mentioned in the 7th-6th century BCE7,8. Similarly to their neighbouring populations,

49 Peucetians and Messapians (living in central and southern Apulia, respectively), the name of the

50 Daunians comes from ancient Greek documents and, given the absence of written Daunian records,

51 the scant information we have on their social, political and religious life are wholly reliant upon

52 the material record, such as their one-of-a-kind stelae8. For instance, we know that they were

53 mainly farmers, animal breeders, horsemen and maritime traders with an established trade network

54 extending across the sea with Illyrian tribes8–10. A fascinating aspect of this population, as opposed

55 to their neighbours in Apulia, was their tenacious resistance to external influences. For instance,

56 they did not acquire either social or cultural Hellenic elements and no Greek alphabet inscriptions

57 have been found in their settlements. Indeed, they retained a strong cultural identity and political

58 autonomy until the Roman arrival in the late 4th - early 3rd century BCE8.

59 Despite the extensive archaeological literature, their origin has been lost to time and, as

60 early as in the Hellenistic period, various legends already existed connecting them to either Illyria

61 (an ancient region broadly identifiable with the Balkan peninsula), Arkadia (present-day

62 Peloponnesus) or Crete7,8.

63 To shed light on this population and provide a glance of the Iron Age genetic landscape of

64 the Southern Italian peninsula, we collected human remains from three Iron Age necropoleis

65 geographically located within the area historically inhabited by Daunians: Ordona (ancient

66 Herdonia), one of the largest settlements estimated at 600 hectares8, Salapia, and San Giovanni

67 Rotondo (Figure 1A). Here, we provide for the first time a genetic investigation of Iron Age

68 Apulian associated with the Daunian culture, offering insight into the genetic landscape of pre-

69 Imperial Southern Italy.

70 Results

71 We extracted DNA from 34 human skeletal remains (petrous bone = 23 and teeth = 11)

72 from three necropoleis (Ordona = 19; Salapia = 12; San Giovanni Rotondo = 3; hereafter ORD,

73 SAL and SGR, respectively) at the Ancient DNA Laboratory of the Institute of Genomics,

74 University of Tartu in Estonia (Data S1A). All three necropoleis are geographically located less

75 than 50 km from each other in modern Apulia, Southeastern Italy. Ordona and Salapia are

76 archaeologically dated to the Daunian period (6th-3rd century BCE) except one individual

77 (ORD010) archaeologically dated to the Medieval time period (which in Europe dates

78 approximately from the 5th to the late 15th century CE) (Figure 1B). Based on the museum record,

79 the samples from the San Giovanni Rotondo necropole have been archaeological inferred to be

80 from the Iron Age period. After screening 21 libraries at a low depth (±20M reads per library), we

81 additionally sequenced to higher depth 16 libraries with endogenous DNA between 1.81 - 38.82%

82 and mitochondrial DNA-based (mtDNA) contamination estimated at less than 2.89% (Data S1A).

83 The sequencing runs were merged resulting in 16 individuals for genome-wide analysis:

84 eight from Ordona, five from Salapia, and three from San Giovanni Rotondo. The final dataset

85 includes individuals with an average genomic coverage between 0.031 - 0.995× and a number of

86 single nucleotide polymorphisms (SNPs) overlapping with Human Origins 1240k between

87 ~40,000 and ~810,000 (Data S1A).

88 Out of those 16 individuals, we selected 10 individuals based on their proximity within the

89 principal component analysis (PCA) space (Figure 1C) for radiocarbon dating and estimated their

90 age between 1157 and 275 calBCE with a median date of 521 calBCE (Data S1B). The radiocarbon

91 dates confirm the archaeological dates of individuals from Salapia and Ordona as well as the Iron

92 Age affiliation of the two San Giovanni Rotondo samples (SGR002 and SGR003). Two additional

93 samples (ORD010 and SGR001) with a shift towards the Near East in the PCA (Figure 1C) were

94 radiocarbon dated to 1078 - 1156 calCE (95.4%) and 670 - 774 calCE (95.4%) respectively

95 (Data S1B). Based on their dates, the samples were used as an external control for further analyses

96 focusing on Iron Age Apulia (IAA).

97 We determined the mitochondrial DNA (mtDNA) haplotype of each individual and the Y

98 chromosome (Ychr) haplogroup for 9 male individuals (See STAR methods and Data S1A and

99 S1C-D). We found that the mtDNA haplotypes mostly belong to the mtDNA lineages H1, H5, K1,

100 and U5, haplotypes found in previous studies of individuals from this time period in the Italian

101 Peninsula6. Besides the Ychr haplogroup R1b, which is the most frequent haplogroup during the

102 Bronze Age in the Italian Peninsula and on the islands Sardinia and Sicily4,6,11–13, we found the

103 Ychr lineages I1-M253, I2d-M223, and J2b-M241. The haplogroup I2d-M223 was one of the main

104 Y chromosome lineages in Western Europe until the Late Neolithic whereas J2b-M241 first

105 appears in the Bronze Age3,4,12,14,15. We found one Early Medieval individual (SGR001 (670 - 774

106 calCE (95.4%)) belonging to haplogroup I1-M253, which is common in Northern Europe and

107 previously also detected in a 6th Century Langobard burial from North Italy 16.

108 We used READ17 to identify pairs with first or second degree of genetic relatedness from

109 autosomal data (See STAR methods and Data S1E-H for details, Figure S11). We found one first-

110 degree relationship between the two female individuals ORD001 (age: 9 - 11 years, 651- 544

111 calBCE (95.4%)) and ORD009 (age: 40 - 45 years, 570 - 406 calBCE (95.4%)) from Ordona

112 sharing the identical mtDNA haplogroup H5c and indicating a mother-daughter relationship

113 (Data S1, Figure S1A-B).

114 The making of modern Italians

115 To explore the genetic make-up of the IAA population, we performed a PCA projecting

116 the ancient individuals onto the genetic variation of modern Eurasian samples (Figure 1C, Data S2

117 and Data S3). Our samples are largely scattered between modern peninsular Italians and

118 Sardinians, and, in contrast to what was generally described18,19 for other European Iron Age

119 populations (e.g., Northern_Europe_IA, Western_Europe_IA and Levant_IA in Figure 1C), they

120 are still clearly distant from the genetic variability of modern-day inhabitants of Apulia. The

121 downward shift of Iron Age Apulians from the present-day ones is further confirmed by the

122 significantly negative f4(Modern Apulians, IAA; X, Mbuti), where X is a

123 Neolithic/Chalcolithic/Copper Age population (Figure 2A, Data S4). Within the remarkable

124 heterogeneity reported by the PCA, which does not mirror the archaeological sites, the two

125 medieval individuals are shifted towards modern Middle Eastern and Caucasus populations

126 (ORD010 and SGR001), while the others are stretched along the PC2. This pattern partially

127 mirrors the chronological date with the most recent being more similar to present-day Southern

128 Europeans, and is further strengthened when considering the PC3 distribution (Figure S2). Three

129 samples located at the bottom of the PCA (ORD004, ORD019, SAL007) and one (SAL010) falling

130 in the middle did not include modern Apulians among the top 25 results of an f3 outgroup analysis

131 (Figure S3). All of them showed an affinity to Copper and Bronze Age Italians11 as well as the

132 Aegean and the Mediterranean worlds (including Minoans, Greece, Croatians, and Gibraltar). A

133 similar distribution is mirrored in the Multi-Dimensional scaling (MDS) built from the f3 outgroup

134 measures, where the oldest IAA individual (SAL001; 1235 - 1048 calBCE (95.4%)) lies farthest

135 from the modern samples, while the medieval ones (ORD010: 1078 - 1156 cal CE (95.4%) and

136 SGR001: 670 - 774 cal CE (95.4%)) are the closest (Figure S4).

137 The peculiar positioning of the IAA individuals casts doubt on when the major population

138 shift resulting in modern Italian genetic composition took place. The shift towards the modern

139 Italian genetic variability can be seen with the Republican-Imperial Roman samples6, the latter

140 being more “similar” to modern Italians (Figure 1C). Whether Apulian individuals dating back to

141 the Imperial phase would also show a repositioning towards modern genetic variability remains an

142 open question, although the later, medieval samples of this study point in that direction.

143

144 The pan-Mediterranean genetic landscape of Iron Age Apulia

145 The geographic location of Apulia, a narrow peninsula stretching out in the sea at the South

146 of Italy, has made this region an important Mediterranean crossroads connecting Western Europe,

147 the Balkans, the Aegean, and Levant worlds. This is reflected in the PCA where IAA individuals

148 are closely related to other Iron Age populations from the Mediterranean and surrounding areas

149 (e.g., Montenegro, Bulgaria and Sardinia) (Figure 1C and Figure S4). Nomadic or cosmopolitan

150 groups scatter like IAA: three Punic individuals from Sardinia (Italy_Sardinia_IA_Punic3), three

151 Moldova Scythians already reported to be genetically similar to Southern Europeans20, Spanish

152 individuals from the Hellenistic and the Romans periods21 and an individual from the 12th century

153 Iron Age Ashkelon22 which clusters with ORD001.

154 In order to shed light onto the genetic composition of the IAA individuals, we modelled

155 them as a combination of the main ancestries documented across Western Europe at that time:

156 Western Hunter-Gatherers (WHG), Anatolian Neolithic (AN), Steppe-related and,

157 interchangeably, Caucasus Hunter-Gatherers (CHG) or Iranian Neolithic (IN) using the

158 qpWave/qpAdm framework (Figure 2B, Figure S5A, STAR Methods). Broadly, the contributions

159 of such ancestries to the genetic variability of ancient European populations vary according to their

160 geographical positions: in particular, northernmost locations received higher proportions of WHG,

161 Steppe-related ancestry and, consequently, CHG ancestries, while Southern European groups

162 carried variable Iranian Neolithic or CHG traces23. In view of this, we observed that while the IAA

163 individuals could generally be modelled as a two-way admixture between AN and Steppe

164 (0.63±0.08 and 0.37±0.08, respectively), the alternative model AN + CHG/IN could also fit for a

165 subset of them, particularly in case of the samples ORD004, ORD010 and SAL010 with higher or

166 comparable p-values (Figure S5A, first row with two sources). When three or four sources were

167 tested, the presence of WHG ancestry in the majority of our individuals emerges, which, together

168 with AN, Steppe and CHG/IN, forms a supported model for IIA samples (Figure 2B, Figure S5A

169 and Data S5). Notably, for the individuals stretching downwards in the PCA (ORD004, ORD019,

170 SGR002 and the Medieval ORD010) a three-way admixture involving AN, Steppe and CHG/IN

171 is generally preferable. To better understand the putative contribution of more recent populations,

172 we modelled our samples with base sources (WHG, AN, Steppe-related and CHG/IN) and,

173 alternatively, Minoans (Odigitria and Lasithi), Amhara_NAF and Roman Republicans (Figure 2C,

174 Figure S5B-D, STAR Methods). Amhara_NAF can be used as a proxy for the Non-African

175 component in modern Ethiopian individuals that was tentatively linked to the Sea People, a Bronze

176 Age nomadic seafaring population22,24. Together with Minoans and Roman Republicans, this

177 component can be broadly modelled as a Pan-Mediterranean population (constituted by AN and

178 IN/CHG components) with the addition of WHG and Steppe-related ancestry in Roman

179 Republicans. When modelled also with Minoans and Amhara_NAF, which roughly proxies the

180 same ancestral signature, the majority of the samples required an additional CHG/IN contribution

181 (two-way admixtures in Figure S5B,C) as well as Steppe-related and WHG. We further observed

182 that, as previously seen, the WHG contribution is less clear in those samples stretching downwards

183 in the PCA. While the CHG/IN additional contribution may simply proxy the presence of Steppe-

184 related ancestry in IAA, the absence of which in Minoans has already been reported25, the same

185 can not be said about Roman Republicans (two-way admixtures in Figure S5D), which harboured

186 a considerable amount of Steppe component6. However, this signature is not confirmed with f4

187 analyses (Figure S6 B,C), where just Mycenaean groups report less CHG ancestry than our

188 samples.

189 The broader picture emerging from qpAdm analyses is the pervasive presence of coeval

190 Italian ancestries (Rome Republicans), as well as previous Bronze Age sources (Minoans and Sea

191 People) spread far and wide across the Mediterranean Sea. In such a melting pot scenario, the

192 peculiar genetic heterogeneity of IAA individuals, who lived in close temporal and geographical

193 proximity, stand out (Figure 1C, Figure S4, Figure S7). An example of the cosmopolitan nature of

194 Iron Age Mediterranean is the first-degree relationship between ORD009 (mother) and ORD001

195 (daughter), whose positions in the PCA strikingly differ with the individual ORD001 being

196 stretched towards Middle Eastern and Caucasus modern populations, as a consequence of the

197 foreign origin of the father (Figure 1C and Figure S4). F4 analyses in the form f4(ORD009,

198 ORD001; X, Mbuti) report a slightly significant (Z-score between -2 and -3) excess of Greece_N,

199 Portugal_LN_C, Lebanon_Roman and Italy_Sicily_EBA in ORD001, which may explain its

200 eastward shift (Figure S8A). Moreover, ORD001, together with SGR002, but not ORD009

201 harboured more CHG when compared to Lebanon_Hellenistic and Lebanon_IA3 samples,

202 respectively (Figure S8C), as well as an increase in Lebanon_Hellenistic traces when compared

203 with modern Apulians (data not shown).

204 We also investigated whether the PCA scattering was due to varying African or Levantine

205 contributions with f4(Rome Republican, IAA, Levant_N/YRI, Mbuti) and tried the same on

206 Medieval ancient Apulians (ORD010 and SGR001). However, none of the tested ancient Apulians

207 shows a significant excess of YRI ancestry when compared to the contemporary Roman

208 Republicans, even though ORD014, SAL007 and SAL011 show negative f4 values with a Z-score

209 between 2 and 3 (Figure S8B).

210

211 The origin of Daunians

212 The genetic heterogeneity of IAA individuals connected to the Daunian population and the

213 cosmopolitan landscape of Iron Age Mediterranean populations hinder a full reconstruction of the

214 demographic processes leading to the Daunians. Nevertheless, a few milestones can be spotted.

215 When we performed f3 analyses to investigate the nearest possible source for each IAA

216 individual using Minoans, Iron Age Croatians and the local Roman Republicans (Figure 3A), we

217 found that none of the IAA individuals shows higher affinities with Minoans. Three of them,

218 clustered close to modern Italians in the PCA (ORD001, ORD014 and SGR003, Figure 1C), show

219 higher affinity with the Iron Age Croatian sample (ORD004 followed this pattern too, but with

220 lower f3 values). However, the remaining majority are closest to the Roman Republicans, which

221 can be interpreted as representative of local Iron Age peninsular Italy ancestry.

222 Moreover, the WHG contribution, which was a necessary component to explain IAA and

223 Roman Republicans according to qpAdm output, is absent from Minoans and Iron Age Croatians,

224 thus making it a putative signature of an at least partial autochthonous origin (Figure 2B,C and

225 Figure S5). These results are confirmed for Minoans, but not for Croatia_EIA, by the f4 analyses

226 (Figure 3B, Figure S6A and Data S6). Indeed, the significantly negative f4(Minoans, IAA; WHG,

227 Mbuti) (Figure 3B and Figure S6A), as well as the

228 f4(Greece_Minoan_Lassithi/Greece_BA_Mycenaean/Greece_BA_Mycenaean_Pylos, IAA; X,

229 Mbuti), reported a significant excess of WHG ancestry (X being Tagliente2, Loschbour,

230 Italy_Central_M, Switzerland_Bichon and so on) in all IAA individuals, with the exception of

231 ORD004, SAL001 and SGR003 (also the medieval samples ORD010 and SGR001 deviate from

232 this pattern, Data S6). An excess of Bronze Age Steppe-related component, which at that time was

233 already present along the Italian peninsula11, was clearly present in SGR002, ORD006 and

234 ORD009 by the f4(IAA, Greece_Minoan_Lassithi; X, Mbuti) (Data S6).

235 The excess of WHG ancestry, tentatively suggesting a local origin, is somewhat blurred by

236 the genetic similarity of the two most probable sources - Illyrians (Croatia EIA) and an

237 autochthonous one (Roman Republicans), which together make part of the same Mediterranean

238 continuum. Indeed, while no significantly negative f4(Croatia_EIA, IAA; X, Mbuti) values have

239 been found (with the exception of X being Italy_C_BA, Italy_Iceman_CA, Portugal_MBA and

240 Anatolia_MLBA in SAL007, which retains the highest proportion of AN in qpAdm (Figure 2B

241 and Figure S5), the same pattern is obtained when IAA individuals are compared with Roman

242 Republicans (f4(Roman Republicans, IAA; X, Mbuti), (Data S6)). Imperial individuals from a few

243 centuries later (f4(Rome_Imperial, IAA; X, Mbuti)) show quite the opposite pattern: no positive

244 results have been produced with the exception of ORD004 (X=Lebanon_Roman), SAL001

245 (X=Italy_Sardinia_Roman_o), SAL010 (X=Russia_LateMaikop) and ORD010. Conversely, the

246 negative f4 values point toward WHG, Neolithic and Bronze Age Steppe-related ancestries

247 (Data S6).

248 Another signal coming from qpAdm analyses is the apparent excess of CHG ancestry in

249 IAA; however, the predominant contribution of CHG to the Steppe-related ancestry that, by the

250 Iron Age, had already spread to the Mediterranean area makes it hard to properly detect a CHG

251 signature independent from the Steppe wave, possibly brought by pan-Mediterranean influxes.

252 When directly investigated with an f4 framework, IAA shows generally more CHG than

253 Mycenaean, less CHG than contemporary Croatian_EIA and, in some cases (ORD019, SGR002

254 and the Medieval SGR001 with Z-scores higher than 2) more CHG than older Croatian samples

255 (_N and _MN) (Figure S6).

256 Discussion

257 The new genomic sequences Daunian samples reveal that Iron Age (pre-Imperial)

258 Southern Italy (Apulia) can be placed within a Pan-Mediterranean genetic continuum that stretches

259 from Crete (Minoans25) and the Levant (Sea People22,24) to the Republican Rome and the Iberian

260 Peninsula6, mainly composed by AN and IN/CHG genetic features with the addition of WHG and

261 Steppe-related influences in Continental Italy. Pre-Imperial Italian populations, being part of this

262 broader landscape, are not directly superimposable with contemporary Italians which instead seem

263 to be influenced by the homogenizing effect of Imperial Roman and late Antiquity events.

264 Within the described Pan Mediterranean landscape, the IAA/Daunians show a compelling

265 heterogeneity, and the highest genetic affinity to Republican Romans and Iron Age Croatians,

266 while Minoans and other Iron Age Greek samples show absent or reduced WHG contribution when

267 compared to IAA. This makes a Cretan or Arkadian origin less likely, even though some tales have

268 connected them with the Greek hero Diomedes and many ancient historians have claimed such

269 origins for their neighbour Messapians and Peucetians.

270 The Daunians maintained strong commercial and political relations with the Illyrian

271 people, controlling together the area spanning from the Dalmatia to the Gargano peninsula10 and

272 had many cultural affinities with them26. The material culture, involving peculiar anthropomorphic

273 statue stelae, has provided some information on Daunian culture and may also help in unravelling

274 their mysterious origin. In particular, the forearm decorations on a female stela have been

275 interpreted as tattoos and, while tattooing practices were considered barbarian among the Greeks27,

276 they were customary in populations from Tracia and Illyria and, more generally, among the women

277 of status from the Balkans8,28.

278 It is not clear whether these connections indicate a movement of people or a sharing of

279 cultural ideas and a conclusive answer to the origin of the Daunians remains elusive. From a

280 parsimony perspective, the genetic results point to an autochthonous origin, although we cannot

281 exclude additional influences from Croatia (ancient Illyria), as described by available historical

282 sources and by the material remains8,29.

283

284 Table

285 Table 1. Archaeological information, dating, genome coverage, genetic sex, mtDNA, and Y chromosome 286 haplogroups of the individuals of this study selected for genome-wide analysis. Dates in BP are raw 287 radiocarbon dates, calibrated dates are the 95.4% probability and were calibrated using IntCal2030. Gen.- 288 genetic; HG-haplogroup. See also Data S1. 289

Y no. of Genome Gen. mtDNA chromosome SNPs

Coverag Individual Site Date Sex HG HG e

2516 ± 25 BP; 651- ORD001 Ordona 0.0396 XX H5c - 53,277 544 calBCE

2374 ± 21 BP; 490 - ORD004 Ordona 0.0429 XX U8b1b1 R1b-M269 56,070 394 calBCE

2476 ± 29 BP; 770 - ORD006 Ordona 0.12 XY H+16291T - 158,562 476 calBCE

2433 ± 27 BP; 570 - ORD009 Ordona 0.995 XX H5c - 805,966 406 calBCE

984 ± 25 BP; 1078 - ORD010 Ordona 0.91 XX X2i - 769,336 1156 calCE

ORD011 Ordona not dated 0.0889 XY H1e R1b-P312 116,800

2438 ± 25 BP; 570 - ORD014 Ordona 0.108 XY I5a2+16086C J2b2-L283 141,736 408 calBCE

I2d- ORD019 Ordona not dated 0.0484 XY T2e 61,292 Z2093/Y3670

2946 ± 30 BP; 1235 - SAL001 Salapia 0.049 XY H1+16189! J2b-M241 64,574 1048 calBCE

2287 ± 24 BP; 401 - SAL003 Salapia 0.113 XX K1a2a - 144,490 354 calBCE

SAL007 Salapia not dated 0.0529 XX K1a+195T! - 64,034

SAL010 Salapia not dated 0.031 XY U5a1 J2b-M241 39,174

2241 ± 23 BP; 313 - SAL011 Salapia 0.0496 XY U5b1 I2d-M223 62,155 206 calBCE

San 1285 ± 23 BP; 670 - SGR001 Giovanni 0.044 XY U3a I1-M253 59,213 774 calCE Rotondo

San 2451 ± 22 BP; 591 - SGR002 Giovanni 0.102 XY U5b1d1 R1b-M269 131,437 415 calBCE Rotondo

San 2205 ± 26 BP; 368 - SGR003 Giovanni 0.0572 XX H1+16311T! - 76,687 195 calBCE Rotondo

290

291

292

293

294

295

296

297 STAR Methods

298 Resource availability

299 Lead Contact

300 Further information and requests for resources and reagents should be directed to and will be

301 fulfilled by the Lead Contact: Serena Aneli ([email protected])

302 Materials Availability

303 This study did not generate new unique reagents.

304 Data and Code Availability

305 The DNA sequences generated during this study are available at the European Nucleotide Archive

306 (ENA; [link]) at the accession number [accession number]. The data are also available in PLINK

307 format through the data depository of the EBC (http://evolbio.ut.ee).

308 Experimental model and subject details

309 The ancient human remains analysed in this work belong to the collections of the Museum of

310 Anthropology, University of Padua and have been found and catalogued by different

311 archaeological campaigns carried out during the twentieth century.

312 Ordona

313 The necropolis of Herdonia (today's Ordona, within the Apulian Foggia province in Italy) was

314 studied by different archaeological campaigns interested in the Daunians, Roman as well as the

315 medieval settlements in 1978 and 198131. The human remains collected on such occasions were

316 later extensively catalogued and studied and new paleopathological evidence was also brought

317 back to light32. Inhabited starting from the Neolithic period, Herdonia became an important

318 Daunian center from the 6th century BCE.

319 For this study, in collaboration with the University of Padova and Museum of Anthropology of

320 Padova, samples of human remains (petrous bone=19) were taken. The samples ORD001,

321 ORD004, ORD006, ORD009, ORD010, and ORD014 were dated at 14CHRONO Centre for

322 Climate, the Environment, and Chronology in Belfast, UK (Data S1B).

323 Salapia

324 The necropolis of Salapia, an ancient town located 10 km from contemporary Cerignola, within

325 the Apulian Foggia province in Italy. The osteological samples were brought by Prof. Santo Tiné

326 to the Museum of Anthropology of the University of Padova with no further information on the

327 archaeological context, and osteological studies were carried out by Cleto Corrain and colleagues

328 in 197133. From this site, samples of 12 human remains (petrous bone=5, teeth=7) were taken. The

329 samples SAL001, SAL003, and SAL011 were dated at 14CHRONO Centre for Climate, the

330 Environment, and Chronology in Belfast, UK (Data S1B).

331 San Giovanni Rotondo

332 The San Giovanni Rotondo samples come from the osteo-archaeological collection of the Museum

333 of Anthropology of the University of Padova and are not associated to any further record with the

334 exception of a broad “Iron Age” archaeological label and may be part of the samples brought to

335 the Museum by Prof. Santo Tiné in the 1960s. From this site, samples of human remains (petrous

336 bone=3) were taken. The samples SGR001, SGR002, and SGR003 were dated at 14CHRONO

337 Centre for Climate, the Environment, and Chronology in Belfast, UK (Data S1B).

338 Method Details

339 All of the laboratory work was performed in dedicated ancient DNA laboratories at the Estonian

340 Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia. The library quantification

341 and sequencing were performed at the Core Facility of the Institute of Genomics, Tartu, Estonia.

342 The main steps of the laboratory work are detailed below.

343 DNA extraction

344 In total 34 samples from human remains were extracted for DNA analysis (Data S1).

345 The first layer of pars petrous was removed with a sterilised drill bite to avoid exogenous

346 contamination. A 10 mm core of the inner ear was sampled from the pars petrous. The drill bits

347 and core drill were sterilised in between samples with 6% (w/v) bleach followed by distilled water

348 and then ethanol rinse. Root portions of teeth were removed with a sterile drill wheel.

349 The root and the petrous portions were soaked in 6% (w/v) bleach for 5 minutes. Samples were

350 rinsed three times with 18.2 MΩcm H2O and soaked in 70% (v/v) Ethanol for 2 minutes. The tubes

351 were shaken during the procedure to dislodge particles. The samples were transferred to a clean

352 paper towel on a rack inside a class IIB hood with the UV light on and allowed to dry for two to

353 three hours.

354 Afterwards, the samples were weighed to calculate the accurate volume of EDTA (20x EDTA [µl]

355 of sample mass [mg]) and Proteinase K (0.5x Proteinase K [µl] of sample mass [mg]). EDTA and

356 Proteinase K were added into PCR-clean 5 ml or 15 ml conical tubes (Eppendorf) along with the

357 samples inside the IIB hood and the tubes were incubated 72 h on a slow shaker at room

358 temperature.

359 The DNA extracts (of root portions and pars petrous portions) were concentrated to 250 µl using

360 the Vivaspin® Turbo 15 (Sartorius) and purified in large volume columns (High Pure Viral

361 Nucleic Acid Large Volume Kit, Roche) using 2.5 ml of PB buffer, 1 ml of PE buffer and 100 μl

362 of EB buffer (MinElute PCR Purification Kit, QIAGEN). For the elution of the endogenous DNA,

363 the silica columns were transferred to a collection tube to dry and followed in 1.5 ml DNA lo-bind

364 tubes (Eppendorf) to elute. The samples were incubated with 100 µl EB buffer at 37 C for 10

365 minutes and centrifuged at 13,000 rpm for two minutes. After centrifugation, the silica columns

366 were removed and the samples were stored at -20 C. Only one extraction was performed per

367 extraction for screening and 30 µl used for libraries.

368 Library preparation

369 Sequencing libraries were built using NEBNext® DNA Library Prep Master Mix Set for 454™

370 (E6070, New England Biolabs) and Illumina-specific adaptors34 following established protocols34–

371 36. The end repair module was implemented using 18.75 μl of water, 7.5 μl of buffer and 3.75 μl

372 of enzyme mix, incubating at 20 °C for 30 minutes. The samples were purified using 500 μl PB

373 and 650 μl of PE buffer and eluted in 30 μl EB buffer (MinElute PCR Purification Kit, QIAGEN).

374 The adaptor ligation module was implemented using 10 μl of buffer, 5 μl of T4 ligase and 5 μl of

375 adaptor mix34, incubating at 20 °C for 15 minutes. The samples were purified as in the previous

376 step and eluted in 30 μl of EB buffer (MinElute PCR Purification Kit, QIAGEN). The adaptor fill-

377 in module was implemented using 13 μl of water, 5 μl of buffer and 2 μl of Bst DNA polymerase,

378 incubating at 37 °C for 30 and at 80 °C for 20 minutes. Libraries were amplified using the

379 following PCR set up: 50μl DNA library, 1X PCR buffer, 2.5mM MgCl2, 1 mg/ml BSA, 0.2μM

380 inPE1.0, 0.2mM dNTP each, 0.1U/μl HGS Taq Diamond and 0.2μM indexing primer. Cycling

381 conditions were: 5’ at 94C, followed by 18 cycles of 30 seconds each at 94C, 60C, and 68C, with

382 a final extension of 7 minutes at 72C. The samples were purified and eluted in 35 μl of EB buffer

383 (MinElute® PCR Purification Kit, QIAGEN). Three verification steps were implemented to make

384 sure library preparation was successful and to measure the concentration of dsDNA/sequencing

385 libraries - fluorometric quantitation (Qubit, Thermo Fisher Scientific), parallel capillary

386 electrophoresis (Fragment Analyser, Agilent Technologies) and qPCR.

387 DNA sequencing

388 DNA was sequenced using the Illumina NextSeq500/550 High-Output single-end 75 cycle kit. As

389 a norm, 15 samples were sequenced together on one flow cell; additional data was generated for

390 16 samples to increase coverage (Data S1).

391 Quantification and statistical analysis

392 Mapping

393 Before mapping, the sequences of the adapters, indexes, and poly-G tails occuring due to the

394 specifics of the NextSeq 500 technology were cut from the ends of DNA sequences using cutadapt-

395 1.1137. Sequences shorter than 30 bp were also removed with the same program to avoid random

396 mapping of sequences from other species. The sequences were aligned to the reference sequence

397 GRCh37 (hs37d5) using Burrows- Wheeler Aligner (BWA 0.7.12)38 and the command mem with

398 re-seeding disabled.

399 After alignment, the sequences were converted to BAM format and only sequences that mapped

400 to the human genome were kept with samtools 1.339. Afterwards, the data from different flow cell

401 lanes were merged and duplicates were removed using picard 2.12

402 (http://broadinstitute.github.io/picard/index.html). Indels were realigned using GATK 3.540 and

403 reads with a mapping quality less than 10 were filtered out using samtools 1.339.

404 aDNA authentication

405 As a result of degradation over time, aDNA can be distinguished from modern DNA by certain

406 characteristics: short fragments and a high frequency of C=>T substitutions at the 5' ends of

407 sequences due to cytosine deamination. The program mapDamage2.041 was used to estimate the

408 frequency of 5' C=>T transitions. Rates of contamination were estimated on mitochondrial DNA

409 by calculating the percentage of non-consensus bases at haplogroup-defining positions as detailed

410 in42. Each sample was mapped against the RSRS downloaded from phylotree.org and checked

411 against haplogroup-defining sites for the sample-specific haplogroup (Data S1A).

412 Samtools 1.939 option stats was used to determine the number of final reads, average read length,

413 average coverage etc. The final average endogenous DNA content of all individuals (proportion

414 of reads mapping to the human genome) was 10.39% (0.09 - 38.82%) (Data S1A).

415 Calculating genetic sex estimation

416 Genetic sex was calculated using the methods described in43, estimating the fraction of reads

417 mapping to Y chromosome out of all reads mapping to either X or Y chromosome. Additionally,

418 sex was determined using a method described in44, calculating the X and Y ratio by the division

419 of the coverage by the autosomal coverage. Here, the sex was calculated for samples with a

420 coverage >0.01× and only reads with a mapping quality >10 were counted for the autosomal, X,

421 and Y chromosome (Data S1A).

422 Determining mtDNA haplogroups

423 Mitochondrial DNA haplogroups were determined using Haplogrep2 on the command line. For

424 the determination, the reads were re-aligned to the reference sequence RSRS and the parameter -

425 rsrs were given to estimate the haplogroups using Haplogrep245,46(Data S1A). Subsequently, the

426 identical results between the individuals were checked visually by aligning mapped reads to the

427 reference sequence using samtools 0.1.1939 command tview and confirming the haplogroup

428 assignment in PhyloTree. Additionally, private mutations were noted for further kinship analysis.

429 The polymorphisms were estimated using the online platform of haplogrep2. Here, the variant

430 calling files (vcf) were uploaded to the online platform and the known polymorphism in the RSRS

431 were converted to rCRS (Data S1D).

432 Y chromosome variant calling and haplotyping

433 A total of 161,140 binary Y chromosome SNPs that have been detected as polymorphic in previous

434 high coverage whole Y chromosome sequencing studies47–49 were called in 9 male individuals with

435 more than 0.01× autosomal coverage using ANGSD-0.91647–49 ‘-doHaploCall’ option. A subset

436 of 826 sites had at least one of the 9 individuals with a derived allele (DATA C- Table Y). Basal

437 haplogroup affiliations of each sample were determined by assessing the proportion of derived

438 allele calls in a set of primary haplogroup defining internal branches, as defined in47, using 1677

439 informative sites.

440 Kinship analysis

441 All newly generated individuals with an average human coverage more than 0.03× were selected

442 to assess kinship relationships up to the 3rd degree. We divided the individuals in different groups

443 regarding their geographically area and resulting relationships. First, we were called all individuals

444 using ANGSD-0.91650 command --doHaploCall to sample a random base for the positions that are

445 present at MAF>0.1 in the 1000 Genomes GBR population51 giving a total of 4,045,514 SNPs for

446 autosomal kinship analysis. The ANGSD output files were converted to .tped format and used as

447 an input for kinship analyses with READ17. First, we tested all individuals together and found one

448 1st degree relationship between ORD001 and ORD009 and two 2nd degree relationships between

449 ORD004, SAL007, and SAL011. We tested those relationships using all individuals from Ordona

450 including SAL007 and SAL011 and all individuals from Salapia including ORD004. We compared

451 the estimated mtDNA haplogroups, radiocarbon dates, genetic sexes, average human coverages,

452 and the age of death from the individuals to confirm or dismiss relationships. (Data S1, Figure S1).

453 Based on the outputs, we dismissed the possible 2nd degree relationships.

454 Dataset preparation and pre-processing for autosomal analysis

455 We assembled a genome-wide dataset of ancient and modern samples by converting the following

456 datasets, where needed, in PLINK format using convertf from the EIGENSOFT 8.0.052 and

457 merging them together with PLINK 1.953: i) the ancient individuals and the Mbuti Congolese

458 individuals (HGDP54) from the “1240K” dataset from Dr David Reich laboratory

459 (https://reich.hms.harvard.edu/allen-ancient-dna-resource-aadr-downloadable-genotypes-present-

460 day-and-ancient-dna-data, version 44.3 release), ii) the modern samples from “1240K+HO” of the

461 same release, iii) the Italian Chalcolithic and Bronze Age samples produced by a recent study11,

462 iv) the genotypes of an Italian hunter-gatherer from the Late Epigravettian site of Riparo Tagliente

463 dated around 17kya55, v) additional genome-wide data of 129 modern-day Italian samples covering

464 the entire country56, vi) genome-wide data of 217 present-day Apulian individuals (available at

465 this link https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44974) and 48 haploid

466 genomes representing the Eurasian component of modern Ethiopians (here called Amhara_NAF

467 for “Non African Fraction”24). We excluded the ancient samples showing issues in their group

468 assignment (i.e., “Ignore” in the “1240K” dataset) or in their DNA quality (e.g, those not

469 containing the string “PASS”, with the exception of the Iceman individual, or those with less than

470 5,000 SNPs) and one of a pair of related samples. We further refined the list of ancient samples by

471 retaining only those coming from geographical regions relevant for this study (Data S2)3,4,6,12,14–

472 16,18–23,25,42,44,57–102. The same geographical filter was applied on the modern samples from

473 “1240K+HO” and only those flagged as “PASS (genotyping)” have been selected in order to

474 minimize variation due to different genotyping techniques (Data S3)23,54,72,103,104. In case of

475 duplicated samples, we selected the item showing the highest number of SNPs among the 1240K

476 SNP set. Finally we added the newly generated ancient Apulian samples to the merge.

477 We used two different SNPs set for the following analyses. The autosomal “1240K” SNP set

478 (1,150,639 SNPs) was used for the analyses involving just ancient samples, such as the f-statistics

479 and qpAdm analyses (see below). Conversely, the autosomal “HO” SNP set was used for those

480 analyses relying also on modern populations (e.g., PCA and ADMIXTURE). In the latter case, we

481 further refine the “HO” SNP set by removing monomorphic SNPs and those with more than 5%

482 missing count in modern populations with PLINK, thus obtaining 503,062 SNPs.

483 Principal component analysis

484 We performed principal component analysis using the program smartpca implemented in

485 EIGENSOFT software 8.0.052 with the parameters “lsqproject” and “shrinkmode”. In particular,

486 we projected the ancient samples' genetic variation onto the principal components inferred from

487 the modern samples of the “1240K+HO” dataset. Modern Italian samples coming from56, the

488 newly genotyped ones from modern Apulia and the Amhara_NAF were also projected.

489 Admixture

490 We used the same dataset of modern and ancient individuals presented in the PCA to explore the

491 genetic components of each individual. For the analysis, we exploited the model-based algorithm

492 implemented in ADMIXTURE105 projecting ancient individuals (-P flag) into the genetic structure

493 calculated on the modern dataset, due to missing data in the ancient individuals. We performed

494 unsupervised Admixture for K ∈ {2..10} for modern individuals and used the “per-cluster”

495 inferred allele frequencies to project the ancient individuals. We visualised the Q output using R

496 3.6106.

497 f4 statistics

498 We performed a series of f4 statistics using the program qpDstat (option f4mode) implemented in

499 the software ADMIXTOOLS 7.0.254 in different forms. In particular, we grouped together ancient

500 published samples from the same cultural/archeological assemblages (labels used for f3 and f4

501 analyses can be found in the column “Analysis.Label” of Data S2). Conversely, ancient Apulian

502 samples were both analysed as individual samples and grouped together according to their

503 archeological age (Iron Age samples were grouped together under the acronym “IAA”, Iron Age

504 Apulians). 10 individuals from the Mbuti population from Congo coming from the “1240K”

505 dataset were used as an outgroup.

506 Outgroup f3 statistics

507 To investigate genetic affinities between ancient Apulian samples with other ancient and modern

508 human populations, we performed a series of Outgroup f3 analyses in the form f3(X, Y;

509 outgroup=Mbuti) using the qp3Pop function implemented in ADMIXTOOLS 7.0.254. As above-

510 described we used the “Analysis.Label” groups for the ancient samples while we used the

511 “Group.Label” already present in the “1240K+HO” annotation file for modern samples.

512 We also computed the distance matrices from the Outgroup f3 results comparing ancient Apulian

513 samples (both Iron and Middle Age samples) with other published ancient samples by subtracting

514 the f3 values from 1 and we performed a classical (metric) Multi-Dimensional Scaling (MDS) with

515 default options using the function cmdscale in the stats package of R (version 4.0.4107).

516 qpAdm

517 We exploited the qpWave/qpAdm framework within the software ADMIXTOOLS 7.0.2 to

518 investigate the genetic composition of ancient Apulian samples and other ancient samples of

519 interest with respect to human ancestries that contributed to coeval European population in the

520 Mediterranean area. In particular, we tested a number of left sources from 2 to 5 in combination

521 with a list of reference sources (right). We used the options ‘‘allsnps=YES’’ and “inbreed=NO”

522 (the last option was used because some populations were composed of just one haploid individual).

523 We tested four different sets of left sources. The “base” set included Western hunter-gatherers

524 (Loschbour_published.DG), Anatolian Neolithic (26 samples flagged as “Anatolia_N” in the

525 Analysis.Label column of Data S2), Iranian Neolithic (samples Iran_GanjDareh_N), Caucasus

526 hunter-gatherers (KK1.SG and SATP.SG) and Yamnaya (10 Russia_Samara_EBA_Yamnaya

527 samples). To this set of base sources we separately added as left sources: Minoans (both

528 Greece_Minoan_Lassithi and Greece_Minoan_Odigitria, but taken individually), Amhara_NAF

529 and Roman Republican samples (Italy_Central_Republic_IA). In each run, we consistently used

530 the same set of right sources (if present in the left set, they were removed from the right):

531 Russia_Ust_Ishim_HG_published.DG (which was always kept as the first of the list),

532 Russia_Kostenki14, Russia_AfontovaGora3, Eastern hunter-gatherers

533 (I0061=Russia_HG_Karelia, I0124=Russia_HG_Samara, I0211=Russia_HG_Karelia and

534 UzOO77=Russia_EHG), Spain_ElMiron, Belgium_UP_GoyetQ116_1_published_all, Levant_N

535 (Israel_PPNB), Russia_MA1_HG.SG, Israel_Natufian_published, Czech_Vestonice16 and

536 Caucasus hunter-gatherers.

537 Additional resources

538

539 Acknowledgments

540 The work was supported by the Estonian Research Council grant PUT (PRG243) (A.S., M.M.,

541 C.L.S); the European Union through the European Regional Development Fund (Project No. 2014-

542 2020.4.01.16-0030) (C.L.S., M.M.); the European Regional Development Fund (Project No. 2014-

543 2020.4.01.15-0012) (M.M.) and my UniPd PRID 2019 (S.A., L.P.); the authors would like to thank

544 Dr. Francesco Bertolini for facilitating the research of A.R. in the last stage of the manuscript

545 preparation.

546 Author contributions

547 Conceptualization = L.P., C.L.S.

548 Formal Analysis = S.A., T.S.

549 Funding acquisition = M.M., L.P.

550 Investigation = T.S. (aDNA data generation), A.S. (quality control)

551 Project administration = C.L.S.

552 Resources = C.S., N.C., L.M.

553 Supervision = L.P. and C.L.S.

554 Visualization = S.A., T.S.

555 Writing – original draft = S.A., T.S., L.P.

556 Writing – review & editing = All authors

557 Declaration of interests

558 The authors declare no competing interests.

559 Supplementary Data

560 Data S1. Sample information (Related to Table 1). (A) Summary archaeological, mapping, 561 uniparental marker, genetic sex estimation, and damage statistics for samples sequenced in this 562 study. (B) Results of radiocarbon dating of newly generated samples in this study. (C) Binary Y 563 chromosome haplogroup-informative variants found in derived state in at least one of the Iron Age 564 Italian genomes. (D) Mitochondrial variants present in the newly generated sample in this study. 565 Polymorphisms are estimated with haplogrep2. Here, the variant calling file (vcf) is uploaded on 566 the online platform and the input file with the known polymorphism in chrRSRS is converted to 567 rCRS. (E) Comparison of the mean P0 values when running READ on different groupings of all 568 individuals. (F) READ results for individuals when running all individuals with coverage over 569 0.03x together. (G) READ results for individuals when running all Ordona individuals including 570 SAL007 and SAL011 with coverage over 0.03X together. (H) READ results for individuals when 571 running all Salapia individuals including ORD004 with coverage over 0.03X together. 572 573 Data S2. List and available information of published ancient samples used in this work. 574 575 Data S3. List and available information of published modern samples used in this work. 576 577 Data S4. f4 investigating the genetic relationships among Iron Age Apulians (IAA) and modern 578 Apulians. 14 Apulian samples from Raveane et al. 2019 (Modern_Apulia_GP) were used as 579 Modern Apulians (Data S3). 580 581 Data S5. qpAdm results with 2, 3 and 4 possible sources for each test model (see STAR methods). 582 583 Data S6. f4 investigating the genetic relationships among Iron Age Apulians (IAA) and the two 584 Middle Age Apulian samples, the putative Daunians'population of origin (ancient populations 585 coming from Crete, Peloponnese, Croatia and Iron Age Italians) and other ancient human groups. 586 f4 analyses were computed in the form f4(IAA, X; Y, Mbuti) where X is a putative Daunians source 587 and Y is another ancient population. 588

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595

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34 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 1: Geographical location, dating and genetic structure. (A) Geographical location of the newly generated Apulian ancient individuals (green, red and blue dia- monds and triangles) and other published Iron Age samples from Italy and surrounding areas (color scale mirroring their “years before present” dates). See also Table 1, Data S1, and Data S2. (B) Dating and number of SNPs from 1240K set covered. Samples with thick edges have been radiocarbon dated (mean presented), while for the others we represented their archaeological dating (Table 1, Data S1B). (C) Principal component analysis (PCA) of newly generated individuals with reference ancient individuals projected onto the genetic variation inferred from modern-day Western Eurasian populations (Data S2 and Data S3). For the ancient reference populations which have not been attributed to the Iron Age, we plotted their centroids. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 2: Genetic relationship of Iron Age and Middle Age Apulians and their ancestral composition. (A) Heatmap representing the Z-score values of f4(Modern Apulia, IAA; X, Mbuti) where X is an ancient Italian population. We also added the two Middle Age samples for comparison. Tests with Z-scores between -3 and 3 or with less than 5,000 SNPs were not included (P: Palaeolithic, M: Mesolithic, N: Neolithic, C: Chalcolithic, CA: Copper Age, BA: Bronze Age, IA: Iron Age, A: Antiquity). (B) qpAdm proportions of ancient Apulian samples and other reference populations (Mod- ern Apulians, Minoans, Croatia EIA and the Roman individuals from the Republican and the Imperial period) using “base” sources: Caucasus and Western hunter-gatherer component (HG), Anatolia Neolithic (Anatolia N), Iranian Neolithic (Iran N), Steppe- related ancestry. (C) qpAdm proportions using also the Minoans as source (STAR methods). In B and C, we plotted the model with the highest number of sources and p-value (complete results may be seen in Figure S5). bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure 3: Genetic afﬁnities of Iron Age Apulian samples with the putative populations of origin: Minoans (Minoan Lassithi), Illyrians (here proxied by the Croa- tia EIA individual) and the Roman Republicans (here proxying the autochthonous Iron Age Italian ancestry). (A) Outgroup f3 statistics of IAA samples compared with the putative Daunian sources. Samples have been sorted and grouped according to the source whose f3 values were higher. (B) Heatmap showing the Z-score values of f4(putative sources, IAA P; X, Mbuti) where X is an ancient Italian population and IAA P is the entire set of Iron Age Apulian samples taken together. Tests with Z-scores between -3 and 3 or with less than 5,000 SNPs were not included (P: Palaeolithic, M: Mesolithic, N: Neolithic, C: Chalcolithic, CA: Copper Age, BA: Bronze Age, IA: Iron Age, A: Antiquity). bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Supplementary Materials

This PDF ﬁle includes:

• Supplementary Figures 1 to 7. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

●● ●●●●● ●●●●●●●●●● ●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●● ●●●●●●●●●● ●●●●●●●●●●●●●●● ●●●●●●●●●● ●●●●● 15 10 ●●●●●●●●●●● ●●●●● ●●●● ●●●●● ●● 2nd degree●● Frequency

1st ●degree Average pairwise P0 (± 2SE) .503 0.35 0.30 0.25 Identical/Twins 1st degree 2nd degree 5 0 Identical/Twins 0.28 0.30 0.32 0.34

Average pairwise P0 SAL007SAL010 SAL007SAL011 SAL003SAL011 SAL011SAL001 SAL003SAL007 SAL007SAL001 SAL003SAL010 SAL010SAL001 SAL003SAL001 SAL010SAL011 SAL007SGR003 SAL007SGR002 SAL010SGR002 SAL011SGR002 SAL010SGR001 SAL003SGR002 SAL011SGR001 SAL010SGR003 SGR002SAL001 SAL011SGR003 SAL003SGR003 SAL007SGR001 SAL003SGR001 SAL001SGR003 SGR001SAL001 SAL011ORD004 SAL007ORD004 ORD004SAL001 ORD019SAL011 SAL003ORD004 ORD006SAL011 SAL010ORD004 ORD019SAL010 ORD009SAL007 ORD001SAL007 ORD011SAL011 ORD019SAL007 ORD006SAL007 ORD009SAL011 ORD006SAL010 ORD014SAL011 ORD014SAL007 ORD001SAL011 ORD006SAL001 ORD019SAL003 ORD011SAL010 ORD010SAL007 ORD010SAL011 ORD011SAL007 ORD014SAL010 ORD006SAL003 ORD010SAL010 ORD014SAL001 ORD011SAL003 ORD009SAL003 ORD009SAL001 ORD010SAL001 ORD009SAL010 ORD014SAL003 ORD010SAL003 ORD011SAL001 ORD019SAL001 ORD001SAL001 ORD001SAL003 ORD001SAL010 SGR002SGR003 SGR001SGR002 SGR001SGR003 ORD004SGR003 SGR002ORD004 SGR001ORD004 ORD019SGR002 ORD019SGR003 ORD006SGR002 ORD006SGR001 ORD011SGR002 ORD006SGR003 ORD011SGR003 ORD014SGR002 ORD009SGR002 ORD014SGR003 ORD001SGR002 ORD001SGR003 ORD009SGR003 ORD001SGR001 ORD010SGR002 ORD014SGR001 ORD019SGR001 ORD010SGR003 ORD010SGR001 ORD011SGR001 ORD009SGR001 ORD001ORD009 ORD006ORD004 ORD011ORD004 ORD014ORD004 ORD019ORD004 ORD001ORD019 ORD001ORD004 ORD009ORD004 ORD010ORD004 ORD006ORD019 ORD009ORD019 ORD014ORD019 ORD010ORD011 ORD006ORD011 ORD011ORD019 ORD001ORD006 ORD010ORD019 ORD011ORD014 ORD009ORD011 ORD006ORD009 ORD006ORD014 ORD006ORD010 ORD009ORD010 ORD001ORD010 ORD009ORD014 ORD010ORD014 ORD001ORD014 ORD001ORD011

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 6 5 4 ● ● ● ● ● ● ● ● ● ● ● ●

2nd degree● ● Frequency

1st● degree Average pairwise P0 (± 2SE) .503 0.35 0.30 0.25 Identical/Twins 1st degree 2nd degree 3 2 1 0 Identical/Twins 0.28 0.30 0.32 0.34

Average pairwise P0 SAL007SAL011 SAL011ORD004 SAL007ORD004 ORD006SAL011 ORD019SAL011 ORD001SAL007 ORD009SAL007 ORD011SAL011 ORD019SAL007 ORD006SAL007 ORD009SAL011 ORD014SAL011 ORD014SAL007 ORD001SAL011 ORD010SAL011 ORD011SAL007 ORD010SAL007 ORD001ORD009 ORD006ORD004 ORD011ORD004 ORD014ORD004 ORD001ORD019 ORD019ORD004 ORD009ORD004 ORD001ORD004 ORD010ORD004 ORD006ORD019 ORD014ORD019 ORD010ORD011 ORD011ORD019 ORD009ORD019 ORD006ORD011 ORD010ORD019 ORD011ORD014 ORD009ORD011 ORD006ORD010 ORD001ORD006 ORD006ORD009 ORD006ORD014 ORD009ORD010 ORD009ORD014 ORD010ORD014 ORD001ORD010 ORD001ORD014 ORD001ORD011 C. 3.0

● ● ● ● ● ● ● ● ● ● ● ● ●

● ● Frequency 2nd degree Average pairwise P0 (± 2SE) 1st degree Identical/Twins 1st degree 2nd degree . . . . . 2.5 2.0 1.5 1.0 0.5 0.0 .402 .803 .203 .60.38 0.36 0.34 0.32 0.30 0.28 0.26 0.24 0.31 0.32 0.33 0.34

Average pairwise P0 SAL007SAL010 SAL007SAL011 SAL011SAL001 SAL003SAL011 SAL003SAL007 SAL007SAL001 SAL003SAL010 SAL010SAL001 SAL003SAL001 SAL010SAL011 Identical/TwinsSAL011ORD004 SAL007ORD004 SAL001ORD004 SAL003ORD004 SAL010ORD004

Figure S1. Graphical output of READ. A) All newly generated individuals run together regardless of geography or chronology. B) All newly generated individuals from the archaeological site Ordona plus SAL007 and SAL011. C) All newly generated individuals from the archaeological site Salapia plus ORD004. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure S2. Correlation of radiocarbon dating and principal components for the ancient Apulian samples. A) Pearson correlation of dates with the ﬁrst three principal components for the radiocarbon dated ancient Apulian samples. B) Same as A, after removing the Middle Age samples ORD010 and SGR001. C), D) and E) show three principal components analyses based on PC1 vs PC2, PC2 vs PC3 and PC1 vs PC3, respectively. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A SAL001 ORD006 ORD001 SGR002 Greece_Crete_Armenoi 1980 Italy_Sicily_BellBeaker 2716 Italy_Sicily_C_o 1440 Sicily_EBA 1394 Spain_Roman_oAegean 2050 Italy_Remedello_CA 24013 Italy_Sicily_BellBeaker 884 Turkey_IA_o2 8090 Italy_Iceman_CA 47620 Italy_Remedello_EBA 20360 Spain_IA_Tartessian 4466 Montenegro_IA 1338 Broion_CA 17907 Italy_Sicily_BA 86862 France_LBA 4456 ReginaMargherita 28311 England_IA_ERoman 28041 Spain_LN 37549 Anatolia_Kumtepe_N 4384 Italy_Remedello_CA 20263 Germany_Blatterhohle_MN 25977 Gibraltar_EN 42766 Sicily_EBA 562 Gattolino 42721 LaSassa 39359 Sicily_EBA 1771 Modern_Apulia 6829 Italy_Iceman_CA 96258 Italy_Sardinia_C_MonteClaro 44320 Gibraltar_EBA 51176 France_LN 13353 Broion_CA 36352 Gibraltar_EN 16224 Italy_Iceman_CA 117014 Italy_Remedello_CA 8300 Amhara_NAF 100397 Modern_Apulia 8573 LaSassa 98721 Portugal_EBA 4962 Denmark_LN 17889 Italy_Imperial_oCentralEuropean.R116 33468 Greece_Minoan_Odigitria 29712 Italy_Sardinia_MBA_published_o 20382 Croatia_C 16728 Amhara_NAF 49582 Amhara_NAF 121452 Spain_Roman_oAegean 1758 Spain_LN 30775 Italy_Sicily_C_o 1825 Modern_Apulia 20650 Anatolia_TitrisHoyuk_EBA 4807 Italy_North_BellBeaker_1 33533 Italy_North_BellBeaker_2 34084 Anatolia_Ikiztepe 9065 Czech_IA 23444 Italy_Remedello_EBA 17003 Italy_Central_C 49049 Turkey_IA_o2 9862 Italy_C_BA 35133 Broion_EBA 43903 Austria_EN_LBK 49409 Italy_Sardinia_MBA 90466 Croatia_EIA 28572 Italy_Central_C 99342 Croatia_MN 44004 Denmark_LN 24978 Greece_Crete_Armenoi 1639 Austria_EN_LBK 100381 Switzerland_BellBeaker 11748 Croatia_EN_Impressa 86706 Croatia_EN_Impressa 28409 Italy_Sardinia_BA_Nuragic 101842 Italy_Sicily_BellBeaker 1078 Italy_Imperial_o2.R111 56975 Croatia_MN 36049 LaSassa 80102 Gattolino 20758 Italy_C_BA 105310 Italy_Sardinia_MBA 29212 Hungary_EC 81096 Croatia_C 8251 Italy_Sardinia_BA_Nuragic 124312 Spain_Hellenistic_oLocal 25749 Italy_Sardinia_MBA 71238 Spain_IA_Tartessian 5232 France_EMBA 25676 Broion_BA 34002 Modern_Apulia 16753 Croatia_EN_Impressa 34666 Broion_EBA 53732 Iberia_BA 35984 Anatolia_Boncuklu_N 92994 Croatia_MBA 37384 Italy_Sicily_C_o 4469 Hungary_EC 32659 Gibraltar_EBA 38954 Italy_Sardinia_N 44162 Portugal_MBA 113551 Portugal_LBA 1706 France_MN 109068

ORD011 ORD019 SAL007 SAL010 Italy_Sicily_C_o 3279 Montenegro_IA 621 Italy_Remedello_EBA 8374 Montenegro_LBA 662 Sicily_EBA 1235 Sicily_EBA 637 Italy_Iceman_CA 45814 Tagliente 6889 Modern_Apulia 15342 Broion_CA 16863 Turkey_IA_o2 3852 Portugal_LBA 1230 Gibraltar_EN 30299 Anatolia_Ikiztepe 3162 Broion_CA 17079 Greece_Minoan_Odigitria 6842 Turkey_IA_o2 7355 Greece_Minoan_Odigitria 10645 Italy_C_BA 41951 ReginaMargherita 8324 Italy_Remedello_CA 18070 France_EMBA 9510 Tagliente 10783 Spain_EBA_Mallorca 6945 France_LN 29727 Spain_Hellenistic_oAegean 17159 Portugal_LBA 1946 Italy_Imperial_o2.R111 14373 Italy_Iceman_CA 86702 Italy_Sardinia_Roman 17650 LaSassa 37849 Broion_EBA 12841 Hungary_EC 73271 Broion_EBA 20158 Gattolino 19976 Italy_Sicily_C_o 1139 Broion_BA 76175 Gattolino 19563 France_EMBA 9635 Amhara_NAF 29907 Amhara_NAF 90120 Anatolia_TitrisHoyuk_EBA 5249 Croatia_C 7505 Italy_Iceman_CA 28627 Broion_CA 32811 Croatia_EN_Impressa 32217 Broion_EBA 20438 Greece_LN 28634 Italy_Sardinia_N 81197 Spain_IA_Tartessian 4801 Spain_LN 14684 Spain_MBA 26003 Italy_Sardinia_C_MonteClaro 81635 Montenegro_LBA 1054 Gibraltar_EN 14193 England_IA_Roman 30521 Switzerland_LN 92418 Amhara_NAF 46989 Italy_Central_C 47287 Spain_Roman_oLocal 11025 Greece_LN 86368 Italy_Sicily_BA 31083 Anatolia_Kumtepe_N 5388 Crimea_Pantikapaion 9579 Gattolino 37494 LaSassa 37491 Iberia_BA 42919 Italy_Sicily_EBA_o1 22609 Italy_C_BA 78490 Italy_Iceman_CA 45049 Portugal_LN_C 48342 Croatia_N 21040 Broion_EBA 39376 Austria_EN_LBK 46519 Italy_Sardinia_MBA 31928 Italy_Sardinia_MBA_published_o 14234 Israel_Middle_Late_PPNB 8826 Anatolia_Boncuklu_N 43532 Italy_Sardinia_EBA 48747 Kazakhstan_Sarmatian 6944 Italy_Sardinia_C 90602 Bulgaria_IA 27642 Croatia_EN_Impressa 32806 Italy_IA_Republic_oEasternMediterranean 26253 Italy_Central_N 92763 Greece_N 47441 Italy_Remedello_CA 10441 Jordan_PPNB 3446 Greece_Minoan_Odigitria 21416 Italy_Sardinia_EBA_Nuragic 32938 Amhara_NAF 47884 Estonia_CordedWare 26921 Italy_Sardinia_EBA_Nuragic 65382 Portugal_MBA 44416 Hungary_EN 39615 Italy_Central_Republic_IA 30435 Spain_LN 27730 Italy_Sardinia_N 41250 Sicily_EBA 580 Spain_EBA 30940

ORD014 ORD009 ORD004 SAL003 Montenegro_IA 1459 Montenegro_IA 8005 Croatia_C 6876 Greece_Crete_Armenoi 4310 Sicily_EBA 1622 Portugal_LBA 25650 Portugal_LBA 1821 Broion_EBA 47524 Portugal_LBA 4681 Italy_Sicily_BellBeaker 12799 Italy_Remedello_CA 8624 France_LN 36203 Italy_Sicily_C_o 3969 Modern_Apulia 103699 ReginaMargherita 11876 Tagliente 25068 Modern_Apulia 18437 Amhara_NAF 610631 Italy_Iceman_CA 40010 Croatia_N 78519 Spain_EBA_Mallorca 27609 Italy_Sicily_C_o 21630 Spain_EBA_Mallorca 9804 France_MBA 8487 Gibraltar_EBA 44833 Greece_Crete_Armenoi 24526 Gattolino 17606 Italy_Sardinia_MBA 77854 Spain_LBA 32547 France_LN 199599 Italy_Sicily_BA 28331 Italy_Central_C 107906 LaSassa 88095 Italy_Central_C 605414 Gibraltar_EBA 16104 Spain_LN 33769 Gibraltar_EN 37027 Italy_Sicily_BA 418790 Spain_LN 12861 Gibraltar_EN 35605 Amhara_NAF 109289 Croatia_MN 542314 Italy_Sardinia_IA 29183 Amhara_NAF 108800 Croatia_C 18833 Gattolino 252357 Bulgaria_IA 25295 Anatolia_Ikiztepe 7801 Croatia_EIA 78359 Hungary_EC 490677 Romania_C 31865 Modern_Apulia 18529 Turkey_IA_o2 8837 Italy_Sicily_N 595636 Italy_Imperial_oCentralEuropean.R116 28211 Italy_C_BA 95080 Hungary_MN_LBK 100744 Italy_C_BA 529700 Broion_EBA 18170 Italy_North_BellBeaker_2 75074 Italy_Sardinia_EBA_Nuragic 79612 Gibraltar_EN 199638 Croatia_EN_Impressa 29001 Serbia_EN 102396 Jordan_PPNB 12960 Italy_Sardinia_LBA 564199 Gibraltar_EN 13255 Italy_Sardinia_EBA 112171 Italy_Central_C 108214 Broion_EBA 264991 France_LBA 4472 Greece_LN 104481 Italy_Remedello_EBA 18430 Italy_Sardinia_N 544908 LaSassa 33495 Macedonia_N 80781 Italy_Imperial_oCentralEuropean.R37 69268 Italy_North_BellBeaker_2 419911 Hungary_IA_Scythian 36141 Spain_Roman_oAegean 4437 Italy_Sicily_N 107266 Austria_EN_LBK 610580 Italy_Sardinia_LBA 38463 Italy_Sardinia_LBA 100798 Italy_Sardinia_Roman 43644 Italy_Central_N 628876 Greece_LN 39849 Italy_Central_N 112227 Scotland_N 115112 Croatia_C 101343 Amhara_NAF 41738 Hungary_IA_Scythian 94904 Spain_Greek_oLocal 92670 Italy_Sardinia_MBA 435911 Spain_Hellenistic_oAegean 15535 Italy_North_BellBeaker_1 36488 Italy_Sardinia_LBA 102242 Greece_LN 583949 Spain_LBA 11869 Austria_EN_LBK 109101

SGR003 SAL011 SGR001 ORD010 Montenegro_IA 778 Sicily_EBA 617 Montenegro_LBA 983 Amhara_NAF 582662 Sicily_EBA 776 Italy_Sicily_C_o 1657 Sicily_EBA 611 Portugal_LBA 24553 Spain_IA_Tartessian 6251 Turkey_IA_o2 3888 Montenegro_IA 584 Croatia_C 97172 Portugal_EBA 7226 Portugal_LBA 1912 Greece_Crete_Armenoi 1895 Modern_Apulia 99047 Italy_Remedello_EBA 9905 Italy_Remedello_CA 10180 Broion_CA 16662 Italy_Remedello_EBA 97380 France_LBA 6313 Broion_CA 16966 Modern_Apulia 7634 Italy_Central_C 577855 Spain_LN 17617 Montenegro_IA 628 Anatolia_Kumtepe_N 4969 Montenegro_LBA 12839 Spain_EBA_Mallorca 13917 Italy_C_BA 41215 Portugal_LBA 1990 Greece_Minoan_Odigitria 137327 Italy_Sicily_BellBeaker 1242 Modern_Apulia 8009 Spain_LBA 13240 Italy_Sicily_N 569498 Modern_Apulia 9831 France_EMBA 9415 Croatia_C 7592 Gibraltar_EN 192513 Gibraltar_EN 19049 Montenegro_LBA 1037 Gibraltar_EN 15179 Gibraltar_EBA 231890 Broion_CA 21067 Italy_Remedello_EBA 8235 Israel_Ashkelon_IA1_o 9242 Italy_Sicily_BA 401731 Italy_Remedello_CA 11532 Italy_Iceman_CA 45319 Portugal_EBA 5598 Austria_EN_LBK 583638 Italy_Sardinia_MBA 41712 Broion_EBA 20435 Amhara_NAF 45548 Greece_LN 557420 Croatia_C 9748 France_LN 15950 Italy_Sardinia_Roman 17784 Croatia_EN_Impressa 405691 Italy_Sicily_BA 40019 Denmark_BA 3900 Italy_Iceman_CA 43926 Italy_Sardinia_EBA_Nuragic 419323 Spain_Roman_oLocal 22047 Hungary_IA_Scythian 41043 Spain_LN 14173 Italy_Central_N 600479 Broion_BA 48779 Amhara_NAF 47462 Iberia_BA 40835 Italy_Sicily_EBA_o1 452520 Italy_Sardinia_EBA_Nuragic 41641 Italy_Imperial_oCentralEuropean.R37 29721 Gibraltar_EBA 18129 Spain_EBA_Mallorca 141764 Hungary_EC 47071 Italy_Imperial_o2.R111 22539 Italy_Central_C 45285 Italy_Sardinia_BA_Nuragic 592298 Italy_Sardinia_Roman_o 8026 LaSassa 37686 Italy_North_BellBeaker_1 15256 Serbia_EN 547095 Croatia_EN_Impressa 40801 Spain_LN 14467 Hungary_EC 36892 Spain_LN 179381 Austria_EN_LBK 57895 Greece_LN 45394 Spain_Hellenistic_oAegean 17338 Italy_Sardinia_C 584915 Amhara_NAF 57826 Jordan_PPNB 4624 Croatia_EN_Impressa 32111 Croatia_MN 519389 Hungary_EN 49843 Serbia_EN 43613 ReginaMargherita 12971 Italy_Sardinia_EBA 600380 0.26 0.30 0.34 0.26 0.30 0.34 0.26 0.30 0.34 0.26 0.30 0.34

B SAL001 ORD006 ORD001 SGR002 Sardinian 27858 Sardinian 70296 Norwegian 22498 Sardinian 56990 Basque 27893 Orcadian 69398 Sardinian 22835 Scottish 54274 Estonian 27305 Basque 70336 Romanian 22239 Basque 56995 Spanish_North 26671 English 69073 English 22421 Spanish_North 54580 English 27381 Lithuanian 68868 Basque 22842 English 55937 Orcadian 27515 Spanish_North 67409 Spanish_North 21893 Lithuanian 55804 Norwegian 27387 Scottish 66978 Finnish 22259 Orcadian 56252 Scottish 26519 Norwegian 69199 Czech 22493 Italian_North 56839 Moldavian 27200 Estonian 68929 French 23246 Norwegian 56096 Hungarian 27879 French 71548 Orcadian 22543 French 58102 Italian_South 26551 Hungarian 70287 Scottish 21803 Hungarian 57000 Lithuanian 27309 Czech 69108 Lithuanian 22406 Spanish 59439 Croatian 27359 Romanian 68663 Italian_North 22815 Belarusian 55936 Italian_North 27799 Italian_North 70147 Gagauz 22282 Czech 55971 French 28392 Ukrainian_North 68247 Estonian 22416 Romanian 55592 Ukrainian 27595 Croatian 69130 Ukrainian_North 22169 Croatian 55942 Albanian 26965 Ukrainian 69621 Belarusian 22479 Estonian 55815 Spanish 29045 Bulgarian 69091 Moldavian 22311 Ukrainian 56442 Ukrainian_North 27016 Russian 71863 Hungarian 22867 Moldavian 55644 Bulgarian 27374 Spanish 73248 Spanish 23771 Greek 56889 Romanian 27160 Moldavian 68683 Albanian 22068 Russian 58309 Gagauz 27225 Belarusian 69017 Greek 22802 Bulgarian 56022 Finnish 27186 Albanian 67968 Russian 23325 Albanian 55067 Czech 27382 Greek 70239 Ukrainian 22651 Ukrainian_North 55309 Belarusian 27377 Finnish 68613 Croatian 22469 Italian_South 54179

ORD011 ORD019 SAL007 SAL010 Sardinian 51419 Spanish_North 24856 Sardinian 26391 Scottish 16019 Basque 51414 Scottish 24624 Scottish 25071 English 16534 Spanish_North 49321 Basque 25910 Basque 26348 Basque 16868 English 50460 English 25391 Spanish_North 25265 Lithuanian 16499 Scottish 49017 Lithuanian 25339 Italian_North 26272 Estonian 16508 Italian_North 51371 Norwegian 25480 Norwegian 25939 Norwegian 16564 Hungarian 51380 Sardinian 25908 English 25870 Italian_North 16831 Norwegian 50660 Orcadian 25520 Lithuanian 25842 Spanish_North 16133 Moldavian 50217 French 26401 Orcadian 26051 Sardinian 16901 French 52367 Moldavian 25304 Spanish 27456 Belarusian 16546 Ukrainian_North 49926 Italian_North 25857 French 26876 Moldavian 16439 Spanish 53500 Hungarian 25885 Gagauz 25750 Croatian 16576 Belarusian 50495 Czech 25426 Czech 25847 Romanian 16425 Albanian 49741 Ukrainian 25621 Albanian 25461 Bulgarian 16579 Lithuanian 50397 Romanian 25254 Hungarian 26357 Orcadian 16639 Orcadian 50764 Albanian 24987 Moldavian 25718 Russian 17258 Greek 51417 Belarusian 25470 Romanian 25680 French 17188 Estonian 50483 Greek 25906 Ukrainian 26099 Czech 16531 Croatian 50511 Croatian 25451 Greek 26372 Spanish 17592 Bulgarian 50538 Spanish 26975 Estonian 25805 Hungarian 16869 Czech 50520 Finnish 25277 Belarusian 25893 Ukrainian_North 16307 Romanian 50130 Bulgarian 25453 Bulgarian 25920 Finnish 16400 Ukrainian 50924 Estonian 25361 Croatian 25854 Ukrainian 16711 Russian 52528 Gagauz 25253 Ukrainian_North 25608 Mordovian 17019 Gagauz 50091 Russian 26488 Russian 26963 Kumyk 16488

ORD014 ORD009 ORD004 SAL003 Scottish 59583 Basque 341444 Spanish_North 22901 Sardinian 61707 Basque 62564 Sardinian 341172 Lithuanian 23439 Basque 61792 Czech 61418 Lithuanian 334526 Basque 23977 Italian_North 61619 Norwegian 61564 English 335164 Sardinian 23987 Scottish 58804 Italian_North 62419 Norwegian 336035 Norwegian 23583 Lithuanian 60512 Lithuanian 61260 Spanish_North 327388 Czech 23519 Spanish_North 59170 Croatian 61473 Orcadian 336833 Orcadian 23619 Czech 60628 Sardinian 62520 Croatian 335393 Bulgarian 23523 French 62894 Estonian 61332 Scottish 325410 English 23472 Orcadian 60905 Ukrainian_North 60662 French 347440 Italian_North 23937 English 60574 Spanish_North 59978 Italian_North 340772 Finnish 23308 Ukrainian 61109 Orcadian 61700 Estonian 334775 French 24392 Albanian 59634 French 63691 Czech 335388 Scottish 22802 Greek 61665 Belarusian 61339 Hungarian 341210 Ukrainian 23690 Moldavian 60300 Albanian 60531 Ukrainian 338138 Moldavian 23379 Croatian 60659 Moldavian 61172 Belarusian 335243 Hungarian 23962 Spanish 64228 Finnish 60926 Romanian 332953 Croatian 23532 Bulgarian 60662 Bulgarian 61476 Albanian 330212 Belarusian 23527 Norwegian 60743 Ukrainian 61913 Moldavian 333575 Estonian 23428 Romanian 60210 English 61361 Gagauz 333243 Spanish 24961 Ukrainian_North 59888 Gagauz 61041 Spanish 355303 Gagauz 23404 Gagauz 60275 Hungarian 62461 Ukrainian_North 331510 Romanian 23388 Hungarian 61715 Spanish 65125 Greek 340960 Albanian 23129 Russian 63102 Romanian 61003 Russian 348798 Russian 24507 Estonian 60551 Greek 62513 Bulgarian 335595 Greek 23934 Belarusian 60613

SGR003 SAL011 SGR001 ORD010 Albanian 31885 Sardinian 26248 Basque 25768 Sardinian 326659 Spanish_North 31657 Italian_North 26227 Spanish_North 24748 Basque 326816 Basque 33046 Spanish_North 25138 Croatian 25333 Spanish_North 313300 Sardinian 33002 English 25776 Sardinian 25749 English 320877 Czech 32437 Basque 26290 Czech 25349 Italian_North 326175 Norwegian 32436 Norwegian 25843 Italian_North 25754 Orcadian 322491 Croatian 32461 Czech 25778 Ukrainian 25579 Albanian 316157 Bulgarian 32413 French 26779 Ukrainian_North 25044 Norwegian 321784 Italian_North 32953 Lithuanian 25685 English 25362 Scottish 311547 Lithuanian 32294 Romanian 25581 Belarusian 25330 Moldavian 319390 French 33586 Spanish 27376 Bulgarian 25371 French 332571 Moldavian 32277 Orcadian 25933 Albanian 24958 Greek 326401 English 32416 Estonian 25701 Orcadian 25491 Lithuanian 320269 Ukrainian 32709 Gagauz 25640 Scottish 24576 Hungarian 326600 Estonian 32368 Hungarian 26268 Lithuanian 25282 Croatian 321071 Scottish 31475 Belarusian 25780 Gagauz 25207 Czech 321074 Greek 32972 Albanian 25355 Norwegian 25413 Bulgarian 321208 Ukrainian_North 32060 Moldavian 25657 French 26266 Romanian 318816 Belarusian 32421 Bulgarian 25808 Moldavian 25207 Gagauz 318998 Orcadian 32555 Ukrainian_North 25464 Greek 25766 Spanish 340085 Spanish 34345 Finnish 25577 Hungarian 25791 Estonian 320610 Hungarian 32971 Russian 26867 Spanish 26829 Italian_South 311454 Gagauz 32209 Scottish 24953 Finnish 25199 Ukrainian 323667 Romanian 32228 Croatian 25779 Estonian 25321 Belarusian 321023 Russian 33728 Greek 26264 Romanian 25155 Ukrainian_North 317371 0.24 0.25 0.26 0.24 0.25 0.26 0.24 0.25 0.26 0.24 0.25 0.26

Figure S3. Outgroup f3 analyses in the form f3(Ancient Apulian samples, X; Mbuti). A) Outgroup f 3 analyses comparing the newly generated ancient Apulian samples with other ancient human groups (see STAR Methods and Data S1). B) Outgroup f 3 analyses comparing the newly generated ancient Apulian samples with present-day populations (see STAR Methods and Data S2). The number of the SNPs used in each run is reported near each f 3 value. The ancient Apulian samples are plotted according to their age (SAL001 is the oldest) and Middle Age samples (ORD010 and SGR001) are reported in blue. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure S4. outgroup-f3 multidimensional scaling (MDS) of ancient Apulian samples and published ancient and modern reference populations. A pairwise ma- trix of outgroup f 3(Ancient Apulian samples, X; Mbuti) distance was used to com- pute the MDS (STAR Methods) after removing samples belonging to Palaelolithic and Mesolithic periods. Ancient and modern groups were aggregated according to their published label (Data S1, Data S2 and STAR Methods). bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure S5. Ancestral composition of ancient Apulian samples inferred by qpAdm. A) qpAdm proportions of ancient Apulian samples and other reference populations (Modern Apulians, Minoans, Croatia EIA and the Roman individuals from the Republi- can and the Imperial period) using base sources: Caucasus and Western hunter-gatherer component (HG), Anatolia Neolithic (Anatolia N), Iranian Neolithic (Iran N), Steppe- related ancestry. B), C) and D) Same as A, using also the Minoans, Amhara NAF and Rome Republicans as source (STAR methods). Only the models with p-values higher than 0.05 are shown. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A f4(X, IAA; WHG, Mbuti)

SAL001 ORD006 ORD001 SGR002 Croatia_LateC_EBA_Vucedol Italy_Central_Republic_IA Croatia_EIA Croatia_EIA Italy_Central_Republic_IA Croatia_C Italy_Central_Republic_IA Italy_Central_Republic_IA Croatia_MBA Croatia_EIA Greece_Minoan_Odigitria Croatia_MBA Greece_BA_Mycenaean_Pylos Croatia_MBA Croatia_MBA Greece_Crete_Armenoi Croatia_EIA Croatia_MN Croatia_N Croatia_EN_Impressa Greece_BA_Mycenaean Greece_Crete_Armenoi Croatia_MN Croatia_C Croatia_MN Croatia_LateC_EBA_Vucedol Croatia_LateC_EBA_Vucedol Croatia_LateC_EBA_Vucedol Greece_Minoan_Odigitria Croatia_N Croatia_EN_Impressa Croatia_MN Croatia_C Croatia_EN_Impressa Greece_Minoan_Lassithi Croatia_N Croatia_EN_Impressa Greece_Minoan_Lassithi Italy_Imperial Italy_Imperial Croatia_N Italy_Imperial Greece_BA_Mycenaean_Pylos Greece_Minoan_Lassithi Greece_Minoan_Lassithi Greece_Minoan_Odigitria Croatia_C Greece_BA_Mycenaean_Pylos Italy_Imperial Greece_BA_Mycenaean Greece_BA_Mycenaean Greece_Minoan_Odigitria Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_Crete_Armenoi Greece_BA_Mycenaean ORD011 ORD019 SAL007 SAL010 Italy_Central_Republic_IA Italy_Central_Republic_IA Italy_Central_Republic_IA Greece_Crete_Armenoi Croatia_EIA Croatia_LateC_EBA_Vucedol Croatia_MBA Croatia_C Croatia_EN_Impressa Croatia_MBA Croatia_EIA Croatia_LateC_EBA_Vucedol Croatia_N Croatia_EIA Croatia_MN Italy_Central_Republic_IA Croatia_MBA Croatia_EN_Impressa Croatia_LateC_EBA_Vucedol Croatia_EIA Croatia_MN Greece_Minoan_Odigitria Croatia_C Croatia_N Croatia_LateC_EBA_Vucedol Croatia_MN Croatia_EN_Impressa Croatia_EN_Impressa Greece_Minoan_Odigitria Greece_BA_Mycenaean_Pylos Croatia_N Croatia_MBA Greece_BA_Mycenaean_Pylos Croatia_N Italy_Imperial Greece_BA_Mycenaean Greece_Minoan_Lassithi Italy_Imperial Greece_Minoan_Lassithi Croatia_MN Italy_Imperial Greece_BA_Mycenaean Greece_Minoan_Odigitria Greece_BA_Mycenaean_Pylos Croatia_C Greece_Minoan_Lassithi Greece_BA_Mycenaean Greece_Minoan_Lassithi Greece_Crete_Armenoi Croatia_C Greece_Crete_Armenoi Greece_Minoan_Odigitria Greece_BA_Mycenaean Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Italy_Imperial ORD014 ORD009 ORD004 SAL003 Italy_Central_Republic_IA Italy_Central_Republic_IA Italy_Central_Republic_IA Italy_Central_Republic_IA Croatia_MBA Croatia_C Croatia_EIA Croatia_C Croatia_EIA Croatia_EIA Croatia_MBA Croatia_MBA Croatia_N Croatia_MBA Croatia_N Croatia_EIA Croatia_LateC_EBA_Vucedol Croatia_LateC_EBA_Vucedol Croatia_EN_Impressa Greece_Minoan_Odigitria Croatia_MN Croatia_N Croatia_C Croatia_MN Greece_Minoan_Odigitria Croatia_EN_Impressa Greece_Minoan_Odigitria Croatia_EN_Impressa Croatia_C Croatia_MN Croatia_LateC_EBA_Vucedol Croatia_N Croatia_EN_Impressa Greece_Minoan_Odigitria Italy_Imperial Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Greece_Minoan_Lassithi Croatia_MN Greece_BA_Mycenaean Greece_BA_Mycenaean Italy_Imperial Greece_Minoan_Lassithi Greece_Minoan_Lassithi Italy_Imperial Greece_BA_Mycenaean Greece_BA_Mycenaean Italy_Imperial Greece_Crete_Armenoi Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Greece_Crete_Armenoi Greece_Crete_Armenoi SGR003 SAL011 SGR001 ORD010 Croatia_EIA Greece_Crete_Armenoi Italy_Central_Republic_IA Italy_Central_Republic_IA Greece_Minoan_Odigitria Croatia_EIA Croatia_MBA Croatia_EIA Italy_Central_Republic_IA Italy_Central_Republic_IA Croatia_C Croatia_MBA Croatia_C Croatia_MBA Croatia_EIA Croatia_LateC_EBA_Vucedol Croatia_MN Croatia_MN Greece_BA_Mycenaean Croatia_EN_Impressa Croatia_LateC_EBA_Vucedol Croatia_N Croatia_LateC_EBA_Vucedol Croatia_C Croatia_EN_Impressa Croatia_LateC_EBA_Vucedol Croatia_MN Croatia_MN Croatia_MBA Croatia_EN_Impressa Croatia_EN_Impressa Croatia_N Italy_Imperial Greece_Minoan_Odigitria Croatia_N Greece_Crete_Armenoi Croatia_N Greece_Minoan_Lassithi Greece_Minoan_Odigitria Greece_BA_Mycenaean Greece_BA_Mycenaean Italy_Imperial Greece_Minoan_Lassithi Greece_Minoan_Lassithi Greece_Minoan_Lassithi Croatia_C Italy_Imperial Greece_BA_Mycenaean_Pylos Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Italy_Imperial Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean Greece_Crete_Armenoi Greece_Minoan_Odigitria −0.01 0.00 0.01 −0.01 0.00 0.01 −0.01 0.00 0.01 −0.01 0.00 0.01 B f4(X, IAA; CHG, Mbuti) SAL001 ORD006 ORD001 SGR002 Greece_Minoan_Lassithi Croatia_EIA Croatia_EIA Croatia_EIA Greece_Minoan_Odigitria Croatia_LateC_EBA_Vucedol Greece_Minoan_Odigitria Greece_Minoan_Odigitria Croatia_EIA Italy_Central_Republic_IA Croatia_MBA Croatia_LateC_EBA_Vucedol Croatia_EN_Impressa Croatia_C Italy_Central_Republic_IA Greece_Crete_Armenoi Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Greece_BA_Mycenaean Croatia_C Greece_BA_Mycenaean Italy_Imperial Croatia_MN Croatia_N Croatia_N Croatia_EN_Impressa Italy_Imperial Croatia_EN_Impressa Italy_Imperial Croatia_MN Croatia_N Italy_Central_Republic_IA Italy_Central_Republic_IA Croatia_MBA Greece_Minoan_Lassithi Croatia_MBA Croatia_MBA Croatia_N Croatia_EN_Impressa Italy_Imperial Croatia_C Greece_BA_Mycenaean Croatia_C Greece_Minoan_Lassithi Greece_BA_Mycenaean_Pylos Greece_Minoan_Odigitria Croatia_LateC_EBA_Vucedol Croatia_MN Croatia_MN Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos ORD011 ORD019 SAL007 SAL010 Croatia_LateC_EBA_Vucedol Croatia_EIA Greece_BA_Mycenaean Greece_Crete_Armenoi Greece_Crete_Armenoi Greece_Crete_Armenoi Croatia_MBA Croatia_C Croatia_EIA Croatia_EN_Impressa Croatia_EIA Croatia_EIA Italy_Imperial Italy_Central_Republic_IA Italy_Central_Republic_IA Greece_BA_Mycenaean Croatia_EN_Impressa Croatia_C Greece_Minoan_Lassithi Croatia_MN Italy_Central_Republic_IA Italy_Imperial Croatia_LateC_EBA_Vucedol Italy_Imperial Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean Italy_Imperial Italy_Central_Republic_IA Croatia_N Croatia_MBA Greece_Crete_Armenoi Croatia_EN_Impressa Greece_Minoan_Lassithi Greece_Minoan_Odigitria Greece_Minoan_Odigitria Greece_Minoan_Odigitria Croatia_MBA Greece_Minoan_Lassithi Croatia_N Greece_Minoan_Lassithi Croatia_MN Croatia_MN Croatia_MN Croatia_N Greece_Minoan_Odigitria Greece_BA_Mycenaean_Pylos Croatia_EN_Impressa Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean Croatia_LateC_EBA_Vucedol Croatia_C Croatia_MBA Croatia_C Croatia_N Greece_BA_Mycenaean_Pylos Croatia_LateC_EBA_Vucedol ORD014 ORD009 ORD004 SAL003 Croatia_EIA Croatia_EIA Croatia_C Croatia_EIA Greece_Minoan_Odigitria Greece_Minoan_Odigitria Greece_Minoan_Odigitria Croatia_LateC_EBA_Vucedol Croatia_MBA Croatia_C Croatia_EIA Croatia_C Croatia_N Italy_Central_Republic_IA Italy_Central_Republic_IA Italy_Imperial Croatia_LateC_EBA_Vucedol Croatia_MBA Greece_Minoan_Lassithi Croatia_MBA Italy_Imperial Italy_Imperial Croatia_LateC_EBA_Vucedol Italy_Central_Republic_IA Greece_Minoan_Lassithi Croatia_LateC_EBA_Vucedol Italy_Imperial Greece_Minoan_Lassithi Italy_Central_Republic_IA Greece_Minoan_Lassithi Croatia_N Greece_BA_Mycenaean Greece_BA_Mycenaean Croatia_EN_Impressa Greece_BA_Mycenaean Croatia_MN Croatia_MN Croatia_N Croatia_MN Croatia_EN_Impressa Croatia_C Croatia_MN Croatia_EN_Impressa Greece_Minoan_Odigitria Croatia_EN_Impressa Greece_BA_Mycenaean Croatia_MBA Croatia_N Greece_Crete_Armenoi Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Greece_Crete_Armenoi Greece_Crete_Armenoi SGR003 SAL011 SGR001 ORD010 Croatia_C Greece_BA_Mycenaean_Pylos Croatia_LateC_EBA_Vucedol Croatia_EIA Croatia_EIA Croatia_EIA Italy_Central_Republic_IA Greece_Crete_Armenoi Greece_Minoan_Odigitria Greece_Minoan_Odigitria Greece_BA_Mycenaean Greece_Minoan_Odigitria Croatia_LateC_EBA_Vucedol Greece_BA_Mycenaean Croatia_MBA Croatia_LateC_EBA_Vucedol Italy_Central_Republic_IA Greece_Crete_Armenoi Croatia_EIA Greece_Minoan_Lassithi Croatia_MN Greece_Minoan_Lassithi Italy_Imperial Italy_Central_Republic_IA Italy_Imperial Italy_Central_Republic_IA Croatia_EN_Impressa Italy_Imperial Greece_Minoan_Lassithi Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Greece_BA_Mycenaean Greece_BA_Mycenaean Croatia_MBA Croatia_MN Croatia_MBA Croatia_EN_Impressa Croatia_EN_Impressa Croatia_N Croatia_EN_Impressa Croatia_N Croatia_N Greece_Minoan_Odigitria Croatia_MN Croatia_MBA Italy_Imperial Greece_Crete_Armenoi Croatia_C Greece_BA_Mycenaean_Pylos Croatia_C Croatia_C Croatia_N Greece_Crete_Armenoi Croatia_MN Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos −0.01 0.00 0.01 −0.01 0.00 0.01 −0.01 0.00 0.01 −0.01 0.00 0.01 C f4(X, IAA; IN, Mbuti)

SAL001 ORD006 ORD001 SGR002 Greece_Crete_Armenoi Croatia_C Croatia_EIA Greece_Crete_Armenoi Croatia_MBA Greece_Minoan_Lassithi Greece_Minoan_Odigitria Croatia_LateC_EBA_Vucedol Croatia_LateC_EBA_Vucedol Greece_Minoan_Odigitria Croatia_MBA Croatia_EN_Impressa Greece_Minoan_Odigitria Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Croatia_EIA Greece_Minoan_Lassithi Croatia_EIA Croatia_MN Croatia_MBA Greece_BA_Mycenaean Croatia_MBA Italy_Imperial Italy_Imperial Italy_Imperial Italy_Imperial Greece_BA_Mycenaean Greece_Minoan_Odigitria Croatia_EIA Italy_Central_Republic_IA Croatia_N Greece_BA_Mycenaean Croatia_MN Greece_BA_Mycenaean Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Croatia_C Croatia_MN Italy_Central_Republic_IA Croatia_C Italy_Central_Republic_IA Croatia_EN_Impressa Croatia_EN_Impressa Croatia_N Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Croatia_C Italy_Central_Republic_IA Croatia_N Croatia_N Greece_BA_Mycenaean_Pylos Croatia_MN Croatia_EN_Impressa Greece_Crete_Armenoi Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos ORD011 ORD019 SAL007 SAL010 Greece_Crete_Armenoi Greece_Minoan_Odigitria Greece_Crete_Armenoi Croatia_EIA Greece_Minoan_Lassithi Greece_Crete_Armenoi Croatia_MBA Greece_Minoan_Odigitria Italy_Imperial Greece_BA_Mycenaean Croatia_LateC_EBA_Vucedol Greece_Crete_Armenoi Croatia_EIA Croatia_EIA Italy_Imperial Croatia_C Croatia_LateC_EBA_Vucedol Croatia_MBA Greece_Minoan_Lassithi Italy_Imperial Greece_Minoan_Odigitria Italy_Imperial Croatia_MN Greece_Minoan_Lassithi Greece_BA_Mycenaean Greece_Minoan_Lassithi Italy_Central_Republic_IA Croatia_EN_Impressa Croatia_EN_Impressa Greece_BA_Mycenaean_Pylos Greece_Minoan_Odigitria Italy_Central_Republic_IA Croatia_MN Italy_Central_Republic_IA Croatia_EIA Croatia_MN Croatia_MBA Croatia_EN_Impressa Croatia_N Greece_BA_Mycenaean Italy_Central_Republic_IA Croatia_LateC_EBA_Vucedol Greece_BA_Mycenaean Croatia_MBA Greece_BA_Mycenaean_Pylos Croatia_MN Croatia_EN_Impressa Croatia_LateC_EBA_Vucedol Croatia_N Croatia_N Croatia_C Croatia_N Croatia_C Croatia_C Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos ORD014 ORD009 ORD004 SAL003 Croatia_EIA Croatia_EIA Greece_Minoan_Odigitria Greece_Minoan_Odigitria Croatia_MBA Greece_Minoan_Odigitria Greece_Minoan_Lassithi Croatia_MBA Greece_BA_Mycenaean Croatia_LateC_EBA_Vucedol Croatia_MBA Italy_Imperial Italy_Imperial Italy_Imperial Italy_Imperial Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Croatia_MBA Croatia_LateC_EBA_Vucedol Greece_Minoan_Lassithi Greece_Minoan_Odigitria Greece_Minoan_Lassithi Croatia_EN_Impressa Greece_Crete_Armenoi Croatia_LateC_EBA_Vucedol Greece_BA_Mycenaean Italy_Central_Republic_IA Croatia_EIA Croatia_MN Croatia_C Greece_BA_Mycenaean Italy_Central_Republic_IA Italy_Central_Republic_IA Croatia_EN_Impressa Croatia_C Greece_BA_Mycenaean Croatia_N Italy_Central_Republic_IA Croatia_MN Croatia_C Croatia_EN_Impressa Croatia_MN Croatia_EIA Greece_BA_Mycenaean_Pylos Greece_BA_Mycenaean_Pylos Croatia_N Croatia_N Croatia_MN Croatia_C Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Croatia_N Greece_Crete_Armenoi Greece_BA_Mycenaean_Pylos Greece_Crete_Armenoi Croatia_EN_Impressa SGR003 SAL011 SGR001 ORD010 Greece_Crete_Armenoi Croatia_EIA Croatia_LateC_EBA_Vucedol Croatia_EIA Croatia_EIA Greece_BA_Mycenaean_Pylos Greece_Minoan_Odigitria Greece_Minoan_Odigitria Croatia_C Greece_Crete_Armenoi Croatia_EIA Greece_Crete_Armenoi Greece_Minoan_Odigitria Greece_Minoan_Odigitria Italy_Imperial Croatia_MBA Italy_Central_Republic_IA Italy_Central_Republic_IA Greece_BA_Mycenaean Italy_Imperial Italy_Imperial Italy_Imperial Croatia_MBA Greece_BA_Mycenaean Greece_BA_Mycenaean Greece_Minoan_Lassithi Italy_Central_Republic_IA Croatia_LateC_EBA_Vucedol Croatia_EN_Impressa Croatia_MBA Greece_Minoan_Lassithi Greece_Minoan_Lassithi Greece_Minoan_Lassithi Croatia_LateC_EBA_Vucedol Croatia_C Italy_Central_Republic_IA Croatia_MN Croatia_N Croatia_EN_Impressa Croatia_EN_Impressa Croatia_MBA Croatia_EN_Impressa Greece_BA_Mycenaean_Pylos Croatia_MN Croatia_LateC_EBA_Vucedol Croatia_MN Croatia_MN Croatia_C Croatia_N Greece_BA_Mycenaean Greece_Crete_Armenoi Croatia_N Greece_BA_Mycenaean_Pylos Croatia_C Croatia_N Greece_BA_Mycenaean_Pylos −0.005 0.000 0.005 0.010 −0.005 0.000 0.005 0.010 −0.005 0.000 0.005 0.010 −0.005 0.000 0.005 0.010

Figure S6. Genetic relationships among Iroan Age Apulians (IAA), their putative sources (ancient populations coming from Crete, Peloponnese, Croatia and Iron Age Italians) and Caucasus, Western hunter-gatherer (CHG and WHG, respectively) and Iranian Neolithic (IN) components. A) f 4(X, IAA; WHG, Mbuti) values, where X is a putative source of the Daunian population. B) and C) Same as A, using CHG and IN, respectively. Purple points represent f 4 values with signiﬁcant Z-scores (|Z| ≥ 3), pink points represent almost signiﬁcant f 4 values (2 ≤ |Z| < 3), while dashed lines indicate f 4 runs involving less than 5,000 SNPs. Also the Middle Age Apulian samples (ORD010 and SGR001) were added for comparison. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

A. B. K=2 K=2

K=3 K=3

K=4 K=4

K=5 K=5

K=6 K=6

K=7 K=7

K=8 K=8

K=9 K=9

K=10 K=10 EHG SAL001 SAL003 SAL007 SAL010 SAL011 SGR001 SGR002 SGR003 Spain_C ORD001 ORD004 ORD006 ORD009 ORD010 ORD011 ORD014 ORD019 an_A r I an_N r I z d Ezi Sicily_EBA Spain_EN Spain_I A a olinoGat t LaSassa an_BA r I an_CA r I A an_I r I aly_LA t I Spain_LN Taglient e rael_C sr I Villabr una z ri Aze e bia_ENSer Spain_EBA Russia_BA Bulgar ia_N ia_CCr oat rotia_NCr oat A Czech_I England_N a via_BALat via_HGLat Gr eece_N ia_BA ber I roion_BABr oion_CABr Spain_LBA rael_I A sr I aine_NUkr ntolia_CAnat ntolia_NAnat r k e Gre mykKu z chCze ze Dru ctland_NScot Nor A way_I Loschbour ugal_C t Por Rom ania_C Czech_EBA England_I A onia_BAEst onia_I A Est rance_ENFr A ance_I Fr ance_LNFr via_M N Lat otenki14Kost Gr eece_LN biza_PunicI roion_EBABr Bulgar ia_I A rmenia_C m Ar Spain_M BA Spain_M LN aly_C_BA t I yian a Syri Tu sh rki ezg n L i alk r ka l Ba rotia_EI A Cr oat rotia_M N Cr oat England_LBA ance_EBAFr ance_LBAFr rac_ N ance_M Fr Hungar y_EC Hungar y_EN Bulgar ia_EBA zrbaijan_CAzer baijan_NAzer e any_N Ger m Gibr _EN alt ar aly_Sicily_N t I dan_EBAJor dan_LBAJor ntolia_EBAAnat rael_PPNB sr I r ch n Fre dy i e yg Ad y iot o ri Cyp ctland_LBAScot rocco_EN or M occo_LN or M acedonia_NM ugal_EBA t Por ugal_LBA t Por ugal_M N t Por Caucasus_HG rotia_M BACr oat k_BADenm ar A k_I Denm ar k_LN Denm ar England_M BA rac_ BA ance_M Fr A2Lebanon_I A3Lebanon_I Hungar y_EBA Spain_I A_Celt rmenia_EBA m Ar enia_LBA m Ar Spain_Rom an Gibr _EBA alt ar aly_Sicily_BA t I dan_PPNBJor dan_PPNCJor rael_M LBA sr I mhra_NAF har Am usian ssi a Ru sh tti Sco n a i ci l Si alt se te l Ma as e u sq Ba sh i n n Fi z u a g Ga n a i n Ira Assyri n a sh i l g En ctland_MScot BA Russia_M aikop drn_Apulia oder M aly t n_I oder M ugal_LN_C t Por ugal_M BA t Por England_C_EBA rance_EM BAFr Lebanon_M BA Bulgar ia_M LBA rmenia_M BA m Ar aly_Sicily_C_o t I aly_Sicily_EBA t I aly_Sicily_LBA t I l_ e ial per aly_I m t I Swit land_LN zer A_o2 key_I Tur A_o3 key_I Tur ntolia_MAnat LBA panish i n a Sp set n a Osse ti Russia_Scyt hian land_C_EBAScot utria_EN_LBK r Aust rance_EN_MFr N aly_Sar dinia_N t I dan_LBA_IJor A aly_Sar dinia_C t I Swit land_EBA zer aly_Cent al_C t r I aly_Cent al_N t r I radian a i Orca d hec n e ch e Ch n a ti a Cro n a ti yp Eg n a i n Esto Russia_Ekven_I A Lebanon_Rom an A o_I enegr ont M Poland_BellBeaker Czech_BellBeaker y ia_Ebla_EMSyr BA aly_Sar dinia_I t I A aine_ScytUkr hian ntolia_IAnat epe kizt aly_Cent al_M t r I kainian a i n i Ukra oldavi n d a l Mo ovi n rd a Mo eor n a i rg o Ge lbanian a i n a b Al n a i n Arme usaSrma ianRussia_Sar at m England_BellBeaker oldova_Scyt hianM o_LBA enegr ont M ReginaM a it gher ar rance_BellBeakerFr Lebanon_ERom an Lebanon_Hellenist ic aly_Sicily_EBA_o1 t I aly_Sicily_EBA_o2 t I ugryMN_LBKHungar y_M l_ e an_CA aly_I cem t I Swit land_Bichon zer aly_Sar dinia_LBA t I aly_Sar dinia_EBA t I ntolia_CentAnat al_N r om n a i n ma Ro n a i n i rd Sa bk ian si a a kh Ab n a i n a rd Jo se e n a b e L edouinA n i u o d Be B n i u o d Be n a ri a g l Bu Russia_Lat aikop eM Spain_EBA_M allor ca Spain_Gr eek_oLocal England_I A_Rom an aly_Rem t edello_CAI aly_Sar dinia_M t I BA o a_a e_PPNB dan_Lat Jor aly_I A_Republic_o t I ntolia_Boncuklu_NAnat oregian a i g rwe No ungar n a ri a g n Hu elar ian si a ru a l Be oldova_Cim ianM er m Cr im ea_Pant ikapaion Czech_Cor e dedWar England_I A_ERom an e any_BellBeakerGer m aly_Rem t edello_EBAI Spain_I essian A_Tar t Spain_Rom an_oLocal aly_Sicily_BellBeaker t I rael_Ashkelon_I sr I A1 ael_Ashkelon_I sr I A2 ael_Ashkelon_LBA sr I ntolia_TellKurAnat du_EC ntolia_KumAnat epe_N t alesinian a i n sti e l Pa huanian a i n a u th i L s onia_CorEst e dedWar Russia_EBA_Yam naya Spain_Gr eek_oAegean ugryIA_Scyt hianHungar y_I Spain_Hellenist ic_oLocal Swit land_BellBeaker zer aly_Sar dinia_Rom t I an ntolia_Alalakh_MAnat LBA Russia_St aikop eppe_M rotia_EN_I essa pr Cr oat m Spain_Rom an_oAegean aly_Sar dinia_M t I edieval rael_Ashkelon_I sr I A1_o ial_o3. per R68 aly_I m t I ial_o4. per R42 aly_I m t ial_o4.I per R70 aly_I m t ial_o5.I per R67 aly_I m t I l_ e ial_o1. per R45 aly_I m t ial_o1.I per R80 aly_I m t I ntolia_TellKurAnat olia_TepecikCifAnat du_EM C lik_N t aine_EBA_YamUkr naya ntolia_Buyukkaya_ECAnat Russia_Nor h_Caucasus t Russia_Ear ian at ly_Sar m ianRussia_Lat at e_Sar m Hungar y_EBA_BellBeaker Spain_Hellenist ic_oAegean aly_Sar dinia_Rom t I an_o ian at an_Sar m Kazakhst e n_o eWre any_Cor dedWar Ger m Gr eece_BA_M ycenaean enoi e_Ar m Gr eece_Cr et inoan_LassitGr eece_M hi inoan_OdigitGr eece_M ia r l_ e ial_o2. per R111 aly_I m t I ntolia_TitAnat isHoyuk_EBA r ntolia_IAnat eC epe_Lat kizt ntolia_ArAnat slant epe_EBA t orth No _ n a i l Ita l_ e ial_o3. per R1551 aly_I m t I ial_o4. per R1547 aly_I m t ial_o4.I per R1550 aly_I m t I aly_Nor h_BellBeaker t t I _1 aly_Nor h_BellBeaker t t I _2 aly_Nor h_BellBeaker t t I _3 aly_Sar dinia_BA_Nur t I agic pi_ AFrmete a Spain_M er BA_For ent m rael_M iddle_Lat sr e_PPNBI aly_Sar dinia_I t I A_Punic_1 aly_Sar dinia_I t I A_Punic_2 aly_Cent al_Republic_I t r I A t outh u So _ n a i l Ita Russia_I ian A_Ear at lySar m aly_Sar dinia_EBA_Nur t I agic ntolia_ArAnat eC slant epe_Lat panis orth No _ sh i n a Sp rotia_Lat eC_EBA_VucedolCr oat e n_ltte hohle_M N er any_BlatGer t m uris alik si r ke i l Ba Tu _ sh rki aly_Sar dinia_C_M t I eClar ont o ntolia_CamAnat libelTar lasi_Lat eC kainian_N rth No _ n a i n i Ukra anar_Ilander e d n a Isl ry_ a n Ca Russia_Nor h_Caucasus_M BA t Gr eece_BA_M ycenaean_Pylos l_ e ial_oAf per ican. R132 aly_I m r t I k ieIAWs rncthian nScyt er aine_IUkr A_West r andari a d n Ba _ n a i n Ira Russia_Sam a_EBA_Yam ar naya o naIroGte_ esolit onGat es_M Rom ania_I hic r Russia_Kalm ykia_EBA_Yam naya aly_Sar dinia_M t I BA_published_o e_M lim sl i Mu _ se e n a b e L gp Ti In rmediat ePer iod m er nt _ThirEgypt dI e_C isian a sti ri Ch _ se e n a b e L Belgium _UP_Goyet Q116_1_published_all l_ e ial_oCent per alEur aly_I m R37 r opean. t I l_ e ial_oCent per alEur aly_I m R116 r opean. t I aly_Nor h_Ear edieval_Langobar lyM t t I ds_1 aly_Nor h_Ear edieval_Langobar lyM t t I ds_2 aly_Nor h_Ear edieval_Langobar lyM t t I ds_3 aly_Nor h_Ear edieval_Langobar lyM t t I ds_4 aly_I A_Republic_oEast anean t r I edit er nM er aly_I A_Republic_oEast anean_o t r I edit er nM er

Figure S7. Model-based clustering on modern and ancient individuals as inferred by ADMIXTURE. A) The ancestral components were inferred in a set of 90 modern Eurasian populations. B) Using the allele frequency for ancestral components inferred in A. we projected a subset of ancient Europasian individuals. bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454498; this version posted July 30, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Figure S8. f4 analyses investigating the genetic heterogeneity of IAA samples. A) Almost significant f 4 values involving a putative first-degree relationship between ORD009 and ORD001 (possibly, mother and daughter). B) f 4 analyses involving Rome Republicans, IAA and Levant N/YRI. C) and D) show the f 4 analyses involving IAA, Levant N and, alternatively, CHG and IN. In all plots, purple points represent f 4 values with significant Z-scores (|Z| ≥ 3), pink points represent almost significant f 4 values (2 ≤ |Z| < 3), while dashed lines indicate f 4 runs involving less than 5,000 SNPs. Also the Middle Age Apulian samples (ORD010 and SGR001) were added for comparison.