High-resolution mitochondrial DNA analysis sheds
light on human diversity, cultural interactions, and population
mobility in Northwestern Amazonia
Department of Evolutionary Genetics, Max
Planck Institute for Evolutionary
Anthropology, Leipzig D-04103, Germany
Department of Linguistic and Cultural
Evolution, Max Planck Institute for the
Science of Human History, Jena D-07745,
Laboratorio de Gen
Humana, Universidad del Valle, Cali,
Dynamique du Langage, UMR5596, CNRS
e de Lyon, Lyon Cedex 07
Leonardo Arias, Department of
Evolutionary Genetics, Max-Planck-Institute
for Evolutionary Anthropology, Deutscher
Platz 6, Leipzig, D-04103, Germany.
Departamento Administrativo de Ciencia,
Tecnología e Innovaci
Max Planck Society
Objectives: Northwestern Amazonia (NWA) is a center of high linguistic and cultural diversity.
Several language families and linguistic isolates occur in this region, as well as different subsistence
patterns, with some groups being foragers and others agriculturalists. In addition, speakers of East-
ern Tukanoan languages are known for practicing linguistic exogamy, a marriage system in which
partners are taken from different language groups. In this study, we use high-resolution mitochon-
drial DNA sequencing to investigate the impact of this linguistic and cultural diversity on the
genetic relationships and population structure of NWA groups.
Methods: We collected saliva samples from individuals representing 40 different NWA ethnolin-
guistic groups and sequenced 439 complete mitochondrial genomes to an average coverage of
Results: The mtDNA data revealed that NWA populations have high genetic diversity with exten-
sive sharing of haplotypes among groups. Moreover, groups who practice linguistic exogamy have
higher genetic diversity, while the foraging Nukak have lower genetic diversity. We also find that
rivers play a more important role than either geography or language affiliation in structuring the
genetic relationships of populations.
Discussion: Contrary to the view of NWA as a pristine area inhabited by small human populations
living in isolation, our data support a view of high diversity and contact among different ethnolin-
guistic groups, with movement along rivers probably facilitating this contact. Additionally, we
provide evidence for the impact of cultural practices, such as linguistic exogamy, on patterns of
genetic variation. Overall, this study provides new data and insights into a remote and little-
studied region of the world.
haplogroup, South America, language, exogamy, Amazonia
Northwestern Amazonia (NWA) contains tremendous biological, lin-
guistic, and cultural diversity, which likely reflects the heterogeneity of
the landscape, especially the complex and extensive network of rivers
found in this area. The region (Figure 1) extends from the Andean foot-
hills in the west to the area between the Orinoco River and the Rio
Negro in the east, and extends south until the confluence between the
Rio Negro and the Amazon River. The northern border is defined by
the Eastern Andean Cordillera and the Colombian-Venezuelan llanos,
and the southern by the full length of the Putumayo River (Eriksen,
In terms of linguistic diversity, NWA harbors ethnolinguistic groups
belonging to the main South American language families accepted by
Am J Phys Anthropol.2017;1–18. wileyonlinelibrary.com/journal/ajpa V
C2017 Wiley Periodicals, Inc.
Received: 20 February 2017
Revised: 17 September 2017
Accepted: 7 October 2017
most linguists (Campbell, 1997; Chacon, 2014; Dixon and Aikhenvald,
1999), namely Arawakan, Carib, Tupi, and Quechua. Additionally,
several local language families are also present, such as Tukanoan,
Guahiban, Huitotoan, Boran, Peba-Yaguan, Piaroa-Saliban, and Maku-
Puinave (see glottolog.org for a classification of the language families),
as well as various isolate languages like Tikuna, Cofan, and Kamentsa
(Landaburu, 2000). Furthermore, several indigenous groups live in vol-
untary isolation, and almost nothing is known about their linguistic
affiliation (Franco, 2002). The area has been proposed as the place of
origin of the Arawakan family, since it contains the highest linguistic
diversity within the family (Aikhenvald, 1999; Heckenberger, 2002;
Zucchi, 2002). In addition, all 20 languages of the Tukanoan family are
found in the area. These are classified into two branches: the Western
Tukanoan branch distributed along the Putumayo, Caquet
a, and Napo
Rivers and the Eastern Tukanoan branch along the Vaup
es, Rio Negro,
and Apaporis Rivers and their tributaries (Chacon, 2014). The Carib,
Tupi, and Quechua language families are probably recent immigrants to
NWA, since only one language per family is present in the area, while
the majority of languages within these families are found elsewhere. In
addition, the Tupi language Nheengat
u or Lingua Geral is found in the
region; however, this is a very recent introduction spread by mission-
aries during the 17th and 18th centuries and by traders during the
rubber boom in the 19th century, when it was used as a trade language
(Sorensen, 1967; Stenzel, 2005).
In terms of cultural diversity, while NWA has often been viewed as
a pristine area inhabited only by small, isolated, seminomadic tribes
with an economy based on hunting and gathering (Denevan, 1992;
Meggers, 1954), in fact there is considerable variation in subsistence
and marriage practices. Although some groups are traditional foragers,
others engage in agriculture, and instead of being isolated, archeologi-
cal and anthropological evidence now shows that NWA was indeed
part of a continent-wide network of exchange and trade. Complex soci-
eties organized in chiefdoms and multiethnic confederations arose in
the region, and multilingualism and extensive interactions among eth-
nolinguistic groups were the norm (Heckenberger, 2002; Hornborg,
2005; Santos-Granero, 2002; Vidal, 1997).
In particular, the groups speaking Eastern Tukanoan languages and
some of their Arawakan neighbors living in the basin of the Vaup
River and Rio Negro engage in an exceptional marital practice known
as linguistic exogamy (Aikhenvald, 1996; Chacon and Cay
Sorensen, 1967; Stenzel, 2005). According to this cultural norm, indi-
viduals are required to marry someone from a different language group,
with each individual’s linguistic affiliation being determined by the lan-
guage of the father. Linguistic exogamy thus creates a situation of
FIGURE 1 Geographic location of the sampling sites. Every triangle corresponds to a single community, which may contain more than one
ethnolinguistic group. 1. Curripaco and Bare, 2. Matapi, 3. Ach-Piapoco, 4. Yucuna, 5. Carijona, 6. Desano, Yuruti, Pisamira, and Karapana, 7.
Pira-Wanano, 8. Siriano, 9. Tanimuka, 10. Tukano, 11. Tuyuca and Tatuyo, 12. Coreguaje, 13. Siona, 14. Guayabero, 15. Sikuani, 16. Murui,
17.Uitoto, 18. Kamentsa, 19. Nukak, 20. Puinave, 21. Pasto, 22. Yagua, 23. Saliba, 24. Inga, 25. Tikuna, 26. Cocama
ARIAS ET AL.
multilingualism and movement of people (particularly women, since it is
accompanied by patrilocality and patrilineality) among the groups par-
ticipating in the system (Sorensen, 1967).
Historical linguistics, cultural anthropology, and archeology are the
main disciplines that have traditionally addressed questions regarding
the origins, pre-history, and genetic relationships of NWA ethnolinguis-
tic groups (Campbell, 1997; Chacon, 2014; Heckenberger, 2008; Lath-
rap, 1970; Meggers, 1948; Nettle, 1999). However, due to the
incomplete archeological record, the limitations of linguistic methods
based on lexical cognates to establish deep time relationships (Dediu
and Levinson, 2012; Hock and Joseph, 2009), and the insufficiency of
documentation and description of a large number of the NWA soci-
eties, many of these questions remain to be fully answered. The oldest
archeological evidence of human occupation in NWA comes from a
single site on the Middle Caquet
a River, which has been dated
between 9250 and 8100 BP. It contains a great variety of stone arti-
facts, carbonized seeds and other botanical remains from different
palm species, as well as phytoliths of bottle gourd, leren, and pumpkin
(Aceituno, Loaiza, Delgado-Burbano, & Barrientos, 2013; Gnecco and
Mora, 1997), indicating that these early human groups relied on vege-
table resources that are still being exploited by contemporary societies
One hypothesis about the peopling of NWA was proposed by
u (1950), who suggested that the region was first inhabited
by hunter-gatherer populations (HGPs), perhaps the ancestors of the
Maku-Puinave groups, most of whom still practice a foraging lifestyle.
Proto-Arawakan groups then started expanding into the region from
their place of origin located between the Orinoco River and the Rio
Negro (Heckenberger, 2002; Lathrap, 1970). Finally, the Tukanoans are
assumed to have arrived in the area and displaced peoples speaking
Arawakan and Maku-Puinave languages from the Vaup
es (the Tukano-
ans probably came from the Napo-Putumayo, where Western Tukano-
ans still live). However, this scenario does not account for the presence
of groups belonging to the Carib, Guahiban, Huitotoan, and Boran lan-
guage families and the various language isolates in the region.
Genetic studies can provide insights into population history, and
indeed studies of mitochondrial DNA (mtDNA) genetic variation in
Native American populations have contributed greatly to our knowl-
edge about the peopling of the Americas. Early studies using restriction
fragment length polymorphisms (RFLP) and sequencing of the hyper-
variable region one (HVS-I) identified five founder lineages or hap-
logroups, designated as A–D and X (Bailliet, Rothhammer, Carnese,
Bravi, & Bianchi, 1994; Barbieri, Heggarty, Castri, Luiselli, & Pettener,
2011; Gaya-Vidal et al., 2011; Keyeux, Rodas, Gelvez, & Carter, 2002;
Lewis et al., 2007; Schurr, 2004; Torroni et al., 1993). Whereas hap-
logroups A–D are widely distributed in the Americas, haplogroup X is
restricted to North America (Bolnick and Smith, 2003; Malhi, Schultz, &
Smith, 2001). The analysis of HVS-I in several Native American popula-
tions showed that haplogroups A-D exhibit similar levels of diversity
(Bonatto and Salzano, 1997), supporting the hypothesis of a single ori-
gin of all Native American populations from a Northeast Asian source.
Additionally, HVS-I data have been used to determine the genetic rela-
tionships among indigenous populations in South America and to test
hypotheses concerning how genetic variation is structured at the
regional and continental levels (Barbieri et al., 2011; Gaya-Vidal et al.,
2011; Lewis et al., 2007; Marrero et al., 2007; Melton et al., 2007).
These studies revealed that Andean (or western) populations show
higher levels of diversity and low genetic distances in contrast to the
Eastern populations, who show the opposite pattern. However, in pre-
vious studies, NWA populations have been generally underrepresented,
and hence inferences about the genetic structure of the entire Amazo-
nian region are based on data from a small number of populations.
Recent developments in sequencing technology allow the determi-
nation of complete mtDNA genomes at the population level and thus
enable unbiased insights into the maternal history of human popula-
tions (Delfin et al., 2014; Gunnarsdottir, Li, Bauchet, Finstermeier, &
Stoneking, 2011; Kivisild, 2015). At present, no such studies are
reported for South American indigenous populations. Available studies
of complete mtDNA genomes from Native Americans have been
restricted to a limited number of individuals carrying particular hap-
logroups, usually selected based on their HVS-I sequences (Achilli et al.,
2013; Bodner et al., 2012; de Saint Pierre et al., 2012; Fagundes et al.,
2008; Lee and Merriwether, 2015; Perego et al., 2009, 2010), or to
archeological remains from different time periods (Fehren-Schmitz
et al., 2015; Llamas et al., 2016). These studies have primarily focused
on inferences about the peopling of the continent, the number of
migrations, the divergence times of haplogroups and changes in the
effective population size through time.
Nevertheless, several problems and biases are associated with this
sampling strategy. First, the overall diversity might be underestimated,
since individuals carrying the same HVS-I sequence can exhibit consid-
erable variation in the coding region (Gunnarsdottir et al., 2011). Sec-
ond, the reconstruction of demographic trends can be skewed, since
the estimation of effective population sizes through time using Bayes-
ian coalescent methods (i.e., Bayesian skyline plots [BSPs] in BEAST)
can generate spurious signals of population growth when based on
samples selected by haplogroup (Gunnarsdottir et al., 2011). Last, the
histories and origins of specific populations cannot be investigated,
since the coalescent age of a particular lineage does not correspond to
the age of the population, especially when the diversity within each lin-
eage is unknown (Schurr, 2004).
In this study, we use complete mtDNA sequencing in a large and
representative sample of populations covering the extant ethnolinguis-
tic diversity from NWA to reconstruct their maternal history, as well as
to determine their genetic diversity and to make inferences about the
origins of this diversity. Finally, we aim to investigate the impact of
pre-historic population dynamics and cultural interactions on the struc-
ture of the genetic variation observed among present-day NWA
MATERIALS AND METHODS
Samples from unrelated individuals belonging to 40 ethnolinguistic
groups were collected during several expeditions carried out by one of
ARIAS ET AL.
TABLE 1 Sampled ethnolinguistic groups with information on merged groups (see “Population Samples”Section) given below the compound
Population Label in Figure 1 nCensus size
Language family Subsistence strategy
River/place of residence
Yucu-Matapi 39 Arawakan AG Mirití-Paran
Yucuna 4 31 550 Arawakan AG Mirití-Paran
Matapi 2 8 220 Arawakan AG Mirití-Paran
Curripaco 17 Arawakan AG Atabapo
Curripaco 1 16 7,827 Arawakan AG Atabapo
Bare 1 1 NA
Arawakan AG Atabapo
Ach-Piapoco 24 Arawakan AG Meta
Achagua 3 6 283 Arawakan AG Meta
Piapoco 3 18 4,926 Arawakan AG Meta
1 311 Arawakan AG Mirití-Paran
Carijona 5 8 307 Carib AG Upper-Vaup
Cofan 6 877 Cofan AG Guam
Barasano 4 2,008 Eastern Tukanoan AG Upper-Vaup
Desano 6 17 2,457 Eastern Tukanoan AG Upper-Vaup
Kubeo 5 6,647 Eastern Tukanoan AG Upper-Vaup
Other-ET 10 Eastern Tukanoan AG Upper-Vaup
Tuyuca 11 7 642 Eastern Tukanoan AG Upper-Vaup
Yuruti 6 1 687 Eastern Tukanoan AG Upper-Vaup
Pisamira 6 1 61 Eastern Tukanoan AG Upper-Vaup
Karapana 6 1 464 Eastern Tukanoan AG Upper-Vaup
Pira-Wanano 13 Eastern Tukanoan AG Upper-Vaup
Piratapuyo 7 8 697 Eastern Tukanoan AG Upper-Vaup
Wanano 7 5 1,395 Eastern Tukanoan AG Upper-Vaup
Siriano 8 10 749 Eastern Tukanoan AG Upper-Vaup
Tanimuka 9 10 1,247 Eastern Tukanoan AG Mirití-Paran
Tuka-Tatuyo 10 Eastern Tukanoan AG Upper-Vaup
Tukano 10 8 6,996 Eastern Tukanoan AG Upper-Vaup
Tatuyo 11 2 331 Eastern Tukanoan AG Upper-Vaup
Siona 13 17 734 Western Tukanoan AG Putumayo
Coreguaje 12 19 2,212 Western Tukanoan AG Caquet
Sikuani 15 16 23,006 Guahiban HGP Guaviare
Guayabero 14 35 1,118 Guahiban HGP Guaviare
Saliba 23 16 1,929 Piaroa-Saliban AG Meta
26 7,343 Huitotoan AG Putumayo
Murui 16 18 Huitotoan AG Putumayo
Uitoto 17 8 Huitotoan AG Putumayo
Puinave 20 19 6,604 Maku-Puinave HGP Inirida
Nukak 19 16 1,483 Maku-Puinave HGP Interfluvial
Pasto 21 14 69,789 Pasto AG Andean
Kamentsa 18 11 4,773 Kamentsa AG Andean
Inga 24 17 19,079 Quechuan AG Andean
Tikuna 25 18 7,102 Tikuna AG Amazonas
Cocama 26 17 792 Tupi AG Amazonas
Yagua 22 13 297 Peba-Yaguan AG Amazonas
ARIAS ET AL.
the authors (L.A.) in five departments (administrative divisions) of
NWA, namely: Amazonas, Guainía, Guaviare, Meta and Putumayo
(Table 1, Figure 1). The samples consisted of either saliva (n 5400), col-
lected as 3 mL of saliva in 3 mL of lysis buffer (Quinque, Kittler, Kayser,
Stoneking, & Nasidze, 2006), or blood samples (n560) stabilized with
EDTA. Written informed consent was obtained from each participant,
and from the community leader and/or local/regional indigenous
organizations, after giving a full description of the aims of the study.
Local translators and fieldwork assistants helped to explain and trans-
late into the local languages when individuals or communities were not
proficient in Spanish. Additionally, each participant answered a short
questionnaire soliciting information regarding their birthplace, language,
ethnic affiliation and that of their parents and grandparents. The study
was approved by the ethics committee of the Universidad del Valle in
Cali, Colombia and the Ethics Commission of the University of Leipzig
Medical Faculty. All procedures were undertaken in accordance with
the Declaration of Helsinki on ethical principles and an export permit
was issued by the Colombian Ministry of Health and Social Protection.
DNA sequencing and sequence processing
The DNA was extracted from blood samples with the “salting out”
method (Miller, Dykes, & Polesky, 1988) and from the saliva samples
with the QIAamp DNA Midi kit (Qiagen), starting from 2.0 mL of the
saliva/buffer mixture. The concentration of DNA was quantified with a
NanoDrop 8000 spectrophotometer (Thermo Scientific). We prepared
genomic libraries with double indices and enriched for full mtDNA
genomes using a hybridization-capture method described previously in
Kircher, Sawyer, and Meyer (2012) and Maricic, Whitten, and Paabo
(2010). From the enriched libraries, paired-end sequences of 100 bp
length were generated on the Illumina Hiseq 2500 platform. Base-
calling was performed using freeIbis (Renaud, Kircher, Stenzel, & Kelso,
2013), and Illumina adapters were trimmed and completely overlapping
paired sequences were merged using leeHOM (Renaud, Stenzel, &
Kelso, 2014a). The sequencing data were de-multiplexed using deML
(Renaud, Stenzel, Maricic, Wiebe, & Kelso, 2014b) and the sequences
aligned against the human reference genome 19 using BWA’saln algo-
rithm (Li and Durbin, 2009). After duplicate removal using PicardTools
v2.1.1 (https://github.com/broadinstitute/picard), we performed an
iterative alignment for each library individually to obtain mtDNA con-
sensus sequences. In the first step, we extracted all sequencing reads
of a library that aligned either to the mitochondrial genome or to a list
of nuclear copies of mtDNA (Li, Schroeder, Ko, & Stoneking, 2012). We
subsequently aligned these reads to the revised Cambridge Reference
Sequence (rCRS; Andrews et al. 1999) using BowTie2’svery-sensitive
algorithm (Langmead and Salzberg, 2012) and called a consensus
sequence. In the second step, the reads were re-aligned to the library’s
respective consensus sequence generated in the first step, using the
same BowTie2 settings. After the second alignment step, we called a
final consensus sequence that was used throughout the rest of the
analysis. Final sequences in fasta format were aligned to the rCRS
(Andrews et al., 1999) with the multiple sequence alignment software
Mafft (Katoh and Standley, 2013), and manually inspected for align-
ment errors with Bioedit ver. 7.2.5 (Hall, 1999). The two poly-C regions
(np 303–315 and 16,183–16,194) were excluded from the subsequent
analyses. Although one position (16,189) diagnostic for haplogroup B2
is therefore not considered in the haplogroup calling analysis, the addi-
tional substitutions defining this haplogroup that occur elsewhere in
the mitochondrial genome enable unambiguous assignment of sequen-
ces to this lineage.
We considered populations with a sample size of 10 individuals or
more, and merged populations with sample sizes smaller than 10 based
on linguistic criteria when our initial analyses did not show significant
genetic differences, as follows (Table 1). The Arawakan groups Achagua
(n56) and Piapoco (n518) were merged into a single population, since
their indigenous reservations are adjacent and individuals often inter-
marry (data available on request); one Bare (n51) individual was added
to the Curripaco (n516) sample among whom he was living when
sampled on the Atabapo River; the Yucuna (n531) and Matapi (n58)
were merged into a single population, since they both speak Yucuna,
live along the same river, and intermarry (data available on request);
and the Murui (n518) and Uitoto (n58) were merged, as these two
groups belong to the same language family, which is composed of
several dialects that are mutually intelligible (http://glottolog.org/
resource/languoid/id/huit1251, accessed on May 31, 2017). Finally,
TABLE 1 (Continued)
Population Label in Figure 1 nCensus size
Language family Subsistence strategy
River/place of residence
Guambiano 1 23,462 Barbacoan AG Andean
Nasa 1 138,501 Nasa AG Andean
Mestizo 9 NA Mestizo
Adapted from Arango and S
AG, agriculturalist; HGP, Hunter-gatherer populations, data from D-PLACE (Kirby et al., 2016) and HG (https://huntergatherer.la.utexas.edu/home,
accessed on June 6, 2017).
NA: data not available.
Populations with label in italics were not considered in the population-based analyses.
Census data reports the population size including groups that speak five dialectal varieties.
Mestizo is an autonym used by people of mixed ancestry.
ARIAS ET AL.
following the latest classification of the Tukanoan family (Chacon,
2014), the Eastern Tukanoan groups Piratapuyo (n58) and Wanano
(n55) were merged as Pira-Wanano; Tukano (n58) and Tatuyo
(n52) were merged as Tuka-Tatuyo; and Tuyuca (n57), Yuruti (n51),
Pisamira (n51), and Karapana (n51) were merged as Other-ET. The
only group with a sample size smaller than 10 that we retained as a
separate group in the analyses were the Carijona (n58), since this is
the only Carib-speaking group living in NWA. Moreover, they are at
risk of disappearing both physically and culturally, with <30 active
speakers of Carijona scattered in two communities, and they occupy an
important place in the ethno-history of the region (Franco, 2002). We
excluded Barasano (n54), Kubeo (n55), Cofan (n56), Cabiyari
(n51), Guambiano (n51), and Nasa (n51) individuals from all the
analyses except the haplotype networks, since this analysis represents
the evolutionary relationships among individual sequences. We further-
more excluded nine individuals with maternal ancestry tracing outside
of NWA (labeled “Mestizo”in Table 1) from all analyses. After merging
and filtering as described above, 412 sequences from 24 groups were
kept in the population-based analyses.
Based on information from D-PLACE (Kirby et al. 2016) and HG data-
base (https://huntergatherer.la.utexas.edu/home, accessed on June 6,
2017), we divided the populations into agriculturalists (AG) and HGP.
In the latter category, we placed the Nukak, who currently still practice
a foraging way of life, as well as the Puinave, Sikuani, and Guayabero,
who have all adopted agriculture only very recently (Kondo, 2002;
on and Instituto Colombiano de Cultura, 1992).
The haplogroup affiliation of the individual sequences was deter-
mined with Haplogrep (Kloss-Brandstatter et al., 2011), based on Phy-
lotree build 16 (van Oven and Kayser, 2009). Haplogroup frequencies
by population were estimated by simple counting, and a correspon-
dence analysis (CA) based on the frequency of sub-haplogroups (e.g.,
A2a) was performed and visualized with the R-packages FactoMineR
(Le, Josse, & Husson, 2008) and factoextra (Kassambara and Mundt,
Population-based statistical analyses were performed with Arle-
quin v3.5 (Excoffier and Lischer, 2010). These include the analysis of
molecular variance (AMOVA), estimation of molecular diversity indices,
the estimation of pairwise genetic distances based on U
D test of selective neutrality. A multidimensional scaling analysis (MDS)
was performed on the matrix of pairwise U
values to visualize the
distances between populations. Additionally, we performed a Mantel
test to evaluate the correlations between genetic distances and geo-
graphic distances. The matrix of geographic distances was built using
the geographic coordinates of the location where the majority of sam-
ples for each ethnolinguistic group were collected and then calculating
the great circle distances between locations via the R packages ade4
and geosphere (Dray and Dufour, 2007; Hijmans, 2016). Furthermore,
a multiple regression analysis on distance matrices (MRM) (Goslee and
Urban, 2007) with the form: MRM(as.dist(gen.dist) –as.dist(geo.dist)1
as.dist(rivers.dist)) was performed. This analysis takes into consideration
a matrix of geographic distances and a matrix of proximity along rivers
as predictor variables of the genetic distances (pairwise U
between populations (Pugach et al., 2016; Yunusbayev et al., 2012).
For the matrix of river distances, a value of zero was given to popula-
tions living along the same river or on rivers that are closely connected,
and a value of one was given to populations living on different rivers.
The sharing of haplotypes between populations was estimated
with in-house R scripts as the proportion of pairs of identical sequen-
ces shared between populations. Additionally, networks of haplotypes
were constructed with the software Network ver. 220.127.116.11 and visual-
ized with Network Publisher ver. 18.104.22.168 (http://www.fluxus-engineer-
ing.com). Finally, BSPs were constructed by population and by
haplogroup (i.e., A2, B2, C1, and D1) with BEAST ver. 1.8.2 (Drum-
mond, Suchard, Xie, & Rambaut, 2012). For this analysis, the best sub-
stitution model was estimated with jModeltest 2.1.7 (Darriba, Taboada,
Doallo, & Posada, 2012), and BEAST was used to estimate whether a
strict or a relaxed clock model best fits the data. This analysis was per-
formed on both the complete sequences and the sequences partitioned
TABLE 2 Frequency of haplogroups for the 24 NWA ethnolinguis-
tic groups included in the population analyses
Population nA2 B2 C1 D1
Yucu-Matapi 39 0.28 0.10 0.56 0.05
Curripaco 17 0.18 0.53 0.24 0.06
Ach-Piapoco 24 0.54 0.04 0.42 0.00
Carijona 8 0.13 0.25 0.63 0.00
Desano 17 0.29 0.12 0.41 0.18
Other-ET 10 0.50 0.00 0.30 0.20
Pira-Wanano 13 0.31 0.08 0.38 0.23
Siriano 10 0.40 0.10 0.40 0.10
Tanimuka 10 0.50 0.10 0.40 0.00
Tuka-Tatuyo 10 0.30 0.10 0.30 0.30
Siona 17 0.59 0.35 0.00 0.06
Coreguaje 19 0.11 0.16 0.74 0.00
Sikuani 16 0.25 0.00 0.75 0.00
Guayabero 35 0.43 0.23 0.34 0.00
Saliba 16 0.19 0.06 0.56 0.19
Mur-Uitoto 26 0.23 0.12 0.31 0.35
Puinave 19 0.11 0.42 0.47 0.00
Nukak 16 0.00 0.31 0.69 0.00
Pasto 14 0.36 0.14 0.21 0.29
Kamentsa 11 0.18 0.09 0.64 0.09
Inga 17 0.59 0.06 0.29 0.06
Tikuna 18 0.44 0.00 0.44 0.11
Cocama 17 0.29 0.35 0.29 0.06
Yagua 13 0.62 0.15 0.23 0.00
ARIAS ET AL.
into coding (577–16023) and non-coding (16024-576) regions, apply-
ing the corresponding substitution rates reported previously in Soares
et al. (2009).
We generated 439 complete mitochondrial sequences to an average
coverage per sample of 1,0303, which were deposited in GenBank
with accession numbers: KY645515-KY645943 and MF152733-
MF152739. All sequences belonged to one of the main Native Ameri-
can haplogroups, namely A2, B2, C1, and D1. Haplogroups A2 and C1
were the most frequent lineages in the NWA populations (excluding
the so-called “Mestizos”), with more than half of all sequences belong-
ing to A2 and C1 together. Table 2 provides a breakdown of the hap-
logroup frequencies for the ethnolinguistic groups included in the
The CA (Figure 2) shows the clustering of populations based on
the frequency of sub-haplogroups (Supporting Information Table S1).
We observed differences among populations without a clear clustering
by language family, with the exception of the Eastern Tukanoan
groups. Most of these are clustered on the left side of the plot,
although the Tanimuka do not cluster with the other Eastern Tukanoan
groups. Additionally, Guayabero and Sikuani (who speak languages
belonging to the Guahiban family) were located close to each other in
the lower left pane of the plot. In addition to language affiliation, a few
populations clustered due to geographic proximity, namely the
Kamentsa, Pasto and Inga, who all live close to one another in the
Andean foothills. In other cases, the relatively close proximity of popu-
lations in the plot could be attributed to their being settled along the
same river or on rivers that are part of the same basin (Supporting
Information Figure S1), such as the Curripaco and Puinave, who live on
the Inírida and Atabapo Rivers.
Molecular diversity indices
The genetic variation in these communities was assessed through dif-
ferent molecular diversity indices (Figure 3 and Supporting Information
Table S2). On average, the gene diversity in these groups was high
(0.9), but there were also differences amongst them. For example, East-
ern Tukanoan groups showed consistently high values of gene diver-
sity, with the exception of the Tanimuka, who had one of the lowest
values (0.73). The Western Tukanoan groups Coreguaje (0.92) and
Siona (0.82) showed lower values than Eastern Tukanoan groups.
Among Arawakans, the Ach-Piapoco had the lowest value (0.77). The
hunter-gatherer group Nukak showed the lowest gene diversity of all
groups (0.64), with only four haplotypes observed among the 16 indi-
viduals analyzed. Additionally, agriculturalist groups tended to have
higher gene diversities (average 50.92) than hunter-gatherer groups
(average50.80) (Mann-Whitney U test, p-value5.03).
FIGURE 2 CA based on the sub-haplogroup frequencies by population. Populations are color-coded by linguistic affiliation
ARIAS ET AL.
The mean number of pairwise differences per population showed
less variation, with an average of 41.07 617.86 differences. The
smallest values were found in Sikuani (24.08 611.18) and Nukak
(31.07 614.33), and the largest values were observed in Cocama
(44.64 620.37), Carijona (42.71620.8), and Siriano (41.38619.66)
The D values of Tajima’s test of neutrality (Tajima, 1989) ranged
from 20.735 to 2.318. Under neutrality, Tajima’s D is expected to be
equal to zero, and significant departures are interpreted as a result of
selection or changes in population size. Although none of the D val-
ues were significant (all p-values >0.2; Supporting Information Table
S2), positive D values >1.2 were obtained for Guayabero, Nukak,
Sikuani, and Tanimuka, which may reflect recent reductions in the
size of these populations. This hypothesis was supported both by the
distribution of pairwise differences by population (Supporting Infor-
mation Figure S2), which showed increased frequencies for the cate-
gory of small differences (0 and 1 differences) and for the category
of large differences (50 or more), as well as by the Bayesian recon-
struction of population size changes through time (BSP plots, Sup-
porting Information Figure S3). Furthermore, the Tanimuka and
Nukak had the lowest gene diversity values of any population
A total of 216 different haplotypes were observed among the 412
sequences included in this analysis. Of these, 146 were unique haplo-
types (i.e., found in single individuals) and 70 haplotypes were shared:
39 exclusively within populations, 18 exclusively between populations,
and 13 both within and between populations. The shared haplotypes
accounted for 64.6% of all the sequences analyzed. This amount of hap-
lotype sharing between populations is quite high when compared with
other population-based studies of complete mitochondrial genomes
(Table 3). In other studies, the majority of shared haplotypes were gen-
erally observed within populations, with the exception of two African
datasets from Burkina Faso and Zambia (Barbieri, Butthof, Bostoen, &
Pakendorf, 2013; Barbieri et al. 2012), which showed low levels of shar-
ing both within and between populations. The highest level of sharing
between populations was observed for Siberian populations spread
over a large geographic area (Duggan et al., 2013); the NWA popula-
tions analyzed in this study showed the second highest value of sharing
Figure 4 shows the proportion of pairs of sequences shared
between and within NWA populations. Siriano, Other-ET, and Pasto
FIGURE 3 Molecular diversity indices by population. Dashed lines correspond to average values, except for Tajima’sDtestwhereit
corresponds to zero. Populations are color-coded by linguistic affiliation as in Figure 2
ARIAS ET AL.
were the only groups without shared haplotypes within the popula-
tions, although Siriano and Other-ET did share with other populations.
The majority of between-group haplotype sharing involved Arawakan
and Eastern Tukanoan groups. The Arawakan groups shared mostly
with groups living in close proximity (Supporting Information Figure
S4), for example, Yucu-Matapi with Tanimuka; Curripaco with Puinave
and Nukak; and Ach-Piapoco with Saliba and with the Guahiban groups
Sikuani and Guayabero. Most Eastern Tukanoan groups, who practice
linguistic exogamy, shared haplotypes among each other (except for
Tanimuka, who shared only with Yucu-Matapi). In contrast, the
TABLE 3 Shared haplotypes in a worldwide sample of complete mitochondrial sequences sampled at the population level
NW Amazonia 412 216 0.676 0.241 0.144 Present study
Burkina Faso 335 332 0.991 0.006 0.003 Barbieri et al. (2012)
SW Zambia 169 146 0.897 0.048 0.055 Barbieri et al. (2013)
Botswana/Namibia 218 128 0.75 0.188 0.133 Barbieri et al. (2014)
Philippines 365 233 0.734 0.227 0.077 Delfin et al. (2014)
Sumatra 72 48 0.771 0.229 0.021 Gunnarsdottir et al. (2011)
Taiwan 549 299 0.669 0.308 0.084 Ko et al. (2014)
Oceania 1,331 650 0.689 0.277 0.106 Duggan et al. (2014)
Siberia 525 244 0.574 0.336 0.217 Duggan et al. (2013)
113 90 0.867 0.133 0 Mizuno et al. (2014)
Note. The proportions do not sum up to 1 since some haplotypes are shared both within and between populations.
The individuals from Mexico are all Native Americans from the Mazahua and Zapotec ethnic groups.
FIGURE 4 Matrix of shared haplotypes between populations. The color scale indicates the proportion of the total haplotypes that are
shared within (on the diagonal) or between (below the diagonal) populations
ARIAS ET AL.
Western Tukanoan groups Siona and Coreguaje shared primarily within
their populations and did not share haplotypes with the Eastern
The groups from the Andean foothills–Inga, Kamentsa, and Pasto–
showed different patterns of shared haplotypes, despite the fact that
they live in close geographic proximity. The Pasto, a group that has lost
its native language and is largely incorporated into the admixed local
population, shared no haplotypes with any population. The Kamentsa
shared haplotypes only with the Inga, while the Inga also shared haplo-
types with three other groups located further inside the Amazonian
area—Carijona, Coreguaje, and Mur-Uitoto. Finally, of the three groups
living on the banks of the Amazon River close to the town of Leticia,
the Cocama shared with both the Yagua and Tikuna, whereas the latter
two groups did not share with one another.
The networks of haplotypes (Supporting Information Figure S5A–D)
complement the patterns of sequence sharing, but in addition allow us
to discern clusters of related (not just identical) haplotypes. We
observed that some of these clusters included sequences from differ-
ent language families while others were restricted to specific language
families or to groups living in close geographic proximity (Supporting
Information Table S3). For instance, Arawakan and Eastern Tukanoan
groups exhibited several haplotypes within haplogroups A2, B2, and C1
(Supporting Information Figures S5A–C and Supporting Information
Table S3) that were either shared or separated by only a few muta-
tional steps. Notably, several of these clusters also included individuals
speaking Maku-Puinave languages. Clusters of haplotypes restricted to
specific groups are represented by clusters I and II of haplogroup D,
which are exclusive to Eastern Tukanoan and Huitotoan populations,
respectively. Furthermore, the haplotypes of the Quechuan populations
and the Kamentsa, who live in close proximity in the Andean foothills,
were either shared between them or closely related. Finally, the haplo-
types of the Guayabero and Sikuani (Guahiban) were mostly differenti-
ated from those of other populations and generally shared by several
individuals within the family (Clusters II and III in Supporting
Information Figure S5A; Cluster I in Supporting Information Figure
S5C). The sequences belonging to cluster I in haplogroup C lack the
diagnostic mutation A13263G for haplogroup C, but contain other
diagnostic mutations that allow unambiguous assignment to hap-
logroup C. MtDNAs with this variant were previously identified in east-
ern Colombia by RFLP typing (Torres et al., 2006), where they occurred
at high frequency in Guahibo, Piapoco, and Saliba groups. Given their
high frequencies in the Guahiban groups, these haplotypes appear to
belong to an autochthonous lineage that has diffused into other groups
living in the Orinoco basin.
Genetic structure and genetic distances
The AMOVA (Table 4) allows us to test different hypotheses about
how genetic variation is structured in NWA. We defined groups apriori
based on their language affiliation, geographic proximity, and distribu-
tion along major rivers or their tributaries to evaluate how much of the
observed variation was explained by each grouping strategy. We
observed that, of the three strategies, grouping populations by their
distribution along rivers resulted in the largest among-group compo-
nent of the genetic variance. In contrast, both language and geography
were a poor predictor of the genetic structure, showing negative and
non-significant values for the component of variance due to differen-
ces among groups. Although grouping by rivers performed better than
grouping by geography or language, it still did not provide a very good
description of the genetic structure, since the percentage of variance
due to differences among populations within groups was still higher
than the among groups component, suggesting the existence of other
influences on substructure within populations.
The matrix of genetic distances between populations based on
values (Supporting Information Figure S6) was used to
construct an MDS plot (Figure 5). The populations did not form any
clear clustering: the majority of populations were grouped together in
the center of the plot (indicated by the inner circle in Figure 5) with an
average pairwise U
50.03, while around the main cluster a second
group of populations showed higher differentiation (external circle,
50.07). Sikuani, Siona, and the hunter-gatherer Nukak
TABLE 4 Analysis of molecular variance
No. groups Among groups Within groups Within populations Global FST
One group 1 11.12** 88.88 0.1112
14 21.33 12.37** 88.96** 0.1104
6 1.04 10.24** 88.72** 0.1128
11 5.42** 5.99** 88.59** 0.1141
1. Arawak: Yucu-Matapi, Curripaco, Ach-Piapoco; 2. Carib: Carijona; 3. Eastern-Tukanoan: Desano, Pira-Wanano, Siriano, Tuka-Tatuyo, Other-ET,
Tanimuka; 4. Western-Tukanoan: Coreguaje, Siona; 5. Guahiban: Sikuani, Guayabero; 6.Huitoto: Mur-Uitoto; 7. Maku-Puinave: Puinave, Nukak; 8.
Kamentsa; 9. Pasto; 10. Piaroa-Saliba: Saliba; 11. Peba-Yaguan: Yagua; 12. Quechua: Inga; 13.Tikuna; 14. Tupi: Cocama.
1. Saliba, Ach-Piapoco; 2.
Sikuani, Guayabero, Nukak, Desano, Pira-Wanano, Siriano, Tuka-Tatuyo, Other-ET, Carijona; 3. Coreguaje, Siona, Mur-Uitoto, Inga, Kamentsa, Pasto; 4.
Curripaco, Puinave; 5. Yucu-Matapi, Tanimuka; 6. Cocama, Tikuna, Yagua.
1. Meta: Saliba, Ach-Piapoco; 2. Vaupes: Desano, Pira-Wanano, Siriano,
Tuka-Tatuyo, Other-ET, Carijona; 3. Guaviare: Guayabero, Sikuani; 4. Interfluve: Nukak; 5. Atabapo-Inirida: Curripaco, Puinave; 6. High-Putumayo: Inga,
Kamentsa, Pasto; 7. Middle-Putumayo: Siona; 8. Lower-Putumayo: Mur-Uitoto; 9. Middle-Caqueta: Coreguaje; 10. Mirití-Parana: Yucu-Matapi,
Tanimuka; 11. Amazon: Cocama, Tikuna, Yagua.
ARIAS ET AL.
appeared as outliers with high genetic differentiation (average
50.22). This picture did not change after adding an additional
dimension to the MDS plot (Supporting Information Figure S7). Particu-
larly striking were the small genetic distances between the Eastern
Tukanoan groups, who clustered together in the center of the MDS
plot. Although the Tanimuka appeared more distant from the main
cluster of Eastern Tukanoan groups, their pairwise U
values were not
significantly different (Supporting Information Figure S6) and the aver-
(0.02) indicated low genetic differentiation among all Eastern
Tukanoan groups. In contrast, the Coreguaje and the Siona, who speak
languages of the Western Tukanoan branch, showed larger genetic dis-
tances, both with the Eastern Tukanoan groups and with each other.
Populations from each of the other language families did not form clus-
ters with their linguistic relatives. For example, Arawakan groups occu-
pied different positions in the plot and their U
The results of the Mantel test showed a lack of significant correla-
tion between geographic distances, estimated as great-circle distances,
and the matrix of pairwise U
values (r50.07, p-value50.28). How-
ever, since rivers emerged as an important factor explaining the struc-
ture of genetic variation in the AMOVA results (Table 4), we also
performed a MRM, where we added rivers as an additional predictor
variable. Adding rivers to the regression model resulted in an increase
in the amount of variation explained by the model (Table 5), with rivers
being a significant predictor (p-value 50.01). We then jack-knifed over
populations (Pugach et al. 2016; Ramachandran et al., 2005) and
identified three populations as outliers—Sikuani, Siona, and Nukak—
groups that appeared as outliers in the MDS plot as well (Figure 5). We
performed the multiple regression analysis excluding the outliers, and
this resulted in an increase of 3.4% in the R square value, a better cor-
relation between genetic and geographic distances, and geography
becoming a significant predictor factor (p-value <0.05) (Table 5 and
Supporting Information Figure S8), although rivers were no longer a
significant predictor of genetic subdivision.
Bayesian demographic reconstruction
BSPs were generated for each haplogroup (A2, B2, C1, and D1) and
population. All four haplogroups showed an increase in effective popu-
lation size between 17,500 and 25,000 years before present. This sig-
nal was more evident for haplogroups A2 and C1, which had the
highest number of sequences (Supporting Information Figure S9). In
contrast, the BSP plots by population showed different outcomes. We
observed four main trajectories (Supporting Information Figure S3): (a)
a signal of population size increase shown by Yucu-Matapi, Curripaco,
Desano, Siriano, Inga, Pasto, Mur-Uitoto, Tikuna, and Cocama (exem-
plified by Yucu-Matapi in Supporting Information Figure S3A); (b)
population stability through time shown by Ach-Piapoco, Tanimuka,
Coreguaje, Siona, Kamentsa, Puinave, and Yagua (exemplified by Core-
guaje in Supporting Information Figure S3B); and (c) population con-
traction shown by Sikuani, Guayabero, and Nukak (exemplified by
Nukak in Supporting Information Figure S3C), which is particularly
FIGURE 5 MDS plot based on U
genetic distances. Stress value is given in percentage. The inner circle indicates populations with low
genetic differentiation and the outer circle indicates populations with moderate differentiation. mPhiST is the average pairwise U
within each circle
ARIAS ET AL.
striking for Sikuani (Supporting Information Figure S3D). These differ-
ences in the effective population size through time suggest that these
populations have independent demographic histories.
We have investigated the genetic diversity of ethnolinguistic groups
from NWA at the level of complete mitochondrial genomes. This area
is underrepresented in previous studies, and our data help to fill a gap
in our knowledge about the genetic diversity of modern human popula-
tions. We have found that NWA harbors a considerable amount of
genetic diversity, with evidence for contact among different ethnolin-
guistic groups, contrary to the common picture of Amazonian popula-
tions as being small and isolated with low genetic diversity (Fuselli
et al., 2003; Wang et al., 2007). NWA populations show values of
nucleotide diversity as high as or higher than those observed in most
other non-African populations (Supporting Information Figure S10),
and they display the second-highest amount of sequence sharing in a
world-wide comparison (Table 3). The complete mitochondrial genome
is the maximum level of resolution one can achieve to differentiate
individuals and populations at the maternal level, so the presence of
identical sequences among populations living in distant geographic
areas likely indicates their common ancestry and/or recent contact.
Lack of genetic structure along linguistic lines
Although our dataset includes populations speaking languages belong-
ing to different language families, we found that linguistic affiliation is a
poor predictor of genetic structure, as shown by the AMOVA (Table 4)
and the CA plot based on sub-haplogroup frequencies (Figure 2 and
Supporting Information Table S1). These results indicate that language
does not constitute a barrier to gene flow, and that groups have been
interacting with neighboring groups for some time, especially along riv-
ers, which in our analyses performed better in explaining the patterns
of genetic diversity. Archeological and linguistic evidence demonstrates
that NWA has been an area of intense contact and movement of peo-
ples of different cultural traditions, as evidenced by the diffusion of
ceramic styles (Heckenberger, 2002; Lathrap, 1970; Zucchi, 2002) and
shared subsistence strategies, by the existence of language areas and
contact-induced linguistic change (Aikhenvald, 1999), and the general-
ized multilingualism among groups (Sorensen, 1967; Stenzel, 2005).
Likewise, ethnographic studies provide additional evidence of contact
among groups. For example, both Arawakans and Eastern Tukanoans
share a ceremonial complex for male initiation known as Yurupari, in
which sacred flutes and trumpets are only played by males, as well as
sharing myths concerning the hero K
uwai (Hugh-Jones, 1979; Jackson,
1983; Vidal, 2002). In addition, the Eastern Tukanoan groups from the
Pira-Parana and Apaporis Rivers (Barasano, Makuna, and Tanimuka)
reveal Arawakan influence, since they also practice dances with masks
during the season of high abundance of the palm tree fruit pupunha
(Bactris gasipaes) (Hugh-Jones, 1979).
The genetic distances among populations provide additional evi-
dence in this regard. Although the global U
value of 0.11 indicates
moderate differentiation (Hartl and Clark, 2007), this value is driven by
three populations, namely the Siona, Sikuani, and Nukak. These are
highly differentiated from the other populations, most likely reflecting
the effects of genetic drift due to bottlenecks, as indicated by the posi-
tive Tajima’s D values (Figure 3) and the distribution of pairwise differ-
ences (Supporting Information Figure S2). When we exclude these
populations, we observe an average pairwise U
of 0.07, and popula-
tions appear close together in the MDS plot (Figure 5), indicating low
genetic differentiation among NWA populations.
In this general picture, the Eastern Tukanoan groups stand apart,
since they cluster together in the CA and MDS plots (Figures 2 and 5),
and their pairwise genetic distances are small and non-significant (Sup-
porting Information Figure S6). Linguists have proposed a time depth
for the Tukanoan family of 2000–2500 years, based on a comparison
of the diversity in Tukanoan languages with the diversity in Romance
and Germanic languages (Chacon, 2014). The time depth of the Eastern
Tukanoan branch (and thus the time to the most recent common
ancestor of the Eastern Tukanoan languages) would be even more
recent, and as such might indicate that the peoples speaking these lan-
guages share recent common genetic ancestry as well (at least on the
maternal side). However, the Eastern Tukanoan groups practice linguis-
tic exogamy, and the close genetic relationships among these popula-
tions might be the result of this marital system, in which women move
among different ethnolinguistic groups. The consequences of the lin-
guistic exogamy are also evident in the gene diversity values and the
TABLE 5 Multiple regression analysis on distance matrices
gen.dist all populations
Reg.coefficient p-value R
Simple regression geo.dist 3.28 310
0.444 0.009 0.444
Multiple regression geo.dist 9.64 310
0.983 0.036 0.126
rivers.dist 5.71 310
gen.dist without outliers
Simple regression geo.dist.no.outliers 6.70 310
0.026 0.067 0.026
Multiple regression geo.dist.no.outliers 5.76 310
0.112 0.070 0.040
rivers.dist.no.outliers 1.38 310
ARIAS ET AL.
patterns of shared haplotypes. Eastern Tukanoans show the highest
gene diversity values and share more haplotypes among themselves
than with other non-Eastern Tukanoan groups. In addition, their haplo-
types tend to be closely related, as seen in the phylogenetic networks
(Supporting Information Figure S5). Analyses of the Y-chromosome as
well as nuclear markers will help to disentangle the effects of linguistic
exogamy versus recent common ancestry on the patterns of genetic
variation among Eastern Tukanoan groups.
The Tanimuka stand apart from the other Eastern Tukanoan
groups in the analyses, and this may reflect their settlement further
south, along the Apaporis and Mirití-Paran
a Rivers. Moreover, they do
not participate in the linguistic exogamic system with other Eastern
Tukanoan groups, but interact mainly with the Arawakan groups
Yucuna and Matapi. These interactions are reflected in the patterns of
haplotype sharing (Figure 4) as well as in their language, which shows
evidence of Arawakan influence (Barnes, 1999; Chacon, 2014).
The role of rivers in structuring genetic variation
Besides language, geography is another important factor in structuring
the patterns of genetic variation in human populations (Ramachandran
et al., 2005; Sch€
onberg, Theunert, Li, Stoneking, & Nasidze, 2011;
Wang et al., 2007). One of the most salient characteristics of the physi-
cal landscape of NWA is the high density of rivers that drain the area,
and their importance for human populations was earlier recognized by
explorers and ethnographers that traveled through the region (Koch-
unberg, 1995; Wallace, 1853). We found that the distribution of
populations along rivers is an additional important factor influencing
their genetic structure. AMOVA (Table 4) shows that clustering popula-
tions according to the rivers where they are distributed explains more
of the genetic variation that is due to differences among groups than
does grouping them by linguistic affiliation, that is, populations living in
the same river basin or along closely connected rivers are genetically
more similar than those living on different rivers. This pattern is also
observed in the distribution of sub-haplogroups among populations,
which drive their location in the CA plot (Supporting Information Figure
S1). For example, the Curripaco and Puinave, who live on the Inírida
and Atabapo Rivers, are located close together in the plot. The pres-
ence of Coreguaje, Yucu-Matapi, and Mur-Uitoto in the center of the
plot could reflect their presence in a region where the Putumayo and
a Rivers are separated by their shortest distance, therefore facil-
itating contact among people inhabiting the basins and tributaries of
these two rivers. Indeed, one Murui individual was sampled in a Core-
guaje community, and two Uitoto individuals were sampled in the
Mirití-Parana region, thus providing evidence for the movement of
people among these groups. The results of the MRM analysis provide
additional evidence in this regard: even though no correlation between
genetic distances and geographic distances was observed via the Man-
tel test, adding river distances as an additional predictor variable
resulted in an increase of around 3% of the R-square value (Table 5),
indicating that rivers contribute to explaining a slightly higher percent-
age of the variation observed in the genetic distances.
Rivers in Amazonia serve a double function in providing a means
of communication as well as subsistence, and the wide distribution of
certain cultural traits (e.g., the production of Saladoid-Barrancoid
ceramics and circular plaza village settlement patterns) has been associ-
ated with the expansion of Arawakan-speaking populations along the
extensive system of NWA waterways (Heckenberger, 2002; Hornborg,
2005; Lathrap, 1970; Lowie, 1948). They also mark a distinction in sub-
sistence strategies between the more numerous “river people”who
build canoes, settle along rivers, and rely on horticulture and fishing,
and the “forest people”who inhabit the interfluvial areas, settle away
from the major rivers, and base their subsistence on foraging (Epps and
Stenzel, 2013). Additionally, the rivers have profound meanings and are
embedded in the cosmogonies of several NWA indigenous groups. The
Eastern Tukanoan creation myths describe the journeys that the ances-
tors of the people made to settle this world on board an anaconda
canoe that traveled up the Vaupes River; from the anaconda’sbodyall
the Tukanoan siblings emerged (Chernela, 2010; Jackson, 1983). Ara-
wakan groups also describe a series of ever returning voyages from the
sacred center of the world and the place of emergence of the first
ancestors at the rapids of Hípana on the Aiary River, covering the major
arteries of the Rio Negro, Orinoco, and Amazon Rivers (Wright, 2002;
Zucchi, 2002). Therefore, our findings about the role of rivers in struc-
turing the genetic variation are in keeping with the ethnographically
demonstrated role that rivers play for NWA populations.
The lack of fit between genetic and simple geographic distances
may be the result of relatively recent movements and the displacement
of ethnolinguistic groups from their traditional territories. Population
dynamics and population sizes were drastically altered during the last
five centuries, starting with early colonial times (16th and 17th centu-
ries), when many groups were decimated by newly introduced epidem-
ics and moved away from the accessible margins of the major rivers to
avoid the slave raids of the Spanish, Portuguese, and Dutch colonizers
(Santos-Granero 2002). Similar perturbations happened during the time
of the Christian missions in the 18th century, when many groups were
forced to relocate to multiethnic mission settlements, and finally during
the rubber boom between the 19th and beginning of the 20th centu-
ries, when the groups who managed to escape the mercenaries exploit-
ing the rubber fields resettled in remote areas in the headwaters of
small rivers (Dixon and Aikhenvald, 1999; Hill and Santos-Granero,
2002; Stenzel, 2005). The inferred reduction in population size of the
Tanimuka, Sikuani, Guayabero, and Nukak, as indicated by their low
diversity values, the positive Tajima’s D values (Figure 3), the distribu-
tion of pairwise differences (Supporting Information Figure S2), and the
reconstruction of effective population sizes (Supporting Information
Figure S3C,D), might be a result of these social upheavals.
The impact of subsistence strategies
on the genetic diversity
NWA contains groups with different subsistence strategies, with manioc
(Manihot esculenta) the main staple among horticulturalist groups, who
are best described as riverine horticultural societies, given their close
association with rivers. The Nukak, in contrast, are traditionally foragers,
ARIAS ET AL.
who still rely on hunting and gathering, and move throughout the exten-
sive area between the Guaviare and Inírida Rivers. Furthermore, the
Guayabero, Sikuani, and Puinave are traditional foragers who have only
recently undergone the transition to agriculture, and are therefore con-
sidered as HGP together with Nukak in our analyses (Table 1). Our data
show that agricultural societies (AG) have higher levels of diversity on
average than forager groups (HGP) as indicated by the Mann-Whitney U
test (p-value 5.03), while the HGP groups have larger values of Tajima’s
D statistic (Figure 3) and do not show signals of population expansion
(Supporting Information Figure S3). These findings agree with patterns
reported for other HGPs around the world (Aime et al., 2013; Excoffier
and Schneider, 1999; Oota et al., 2005) and contrast with the genetic sig-
nature of an agricultural way of life, namely higher effective population
size (Patin et al., 2014), higher levels of diversity, and significantly nega-
tive values of Tajima’s D test (Aime et al., 2013).
However, subsistence strategies are flexible and diverse among
NWA populations. Horticulturalists complement their diet with occa-
sional hunting and/or gathering of several kinds of palm fruit, and
extensive exchanges between AG and HGP groups have been
reported (Jackson, 1983; Milton, 1984). In this system, HGP popula-
tions usually provide meat and several products from the forest, such
as the poison curare for the tips of darts and arrows, in exchange for
different cultivated products, such as manioc and other trade goods
(Epps and Stenzel, 2013; Jackson, 1983; Milton, 1984). Nonetheless,
this exchange seems to be exclusively restricted to goods and labor,
with little or no intermarriage documented between AG and HGP
groups (Aikhenvald, 1996). In contrast, we observed shared haplo-
types between AG and HGP groups, which likely reflects recent inter-
marriage or recent common ancestry. For example, the most frequent
haplotype in the Arawakan AG group Curripaco (Haplotype H_84 in
Supporting Information Figure S4) is observed at high frequency in the
HGP Nukak (and in the Eastern Tukanoan AG group Siriano). More-
over, the HGP Puinave share several haplotypes with the AG group
Curripaco (H_219, H_161, H_117 in Supporting Information Figure
S4), a likely result of intermarriage between these groups, since there
are communities on the Inírida River where one finds individuals from
both groups. Similarly, the Guahiban HGP groups Sikuani and Guaya-
bero exhibit a haplotype at high frequency (H_43 in Supporting Infor-
mation Figure S4) that is shared with the AG Ach-Piapoco as well as
further haplotypes related to haplotypes found in AG Arawakan
groups (Clusters I and II in Supporting Information Figure S5B,C). This
may reflect contact among them, since there are Piapoco communities
on the lower Guaviare River as well as Sikuani communities on the
Meta River, places where these groups overlap.
However, it is difficult to determine the direction of the gene flow
or to distinguish between contact and common ancestry as explana-
tions for shared mtDNA haplotypes. Nevertheless, it is plausible that,
where haplotypes are shared, the source population is the one in which
the haplotype is present at higher frequency. For instance, the shared
haplotype between the HGP Puinave and the AG Curripaco (H_219 in
Supporting Information Figure S4) has a likely origin in Puinave,
because of its higher frequency and the presence of related haplotypes
in Puinave (Cluster I Supporting Information Figure S5B). The source of
the shared haplotype among the HGP Nukak and the AG Curripaco
and Siriano (H_84 in Supporting Information Figure S4) is more difficult
to infer, since its frequency is similar in the Nukak and in the Curripaco;
furthermore, three other haplotypes present in the HGP Nukak and
Guayabero are only one mutation apart from it (Cluster II in Supporting
Information Figure S5B). Therefore, it is likely that this haplotype, too,
moved from the HGP populations into the AG Curripaco. A similar
explanation could be given for H_43 in Figure S4, which is part of the
Cluster I in Supporting Information Figure S5C, moving from the HGP
Guayabero and Sikuani into the AG Ach-Piapoco.
Thus, these observations seem to fit a scenario of asymmetric
gene flow in which women move from HGP to AG, a pattern that has
been reported for populations in Central and Southern Africa (Barbieri
et al., 2014; Destro-Bisol et al., 2004; Verdu et al., 2013). However,
this scenario will need to be further refined by analyses of Y-
chromosome and genome-wide data, which will allow us to determine
whether the gene flow among groups was sex-biased (i.e., involving the
movement of only females or only males among groups) and to make
inferences about the time and magnitude of these events.
In conclusion, this study provides new data from this remote and
little-studied part of the world, which allow insights into the impact of
cultural practices on the patterns of genetic variation and on the popu-
lation dynamics of NWA groups. Although our current data do not
allow us to distinguish whether the population movements took place
prior to or as a consequence of European contact, analyses of Y-
chromosome variation and genome-wide data will shed further light on
the genetic history of NWA. Furthermore, historical genetic studies will
benefit from more archeological work in NWA, since huge areas remain
We are grateful to all sample donors, communities, community lead-
ers, and regional indigenous organizations. L.A. especially gives
thanks to Consejo Regional Indígena del Guaviare, Asociaci
Autoridades Tradicionales y Cabildos de los Pueblos Indígenas del
Municipio de Leguízamo y Alto Resguardo Predio Putumayo,
on de Cabildos Indígenas del Trapecio Amaz
on Zonal Indígena Del Putumayo, the staff of Parques Nacio-
nales Naturales in Puerto Leguízamo, the office of Indigenous Affairs
in Puerto Inírida, Rafael Rodriguez, William Yucuna, the late Gustavo
Arias, and all people who helped during the fieldtrips for their valua-
ble collaboration and warm welcome during our stay in their com-
munities. We also acknowledge Roland Schroeder for laboratory
technical assistance, and Enrico Macholdt, Alexander Huebner, Irina
Pugach, and Michael Dannemann for advice with the data analyses.
B.P. acknowledges the LABEX ASLAN (ANR-10-LABX-0081) of Uni-
e de Lyon for its financial support within the program “Inves-
tissements d’Avenir”(ANR-11-IDEX-0007) of the French government
operated by the National Research Agency (ANR). L.A. was supported
by a graduate grant from COLCIENCIAS; research was supported by
funds from the Max Planck Society.
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How to cite this article: Arias L, Barbieri C, Barreto G, Stoneking
M, Pakendorf B. High-resolution mitochondrial DNA analysis
sheds light on human diversity, cultural interactions, and popula-
tion mobility in Northwestern Amazonia. Am J Phys Anthropol.
ARIAS ET AL.