Uniparental genetic markers in South Amerindians.

A comprehensive review of uniparental systems in South Amerindians was undertaken. Variability in the Y-chromosome haplogroups were assessed in 68 populations and 1,814 individuals whereas that of Y-STR markers was assessed in 29 populations and 590 subjects. Variability in the mitochondrial DNA (mtDNA) haplogroup was examined in 108 populations and 6,697 persons, and sequencing studies used either the complete mtDNA genome or the highly variable segments 1 and 2. The diversity of the markers made it difficult to establish a general picture of Y-chromosome variability in the populations studied. However, haplogroup Q1a3a* was almost always the most prevalent whereas Q1a3* occurred equally in all regions, which suggested its prevalence among the early colonizers. The STR allele frequencies were used to derive a possible ancient Native American Q-clade chromosome haplotype and five of six STR loci showed significant geographic variation. Geographic and linguistic factors moderately influenced the mtDNA distributions (6% and 7%, respectively) and mtDNA haplogroups A and D correlated positively and negatively, respectively, with latitude. The data analyzed here provide rich material for understanding the biological history of South Amerindians and can serve as a basis for comparative studies involving other types of data, such as cultural data.

Introduction

Native Americans have been the subject of a large number of population genetic studies because of particular characteristics: (a) there are groups among them that until recently had a hunter-gatherer way of living with only incipient agriculture, typical of our ancestors, (b) they show considerable interpopulation but low intrapopulation variability, and (c) since until recently they could not write there is no written record of their history, except for those of non-Amerindian colonizers. Biological studies can therefore be used to investigate their past.

The first genetic studies examined the variability in blood groups and proteins and have been summarized in Salzano and Callegari-Jacques (1988) and Crawford (1998). The advent of modern molecular biology, which allows direct, detailed DNA analysis, has opened new possibilities for investigating these populations.

DNA studies can basically be divided into two groups: those involving autosomal markers and those involving uniparental (Y-chromosome, mitochondrial DNA) markers. The latter are important because they can provide a clear-cut pattern of historical events that is not clouded by recombination factors. For Amerindians, the number of reviews that have dealt with these markers is not large or comprehensive. For the Y-chromosome, Bortolini considered 438 individuals from 23 Southern and one Northern Amerindian populations who were screened for eight single nucleotide polymorphisms (SNPs) and six short tandem repeat/microsatellite (STR) loci, and Zegura studied 63 binary polymorphisms and 10 STR regions in 2,344 persons from 15 Northern and three Southern Amerindian groups. Only a few recent studies have used all known SNPs necessary to identify the major Native American Y-haplogroups and their sublineages in Amerindian populations (Geppert ; Jota ; Bisso-Machado ).

The most recent mtDNA reviews were published four years ago and involved sequence variability in the hypervariable region 1 (Hunley ; Lewis Jr ). Schurr and Sherry (2004), on the other hand, associated data from Y-chromosome markers with mitochondrial DNA (mtDNA) results, providing a good picture of the information available at the time. No general review considering both data sets has been published since then.

This review provides a detailed, comprehensive survey of Y-chromosome haplogroup frequency variation in 68 populations involving 1,814 individuals. In addition, specific information on Y-STR markers for 29 populations and 590 subjects is given. The haplogroup mtDNA data included 108 populations involving a total of 6,697 persons. Geographic and linguistic factors that may have influenced this variation were carefully considered, leading to a global, overview of the genetic pattern associated with these markers in South Amerindians. Information on mtDNA sequencing studies is also supplied.

Materials and Methods

The data used in this review were obtained from 17 primary surveys of the Y-chromosome and 66 primary surveys of mtDNA. These studies were retrieved through PubMed and by searching the reference lists of the corresponding papers. Haplogroup frequencies were obtained by direct counting. Intra- and inter-populational diversity was calculated with AMOVA (Weir and Cockerham, 1984; Excoffier ; Weir, 1996) using Arlequin 3.5.1.2 software (Excoffier and Lischer, 2010). AMOVA was also used to estimate the level of differentiation between and within 17 pre-defined language and 7 geographical categories, respectively. The distribution patterns of the mtDNA haplogroup frequencies were established by generating isoline maps using IDRISI 16.0 software (IDRISI Taiga) (Eastman, 2006). Spearman’s correlation coefficients were calculated with PASW Statistics 18 software. Average heterozygosity (ah) was calculated with Arlequin 3.5.1.2 software.

Results and Discussion

Table 1 gives the distribution of the Q and non-Q-chromosomes (defined by a set of SNPs), as well as linguistic and geographical information for the samples considered. The samples were distributed from latitude 11° North to 45° South and longitude 46° to 76° West, with the individuals involved speaking 23 languages. Sample sizes varied widely from 1 to 151 individuals. Twenty-two of the studies involved less than 10 persons. Unfortunately, there is no standardization on the number of SNPs studied and in most cases only the M242 and M3 markers (which define the Asian/Native American paragroup Q* and its autochthonous Native American sublineage Q1a3a*, respectively; Pena ; Bortolini ; Seielstad ) were investigated. This fact precludes a complete, precise view of the distribution of Q1a3a sublineages and other Q clade chromosomes in South America. For this reason, the information in Table 1 was limited to the frequencies of the Q and non-Q-lineages only. Note that non-Q-chromosomes (which, for the reasons given above, could not be identified in sublineages) were identified in ∼50% of the tribal groups. For some of these populations admixture with non-Indians is known and could be the source of these non-Q chromosomes (for example, Mapuche and Guarani; Marrero ; Bailliet ; Blanco-Verea ). Overall, the numbers presented in Table 1 indicate a higher presence of non-Q lineages in southern populations than in those of the northern/Amazonian region, probably because of greater admixture with non-Indians in the former than in the latter. However, for some isolated groups such as the Yanomámi, it is unlikely that admixture explains the findings. In these cases other causes are more probable, such as the presence of unknown autochthonous lineages and/or known Q lineages whose defining markers were not tested.

Table 1

The distribution of Q and non-Q lineages and linguistic and geographical information for the samples considered.

Populations (n)1	Haplogroup (%)		Language2	Geographical coordinates	References
	Q lineages/Amerindian origin	Non-Q lineages
Wayuu (19)	69	31	Arawakan	11° N; 73° W	Bortolini et al. (2003)
Kogi (17)	100		Chibchan	11° N; 74° W	Rojas et al. (2010)
Barira (12)	100		Chibchan	10° 44′ N; 71° 23′ W	Bortolini et al. (2003)
Arsario (Wiwa) (6)	100		Chibchan	10° 25′ N; 73° 05′ W	Rojas et al. (2010)
Arhuaco (Ijka) (19)	100		Chibchan	9° 04′ N; 73° 59′ W	Rojas et al. (2010)
Warao (12)	100		Warao	9° N; 61° W	Bortolini et al. (2003)
Yukpa (12)	100		Carib	8° 40′ N; 72° 41′ W	Bortolini et al. (2003)
Zenu (52)	79	21	Spanish3	8° 30′ N; 76° W	Bortolini et al. (2003); Rojas et al. (2010)
Embera (13)	92	8	Choco	7° N; 76° 30′ W	Rojas et al. (2010)
Makiritare (25)	68	32	Carib	5° 33′ N; 65° 33′ W	Lell et al. (2002)
Kali’na (21)	81	19	Carib	5° 31′ N; 53° 47′ W	Mazières et al. (2008)
Waunana (29)	100		Choco	4° 50′ N; 77° W	Rojas et al. (2010)
Palikur (35)	94	6	Arawakan	4° N; 51° 45′ W	Mazières et al. (2008)
Macushi (4)	100		Carib	4° N; 60° 50′ W	Lell et al. (2002)
Piaroa (6)	100		Salivan	3° 57′ N; 66° 22′ W	Lell et al. (2002)
Wapishana (2)	50	50	Arawakan	3° 07′ N; 60° 03′ W	Lell et al. (2002)
Emerillon (9)	100		Tupi	3° N; 53° W	Mazières et al. (2008)
Yanomámi (39)	38	62	Yanomam	2° 50′ N; 54° W	Rodriguez-Delfin et al. (1997); Lell et al. (2002)
Tiryió (4)	100		Carib	2° N; 56° W	Bortolini et al. (2003)
Apalaí (57)	98	2	Carib	1° 20′ N; 54° 40′ W	Rodriguez-Delfin et al. (1997); Bortolini et al. (2003)
Wayampi (62)	100		Tupi	1° N; 53° W	Rodriguez-Delfin et al. (1997); Bortolini et al. (2003); Mazières et al. (2008)
Yagua (7)	100		Peba-Yaguan	0° 51′ N; 72° 27′ W	Bortolini et al. (2003)
Ingano (108)	80	20	Quechuan	0° 50′ N; 77° W	Bortolini et al. (2003); Rojas et al. (2010)
Wai-Wai (9)	100		Carib	0° 40′ S; 58° W	Bisso-Machado et al. (2011)
Urubu-Kaapor (16)	100		Tupi	2°–3° S; 46°–47° W	Bortolini et al. (2003)
Huitoto (4)	75	25	Witotoan	2° 14′ S; 72° 19′ W	Bortolini et al. (2003)
Arara (15)	100		Carib	3° 30′–4° 20′ S; 53° 0′–54° 10′ W	Rodriguez-Delfin et al. (1997); Bianchi et al. (1998); Bisso-Machado et al. (2011)
Asurini (4)	100		Tupi	3° 35′–4° 12′ S; 49° 40′–52° 26′ W	Bortolini et al. (2003)
Ticuna (59)	93	7	Ticuna	4° S; 69° 58′ W;	Bortolini et al. (2003); Rojas et al. (2010)
Parakanã (20)	100		Tupi	5° 22′ S; 51° 17′ W	Bortolini et al. (2003)
Xikrin (14)	100		Macro-Ge	5° 55′ S; 51° W	Bortolini et al. (2003); Bisso-Machado et al. (2011)
Suruí (24)	96	4	Tupi	5° 58′–10° 50′ S; 48° 39′–61° 10′ W	Underhill et al. (1996); Bisso-Machado et al. (2011)
Araweté (4)	100		Tupi	5° 9′ S; 52° 22′ W	Bisso-Machado et al. (2011)
Munduruku (1)	100		Tupi	6° 23′ S; 59° 9′ W	Bisso-Machado et al. (2011)
Jamamadi (3)	100		Arauan	7° 15′ S; 66° 41′ W	Bisso-Machado et al. (2011)
Gorotire (19)	100		Macro-Ge	7° 44′ S; 51° 10′ W	Bortolini et al. (2003); Bisso-Machado et al. (2011)
Krahó (15)	93	7	Macro-Ge	8° S; 47° 15′ W	Lell et al. (2002); Bortolini et al. (2003)
Kuben-Kran-Kegn (9)	100		Macro-Ge	8° 10′ S; 52° 8′ W	Bisso-Machado et al. (2011)
Tenharim (1)	100		Tupi	8° 20′ S; 62° W	Bisso-Machado et al. (2011)
Mekranoti (9)	78	22	Macro-Ge	8° 40′ S; 54° W	Bortolini et al. (2003)
Kayapó (10)	100		Macro-Ge	9° S; 53° W	Rodriguez-Delfin et al. (1997)
Karitiana (18)	100		Tupi	9° 30′ S; 64° 15′ W	Underhill et al. (1996); Bisso-Machado et al. (2011)
Cinta-Larga (15)	100		Tupi	9° 50′–12° 30′ S; 59° 10′–60° 50′ W	Bortolini et al. (2003)
Gavião (7)	100		Tupi	10° 10′ S; 61° 8′ W	Bisso-Machado et al. (2011)
Karipuna (1)		100	Tupi	10° 14′ S; 64° 13′ W	Bisso-Machado et al. (2011)
Zoró (6)	100		Tupi	10° 20′ S; 60° 20′ W	Bisso-Machado et al. (2011)
Matsiguenga (28)	91	9	Arawakan	10° 47′–12° 51′ S; 73° 17′ -70° 44′ W	Mazières et al. (2008)
Pacaás Novos (Wari) (29)	100		Chapacura-Wanham	11° 8′ S; 65° W	Bortolini et al. (2003)
Panoa (5)	100		Pano	12° 55′ S; 65° 12′ W	Lell et al. (2002)
Xavante (15)	100		Macro-Ge	14° S; 52° 30′ W	Bisso-Machado et al. (2011)
Quechua (44)	73	27	Quechuan	14° 30′ S; 69° W	Gayà-Vidal et al. (2011)
Aymara (59)	97	3	Aymaran	17° 68′ S; 69° 16′ W	Gayà-Vidal et al. (2011)
Ayoreo (9)	78	22	Zamucoan	19° S; 60° 30′ W	Bailliet et al. (2009)
Wichí (Mataco) (151)	48	52	Mataco-Guaicuru	22° 28′ S; 62° 70′ W	Demarchi and Mitchell (2004); Bailliet et al. (2009)
Lengua (36)	97	3	Mascoian	22° 45′ S; 58° 5′ W	Bailliet et al. (2009); Bisso-Machado et al. (2011)
Chorote (9)	89	21	Mataco-Guaicuru	22° 90′ S; 65° 40′ W;	Bailliet et al. (2009)
Aché (54)	98	2	Tupi	23° 30′–24° 10′ S; 55° 50′–56° 30′ W	Bortolini et al. (2003)
Guarani (78)	77	23	Tupi	23° 6′ S; 55° 12′ W	Bortolini et al. (2003); Marrero et al.(2007)
Pilagá	47	53	Mataco-Guaicuru	24° S; 59° W	Demarchi and Mitchell (2004)
Colla (63)	35	65	Quechuan3	24° 10′–24° 43′ S; 65° 17′–65° 52′ W	Blanco-Verea et al. (2010); Toscanini et al. (2011)
Toba (89)	88	12	Mataco-Guaicuru	26° S; 58° W	Demarchi and Mitchell (2004); Bailliet et al. (2009); Toscanini et al. (2011)
Kaingang (59)	69	31	Macro-Ge	28° S; 51° 20′ W	Bortolini et al. (2003); Marrero et al. (2007); Bisso-Machado et al. (2011)
Diaguita (24)	37	63	Quechuan4	28° 20′ S; 67° 43′ W	Blanco-Verea et al. (2010)
Mocoví (40)	60	40	Mataco-Guaicuru	29° 51′ S; 59° 56′ W	Bailliet et al. (2009)
Pehuenche (18)	83	17	Araucanian	37° 43′ S; 71° 16′ W	Bailliet et al. (2009)
Mapuche (105)	36	64	Araucanian	39° 10′–41° 20′ S; 68° 37′–70° 22′ W	Bailliet et al. (2009); Blanco-Verea et al. (2010)
Huilliche (26)	50	50	Araucanian	41° 16′ S; 73° W	Bailliet et al. (2009)
Tehuelche (20)	65	35	Chon	45° S; 71° W	Bailliet et al. (2009)

Arranged according to latitude.

Classification according to Lewis (2009).

Original language is extinct.

The Diaguita spoke originally Kakán, but this language became extinct and was substituted by Quechua.

Despite the great variation in the number of Y-SNPs used in these studies, Figure 1 illustrates some of the trends that were observed: The autochthonous Native American Q1a3a* is almost always the most prevalent, whereas its sublineages (Q1a3a1, Q1a3a2, Q1a3a3 and Q1a3a4) seem to have more restricted geographical distributions. The second most prevalent, Q1a3*, appears to occur equally in all regions, suggesting its presence among the first settlers of South America. The other known Q clade chromosomes (Q1*, Q1a*, Q1a1, Q1a2, Q1a4, Q1a5, Q1a6 and Q1b) have not yet been identified in South America. Only one non-Q-chromosome (C3*) of probable native origin has been described in northwest South Amerindian populations (Figure 1; Geppert ).

Figure 1

Y-chromosome phylogenetic tree considering only the Q derived lineages. Note: The letters and numbers in the branches indicate the name of the loci where the mutations occurred, leading to the haplogroup classification. The data for this tree were compiled from the references in Table 1, plus Santos , Underhill , 2001), Karafet et al. (1997, 1999, 2008), Carvalho-Silva , Vallinoto , Bortolini , The Y-Chromosome Consortium (2002) and Geppert .

The nature of some evolutionary and demographic scenarios, mediated by men, in native American populations has also been evaluated by using Y microsatellite markers (Y-STRs), which have a much faster evolutionary rate than SNPs. Y-STRs allow the retrieval of population and chromosome evolutionary histories. For example, STR data have been used to estimate that the mutations that gave rise to the Q1a3a1 and Q1a3a4 sublineages occurred 7,972 ± 2,916 and 5,280 ± 1,330 years ago, probably in northwest South America and the Andean region, respectively (Bortolini ; Jota ).

Table 2 shows the STR allele frequencies observed in 29 South Amerindian populations, based only on Q clade chromosomes. In this compilation, we considered only studies containing information on the allele frequencies for each population individually. There was considerable variation in the number of samples tested in each study, the number of tribes, and the number of individuals per tribe. Depending on the locus considered, the number of alleles observed ranged from one to eight, with some of them appearing in only one study while others were present in almost all populations. Based on the most prevalent alleles per locus we reconstructed a probable haplotype of the ancient Native American Q-clade chromosome (ANAQC) as: 13(DYS19)-12(DYS388)-14(DYS389I)-31(DYS389II)-2 4(DYS390)-10(DYS391)-14(DYS392)-13(DYS393)-14(DYS437)-11(DYS438)-12(DYS439)-20(DYS448)-15(D YS456)-16(DYS458)-22(DYS635). Using this information and additional data for these loci (except DYS388) reported in the Y Chromosome Haplotype Reference Database we found no matches in 36,448 haplotypes (245 populations). Although we found no complete identity with our estimated ANAQC, three one-step neighbor haplotypes were encountered, two in individuals with an admixed ancestry living in Latin American countries and one in a Native American individual (Kaqchiquel).

Table 2(a)

Y-Q-chromosome STR studies in distinct South Amerindian samples in which allele frequencies can be assessed (Part A).

	Ref. (n)
STR (allele)	Aché (48)2	Apalaí (9)1	Arara (8)1	Aymara (57)9	Ayoreo (2)7	Barira (12)2	Diaguita (9)8	Guarani (47)[4, 5]	Ingano (8)2	Kaingang (17)5	Kayapó (10)1	Colla (22)[6, 8]	Lengua (6)7	Mapuche (24)[6, 8]	Mekranoti (5)2
DYS19 (12)				0.020					0.250
DYS19 (13)	1.000			0.820		0.920	1.000	0.790	0.620	0.300		0.910	0.500	0.830	0.600
DYS19 (14)				0.160	1.000	0.080		0.190	0.130	0.300		0.090	0.330	0.040	0.400
DYS19 (15)								0.020		0.350			0.170	0.130
DYS19 (16)										0.050
DYS19 total
DYS388 (12)	1.000					1.000			0.750						1.000
DYS388 (13)									0.120
DYS388 (14)									0.130
DYS388 (17)
DYS388 total
DYS389I (12)				0.020				0.280		0.180		0.040	0.160	0.040
DYS389I (13)				0.470	0.500		0.220	0.020		0.820		0.410	0.500	0.750
DYS389I (14)				0.510	0.500		0.780	0.550				0.550	0.170	0.210
DYS389I (15)								0.150					0.170
DYS389I total
DYS389II (17)
DYS389II (18)
DYS389II (19)
DYS389II (26)										0.060
DYS389II (27)													0.160
DYS389II (28)				0.020				0.020		0.120
DYS389II (29)				0.090	0.500			0.150		0.290		0.090	0.500	0.290
DYS389II (30)				0.370	0.500		0.440	0.130		0.470		0.180	0.170	0.420
DYS389II (31)				0.450			0.560	0.620		0.060		0.500		0.250
DYS389II (32)				0.070				0.080				0.090	0.170	0.040
DYS389II (33)												0.140
DYS389II (34)
DYS389II total
DYS390 (20)
DYS390 (21)		0.230	0.120	0.070						0.060	0.100	0.040
DYS390 (22)		0.110						0.130						0.040
DYS390 (23)	1.000	0.330	0.880	0.560		0.080	0.330	0.080	0.250		0.100	0.640	0.330	0.420	0.400
DYS390 (24)		0.330		0.250	1.000	0.920	0.450	0.680	0.370	0.940	0.700	0.180	0.670	0.330	0.600
DYS390 (25)				0.120			0.220	0.090	0.250		0.100			0.210
DYS390 (26)								0.020	0.130			0.140
DYS390 (27)
DYS390 total
DYS391 (9)				0.020										0.210
DYS391 (10)	1.000			0.820	1.000	1.000	0.890	0.210	0.860			0.820	1.000	0.750	1.000
DYS391 (11)				0.140			0.110	0.790	0.140			0.180		0.040
DYS391 (12)				0.020
DYS391 total
DYS392 (11)										0.060
DYS392 (12)												0.140
DYS392 (13)		1.000	1.000			0.920		0.070	0.120	0.350	0.700	0.050		0.170	1.000
DYS392 (14)	1.000			0.470	0.500	0.080	0.450	0.720	0.880	0.530	0.300	0.360	0.830	0.710
DYS392 (15)				0.040	0.500		0.330	0.210		0.060		0.090	0.170	0.120
DYS392 (16)				0.470			0.220					0.360
DYS392 (17)				0.020
DYS392 (18)
DYS392 total
DYS393 (11)								0.480
DYS393 (12)		0.220	0.120			0.080		0.090	0.120	0.060	0.400	0.090			0.400
DYS393 (13)	1.000	0.780	0.880	0.440	1.000		0.670	0.340	0.760	0.590	0.600	0.550	1.000	1.000	0.600
DYS393 (14)				0.560		0.920	0.330	0.090	0.120	0.350		0.360
DYS393 (15)
DYS393 (16)
DYS393 total
DYS437 (8)
DYS437 (9)
DYS437 (11)														0.040
DYS437 (14)				1.000			1.000	0.930		0.590		1.000		0.920
DYS437 (15)								0.070		0.410				0.040
DYS437 total
DYS438 (9)
DYS438 (10)				0.050			0.220							0.040
DYS438 (11)				0.930			0.670	0.860		0.590		1.000		0.920
DYS438 (12)				0.020			0.110	0.140		0.410
DYS438 (16)														0.040
DYS438 total
DYS439 (9)												0.050
DYS439 (10)										0.060				0.130
DYS439 (11)				0.160			0.220	0.070		0.230		0.050		0.220
DYS439 (12)				0.240			0.450	0.640		0.590		0.360		0.390
DYS439 (13)				0.370			0.330	0.290		0.060		0.270		0.260
DYS439 (14)				0.230						0.060		0.270
DYS439 total												0.200
DYS448 (18)
DYS448 (19)				0.110
DYS448 (20)				0.770								0.800
DYS448 (21)				0.120
DYS448 (22)
DYS448 total
DYS456 (11)				0.020
DYS456 (13)				0.050
DYS456 (14)				0.020
DYS456 (15)				0.800								0.900
DYS456 (16)				0.090								0.100
DYS456 (17)				0.020
DYS456 total
DYS458 (13)				0.050								0.100
DYS458 (15)				0.030
DYS458 (16)				0.490								0.700
DYS458 (17)				0.250								0.200
DYS458 (18)				0.140
DYS458 (19)				0.040
DYS458 total
DYS635 (22)				0.820								0.700
DYS635 (23)				0.160								0.300
DYS635 (24)
DYS635 (26)				0.020
DYS635 total

Rodriguez-Delfin ;

Bortolini ;

Demarchi and Mitchell (2004);

Altuna ;

Leite ;

Toscanini ;

Bailliet ;

Blanco-Verea ;

Gayà-Vidal ;

Jota .

Table 3 shows the results of the molecular analysis of variance for populations structured by language or geography based on the data in Table 2. The estimates were calculated for each STR locus because testing heterogeneity prevented haplotype identification. As expected, most of the diversity was attributable to intrapopulation variation, with one exception (DYS437) that was explained by the fixation of allele 14 in 40% of the populations, whereas only allele 8 was found in the Wichí. In contrast, significant variation among subdivisions was detected for only six loci (DYS398I, DYS391, DYS392, DYS393, DYS437 and DYS456) and in five out of these six it was attributable to geography. There was also considerable inter-population/within subdivision variability (significant in 28 of 30 evaluations), with the average percentage being 16% for geography and 21% for language.

Table 3

Analysis of molecular variance of the distinct alleles of the Y-Q STRs in relation to the language and geography of the populations tested.

STR loci (structured by)	Among subdivisions	Among populations within subdivisions	Within populations
DYS19 (Language)1	0	0.311*	0.689*
DYS19 (Geography)2	0	0.332*	0.668*
DYS388 (Language)1	0.045	0.317*	0.638*
DYS388 (Geography)2	0.091	0.240*	0.669*
DYS389I (Language)1	0.227*	0.030	0.743*
DYS389I (Geography)2	0.116	0.148*	0.736*
DYS389II (Language)1	0.036	0.077*	0.887*
DYS389II (Geography)2	0	0.125*	0.875*
DYS390 (Language)1	0.008	0.326*	0.666*
DYS390 (Geography)2	0	0.359*	0.642*
DYS391 (Language)1	0	0.385*	0.615*
DYS391 (Geography)2	0.253*	0.131*	0.616*
DYS392 (Language)1	0.005	0.319*	0.676*
DYS392 (Geography)2	0.007*	0.262*	0.661*
DYS393 (Language)1	0	0.331*	0.669*
DYS393 (Geography)2	0.177*	0.167*	0.656*
DYS437 (Language)1	0.289	0.273*	0.438*
DYS437 (Geography)2	0.390*	0.213*	0.397*
DYS438 (Language)1	0.048	0.025	0.927*
DYS438 (Geography)2	0.023	0.054*	0.923*
DYS439 (Language)1	0.019	0.054*	0.929*
DYS439 (Geography)2	0.055	0.034*	0.911*
DYS448 (Language)1	0	0.148*	0.852*
DYS448 (Geography)2	0	0.073*	0.927*
DYS456 (Language)1	0	0.078*	0.922*
DYS456 (Geography)2	0.017*	0.044*	0.939*
DYS458 (Language)1	0	0.144*	0.856*
DYS458 (Geography)2	0.043	0.069*	0.888*
DYS635 (Language)1	0	0.278*	0.722*
DYS635 (Geography)2	0	0.128*	0.872*

Language: Tupi: Aché, Guarani, Parakanã, Wayampi; Carib: Apalaí, Arara, Yukpa; Macro-Ge: Kaingang, Kayapó, Mekranoti; Quechua: Diaguita, Quechua, Ingano; Mataco-Guaicuru: Mocoví, Toba, Wichí, Pilagá; Isolated languages and others with only one population were included as a sixth group.

Geography: Amazonia/Central Brazilian Plateau: Apalaí, Arara, Kayapó, Mekranoti, Pacaás Novos, Parakanã, Ticuna, Warao, Wayampi, Yanomámi; Southern Brazil: Guarani and Kaingang; Chaco: Ache, Ayoreo, Lengua, Mocoví, Pilagá, Toba, Wichí; Andes: Aymara, Barira, Diaguita, Kolla, Quechua, Wayuu, Yukpa, Zenu.

Significant values (p = 0.05). Negative values were adjusted to zero.

Table 4 summarizes the information on sequencing studies of mitochondrial DNA. The mtDNA genome of representative individuals from 35 populations has been entirely sequenced, as reported in six publications (Ingman ; Kivisild ; Tamm ; Fagundes ; Perego , 2010). However, the analyses performed did not consider the within South Amerindian relationships and were mostly concerned with interethnic or interhaplogroup comparisons. Based on 86 complete Amerindian genomes, Fagundes concluded that the prehistoric colonization of the Americas involved a single founding population, with an initial differentiation from Asia occurring in Beringia that ended around 19,000–23,000 years ago, with a moderate bottleneck. Expansion into the New World would have occurred about 18,000 years ago. An extensive 5.76 kb analysis by Dornelles established that haplogroup X is not present in extant South American Indians.

Table 4

Mitochondrial DNA sequencing studies in South Amerindian populations.

Population	HVS-I	HVS-II	Complete mt genome	References
Aché	X	X	X	Schmitt et al. (2004); Dornelles et al. (2005); Fagundes et al. (2008); Yang et al. (2010)
Ancash	X		X	Lewis Jr et al. (2005); Perego et al. (2009)
Andean	X			García-Bour et al. (2004)1
Apalaí	X			Lobato-da-Silva et al. (2001); Mazières et al. (2008)
Arara	X		X	Santos et al. (1996); Lobato-da-Silva et al. (2001); Ribeiro-dos-Santos et al. (2001); Silva Jr et al. (2002, 2003)2; Fagundes et al. (2008)
Araweté	X			Lobato-da-Silva et al. (2001)
Arequipa	X		X	Fuselli et al. (2003); Perego et al. (2009)
Arhuaco	X	X	X	Melton et al. (2007); Tamm et al. (2007); Yang et al. (2010)
Arsario	X		X	Melton et al. (2007); Tamm et al. (2007)
Asurini	X	X		Lobato-da-Silva et al. (2001); Dornelles et al. (2005)
Auca			X	Kivisild et al. (2006)
Awa-Guajá	X			Santos et al. (1996); Lobato-da-Silva et al. (2001)
Awa-Juriti	X			Lobato-da-Silva et al. (2001)
Aymara	X	X		Corella et al. (2007); Lewis Jr et al. (2007); Yang et al. (2010); Barbieri et al. (2011)
Ayoreo	X	X		Dornelles et al. (2004, 2005)
Catamarca			X	Tamm et al. (2007)
Cayapa	X	X	X	Rickards et al. (1999); Tamm et al. (2007)
Chimane	X			Corella et al. (2007)
Chilean North Coast	X			Moraga et al. (2005)1
Cinta Larga	X	X		Lobato-da-Silva et al. (2001); Dornelles et al. (2005)
Coreguaje			X	Tamm et al. (2007)
Coya	X	X		Alvarez-Iglesias et al. (2007)
Cubeo	X	X		Torres et al. (2006)
Curripaco	X	X		Torres et al. (2006)
Desano	X	X		Torres et al. (2006)
Diaguita			X	Perego et al. (2010)
Embera	X	X	X	Torres et al. (2006); Tamm et al. (2007)
Emerillon	X			Mazières et al. (2008)
Gavião	X		X	Ward et al. (1996); Fagundes et al. (2008)
Gorotire	X	X		Dornelles et al. (2005)
Guahibo	X	X		Vona et al. (2005); Torres et al. (2006)
Guarani	X	X	X	Ingman et al. (2000); Silva Jr et al. (2002, 2003)2; Dornelles et al. (2005); Kivisild et al. (2006); Marrero et al. (2007); Fagundes et al. (2008); Sala et al. (2010); Yang et al. (2010)
Huilliche	X	X		Yang et al. (2010)
Huitoto	X	X		Monsalve et al. (1994); Torres et al. (2006)
Içana River Indians	X	X		Dornelles et al. (2005)
Ignaciano	X			Bert et al. (2004)
Inga	X	X		Torres et al. (2006); Yang et al. (2010)
Jaqaru	X			Lewis Jr et al. (2007)
Jamamadi	X			Lobato-da-Silva et al. (2001)
Jebero	X	X		Monsalve et al. (1994); Torres et al. (2006)
Kaingang	X	X		Dornelles et al. (2005); Marrero et al. (2007); Yang et al. (2010)
Kali’na	X			Mazières et al. (2008)
Karitiana	X			Lobato-da-Silva et al. (2001);
Katuena	X		X	Santos et al. (1996); Lobato-da-Silva et al. (2001); Silva Jr et al. (2002, 2003)2; Fagundes et al. (2008)
Kayapó	X			Lobato-da-Silva et al. (2001); Silva Jr et al. (2002, 2003)2
Kawéskar	X			García-Bour et al. (2004)1
Kogi	X	X	X	Melton et al. (2007); Tamm et al. (2007); Yang et al. (2010)
Kolla			X	Perego et al. (2010)
Krahô	X	X		Dornelles et al. (2005)
Kikretun	X		X	Santos et al. (1996); Fagundes et al. (2008)
Kubenkokre	X		X	Santos et al. (1996); Fagundes et al. (2008)
Kuben-Kran-Kegn	X	X		Dornelles et al. (2005)
Lengua	X	X		Dornelles et al. (2005)
Mapuche	X	X		Ginther et al. (1993); Moraga et al. (2000); Dornelles et al. (2005)
Mekranoti	X	X		Dornelles et al. (2005)
Mocovi			X	Tamm et al. (2007)
Movima	X			Bert et al. (2004); Melton et al. (2007)
Munduruku	X			Lobato-da-Silva et al. (2001);
Mura	X	X		Dornelles et al. (2005)
Ocaina	X	X		Monsalve et al. (1994); Torres et al. (2006)
Pacaás Novos	X	X		Dornelles et al. (2005)
Paez	X	X		Torres et al. (2006)
Palikur	X			Lobato-da-Silva et al. (2001); Mazières et al. (2008)
Parakanã	X	X		Lobato-da-Silva et al. (2001); Dornelles et al. (2005)
Pehuenche	X	X		Merriwether et al. (1994, 1995); Merriwether and Ferrell (1996); Moraga et al. (1997, 2000); García et al. (2006)
Peruvian Andes	X	X		Shinoda et al. (2006)1; Fehren-Schmitz et al. (2011)1
Peruvian Southern	X			Fehren-Schmitz et al. (2010)1
Coast
Piapoco	X	X		Torres et al. (2006)
Pilagá	X			Cabana et al. (2006)
Poturujara	X		X	Santos et al. (1996); Lobato-da-Silva et al. (2001); Silva Jr et al. (2002, 2003)2; Fagundes et al. (2008)
Puinave	X	X		Torres et al. (2006)
Puno	X			Lewis Jr et al. (2007)
Quechua	X	X	X	Monsalve et al. (1994); Silva Jr et al. (2002, 2003)2; Fuselli et al. (2003); Dornelles et al. (2005); Kivisild et al. (2006); Corella et al. (2007); Lewis Jr et al. (2007); Fagundes et al. (2008); Yang et al. (2010); Barbieri et al. (2011)
Saliva	X	X		Torres et al. (2006)
Salta			X	Tamm et al. (2007)
Sateré Mawé	X	X		Dornelles et al. (2005)
Selknam	X			García-Bour et al. (2004)1
Sicán	X			Shimada et al. (2004)1
Suruí	X		X	Lobato-da-Silva et al. (2001); Fagundes et al. (2008)
Tayacaja	X			Bert et al. (2004)
Ticuna	X	X		Monsalve et al. (1994); Torres et al. (2006); Rojas et al. (2010); Yang et al. (2010)
Tiriyó	X	X	X	Santos et al. (1996); Lobato-da-Silva et al. (2001); Silva Jr et al. (2002, 2003)2; Dornelles et al. (2005); Fagundes et al. (2008)
Toba	X			Cabana et al. (2006)
Trinitario	X			Bert et al. (2004)
Tucuman			X	Tamm et al. (2007)
Tupe	X			Lewis Jr et al. (2007)
Txukahamãe	X	X		Dornelles et al. (2005)
Uro	X			Barbieri et al. (2011)
Urubu Kaapor	X	X		Lobato-da-Silva et al. (2001); Dornelles et al. (2005)
Vaupe			X	Tamm et al. (2007)
Wai-wai			X	Fagundes et al. (2008)
Wayampi	X	X	X	Santos et al. (1996); Lobato-da-Silva et al. (2001); Silva Jr et al. (2002, 2003)2; Dornelles et al. (2005); Fagundes et al. (2008); Mazières et al. (2008)
Warao			X	Ingman et al. (2000)
Waunana			X	Tamm et al. (2007)
Wayuu	X	X	X	Torres et al. (2006); Melton et al. (2007); Tamm et al. (2007); Yang et al. (2010)
Wichí	X			Cabana et al. (2006)
Xavante	X	X	X	Ward et al. (1996); Dornelles et al. (2005); Fagundes et al. (2008)
Xikrin	X	X		Lobato-da-Silva et al. (2001); Dornelles et al. (2005)
Yagua	X	X		Monsalve et al. (1994); Torres et al. (2006)
Yámana	X			García-Bour et al. (2004)1
Yanomámi	X	X	X	Easton et al. (1996); Santos et al. (1996); Merriwether et al. (2000); Lobato-da-Silva et al. (2001); Silva Jr et al. (2002, 2003)2; Williams et al. (2002); Dornelles et al. (2005); Fagundes et al. (2008)
Yungay	X			Lewis Jr et al. (2007)
Yuracare	X			Bert et al. (2004)
Zenu	X	X		Torres et al. (2006)
Zoró	X		X	Ward et al. (1996); Fagundes et al. (2008)

Ancient DNA.

Sequencing included almost half of the genome (sites 7,148–15,976).

The most extensive set of data involves the highly variable segment 1 (HVS-I) that has been studied in 92 populations and reported in 30 papers; surveys that have included the HVS-II region are much less common (10 articles) (Table 4). For HVS-I, Merriwether provided an excellent example of how intrapopulation variability in the Yanomámi could be interpreted in a historical and demographical context and relating it to other Amerindian and Asian data. They studied 129 Yanomámi sequences from individuals in eight villages and compared their haplotypes with those of other Asian and New World populations, in a total of 482 unique haplotypes. Interestingly, the pairwise inter-population gene flow estimates were lower between some pairs of Yanomámi villages than between them and four other South Amerindian groups.

With regard to intrapopulation variability, as measured by Θk, Fuselli and Corella reported extensive variation for 14 and 27 Central and Southern Amerindian populations, respectively (e.g., from 0.659 for the Quechua of Peru to 0.011 for the Xavante of the Brazilian Mato Grosso). Intra- and intergroup nucleotide diversity was calculated by Melton for 20 of these Amerindian groups, whereas Barbieri compared the sources of variation among North, Central and South Amerindians in 51 populations; the latter authors observed 3% variation among the three sets, 21% variation among populations within the subcontinent and 76% variation within populations.

To explore the mtDNA data further we compiled the prevalences of haplogroups A–D for 109 populations, in a total of 6,697 individuals distributed between latitude 11° North and 54° South, and longitude 46° to 78° West (Table 5). Sample sizes varied widely, from only one subject tested (Jebero) up to 491 (Yanomámi). The haplogroup frequencies reported in 52 articles also varied widely. The presence of mtDNA genomes of probable non-Amerindian origin was rare in all regions and populations, in contrast to the Y-SNP data (Table 1). Asymmetrical sex-mediated admixture was common during the first centuries of South American colonization, and involved mostly European men and Amerindian/African women. The main consequences of this historical contact was the formation of mestizos and the present-day national societies; the former are characterized by a composite genome, with the majority of Y-chromosomes being of European origin, while their mtDNA derives from Amerindian or African sources (Bortolini ; Alves-Silva ; Carvalho-Silva ; Salzano and Bortolini, 2002). Asymmetrical mating could also explain the introduction of non-Amerindian Y-chromosomes into the tribes, while the autochthonous mtDNA genomes were preserved. However, the admixture dynamics are probably different from those observed in urban groups since they normally involve Amerindian women who live on reservations and men who live near the border of the reservations. In this situation, the children normally remain with their mothers. This phenomenon has been described for Guarani Indians (Marrero ), but the data presented here indicate that it could be much more common than previously thought.

Table 5

Mitochondrial DNA haplogroup and linguistic and geographical information for the samples considered.

Population (n)1	Haplogroups (%)					Language	Geographical coordinates	References
	A	B	C	D	Others2
Wayuu (89)	26	28	45	0	1	Arawakan	11° N; 73° W	Mesa et al. (2000); Keyeux et al. (2002); Melton et al. (2007)
Kogi (153)	67	0	33	0	0	Chibchan	11° N; 74° W	Keyeux et al. (2002); Melton et al. (2007); Rojas et al. (2010)
Arsario (Wiwa) (76)	63	0	37	0	0	Chibchan	10° 25′ N; 73° 05′ W	Keyeux et al. (2002); Melton et al. (2007); Rojas et al. (2010)
Chimila (35)	88	0	3	6	3	Chibchan	10° 16′ N; 74° 4′ W	Keyeux et al. (2002)
Arhuaco (Ijka) (134)	87	1	12	0	0	Chibchan	9° 04′ N; 73° 59′ W	Keyeux et al. (2002); Melton et al. (2007); Rojas et al. (2010)
Yukpa (88)	0	100	0	0	0	Carib	8° 40′ N; 72° 41′ W	Keyeux et al. (2002)
Zenu (107)	19	38	36	5	2	Spanish	8° 30′ N; 76° W	Mesa et al. (2000); Keyeux et al. (2002); Torres et al. (2006)
Embera (43)	53	35	2	5	5	Choco	7° N; 76° 30′ W	Mesa et al. (2000); Keyeux et al. (2002)
Tule-Cuna (30)	50	27	20	0	3	Chibchan	6° 56′ N; 76° 45′ W	Keyeux et al. (2002)
Guane-Butaregua (33)	12	64	0	24	0	Chibchan	6° 15′ N; 73° 15′ W	Keyeux et al. (2002)
Cubeo (22)	27	18	50	5	0	Tucanoan	5° 9′ N; 70° 18W	Torres et al. (2006)
Makiritare (10)	20	0	70	10	0	Carib	5° 33′ N; 65° 33′ W	Torroni et al. (1993)
Kali’ na (Galibi) (29)	7	41	38	7	7	Carib	5° 31′ N; 53° 47′ W	Mazières et al. (2008)
Guahibo (99)	52	3	33	0	12	Guahiban	5° N; 69° W	Keyeux et al. (2002); Vona et al. (2005); Torres et al. (2006)
Waunana (161)	21	49	16	14	0	Choco	4° 50′ N; 77° W	Keyeux et al. (2002); Tamm et al. (2007); Rojas et al. (2010)
Palikúr (64)	1	47	4	47	1	Arawakan	4° N; 51° 45′ W	Lobato-da-Silva et al. (2001); Mazières et al. (2008)
Macushi (10)	10	20	30	40	0	Carib	4° N; 60° 50′ W	Torroni et al. (1993)
Páez (51)	59	12	27	2	0	Páez	3° 9′ N; 75° 28′ W	Keyeux et al. (2002); Torres et al. (2006)
Ocaina (2)	0	0	100	0	0	Witotoan	3° 58′ N; 68° 2′ W	Torres et al. (2006)
Jebero (1)	0	0	100	0	0	Cahuapanan	3° 58′ N; 68° 2′ W	Torres et al. (2006)
Piaroa (28)	36	11	21	32	0	Salivan	3° 57′ N; 66° 22′ W	Torroni et al. (1993); Keyeux et al. (2002)
Desano (2)	50	0	0	50	0	Tucanoan	3° 24′ N; 69° 40′ W	Torres et al. (2006)
Wapishana (12)	0	25	8	67	0	Arawakan	3° 07′ N; 60° 03′ W	Torroni et al. (1993)
Emerillon (30)	30	70	0	0	0	Tupi	3° N; 53° W	Mazières et al. (2008)
Guambiano (23)	4	4	79	13	0	Barbacoan	2° 6′ N; 76° 23′ W	Keyeux et al. (2002)
Yanomámi (491)	2	25	50	19	4	Yanomam	2° 50′ N; 54° W	Torroni et al. (1992, 1993); Easton et al. (1996); Merriwether et al. (2000); Williams et al. (2002); Silva Jr et al. (2003)
Guayabero (30)	50	17	13	0	20	Guahiban	2° 25′ N; 71° 4′ W	Keyeux et al. (2002)
Curripaco (22)	41	36	23	0	0	Arawakan	2° 10′ N; 68° 54′ W	Keyeux et al. (2002); Torres et al. (2006)
Tiriyó (32)	9	19	22	47	3	Carib	2° N; 56° W	Lobato-da-Silva et al. (2001); Silva Jr et al. (2003)
Nukak (20)	0	20	80	0	0	Maku	1° 44′ N; 70° 44′ W	Keyeux et al. (2002)
Apalaí (120)	37	1	30	32	0	Carib	1° 20′ N; 54° 40′ W	Lobato-da-Silva et al. (2001); Mazières et al. (2008)
Cayapa (120)	29	40	9	22	0	Barbacoan	1° 17′ N; 78° 50′ W	Rickards et al. (1999)
Wayampi (99)	62	11	8	19	0	Tupi	1° N; 53° W	Santos et al. (1996); Lobato-da-Silva et al. (2001); Silva Jr et al. (2003); Mazières et al. (2008)
Siona (12)	75	17	8	0	0	Tucanoan	0° 6′ N; 75° 36′ W	Keyeux et al. (2002)
Pasto (9)	67	33	0	0	0	Barbacoan	0° 58′ N; 77° 44′ W	Keyeux et al. (2002)
Yagua (12)	25	0	67	8	0	Peba-Yaguan	0° 51′ N; 72° 27′ W	Torres et al. (2006)
Ingano (111)	18	38	42	0	2	Quechuan	0° 50′ N; 77° W	Mesa et al. (2000); Keyeux et al. (2002); Torres et al. (2006); Rojas et al. (2010)
Tucano (17)	0	18	47	35	0	Tucanoan	0° 42′ N; 69° 53′ W	Keyeux et al. (2002)
Coreguaje (69)	4	20	66	6	4	Tucanoan	0° 38′ N; 76° 8′ W	Keyeux et al. (2002); Tamm et al. (2007)
Awa-Juriti (18)	0	72	11	0	17	Tucanoan	0° 16′ N; 70° 45′ W	Lobato-da-Silva et al. (2001)
Muinane (19)	11	21	37	26	5	Witotoan	0° 11′ N; 73° 25′ W	Keyeux et al. (2002)
Poturujara (23)	44	0	26	30	0	Tupi	0° 18′ S; 55° 18′ W	Lobato-da-Silva et al. (2001); Silva Jr et al. (2003)
Katuena (23)	26	9	35	30	0	Carib	0° 40′ S; 57° 30′ W	Lobato-da-Silva et al. (2001); Silva Jr et al. (2003)
Wai-wai (26)	15	15	43	27	0	Carib	0° 40′ S; 58° W	Bonatto and Salzano (1997)
Urubu Kaapor (42)	21	31	14	29	5	Tupi	2°–3° S; 46°–47° W	Torroni et al. (1992, 1993); Lobato-da-Silva et al. (2001); Dornelles et al. (2005)
Huitoto (35)	23	3	25	46	3	Witotoan	2° 14′ S; 72° 19′ W	Keyeux et al. (2002); Torres et al. (2006)
Arara (70)	54	20	26	0	0	Carib	3° 30′–4° 20′ S; 53° 0′–54° 10′ W	Lobato-da-Silva et al. (2001); Ribeiro-dos-Santos et al. (2001); Silva Jr et al. (2003); Bisso-Machado (2010, MSc Dissertation, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.)
Awa-Guajá (53)	13	87	0	0	0	Tupi	3° 30′ S; 46° 40′ W	Lobato-da-Silva et al. (2001)
Asurini (24)	4	54	17	21	4	Tupi	3° 35′–4° 12′ S; 49° 40′–52° 26′ W	Lobato-da-Silva et al. (2001)
Piapoco (39)	18	3	15	5	59	Arawakan	3° 36′ S; 70° 23′ W	Torres et al. (2006)
Puinave (19)	5	16	58	16	5	Puinave	3° 36′ S; 70° 23′ W	Torres et al. (2006)
Sáliba (13)	15	0	55	15	15	Salivan	3° 49′ S; 70° 9′ W	Torres et al. (2006)
Ticuna (371)	20	11	35	33	1	Ticuna	4° S; 69° 58′ W	Schurr et al. (1990); Mesa et al. (2000); Torres et al. (2006); Mendes-Junior and Simões (2009); Rojas et al. (2010)
Parakanã (31)	6	39	32	23	0	Tupi	5° 22′ S; 51° 17′ W	Lobato-da-Silva et al. (2001); Bisso-Machado (2010, MSc Dissertation)
Xikrin (33)	30	64	3	3	0	Macro-Ge	5° 55′ S; 51° W	Lobato-da-Silva et al. (2001); Dornelles et al. (2005); Bisso-Machado (2010, MSc Dissertation)
Suruí (44)	7	4	0	89	0	Tupi	5° 58′ -10° 50′ S; 48° 39′ -61° 10′ W	Bonatto and Salzano (1997); Lobato-da-Silva et al. (2001)
Araweté (18)	39	0	50	11	0	Tupi	5° 9′ S; 52° 22′ W	Lobato-da-Silva et al. (2001)
Munduruku (92)	12	17	9	58	4	Tupi	6° 23′ S; 59° 9′ W	Torroni et al. (1992, 1993); Lobato-da-Silva et al. (2001); Marrero et al. (2007); Bisso-Machado (2010, MSc Dissertation)
Marubo (10)	10	0	60	30	0	Panoan	6° 47′ S; 72° 80′ W	Torroni et al. (1993)
Jamamadi (23)	0	0	96	4	0	Arauan	7° 15′ S; 66° 41′ W	Lobato-da-Silva et al. (2001); Bisso-Machado (2010, MSc Dissertation)
Yungay (38)	5	45	34	16	0	Quechuan	7° 26′ S; 77° 4′ W	Lewis Jr et al. (2007)
Ancash (33)	9	52	18	21	0	Quechua	7° 41′ S; 77° 6′ W	Lewis Jr et al. (2005)
Gorotire (11)	28	18	18	36	0	Macro-Ge	7° 44′ S; 51° 10′ W	Bisso-Machado (2010, MSc Dissertation)
Krahó (14)	29	57	14	0	0	Macro-Ge	8° S; 47° 15′ W	Torroni et al. (1993)
Kuben-Kran-Kegn (19)	58	26	6	10	0	Macro-Ge	8° 10′ S; 52° 8′ W	Bisso-Machado (2010, MSc Dissertation)
Mekranoti (19)	26	63	11	0	0	Macro-Ge	8° 40′ S; 54° W	Dornelles et al. (2005); Bisso-Machado (2010, MSc Dissertation)
Kubenkokre (4)	0	100	0	0	0	Macro-Ge	8° 43′ S; 53° 23′ W	Marrero et al. (2007)
Kayapó (13)	46	54	0	0	0	Macro-Ge	9° S; 53° W	Lobato-da-Silva et al. (2001)
Karitiana (19)	0	11	0	89	0	Tupi	9° 30′ S; 64° 15′ W	Lobato-da-Silva et al. (2001)
Cinta-Larga (45)	25	0	20	53	2	Tupi	9° 50′–12° 30′ S; 59° 10′–60° 50′ W	Lobato-da-Silva et al. (2001); Dornelles et al. (2005); Bisso-Machado (2010, MSc Dissertation)
Gavião (27)	15	15	0	70	0	Tupi	10° 10′ S; 61° 8′ W	Ward et al. (1996)
Tupe (16)	0	69	31	0	0	Aymaran	10° 16′ S; 75° 47′ W	Lewis Jr et al. (2007)
Txukahamãe (2)	100	0	0	0	0	Macro-Ge	10° 20′ S; 53° 5′ W	Dornelles et al. (2005)
Zoró (30)	20	7	13	60	0	Tupi	10° 20′ S; 60° 20′ W	Ward et al. (1996)
Matsiguenga (38)	5	92	0	3	0	Arawakan	10° 47′–12° 51′ S; 73° 17′ -70° 44′ W	Mazières et al. (2008)
Kokraimoro (2)	50	50	0	0	0	Macro-Ge	10° 49′ S; 55° 27′ W	Marrero et al. (2007)
Pacaás Novos (Wari) (30)	40	30	27	3	0	Chapacura-Wanh am	11° 8′ S; 65° W	Bisso-Machado (2010, MSc Dissertation)
Tayacaja (61)	21	33	13	30	3	Quechuan	12° 24′ S; 74° 34′ W	Fuselli et al. (2003)
Arequipa (22)	9	68	14	9	0	Quechua	13° 13′ S; 72° 11′ W	Fuselli et al. (2003)
Trinitario (35)	14	40	37	3	6	Arawakan	14° S; 65° W	Bert et al. (2001)
Xavánte (25)	16	84	0	0	0	Macro-Ge	14° S; 52° 30′ W	Ward et al. (1996)
Movima (22)	9	9	64	18	0	Movima	14° 26′ S; 65° 53′ W	Bert et al. (2001)
Quechua (232)	14	62	15	9	0	Quechuan	14° 30′ S; 69° W	Merriwether et al. (1995); Bert et al. (2001); Silva Jr et al. (2003); Lewis Jr et al. (2007); Corella et al. (2007); Barbieri et al. (2011); Gayà-Vidal et al. (2011)
Chimane (Moseten) (71)	39	54	3	0	4	Chimane	14° 41′ S; 66° 50′ W	Bert et al. (2001); Corella et al. (2007);
Ignaciano (22)	18	36	41	0	5	Arawakan	15° 1′ S; 66° 4′ W	Bert et al. (2001)
Uro (64)	11	69	9	11	0	Uru-Chipaya	15° 45′ S; 69° 53′ W	Barbieri et al. (2011)
Yuracare (28)	39	32	21	4	4	Yuracare	17° S; 65° W	Bert et al. (2001)
Aymara (411)	4	76	8	11	1	Aymaran	17° 68′ S; 69° 16′ W	Merriwether et al. (1995); Easton et al. (1996); Bert et al. (2001); Lewis Jr et al. (2007); Corella et al. (2007); Barbieri et al. (2011); Gayà-Vidal et al. (2011)
Ayoreo (91)	0	0	83	17	0	Zamucoan	19° S; 60° 30′ W	Dornelles et al. (2004)
Wichí (199)	12	51	7	29	1	Mataco-Guaicuru	22° 28′ S; 62° 70′ W	Torroni et al. (1993); Bianchi et al. (1995); Bravi et al. (1995); Demarchi et al. (2001); Cabana et al. (2006)
Chorote (34)	15	44	23	18	0	Mataco-Guaicuru	22° 90′ S; 65° 40′ W	Bianchi et al. (1995); Bravi et al. (1995)
Humahuaca (46)	11	68	17	4	0	Spanish	23° 11′ S; 65° 20′ W	Dipierri et al. (1998)
Aché (63)	10	90	0	0	0	Tupi	23° 30′–24° 10′ S; 55° 50′–56° 30′ W	Schmitt et al. (2004)
Atacameño (79)	13	73	10	4	0	Atacama	23° 50′ S; 68° W	Baillliet et al. (1994); Merriwether et al. (1995); Merriwether and Ferrell (1996)
Guarani (249)	77	6	9	6	2	Tupi	23° 6′ S; 55° 12′ W	Silva Jr et al. (2003); Marrero et al. (2007); García and Demarchi (2009)
Pilagá (41)	5	37	27	29	2	Mataco-Guaicuru	24° S; 59° W	Demarchi et al. (2001); Cabana et al. (2006)
Coya (60)	13	57	23	5	2	Coya	25° 30′ S; 67° 28′ W	Álvarez-Iglesias et al. (2007)
Toba (80)	15	43	5	37	0	Mataco-Guaicuru	26° S; 58° W	Bianchi et al. (1995); Demarchi et al. (2001); Goicoechea et al. (2001); Cabana et al. (2006)
Jujuy (19)	16	58	16	10	0	Spanish	27° 27′ S; 58° 59′ W	Dipierri et al. (1998)
Kaingang (79)	47	4	48	0	1	Macro-Ge	28° S; 51° 20′ W	Dornelles et al. (2005); Marrero et al. (2007)
Mocoví (5)	80	0	0	20	0	Mataco-Guaicuru	29° 51′ S; 59° 56′ W	Tamm et al. (2007)
Pehuenche (205)	2	9	40	49	0	Araucanian	37° 43′ S; 71° 16′ W	Merriwether et al. (1995); Moraga et al. (1997, 2000)
Mapuche (314)	5	23	32	36	4	Araucanian	39° 10′–41° 20′ S; 68° 37′–70° 22′ W	Ginther et al. (1993); Horai et al. (1993); Bailliet et al. (1994); Bianchi et al. (1995); Moraga et al. (2000)
Huilliche (207)	4	28	20	48	0	Araucanian	41° 16′ S; 73° W	Bailliet et al. (1994); Merriwether et al. (1995); Merriwether and Ferrell (1996)
Aónikenk[3, 4] (15)	0	0	27	73	0	Chon	45° S; 71° W	Lalueza (1995, PhD thesis, Universitat de Barcelona, Barcelona, Spain)
Tehuelche4 (29)	0	20	24	56	0	Chon	45° S; 71° W	Moraga et al. (2000)
Yámana3 (Yaghan) (32)	0	0	63	37	0	Yámana	47° S; 74° W	Lalueza (1995, PhD thesis); Moraga et al. (1997, 2000)
Kawéskar2 (Alacaluf) (19)	0	0	16	84	0	Alacalufan	49° S; 74° W	Lalueza (1995, PhD thesis)
Selknam2 (Ona) (16)	0	0	56	38	6	Chon	54° S; 74° W	Lalueza (1995, PhD thesis); García-Bour et al. (2004)

Arranged according to latitude.

Probably of non-Amerindian origin.

Ancient DNA.

Aónikenk and Tehuelche are the same tribe separated by time. Aónikenk refers to ancient DNA.

Table 6 summarizes the influence of geography. In the seven regions that were defined, 74% of the variation occurred within populations, 6% among geographic divisions and 20% among populations within divisions. To analyze this variability further, the isolated frequencies of haplogroups A to D were plotted as shown in Figure 2. High frequencies of haplogroup C were observed in specific regions along the northwestern portion of the continent, with additional high spots in southern Brazil and northern Argentina. The prevalences of haplogroups B and D showed a clear east-west separation, while for haplo-group A there were three main high prevalence nuclei in the north, center and south of the continent. Spearman’s correlation coefficient between haplogroup frequencies and latitude yielded a positive value (0.27; p < 0.01) for haplogroup A, with a corresponding negative one (−0.25; p < 0.01) for haplogroup D. The coefficients for haplo-groups B and C were not significant.

Table 6

Mitochondrial DNA haplogroup frequencies by geography.

Geographic divisions	No. of populations	No. of individuals	Haplogroups (%)
			A	B	C	D	Other
Amazonia	55	2410	20	21	31	25	3
Central Plateau	2	39	21	74	5	0	0
Southern Brazil	2	328	70	6	18	4	2
Chaco	6	479	10	43	22	24	1
Southern South America	3	726	4	20	31	43	2
Tierra del Fuego	5	111	0	5	39	55	1
Andes	35	2604	27	45	20	7	1
Total	108	6697

AMOVA results: (a) Among geographic divisions: 6.2%; (b) Among populations within geographic divisions: 19.5%; (c) Within populations: 74.3%. The three values are statistically significant.

Figure 2

Isoline map distribution showing the geographic pattern of the four (A–D) mtDNA haplogroups in South Amerindians. The dots indicate the locations of the populations sampled. As indicated in the scales given at right of each map, the colors represent the haplogroup frequencies, from dark blue (0.00) to red (1.00).

Table 7 summarizes the influence of language. Sixteen main language groups were considered, plus a composite set of “others”. The AMOVA results indicated that 73% of the haplogroup prevalence variability occurred within populations, with 7% of it being attributable to languages. However, there was considerable heterogeneity (20%) within the language categories established. Overall, the variability was similar to that obtained for geography.

Table 7

Mitochondrial DNA haplogroup frequencies by language.

Language	No. of populations	No. of individuals	Haplogroups (%)
			A	B	C	D	Other
Tupi	16	889	38	24	10	27	1
Macro-Ge	11	221	37	38	21	3	1
Carib	9	408	24	32	25	18	1
Chibchan	6	461	69	6	22	2	1
Mataco-Guaicuru	5	359	13	46	11	29	1
Arawakan	8	321	16	38	24	13	9
Araucanian	3	726	4	20	31	43	2
Choco	2	204	28	46	13	12	1
Chon	3	60	0	10	33	55	2
Tucanoan	6	140	14	26	48	8	4
Aymaran	2	427	4	76	9	10	1
Barbacoan	3	152	28	34	19	19	0
Guahiban	2	129	51	6	29	0	14
Witotoan	3	56	18	9	32	37	4
Salivan	2	41	29	7	32	27	5
Quechuan	6	497	14	51	23	11	1
Other	21	1606	13	26	40	19	2
Total	108	6697

AMOVA results: (a) Among language groups: 6.6%; (b) Among populations within language groups: 20.1%; (c) Within populations: 73.3%. The three values are statistically significant.

Conclusion

South Amerindians have been extensively studied with regard to the Y-chromosome, as well as and especially so for mtDNA markers. In agreement with studies from other regions, by far most of the mtDNA variability (73%–74%) is intrapopulational. Geographical and linguistic factors influenced the patterns of mtDNA diversity to a similar extent, while geography was apparently more important than language in explaining the data for the Y chromosome Q clade-STRs. Additional factors that may have influenced these results include distinct male and female migration patterns, as well as cultural and other characteristics. The fact that most studies have generally dealt with small populations, in which genetic drift may be important, could also have influenced the results.

Table 2(b)

Y-Q-chromosome STR studies in distinct South Amerindian samples in which allele frequencies can be assessed (Part B).

	Ref. (n)
STR (allele)	Mocoví (2)8	Pacaás Novos (15)2	Parakanã (4)2	Pilagá (9)3	Quechua (58)[10, 11]	Ticuna (36)2	Toba (70)[3, 7]	Warao (12)2	Wayampi (10)1	Wayuu (14)2	Wichí (27)3	Yanomama (9)1	Yukpa (12)2	Zenu (28)2	Total (590)
DYS19 (12)							0.030				0.030				0.010
DYS19 (13)	0.500			0.790	0.950	0.850	0.870	1.000		0.790	0.640		0.550	0.650	0.890
DYS19 (14)	0.500	1.000		0.210	0.030	0.090	0.090			0.140	0.230		0.450	0.270	0.050
DYS19 (15)					0.020	0.060	0.010			0.070	0.100			0.080	0.040
DYS19 (16)															0.010
DYS19 total															474
DYS388 (12)		0.860	1.000			0.780		0.750		0.570			0.500	0.500	0.780
DYS388 (13)		0.140				0.220		0.250		0.430			0.500	0.430	0.200
DYS388 (14)															0.010
DYS388 (17)														0.070	0.040
DYS388 total															189
DYS389I (12)					0.090										0.080
DYS389I (13)	1.000				0.240		0.800								0.440
DYS389I (14)					0.670		0.200								0.450
DYS389I (15)															0.030
DYS389I total															288
DYS389II (17)					0.270										0.020
DYS389II (18)					0.530										0.030
DYS389II (19)					0.200										0.010
DYS389II (26)															0.010
DYS389II (27)															0.010
DYS389II (28)					0.090										0.030
DYS389II (29)					0.070										0.110
DYS389II (30)					0.210		0.500								0.290
DYS389II (31)	0.500				0.540		0.320								0.390
DYS389II (32)	0.500				0.090		0.160								0.080
DYS389II (33)															0.010
DYS389II (34)							0.020								0.010
DYS389II total															288
DYS390 (20)					0.020										0.010
DYS390 (21)					0.240										0.070
DYS390 (22)					0.020		0.080				0.030	0.780			0.070
DYS390 (23)	0.500	0.450		0.210	0.450	0.060	0.110	0.080	1.000	0.220	0.070			0.250	0.320
DYS390 (24)	0.500	0.550	1.000	0.790	0.220	0.150	0.730	0.920		0.560	0.740	0.110	1.000	0.290	0.400
DYS390 (25)					0.050	0.760	0.080			0.220	0.130			0.420	0.110
DYS390 (26)											0.030				0.010
DYS390 (27)						0.030						0.110		0.040	0.010
DYS390 total															659
DYS391 (9)										0.070	0.030				0.030
DYS391 (10)	1.000	1.000		0.890	0.840	0.930	0.900	0.250		0.570	0.870		1.000	0.640	0.800
DYS391 (11)			1.000	0.110	0.160	0.070	0.100	0.750		0.360	0.100			0.360	0.160
DYS391 (12)															0.010
DYS391 total															512
DYS392 (11)							0.030			0.570	0.060				0.020
DYS392 (12)									1.000	0.070				0.130	0.030
DYS392 (13)	1.000	0.890		0.100			0.100	0.110			0.130	0.890	0.180	0.060	0.170
DYS392 (14)		0.110		0.800	0.520	0.380	0.670	0.890		0.290	0.420	0.110	0.460	0.560	0.510
DYS392 (15)				0.100	0.070	0.620	0.190			0.070	0.390		0.360	0.250	0.150
DYS392 (16)					0.290										0.100
DYS392 (17)					0.020										0.010
DYS392 (18)					0.100		0.010								0.010
DYS392 total															535
DYS393 (11)			1.000												0.040
DYS393 (12)						0.060	0.010			0.100	0.060			0.040	0.040
DYS393 (13)	1.000	0.780		1.000	0.550	0.710	0.980	0.750		0.800	0.840	0.890	0.500	0.200	0.670
DYS393 (14)		0.220			0.450	0.170	0.010	0.250	1.000	0.100	0.100	0.110	0.500	0.240	0.220
DYS393 (15)						0.030								0.480	0.020
DYS393 (16)						0.030								0.040	0.010
DYS393 total															584
DYS437 (8)				0.420			0.360			1.000					0.200
DYS437 (9)				0.580			0.030								0.040
DYS437 (11)															0.010
DYS437 (14)					1.000		0.500								0.700
DYS437 (15)							0.110								0.050
DYS437 total															322
DYS438 (9)					0.020										0.010
DYS438 (10)							0.050			0.160					0.050
DYS438 (11)				0.790	0.930		0.850			0.840					0.850
DYS438 (12)				0.210	0.050		0.100								0.080
DYS438 (16)															0.010
DYS438 total															322
DYS439 (9)															0.010
DYS439 (10)															0.010
DYS439 (11)					0.090		0.130			0.230					0.140
DYS439 (12)				0.320	0.240		0.500			0.710					0.400
DYS439 (13)				0.680	0.500		0.290			0.060					0.330
DYS439 (14)					0.170		0.080								0.110
DYS439 total															322
DYS448 (18)															0.010
DYS448 (19)					0.140		0.020								0.090
DYS448 (20)					0.550		0.930								0.740
DYS448 (21)					0.240		0.050								0.140
DYS448 (22)					0.070										0.020
DYS448 total															169
DYS456 (11)															0.010
DYS456 (13)															0.020
DYS456 (14)					0.230		0.020								0.090
DYS456 (15)					0.720		0.730								0.750
DYS456 (16)					0.050		0.250								0.120
DYS456 (17)															0.010
DYS456 total															169
DYS458 (13)															0.020
DYS458 (15)					0.030		0.040								0.040
DYS458 (16)					0.360		0.180								0.380
DYS458 (17)					0.520		0.550								0.410
DYS458 (18)					0.090		0.230								0.140
DYS458 (19)															0.010
DYS458 total															169
DYS635 (22)					0.950		0.950								0.890
DYS635 (23)					0.020		0.050								0.090
DYS635 (24)					0.030										0.010
DYS635 (26)															0.010
DYS635 total															169

Rodriguez-Delfin ;

Bortolini ;

Demarchi and Mitchell (2004);

Altuna ;

Leite ;

Toscanini ;

Bailliet ;

Blanco-Verea ;

Gayà-Vidal ;

Jota .