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BMC Biology

Research article
Open Access

African-American mitochondrial DNAs often match mtDNAs found in multiple African ethnic groups

  • Bert Ely1Email author,
  • Jamie Lee Wilson2,
  • Fatimah Jackson3 and
  • Bruce A Jackson2
BMC Biology20064:34

https://doi.org/10.1186/1741-7007-4-34

©  Ely et al; licensee BioMed Central Ltd. 2006

Received: 31 May 2006

Accepted: 12 October 2006

Published: 12 October 2006

The Erratum to this article has been published in BMC Biology 2007 5:13

Abstract

Background

Mitochondrial DNA (mtDNA) haplotypes have become popular tools for tracing maternal ancestry, and several companies offer this service to the general public. Numerous studies have demonstrated that human mtDNA haplotypes can be used with confidence to identify the continent where the haplotype originated. Ideally, mtDNA haplotypes could also be used to identify a particular country or ethnic group from which the maternal ancestor emanated. However, the geographic distribution of mtDNA haplotypes is greatly influenced by the movement of both individuals and population groups. Consequently, common mtDNA haplotypes are shared among multiple ethnic groups. We have studied the distribution of mtDNA haplotypes among West African ethnic groups to determine how often mtDNA haplotypes can be used to reconnect Americans of African descent to a country or ethnic group of a maternal African ancestor. The nucleotide sequence of the mtDNA hypervariable segment I (HVS-I) usually provides sufficient information to assign a particular mtDNA to the proper haplogroup, and it contains most of the variation that is available to distinguish a particular mtDNA haplotype from closely related haplotypes. In this study, samples of general African-American and specific Gullah/Geechee HVS-I haplotypes were compared with two databases of HVS-I haplotypes from sub-Saharan Africa, and the incidence of perfect matches recorded for each sample.

Results

When two independent African-American samples were analyzed, more than half of the sampled HVS-I mtDNA haplotypes exactly matched common haplotypes that were shared among multiple African ethnic groups. Another 40% did not match any sequence in the database, and fewer than 10% were an exact match to a sequence from a single African ethnic group. Differences in the regional distribution of haplotypes were observed in the African database, and the African-American haplotypes were more likely to match haplotypes found in ethnic groups from West or West Central Africa than those found in eastern or southern Africa. Fewer than 14% of the African-American mtDNA sequences matched sequences from only West Africa or only West Central Africa.

Conclusion

Our database of sub-Saharan mtDNA sequences includes the most common haplotypes that are shared among ethnic groups from multiple regions of Africa. These common haplotypes have been found in half of all sub-Saharan Africans. More than 60% of the remaining haplotypes differ from the common haplotypes at a single nucleotide position in the HVS-I region, and they are likely to occur at varying frequencies within sub-Saharan Africa. However, the finding that 40% of the African-American mtDNAs analyzed had no match in the database indicates that only a small fraction of the total number of African haplotypes has been identified. In addition, the finding that fewer than 10% of African-American mtDNAs matched mtDNA sequences from a single African region suggests that few African Americans might be able to trace their mtDNA lineages to a particular region of Africa, and even fewer will be able to trace their mtDNA to a single ethnic group. However, no firm conclusions should be made until a much larger database is available. It is clear, however, that when identical mtDNA haplotypes are shared among many ethnic groups from different parts of Africa, it is impossible to determine which single ethnic group was the source of a particular maternal ancestor based on the mtDNA sequence.

Keywords

West CentralMultiple Ethnic GroupSingle Ethnic GroupAfrican Ethnic GroupMaternal Ancestor

Background

The Atlantic slave trade resulted in the forced migration of an estimated 11 million Africans to the Americas. Only 9 million are thought to have survived the passage, and many more died in the early years of captivity. Historical accounts indicate that virtually all enslaved Africans brought to North America came from either West or West Central Africa. A recent comparison of mtDNA sequences from 1148 African Americans living in the US with a database of African mtDNA sequences showed that more than 55% of the US lineages have a West African ancestor, while fewer than 41% came from West Central or South West Africa [1]. In North America, different constellations of African groups were brought to various staging areas [2]. Among the important staging areas for the arrival and distribution of enslaved Africans were the ports of Savannah, GA and Charleston, SC. Estimates of the origin of enslaved Africans received at these sites are presented in Figure 1, with the largest African regional contributions coming from West Central Africa (40%; contemporary Angola, the Congos, Equatorial Guinea, and Gabon), and the West African regions of Senegambia (23%; contemporary Senegal, Gambia, and northern Guinea), and Upper Guinea (18%; contemporary Guinea and Sierra Leone and northwestern Liberia). Africans in the Carolina coast region were intentionally mixed to reduce the possibilities for successful revolts and to facilitate their assimilation into plantation-slave society. The contemporary Gullah/Geechee culture emerged from these Africans.
Figure 1

Proportions of enslaved Africans brought to historic Carolina coast ports from the 17th to 19th centuries CE (from Jackson, 2004 [2]).

Because mitochondrial DNA (mtDNA) is passed from mother to daughter with few, if any, changes occurring over many generations, it is possible to compare contemporary African-American mtDNA haplotypes with contemporary mtDNA haplotypes in a worldwide database to obtain information about the ancestral origins of these mtDNAs. In such a comparison, continent-specific haplotypes are readily observed, and the assignment of mtDNAs to continent of origin is relatively straightforward. The more difficult task is to tie particular mtDNA haplotypes to specific geographical regions and ethnic groups within a continent. This task is particularly difficult for Africa, as there is more genetic diversity among Africans than among people from any other continent and because humanity has resided in Africa longer than anywhere else.

Comparisons of individual mtDNA haplotypes could be used to identify a geographical region, particular country, or even an ethnic group from which a maternal ancestor emanated. However, the geographic distribution of mtDNA haplotypes is greatly influenced by the migration of individuals or population groups. These movements often result in the assimilation of people from other ethnic groups. Intermarriage also causes mtDNA haplotypes to move from one ethnic group to another. Over time, mtDNA haplotypes that originated in a single ethnic group are distributed among many ethnic groups. Despite these complications, mtDNA analyses for the purposes of ancestry reconstruction are increasing in popularity. Many people have had their mtDNA tested with the hope that the test will match their DNA to an mtDNA haplotype found in a particular ethnic group. For African Americans, who have been disenfranchised from their specific African roots, such a test might provide a clue about the ethnic group or country in Africa where one of their maternal ancestors originated. However, if identical mtDNA haplotypes are shared among many ethnic groups from different parts of Africa, it would be impossible to use DNA sequence information to determine which single ethnic group was the source of a particular maternal ancestor. To date, there are no published assessments that provide quantitative information about how often African-American mtDNAs are exact matches to multiple African ethnic groups. Therefore, we decided to compare samples of Carolina coast and other African-American mtDNAs to a database of sub-Saharan African mtDNAs to generate such an assessment.

Results

Database characterization

We assembled a database of 3645 mtDNA HVS-I sequences from the published literature and 80 additional sequences from our own (unpublished) studies of ethnic groups in Mali to generate a database of 3725 sequences. Only sequences from sub-Saharan Africa were included in the database, because North African mtDNAs are quite different from sub-Saharan mtDNAs [1] and few North American slaves are thought to have come from North African countries. Within the sub-Saharan database, more than 50% of the sequences were identical to a sequence from at least one other ethnic group. The remaining sequences either occurred multiple times within a single ethnic group or occurred only once in the database.

To provide a regional analysis of the database, samples were assigned to geographic regions as shown in Table 1 and Figure 2, and the percentages of within-region and among-region matches were determined. The West African region contributed 1528 (41%) of the sequences (Table 2). The sizes of the other regional groups ranged from 127 to 995. Overall, 40% of the sequences were present only once in the database or were found multiple times within a single ethnic group. In contrast, 24% of sequences were found in multiple ethnic groups from at least three geographical regions.
Table 1

Definition of geographic regions.

Geographical regions

Historical areas

Major inclusive countries

West

Senegambia

Senegal, Gambia, northern Guinea

 

Upper Guinea

Guinea, Sierra Leone, northwestern Liberia, parts of Mali

 

Gold Coast

Ghana, Burkina Faso

 

Bight of Benin

Western Nigeria, Benin

West Central

Bight of Bonny

Eastern Nigeria, western Cameroon

 

Central Africa

Angola, the Congos, Equatorial Guinea, Gabon

South

 

Namibia, South Africa

Southeast

Mozambique

Mozambique, western Malagasy

East

 

Tanzania, Kenya, Uganda, Rwanda, Burundi, Ethiopia, Somalia, southern Sudan

North

Magrib

Morocco, Algeria, Spanish Sahara, Mauritania, Tunisia, Libya, Egypt, northern Sudan

Figure 2

Map depicting the geographic locations and the regional groupings of the population samples used in this study.

Table 2

Characteristics of the sub-Saharan mtDNA HVS-I database.

Region

Region matched (%)

 

Total

Uniquea

Multipleb

West

West Central

South

Southeast

East

West

1528

35

20

24

19

0

1

1

West Central

995

37

28

15

13

0

5

2

South

127

61

15

0

0

21

2

0

Southeast

416

25

51

1

15

1

7

0

East

659

59

12

1

2

0

0

27

Total

3725

40

24

     

aHaplotypes found once or in a single ethnic group.

bHaplotypes found in ethnic groups from three or more regions.

Two of the regional groupings, East and South, had an excess of sequences that were found in a single ethnic group, and a corresponding deficit of matches to sequences from multiple regions. This result is consistent with the idea that these two regions are dominated by samples that have low levels of the mtDNA haplotypes that are characteristic of the Bantu [4, 5]. In contrast, the majority of mtDNA sequences from Mozambique in the Southeast region match sequences from multiple regions, and only a small percentage of these sequences are unique to ethnic groups from Mozambique, perhaps reflecting the fact that only Bantu speakers were sampled [5, 6]. In support of this idea, most matches that include sequences from only two regions involve the West Central region that is believed to have been the original Bantu homeland [7].

Comparison of African-American samples with the sub-Saharan databases

Two African-American samples, a sample of African Americans who self-identified as Gullah/Geechee and a sample of African-American DNAs obtained from the Armed Forces DNA Identification Laboratory (AFDIL), were compared with both the original and the expanded databases to provide a sense of how increasing the database size impacts the distribution of exact matches. The Gullah/Geechee people are an African-American microethnic group residing in the Georgia/South Carolina Lowcountry and coastal islands whose numbers are now estimated between 200,000 and 500,000 in the Sea Islands of South Carolina, Georgia, North Florida, and beyond [8]. Gullah/Geechee language and culture include unique practices and artefacts (e.g., coiled basketry, Brer Rabbit stories, praise houses) including a distinct linguistic style with roots among the Mende peoples of Sierra Leone, West Africa. When a sample of 74 Gullah/Geechee mtDNA sequences was compared with the sub-Saharan database, approximately half of the mtDNAs were identical to two or more mtDNAs in the database and only seven mtDNAs matched mtDNAs from a single ethnic group (Table 3). The remaining 28 mtDNAs were not identical to any sequence in the expanded database.
Table 3

Number of perfect matches to African-American HVS-I sequences.

Number of matched ethnic groups

Sample

 

Gullah/Geechee

AFDIL

None

28

39

1

7

9

2–3

6

6

4–9

8

13

>9

25

30

Totals

74

97

Similar results were obtained when the 97 African-American AFDIL mtDNAs were compared with the databases. Approximately half (49) of the mtDNAs were identical to multiple sequences in the original database (Table 3). As with the Gullah/Geechee sample, fewer than 10% of the sequences matched a sequence from a single ethnic group, and 40% of the sequences did not have any perfect match in the database.

When the unmatched AFDIL and Gullah/Geechee mtDNAs were combined and analyzed further, 63% differed from a database sequence at a single nucleotide position (Table 4). Nearly three-quarters of these imperfect matches were to sequences that were found in multiple ethnic groups. Thus, most of the imperfect matches appear to be derived from the common haplotypes by a single mutational event.
Table 4

Imperfect matches to the Gullah/Geechee and AFDIL African-American HVS-I sequences.

 

Number of sequences

Number of ethnic groups matched

Number of sequences

1 mismatch

42

1

12

  

2–3

5

  

4–9

15

  

>9

10

>1 mismatch

25

 

ND

Geographical distribution of database matches

The majority of African-American mtDNAs that were identical to database mtDNAs matched mtDNAs from ethnic groups that were scattered throughout sub-Saharan Africa. However, 41% of the Gullah/Geechee and 37% of the AFDIL mtDNAs that matched database sequences were identical to mtDNAs found only in western (West plus West Central) Africa (Table 5). Only one Gullah/Geechee mtDNA and one AFDIL mtDNA matched mtDNAs that are found exclusively in eastern Africa in the sub-Saharan database. This distribution of matches is consistent with the historical information that most North American slaves were originally from western Africa. Most of the single region matches to both the Gullah/Geechee and the AFDIL mtDNAs occurred with West African samples (Table 6). This result is consistent with the historical records indicating that West Africa was a major source of American slaves, but it also probably reflects the fact that the West African samples made up 41% of the expanded database. Surprisingly, five AFDIL mtDNAs matched only mtDNAs from the two Angolan samples that make up 4% of the database. This result is consistent with historical records indicating that a large proportion of the enslaved Africans brought to the Americas came from the West Central African region of Angola/Congo region, and suggests that ethnic groups in this region of Africa need to be sampled more extensively.
Table 5

Geographical source of mtDNA HVS-I matches.

Number of matches

Gullah/Geechee individuals

AFDIL African-American individuals

 

W. Africa

E. Africa

Both

W. Africa

E. Africa

Both

1–5

14

1

2

16

1

2

>5

5

0

24

5

0

33

Table 6

Distribution of single region matches.

Sample

West

W. Central

East

Gullah/Geechee

9

4

1

AFDL AA

7

3

1

Language group comparisons

Considering Africa's geographical size and population density, and the duration of human residence on this continent, linguistic diversity at the taxonomic level of family is amazing low. This low level of linguistic diversity is probably the consequence of protracted mobility and interaction among Africa's indigenous groups, facilitated by the longstanding presence of such organized political-social units as kingdoms and empires and such sociocultural practices as polygamy.

Among the AFDIL sequences with more than five matches to various African ethnic groups, most language diversity was within the various subfamilies of the Niger-Congo family. These subfamiliesinclude Atlantic Congo (e.g., the ethnic groups Fula, Yoruba, Wolof, Balanta) and Mande (e.g., the ethnic groups Mandingo, Mende, Bambara). However, in some of the sequence matches, different linguistic families were represented altogether, including the Afro-Asiatic (e.g., the Tuareg ethnic group) and Nilo-Saharan (e.g., the Dinka ethnic group) families, along with members of the Niger-Congo family.

The most extensive pan-African haplotype (16189 16192 16223 16278 16294 16309 16390) is in the L2a1 haplogroup. This sequence is observed in West Africa among the Niger-Congo family including the Malinke, Wolof, and others; in North Africa among the Afro-Asiatic family including the Hausa and others; in Central Africa among the Niger-Congo family including the Bamileke and others; in South Africa among the Khoisan family including the Khwe and the Niger-Congo family Bantu speakers; and in East Africa among the Niger-Congo family Kikuyu. Closely related variants are observed among the Afro-Asiatic family including the Tuareg in North and West Africa and among the East African Nilo-Saharan family Dinka. Thus, identical mitochondrial haplotypes are often shared among ethnic groups with considerable language diversity.

Discussion

Because only a small fraction of the sub-Saharan African ethnic groups have been sampled, and there are parts of sub-Saharan Africa that are poorly represented in our database (Figure 2), our database cannot be considered a representative subset of the sub-Saharan mtDNA gene pool. Nevertheless, it is clear that a much larger database is needed since 40% of the African-American samples analyzed have no exact match in our database. The extensive sharing of mtDNA haplotypes among ethnic groups from different regions of Africa is consistent with the historical evidence of extensive migration and mixing of African ethnic groups. Indeed, the well-documented Bantu migrations appear to have had a major impact [4], as have the formation of the historic empires and kingdoms of the region (such as the historic empires of Ghana, Mali, and the Songhai, Bakongo, and Ashanti Kingdoms). Despite the limitations of our database of sub-Saharan mtDNA sequences, it is likely that we have identified the most common haplotypes found in this region. Some are found throughout the region that includes the Bantu migrations, and others are found primarily in either the western or the eastern parts of the continent. We intend to continue to increase the size of our database, because a significantly larger database would provide more information about haplotypes that are present at lower frequencies than the most common haplotypes. Some of these lower-frequency haplotypes are likely to be shared among widely distributed ethnic groups, while others may have a more localized distribution.

Another way to assess our sub-Saharan mtDNA database would be to see how well African-American mtDNAs match database sequences. Historical accounts of the trans-Atlantic slave trade indicate that most North American slaves came from the western coast of Africa, including the geographical regions from present-day Angola to Senegal. When African-American mitochondrial DNA HVS-I sequences were studied, nearly half were identical to those from two or more African ethnic groups in our expanded database. Furthermore, the average number of perfect matches per matching African-American mtDNA increased from 3.6 different ethnic groups to 6.1 different ethnic groups when the size of the database was increased by 53% to its present size of 3725 sequences. These results reflect the fact that approximately half the mtDNA sequences in our sub-Saharan database are shared by members of three or more ethnic groups.

In both of the African-American samples, approximately 40% of the mtDNA sequences did not match any sequence in any other ethnic group (Table 3). However, more than half of these sequences differed from multiple database sequences at a single position (Table 4). Because it is unlikely that more than a few of these differences result from new mutations that occurred in North America or that more than a few lineages went extinct in Africa after being introduced to the new world, this result suggests that only a small fraction of the mtDNA diversity present in sub-Saharan Africa has been sampled, and that much of the unsampled diversity is due to single mutations that have occurred in the common haplotypes.

Many African Americans are interested in learning more about their African roots and are willing to pay to have their mtDNA analyzed in the hope that it will match DNA from a particular African ethnic group. However, as more than half of the mtDNA sequences in the African database are identical to sequences from other ethnic groups, African-American mtDNAs will be much more likely to match sequences from multiple ethnic groups than sequences from a single ethnic group. When this result is coupled with the fact that 40% of African-American mtDNAs did not match any sequence in the database, it is clear that matches to a single African ethnic group will not be the outcome for most African Americans, and even when a match to a single ethnic group is obtained, multiple matches may occur in a larger database. Furthermore, for the typical African American, the maternal ancestor who was the source of the mtDNA was just one of hundreds of enslaved African ancestors. In fact, it likely that there has been more mixing of African ethnic groups in the Americas than has ever occurred elsewhere. Thus, the ancestors of virtually all contemporary African Americans came from a large number of ethnic groups located throughout the region from Senegal to Angola.

Conclusion

Half of the sub-Saharan mtDNA sequences in our database are common haplotypes that are shared among ethnic groups from multiple regions of sub-Saharan Africa. The finding that fewer than 10% of African-American mtDNAs matched mtDNA sequences from a single African region suggests that as few as one in nine African Americans may be able to trace their mtDNA lineage to a particular region of Africa. However, no firm conclusions should be made until a much larger database is available. It is clear, however, that nearly half of contemporary African-American mtDNAs are identical to African haplotypes that are found in multiple ethnic groups throughout sub-Saharan Africa. For these mtDNAs, it is impossible to use only mtDNA sequence information to determine which single ethnic group was the source of the maternal ancestor.

Methods

African-American samples

A sample of 78 African Americans who self-identified as Gullah/Geechee was generated by our laboratories from unrelated people sampled in the coastal areas of South Carolina and Georgia using either cheek swabs or mouthwash to collect buccal cells. DNA was isolated using a BuccalAmp DNA Extraction Kit (Epicentre, Madison, WI) for the cheek swabs or a DNAzol procedure (Molecular Research Center, Cincinnati, OH) for the mouthwash samples. The HVS-I region was amplified and sequenced as described previously [3]. Those mtDNAs with non-African haplotypes, three with Native American haplotypes (two haplotype B and 1 haplotype A2) and one with European mtDNA (haplotype H) were excluded from further analysis (Table 9). A second sample of 104 African-American mtDNA sequences was obtained from Tom Parsons at the Armed Forces DNA Identification Laboratory. In this sample, mtDNAs with non-African haplotypes (five haplotype H, one haplotype J, and one haplotype U4) were excluded.
Table 9

Gullah/Geechee mitochondrial DNA HVS-I sequences included in this study.

ID

Number

Hg

HvI polymorphisms

G299

1

A2

111 154 223 290 319 362

G211

2

B

93 182 183 189 217

RP22

1

K or H

189 265 311

G110

1

L0a1

129 148 168 172 187 188G 189 223 230 311 320

G207

1

L0a1

129 148 168 172 187 188G 189 223 230 293 320

G252

1

L1b1

114A 126 187 189 223 234 239 264 270 278 293 311

RP74

2

L1b1

126 187 189 223 264 270 278 293 311

RP287

1

L1b1

093 111 126 187 189 223 239 270 278 293 311 360

RP290

1

L1b1

111 126 187 189 223 239 270 278 293 311

RP93

1

L1b

126 189 223 264 270 278 311

RP291

1

L1c1a

129 187 189 223 274 278 293 294 311 360

RP25

3

L1c2

078 129 187 189 223 265C 286A 294T 311 320 360

G114

1

L1c

086 129 172 184 187 189 223 261 278 290 311 360

G124

1

L2a

183C 185 189 192 223 278 292 293 294 390

RP293

1

L2a

189 192 223 265 270 278 294 390

G260

1

L2a

189 192 223 278 294 390

RP313

1

L2a1

172 223 278 286 294 309 390

G158

1

L2a1

189 192 223 278 294 309 390

RP53

1

L2a1a

223 278 286 294 309 390

G326

1

L2a1a/b

092 223 278 286 290 294 309 327 390

G323

2

L2b

114A 129 212 213 223 278 390

G233

1

L2b

114A 129 213 223 274 278 390

G126

1

L2b

114A 129 213 223 278 390

G146

1

L2c

(A ins at 149) 207 223 242 278 390

RP94

1

L2c

051 223 278 390

G334

1

L2c

214 223 278 390

G349

1

L2c

214 223 278 390

RP298

1

L2c

223 278 311 390

G174

1

L2c

223 278 390

RP24

1

L2c

223 278 390

RP286

1

L2c2

223 264 278 390

G277

1

L2c2

148 264 278 311 390

G280

1

L2d1

093 129 172 189 207 278 300 354 390

RP59

1

L2d2

111A 145 184 223 239 278 292 311 355 390 399 400

RP26

1

L3b

124 182 183 189 223 278 362

G178

2

L3b

124 223 278 355 362

G173

1

L3b

124 223 278 362

G244

1

L3b2

124 223 278 311 362

G269

1

L3d

124 223

RP292

2

L3d

124 223 362

RP306

1

L3d3

051 124 223 278 304 311

RP295

2

L3e1

179 223 327

RP308

1

L3e1

207 223 327

G313

1

L3e1

223 327

RP302

1

L3e1

223 327 360

G337

1

L3e2

223 258 320

G172

2

L3e2

223 294 320

RP14

1

L3e2

223 320

G339

1

L3e2

223 320 399

G266

1

L3e2b

172 183C 189 223 278 320

G122

5

L3e2b

172 183C 189 223 320

RP28

2

L3e2b

172 189 223 320

RP45

1

L3e2b

189 223 320

G222

1

L3e3

093 223 265T

RP35

1

L3e3

189 223 265T 311

G199

2

L3e3

223 265T

G223

1

L3e4

051 093 209 223 264 320

RP294

1

L3f

209 223 311

G206

1

L3f1

129 209 223 292 295 311

G195

1

L3f1

129 209 223 292 295 311 368

G164

1

L3f1

129 209 223 292 311

G108

2

L3f1

209 223 292 311

Total

78

  

Database assembly

A database of 3725 mtDNA HVS-I sequences from people living in sub-Saharan Africa was assembled from the published literature in October 2005 (Table 7) with the addition of 80 new mtDNA sequences from people belonging to the Malinke and Bambara ethnic groups in Mali (Table 8). DNA from these latter samples was isolated using a BuccalAmp DNA Extraction Kit (Epicentre, Madison, WI) from cheek swabs obtained from unrelated volunteers. MtDNA HVS-I sequences from two African-American population samples were then compared with these databases to determine how often individual HVS-I sequences are identical to African HVS-I sequences in the databases. For these comparisons, only sequences from 16030 to 16420 were considered, and both insertions and differences at positions 16182 and 16183 were ignored. In addition, a change to 16390A was inferred for all L2 haplogroup sequences that did not include this mutation. No attempt was made to correct any other errors that might be present among the published sequences. However, the presence of sequencing errors would have the effect of reducing the incidence of perfect matches so that the frequencies of perfect matches we observe should be considered minimum estimates. Matches to multiple individuals within an African ethnic group were considered a single match. Sequences included in the databases are available from Bert Ely.
Table 7

Mitochondrial DNA HVS-I sequences included in this study.

Ethnic group

Country

Sample size

Reference

West Africa

Multiple

Senegal

50

Rando et al, 1998 [9]

Serer

Senegal

23

Rando et al, 1998 [9]

Wolof

Senegal

48

Rando et al, 1998 [9]

Mandenka

Senegal

110

Graven et al, 1995 [10]; Watson et al, 1997 [11]

Multiple groups

Guiné-Bissau

372

Rosa et al, 2004 [12]

Malinke

Mali

61

Ely et al, unpublished

Bambara

Mali

19

Ely et al, unpublished

Limba

Sierra Leone

67

Jackson et al, 2005 [3]

Loko

Sierra Leone

29

Jackson et al, 2005 [3]

Temne

Sierra Leone

121

Jackson et al, 2005 [3]

Mende

Sierra Leone

59

Jackson et al, 2005 [3]

Unknown group(s)

Sierra Leone

117

Monson et al, 2002 [13]

Fulbe

Nigeria, Niger

60

Watson et al, 1997 [11]

Hausa

Nigeria, Niger

20

Watson et al, 1997 [11]

Kanuri

Nigeria, Niger

14

Watson et al, 1997 [11]

Songhai

Nigeria, Niger

10

Watson et al, 1997 [11]

Tuareg

Nigeria, Niger

23

Watson et al, 1997 [11]

Yoruba

Nigeria

33

Vigilant et al, 1991 [14]; Watson et al, 1997 [11]

Unknown group(s)

Cabo Verde

292

Brehm et al, 2002 [15]

Total

 

1528

 

West Central Africa

Kotoko

Cameroon

18

Èerný et al, 2004 [16]

Hide

Cameroon

23

Èerný et al, 2004 [16]

Masa

Cameroon

31

Èerný et al, 2004 [16]

Mafa

Cameroon

32

Èerný et al, 2004 [16]

Bakaka

Cameroon

50

Coia et al, 2005 [17]

Bamileke

Cameroon

48

Coia et al, 2005 [17]

Bassa

Cameroon

46

Coia et al, 2005 [17]

Daba

Cameroon

20

Coia et al, 2005 [17]

Ewondo

Cameroon

53

Coia et al, 2005 [17]

Fali

Cameroon

41

Coia et al, 2005 [17]

Fulbe

Cameroon

34

Coia et al, 2005 [17]

Mandara

Cameroon

37

Coia et al, 2005 [17]

Podokwo

Cameroon

39

Coia et al, 2005 [17]

Tali

Cameroon

20

Coia et al, 2005 [17]

Tupuri

Cameroon

25

Coia et al, 2005 [17]

Uldeme

Cameroon

28

Coia et al, 2005 [17]

Biaka

Central African Republic

17

Vigilant et al, 1991 [14]; Watson et al, 1997 [11]

Mbenzele-Pygmy

Central African Republic

57

Destro-Bisol et al, 2004 [18]

Angolares

São Tomé and Príncipe

30

Trovoada et al, 2004 [19]

Forros

São Tomé and Príncipe

35

Trovoada et al, 2004 [19]

Tongas

São Tomé and Príncipe

38

Trovoada et al, 2004 [19]

Unknown group(s)

São Tomé and Príncipe

50

Mateu et al, 1997 [20]

Bubi

Equatorial Guinea

45

Mateu et al, 1997 [20]

Fang

Equatorial Guinea

11

Pinto et al, 1996 [21]

Mbuti

Democratic Republic of Congo

13

Vigilant et al, 1991 [14]; Watson et al, 1997 [11]

Bantu-speaking

Cabinda

110

Beleza et al, 2005 [4]

Mbundu

Angola

44

Plaza et al, 2004 [22]

Total

 

995

 

East Africa

Nuer

South Sudan

11

Krings et al, 1999 [23]

Dinka

South Sudan

47

Krings et al, 1999 [23]

Shilluk

South Sudan

7

Krings et al, 1999 [23]

Multiple groups

Ethiopia

21

Kivisild et al, 2004 [24]

Tigrais

Ethiopia, Eritrea

53

Kivisild et al, 2004 [24]

Gurage

Ethiopia

21

Kivisild et al, 2004 [24]

Afar

Ethiopia

16

Kivisild et al, 2004 [24]

Amhara

Ethiopia

120

Kivisild et al, 2004 [24]

Amhara

Ethiopia

7

Quintana-Murci et al, 1999 [25]

Oromo

Ethiopia

33

Kivisild et al, 2004 [24]

Oromo

Kenya, Ethiopia

18

Quintana-Murci et al, 1999 [25]

Unknown group(s)

Kenya

100

Brandstätter et al, 2004 [26]

Kikuyu

Kenya

24

Watson et al, 1997 [11]

Turkana

Kenya

37

Watson et al, 1997 [11]

Somali

Kenya, Somalia, Ethiopia

27

Watson et al, 1997 [11]

Hadza

Tanzania

17

Vigilant et al, 1991 [14]

Hadza

Tanzania

49

Knight et al, 2003 [27]

Dakota

Tanzania

18

Knight et al, 2003 [27]

Iraqw

Tanzania

12

Knight et al, 2003 [27]

Sukuma

Tanzania

21

Knight et al, 2003 [27]

Total

 

659

 

Southeast Africa

Multiple groups

Mozambique

109

Pereira et al, 2001 [6]

Multiple groups

Mozambique

307

Salas et al, 2002 [5]

Total

 

416

 

South Africa

!Kung

Botswana

34

Vigilant et al, 1991 [14]

!Kung

South Africa

43

Chen et al, 2000 [28]

Khwe

South Africa

31

Chen et al, 2000 [28]

Herero

Bostwana, Namibia

19

Vigilant et al, 1991 [14]

Total

 

127

 
Table 8

Malinke and Bambara mitochondrial DNA HVS-I sequences included in this study.

ID

Ethnicity

Haplogroup

Hvs-I polymorphismsa

BAM676

Bambara

L1b

126 187 189 223 264 270 278 311

BAM612

Bambara

L1b1

126 187 189 223 256 264 270 278 293 311

BAM595

Bambara

L1b1

126 187 189 223 264 266 270 278 293 311

BAM599

Bambara

L1b1

126 187 189 223 264 266 270 278 293 311

BAM600-2

Bambara

L1b1

126 187 189 223 264 270 278 293 311

BAM060

Bambara

L2a

223 278 294 368 390

BAM598

Bambara

L2a1

189 192 209 223 278 294 309 390

BAM604

Bambara

L2a1a

223 278 286 294 309 390

BAM627

Bambara

L2b

114A 213 223 278 290 355 390

BAM659

Bambara

L2b1

114A 129 213 223 278 362 390

BAM037

Bambara

L2c

129 223 261 278 390

BAM685

Bambara

L2c2

183 223 264 278 320 390

BAM679-1

Bambara

L2c2

223 264 278 390

BAM629

Bambara

L2d2

111A 145 184 223 239 278 292 355 390 399 400

BAM068

Bambara

L3b

124 223 278 362

BAM072

Bambara

L3e2

223 284 320

BAM605

Bambara

L3e3

093 148 223 265 311

BAM027

Bambara

L3f1

049 129 209 223 292 295 311

BAM614

Bambara

L3f1

223 272 292 311

BAM 552

Malinke

L1b

111 126 187 189 223 239 270 278 311

BAM 237

Malinke

L1b

126 187 189 223 239 264 270 278 311

BAM 357

Malinke

L1b

126 187 189 223 239 264 270 278 311

BAM 040

Malinke

L1b

126 187 189 223 264 270 278 311

BAM 385

Malinke

L1b1

093 126 145 187 189 223 264 270 278 293 311

BAM 555

Malinke

L1b1

126 187 189 213 223 260 264 270 278 293 311

BAM 225

Malinke

L1b1

126 187 189 223 264 270 278 293 311 362 400

BAM 407

Malinke

L1c

129 189 215 223 278 294 311 360

BAM 013

Malinke

L1c2

015 15 bp ins 129 187 189 223 265 286 294 311 360

BAM 397

Malinke

L2a

189 192 223 278 294 390

BAM 221

Malinke

L2a

189 223 278 294 390

BAM 426

Malinke

L2a

223 278 286 294 390

BAM 083

Malinke

L2a

223 278 294 390

BAM 414

Malinke

L2a1

093 189 192 223 265 278 294 309 390

BAM 143

Malinke

L2a1

086 223 230 278 294 309 390

BAM 117

Malinke

L2a1

092 223 278 294 309 390

BAM 341

Malinke

L2a1

093 223 278 294 309 390

BAM 534

Malinke

L2a1

140 189 192 223 278 294 309 390

BAM 665

Malinke

L2a1

189 192 223 266 278 294 309 390

BAM 082

Malinke

L2a1

189 192 223 278 294 309

BAM 174

Malinke

L2a1

192 223 278 294 309 390

BAM 195

Malinke

L2a1

192 223 278 294 309 390

BAM 395

Malinke

L2a1

223 278 294 309 368 390

BAM 406

Malinke

L2a1

223 278 294 309 390

BAM 204

Malinke

L2a1

223 278 309 390

BAM 296

Malinke

L2b1

056 114A 129 213 223 278 362 390

BAM 085

Malinke

L2b1

093 114A 129 213 223 278 355 362 390

BAM 577

Malinke

L2b1

114A 129 213 223 278 311 355 362 390

BAM 290

Malinke

L2b1

114A 129 213 223 278 362 390

BAM 319

Malinke

L2b1

114A 129 213 223 278 362 390

BAM 401

Malinke

L2c

129 223 261 278 362 390

BAM 631

Malinke

L2c

162 223 261 278 390

BAM 427

Malinke

L2c

223 278 362 390

BAM 652

Malinke

L2c

223 278 390

BAM 269

Malinke

L2c1

223 256 261 278 318 390

BAM 432

Malinke

L2c2

093 223 264 278 362 390

BAM 151

Malinke

L2c2

223 264 278 390

BAM 680

Malinke

L2c2

223 264 278 390

BAM 681

Malinke

L2c2

223 264 278 390

BAM 187

Malinke

L2d1

014 129 278 300 354 390 399

BAM 110

Malinke

L2d2

111A 145 184 223 239 278 292 355 360 390 399 400

BAM 463

Malinke

L3b

124 223 278

BAM 185

Malinke

L3b

124 223 278 362

BAM 420

Malinke

L3b

124 223 278 362

BAM 430

Malinke

L3b

124 223 278 362

BAM 384

Malinke

L3b1

223 278 362

BAM 461

Malinke

L3d

111 124 223

BAM 521

Malinke

L3d

111 124 223

BAM 160

Malinke

L3d

124 223

BAM 375

Malinke

L3e2

172 223 239 320

BAM 402

Malinke

L3e2

172 223 320 353

BAM 467

Malinke

L3e2

188 223

BAM 525

Malinke

L3e2

188 223 320

BAM 041

Malinke

L3e2

223 257 290A 320

BAM 464

Malinke

L3e2

223 320

BAM 260

Malinke

L3e2

223 320 362

BAM 070

Malinke

L3f1

157 209 223 274 292 304 311

BAM 398

Malinke

L3f1

188 209 223 292 311

BAM 116

Malinke

L3f1

209 223 274 292 311

BAM 061

Malinke

U5

189 192 270 320

BAM 047

Malinke

U5

189 192 270 320

aNumbers indicate the position of differences from the Cambridge Reference Sequence minus 16,000. All mutations are transitions unless a letter designation is present.

Notes

Declarations

Acknowledgements

The authors thank Dr. Ibrahima Seck for collecting the Malinke and Bambara samples, Alexis Labrie for performing the DNA extractions and the Malinke DNA sequence analysis, Ransford Opong for performing the Bambara DNA sequence analysis, and Jordan G. Rogers Celeste for expert editing of the manuscript. This work was supported in part by grants DBI-0097667 and DBI-0451403 from the National Science Foundation.

Authors’ Affiliations

(1)
Department of Biological Sciences, University of South Carolina, Columbia, USA
(2)
Biomedical Engineering and Biotechnology Program, University of Massachusetts, Lowell, USA
(3)
Department of Anthropology, University of Maryland, College Park, USA

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