Literature DB >> 17038170

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

Bert Ely1, Jamie Lee Wilson, Fatimah Jackson, Bruce A Jackson.   

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.

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Year:  2006        PMID: 17038170      PMCID: PMC1618861          DOI: 10.1186/1741-7007-4-34

Source DB:  PubMed          Journal:  BMC Biol        ISSN: 1741-7007            Impact factor:   7.431


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 regionsHistorical areasMajor inclusive countries
WestSenegambiaSenegal, Gambia, northern Guinea
Upper GuineaGuinea, Sierra Leone, northwestern Liberia, parts of Mali
Gold CoastGhana, Burkina Faso
Bight of BeninWestern Nigeria, Benin
West CentralBight of BonnyEastern Nigeria, western Cameroon
Central AfricaAngola, the Congos, Equatorial Guinea, Gabon
SouthNamibia, South Africa
SoutheastMozambiqueMozambique, western Malagasy
EastTanzania, Kenya, Uganda, Rwanda, Burundi, Ethiopia, Somalia, southern Sudan
NorthMagribMorocco, 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.

RegionRegion matched (%)

TotalUniqueaMultiplebWestWest CentralSouthSoutheastEast
West152835202419011
West Central99537281513052
South1276115002120
Southeast4162551115170
East6595912120027
Total37254024

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 groupsSample

Gullah/GeecheeAFDIL
None2839
179
2–366
4–9813
>92530
Totals7497
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 sequencesNumber of ethnic groups matchedNumber of sequences
1 mismatch42112
2–35
4–915
>910
>1 mismatch25ND

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 matchesGullah/Geechee individualsAFDIL African-American individuals

W. AfricaE. AfricaBothW. AfricaE. AfricaBoth
1–514121612
>550245033
Table 6

Distribution of single region matches.

SampleWestW. CentralEast
Gullah/Geechee941
AFDL AA731

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.

IDNumberHgHvI polymorphisms
G2991A2111 154 223 290 319 362
G2112B93 182 183 189 217
RP221K or H189 265 311
G1101L0a1129 148 168 172 187 188G 189 223 230 311 320
G2071L0a1129 148 168 172 187 188G 189 223 230 293 320
G2521L1b1114A 126 187 189 223 234 239 264 270 278 293 311
RP742L1b1126 187 189 223 264 270 278 293 311
RP2871L1b1093 111 126 187 189 223 239 270 278 293 311 360
RP2901L1b1111 126 187 189 223 239 270 278 293 311
RP931L1b126 189 223 264 270 278 311
RP2911L1c1a129 187 189 223 274 278 293 294 311 360
RP253L1c2078 129 187 189 223 265C 286A 294T 311 320 360
G1141L1c086 129 172 184 187 189 223 261 278 290 311 360
G1241L2a183C 185 189 192 223 278 292 293 294 390
RP2931L2a189 192 223 265 270 278 294 390
G2601L2a189 192 223 278 294 390
RP3131L2a1172 223 278 286 294 309 390
G1581L2a1189 192 223 278 294 309 390
RP531L2a1a223 278 286 294 309 390
G3261L2a1a/b092 223 278 286 290 294 309 327 390
G3232L2b114A 129 212 213 223 278 390
G2331L2b114A 129 213 223 274 278 390
G1261L2b114A 129 213 223 278 390
G1461L2c(A ins at 149) 207 223 242 278 390
RP941L2c051 223 278 390
G3341L2c214 223 278 390
G3491L2c214 223 278 390
RP2981L2c223 278 311 390
G1741L2c223 278 390
RP241L2c223 278 390
RP2861L2c2223 264 278 390
G2771L2c2148 264 278 311 390
G2801L2d1093 129 172 189 207 278 300 354 390
RP591L2d2111A 145 184 223 239 278 292 311 355 390 399 400
RP261L3b124 182 183 189 223 278 362
G1782L3b124 223 278 355 362
G1731L3b124 223 278 362
G2441L3b2124 223 278 311 362
G2691L3d124 223
RP2922L3d124 223 362
RP3061L3d3051 124 223 278 304 311
RP2952L3e1179 223 327
RP3081L3e1207 223 327
G3131L3e1223 327
RP3021L3e1223 327 360
G3371L3e2223 258 320
G1722L3e2223 294 320
RP141L3e2223 320
G3391L3e2223 320 399
G2661L3e2b172 183C 189 223 278 320
G1225L3e2b172 183C 189 223 320
RP282L3e2b172 189 223 320
RP451L3e2b189 223 320
G2221L3e3093 223 265T
RP351L3e3189 223 265T 311
G1992L3e3223 265T
G2231L3e4051 093 209 223 264 320
RP2941L3f209 223 311
G2061L3f1129 209 223 292 295 311
G1951L3f1129 209 223 292 295 311 368
G1641L3f1129 209 223 292 311
G1082L3f1209 223 292 311
Total78

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 groupCountrySample sizeReference
West Africa
MultipleSenegal50Rando et al, 1998 [9]
SererSenegal23Rando et al, 1998 [9]
WolofSenegal48Rando et al, 1998 [9]
MandenkaSenegal110Graven et al, 1995 [10]; Watson et al, 1997 [11]
Multiple groupsGuiné-Bissau372Rosa et al, 2004 [12]
MalinkeMali61Ely et al, unpublished
BambaraMali19Ely et al, unpublished
LimbaSierra Leone67Jackson et al, 2005 [3]
LokoSierra Leone29Jackson et al, 2005 [3]
TemneSierra Leone121Jackson et al, 2005 [3]
MendeSierra Leone59Jackson et al, 2005 [3]
Unknown group(s)Sierra Leone117Monson et al, 2002 [13]
FulbeNigeria, Niger60Watson et al, 1997 [11]
HausaNigeria, Niger20Watson et al, 1997 [11]
KanuriNigeria, Niger14Watson et al, 1997 [11]
SonghaiNigeria, Niger10Watson et al, 1997 [11]
TuaregNigeria, Niger23Watson et al, 1997 [11]
YorubaNigeria33Vigilant et al, 1991 [14]; Watson et al, 1997 [11]
Unknown group(s)Cabo Verde292Brehm et al, 2002 [15]
Total1528
West Central Africa
KotokoCameroon18Èerný et al, 2004 [16]
HideCameroon23Èerný et al, 2004 [16]
MasaCameroon31Èerný et al, 2004 [16]
MafaCameroon32Èerný et al, 2004 [16]
BakakaCameroon50Coia et al, 2005 [17]
BamilekeCameroon48Coia et al, 2005 [17]
BassaCameroon46Coia et al, 2005 [17]
DabaCameroon20Coia et al, 2005 [17]
EwondoCameroon53Coia et al, 2005 [17]
FaliCameroon41Coia et al, 2005 [17]
FulbeCameroon34Coia et al, 2005 [17]
MandaraCameroon37Coia et al, 2005 [17]
PodokwoCameroon39Coia et al, 2005 [17]
TaliCameroon20Coia et al, 2005 [17]
TupuriCameroon25Coia et al, 2005 [17]
UldemeCameroon28Coia et al, 2005 [17]
BiakaCentral African Republic17Vigilant et al, 1991 [14]; Watson et al, 1997 [11]
Mbenzele-PygmyCentral African Republic57Destro-Bisol et al, 2004 [18]
AngolaresSão Tomé and Príncipe30Trovoada et al, 2004 [19]
ForrosSão Tomé and Príncipe35Trovoada et al, 2004 [19]
TongasSão Tomé and Príncipe38Trovoada et al, 2004 [19]
Unknown group(s)São Tomé and Príncipe50Mateu et al, 1997 [20]
BubiEquatorial Guinea45Mateu et al, 1997 [20]
FangEquatorial Guinea11Pinto et al, 1996 [21]
MbutiDemocratic Republic of Congo13Vigilant et al, 1991 [14]; Watson et al, 1997 [11]
Bantu-speakingCabinda110Beleza et al, 2005 [4]
MbunduAngola44Plaza et al, 2004 [22]
Total995
East Africa
NuerSouth Sudan11Krings et al, 1999 [23]
DinkaSouth Sudan47Krings et al, 1999 [23]
ShillukSouth Sudan7Krings et al, 1999 [23]
Multiple groupsEthiopia21Kivisild et al, 2004 [24]
TigraisEthiopia, Eritrea53Kivisild et al, 2004 [24]
GurageEthiopia21Kivisild et al, 2004 [24]
AfarEthiopia16Kivisild et al, 2004 [24]
AmharaEthiopia120Kivisild et al, 2004 [24]
AmharaEthiopia7Quintana-Murci et al, 1999 [25]
OromoEthiopia33Kivisild et al, 2004 [24]
OromoKenya, Ethiopia18Quintana-Murci et al, 1999 [25]
Unknown group(s)Kenya100Brandstätter et al, 2004 [26]
KikuyuKenya24Watson et al, 1997 [11]
TurkanaKenya37Watson et al, 1997 [11]
SomaliKenya, Somalia, Ethiopia27Watson et al, 1997 [11]
HadzaTanzania17Vigilant et al, 1991 [14]
HadzaTanzania49Knight et al, 2003 [27]
DakotaTanzania18Knight et al, 2003 [27]
IraqwTanzania12Knight et al, 2003 [27]
SukumaTanzania21Knight et al, 2003 [27]
Total659
Southeast Africa
Multiple groupsMozambique109Pereira et al, 2001 [6]
Multiple groupsMozambique307Salas et al, 2002 [5]
Total416
South Africa
!KungBotswana34Vigilant et al, 1991 [14]
!KungSouth Africa43Chen et al, 2000 [28]
KhweSouth Africa31Chen et al, 2000 [28]
HereroBostwana, Namibia19Vigilant et al, 1991 [14]
Total127
Table 8

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

IDEthnicityHaplogroupHvs-I polymorphismsa
BAM676BambaraL1b126 187 189 223 264 270 278 311
BAM612BambaraL1b1126 187 189 223 256 264 270 278 293 311
BAM595BambaraL1b1126 187 189 223 264 266 270 278 293 311
BAM599BambaraL1b1126 187 189 223 264 266 270 278 293 311
BAM600-2BambaraL1b1126 187 189 223 264 270 278 293 311
BAM060BambaraL2a223 278 294 368 390
BAM598BambaraL2a1189 192 209 223 278 294 309 390
BAM604BambaraL2a1a223 278 286 294 309 390
BAM627BambaraL2b114A 213 223 278 290 355 390
BAM659BambaraL2b1114A 129 213 223 278 362 390
BAM037BambaraL2c129 223 261 278 390
BAM685BambaraL2c2183 223 264 278 320 390
BAM679-1BambaraL2c2223 264 278 390
BAM629BambaraL2d2111A 145 184 223 239 278 292 355 390 399 400
BAM068BambaraL3b124 223 278 362
BAM072BambaraL3e2223 284 320
BAM605BambaraL3e3093 148 223 265 311
BAM027BambaraL3f1049 129 209 223 292 295 311
BAM614BambaraL3f1223 272 292 311
BAM 552MalinkeL1b111 126 187 189 223 239 270 278 311
BAM 237MalinkeL1b126 187 189 223 239 264 270 278 311
BAM 357MalinkeL1b126 187 189 223 239 264 270 278 311
BAM 040MalinkeL1b126 187 189 223 264 270 278 311
BAM 385MalinkeL1b1093 126 145 187 189 223 264 270 278 293 311
BAM 555MalinkeL1b1126 187 189 213 223 260 264 270 278 293 311
BAM 225MalinkeL1b1126 187 189 223 264 270 278 293 311 362 400
BAM 407MalinkeL1c129 189 215 223 278 294 311 360
BAM 013MalinkeL1c2015 15 bp ins 129 187 189 223 265 286 294 311 360
BAM 397MalinkeL2a189 192 223 278 294 390
BAM 221MalinkeL2a189 223 278 294 390
BAM 426MalinkeL2a223 278 286 294 390
BAM 083MalinkeL2a223 278 294 390
BAM 414MalinkeL2a1093 189 192 223 265 278 294 309 390
BAM 143MalinkeL2a1086 223 230 278 294 309 390
BAM 117MalinkeL2a1092 223 278 294 309 390
BAM 341MalinkeL2a1093 223 278 294 309 390
BAM 534MalinkeL2a1140 189 192 223 278 294 309 390
BAM 665MalinkeL2a1189 192 223 266 278 294 309 390
BAM 082MalinkeL2a1189 192 223 278 294 309
BAM 174MalinkeL2a1192 223 278 294 309 390
BAM 195MalinkeL2a1192 223 278 294 309 390
BAM 395MalinkeL2a1223 278 294 309 368 390
BAM 406MalinkeL2a1223 278 294 309 390
BAM 204MalinkeL2a1223 278 309 390
BAM 296MalinkeL2b1056 114A 129 213 223 278 362 390
BAM 085MalinkeL2b1093 114A 129 213 223 278 355 362 390
BAM 577MalinkeL2b1114A 129 213 223 278 311 355 362 390
BAM 290MalinkeL2b1114A 129 213 223 278 362 390
BAM 319MalinkeL2b1114A 129 213 223 278 362 390
BAM 401MalinkeL2c129 223 261 278 362 390
BAM 631MalinkeL2c162 223 261 278 390
BAM 427MalinkeL2c223 278 362 390
BAM 652MalinkeL2c223 278 390
BAM 269MalinkeL2c1223 256 261 278 318 390
BAM 432MalinkeL2c2093 223 264 278 362 390
BAM 151MalinkeL2c2223 264 278 390
BAM 680MalinkeL2c2223 264 278 390
BAM 681MalinkeL2c2223 264 278 390
BAM 187MalinkeL2d1014 129 278 300 354 390 399
BAM 110MalinkeL2d2111A 145 184 223 239 278 292 355 360 390 399 400
BAM 463MalinkeL3b124 223 278
BAM 185MalinkeL3b124 223 278 362
BAM 420MalinkeL3b124 223 278 362
BAM 430MalinkeL3b124 223 278 362
BAM 384MalinkeL3b1223 278 362
BAM 461MalinkeL3d111 124 223
BAM 521MalinkeL3d111 124 223
BAM 160MalinkeL3d124 223
BAM 375MalinkeL3e2172 223 239 320
BAM 402MalinkeL3e2172 223 320 353
BAM 467MalinkeL3e2188 223
BAM 525MalinkeL3e2188 223 320
BAM 041MalinkeL3e2223 257 290A 320
BAM 464MalinkeL3e2223 320
BAM 260MalinkeL3e2223 320 362
BAM 070MalinkeL3f1157 209 223 274 292 304 311
BAM 398MalinkeL3f1188 209 223 292 311
BAM 116MalinkeL3f1209 223 274 292 311
BAM 061MalinkeU5189 192 270 320
BAM 047MalinkeU5189 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.

Authors' contributions

BE, JLW, BAJ participated in the assembly of the database. The database comparisons were performed by BE. All authors contributed to the interpretation of the data and the writing of the manuscript.
  25 in total

1.  Prehistoric and historic traces in the mtDNA of Mozambique: insights into the Bantu expansions and the slave trade.

Authors:  L Pereira; V Macaulay; A Torroni; R Scozzari; M J Prata; A Amorim
Journal:  Ann Hum Genet       Date:  2001-09       Impact factor: 1.670

2.  Mitochondrial portrait of the Cabo Verde archipelago: the Senegambian outpost of Atlantic slave trade.

Authors:  A Brehm; L Pereira; H-J Bandelt; M J Prata; A Amorim
Journal:  Ann Hum Genet       Date:  2002-01       Impact factor: 1.670

3.  The making of the African mtDNA landscape.

Authors:  Antonio Salas; Martin Richards; Tomás De la Fe; María-Victoria Lareu; Beatriz Sobrino; Paula Sánchez-Diz; Vincent Macaulay; Angel Carracedo
Journal:  Am J Hum Genet       Date:  2002-10-22       Impact factor: 11.025

4.  Pattern of mtDNA variation in three populations from São Tomé e Príncipe.

Authors:  M J Trovoada; L Pereira; L Gusmão; A Abade; A Amorim; M J Prata
Journal:  Ann Hum Genet       Date:  2004-01       Impact factor: 1.670

5.  MtDNA profile of West Africa Guineans: towards a better understanding of the Senegambia region.

Authors:  Alexandra Rosa; António Brehm; Toomas Kivisild; Ene Metspalu; Richard Villems
Journal:  Ann Hum Genet       Date:  2004-07       Impact factor: 1.670

6.  The analysis of variation of mtDNA hypervariable region 1 suggests that Eastern and Western Pygmies diverged before the Bantu expansion.

Authors:  Giovanni Destro-Bisol; Valentina Coia; Ilaria Boschi; Fabio Verginelli; Alessandra Cagliá; Vincenzo Pascali; Gabriella Spedini; Francesc Calafell
Journal:  Am Nat       Date:  2004-01-16       Impact factor: 3.926

7.  Brief communication: mtDNA variation in North Cameroon: lack of Asian lineages and implications for back migration from Asia to sub-Saharan Africa.

Authors:  Valentina Coia; Giovanni Destro-Bisol; Fabio Verginelli; Cinzia Battaggia; Ilaria Boschi; Fulvio Cruciani; Gabriella Spedini; David Comas; Francesc Calafell
Journal:  Am J Phys Anthropol       Date:  2005-11       Impact factor: 2.868

8.  mtDNA variation in the South African Kung and Khwe-and their genetic relationships to other African populations.

Authors:  Y S Chen; A Olckers; T G Schurr; A M Kogelnik; K Huoponen; D C Wallace
Journal:  Am J Hum Genet       Date:  2000-03-28       Impact factor: 11.025

9.  Genetic evidence of an early exit of Homo sapiens sapiens from Africa through eastern Africa.

Authors:  L Quintana-Murci; O Semino; H J Bandelt; G Passarino; K McElreavey; A S Santachiara-Benerecetti
Journal:  Nat Genet       Date:  1999-12       Impact factor: 38.330

10.  African Y chromosome and mtDNA divergence provides insight into the history of click languages.

Authors:  Alec Knight; Peter A Underhill; Holly M Mortensen; Lev A Zhivotovsky; Alice A Lin; Brenna M Henn; Dorothy Louis; Merritt Ruhlen; Joanna L Mountain
Journal:  Curr Biol       Date:  2003-03-18       Impact factor: 10.834

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  13 in total

1.  Inferring genetic ancestry: opportunities, challenges, and implications.

Authors:  Charmaine D Royal; John Novembre; Stephanie M Fullerton; David B Goldstein; Jeffrey C Long; Michael J Bamshad; Andrew G Clark
Journal:  Am J Hum Genet       Date:  2010-05-14       Impact factor: 11.025

2.  Genome-wide ancestry of 17th-century enslaved Africans from the Caribbean.

Authors:  Hannes Schroeder; María C Ávila-Arcos; Anna-Sapfo Malaspinas; G David Poznik; Marcela Sandoval-Velasco; Meredith L Carpenter; José Víctor Moreno-Mayar; Martin Sikora; Philip L F Johnson; Morten Erik Allentoft; José Alfredo Samaniego; Jay B Haviser; Michael W Dee; Thomas W Stafford; Antonio Salas; Ludovic Orlando; Eske Willerslev; Carlos D Bustamante; M Thomas P Gilbert
Journal:  Proc Natl Acad Sci U S A       Date:  2015-03-09       Impact factor: 11.205

3.  Genetic assessment of an isolated endemic Samango monkey (Cercopithecus albogularis labiatus) population in the Amathole Mountains, Eastern Cape Province, South Africa.

Authors:  M Thabang Madisha; Desire L Dalton; Raymond Jansen; Antoinette Kotze
Journal:  Primates       Date:  2017-10-27       Impact factor: 2.163

4.  African mitochondrial haplogroup L7: a 100,000-year-old maternal human lineage discovered through reassessment and new sequencing.

Authors:  Paul A Maier; Göran Runfeldt; Roberta J Estes; Miguel G Vilar
Journal:  Sci Rep       Date:  2022-06-24       Impact factor: 4.996

5.  Characterizing the admixed African ancestry of African Americans.

Authors:  Fouad Zakharia; Analabha Basu; Devin Absher; Themistocles L Assimes; Alan S Go; Mark A Hlatky; Carlos Iribarren; Joshua W Knowles; Jun Li; Balasubramanian Narasimhan; Steven Sidney; Audrey Southwick; Richard M Myers; Thomas Quertermous; Neil Risch; Hua Tang
Journal:  Genome Biol       Date:  2009-12-22       Impact factor: 13.583

6.  Mitochondrial DNA diversity in the African American population.

Authors:  Derek C Johnson; Sadeep Shrestha; Howard W Wiener; Robert Makowsky; Ashish Kurundkar; Craig M Wilson; Brahim Aissani
Journal:  Mitochondrial DNA       Date:  2013-10-09

7.  VKORC1 Asp36Tyr geographic distribution and its impact on warfarin dose requirements in Egyptians.

Authors:  Mohamed Hossam A Shahin; Larisa H Cavallari; Minoli A Perera; Sherief I Khalifa; Anne Misher; Taimour Langaee; Shitalben Patel; Kimberly Perry; David O Meltzer; Howard L McLeod; Julie A Johnson
Journal:  Thromb Haemost       Date:  2013-03-21       Impact factor: 5.249

8.  The imprint of the Slave Trade in an African American population: mitochondrial DNA, Y chromosome and HTLV-1 analysis in the Noir Marron of French Guiana.

Authors:  Nicolas Brucato; Olivier Cassar; Laure Tonasso; Patricia Tortevoye; Florence Migot-Nabias; Sabine Plancoulaine; Evelyne Guitard; Georges Larrouy; Antoine Gessain; Jean-Michel Dugoujon
Journal:  BMC Evol Biol       Date:  2010-10-19       Impact factor: 3.260

9.  Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure.

Authors:  Tulaya Limpiti; Apichart Intarapanich; Anunchai Assawamakin; Philip J Shaw; Pongsakorn Wangkumhang; Jittima Piriyapongsa; Chumpol Ngamphiw; Sissades Tongsima
Journal:  BMC Bioinformatics       Date:  2011-06-23       Impact factor: 3.169

10.  Y chromosome lineages in men of west African descent.

Authors:  Jada Benn Torres; Menahem B Doura; Shomarka O Y Keita; Rick A Kittles
Journal:  PLoS One       Date:  2012-01-25       Impact factor: 3.240

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