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Human mtDNA hypervariable regions, HVR I and II, hint at deep common maternal founder and subsequent maternal gene flow in Indian population groups

Abstract

We have analysed the hypervariable regions (HVR I and II) of human mitochondrial DNA (mtDNA) in individuals from Uttar Pradesh (UP), Bihar (BI) and Punjab (PUNJ), belonging to the Indo-European linguistic group, and from South India (SI), that have their linguistic roots in Dravidian language. Our analysis revealed the presence of known and novel mutations in both hypervariable regions in the studied population groups. Median joining network analyses based on mtDNA showed extensive overlap in mtDNA lineages despite the extensive cultural and linguistic diversity. MDS plot analysis based on Fst distances suggested increased maternal genetic proximity for the studied population groups compared with other world populations. Mismatch distribution curves, respective neighbour joining trees and other statistical analyses showed that there were significant expansions. The study revealed an ancient common ancestry for the studied population groups, most probably through common founder female lineage(s), and also indicated that human migrations occurred (maybe across and within the Indian subcontinent) even after the initial phase of female migration to India.

Introduction

The distribution of human genetic diversity has long been a subject of interest, and it has important implications for human evolution, forensics, and the distribution of genetic diseases in populations. Genetic diversity in human populations is low relative to that in many other species, attesting to the recent origin and small size of the ancestral human population (Li and Sadler 1991; Crouau-Roy et al 1996; Kaessmann et al 1999). Since the seminal study of Cann et al (1987), mitochondrial DNA (mtDNA) data have proven to be extremely useful for studying human evolution, including prehistoric migrations and demographic events such as sudden population expansions or extreme bottlenecks (Sherry et al 1994).

The human mtDNA is a closed circular genome of ~16.5 kb in length (Anderson et al 1981), which includes a 1.1 kb-long noncoding (control) region that represents a highly variable sequence (Greenberg et al 1983; Melton et al 1997). The variable sites in the control regions, hypervariable region I (HVR I) and hypervariable region II (HVR II), each ~400 bp, correspond to the origin of replication and the D-loop. Since mtDNA is maternally inherited, exists in a high copy number (1,000–10,000 copies) in each cell, and is rapidly evolving (5–10 times faster than nuclear DNA), sequence polymorphism of the mtDNA has proved useful in the fields of population and evolution study (Gresham et al 2001; Ingman and Gyllensten 2001; Roychoudhury et al 2001; Yao et al 2002; Kivisild et al 1999; Metspalu et al 2004; Forster and Matsumura 2005; Thangaraj et al 2005; Macaulay et al 2005), anthropology (Derbeneva et al 2002; Houck and Budowle 2002; Koyama et al 2002; Yao and Zhang 2002) and forensic science (Budowle et al 2002; Seo et al 2002).

India comprises one of the largest ethnic populations, with more than 1 billion people drawn from diverse cultures, languages and geographical backgrounds. A number of studies have provided some insights into the maternal genetic structure of Indian populations (Bamshad et al 2001; Kaur et al 2002; Basu et al 2003; Kivisild et al 2003; Rajkumar and Kashyap 2003; Metspalu et al 2004; Palanichamy et al 2004; Rajkumar et al 2005; Thangaraj et al 2005). However, more studies are required to add to the pool of information and to help us to better understand the genetic structures of diverse Indian population groups, where many questions remain unanswered. The present preliminary work proposed to analyse the nature of the variations in hypervariable regions (HVR I and II) and perform phylogenetic analyses on individuals from Uttar Pradesh (UP), Bihar (BI) and Punjab (PUNJ), belonging to the Indo-European linguistic group, and individuals from South India (SI), that have their linguistic roots in the Dravidian language, in order to derive the structures of founder female lineages for these regions in India. We have also focused on providing an overview of the maternal gene pool, regional maternal population expansion time/patterns and their phylogenetic relationships with each other and other world populations.

Materials and methods

Subjects

Blood samples were collected (after seeking the required consent) in RBC lysis buffer from unrelated healthy donors from different population groups of India. One hundred eleven samples were collected, which belonged to: UP (n=33), BI (n=26), PUNJ (n=35) and SI (n=17). Genomic DNA was isolated following the routine protocol of Kunkel et al (1977).

Amplification of mtDNA

PCR amplifications of mtDNA regions—HVR I, for a total of 111 individuals, by a designed primer set AB-6F (5′-ACC CAA TCC ACA TCA AAA CC-3′) and AB-6R (5′-TCA AGG GAC CCC TAT CTG AG-3′) and HVR-II, for 87 individuals, by designed primer set F (5′-GGT CTA TCA CCC TAT TAA CCA C-3′) and R (5′-CTG TTA AAA GTG CAT ACC GCC A-3′)—were performed in 12.5 μl reaction volume mix containing 50 ng of template DNA, 6.25 pmol of each primer, 200 μM of dNTPs, 1.5 mM MgCl2, 1× reaction buffer and 0.3 U of Taq pol enzyme (Bangalore Genei, India). The cycle used was denaturation at 94 °C for 1 min, followed by annealing at 62 °C for 1 min, and then extension at 72 °C for 1 min, repeated for 30 cycles followed by a final extension step at 72 °C for 5 min. PCR products were initially checked in 2% agarose gel and then sequenced (using an ABI 3100 sequencer, USA). The sequences obtained were compared with the revised Cambridge Reference Sequence (CRS) (Anderson et al 1981) to find mutations.

Phylogenetic and statistical analysis

The regional/linguistic descriptions and HVR I haplotypic motifs of the samples are given in Appendix 1. The haplotypic motifs were defined as putative haplogroups by comparing them with HVR I data obtained from Metspalu et al (2004), and the coalescence ages for these haplogroups and their standard errors (SE) for mutation rates were calculated as described by Forster et al (1996). Mitochondrial hypervariable regions (HVR I and II) were analysed for statistical and phylogenetic patterns. The software DNASP 4.0.0.4 (Rozas and Rozas 1999) was used to identify the number of polymorphic sites and number of mutations, to calculate nucleotide diversity, the mean number of mismatches, Fu’s Fs statistics (Fu 1997), Tajima’s D values (Tajima 1989), raggedness statistics and to draw graphical patterns of mismatch distributions (Rogers and Harpending 1992). The other statistical inferences, like initial theta (θa) and values of tau (τ), obtained from DNASP 4.0.0.4, were used to calculate Ne = effective population size (θa/2 μ) and population expansion age AYa = (A × τ/2 μ) years ago (Rogers and Harpending 1992). An average mutation rate μ = 0.00124 per site per generation (Forster et al 1996) with an average generation time A = 20 years, was used for the calculations.

The neighbour-joining (NJ) trees for the studied population groups were generated using MEGA 2.1 software. Pairwise genetic distances between studied populations were computed as a linearisation of FST/(1-FST) (Slatkin 1995) using ARLEQUIN 2.000 software (Schneider et al 2000). These linearised distance values were used to create a MDS plot based on HVR I data using SPSS 10.0.5 (Chicago, IL, USA) and a NJ Tree, based on HVR II data, using PHYLIP (Version 3.5c) (Felsenstein 1989; PHYLIP home page) and a TreeView (version 1.6.1) (see http://taxonomy.zoology.gla.ac.uk/rod/treeview.html) for the studied population groups. Median-joining (MJ) networks (Bandelt et al 1999) for HVR I and II were constructed using the software NETWORK 4.1.0.8.

Results

Analysis of mitochondrial HVR I (nucleotide positions: 16023–16414) and HVR II (nucleotide positions: 53–424) showed the presence of a large number of variations, both known and novel mutations, in the samples analysed. Some of the sequences with mutations were deposited in the GenBank database and accession numbers were obtained: HVR I (AF467445–450, AF542192–198 and AY899182–94) and HVR II (AY642000–023).

The analysis of the putative haplogroups classified on the basis of mtDNA HVR I haplotypic motifs (Appendix 1) showed that 53.15% of the individuals from the studied population groups belonged to haplogroup M lineages with a coalescence age of 66,043.6 + 9,995.7 years. Both U2 and U7 lineages of haplogroup U, each 10.8% of the total, showed a deep but different coalescence age of 58,297.7 + 23,729 and 35,875 + 10,984.6 years, respectively. Individuals represented in haplogroup R lineages (9%), most of them (5.4%) belonging to R5, showed a coalescence age of 52,468 + 17592.5 years. Other observed lineages, known to be of European origin (F, H, HV, J, U1 and U5), represented 9.9% of the total population, whereas 6.3% remained undefined.

Using the HVR I sequence data, the number of polymorphic sites, the number of mutations, the mean number of mismatches, the nucleotide diversities, the initial theta values, the raggedness statistic values, Fu’s Fs statistic values, Tajima’s D values, expansion ages and initial effective population sizes of all the studied population groups were calculated and are given in Table 1. Figure 1 depicts the mismatch distribution patterns and respective NJ trees for the studied population groups based on mitochondrial HVR I data. The unimodal nature, the smoothness (as revealed by the very small values for the raggedness statistics) of the mismatch distribution curves, the reasonably good fits with the expected distributions of the observed mismatch distributions, the branching patterns in the NJ trees, the significantly large negative values of Fu’s Fs statistics, and the highly significant values of Tajima’s D (Table 1) clearly indicate that there were significant expansions of the different population groups studied, which is also supported by the star-like configurations in the MJ networks based on HVR I (Fig. 2a) and HVR II (Fig. 2b) data. An extreme sharing of haplotypes with no population-specific differentiation was also observed in both of the MJ networks.

Table 1 Descriptive statistics based on HVR I in Indian population groups belonging to various linguistic backgrounds
Fig. 1
figure1

Observed (dashed line) and expected (solid line) mismatch distribution curves and respective neighbour-joining trees showing population expansion patterns based on mtDNA HVR I data

Fig. 2a–b
figure2

a Median-joining network of the studied populations based on mtDNA HVR I haplotypes. b Median-joining network of the studied populations based on mtDNA HVR II haplotypes

An MDS plot based on the genetic distances of Slatkin linearised FSTs from mtDNA HVR I data (Fig. 3a) showed that the studied population groups form a compact group and this cluster includes Mongol, Egyptian and sub-Saharan as the nearest population groups. An NJ Tree (Fig. 3b) based on the genetic distances of Slatkin linearised FSTs (given as UP and BI = 0.00, UP and SI = 0.00, BI and SI = 0.00, PUNJ and BI = 0.05, PUNJ and SI = 0.04, PUNJ and UP = 0.09) from HVR II data revealed that the population groups UP and BI formed a single cluster whereas PUNJ branched out, probably depicting genetic affinity among the UP, BI and SI population groups as compared to PUNJ.

Fig. 3a–b
figure3

a MDS plot based on Slatkin’s linearised Fst values obtained from HVR I data showing the genetic relationship between the studied and other world population groups. b Neighbour-joining tree of the studied population groups based on the genetic distances of Slatkin linearised FSTs obtained from HVR II data

Discussion

The geography of India has played a decisive role in the peopling of India. Populations within India have been subjected to foreign invasions and migrations from time to time, resulting in no single apparent origin for any present day population groups and a conglomeration of different Y-chromosomal lineages (Quintana-Murci et al 2001; Saha et al 2005). The maternal gene flow in and out of India has been limited since the initial settling of Indian maternal lineages (Metspalu et al 2004). Indian mtDNA lineages belong to either Asian-specific haplogroup M or western Eurasian-specific haplogroups H, I, J, K, U, W and others that were not established anywhere (Kivisild et al 1999). The high frequency and diversity of mtDNA haplogroup M, the major contributor to the Indian maternal gene pool, has been associated with its southwest-Asian origin (Roychoudhury et al 2000, 2001; Richards et al. 2003; Rajkumar et al. 2005), whereas the presence of lineage M1 in Africa (Quintana-Murci et al 1999) and lack of L3 lineages other than M and N in India has become the most parsimonious view of the origin of haplogroup M in east Africa, which has been supported by the most recent view of single rapid coastal settlement of Asia by three major mtDNA haplogroups, M, N and R (Palanichamy et al 2004; Macaulay et al 2005; Thangaraj et al 2005; Forster and Matsumura 2005) as the founding female lineages to Indian population groups. However, the restricted presence of M as M1 and the phylogeography of M1 in Africa, predominantly in the Afro-Asiatic linguistic phylum (Metspalu et al 2004), leaves the question of the origin of haplogroup M unanswered.

This study of human mtDNA attempts to answer a variety of questions regarding the structures and compositions, the genetic relationships, the ancestries and the effects of migrations on present day females within the population groups studied in India, and it also throws light on their genetic relationships with each other and with other world populations. The observed deep coalescence ages, distribution patterns and high diversities of haplogroup M in all of the studied population groups supported the concept of a common founder of the Indian maternal gene pool acting as a major contributor, irrespective of its place of origin. Further, the overlapping coalescence ages within the standard deviation intervals for the U2 and R5 lineages suggested their coexistence with haplogroup M lineages (Metspalu et al 2004), but comparatively less so in frequency and diversity, which could also be due to independent migration events in India. Whereas, the coalescence age of U7 was observed to be far younger, indicating that it was differentiated later and that the trans-Indian subcontinent spread occurred later too. The mismatch distribution patterns, respective NJ trees, various statistical analyses (Table 1), star-like configurations of the clusters with extreme sharing and the lack of population-specific differentiation in the MJ network (Fig. 2a, b) suggested that all of the population groups underwent expansions in ancient times and had a fundamental maternal similarity. There were also indications of some recent mtDNA migrations, apparent in the form of some small clusters without star-shaped phylogeny in the MJ network (Fig. 2a), that could have been associated with various recent invasions of and migration events to India. A greater maternal genetic proximity was revealed in MDS plot analysis (Fig. 3a) for the studied population groups when compared with other world populations, which also indicated the conservation of the east-Asian mtDNA components and the presence of West Eurasian and African/sub-Saharan lineages. The clustering in the NJ tree (Fig. 3b) and the Fst values indicated a close maternal relationship between all of the Indian populations, whereas the branching out of the Punjab supports the interpretation that there was probably a considerable inflow of genes from Indo-European-speaking populations from central and possibly from West Asia into the Punjab (Passarino et al 1996; Kaur et al 2002). The results obtained also suggest that linguistic/ethnic differences evolved later on, by the process of acculturation, and the recent demic diffusion (Quintana-Murci et al 2001) also brought in some western-Eurasian mtDNA components.

To conclude, the present study supports an ancient common ancestry for the studied population groups through common founder female lineages, but it also indicates a maternal gene flow in ancient times with further ethnic differentiation occurring subsequently through a series of demographic expansions, geographical dispersals, social groupings and later Eurasian admixture.

In future studies, a larger sample size and mitochondrial coding region SNP markers could provide more information and lead to a better comprehension of the evolutionary history of the studied and other Indian population groups.

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Acknowledgement

The financial assistance to SS and ER as NCAHG (UGC) fellows and AS in the form of a Research Associateship by CSIR is acknowledged. The authors also acknowledge the grant given to the National Centre of Applied Human Genetics by UGC, India, and the support as a Centre for Advanced Studies to the School of Life Sciences.

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Correspondence to Ramesh Bamezai.

Appendix 1

Appendix 1

Regional/linguistic descriptions and HVR I haplotypic motifs of the studied samples

S. no Sample Region Linguistic group mtDNA region (16,023–16,414); HVS I motif (-16000) Putative haplogroupa
1 B16 Bihar Indo-European 129, 144A, 148G,b 223, 367Tb M/M5
2 B37 Bihar Indo-European 223, 302 M
3 BD10 Bihar Indo-European 93, 129, 145, 182C, 183C, 189, 318T U/U1/U7
4 BD13 Bihar Indo-European 51, 93A, 154, 206C, 230, 311 U2a
5 BD113 Bihar Indo-European 223, 234 M
6 BD14 Bihar Indo-European 126, 223, 368, 391 M3
7 BD27 Bihar Indo-European 129, 223, 362 M5
8 BD28 Bihar Indo-European 145, 176G, 223, 240, 390 N.D.
9 BD31 Bihar Indo-European 223, 234, 305, 311, 362 M9a
10 BD33 Bihar Indo-European 126, 223, 301, 344 M3
11 BD37 Bihar Indo-European 51, 192, 287, 325, 381 U2b
12 BD39 Bihar Indo-European 309, 318T U7
13 BD52 Bihar Indo-European 86, 223, 284, 327, 398 M
14 BD55 Bihar Indo-European 209, 239, 352, 353 N.D.
15 BHC113 Bihar Indo-European 172, 304, 362 F/R
16 BHC115 Bihar Indo-European 362 MD4
17 BHC130 Bihar Indo-European 223 L3/M/N
18 BHC134 Bihar Indo-European 51, 209, 239, 352, 353 U2b
19 BHC14 Bihar Indo-European 129, 223, 265C, 311 M5
20 BHC156 Bihar Indo-European 223, 275, 304G, 327A,b 390 M
21 BHC27 Bihar Indo-European 51, 104, 207, 227, 408b U2
22 BHC56 Bihar Indo-European 223, 275, 327A,b 390 M
23 BHC66 Bihar Indo-European 75, 93, 129, 223, 291 M
24 BHC91 Bihar Indo-European 129, 169, 223, 391 M
25 BSUY Bihar Indo-European 51, 209, 239, 352, 353 U2b
26 BVIJ Bihar Indo-European 129, 223, 291 M5
27 P14 Punjab Indo-European 51, 209, 239, 352, 353 U2b
28 PBAN Punjab Indo-European 166delA, 223 M
29 PHC50 Punjab Indo-European 93, 266, 325, 356 R5
30 PHC68 Punjab Indo-European 126, 223, 266, 311 M3a
31 PNIR Punjab Indo-European 223 L3/M/N
32 PP55 Punjab Indo-European 145, 176, 223, 261, 266, 291, 311 M4a
33 PP56 Punjab Indo-European 172, 304, 362 F/R
34 PP57 Punjab Indo-European 172, 318T U7
35 PP59 Punjab Indo-European 126, 223, 260 M3
36 PP62 Punjab Indo-European 129, 223, 265C M5
37 PP63 Punjab Indo-European 223, 362 M/MD/MD4
38 PP64 Punjab Indo-European 179delC,b 223 M
39 PP65 Punjab Indo-European 69, 126, 145, 222, 261, 288, 362 J
40 PP67 Punjab Indo-European 223, 294, 311, 318T U7/M4
41 PP68 Punjab Indo-European 126, 129, 169, 223 M3a
42 PP69 Punjab Indo-European 182, 311, 408b M (N.D.)
43 PP70 Punjab Indo-European 129, 148, 266, 290, 318,b 320, 362 R6
44 PP76 Punjab Indo-European 129, 214A,b 223, 252, 291, 298 M/M5
45 PP77 Punjab Indo-European 182, 311, 223, 304 M25 (M- N.D.)
46 PP83 Punjab Indo-European 223, 304 M/M25
47 PP84 Punjab Indo-European 223, 293 M
48 PP86 Punjab Indo-European 129, 223, 296, 311 M5
49 PP87 Punjab Indo-European 126, 173, 181, 209, 260, 362 R21
50 PP88 Punjab Indo-European 51, 209, 239, 311, 352, 353 U2b
51 PP89 Punjab Indo-European 193, 218, 223, 335 M (N.D.)
52 PP91 Punjab Indo-European 126, 223, 304 M3/M25
53 PP94 Punjab Indo-European 182, 311, 408b M (N.D.)
54 PP97 Punjab Indo-European 69, 126, 261 J
55 PPUR Punjab Indo-European 129, 223 M/M5
56 PPUS Punjab Indo-European 93, 192, 256, 270, 362, 399 U5
57 PRAJ Punjab Indo-European 172, 256, 266, 304, 356 R5
58 PRAM Punjab Indo-European 51, 239, 288, 353 U2b
59 PSUR Punjab Indo-European 51, 209, 239, 246, 255delG,b 352, 353 U2b
60 PSUS Punjab Indo-European 223, 257, 261, 324, 362 M
61 PUSH Punjab Indo-European 223, 234 M
62 S12 South India Dravidian 126, 223, 278, 327 M3a
63 S18 South India Dravidian 51, 209, 239, 244,b 352, 353 U2b
64 S22 South India Dravidian 129, 218, 309, 318T U7
65 S28 South India Dravidian 37, 148G, 215, 390 N.D.
66 SHC13 South India Dravidian 192, 291, 295, 298, 390 N.D.
67 SHC15 South India Dravidian 183C, 189, 210, 223, 266 M
68 SHC198 South India Dravidian 69, 274, 318T U7
69 SHC51 South India Dravidian 129, 223 M/M5
70 SHC53 South India Dravidian 51, 86, 259, 261, 291, 353 U2b
71 SHC98 South India Dravidian 69, 274, 318T U7
72 SHC99 South India Dravidian 256, 270, 311, 399 U5
73 SR02 South India Dravidian 172, 256, 266, 304, 356 R5
74 SST14 South India Dravidian 93, 148G,b 210, 223, 266 M/N.D.
75 SST17 South India Dravidian 223, 318T M18
76 SST3 South India Dravidian 93, 124, 223, 266, 349b M
77 SST4 South India Dravidian 93, 100,b 140A,b 194, 223, 233, 241T,b 266 R5/N.D.
78 SST7 South India Dravidian 223, 318T, 322 M18
79 U15 Uttar Pradesh Indo-European 92, 287 N.D.
80 U68 Uttar Pradesh Indo-European 66C,b 126, 145, 176, 223, 261, 311 M4a
81 UANI Uttar Pradesh Indo-European 129, 223, 274, 297, 311, 362 MD4/MG3/M5
82 UBHA Uttar Pradesh Indo-European 126, 223, 408b M3
83 UBOB Uttar Pradesh Indo-European 51, 223, 249, 250 N.D.
84 UCHA Uttar Pradesh Indo-European 223, 234, 292, 311, 316, 362 M/M9
85 UD113 Uttar Pradesh Indo-European 37, 189, 318T U7
86 UD18 Uttar Pradesh Indo-European 309, 318T, 362 U7
87 UD24 Uttar Pradesh Indo-European 318T U7
88 UP124 Uttar Pradesh Indo-European 318T U7
89 UD43 Uttar Pradesh Indo-European 69, 126, 145, 172, 222, 261, 355 J
90 UD47 Uttar Pradesh Indo-European 54,b 266, 304 R5
91 UD50 Uttar Pradesh Indo-European 51, 65T,b 66C,b 129, 172, 206C N.D./U2
92 UD56 Uttar Pradesh Indo-European 309, 318T U7
93 UD64 Uttar Pradesh Indo-European 93, 129, 223, 291 M/M5
94 UHC11 Uttar Pradesh Indo-European 126, 223, 278, 327 M3a
95 UHC114 Uttar Pradesh Indo-European 176, 223, 344 M
96 UHC116 Uttar Pradesh Indo-European 304, 311 HV3/R
97 UHC126 Uttar Pradesh Indo-European 129, 223 M/M5
98 UHC128 Uttar Pradesh Indo-European 54,b 266, 304, 311, 355, 356, 399 R5
99 UHC139 Uttar Pradesh Indo-European 93, 223, 225,b 234, 290 R
100 UHC2 Uttar Pradesh Indo-European 42, 66T,b 129, 223, 243 M/M5
101 UHC24 Uttar Pradesh Indo-European 129, 223, 243 M/M5
102 UHC214 Uttar Pradesh Indo-European 176, 223, 344 M
103 UHC31 Uttar Pradesh Indo-European 86, 145, 223, 261,b 311 M4a
104 UHC32 Uttar Pradesh Indo-European 48, 129, 223 M/M5
105 UHC64 Uttar Pradesh Indo-European 126, 181, 223, 233, 344 R21/N.D.
106 UHC70 Uttar Pradesh Indo-European 223, 213, 362 M6a
107 UHC75 Uttar Pradesh Indo-European 51, 209, 239, 244,b 304, 352, 353 U2b
108 UJEA Uttar Pradesh Indo-European 124, 223, 274, 362 MD4/MG3
109 UKIR Uttar Pradesh Indo-European 309, 318T, 368 U7
110 USIN Uttar Pradesh Indo-European 304, 320, 362 N.D./H
111 63 Uttar Pradesh Indo-European 222delC, 225 N.D./H
  1. aPutative haplogroups defined by HVS I motifs; N.D. = not defined; / = to be confirmed by mtDNA coding region polymorphism
  2. bNovel mutations observed when compared with control region polymorphisms database (source: Brandon et al 2005)

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Sharma, S., Saha, A., Rai, E. et al. Human mtDNA hypervariable regions, HVR I and II, hint at deep common maternal founder and subsequent maternal gene flow in Indian population groups. J Hum Genet 50, 497–506 (2005). https://doi.org/10.1007/s10038-005-0284-2

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Keywords

  • Indian populations
  • Mitochondrial DNA
  • Matrilineal
  • HVR I and II

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