• Nu S-Au Găsit Rezultate

View of Comparative Study of Nei’s D with other Genetic Distance Measures between Barak Valley Muslims and other Nations for ABO Locus

N/A
N/A
Protected

Academic year: 2022

Share "View of Comparative Study of Nei’s D with other Genetic Distance Measures between Barak Valley Muslims and other Nations for ABO Locus"

Copied!
6
0
0

Text complet

(1)

Comparative Study of Nei’s D with other Genetic Distance Measures between Barak Valley Muslims and other Nations for ABO Locus

Supriyo CHAKRABORTY

1,

Saumendra Kumar BHATTACHARJEE

2,

Gauri Datta SHARMA

3

1Assam University, Department of Biotechnology, Silchar 788011, Assam, India; [email protected]

2Silchar Medical College and Hospital, Department of Pathology, Silchar 788014, Assam, India

3Assam University, Department of Life Science and Bioinformatics, Silchar 788011, Assam, India

Abstract

Quantification of the genetic distance between populations is essential in many genetic research programs. Several formulae were proposed for the estimation of genetic distance between populations using gene frequency data. But the selection of a suitable measure for estimating genetic distance between real-world human populations is a very difficult task despite the widely used measure Nei’s D.

The present study was undertaken to estimate the genetic distance between Barak Valley Muslims (BVM) and other twenty-four nations using seven different measures with ABO blood group gene frequency data for comparative analysis and to estimate the correlation coefficients between distance measures and to work out the linear regression equations. Seven genetic distance measures namely Nei’s D, Nei’s Nm, La, Nei’s Da, Dc, Re and Nei’s Ne were estimated between BVM and other 24 nations enroute the journey of mankind from Africa that commenced about 200,000 years ago (www.bradshawfoundation.com). Correlation coefficients between Nei’s D with other measures were estimated to find out which other genetic distance measures were closely related to Nei’s D. Nei’s D showed highly significant (p=0.01) positive correlation with Cavalli-Sforza and Edwards chord distance Dc (0.90), Reynolds Re (0.90), Nei’s Da (0.74) and Nei’s Ne (0.63) but negative correlation with Nei’s Nm and La. Linear regression equations of Nei’s D with other distance measures were estimated as Da =-0.80 + 1.34D, Dc = 1.91 + 4.44D, Re =-0.51 + 0.24D and Ne =-7.60 + 1.30D.

Keywords: ABO gene, genetic distance, human populations Introduction

Quantification of the genetic distance between popu- lations is instrumental in many genetic research programs.

A large number of formulae have been proposed for this purpose. However, the selection of an appropriate measure for assessing genetic distance between real-world human populations that diverged because of mechanisms that are not fully known can be a challenging task (Libiger et al., 2009).

Nei’s standard genetic distance D has been the most widely used genetic distance measure between popula- tions. Since several formulae have already been proposed for genetic distance measurement, it is essential to identify which genetic measures show a close relationship with Nei’s D. Barak Valley zone of Assam in India has a total popu- lation of about 3.21 million including Hindus, Muslims and Christians with a land area of 6,992 square kilometers.

These populations have maintained distinct culture and life style for centuries despite sharing a few common fea- tures. No information is available on the genetic proximity of the Muslims of Barak Valley (BVM) with other nations/

populations in the route of migration of humankind that commenced from Africa nearly 200,000 years ago.

ABO blood grouping system was established by Karl Landsteiner in 1900 on the basis of presence or absence

of two antigens (A and B) on RBC and its Mendelian in- heritance pattern by Bernstein in 1924 (Crow, 1993). In this system, four blood groups namely A, B, AB and O are identified by blood tests. Genetic analysis of the ABO blood group system revealed that three alleles namely A (IA), B (IB) and O (i) determine blood group phenotype.

The A allele produces A antigen, B produces B antigen and the O allele produces neither. Both A and B alleles are mutant forms and show codominance with each other but both are dominant over the O allele in diploid condition.

The nations/populations across the globe can be char- acterized for the distribution of ABO blood groups. These phenotypic data are used to estimate the frequency of dif- ferent alleles of ABO gene using the standard formulae of population and quantitative genetics. The allele frequen- cies of a gene can be used to estimate the genetic distance between two populations. Human genome project (HGP) has given a draft estimate of 25000 to 30000 genes in hu- man genome. The study of all these genes, each with vary- ing number of alleles, at a time in a genome to elucidate the process of molecular evolution is complicated and almost impossible with the latest available state-of-the-art molecular biology technique (October, 2011). Hence it is imperative to study one or a few genes at a time to under- stand the evolutionary process in humankind.

Received 10 November 2011; accepted 27 January 2012

(2)

Nei’s standard genetic distance (D) between two popu- lations without bias correction according to Nei (1972) is estimated as:

( )

=

∑ ∑ ∑ ∑

∑ ∑

12

l u l u

2lu2 2lu1

l u lu1 lu2

P P

P ln P

D

Nei’s minimum distance (Nm) is given by the follow- ing equation:

∑∑ ∑∑ ∑∑

= = = = = =

= m

1 l

v

1 u

m

1 l

v

1 u

m

1 l

v

1 u

lu2 lu1 lu2

2 lu1

1 P P P .P

Nm

Latter’s distance (La) according to Latter (1972) is given by:

∑∑

∑ ∑ ∑ ∑ ∑∑

= =

= = = = = =

= m

1 l

v 1 u

lu2 lu1.

m 1 l

m 1 l

m 1 l

v 1 u

lu2 lu1.

v 1 u

lu2 v

1 u 2 lu1 1

P P 1

P P P

La P

Nei’s Da distance according to Nei et al. (1983) is giv- en by:

∑∑

= =

= m

1 l

v

1 u

lu2 lu1P m1 P

1 Da

Cavalli-Sforza and Edwards chord distance (Dc or CE) according to Cavalli-Sforza and Edwards (1967) is given

by:

∑ ∑

( )

= =

= m

1 l

v

1

u lu1 lu2

3.1416m 2

12 12

.P P 1 2 Dc

Reynolds genetic distance (Re) according to Reynolds et al. (1983) is given by:

( ) ( ) [ ]

( )

∑ ∑

∑ ∑ ∑

− ⎭⎬⎫

⎩⎨

⎧ − +

− −

=

l u lu1 lu2

l u u

2lu2 2lu1 lu2 2

2 lu1 1

P P 1

P P 1 2

n 2 2 1 P

P Re

Nei’s geometric distance (Ne) based on genotype fre- quency data (not gene frequency) is given by:

( )

∑∑

= =

= m

1 l

v

1

u lu1 lu2

m1 P P 12

1 Ne

Correlation and regression analysis

Correlation coefficient between any two distance measures was calculated according to Harris et al. (2007).

Correlation coefficient was tested by the t-test for signifi- cance at p=0.01 and 0.05. Linear regression equation of a distance measure (as dependent variable) on Nei’s D as independent variable was estimated by the method of least squares as per Harris et al. (2007).

Results and discussion

Barak Valley Zone, named after the mighty river Barak flowing through the zone, is located in southern part of As- sam state in North East India. The valley has inhabited one of the major endogamous religious groups, the Muslims, for several centuries. Barak Valley has a total population of about 3.21 million including Hindus, Muslims and Chris- tians with a land area of 6,992 square kilometers. This re- gion is characterized by undulating topography with wide The present study was taken up to estimate the genetic

distance between Barak Valley Muslims (BVM) and each of other 24 nations for ABO blood group gene frequen- cy data using seven different genetic distance measures namely Nei’s D, Nei’s Nm, Latter’s La, Nei’s Da, Cavalli- Sforza and Edwards Dc (RE), Reynolds Re and Nei’s Ne.

Genetic distance between Barak Valley Muslims and other 24 nations along the historic route of human migration as proposed by Stephen Oppenheimer (at http://www.brad- shawfoundation.com) was estimated on the basis of ABO gene frequency and to assess the genetic proximity and the evolutionary relationship of the Barak Valley Muslims with other nations.

To identify the distance measure(s) that shows a close relationship with Nei’s D, correlation analysis was done between the estimates of Nei’s D and other distance mea- sures. Linear regression equations of different distance measures on Nei’s D were worked out to determine the value of a particular distance measure with a given value of Nei’s D.

Materials and methods

In this study, ABO blood group distribution data of 25 populations excluding Barak Valley Muslims were ob- tained from the published literature and websites. The ABO blood group distribution data in Barak Valley Mus- lims were estimated by Chakraborty (2010). The frequen- cies of O, A and B alleles belonging to ABO blood group system for each population were estimated from ABO blood group phenotyping data using the formulae sug- gested by Hedrick (2005) as given below:

N N N 1 N

A= 22+ 23+ 33 N N N 1 N

B= 11+ 13+ 33 N

O= N33

Where N= Total individuals

N11+N13= Individuals having “A” blood group N22+N23= Individuals having “B” blood group N33= Individuals having “O” blood group Genetic distance

The ABO gene frequency data (Tab. 1) were used to estimate the genetic distance between Barak Valley Mus- lims and each of the remaining 24 populations using seven distance measures as given below.

Let the genetic distance for ‘m’ loci with ‘v’ alleles per locus be studied in populations 1 and 2 with n1 and n2 in- dividuals having n as the average number of individuals.

Let Plu1 and Plu2 be the frequencies of allele ‘u’ at locus

‘l’ in population 1 and 2, respectively and let Plu1 and Plu2 be the number of individuals that carry allele ‘u’ at locus

‘l’ in populations 1 and 2 respectively, then seven distance measures can be estimated as follows:

(3)

plain area, low lying water logged tracts and hillocks. The climate of Barak valley is sub-tropical, warm and humid with average annual rainfall of 318 cm and 146 rainy days.

Nearly 80% of the total population depends on agriculture for livelihood.

Gene frequency

The frequencies of O, A and B alleles of ABO gene of different nations/populations were estimated from the ABO blood group distribution data of each population (Tab. 1). In general, the frequency of O allele was the high- est in all the populations. B allele was not reported in Aus- tralians.

Genetic distance between populations

The estimates of various genetic distance measures be- tween Barak Valley Muslims (BVM) and each of the twen- ty-four populations were calculated on the basis of ABO gene frequency data (Tab. 2).

Nei’s D estimate was the lowest (0.0015) between BVM and India (in general) indicating lowest genetic dis- tance between these two populations for ABO gene. On the other hand, the highest Nei’s D value (0.0395) was found between BVM and Australia suggesting greatest genetic distance between these two populations for ABO

gene out of 24 combinations. Nei’s geometric distance (Ne), except all other genetic distance measures, was calcu- lated on the basis of genotypic data estimated from ABO gene frequency.

Nei’s minimum genetic distance (Nm) ranged from the lowest value 0.0074 between BVM and West Indonesia to the highest value 0.0791 between BVM and South China irrespective of sign. Similarly, Latter’s distance (La) ranged from 0.0146 between BVM and West Indonesia to 0.1366 between BVM and South China.

Nei’s Da estimate ranged from 0.0009 between BVM and India to 0.1000 between BVM and Australia. Cav- alli-Sforza and Edwards chord distance (Dc) showed the range from 0.0265 between BVM and India to 0.2847 be- tween BVM and Australia. Reynolds genetic distance (Re) ranged from the lowest estimate 0.00002 between BVM and Bulgaria to the highest value 0.0073 between BVM and Australia. Nei’s Ne estimate ranged from the lowest value 0.0169 between BVM and Sudan to the highest value 0.0808 between BVM and South China. Estimates of genetic distance between BVM and other populations using seven measures are graphically presented (Fig. 2).

Several studies were carried out on genetic distance measurements across different populations. Genetic dis- tance and gene diversity studies by Roy et al. (1990) Tab. 1. Estimates of allele frequencies of ABO gene in Barak Valley Muslims (BVM) and other 24 populations/nations

No.Sl. Population O Allele FrequencyA B Total Reference*

1 Kenya 0.69 0.17 0.14 1.00 Anees and Mirza, 2005

2 Sudan 0.81 0.11 0.08 1.00 www.bloodbook

3 Saudi Arabia 0.58 0.21 0.21 1.00 -do-

4 India (Overall) 0.62 0.16 0.22 1.00 -do-

5 Sri Lanka 0.69 0.16 0.15 1.00 -do-

6 West Indonesia 0.69 0.10 0.21 1.00 Breguet et al., 1986

7 Borneo (Malaysia) 0.62 0.22 0.16 1.00 Kamil et al., 2010

8 South China 0.53 0.23 0.24 1.00 www.bloodbook

9 Australia 0.78 0.22 - 1.00 -do-

10 Bulgaria 0.57 0.31 0.12 1.00 -do-

11 Hungary 0.60 0.27 0.13 1.00 -do-

12 Austria 0.60 0.30 0.10 1.00 -do-

13 Pakistan 0.74 0.12 0.14 1.00 -do-

14 Central Asia (Uzbekistan) 0.56 0.25 0.19 1.00 Revavov et al., 1983

15 Eastern Europe(Poland) 0.57 0.28 0.15 1.00 www.bloodbook

16 Siberia 0.57 0.16 0.27 1.00 -do-

17 Russia 0.57 0.25 0.18 1.00 -do-

18 Alaska .62 0.29 0.09 1.00 -do-

19 USA (Whites) 0.67 0.25 0.08 1.00 -do-

20 Britain 0.69 0.26 0.05 1.00 -do-

21 Norway 0.62 0.32 0.06 1.00 -do-

22 Sweden 0.62 0.31 0.07 1.00 -do-

23 Iceland 0.74 0.19 0.07 1.00 -do-

24 Denmark 0.64 0.27 0.09 1.00 -do-

25 Barak Valley Muslims 0.63 0.18 0.19 1.00 Chakraborty, 2010

*Detailed reference in text

(4)

populations namely Brahmin, Kalita and Kaibarta on the basis of ABO blood groups and other anthropomet- ric characters revealed that the Kaibarta stand apart from the Brahmin and the Kalita, who are similar to each other.

Genetic study by Danker-Hopfe et al. (1988) among 13 Assamese populations including two Muslim groups for the distribution of anthropometric, anthroposcopic and dermatoglyphic traits revealed that the Muslims in As- among 10 endogamous groups in Chattisgarh, India using

the gene frequency data of three genetic loci revealed that the gene differentiation among these population groups is only about 2 per cent.

Genetic differentiation studies in Indian populations by Papiha et al. (1982) revealed that genetic differentia- tion in India populations was low (0.26-1.70%). In Assam, genetic variation studies by Das (1979) among three caste

Tab. 2. Estimates of seven different genetic distance measures between BVM and other nations for ABO gene

No.Sl. Combination Nei’s D Nei’s Nm La Nei’s Da Cavalli-

Sforza Dc Reynolds Re Nei’s Ne

1 BVM-Kenya 0.0045 0.0081 0.0159 0.0027 0.0464 -0.0038 -0.0549

2 BVM-Sudan 0.0268 -0.0453 -0.0996 0.0216 0.1325 0.0051 -0.0169

3 BVM-Saudi Arab 0.0032 0.0569 0.1021 0.0013 0.0330 -0.0042 -0.0762

4 BVM-India 0.0015 0.0388 0.0720 0.0009 0.0265 -0.0047 -0.0691

5 BVM-Sri Lanka 0.0038 0.0080 0.0157 0.0022 0.0418 -0.0039 -0.0552

6 BVM-West Indonesia 0.0083 0.0074 0.0146 0.0068 0.0741 -0.0029 -0.0505

7 BVM-Borneo 0.0027 0.0394 0.0730 0.0017 0.0368 -0.0045 -0.0689

8 BVM-South China 0.0138 0.0 791 0.1366 0.0051 0.0646 -0.0021 -0.0808

9 BVM-Australia 0.0395 -0.0310 -0.0661 0.1000 0.2847 0.0073 0.0239

10 BVM-Bulgaria 0.0276 0.0623 0.1108 0.0135 0.1047 -0.00002 -0.0662

11 BVM-Hungary 0.0136 0.0487 0.0888 0.0076 0.0783 -0.0025 -0.0669

12 BVM-Austria 0.0253 0.0490 0.0893 0.0150 0.1101 -0.0004 -0.0599

13 BVM-Pakistan 0.0113 -0.0144 -0.0297 0.0071 0.0761 -0.0013 -0.0412

14 BVM-Central Asia 0.0093 0.0661 0.1168 0.0039 0.0562 -0.0031 -0.0773

15 BVM-Eastern Europe

(Poland) 0.0161 0.0620 0.1103 0.0074 0.0776 -0.0020 -0.0722

16 BVM-Siberia 0.0106 0.0608 0.1084 0.0045 0.0607 -0.0029 -0.0740

17 BVM-Russia 0.0084 0.0617 0.1098 0.0037 0.0547 -0.0033 -0.0758

18 BVM-Alaska (Eskimo) 0.0235 0.0401 0.0742 0.0158 0.1131 -0.0006 -0.0559

19 BVM-USA Whites 0.0175 0.0177 0.0342 0.0149 0.1098 -0.0013 -0.0483

20 BVM-Britain 0.0261 0.0090 0.0177 0.0269 0.1476 0.0009 -0.0349

21 BVM-Norway 0.0379 0.0404 0.0748 0.0282 0.1513 0.0022 -0.0447

22 BVM-Sweden 0.0328 0.0403 0.0746 0.0235 0.1379 0.0012 -0.0489

23 BVM-Iceland 0.0185 -0.0137 -0.0282 0.0170 0.1172 0.0004 -0.0339

24 BVM-Denmark 0.0187 0.0311 0.0586 0.0138 0.1058 -0.0014 -0.0543

Fig. 1. Linear regression equations showing relationship between Nei’s D with other distance measures

(5)

to very high magnitude of positive correlation of Nei’s D with Cavalli-Sforza and Edwards chord distance Dc and Reynolds Re, the use of anyone measure out of these three measures would be more effective in genetic analysis. Nei’s D showed non-significant negative correlation with Nei’s minimum distance Nm and Latter’s distance La.

Regression analysis

Nei’s D is the most widely used genetic distance mea- sure in research programs. Assuming Nei’s D as a de- pendent variable and anyone of the remaining distance measures (Da, Dc, Re or Ne) as independent variable, the linear regression equations of the latter on Nei’s D were estimated (Tab. 4; Fig. 1). Since Nei’s minimum distance Nm and Latter’s distance La did not show significant cor- relation with Nei’s D, hence Nm and La were not used as dependent variables in determining the linear regression equation with Nei’s D.

These regression equations could be used to estimate the magnitude of the particular genetic distance measure with a given value of Nei’s D between two populations. But the accuracy of the particular genetic estimates calculated from a given estimate of Nei’s D using the above linear regression equations would decrease with the decreasing value of correlation coefficients. In the regression equation y = A+Bx, the B estimate represents the regression coef- ficient (slope) for linear regression and the regression con- stant A represents the magnitude of the y-intercept i.e. the distance from the origin to the point where the straight line intersects the y-axis.

sam were distinguished between Marias (who seemed to be more closely related to Mongoloid populations) and Sheikhs (whose phenotypic appearance was more like that of Hindu caste groups).

Genetic distance studies by Roychoudhury et al. (1982) between Jews and Non-Jews using gene frequency data of nine blood groups and protein loci revealed that the Ye- menite Jews have a high degree of genetic affinity to the Israeli Arabs and the Iranian Jews to the Iranians. Genetic distance studies by Triantaphyllidis et al. (1983) between the inhabitants of nine Mediterranean countries and the three major human races using the gene frequency data of several genetic markers suggested that the Algerians were closer to Negroids while the other Mediterraneans were closer to Caucasoids.

Genetic and taxonomic distance studies by Sokal (1988) among 3466 samples of human populations in Eu- rope based on 97 allele frequencies and 10 cranial variables demonstrated that speakers of different language families in Europe differ genetically and that this difference re- mains even after geographic differentiation.

Correlation analysis

The estimates of correlation coefficients between any two distance measures (Tab. 3) revealed that Nei’s D showed highly significant (p=0.01) positive correlation with Cavalli-Sforza and Edwards chord distance Dc (0.90), Reynolds Re (0.90), Nei’s Da (0.74) and Nei’s Ne (0.63).

This indicated great similarity among these four distance measures and anyone of these measures could be used in- stead of all the four measures in genetic analysis. But due

Tab. 3. Correlation coefficients of Nei’s D with other genetic distance measures

Distance measure Nei’s Nm La Nei’s Da Dc Re Nei’s Ne

Nei’s D -0.24 -0.25 0.74** 0.90** 0.90** 0.63**

** Significant at p=0.01

Fig. 2. Comparison of various genetic distance measures between BVM and other nations for ABO gene

(6)

Das BM (1979). Physical variation in three Assamese castes.

Anthropol Anz 37(3):204-210.

Harris M, Taylor G, Taylor J (2007). Maths and Stats for the life and medical sciences. New Delhi: Viva Books Pvt Ltd, 157-167 p.

Hedrick PW (2005). Genetics of populations (3rd Ed). Sudbury:

Jones and Bartlett Publishers, 63-106 p.

http://www.bradshawfoundation.com

Kamil M, Han Al-Jamal, Yusoff NM (2010). Association of ABO blood groups with diabetes mellitus. Libyan J Med 5 at http://www.journals.sfu.ca/coactions/index.php/ljm/

article/view article/4847/5365.

Landsteiner K (1900). Note the antifermantativen, lytic and agglutinating activity of blood serum and lymph.

Centralblatt f. Bacteriology, Infectious Diseases and Parasites Customer. 27:357-362 (http://en.wikipedia.org/

wiki/Karl_Landsteiner).

Latter BD (1972). Selection in infinite populations with multiple alleles. III. Genetic divergence with centripetal selection and mutation. Genetics 70:475-490.

Libiger O, Nievergelt CM, Schork NJ (2009). Comparison of genetic distance measures using human SNP data. Hum Biol 81(4):389-406.

Nei M (1972). Genetic distance between populations. Am Nat 106:283-292.

Nei M, Tajima F, Yateno Y (1983). Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J Mol Evol 19:150-173.

Papiha SS, Mukherjee BN, Chahal SMS, Malhotra KC, Roberts DF (1982). Genetic heterogeneity and population structure in north-west India. Ann Hum Biol 9(3):235-251.

Reynolds J, Weir BS, Cockerham CC (1983). Estimation of the coancestry coefficient: basis for a short term genetic distance.

Genetics 105:767-779.

Roy M, Datta U, Mitra M, Singhrol CS (1990). Genetic distance and gene diversity among ten endogamous groups in Chattisgarh, Central India. Int J Anthropol 5(2):109- 115.

Roychoudhury AK (1982). Genetic distance between Jews and Non-Jews of four regions. Hum Hered 32(4): 259-263.

Revavov AA, Asanov A, Lunga IN, Bakhramov SM (1983).

Frequencies of ABO system blood groups and haptoglobins in Uzbekistan-the problems of sampling studies. Genetika 19(7):1193-1197.

Sokal RR (1988). Genetic, geographic and linguistic distances in Europe. Proc Natl Acad Sci, USA 85:1722-1726.

Triantaphyllidis CD, Kouvatsi A, Kaplanoglou L (1983).

The genetic distances between the inhabitants of nine Mediterranean countries and the three major human races.

Hum Hered 33(2):137-139.

www.bloodbook.com/world-abo.html.

Conclusions

The results of the present study revealed that the Mus- lims of Barak Valley in Assam showed the highest genetic distance (Nei’s D) with Australians but the lowest with In- dians in general. Correlation analysis between Nei’s D and other distance measures revealed that Nei’s D had highly significant (p=0.01) positive correlation with Cavalli- Sforza and Edwards chord distance Dc (0.90), Reynolds Re (0.90), Nei’s Da (0.74) and Nei’s Ne (0.63). This indi- cated great similarity among these four distance measures.

Nei’s D is the most widely used measure in research pro- grams. Assuming Nei’s D as a dependent variable and any- one of the remaining distance measures (Da, Dc, Re or Ne) as independent variable, the linear regression equations of the latter on Nei’s D in the form y = A+Bx were estimat- ed. These regression equations were Da =-0.80 + 1.34D, Dc = 1.91 + 4.44D, Re =-0.51 + 0.24D and Ne =-7.60 + 1.30D.

Acknowledgements

The authors are thankful to Assam University, Silchar, Assam for providing the necessary facilities to take up this research work.

References

Anees M, Mirza MS (2005). Distribution of ABO and Rh blood group alleles in Gujrat region of Punjab, Pakistan. Proc Pak Acad Sci 42(4):233-238.

Breguet G, Ney R, Gerber H, Garner MF (1986). Treponemal serology and blood groups on Bali Island, Indonesia.

Genitourin Med 62:298-301.

Cavalli-Sforza LL, Edwards AWF (1967). Phylogenetic analysis:

models and estimation procedure. Am J Hum Genet 19:233- 257.

Chakraborty S (2010). Genetic analysis on frequency of alleles for Rh and ABO blood group systems in the Barak Valley populations of Assam. Not Sci Biol 2(2):31-34.

Crow JF (1993). Felix Bernstein and the first human marker locus. Genet 133(1):4-7.

Danker-Hopfe H, Das BM, Walter H, Das PB, Das R (1988).

Anthropological studies in Assam, India-Differentiation processes among Assamese populations. Anthropol Anz 46(2):159-184.

Tab. 4. Linear regression equations of different distance measures on Nei’s D

Dependent

variable (y) Independent

variable (x) Regression equation y = A+Bx

Nei’s Da Nei’s D Da =-0.80 + 1.34D

Cavalli-Sforza Dc Nei’s D Dc = 1.91 + 4.44D

Reynolds Re Nei’s D Re =-0.51 + 0.24D

Nei’s Ne Nei’s D Ne =-7.60 + 1.30D

Referințe

DOCUMENTE SIMILARE

It will be seen that the Muslims in Manipur are be- ing related to 18 plants in study and these plants might have been mostly brought from Brahmaputra valley and Surma valley (now

The purpose of this study was to evaluate the correlation between a serum biomarker, the soluble form of the vasculo-endothelial growth factor (sFlt-1) and the distance between

According to our previous investigations it seems that tolerance, whether regarded as a political practice or a philosophical or moral principle, is a strategy (or tactics) of one

The aim of the present study was to investigate the induction of genetic variability using gamma radiation and selection for salt tolerance based on the similarity

In the present study, the genetic variation and relatedness between and among natural populations of Tilapia zillii from three different reservoirs in Osun

Our study revealed that ISSR markers can be used for studying the genetic diversity in saffron, but should be used along with other markers and more ISSR primers

But the interpopulation genetic distance values estimated for the three populations also tested by one way ANOVA and found to be significantly much different

Analysis of the genetic distance and genetic identity between Barak Valley Hindus and other twenty four na- tions along the route of historic journey of mankind from Africa