### Abstract

Relatedness between individuals as well as evolutionary relationships between populations can be studied by comparing genotypic similarities between individuals. When hypervariable loci are used to describe genotypes, it is shown that both of these problems can be approached with a unified theory based on allele sharing between individuals. The distributions of the number of shared alleles between individuals indicate their kin relationships. Extending this, we obtain statistics for genetic distances between populations based on average number of alleles shared between individuals within and between two different populations. Traditional statistical inferential procedure can be used to establish specific kinship relationships between individuals. We derive estimates of the number of hypervariable loci needed for a specified reliability of such an inference. Evolutionary dynamics of genetic distance statistics based on allele sharing is also studied. It shows that such measures of genetic distances remain linear with the time of divergence for a period comparable to that of the gene frequency-based measures of genetic distances. Statistical properties of measures based on allele sharing establish that for using such summary statistics it is not necessary to know the full characteristics of all loci used. It is enough to know the degree of heterozygosity per locus and the number of loci. Therefore, in principle, this approach can also be used for DNA fingerprinting data in the studies of relatedness between individuals as well as between populations. The possible compromising features of multilocus DNA fingerprinting data are also discussed.

Original language | English |
---|---|

Pages (from-to) | 153-175 |

Number of pages | 23 |

Journal | EXS |

Volume | 67 |

State | Published - 1993 |

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### Cite this

*EXS*,

*67*, 153-175.

}

*EXS*, vol. 67, pp. 153-175.

**A unified approach to study hypervariable polymorphisms : statistical considerations of determining relatedness and population distances.** / Chakraborty, R.; Jin, L.

Research output: Contribution to journal › Review article

TY - JOUR

T1 - A unified approach to study hypervariable polymorphisms

T2 - statistical considerations of determining relatedness and population distances.

AU - Chakraborty, R.

AU - Jin, L.

PY - 1993

Y1 - 1993

N2 - Relatedness between individuals as well as evolutionary relationships between populations can be studied by comparing genotypic similarities between individuals. When hypervariable loci are used to describe genotypes, it is shown that both of these problems can be approached with a unified theory based on allele sharing between individuals. The distributions of the number of shared alleles between individuals indicate their kin relationships. Extending this, we obtain statistics for genetic distances between populations based on average number of alleles shared between individuals within and between two different populations. Traditional statistical inferential procedure can be used to establish specific kinship relationships between individuals. We derive estimates of the number of hypervariable loci needed for a specified reliability of such an inference. Evolutionary dynamics of genetic distance statistics based on allele sharing is also studied. It shows that such measures of genetic distances remain linear with the time of divergence for a period comparable to that of the gene frequency-based measures of genetic distances. Statistical properties of measures based on allele sharing establish that for using such summary statistics it is not necessary to know the full characteristics of all loci used. It is enough to know the degree of heterozygosity per locus and the number of loci. Therefore, in principle, this approach can also be used for DNA fingerprinting data in the studies of relatedness between individuals as well as between populations. The possible compromising features of multilocus DNA fingerprinting data are also discussed.

AB - Relatedness between individuals as well as evolutionary relationships between populations can be studied by comparing genotypic similarities between individuals. When hypervariable loci are used to describe genotypes, it is shown that both of these problems can be approached with a unified theory based on allele sharing between individuals. The distributions of the number of shared alleles between individuals indicate their kin relationships. Extending this, we obtain statistics for genetic distances between populations based on average number of alleles shared between individuals within and between two different populations. Traditional statistical inferential procedure can be used to establish specific kinship relationships between individuals. We derive estimates of the number of hypervariable loci needed for a specified reliability of such an inference. Evolutionary dynamics of genetic distance statistics based on allele sharing is also studied. It shows that such measures of genetic distances remain linear with the time of divergence for a period comparable to that of the gene frequency-based measures of genetic distances. Statistical properties of measures based on allele sharing establish that for using such summary statistics it is not necessary to know the full characteristics of all loci used. It is enough to know the degree of heterozygosity per locus and the number of loci. Therefore, in principle, this approach can also be used for DNA fingerprinting data in the studies of relatedness between individuals as well as between populations. The possible compromising features of multilocus DNA fingerprinting data are also discussed.

UR - http://www.scopus.com/inward/record.url?scp=0027351936&partnerID=8YFLogxK

M3 - Review article

C2 - 8400687

AN - SCOPUS:0027351936

VL - 67

SP - 153

EP - 175

JO - EXS

JF - EXS

SN - 1023-294X

ER -