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Maximum-Likelihood Estimation of Site-Specific Mutation Rates in Human Mitochondrial DNA From Partial Phylogenetic Classification.

Authors :
Rosset, Saharon
Wells, R. Spencer
Soria-Hernanz, David F.
Tyler-Smith, Chris
Royyuru, Ajay K.
Behar, Doron M.
Source :
Genetics. Nov2008, Vol. 180 Issue 3, p1511-1524. 14p.
Publication Year :
2008

Abstract

The mitochondrial DNA hypervariable segment I (HVS-I) is widely used in studies of human evolutionary genetics, and therefore accurate estimates of mutation rates among nucleotide sites in this region are essential. We have developed a novel maximum-likelihood methodology for estimating site-specific mutation rates from partial phylogenetic information, such as haplogroup association. The resulting estimation problem is a generalized linear model, with a nonstandard link function. We develop inference and bias correction tools for our estimates and a hypothesis-testing approach for site independence. We demonstrate our methodology using 16,609 HVS-I samples from the Genographic Project. Our results suggest that mutation rates among nucleotide sites in HVS-I are highly variable. The 16,400-16,500 region exhibits significantly lower rates compared to other regions, suggesting potential functional constraints. Several loci identified in the literature as possible termination-associated sequences (TAS) do not yield statistically slower rates than the rest of HVS-l, casting doubt on their functional importance. Our tests do not reject the null hypothesis of independent mutation rates among nucleotide sites, supporting the use of site-independence assumption for analyzing HVS-I. Potential extensions of our methodology include its application to estimation of mutation rates in other genetic regions, like Y chromosome short tandem repeats. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00166731
Volume :
180
Issue :
3
Database :
Academic Search Index
Journal :
Genetics
Publication Type :
Academic Journal
Accession number :
35950181
Full Text :
https://doi.org/10.1534/genetics.108.091116