AI for Drug Discovery
Marianna Rapsomaniki, Jannis Born, et al.
AMLD EPFL 2024
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 inthis regionare 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-I, 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. Copyright © 2008 by the Genetics Society of America.
Marianna Rapsomaniki, Jannis Born, et al.
AMLD EPFL 2024
Varun S Sharma, Andrea Fossati, et al.
Briefings in Bioinformatics
Tiziana Mordasini, Alessandro Curioni, et al.
ChemBioChem
Seung Gu Kang, Jeff Weber, et al.
ACS Fall 2023