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Biology subjects

Suarez-Menendez, M.

Publications and source records attributed to Suarez-Menendez, M..

2 recordsLinked to original sources

Direct estimation of genome mutation rates from pedigrees in free-ranging baleen whales

Current low germline mutation rate () estimates in baleen whales have greatly influenced research ranging from assessments of whaling impacts to evolutionary cancer biology. However, the reported rates were subject to methodological errors and uncertainty. We estimated directly from pedigrees in natural populations of four baleen whale species and the results were similar to primates. The implications of revised values include pre-exploitation population sizes at 14% of previous genetic diversity-based estimates and the conclusion that in itself is insufficient to explain low cancer rates in gigantic mammals (i.e., Petos Paradox). We demonstrate the feasibility of estimating from whole genome pedigree data in natural populations, which has wide-ranging implications for the many ecological and evolutionary inferences that rely on .

genetics↗

PHFinder: Assisted detection of point heteroplasmy in Sanger sequencingchromatograms

O_LIHeteroplasmy is the presence of two or more organellar genomes (mitochondrial or plastid DNA) in an organism, tissue, cell or organelle. Heteroplasmy can be detected by visual inspection of Sanger sequencing chromatograms, where it appears as multiple peaks of fluorescence at a single nucleotide position. Visual inspection of chromatograms is both consuming and highly subjective, as heteroplasmy is difficult to differentiate from background noise. Few software solutions are available to automate the detection of point heteroplasmies, and those that are available are typically proprietary, lack customization or are unsuitable for automated heteroplasmy assessment in large datasets. C_LIO_LIHere, we present PHFinder, a Python-based, open source tool to assist in the detection of point heteroplasmies in large numbers of Sanger chromatograms. PHFinder automatically identifies point heteroplasmies directly from the chromatogram trace data. The program was tested with Sanger sequencing data from 100 humpback whale (Megaptera novaeangliae) tissue samples with known heteroplasmies. C_LIO_LIPHFinder detected most (90%) of the known heteroplasmies thereby greatly reducing the amount of visual inspection required. PHFinder is flexible, enabling explicit specification of key parameters to infer double peaks (i.e., heteroplasmies). C_LI

bioinformatics↗