Biology subjects

Young, C. C.

Publications and source records attributed to Young, C. C..

3 recordsLinked to original sources

bioRxiv2025

Population genetics of the endangered narrowly endemic Island Marble butterfly (Euchloe ausonides insulanus)

The Island Marble butterfly (Euchloe ausonides insulanus) is an endangered species endemic to the San Juan Islands off the coast of Washington State, United States, and British Columbia, Canada. The species was thought to be extinct for [~]90 years before it was rediscovered at American Camp, San Juan Island National Historical Park in 1998. Here, we report the results of the first population genetic analyses for insulanus, using DNA collected non-invasively from individuals in the last known stronghold for the species. We used DNA extracted from meconium, larval exuviae, and natural mortalities to generate and test thirteen new microsatellite markers to estimate genetic diversity, population structure, and kinship. We assembled and annotated mitochondrial genomes, which were used alongside museum specimens of insulanus collected [~]100 years ago from Vancouver Island, and other members of the E. ausonides species complex, to infer the evolutionary history of the species. The results indicated that insulanus experiences low heterozygosity, a small effective population size (Ne), and low allelic diversity. High levels of inbreeding were found in some individuals, but inbreeding was uneven across the population. No population structure or partitioning of genetic variation by host plant was detected. The mitogenomes of extant insulanus were all identical and modern samples showed a loss of allelic diversity compared to insulanus from museums. Extant insulanus formed a clade with museum specimens and we identified multiple putatively diagnostic alleles to differentiate insulanus from other subspecies. Based on these results, we outline considerations for species management and genetic monitoring.

genetics↗

bioRxiv2023

Development and validation of a reliable DNA copy-number-based machine learning algorithm (CopyClust) for breast cancer integrative cluster classification

The Integrative Clusters (IntClusts) provide a framework for the classification of breast cancer tumors into 10 distinct genomic subtypes based on DNA copy number and gene expression. Current classifiers achieve only low accuracy without gene expression data, warranting the development of new approaches to copy-number-only-based IntClust classification. A novel XGBoost-driven classification algorithm, CopyClust, was trained using genomic features from METABRIC and validated on TCGA achieving a nine-percentage point or greater improvement in overall IntClust subtype classification accuracy.

genomics↗

bioRxiv2019

Evaluation of ACMG Rules for In silico Evidence Strength Using An Independent Computational Tool Absent of Circularities on ATM and CHEK2 Breast Cancer Cases and Controls

The American College of Medical Genetics and Genomics (ACMG) guidelines for sequence variant classification include two criteria, PP3 and BP4, for combining computational data with other evidence types contributing to sequence variant classification. PP3 and BP4 assert that computational modeling can provide \"Supporting\" evidence for or against pathogenicity within the ACMG framework. Here, leveraging a meta-analysis of ATM and CHEK2 breast cancer case-control mutation screening data, we evaluate the strength of evidence determined from the relatively simple computational tool Align-GVGD. Importantly, application of Align-GVGD to these ATM and CHEK2 data is free of logical circularities, hidden multiple testing, and use of other ACMG evidence types. For both genes, rare missense substitutions that are assigned the most severe Align-GVGD grade exceed a \"Moderate pathogenic\" evidence threshold when analyzed in a Bayesian framework; accordingly, we argue that the ACMG classification rules be updated for well-calibrated computational tools. Additionally, congruent with previous analyses of ATM and CHEK2 case-control mutation screening data, we find that both genes have a considerable burden of pathogenic missense substitutions, and that severe ATM rare missense have increased odds ratios compared to truncating and splice junction variants, indicative of a potential dominant-negative effect for those missense substitutions.

genetics↗