American University
Browse

Regional sequence expansion or collapse in heterozygous genome assemblies

Download (4.15 MB)
journal contribution
posted on 2023-08-05, 12:53 authored by Kathryn Celestia Asalone, Kara M. Ryan, Maryam Yamadi, Annastelle L. Cohen, William G. Farmer, Deborah J. George, Claudia Joppert, Kaitlyn Kim, Madeeha F. Mughal, Rana Said, Metin Toksoz-Exley, Evgeny Bisk, John BrachtJohn Bracht

High levels of heterozygosity present a unique genome assembly challenge and can adversely impact downstream analyses, yet is common in sequencing datasets obtained from non-model organisms. Here we show that by re-assembling a heterozygous dataset with variant parameters and different assembly algorithms, we are able to generate assemblies whose protein annotations are statistically enriched for specific gene ontology categories. While total assembly length was not significantly affected by assembly methodologies tested, the assemblies generated varied widely in fragmentation level and we show local assembly collapse or expansion underlying the enrichment or depletion of specific protein functional groups. We show that these statistically significant deviations in gene ontology groups can occur in seemingly high-quality assemblies, and result from difficult-to-detect local sequence expansion or contractions. Given the unpredictable interplay between assembly algorithm, parameter, and biological sequence data heterozygosity, we highlight the need for better measures of assembly quality than N50 value, including methods for assessing local expansion and collapse.

History

Publisher

PLoS Computational Biology

Notes

PLoS Computational Biology, Volume 16, Issue 7, July 2020, Article number e1008104.

Handle

http://hdl.handle.net/1961/auislandora:85523

Usage metrics

    Biology

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC