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Marker Density and Read Depth for Genotyping Populations Using Genotyping-by-Sequencing

Genotyping-by-sequencing (GBS) approaches provide low-cost, high-density genotype information. However, GBS has unique technical considerations, including a substantial amount of missing data and a nonuniform distribution of sequence reads. The goal of this study was to characterize technical variat...

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Detalles Bibliográficos
Autores principales: Beissinger, Timothy M., Hirsch, Candice N., Sekhon, Rajandeep S., Foerster, Jillian M., Johnson, James M., Muttoni, German, Vaillancourt, Brieanne, Buell, C. Robin, Kaeppler, Shawn M., de Leon, Natalia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3606087/
https://www.ncbi.nlm.nih.gov/pubmed/23410831
http://dx.doi.org/10.1534/genetics.112.147710
Descripción
Sumario:Genotyping-by-sequencing (GBS) approaches provide low-cost, high-density genotype information. However, GBS has unique technical considerations, including a substantial amount of missing data and a nonuniform distribution of sequence reads. The goal of this study was to characterize technical variation using this method and to develop methods to optimize read depth to obtain desired marker coverage. To empirically assess the distribution of fragments produced using GBS, ∼8.69 Gb of GBS data were generated on the Zea mays reference inbred B73, utilizing ApeKI for genome reduction and single-end reads between 75 and 81 bp in length. We observed wide variation in sequence coverage across sites. Approximately 76% of potentially observable cut site-adjacent sequence fragments had no sequencing reads whereas a portion had substantially greater read depth than expected, up to 2369 times the expected mean. The methods described in this article facilitate determination of sequencing depth in the context of empirically defined read depth to achieve desired marker density for genetic mapping studies.