The Statistics of Bulk Segregant Analysis Using Next Generation Sequencing
By Paul M. Magwene, John H. Willis, John K. Kelly. PLoS Comput. Biol., 2011
326 citations recorded by the source corpus.
We describe a statistical framework for QTL mapping using bulk segregant analysis (BSA) based on high throughput, short-read sequencing. Our proposed approach is based on a smoothed version of the standard statistic, and takes into account variation in allele frequency estimates due to sampling of segregants to form bulks as well as variation introduced during the sequencing of bulks. Using simulation, we explore the impact of key experimental variables such as bulk size and sequencing coverage on the ability to detect QTLs. Counterintuitively, we find that relatively large bulks maximize the power to detect QTLs even though this implies weaker selection and less extreme allele frequency differences. Our simulation studies suggest that with large bulks and sufficient sequencing depth, the methods we propose can be used to detect even weak effect QTLs and we demonstrate the utility of this framework by application to a BSA experiment in the budding yeast Saccharomyces cerevisiae.
Subfields: Genetics, Molecular Biology, Plant Science
View Paper: https://www.semanticscholar.org/paper/24afd1b8a6839bef98323609a796f45e4b6fa8b6
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Citations in the corpus
- QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. (2013, background): “…of whole genome sequencing to two DNA bulks of progeny with extreme phenotypes have been reported in yeast (X-QTL; Ehrenreich et al., 2010; Wenger et al., 2010; Parts et al., 2011; Swinnen et al., 2012), and its statistical property applied to yeast was also addressed (Magwene et al., 2011).”