About BSA4Yeast

BSA4Yeast is a comprehensive web application that performs QTL (Quantitative Trait Loci) mapping using bulk segregant analysis (BSA) of yeast sequencing data. It has the following main advantages and features:

  • fully automated
  • multiple input file types
  • private storage space
  • comprehensive annotations
  • web-based exploration

    • A step-by-step description of the software is provided in the Use tab to facilitate QTL analyses.

    Yeast (S. cerevisiae) genomics



    The baker's yeast (Saccharomyces cerevisiae) has been used since decades in research studies on genetics, cell biology and more recently genomics. It is a model organism for population genomics than can help to gain a better understanding of genotype-phenotype relationships. Trait profiling and genome analyses show a broad phenotypic and genetic variability in this organism. Thus, it is suitable for deciphering the genetic architecture of simple and complex traits.

    QTL analysis (Quantitative Trait Locus analysis)



    Linkage mapping is a statistical approach to decipher the genetic architecture of simple and complex traits. It relies on the investigation of a progeny obtained by crossing two distinct individuals. In Bulk Segregant Analysis (BSA) based QTL mapping, deep sequencing genotyping, using next generation sequencing technologies, and mapping against genetic markers determined for the parental individuals enables the identification of genes associated with a phenotype of interest. One- or two-tailed bulk design can be applied: A one-tailed bulk design compares of samples from one extreme phenotype (e.g. short lifespan) vs. the entire distribution of phenotypes; a two-tailed bulk design compares samples from two extreme phenotypes against each other (e.g. short lifespan vs. long lifespan).

    NGS (Next Generation Sequencing)



    NGS (Next Generation Sequencing) is a new nucleic acid sequencing approaches emerged allowing to obtain fast and reliable data in a cost-efficient manner. Since 2000, the compact yeast genomes (~12Mb) serve as milestone for comparative genomics and recently for investigating intraspecies variation and the genotype-phenotype relationship combining both NGS and powerful statistical methods.

    G' statistics



    The standard approach for QTL mapping investigates the allele frequency distribution across the chromosomes. The new G-statistic has several advantages over classical allele frequency analyses: (i) G is expected to decrease more rapidly around the causal site, providing narrow QTL candidate intervals; (ii) G takes into account the strength of evidence, as determined by the sample size. However, some features of the G-statistic can also complicate analyses, since the variance in read depth contributes to the variance in G over relatively small spatial scales. The G'-statistic, a smooth version of the G-statistic, developed by Paul Magwene (see Magwene et al., 2011), provides a straightforward framework to analyze BSA sequencing data. It has for example been employed successfully to identify genes involved in yeast biofilm formation or chronological aging (Granek et al., 2013; Jung et al., 2018).