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:
multiple input file types
private storage space
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.
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).
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