Abstract
Bulk segregant analysis (BSA) using microarrays, and extreme array mapping (XAM) have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP) between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP) genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.
Highlights
Mapping the causal allele or alleles for a particular trait is one of the most common methods for learning about the genetic processes underlying biological function
While the signal from an array used for single feature polymorphisms (SFP) measurements is the intensity of hybridization to a single probe, the signal from a Single Nucleotide Polymorphism (SNP) array is the difference in hybridization between the probe with allele 1 at the central base and the probe with allele 2 at the central base
ATSNPTILE array was designed with reference to the Col-0 sequence, so each SNP set has probes for the Col-0 allele and the alleles are compared so that preferential hybridization to the Col-0 allele will result in a positive signal and preferential hybridization to the other allele will result in a negative signal
Summary
Mapping the causal allele or alleles for a particular trait is one of the most common methods for learning about the genetic processes underlying biological function. The microarray genotyping approach was later extended to BSA-based investigations of quantitative traits where the pools were selected from the extreme ends of phenotypes in a continuously variable population This process, called eXtreme Array Mapping (XAM), has successfully mapped Quantitative Trait Loci (QTL) in Arabidopsis and offers a time-efficient and cost-effective method of discovering new QTL [11]. In the case of Arabidopiss, a SNP array was constructed with the ability to interrogate over 200,000 SNPs and this array has been used to genotype over 1,000 natural accessions [12,13 and unpublished data from the Nordborg and Borevitz labs] These resources provide thousands of SNP markers between almost any two lines of the thousands of Arabidopsis (closely related lines will have fewer SNPs). Our method is adaptable for use with SNP arrays for other species
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