Predicting the genomic resolution of bulk segregant analysis

Abstract

Bulk segregant analysis is a technique for identifying the genetic loci that underlie phenotypic trait differences. The basic approach is to compare two pools of individuals from the opposing tails of the phenotypic distribution, sampled from an interbred population. Each pool is sequenced and scanned for alleles that show divergent frequencies between the pools, indicating potential association with the observed trait differences. Bulk segregant analysis has already been successfully applied to the mapping of various quantitative trait loci in organisms ranging from yeast to maize. However, these studies have typically suffered from rather low mapping resolution, and we still lack a detailed understanding of how this resolution is affected by experimental parameters. Here, we use coalescence theory to calculate the expected genomic resolution of bulk segregant analysis for a simple monogenic trait. We first show that in an idealized interbreeding population of infinite size, the expected length of the mapped region is inversely proportional to the recombination rate, the number of generations of interbreeding, and the number of genomes sampled, as intuitively expected. In a finite population, coalescence events in the genealogy of the sample reduce the number of potentially informative recombination events during interbreeding, thereby increasing the length of the mapped region. This is incorporated into our model by an effective population size parameter that specifies the pairwise coalescence rate of the interbreeding population. The mapping resolution predicted by our calculations closely matches numerical simulations and is surprisingly robust to moderate levels of contamination of the segregant pools with alternative alleles. Furthermore, we show that the approach can easily be extended to modifications of the crossing scheme. Our framework will allow researchers to predict the expected power of their mapping experiments, and to evaluate how their experimental design could be tuned to optimize mapping resolution.

Mapping QTL associated with resistance to Pseudomonas syringae pv. actinidiae in kiwifruit (Actinidia chinensis var. chinensis)

“…Bulked DNA has been analysed using BSA methods for a wide range of species and traits ( Michelmore et al., 1991 ; Song et al., 2017 ; Dong et al., 2018 ; Sun et al., 2018 ; Xin et al., 2020 ; Li and Xu, 2022 ; Shen and Messer, 2022 ). The approach taken here used BSA analysis methods to identify alleles for Psa resistance by measuring the shift in allele frequency of an A. chinensis var.…”

“…This investigation was carried out by using a technique called bulk segregant analysis (BSA), which aimed to gain insights into the genetic makeup related to resistance and susceptibility to Psa. BSA operates by assessing alterations in allele frequencies between populations that have segregated due to the pressures of selection, resembling a selection map ( Michelmore et al., 1991 ; Wisser et al., 2008 ; Magwene et al., 2011 ; Li and Xu, 2022 ; Shen and Messer, 2022 ). The BSA technique has been used for the detection of QTL for target traits in various species, including dwarfing in watermelon ( Dong et al., 2018 ), cotyledon colour in soybean ( Song et al., 2017 ), cold resistance in rice ( Sun et al., 2018 ), resistance to ascochyta blight in chickpea ( Deokar et al., 2019 ), and kernel length-width ratio in wheat ( Xin et al., 2020 ).…”

“…The BSA technique has been used for the detection of QTL for target traits in various species, including dwarfing in watermelon ( Dong et al., 2018 ), cotyledon colour in soybean ( Song et al., 2017 ), cold resistance in rice ( Sun et al., 2018 ), resistance to ascochyta blight in chickpea ( Deokar et al., 2019 ), and kernel length-width ratio in wheat ( Xin et al., 2020 ). A typical BSA investigates loci that differ between sample bulks segregating for a trait of interest, combining ideas from linkage mapping and GWAS ( Michelmore et al., 1991 ; Li and Xu, 2022 ; Shen and Messer, 2022 ). Like classical linkage mapping, most BSA trials are designed using two parents with different phenotypes.…”

“…Individuals from the last generation are selected to form two bulks that segregate for the phenotype of interest. Thus, alleles affecting the target phenotype should show a significant difference in frequency between the two bulks, while unselected alleles should remain in both bulks at similar frequencies ( Michelmore et al., 1991 ; Shen and Messer, 2022 ). Diverging from the typical BSA, bulks can be analysed with BSA directly from F 1 populations ( Dai et al., 2018 ; Guan et al., 2019 ).…”

Evolutionary genetics of nonself recognition regarding social and sexual interactions of fungi

“…These pools are then sequenced and allelic differences between pools are expected to be highest near the causal genes. BSA is limited by the number of recombination events (Shen & Messer, 2022) and does not allow for finer analyses due to the pooled DNA. A more recent alternative is low-coverage sequencing, where each individual is sequenced at ±0.1-1.0X, much lower than the standard 30X sequencing for most genome analyses.…”