Year: 2026
Type: preprint
Abstract: ABSTRACT The traits of an organism depend on its genetic background and environment. Bulk segregant analysis (BSA) maps quantitative trait loci (QTL) by measuring parental allele frequencies in pools of genetically recombined progeny (segregants). Conventional BSA requires laborious separate sample handling for each cross and environmental condition. Here, we describe a 96-well liquid format for extreme QTL mapping (X-QTL) in Saccharomyces cerevisiae . We crossed 40 isolates to a common parent carrying mating-type-specific drug-resistance markers at HO , which enabled us to select diploids and haploid segregants in 1 mL cultures. Each well held one segregant pool, which we then grew in deep wells in four conditions: the standard glucose medium, sodium chloride or caffeine added to the standard medium, or acetate replacing glucose as a carbon source. We barcoded DNA samples from each of 384 wells and sequenced them in one Illumina Nova-seq X run. Sequencing data for 181 segregant pools passed quality control steps and was used to map 1,472 QTL in 35 crosses. We replicated a subset of QTL previously mapped in these growth conditions by conventional X-QTL. The 96-well approach increases the throughput of every step of X-QTL, enabling genetic analysis of many more cross and conditions. ARTICLE SUMMARY The traits of an organism are shaped by its genes and environment. A standard approach to find the genetic differences that underlie trait variation in model organisms is to mate two genetically distinct individuals, grow a large number of their offspring in an environmental condition of interest, and compare the frequencies of parental alleles across the genome between a control pool of offspring and a pool that represents a phenotypic tail of improved growth in that condition. We developed a method to adapt this approach to small liquid volumes, enabling genetic analysis of many crosses and conditions in parallel. We applied the method to 40 crosses and 4 conditions and found many regions of the genome where a difference between the parents influenced growth.
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W7221986625