iSeq: A New Double-Barcode Method for Detecting Dynamic Genetic Interactions in Yeast

Abstract

Systematic screens for genetic interactions are a cornerstone of both network and systems biology. However, most screens have been limited to characterizing interaction networks in a single environment. Moving beyond this static view of the cell requires a major technological advance to increase the throughput and ease of replication in these assays. Here, we introduce iSeq—a platform to build large double barcode libraries and rapidly assay genetic interactions across environments. We use iSeq in yeast to measure fitness in three conditions of nearly 400 clonal strains, representing 45 possible single or double gene deletions, including multiple replicate strains per genotype. We show that iSeq fitness and interaction scores are highly reproducible for the same clonal strain across replicate cultures. However, consistent with previous work, we find that replicates with the same putative genotype have highly variable genetic interaction scores. By whole-genome sequencing 102 of our strains, we find that segregating variation and de novo mutations, including aneuploidy, occur frequently during strain construction, and can have large effects on genetic interaction scores. Additionally, we uncover several new environment-dependent genetic interactions, suggesting that barcode-based genetic interaction assays have the potential to significantly expand our knowledge of genetic interaction networks.

Mapping DNA damage‐dependent genetic interactions in yeast via party mating and barcode fusion genetics

“…Ten of those pairs corresponded to strains with GIS r < 0.5 and other 10 with GIS r > 0.5. We found that all 10 strain pairs with GIS r < 0.5 had chromosome V duplicated in one of the two strains, in agreement with the report of iSeq strains showing low strain profile reproducibility, owing to this same chromosome V duplication (Jaffe et al , ). Chromosome V contains the CAN1 locus, the locus at which both BFG‐GI recipients and iSeq strain constructs are inserted.…”

“…The remaining 15% of biological replicates showing low correlations could be identified and removed computationally. We concur with the iSeq study (Jaffe et al , ) that aneuploidies in chromosome V are the main factor contributing to the replicates with low reproducibility. Chromosome V carries both CAN1 and URA3 loci, which were replaced by selection markers in the iSeq protocol (Jaffe et al , ), while CAN1 was replaced by the recipient constructs in BFG‐GI.…”

“…We concur with the iSeq study (Jaffe et al , ) that aneuploidies in chromosome V are the main factor contributing to the replicates with low reproducibility. Chromosome V carries both CAN1 and URA3 loci, which were replaced by selection markers in the iSeq protocol (Jaffe et al , ), while CAN1 was replaced by the recipient constructs in BFG‐GI. Thus, de novo structural variation around these loci during strain construction could explain the low correlation between some pairs of biological replicates.…”

“…In the BFG‐GI protocol, once the donor and recipient barcodes are fused, the “relic” donor plasmid is counter‐selected with 5‐FOA to reduce the chance of undesired recombination events. We concur with Jaffe et al () who suggest that future protocols using constructs located on plasmids, such as the one we used with the proDonor strains, or at other chromosomal loci could eliminate this issue. Despite this issue, the BFG‐GI method proved to be highly accurate when compared with previous benchmark studies.…”

Aneuploidy in yeast: Segregation error or adaptation mechanism?

“…Number of aneuploidy incidents as a function of chromosome size. Data was extracted from eight sources (Duan et al, ; Gallone et al, ; Jaffe et al, ; Kao et al, ; Peter et al, ; Selmecki et al, ; Sharp et al, ; Zhu et al, ), with a total of 1,207 aneuploidies between them. Chromosomes are labelled with Roman numerals…”