How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic effects

Abstract

For a given gene, different mutations influence organismal phenotypes to varying degrees. However, the expressivity of these variants not only depends on the DNA lesion associated with the mutation, but also on factors including the genetic background and rearing environment. The degree to which these factors influence related alleles, genes, or pathways similarly, and whether similar developmental mechanisms underlie variation in the expressivity of a single allele across conditions and among alleles is poorly understood. Besides their fundamental biological significance, these questions have important implications for the interpretation of functional genetic analyses, for example, if these factors alter the ordering of allelic series or patterns of complementation. We examined the impact of genetic background and rearing environment for a series of mutations spanning the range of phenotypic effects for both the scalloped and vestigial genes, which influence wing development in Drosophila melanogaster. Genetic background and rearing environment influenced the phenotypic outcome of mutations, including intra-genic interactions, particularly for mutations of moderate expressivity. We examined whether cellular correlates (such as cell proliferation during development) of these phenotypic effects matched the observed phenotypic outcome. While cell proliferation decreased with mutations of increasingly severe effects, surprisingly it did not co-vary strongly with the degree of background dependence. We discuss these findings and propose a phenomenological model to aid in understanding the biology of genes, and how this influences our interpretation of allelic effects in genetic analysis.

Complex genetic interactions of novel Suppressor of Hairless alleles deficient in co-repressor binding

“…We noted a high degree of variations, however, between independent experiments as well as between lines with formally identical genetic background. Similarly, high variability was observed amongst the three controls N 5419 /+ (derived from N 5419 /FM7c x Oregon R), N 5419 / y 1 w 67c23 , and N 5419 /+; Su(H) gwt /+ ( Fig 3 ) in line with the background sensitivity of N phenotypes [ 6 , 41 – 44 ]. In fact, Su(H) attP did not vary significantly from these controls, and neither did Su(H) LLF .…”

“…Notch mutants were originally picked up by their characteristic notched wing phenotype observed in heterozygous females [ 6 , 39 ] ( Fig 3 ). This phenotype is exquisitely sensitive to genetic background [ 6 , 39 – 41 ], and can be completely rescued by reducing the gene dose of Delta or Hairless [ 42 – 44 ]. We reasoned that H-binding deficient Su(H) alleles might behave similar to H mutants in this context, as we expected them to gain Notch activity, whereas Su(H) null alleles were expected to enhance loss of Notch activity.…”

UDP-GLYCOSYLTRANSFERASE 72E3 Plays a Role in Lignification of Secondary Cell Walls in Arabidopsis

“…To confirm the specificity of the UGT72E3 gene mutation effect and evaluate a possible functional redundancy with UGT72E1 and UGT72E2 , lignin was quantified in the double ugt72e1,2 mutant used as a control. Indeed, mutant complementation is often used to gain knowledge on the role of a particular gene, but has many disadvantages such as position effect of the T-DNA [ 32 ] carrying the non-mutated gene along with the variability of transgene expression by RNA sensing mechanisms [ 33 ] but also possible influences of environmental parameters [ 34 ].…”

Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility

“…Despite these QC advantages, we argue that it is the re-use of lines between studies that will prove key to accounting for variation within these models (Volpato et al, 2018). The genetic background significantly contributes to iPSC cellular heterogeneity (Box 1), including differentiation potency, cellular morphology and gene expression variation (Chandler et al, 2017;Kilpinen et al, 2017). Thus, the effect of a variant of interest must be disentangled from the unique genetic backgrounds of the studied lines.…”