Genome-wide screen for modifiers of Na (+) /K (+) ATPase alleles identifies critical genetic loci

Abstract

Background: Mutations affecting the Na (+) / K (+) ATPase (a.k.a. the sodium-potassium pump) genes cause conditional locomotor phenotypes in flies and three distinct complex neurological diseases in humans. More than 50 mutations have been identified affecting the human ATP1A2 and ATP1A3 genes that are known to cause rapid-onset Dystonia Parkinsonism, familial hemiplegic migraine, alternating hemiplegia of childhood, and variants of familial hemiplegic migraine with neurological complications including seizures and various mood disorders. In flies, mutations affecting the ATPalpha gene have dramatic phenotypes including altered longevity, neural dysfunction, neurodegeneration, myodegeneration, and striking locomotor impairment. Locomotor defects can manifest as conditional bang-sensitive (BS) or temperature-sensitive (TS) paralysis: phenotypes well-suited for genetic screening.

Results: We performed a genome-wide deficiency screen using three distinct missense alleles of ATPalpha and conditional locomotor function assays to identify novel modifier loci. A secondary screen confirmed allele-specificity of the interactions and many of the interactions were mapped to single genes and subsequently validated. We successfully identified 64 modifier loci and used classical mutations and RNAi to confirm 50 single gene interactions. The genes identified include those with known function, several with unknown function or that were otherwise uncharacterized, and many loci with no described association with locomotor or Na(+)/K(+) ATPase function.

Conclusions: We used an unbiased genome-wide screen to find regions of the genome containing elements important for genetic modulation of ATPalpha dysfunction. We have identified many critical regions and narrowed several of these to single genes. These data demonstrate there are many loci capable of modifying ATPalpha dysfunction, which may provide the basis for modifying migraine, locomotor and seizure dysfunction in animals.

Figure 1

Distribution of phenotypic modifiers identified through a deficiency screen. A-C) ATPalpha mutant animals also bearing individual unique chromosomal deficiencies (Df) were assayed for conditional locomotor function to identify modifiers. The data reveal a largely normal distribution centered around a typical response (blue) for each mutant. Those deviating from the typical response were termed putative enhancers (yellow) or suppressors (red). A) ATPalpha ^CJ5 , Df double mutants and B) ATPalpha ^CJ10 , Df double mutants were assayed for recovery from mechanical stress at adult day 15. C) ATPalpha ^DTS1 , Df double mutants were assayed for time to TS paralysis on adult day 1. A-C) The mean response is shown as a dashed green line. +/− 0.5 Std. Dev. are indicated by gray shading.

Figure 2

Schematic of the deficiency screen workflow. Using the Bloomington deficiency kit, 1137 initial interactions were screened using ATPalpha ^CJ5, ATPalpha ^CJ10, or ATPalpha ^DTS1. Putative enhancers and suppressors were selected for verification with a larger sample size. Any verified interacting deficiencies were deemed critical intervals. Once critical intervals were selected a screen for single gene modifiers from within the intervals was performed using available classical mutants and transgenic RNAi strains. If a modifier was found it was retested with other ATPalpha alleles to determine whether the interaction was allele-specific.

Figure 3

Distribution of validated genetic modifiers. A. Protein function of modifiers, as annotated on flybase.org, grouped into major categories. Stj, rasp, slmb, Rpl41/NaCP60E, and punch were included in two categories. B. Modifier loci categorized according to mutant phenotypes (when available). FKBP59, Cact, Scramb1, and Stj were associated with two phenotypic categories.

Figure 4

Genetic interaction between Galectin and ATPalpha . Galectin; ATPalpha double mutants and ATPalpha*, Galectin RNAi flies for each ATPalpha mutant were assayed and compared to ATPalpha* heterozygous controls. The RNAi knockdown was driven ubiquitously with daughterless-Gal4 (daGAL4). The genotypes in each graph are: ATPalpha*/+ (green), Galectin ^DG25505 /+;ATPalpha*/+ (red), daGal4,ATPalpha*/+ (blue), and Galectin-RNAi/+;daGal4,ATPalpha*/+ (orange). Galectin mutants significantly enhanced the ATPalpha ^DTS1 phenotype while galectin-RNAi significantly suppress ATPalpha ^CJ5 and ATPalpha ^CJ10 phenotypes. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 5

Genetic interaction between Spz5 and ATPalpha . ATPalpha/Spz5 double mutants and ATPalpha*, Spz5 RNAi flies for each ATPalpha mutant were assayed and compared to ATPalpha* heterozygous controls. The RNAi knockdown was driven with da-Gal4. The genotypes in each graph are: ATPalpha*/+ (green), Spz5 ^E03444 /ATPalpha* (red), daGal4,ATPalpha*/+ (blue), and Spz5-RNAi/daGal4,ATPalpha* (orange). Spz5 mutants significantly enhanced the ATPalpha ^DTS1 phenotype but Spz5 RNAI significantly suppresses the ATPalpha ^DTS1 phenotype. The ATPalpha ^CJ10 phenotype is suppressed in both the Spz5 mutant and RNAi. The ATPalpha ^CJ5 phenotype was not significantly affected by loss of Spz5. *p < 0.05, **p < 0.01, ***p < 0.001.

Figure 6

Genetic interactions between FKBP59 and ATPalpha . FKBP59; ATPalpha double mutants and ATPalpha*, FKBP59 RNAi flies were assayed and compared to ATPalpha* heterozygous controls. The RNAi knockdown was driven with da-Gal4. The genotypes in each graph are: ATPalpha*/+ (green), FKBP59 ^E03444 /+; ATPalpha*/+ (red), daGal4,ATPalpha*/+ (blue), and FKBP59-RNAi/+;daGal4,ATPalpha*/+ (orange). FKBP59 mutants significantly enhanced the ATPalpha ^DTS1 phenotype. The ATPalpha ^CJ5 phenotype is suppressed by both the FKBP59 mutant and RNAi. *p < 0.05, **p < 0.01, ***p < 0.001.