ArticleScientific reports2015
Collective effects of common SNPs in foraging decisions in Caenorhabditis elegans and an integrative method of identification of candidate genes.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 citing papers in PubMed.
- Identification of Specific Nuclear Genetic Loci and Genes That Interact With the Mitochondrial Genome and Contribute to Fecundity inFrontiers in genetics · 2019Article
- Accumulation of minor alleles and risk prediction in schizophrenia.Scientific reports · 2017Article
- An oxytocin-dependent social interaction between larvae and adult C. elegans.Scientific reports · 2017Article
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Authors and funding
4 authors.
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Abstract
Optimal foraging decision is a quantitative flexible behavior, which describes the time at which animals choose to abandon a depleting food supply. The total minor allele content (MAC) in an individual has been shown to correlate with quantitative variations in complex traits. We have studied the role of MAC in the decision to leave a food lawn in recombinant inbred advanced intercross lines (RIAILs) of Caenorhabditis elegans. We found a strong link between MAC and the food lawn leaving rates (Spearman r = 0.4, P = 0.005). We identified 28 genes of unknown functions whose expression levels correlated with both MAC and leaving rates. When examined by RNAi experiments, 8 of 10 tested among the 28 affected leaving rates, whereas only 2 of 9 did among genes that were only associated with leaving rates but not MAC (8/10 vs 2/9, P < 0.05). The results establish a link between MAC and the foraging behavior and identify 8 genes that may play a role in linking MAC with the quantitative nature of the trait. The method of correlations with both MAC and traits may find broad applications in high efficiency identification of target genes for other complex traits in model organisms and humans.
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