ArticleG3 (Bethesda, Md.)2024
The effect of developmental variation on expression QTLs in a multi parental Caenorhabditis elegans population.
Article in G3 (Bethesda, Md.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- From aerial drone to quantitative trait locus: leveraging next-generation phenotyping to reveal the genetics of color and height in field-grown Lactuca sativa.The Plant journal : for cell and molecular biology · 2025Article
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5 authors at 2 institutions in 1 country.
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Abstract
Regulation of gene expression plays a crucial role in developmental processes and adaptation to changing environments. expression quantitative trait locus (eQTL) mapping is a technique used to study the genetic regulation of gene expression using the transcriptomes of recombinant inbred lines (RILs). Typically, the age of the inbred lines at the time of RNA sampling is carefully controlled. This is necessary because the developmental process causes changes in gene expression, complicating the interpretation of eQTL mapping experiments. However, due to genetics and variation in ambient micro-environments, organisms can differ in their "developmental age," even if they are of the same chronological age. As a result, eQTL patterns are affected by developmental variation in gene expression. The model organism Caenorhabditis elegans is particularly suited for studying the effect of developmental variation on eQTL mapping patterns. In a span of days, C. elegans transitions from embryo through 4 larval stages to adult while undergoing massive changes to its transcriptome. Here, we use C. elegans to investigate the effect of developmental age variation on eQTL patterns and present a normalization procedure. We used dynamical eQTL mapping, which includes the developmental age as a cofactor, to separate the variation in development from genotypic variation and explain variation in gene expression levels. We compare classical single marker eQTL mapping and dynamical eQTL mapping using RNA-seq data of ∼200 multi-parental RILs of C. elegans. The results show that (1) many eQTLs are caused by developmental variation, (2) most trans-bands are developmental QTLs, and (3) dynamical eQTL mapping detects additional eQTLs not found with classical eQTL mapping. We recommend that correction for variation in developmental age should be strongly considered in eQTL mapping studies given the large impact of processes like development on the transcriptome.
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