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. 2024 Dec 5:2024:10.17912/micropub.biology.001235.
doi: 10.17912/micropub.biology.001235. eCollection 2024.

A ubiquinone precursor analogue does not clearly increase the growth rate of Caenorhabditis inopinata

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A ubiquinone precursor analogue does not clearly increase the growth rate of Caenorhabditis inopinata

Gavin C Woodruff et al. MicroPubl Biol. .

Abstract

The evolution of developmental rates may drive morphological change. Caenorhabditis inopinata develops nearly twice as slowly as Caenorhabditis elegans . clk-1 encodes a hydroxylase required for synthesizing ubiquinone, and mutant clk-1 slow growth phenotypes can be rescued by supplying animals with a ubiquinone precursor analogue, 2,4-dihydroxybenzoate. RNA-seq data showing low clk-1 expression raised the possibility that C. inopinata grows slowly because of reduced ubiquinone biosynthesis. C. inopinata did not reveal a clear reduction in the age of maturation when reared on 2,4-dihydroxybenzoate. Further scrutiny of RNA-seq results revealed multiple ubiquinone metabolism genes have low expression in C. inopinata . Divergent clk-1 expression alone may not be a major driver of the evolution of slow development in this species.

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Conflict of interest statement

The authors declare that there are no conflicts of interest present.

Figures

Figure 1. A ubiquinone precursor analogue does not clearly increase the growth rate of
<i>C. inopinata</i>
Figure 1. A ubiquinone precursor analogue does not clearly increase the growth rate of C. inopinata
( a ) clk-1 exhibits a one-fold decrease in expression across three developmental stages in C. inopinata compared to C. elegans . Data from (Woodruff et al. 2024). ( b ) Estimates of developmental timing were made with logistic models. For a given plate, the number of worms at a given developmental stage (in this example, the L4 stage) were counted at least once per day until all animals reached adulthood. The number of worms younger than the L4 stage (Milestone status = 0) or at the L4 stage and older (Milestone status = 1) were plotted over time. A logistic model was fit to this data (solid blue line), and the time at which 50% of the animals were predicted to have passed the milestone was determined (dotted and dashed lines). These estimates of median time to the developmental milestone were then plotted (c) and analyzed. ( c ) The timing of developmental events on DHB. The y-axis represents the median time to the developmental milestone as inferred in (b). Each point represents a plate. Sina plots are strip charts with points taking the contours of a violin plot; black bars represent means. C. elegans WT, PD1074; C. elegans (clk-1) , MQ130; C. inopinata WT, NKZ35. The different facets represent the times to the L4 and adult developmental milestones. ( d ) Cohen's d effect sizes of DHB compared to NGM plates without the compound (using the data shown in (c)). Positive values represent faster developmental rates on DHB. Error bars represent 95% confidence intervals generated with one thousand bootstrap replicates of the data. ( e ) Many ubiquinone synthesis pathway genes are downregulated in C. inopinata . Plotted are the log 2 fold changes in RNA expression of ubiquinone synthesis pathway genes at each developmental stage between C. elegans and C. inopinata . Data from (Woodruff et al. 2024 G3 ). Genes included here are homologs of yeast genes previously reported to contribute to the synthesis of ubiquinone from synthetic analogues (Xie et al. 2012). R144.13 is a homolog of the yeast gene COQ10 (by best reciprocal blastp hit). Y62E10A.6 is a homolog of the yeast gene ARH1 (by best reciprocal blastp hit), which may participate in ubiquinone synthesis (Pierrel et al. 2010). There are no clear single-copy orthologs of the yeast gene COQ9 in C. elegans . YAH1 (implicated in ubiquinone synthesis in yeast (Pierrel et al. 2010)) has a single-copy ortholog in C. elegans (Y73F8A.27), but this gene has no clear best-reciprocal blast hit in C. inopinata . clk-1 is the nematode homolog of the yeast gene COQ7 . All p -values were corrected for multiple tests, and error bars represent 95% confidence intervals (see (Woodruff et al. 2024) for details regarding RNA-seq data and analysis).

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