Fig. 7: Characterisation of labelled kidney transcripts.

a Relationship between gene abundance in liver and kidney, stratified by labelling status within kidney. b Probability of any given gene being labelled within the kidney mRNA SLAMseq dataset. Each point below zero represents a gene that is unlabelled; each point above 1 represents a labelled gene. The probability of any gene being labelled within each group was fitted with a sigmoidal curve. c Proportion of genes labelled in the kidney, stratified by gene status in liver (mean and bootstrapped 95% CI). Genes were classified according to their labelling status in the liver in the “labelled in health” group. A gene was classified as being labelled in the liver according to the beta-binomial test depicted in Fig. 5b it was deemed abundant in liver if it was detected with an adjusted cpm > 10. The proportion of genes identified as being labelled within the kidney was then determined, stratifying the results according to whether the gene was also labelled in liver. d Abundance of “liver-enriched” and “kidney-enriched” genes pulled at random into matching cpm bins. e T > C conversion rates within “liver-enriched” and “kidney-enriched” genes with matched cpm distributions. Genes exhibiting strong 4sU-dependent labelling were first filtered out. In the RNA labelling groups, rates were higher in the liver-enriched than the kidney-enriched genes (p < 2^–16 by ANOVA and two-sided post hoc Bonferroni correction). In the Cre -ve control group, there was no difference in the T > C conversion rate between “liver-enriched” and “kidney-enriched” genes (p = 0.84). f Number of genes labelled in kidney in different experimental groups. g Abundance of genes identified as being likely transferred from liver to kidney, in liver and kidney datasets. h Our data are compatible with the transfer of dissociated thiolated nucleotides and intact RNA molecules or large fragments of RNA molecules from liver to kidney. Data from male mice; n = 6 (labelled after paracetamol), n = 6 (labelled in health), n = 5 (Cre-negative control), n = 3 (4TU-negative control), n = 3 (4sU positive control). Source data are provided as a Source Data file.