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Transcriptional and mutational signatures of the Drosophila ageing germline

Abstract

Ageing is a complex biological process that is accompanied by changes in gene expression and mutational load. In many species, including humans, older fathers pass on more paternally derived de novo mutations; however, the cellular basis and cell types driving this pattern are still unclear. To explore the root causes of this phenomenon, we performed single-cell RNA sequencing on testes from young and old male Drosophila and genomic sequencing (DNA sequencing) on somatic tissues from the same flies. We found that early germ cells from old and young flies enter spermatogenesis with similar mutational loads but older flies are less able to remove mutations during spermatogenesis. Mutations in old cells may also increase during spermatogenesis. Our data reveal that old and young flies have distinct mutational biases. Many classes of genes show increased postmeiotic expression in the germlines of older flies. Late spermatogenesis-biased genes have higher dN/dS (ratio of non-synonymous to synonymous substitutions) than early spermatogenesis-biased genes, supporting the hypothesis that late spermatogenesis is a source of evolutionary innovation. Surprisingly, genes biased in young germ cells show higher dN/dS than genes biased in old germ cells. Our results provide new insights into the role of the germline in de novo mutation.

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Fig. 1: Overview of experimental design and visualization of old and young datasets.
Fig. 2: The proportion of mutated cells and mutation load across cell types for young and old flies.
Fig. 3: Age-related trends in mutational signatures.
Fig. 4: Global expression patterns of de novo genes and TEs changes with age in each cell type.
Fig. 5: dN/dS trends of cell type- and age-biased genes.

Data availability

Raw sequence data have been deposited to NCBI BioProject no. PRJNA777411.

Code availability

The code used for processing the data has been deposited at https://github.com/LiZhaoLab/Mutation_project. This repository also includes permanent links to large data files including a Seurat RDS and mutation database.

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Acknowledgements

We thank H. Duan and C. Zhao at the Genomics Resource Center of Rockefeller University for their help with the scRNA-seq libraries and members of the Zhao lab for their helpful comments and suggestions. We thank Z. Gao from UPenn for the suggestions on interpreting mutational signatures. The work was supported by National Institutes of Health MIRA no. R35GM133780, the Robertson Foundation, a Monique Weill-Caulier Career Scientist Award, a Rita Allen Foundation Scholar Program, a Vallee Scholar Program (no. VS-2020-35) and an Alfred P. Sloan Research Fellowship (no. FG-2018-10627) to L.Z.

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Authors and Affiliations

Authors

Contributions

E.W. and L.Z. conceived the study and designed the experiments and analysis. C.B.L., E.W. and N.S. performed the experiments and generated the data. E.W. performed all the analysis with input from L.Z. E.W. and L.Z. wrote the manuscript with the input from all authors.

Corresponding author

Correspondence to Li Zhao.

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The authors declare no competing interests.

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Nature Ecology & Evolution thanks Shixiang Sun and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Dot plots of key marker genes in old and young fly testes.

Split by cell type, these are the average expression values of the ‘SCT’ slot in the old (a) and young (b) Seurat objects. Color corresponds to the level of expression, and the size of the dot represents the percent of cells of a class where a gene is detected.

Extended Data Fig. 2 Correlograms of germ cells between scRNA-seq replicates.

Correlations have been split between cell types. For each cell type, replicates from each age group all correlate with Pearson’s R>0.91. Correlations were drawn from gene expression values from the ‘RNA’ slot of the Seurat object using the corrplot R package.

Extended Data Fig. 3 Age-related differential expression of genes, including genome maintenance genes.

Shown are the results of differential expression tests between old and young flies, calculated separately for each cell type. Log2 fold changes refer to the ratio between expression in young compared to old flies. P values are from a 2-sided Wilcoxon test and corrected with Bonferroni’s correction. Enrichment statistics for genome maintenance genes are in Supplementary Table 2.

Extended Data Fig. 4 Expression vs. number of SNPs detected.

We averaged the expression of every gene across every replicate and then compared the number of SNPs detected within genes with lower than mean expression (‘Low expression’, n = 310) with genes with expression greater than the mean expression of all genes (‘High expression’, n = 1488). For each group we compared genes with a two-sided Wilcoxon test, then adjusted p values with Bonferroni’s correction. There are significantly more mutations in lowly expressed genes in every replicate. Boxes represent the 75th to 25th percentiles, the top whisker represents the largest value within 1.5 times the interquartile range, and the bottom whisker represents the smallest value within 1.5 times the interquartile range of the 25th percentile.

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Witt, E., Langer, C.B., Svetec, N. et al. Transcriptional and mutational signatures of the Drosophila ageing germline. Nat Ecol Evol (2023). https://doi.org/10.1038/s41559-022-01958-x

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