Transposition, duplication, and divergence of the telomerase RNA underlies the Mimulus telomere evolution
Kumawat, S.; Martinez, I.; Logeswaran, D.; Chen, H.; Coughlan, J.; Chen, J.; Yuan, Y.-w.; Sobel, J.; Choi, J. Y.
Show abstract
Telomeres are nucleoprotein complexes with a crucial role of protecting chromosome ends. It consists of simple repeat sequences and dedicated telomere-binding proteins. Because of its vital functions, components of the telomere, for example its sequence, should be under strong evolutionary constraint. But across all plants, telomere sequences display a range of variation and the evolutionary mechanism driving this diversification is largely unknown. Here, we discovered in Monkeyflower (Mimulus) the telomere sequence is even variable between species. We investigated the basis of Mimulus telomere sequence evolution by studying the long noncoding telomerase RNA (TR), which is a core component of the telomere maintenance complex and determines the telomere sequence. We conducted total RNA-based de novo transcriptomics from 16 Mimulus species and analyzed reference genomes from 6 species, and discovered Mimulus species have evolved at least three different telomere sequences: (AAACCCT)n, (AAACCCG)n, and (AAACCG)n. Unexpectedly, we discovered several species with TR duplications and the paralogs had functional consequences that could influence telomere evolution. For instance, M. lewisii had two sequence-divergent TR paralogs and synthesized a telomere with sequence heterogeneity, consisting of AAACCG and AAACCCG repeats. Evolutionary analysis of the M. lewisii TR paralogs indicated it had arisen from a transposition-mediate duplication process. Further analysis of the TR from multiple Mimulus species showed the gene had frequently transposed and inserted into new chromosomal positions during Mimulus evolution. From our results, we propose the TR transposition, duplication, and divergence model to explain the evolutionary sequence turnovers in Mimulus and potentially all plant telomeres.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Chromosome level genome assembly and annotation of highly invasive Japanese stiltgrass (Microstegium vimineum) 96%
- Synteny identifies reliable orthologs for phylogenomics and comparative genomics of the Brassicaceae 95%
- The mitogenome of Norway spruce and a reappraisal of mitochondrial recombination in plants 95%
Similar papers in this journal
- Jack of all trades: genome assembly of Wild Jack and comparative genomics of Artocarpus 97%
- Hybridization history and repetitive element content in the genome of a homoploid hybrid, Yucca gloriosa (Asparagaceae) 95%
- Mitochondrial fostering: the mitochondrial genome may play a role in plant orphan gene evolution 95%
Similar papers in this journal
- Aiming off the target: studying repetitive DNA using target capture sequencing reads 96%
- Expanding the Triangle of U: The genome assembly of Hirschfeldia incana provides insights into chromosomal evolution, phylogenomics and high photosynthesis-related traits 95%
- More than a prickly morphology: plastome variation in the prickly pear cacti (Opuntieae) 95%
Similar papers in this journal
- Whole Genome Assembly and Annotation of Northern Wild Rice, Zizania palustris L., Supports a Whole Genome Duplication in the Zizania Genus 96%
- Comparative Genomics of Six Juglans Species Reveals Patterns of Disease-associated Gene Family Contractions. 96%
- Satellite DNA landscapes after allotetraploidisation of quinoa (Chenopodium quinoa) reveal unique A and B subgenomes 95%
Similar papers in this journal
- Genomic diversity and evolution in the Hawaiian Islands endemic Kokia (Malvaceae) 96%
- Comparative transcriptomics reveals divergence in pathogen response gene families amongst 20 forest tree species 96%
- Conserving a threatened North American walnut: a chromosome-scale reference genome for butternut (Juglans cinerea) 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.