bioRxivEvolutionary BiologyPreprint
Pangenome-based dynamic trajectories of intracellular gene transfers in Poaceae unveil a high rate of unceasing integration and selective retention in Triticeae
Y. Chen, Y. Guo, X. Xie, Z. WangiD, L. Miao, Z. Yang, Y. Jiao, C. Xie, J. Liu, Z. Hu, M. Xin, Y. Yao, Z. Ni, Q. Sun, H. Peng, W. Guo
Abstract
Intracellular gene transfers (IGTs) between the nucleus and organelles, including plastids and mitochondria, constantly reshapes the nuclear genome during evolution. Despite the substantial contribution of IGTs to genome variation, the dynamic trajectories of IGTs at the pangenomic level remain elusive. Here, we propose a novel approach, IGTminer, to map the evolutionary trajectories of IGTs by collinearity and gene reannotation across multiple genome assemblies. IGTminer was applied to create a nuclear organelle gene (NOG) map across 67 genomes covering 15 Poaceae species, including important crops, revealing the polymorphisms and trajectory dynamics of NOGs. The NOGs produced were verified by experimental evidence and resequencing datasets. We found that most of the NOGs were recently transferred and lineage specific, and that Triticeae species tended to have more NOGs than other Poaceae species. Wheat had a higher retention rate of NOGs than maize and rice, and the retained NOGs were likely involved in the photosynthesis and translation pathways. Large numbers of NOG clusters were aggregated in hexaploid wheat during two rounds of polyploidization and contributed to the genetic diversities among modern wheat varieties. Finally, we proposed a radiocarbon-like model illustrating the transfer and elimination dynamics of NOGs, highlighting the unceasing integration and selective retention of NOGs over evolutionary time. In addition, we implemented an interactive webserver for NOG exploration in Poaceae. In summary, this study provides new resources and clues for the roles of IGTs in shaping inter- and intraspecies genome variation and driving plant genome evolution.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: clustering
- research focus: variant calling
- research focus: database / resource
- approach: deep learning
- approach: statistical model
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