A Collinearity-incorporating Homology Inference Strategy for Connecting Emerging Assemblies in Triticeae Tribe as a Pilot Practice in the Plant Pangenomic Era.
2020
ABSTRACT Plant genome sequencing has dramatically increased, and some species even have multiple high-quality reference versions. Demands for clade-specific homology inference and analysis have increased in pangenomic era. We proposed a novel method, GeneTribe ( https://chenym1.github.io/genetribe/ ), for homology inference among genetically similar genomes that incorporates gene collinearity and shows better performance than traditional sequence-similarity-based methods in terms of accuracy and scalability. The Triticeae tribe is a typical allopolyploid-rich clade with complex species relationships that includes many important crops such as wheat, barley, and rye. We then built Triticeae-GeneTribe ( http://wheat.cau.edu.cn/TGT/ ) as a homology database, by integrating 12 Triticeae genomes and 3 outgroup model genomes and implemented versatile analysis and visualization functions. With macrocollinearity analysis, we were able to construct a refined model illustrating the structural rearrangements of the 4A-5A-7B chromosomes in wheat as two major translocation events. With collinearity analysis at both the macro- and microscale, we illustrated the complex evolutionary history of homologs of the wheat vernalization gene Vrn2 as a combined result of genome translocation, duplication, and polyploidization and gene loss events. Our work provides a useful practice for connecting emerging genome assemblies, with awareness of the extensive polyploidy in plants, and will help researchers efficiently exploit genome sequence resources.
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