A Collinearity-Incorporating Homology Inference Strategy for Connecting Emerging Assemblies in the Triticeae Tribe as a Pilot Practice in the Plant Pangenomic Era

• Published in: Molecular plant 2020-12, Vol.13 (12), p.1694-1708
• Main Authors: Chen, Yongming, Song, Wanjun, Xie, Xiaoming, Wang, Zihao, Guan, Panfeng, Peng, Huiru, Jiao, Yuannian, Ni, Zhongfu, Sun, Qixin, Guo, Weilong
• Format: Article
• Language: English
• Subjects: collinearity; homology inference; pangenome; polyploid; Triticeae tribe
• ISSN: 1674-2052; 1752-9867
• DOI: 10.1016/j.molp.2020.09.019

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 the pangenomic era. Here we present 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 built Triticeae-GeneTribe (http://wheat.cau.edu.cn/TGT/), 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, which evolved 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. This work reports the development of a novel method incorporating collinearity for homology inference among genetically similar genomes, with improved performance and scalability. A comprehensive homology database is built for the tribe Triticeae. With macro- and microcollinearity analysis, the authors proposed a refined model of the chromosome 4A-5A-7B translocations and illustrated the complex evolutionary history of the TaVrn2 homologs.