Pangenome-based trajectories of intracellular gene transfers in Poaceae unveil high cumulation in Triticeae.

Intracellular gene transfers (IGTs) between the nucleus and organelles, including plastids and mitochondria, constantly reshape 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 developed an approach, IGTminer, that maps the evolutionary trajectories of IGTs using collinearity and gene reannotation across multiple genome assemblies. We applied IGTminer to create a nuclear organellar gene (NOG) map across 67 genomes covering 15 Poaceae species, including important crops. The resulting NOGs were verified by experiments and sequencing data sets. Our analysis revealed that most NOGs were recently transferred and lineage specific and that Triticeae species tended to have more NOGs than other Poaceae species. Wheat (Triticum aestivum) had a higher retention rate of NOGs than maize (Zea mays) and rice (Oryza sativa), and the retained NOGs were likely involved in photosynthesis and translation pathways. Large numbers of NOG clusters were aggregated in hexaploid wheat during 2 rounds of polyploidization, contributing to the genetic diversity among modern wheat accessions. We implemented an interactive web server to facilitate the exploration of NOGs in Poaceae. In summary, this study provides resources and insights into the roles of IGTs in shaping interspecies and intraspecies genome variation and driving plant genome evolution.

ggComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat.

Accurate germplasm characterization is a vital step for accelerating crop genetic improvement, which remains largely infeasible for crops such as bread wheat (Triticum aestivum L.), which has a complex genome that undergoes frequent introgression and contains many structural variations. Here, we propose a genomic strategy called ggComp, which integrates resequencing data with copy number variations and stratified single-nucleotide polymorphism densities to enable unsupervised identification of pairwise germplasm resource-based Identity-By-Descent (gIBD) blocks. The reliability of ggComp was verified in wheat cultivar Nongda5181 by dissecting parental-descent patterns represented by inherited genomic blocks. With gIBD blocks identified among 212 wheat accessions, we constructed a multi-scale genomic-based germplasm network. At the whole-genome level, the network helps to clarify pedigree relationship, demonstrate genetic flow, and identify key founder lines. At the chromosome level, we were able to trace the utilization of 1RS introgression in modern wheat breeding by hitchhiked segments. At the single block scale, the dissected germplasm-based haplotypes nicely matched with previously identified alleles of "Green Revolution" genes and can guide allele mining and dissect the trajectory of beneficial alleles in wheat breeding. Our work presents a model-based framework for precisely evaluating germplasm resources with genomic data. A database, WheatCompDB (http://wheat.cau.edu.cn/WheatCompDB/), is available for researchers to exploit the identified gIBDs with a multi-scale network.

Innovative computational tools provide new insights into the polyploid wheat genome.

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

In situ densification and heparin immobilization of bacterial cellulose vascular patch for potential vascular applications.

Nowadays, developing vascular grafts (e.g., vascular patches and tubular grafts) is challenging. Bacterial cellulose (BC) with 3D fibrous network has been widely investigated for vascular applications. In this work, different from BC vascular patch cultured with the routine culture medium, dopamine (DA)-containing culture medium is employed to in situ synthesize dense BC fibrous structure with significantly increased fiber diameter and density. Simultaneously, BC fibers are modified by DA during in situ synthesis process. Then DA on BC fibers can self-polymerize into polydopamine (PDA) accompanied with the removal of bacteria in NaOH solution, obtaining PDA-modified dense BC (PDBC) vascular patch. Heparin (Hep) is subsequently covalently immobilized on PDBC fibers to form Hep-immobilized PDBC (Hep@PDBC) vascular patch. The obtained results indicate that Hep@PDBC vascular patch exhibits remarkable tensile and burst strength due to its dense fibrous structure. More importantly, compared with BC and PDBC vascular patches, Hep@PDBC vascular patch not only displays reduced platelet adhesion and improved anticoagulation activity, but also promotes the proliferation, adhesion, spreading, and protein expression of human umbilical vein endothelial cells, contributing to the endothelialization process. The combined strategy of in situ densification and Hep immobilization provides a feasible guidance for the construction of BC-based vascular patches.

Tagging large CNV blocks in wheat boosts digitalization of germplasm resources by ultra-low-coverage sequencing.

BACKGROUND: The massive structural variations and frequent introgression highly contribute to the genetic diversity of wheat, while the huge and complex genome of polyploid wheat hinders efficient genotyping of abundant varieties towards accurate identification, management, and exploitation of germplasm resources. RESULTS: We develop a novel workflow that identifies 1240 high-quality large copy number variation blocks (CNVb) in wheat at the pan-genome level, demonstrating that CNVb can serve as an ideal DNA fingerprinting marker for discriminating massive varieties, with the accuracy validated by PCR assay. We then construct a digitalized genotyping CNVb map across 1599 global wheat accessions. Key CNVb markers are linked with trait-associated introgressions, such as the 1RS·1BL translocation and 2NvS translocation, and the beneficial alleles, such as the end-use quality allele Glu-D1d (Dx5 + Dy10) and the semi-dwarf r-e-z allele. Furthermore, we demonstrate that these tagged CNVb markers promote a stable and cost-effective strategy for evaluating wheat germplasm resources with ultra-low-coverage sequencing data, competing with SNP array for applications such as evaluating new varieties, efficient management of collections in gene banks, and describing wheat germplasm resources in a digitalized manner. We also develop a user-friendly interactive platform, WheatCNVb ( http://wheat.cau.edu.cn/WheatCNVb/ ), for exploring the CNVb profiles over ever-increasing wheat accessions, and also propose a QR-code-like representation of individual digital CNVb fingerprint. This platform also allows uploading new CNVb profiles for comparison with stored varieties. CONCLUSIONS: The CNVb-based approach provides a low-cost and high-throughput genotyping strategy for enabling digitalized wheat germplasm management and modern breeding with precise and practical decision-making.

Dispersed emergence and protracted domestication of polyploid wheat uncovered by mosaic ancestral haploblock inference.

Major crops are all survivors of domestication bottlenecks. Studies have focused on the genetic loci related to the domestication syndrome, while the contribution of ancient haplotypes remains largely unknown. Here, an ancestral genomic haploblock dissection method is developed and applied to a resequencing dataset of 386 tetraploid/hexaploid wheat accessions, generating a pan-ancestry haploblock map. Together with cytoplastic evidences, we reveal that domesticated polyploid wheat emerged from the admixture of six founder wild emmer lineages, which contributed the foundation of ancestral mosaics. The key domestication-related loci, originated over a wide geographical range, were gradually pyramided through a protracted process. Diverse stable-inheritance ancestral haplotype groups of the chromosome central zone are identified, revealing the expanding routes of wheat and the trends of modern wheat breeding. Finally, an evolution model of polyploid wheat is proposed, highlighting the key role of wild-to-crop and interploidy introgression, that increased genomic diversity following bottlenecks introduced by domestication and polyploidization.