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Abstract Availability of readily transformable germplasm, as well as efficient pipelines for gene discovery are notable bottlenecks in the application of genome editing in potato. To study and introduce traits such as resistance against biotic and abiotic factors, tuber quality traits and self-fertility, model germplasm that is amenable to gene editing and regeneration is needed. Cultivated potato is a heterozygous autotetraploid and its genetic redundancy and complexity makes studying gene function challenging. Genome editing is simpler at the diploid level, with fewer allelic variants to consider. A readily transformable diploid potato would be further complemented by genomic resources that could aid in high throughput functional analysis. The heterozygous Solanum tuberosum Group Phureja clone 1S1 has a high regeneration rate, self-fertility, desirable tuber traits and is amenable to Agrobacterium-mediated transformation. We leveraged its amenability to Agrobacterium-mediated transformation to create a Cas9 constitutively expressing line for use in viral vector-based gene editing. To create a contiguous genome assembly, a homozygous doubled monoploid of 1S1 (DM1S1) was sequenced using 44 Gbp of long reads generated from Oxford Nanopore Technologies (ONT), yielding a 736 Mb assembly that encoded 31,145 protein-coding genes. The final assembly for DM1S1 represents a nearly complete genic space, shown by the presence of 99.6% of the genes in the Benchmarking Universal Single Copy Orthologs (BUSCO) set. Variant analysis with Illumina reads from 1S1 was used to deduce its alternate haplotype. These genetic and genomic resources provide a toolkit for applications of genome editing in both basic and applied research of potato. 

Since they emerged approximately 125 million years ago, flowering plants have evolved to dominate the terrestrial landscape and survive in the most inhospitable environments on earth. At their core, these adaptations have been shaped by changes in numerous, interconnected pathways and genes that collectively give rise to emergent biological phenomena. Linking gene expression to morphological outcomes remains a grand challenge in biology, and new approaches are needed to begin to address this gap. Here, we implemented topological data analysis (TDA) to summarize the high dimensionality and noisiness of gene expression data using lens functions that delineate plant tissue and stress responses. Using this framework, we created a topological representation of the shape of gene expression across plant evolution, development, and environment for the phylogenetically diverse flowering plants. The TDA-based Mapper graphs form a well-defined gradient of tissues from leaves to seeds, or from healthy to stressed samples, depending on the lens function. This suggests that there are distinct and conserved expression patterns across angiosperms that delineate different tissue types or responses to biotic and abiotic stresses. Genes that correlate with the tissue lens function are enriched in central processes such as photosynthetic, growth and development, housekeeping, or stress responses. Together, our results highlight the power of TDA for analyzing complex biological data and reveal a core expression backbone that defines plant form and function.