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Wan, E.

Publications and source records attributed to Wan, E..

2 recordsLinked to original sources

Convergent evolution of effector protease recognition by Arabidopsis and barley

The Pseudomonas syringae cysteine protease AvrPphB activates the Arabidopsis resistance protein RPS5 by cleaving a second host protein, PBS1. AvrPphB induces defense responses in other plant species, but the genes and mechanisms mediating AvrPphB recognition in those species have not been defined. Here, we show that AvrPphB induces defense responses in diverse barley cultivars. We show also that barley contains two PBS1 orthologs, that their products are cleaved by AvrPphB, and that the barley AvrPphB response maps to a single locus containing a nucleotide-binding leucine-rich repeat (NLR) gene, which we termed AvrPphB Resistance 1 (Pbr1). Transient co-expression of PBR1 with wild-type AvrPphB, but not a protease inactive mutant, triggered defense responses, indicating that PBR1 detects AvrPphB protease activity. Additionally, PBR1 co-immunoprecipitated with barley and N. benthamiana PBS1 proteins, suggesting mechanistic similarity to detection by RPS5. Lastly, we determined that wheat cultivars also recognize AvrPphB protease activity and contain a Pbr1 ortholog. Phylogenetic analyses showed however that Pbr1 is not orthologous to RPS5. Our results indicate that the ability to recognize AvrPphB evolved convergently, and imply that selection to guard PBS1-like proteins is ancient. Also, the results suggest that PBS1-based decoys may be used to engineer protease effector recognition-based resistance in barley and wheat.

plant biology

Multiplexing droplet-based single cell RNA-sequencing using natural genetic barcodes

Droplet-based single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes from tens of thousands of cells. Multiplexing samples for single cell capture and library preparation in dscRNA-seq would enable cost-effective designs of differential expression and genetic studies while avoiding technical batch effects, but its implementation remains challenging. Here, we introduce an in-silico algorithm demuxlet that harnesses natural genetic variation to discover the sample identity of each cell and identify droplets containing two cells. These capabilities enable multiplexed dscRNA-seq experiments where cells from unrelated individuals are pooled and captured at higher throughput than standard workflows. To demonstrate the performance of demuxlet, we sequenced 3 pools of peripheral blood mononuclear cells (PBMCs) from 8 lupus patients. Given genotyping data for each individual, demuxlet correctly recovered the sample identity of > 99% of singlets, and identified doublets at rates consistent with previous estimates. In PBMCs, we demonstrate the utility of multiplexed dscRNA-seq in two applications: characterizing cell type specificity and inter-individual variability of cytokine response from 8 lupus patients and mapping genetic variants associated with cell type specific gene expression from 23 donors. Demuxlet is fast, accurate, scalable and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

bioinformatics