Motivation Single-cell RNA sequencing (scRNA-seq) techniques have revolutionized the investigation of transcriptomic landscape in individual cells. Recent advancements in spatial transcriptomic technologies further enable gene expression profiling and spatial organization mapping of cells simultaneously. Among the technologies, imaging-based methods can offer higher spatial resolutions, while they are limited by either the small number of genes imaged or the low gene detection sensitivity. Although several methods have been proposed for enhancing spatially resolved transcriptomics, inadequate accuracy of gene expression prediction and insufficient ability of cell-population identification still impede the applications of these methods. Results We propose stPlus, a reference-based method that leverages information in scRNA-seq data to enhance spatial transcriptomics. Based on an auto-encoder with a carefully tailored loss function, stPlus performs joint embedding and predicts spatial gene expression via a weighted k-nearest-neighbor. stPlus outperforms baseline methods with higher gene-wise and cell-wise Spearman correlation coefficients. We also introduce a clustering-based approach to assess the enhancement performance systematically. Using the data enhanced by stPlus, cell populations can be better identified than using the measured data. The predicted expression of genes unique to scRNA-seq data can also well characterize spatial cell heterogeneity. Besides, stPlus is robust and scalable to datasets of diverse gene detection sensitivity levels, sample sizes and number of spatially measured genes. We anticipate stPlus will facilitate the analysis of spatial transcriptomics. Availability and implementation stPlus with detailed documents is freely accessible at http://health.tsinghua.edu.cn/software/stPlus/ and the source code is openly available on https://github.com/xy-chen16/stPlus.

The post-translational modification lysine 2hydroxyisobutyrylation (K hib ) plays an important role in gene transcription, metabolism, and enzymatic activity. K hib sites have been identified in rice (Oryza sativa). However, the K hib status of proteins in rice flowers during pathogen infection remains unclear. Here, we report a comprehensive identification of K hib -modified proteins in rice flowers, and the changes in these proteins during infection with the fungal pathogen Ustilaginoidea virens. By using a tandem mass tag-based quantitative proteomics approach, we identified 2,891 K hib sites on 964 proteins in rice flowers. Our data demonstrated that 2-hydroxyisobutyrylated proteins are involved in diverse biological processes. K hib levels were substantially reduced upon infection with U. virens. Chromatin immunoprecipitation polymerase chain reaction (PCR) and reverse transcription quantitative PCR analyses revealed that histone K hib is involved in the expression of disease-resistance genes. More importantly, most quantified sites on core histones H3 were downregulated upon U. virens infection. In addition, the histone deacetylases HDA705, HDA716, SRT1, and SRT2 are involved in the removal of K hib marks in rice. HDA705 was further confirmed to negatively regulate rice disease resistance to pathogens U. virens, Magnaporthe oryzae, and Xanthomonas oryzae pv. oryzae (Xoo). Our data suggest that U. virens could modulate K hib in rice flowers during infection.

Lysine 2-hydroxyisobutyrylation (K hib) is a newly identified post-translational modification (PTM) that plays important roles in transcription and cell proliferation in eukaryotes. However, its function remains unknown in phytopathogenic fungi. Here, we performed a comprehensive assessment of K hib in the rice false smut fungus Ustilaginoidea virens, using Tandem Mass Tag (TMT)-based quantitative proteomics approach. A total of 3 426 K hib sites were identified in 977 proteins, sugg esting that K hib is a common and complex PTM in U. virens. Our data demonstrated that the 2-hydroxyisobutyrylated proteins are involved in diverse biological processes. Network analysis of the modified proteins revealed a highly interconnected protein network that included many well-studied virulence factors. We confirmed that the Zn-binding reduced potassium dependency3type histone deacetylase (UvRpd3) is a major enzyme that removes 2-hydroxyisobutyrylation and acetylation in U. virens. Notably, mutations of K hib sites in the mitogen-activated protein kinase (MAPK) UvSlt2 significantly reduced fungal virulence and decreased the enzymatic activity of UvSlt2. Molecular dynamics simulations demonstrated that 2-hydroxyisobutyrylation in UvSlt2 increased the hydrophobic solvent-accessible surface area and thereby affected binding between the UvSlt2 enzyme and its substrates. Our findings thus establish K hib as a major post-translational modification in U. virens and point to an important role for K hib in the virulence of this phytopathogenic fungus.

Background Before studying gene expression of different organisms, it is important to determine the best reference gene. At present, the most accurate method of detecting gene expression is quantitative real-time PCR (RT-qPCR). With this method, reference genes that are stable in different biological systems and under different conditions can be obtained. Toona ciliata Roem (T. ciliata). is a valuable and fast-growing timber specie. In this study, 20 reference genes were identified using RT-qPCR, as a primary prerequisite for future gene expression analysis. Four different methods, geNorm, NormFinder, BestKeeper, and RankAggreg were used to evaluate the expression stability of the 20 candidate reference genes in various tissues under different conditions. Results The experimental results showed that TUB-α was the most stably expressed reference gene across all samples and UBC17 was the most stable in leaves and young stems under Hypsipyla robusta (H. robusta) and methyl jasmonate (MeJA) treatments. In addition, PP2C59 and UBC5B were the best-performing genes in leaves under H. robusta treatment, while HIS1 and ACT7 were the best reference genes in young stems. The two best reference genes were 60S-18 and TUB-α after treatment at 4 °C. The expression of HIS6 and MUB1 was the most stable under PEG6000 treatment. The accuracy of the selected reference genes was verified using the transcription factor MYB3 (TcMYB3) gene. Conclusions This is the first report to verify the best reference genes for normalizing gene expression in T. ciliata under different conditions, which will facilitate future elucidation of gene regulations in this species.