Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

Prioritizing Metabolic Gene Regulators through Multi-Omic Network Integration in Maize

Elucidating gene regulatory networks (GRNs) is a major area of study within plant systems biology. Phenotypic traits are intricately linked to specific gene expression profiles. These expression patterns arise primarily from regulatory connections between sets of transcription factors (TFs) and their target genes. In this study, we integrated publicly available co-expression networks derived from more than 6,000 RNA-seq samples, 283 protein-DNA interaction assays, and 16 million of SNPs used to identify expression quantitative loci (eQTL), to construct TF-target networks. In total, we analyzed ~4.6M interactions to generate four distinct types of TF-target networks: co-expression, protein-DNA interaction (PDI), trans-expression quantitative loci (trans-eQTL), and cis-eQTL combined with PDIs. To improve the functional annotation of TFs based on its target genes, we implemented three different strategies to integrate these four types of networks. We subsequently evaluated the effectiveness of our method through loss-of function mutant and random networks. The multi-network integration allowed us to identify transcriptional regulators of hormone-, metabolic- and development-related processes. Finally, using the topological properties of the fully integrated network, we identified potentially functional redundant TF paralogs. Our findings retrieved functions previously documented for numerous TFs and revealed novel functions that are crucial for informing the design of future experiments. The approach here-described lays the foundation for the integration of multi-omic datasets in maize and other plant systems.

Exploring Camelina sativa lipid metabolism regulation by combining gene co-expression and DNA affinity purification analyses

Camelina (Camelina sativa) is an annual oilseed plant that is gaining momentum as a biofuel cover crop. Understanding gene regulatory networks is essential to deciphering plant metabolic pathways, including lipid metabolism. Here, we take advantage of a growing collection of gene expression datasets to predict transcription factors (TFs) associated with the control of Camelina lipid metabolism. We identified approximately 350 TFs highly co-expressed with lipid-related genes (LRGs). These TFs are highly represented in the MYB, AP2/ERF, bZIP, and bHLH families, including a significant number of homologs of well-known Arabidopsis lipid and seed developmental regulators. After prioritizing the top 22 TFs for further validation, we identified DNA-binding sites and predicted target genes for 16 out of the 22 TFs tested using DNA affinity purification followed by sequencing (DAP-seq). Enrichment analyses of targets supported the co-expression prediction for most TF candidates, and the comparison to Arabidopsis revealed some common themes, but also aspects unique to Camelina. Within the top potential lipid regulators, we identified CsaMYB1, CsaABI3AVP1-2, CsaHB1, CsaNAC2, CsaMYB3, and CsaNAC1 as likely involved in the control of seed fatty acid elongation and CsaABI3AVP1-2 and CsabZIP1 as potential regulators of the synthesis and degradation of triacylglycerols (TAGs), respectively. Altogether, the integration of co-expression data and DNA-binding assays permitted us to generate a high-confidence and short list of Camelina TFs involved in the control of lipid metabolism during seed development.

Prediction of conserved and variable heat and cold stress response in maize using cis-regulatory information

Changes in gene expression are important for responses to abiotic stress. Transcriptome profiling of heat- or cold-stressed maize genotypes identifies many changes in transcript abundance. We used comparisons of expression responses in multiple genotypes to identify alleles with variable responses to heat or cold stress and to distinguish examples of cis- or trans-regulatory variation for stress-responsive expression changes. We used motifs enriched near the transcription start sites (TSSs) for thermal stress-responsive genes to develop predictive models of gene expression responses. Prediction accuracies can be improved by focusing only on motifs within unmethylated regions near the TSS and vary for genes with different dynamic responses to stress. Models trained on expression responses in a single genotype and promoter sequences provided lower performance when applied to other genotypes but this could be improved by using models trained on data from all three genotypes tested. The analysis of genes with cis-regulatory variation provides evidence for structural variants that result in presence/absence of transcription factor binding sites in creating variable responses. This study provides insights into cis-regulatory motifs for heat- and cold-responsive gene expression and defines a framework for developing models to predict expression responses across multiple genotypes.

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.

CamRegBase: a gene regulation database for the biofuel crop, Camelina sativa

Camelina is an annual oilseed plant from the Brassicaceae family that is gaining momentum as a biofuel winter cover crop. However, a significant limitation in further enhancing its utility as a producer of oils that can be used as biofuels, jet fuels or bio-based products is the absence of a repository for all the gene expression and regulatory information that is being rapidly generated by the community. Here, we provide CamRegBase (https://camregbase.org/) as a one-stop resource to access Camelina information on gene expression and co-expression, transcription factors, lipid associated genes and genome-wide orthologs in the close-relative reference plant Arabidopsis. We envision this as a resource of curated information for users, as well as a repository of new gene regulation information.

Discovery of modules involved in the biosynthesis and regulation of maize phenolic compounds

Phenolic compounds are among the most diverse and widespread of specialized plant compounds and underly many important agronomic traits. Our comprehensive analysis of the maize genome unraveled new aspects of the genes involved in phenylpropanoid, monolignol, and flavonoid production in this important crop. Remarkably, just 19 genes accounted for 70 % of the overall mRNA accumulation of these genes across 95 tissues, indicating that these are the main contributors to the flux of phenolic metabolites. Eighty genes with intermediate to low expression play minor and more specialized roles. Remaining genes are likely undergoing loss of function or are expressed in limited cell types. Phylogenetic and expression analyses revealed which members of gene families governing metabolic entry and branch points exhibit duplication, subfunctionalization, or loss of function. Co-expression analysis applied to genes in sequential biosynthetic steps revealed that certain isoforms are highly co-expressed and are candidates for metabolic complexes that ensure metabolite delivery to correct cellular compartments. Co-expression of biosynthesis genes with transcription factors discovered connections that provided candidate components for regulatory modules governing this pathway. Our study provides a comprehensive analysis of maize phenylpropanoid related genes, identifies major pathway contributors, and novel candidate enzymatic and regulatory modules of the metabolic network.

Diversity of genetic lesions characterizes new Arabidopsis flavonoid pigment mutant alleles from T-DNA collections

The visual phenotypes afforded by flavonoid pigments have provided invaluable tools for modern genetics. Many Arabidopsis transparent testa (tt) mutants lacking the characteristic proanthocyanidin (PA) seed coat pigmentation and often failing to accumulate anthocyanins in vegetative tissues have been characterized. These mutants have significantly contributed to our understanding of flavonoid biosynthesis, regulation, and transport. A comprehensive screening for tt mutants in available large T-DNA collection lines resulted in the identification of 16 independent lines lacking PAs and anthocyanins, or with seed coat pigmentation clearly distinct from wild type. Segregation analyses and the characterization of second alleles in the genes disrupted by the indexed T-DNA insertions demonstrated that all the lines contained at least one additional mutation responsible for the tt phenotypes. Using a combination of RNA-Seq and whole genome re-sequencing and confirmed through complementation, we show here that these mutations correspond to novel alleles of ttg1 (two alleles), tt3 (two alleles), tt5 (two alleles), ban (two alleles), tt1 (two alleles), and tt8 (six alleles), which harbored additional T-DNA insertions, indels, missense mutations, and large genomic deletion. Several of the identified alleles offer interesting perspectives on flavonoid biosynthesis and regulation.

RNAseq analysis of cassava reveals similar plant responses upon infection with pathogenic and non-pathogenic strains of Xanthomonas axonopodis pv. manihotis

An RNAseq-based analysis of the cassava plants inoculated with Xam allowed the identification of transcriptional upregulation of genes involved in jasmonate metabolism, phenylpropanoid biosynthesis and putative targets for a TALE. Cassava bacterial blight, a disease caused by the gram-negative bacterium Xanthomonas axonopodis pv. manihotis (Xam), is a major limitation to cassava production worldwide and especially in developing countries. The molecular mechanisms underlying cassava susceptibility to Xam are currently unknown. To identify host genes and pathways leading to plant susceptibility, we analyzed the transcriptomic responses occurring in cassava plants challenged with either the non-pathogenic Xam strain ORST4, or strain ORST4(TALE1 Xam ) which is pathogenic due to the major virulence transcription activator like effector TALE1 Xam . Both strains triggered similar responses, i.e., induction of genes related to photosynthesis and phenylpropanoid biosynthesis, and repression of genes related to jasmonic acid signaling. Finally, to search for TALE1 Xam virulence targets, we scanned the list of cassava genes induced upon inoculation of ORST4(TALE1 Xam ) for candidates harboring a predicted TALE1 Xam effector binding element in their promoter. Among the six genes identified as potential candidate targets of TALE1 Xam a gene coding for a heat shock transcription factor stands out as the best candidate based on their induction in presence of TALE1 Xam and contain a sequence putatively recognized by TALE1 Xam .