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Camelina ( Camelina sativa ), an allohexaploid species, is an emerging aviation biofuel crop that has been the focus of resurgent interest in recent decades. To guide future breeding and crop improvement efforts, the community requires a deeper comprehension of subgenome dominance, often noted in allopolyploid species, "alongside an understanding of the genetic diversity" and population structure of material present within breeding programs. We conducted population genetic analyses of a C. sativa diversity panel, leveraging a new genome, to estimate nucleotide diversity and population structure, and analyzed for patterns of subgenome expression dominance among different organs. Our analyses confirm that C. sativa has relatively low genetic diversity and show that the SG3 subgenome has substantially lower genetic diversity compared to the other two subgenomes. Despite the low genetic diversity, our analyses identified 13 distinct subpopulations including two distinct wild populations and others putatively representing founders in existing breeding populations. When analyzing for subgenome composition of long non-coding RNAs, which are known to play important roles in (a)biotic stress tolerance, we found that the SG3 subgenome contained significantly more lincRNAs compared to other subgenomes. Similarly, transcriptome analyses revealed that expression dominance of SG3 is not as strong as previously reported and may not be universal across all organ types. From a global analysis, SG3 "was only significant higher expressed" in flower, flower bud, and fruit organs, which is an important discovery given that the crop yield is associated with these organs. Collectively, these results will be valuable for guiding future breeding efforts in camelina., Competing Interests: The authors declare no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nanjing Agricultural University.)

Variation in gene expression levels is pervasive among individuals and races or varieties, and has substantial agronomic consequences, for example, by contributing to hybrid vigor. Gene expression level variation results from mutations in regulatory sequences (cis) and/or transcription factor (TF) activity (trans), but the mechanisms underlying cis- and/or trans-regulatory variation of complex phenotypes remain largely unknown. Here, we investigated gene expression variation mechanisms underlying the differential accumulation of the insecticidal compounds maysin and chlorogenic acid in silks of widely used maize (Zea mays) inbreds, B73 and A632. By combining transcriptomics and cistromics, we identified 1,338 silk direct targets of the maize R2R3-MYB TF Pericarp color1 (P1), consistent with it being a regulator of maysin and chlorogenic acid biosynthesis. Among these P1 targets, 464 showed allele-specific expression (ASE) between B73 and A632 silks. Allelic DNA-affinity purification sequencing identified 34 examples in which P1 allelic specific binding (ASB) correlated with cis-expression variation. From previous yeast one-hybrid studies, we identified 9 TFs potentially implicated in the control of P1 targets, with ASB to 83 out of 464 ASE genes (cis) and differential expression of 4 out of 9 TFs between B73 and A632 silks (trans). These results provide a molecular framework for understanding universal mechanisms underlying natural variation of gene expression levels, and how the regulation of metabolic diversity is established., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Elucidating gene regulatory networks 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. Here, we integrated 46 co-expression networks, 283 protein-DNA interaction (PDI) assays, and 16 million SNPs used to identify expression quantitative trait 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, PDI, trans -eQTL, and cis -eQTL combined with PDIs. To functionally annotate TFs based on their target genes, we implemented three different network integration strategies. We evaluated the effectiveness of each strategy through TF loss-of function mutant inspection and random network analyses. The multi-network integration allowed us to identify transcriptional regulators of several biological processes. Using the topological properties of the fully integrated network, we identified potential functionally 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.

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., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists.)

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., (© 2022 Society for Experimental Biology and John Wiley & Sons Ltd.)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists.)

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., Competing Interests: SJ, AB, BC, NF, AF, SH, PK, ML, NP, SR, MS, PA, AA, CA, SB, JB, PD, LD, ME, SG, FG, KK, DK, SK, AM, NN, TO, MO, GP, EQ, RS, RU, JW, KV, RW, DE, KB, SR No competing interests declared, (© 2021, Plant Cell Atlas Consortium et al.)

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., (© The Author(s) 2020. Published by Oxford University Press.)

The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize ( Zea mays ) transcriptome data sets including >6000 RNA sequencing samples to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, and tissue-and-genotype samples). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans -eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications., (© 2020 American Society of Plant Biologists. All rights reserved.)

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., (Copyright © 2019 Elsevier B.V. All rights reserved.)

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., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary information and resources, and outline the methods for obtaining data. The second stage consists of designing the schema, which involves defining the entire arrangement of the database in a systematic plan. The third stage is the implementation, defined by actualization of the database by using software according to a predefined schema. The final stage is development, where the database is made available to users in a web-accessible system. The result is a knowledgebase that integrates all the information pertaining to gene regulation, and which is easily expandable and transferable.

Key Message: 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 .