Biology subjects

Grotewold, E.

Publications and source records attributed to Grotewold, E..

9 recordsLinked to original sources

bioRxiv2025

Origin, domestication, and diversity of the climate resilient Ethiopian cereal teff

Teff (Eragrostis tef) is a climate-resilient cereal and staple crop in the Horn of Africa, cultivated by millions of smallholder farmers. Despite its cultural and nutritional significance, teff has limited genomic tools, constraining progress in yield improvement and trait optimization. Here, we assembled and resequenced the Teff Association Panel (TAP), a diverse set of 265 landraces and cultivars, to investigate the domestication history, genetic diversity, and agronomic traits of teff. Phylogenetic and population genetic analyses confirm Eragrostis pilosa as the direct progenitor of teff, with domestication likely occurring in the Tigray region of Ethiopia. We generated a high-quality reference genome for E. pilosa and found extensive chromosomal collinearity and minimal gene loss compared to teff, with teff-specific genes enriched in functions related to domestication traits. We identified signatures of selection across the teff genome and used genome-wide association studies (GWAS) to map loci associated with seed color and panicle architecture. Integrated GWAS, expression, metabolic, and comparative genomic analyses pinpoint a major seed color locus containing orthologs of the TT7 cytochrome P450 gene involved in flavonoid hydroxylation and the TT2 MYB transcription factor regulating proanthocyanidin biosynthesis. For panicle architecture, we identified a strong association near a teff ortholog of Dense and Erect Panicle 1 (DEP1), a key regulator of inflorescence structure in rice and sorghum. This suggests convergent selection on shared genetic pathways controlling panicle morphology across cereals. Our findings confirm the evolutionary origin of teff, identify key domestication loci, and highlight untapped genetic diversity among Ethiopian breeding lines. These genomic resources provide a foundation for accelerating teff improvement through molecular breeding and genome editing to enhance yield, resilience, and nutrition.

plant biology↗

bioRxiv2024

Transcriptome profiling of maize transcription factor mutants to probe gene regulatory network predictions

Transcription factors (TFs) play important roles in regulation of gene expression and phenotype. A variety of approaches have been utilized to develop gene-regulatory networks (GRNs) to predict the regulatory targets for each TF, such as yeast-one-hybrid (Y1H) screens and gene co-expression network (GCN) analysis. Here we identified potential TF targets and used a reverse genetics approach to test the predictions of several GRNs in maize. Loss-of-function mutant alleles were isolated for 22 maize TFs. These mutants did not exhibit obvious morphological phenotypes. However, transcriptomic profiling identified differentially expressed genes in each of the mutant genotypes, and targeted metabolic profiling indicated variable phenolic accumulation in some mutants. An analysis of expression levels for predicted target genes based on Y1H screens identified a small subset of predicted targets that exhibit altered expression levels. The analysis of predicted targets from GCN-based methods found significant enrichments for prediction sets of some TFs, but most predicted targets did not exhibit altered expression. This could result from false-positive GCN predictions, a TF with a secondary regulatory role resulting in minor effects on gene regulation, or redundant gene regulation by other TFs. Collectively, these findings suggest that loss-of-function for single uncharacterized TFs might have limited phenotypic impacts but can reveal subsets of GRN predicted targets with altered expression.

plant biology↗

bioRxiv2024

Camelina CircRNA Landscape: Implications for Gene Regulation and Fatty Acid Metabolism

Circular RNAs (circRNAs) are closed-loop RNAs forming a covalent bond between their 3 and 5 ends, the backsplice junction (BSJ), rendering them resistant to exonucleases and thus more stable compared to linear RNAs. Identification of circRNAs and distinction from its cognate linear RNA is only possible by sequencing the BSJ that is unique to the circRNA. CircRNAs are involved in regulation of their cognate RNAs by increasing transcription rates, RNA stability and alternative splicing. We have identified circRNAs from Camelina sativa that are associated with the regulation of germination, light response, and lipid metabolism. We sequenced light-grown and etiolated seedlings after 5 or 7 days post-germination and identified a total of 3,447 circRNAs from 2,763 genes. Most circRNAs originate from a single homeolog of the three subgenomes from allohexaploid camelina and correlates with higher ratios of alternative splicing of their cognate genes. A network analysis shows the interactions of select miRNA:circRNA:mRNAs for regulation of transcript stabilities where circRNA can act as a competing endogenous RNA. Several key lipid metabolism genes can generate circRNA and we confirmed the presence of KASII circRNA as a true circRNA. CircRNA in camelina can be a novel target for breeding and engineering efforts. Core ideasO_LIFirst discovery of 3,447 genic and 307 intergenic unique putative circRNAs from Camelina sativa. C_LIO_LIWe identified circRNAs that were regulated in response to seedling de-etiolation. C_LIO_LIMost circRNAs originate from only one homeolog of the three subgenomes in this allohexaploid Camelina. C_LIO_LIAlternative splicing of exon skipping and intron retention positively correlate with circRNA occurrence. C_LIO_LIValidation of KASII circRNAs as an example of lipid metabolism pathways potentially regulated by circRNA. C_LI

plant biology↗

bioRxiv2024

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

Gene regulatory networks (GRNs) link transcription factors (TFs) to the biological processes they control. Assembling them remains difficult because the relevant data types (gene expression, protein-DNA interactions, and genetic variation) are large, heterogeneous, and rarely combined. Here, we developed and benchmarked a framework that integrates these data into TF-function predictions in maize. We assembled four complementary TF-target gene network layers, based on expression, protein-DNA interaction, trans-expression quantitative trait loci (eQTL), and cis-eQTL-supported interaction, from 46 Random Forest (RF)-inferred regulatory networks, 283 protein-DNA interaction assays, and eQTLs derived from 16 million SNPs across 304 inbred lines. Together these layers comprised ~4.6 million interactions. We then compared three strategies for integrating them, benchmarking each against published TF knockout data. A network-based approach, which represents every gene as a low-dimensional vector (embedding) learned from the combined network, outperformed the two overlap-based strategies, annotating over eight times more TFs (~3,000), agreeing most closely with gene knockout responses where predictions existed, and remaining robust when individual layers lacked data. The predictions recovered TF functions and predicted new regulators of hormone, developmental, and metabolic processes, which we prioritized per process and mapped to specific conditions. Using similarity on the low-dimensional vector representation (embedding), we further identified candidate functionally redundant or diverged TF paralogs. Because it relies only on data types now common across species, the framework provides a generalizable template for prioritizing regulatory genes in maize and other plants.

plant biology↗

bioRxiv2023

Mutator transposon insertions within maize genes often provide a novel outward reading promoter

The highly active family of Mutator (Mu) DNA transposons has been widely used for forward and reverse genetics in maize. There are examples of Mu-suppressible alleles which result in conditional phenotypic effects based on the activity of Mu. Phenotypes from these Mu- suppressible mutations are observed in Mu-active genetic backgrounds, but absent when Mu activity is lost. For some Mu-suppressible alleles, phenotypic suppression likely results from an outward-reading promoter within Mu that is only active when the autonomous Mu element is silenced or lost. We isolated 35 Mu alleles from the UniformMu population that represent insertions in 24 different genes. Most of these mutant alleles are due to insertions within gene coding sequences, but several 5 UTR and intron insertions were included. RNA-seq and de novo transcript assembly were utilized to document the transcripts produced from 33 of these Mu insertion alleles. For 20 of the 33 alleles, there was evidence of transcripts initiating within the Mu sequence reading through the gene. This outward-reading promoter activity was detected in multiple types of Mu elements and doesnt depend on the orientation of Mu. Expression analyses of Mu-initiated transcripts revealed the Mu promoter often provides gene expression levels and patterns that are similar to the wild-type gene. These results suggest the Mu promoter may represent a minimal promoter that can respond to gene cis-regulatory elements. Findings from this study have implications for maize researchers using the UniformMu population, and more broadly highlights a strategy for transposons to co-exist with their host. Article SummaryMutator (Mu) transposable elements are a widely used tool for insertional mutagenesis in maize and often insert in the 5 regions of genes. The characterization of transcripts for Mu insertion alleles reveals complex transcripts. These often result in one transcript that covers the first portion of the gene terminating in Mu and a second transcript initiating within Mu covering the latter portion of the gene. This may reflect a strategy for Mu to minimize the consequences of insertions within genes.

plant biology↗

bioRxiv2021

Applying cis-regulatory codes to predict conserved and variable heat and cold stress response in maize

Changes in gene expression are important for response to abiotic stress. Transcriptome profiling performed on maize inbred and hybrid genotypes subjected to heat or cold stress identifies many transcript abundance changes in response to these environmental conditions. Motifs that are enriched near differentially expressed genes were used to develop machine learning models to predict gene expression responses to heat or cold. The best performing models utilize the sequences both upstream and downstream of the transcription start site. Prediction accuracies could be improved using models developed for specific co-expression clusters compared to using all up- or down-regulated genes or by only using motifs within unmethylated regions. Comparisons of expression responses in multiple genotypes were used to identify genes with variable response and to identify cis- or trans-regulatory variation. Models trained on B73 data have lower performance when applied to Mo17 or W22, this could be improved by using models trained on data from all genotypes. However, the models have low accuracy for correctly predicting genes with variable responses to abiotic stress. This study provides insights into cis-regulatory motifs for heat- and cold-responsive gene expression and provides a framework for developing models to predict expression response to abiotic stress across multiple genotypes. One sentence summaryTranscriptome profiling of maize inbred and hybrid seedlings subjected to heat or cold stress was used to identify key cis-regulatory elements and develop models to predict gene expression responses.

plant biology↗

bioRxiv2020

Modeling gene regulation in response to wounding: temporal variations, hormonal variations, and specialized metabolism pathways induced by wounding

Plants respond to wounding stress by changing gene expression patterns and inducing jasmonic acid (JA), as well as other plant hormones. This includes activating some specialized metabolism pathways, including the glucosinolate pathways, in the case of Arabidopsis thaliana. We model how these responses are regulated by using machine learning to incorporate putative cis-regulatory elements (pCREs), known transcription factor binding sites from literature, in-vitro DNA affinity purification sequencing (DAP-seq) and DNase I hypersensitive sites to predict gene expression for genes clustered by their wound response using machine learning. We found temporal patterns where regulatory sites and regions of open chromatin differed between clusters of genes up-regulated at early and late wounding time points as well as clusters where JA response was induced relative to clusters where JA response was not induced. Overall, we identified pCREs that improved model predictions of expression clusters over known binding sites. We discovered 4,255 pCREs related to wound response at different time points and 2,569 pCREs related to differences between JA-induced and non-JA induced wound response. In addition, pCREs found to be important at different wounding time points were mapped to the promoters of genes in a glucosinolate biosynthesis pathway indicating regulation of this pathway under wounding stress. Finally, we experimentally validated a predicted cis-regulatory element, CCGCGT, showing that knock-out via CRISPR-Cas9 reduces gene expression in response to wounding.

plant biology↗

bioRxiv2020

Co-expression signatures of combinatorial gene regulation

Gene co-expression analyses provide a powerful tool to determine gene associations. The interaction of transcription factors (TFs) with their target genes is an essential step in gene regulation, yet to what extent TFs-target gene associations are recovered in co-expression studies remains unclear. Using the wealth of data available for Arabidopsis, we show here that protein-DNA interactions are overall poor indicators of TF-target co-expression, yet the inclusion of TF-TF interaction information significantly enhance co-expression signals. These results highlight the impact of combinatorial gene control on such gene association networks. We integrated this information to predict higher-order regulatory complexes, which are difficult to identify experimentally. We demonstrate that genes strongly co-expressed with a TF are also enriched in indirect targets. Our results have significant implications on the empirical understanding of complex gene regulatory networks and transcription factor function, and the significance of co-expression from the perspective of protein-protein and protein-DNA interactions.

systems biology↗

bioRxiv2017

Stimulation of the final cell cycle in the stomatal lineage by the cyclin CYCD7;1 under regulation of the MYB transcription factor FOUR-LIPS

Abstract (180 words)Stomatal guard cells are formed through a sequence of asymmetric and symmetric divisions in the epidermis of the sporophyte of most land plants. We show that several D-type cyclins are consecutively activated in the stomatal linage in the epidermis of Arabidopsis thaliana. Whereas CYCD2;1 and CYCD3;2 are activated in the meristemoids early in the lineage, CYCD7;1 is activated before the final division. CYCD7;1 expression peaks in the guard mother cell, where its transcription is modulated by the FOUR-LIPS/MYB88 transcription factor. FOUR-LIPS/MYB88 interacts with the CYCD7;1 promoter and represses CYCD7;1 transcription. CYCD7;1 stimulates the final symmetric division in the stomatal lineage, since guard cell formation is delayed in the cycd7;1 mutant epidermis and guard mother cell (GMC) divisions in four-lips mutant guard mother cells are limited by loss of function of CYCD7;1. Hence, the precise activation of a specific D-type cyclin, CYCD7;1, is required for correct timing of the last symmetric division that creates the stomatal guards cells, and CYCD7;1 expression is regulated by the FLP/MYB pathway that ensures cell cycle arrest in the stomatal guard cells.\n\nSummary StatementThe formation of paired guard cells in the epidermis of the Arabidopsis thaliana shoot, requires the activity of the D-type cyclin CYCD7;1 for the normal timing of the final division.

plant biology↗