Stable unmethylated DNA demarcates expressed genes and their cis-regulatory space in plant genomes

Crisp, Peter A.; Marand, Alexandre P.; Noshay, Jaclyn M.; Zhou, Peng; Lu, Zefu; Schmitz, Robert J.; Springer, Nathan M.

doi:10.1073/pnas.2010250117

Cited by 82 publications

(108 citation statements)

References 99 publications

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“…While many TFBSs are likely quite near the transcription start site (TSS), they could also be located in more distal regions. The identification of enriched motifs within B73 (B) or B73/Mo17/W22 (BMW) DEGs was performed using several sets of search spaces including regions of different promoter size (0.5kb, 1kb and 2kb), orientations (upstream of TTS, downstream of TSS or a combination of both), and a subset of the sequence filtered to only retain regions classified as unmethylated (Crisp et al, 2020) or accessible chromatin [based on (Ricci et al, 2019)] (Figure 3A, see methods for details). A total of 1,950 motifs were identified using B73 DEGs and 4,981 unique motifs were obtained using BMW DEGs with the number of motifs varying substantially for different groups of DEGs (Figure 3B; Figure S7).…”

Section: Resultsmentioning

confidence: 99%

“…However, we find that just using more sequence does not necessarily improve the prediction accuracies. Studies have highlighted the value of using chromatin modifications to reveal the location of important regulatory regions, especially in species with large complex genomes (Oka et al, 2017; Ricci et al, 2019; Crisp et al, 2020). Predictive models that only use the presence of motifs within unmethylated regions or accessible regions provide improvement in performance for some groups of genes even though this removes >50% of the sequence that is methylated.…”

Section: Discussionmentioning

confidence: 99%

“…In contrast, the use of regions defined as accessible chromatin in a previous study (Ricci et al, 2019) did not improve prediction accuracies. Recent work has suggested that unmethylated regions may provide a catalogue of potential regulatory elements in plants (Crisp et al, 2020). Many regions that contain stress-specific regulatory elements are likely unmethylated even in control conditions while many of the regions of accessible chromatin may be more dynamic and only become accessible in specific conditions (Zeng et al, 2019; Wang et al, 2020a; Parvathaneni et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…The location of regulatory elements can be inferred through analyses of accessible chromatin, especially when focused on regions that are accessible only following stress treatments (Maher et al, 2018; Raxwal et al, 2020; Han et al, 2020). Alternatively, DNA methylation signatures are stable across tissues, developmental stages and environmental conditions, and can provide effective filters in mining functional regulatory elements (Crisp et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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

Zhou

Myers

Magnusson

et al. 2021

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Zhou

Myers

Magnusson

et al. 2021

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“…2b ) 10 . Notably, 30% (22,456/73,791) of distal ACRs overlapped with LTR transposons, including the major maize domestication locus tb1 -enhancer, and were generally devoid of DNA methylation 11, 12 . These findings are consistent with transposable elements playing a prominent role in CRE evolution of the maize genome ( Fig.…”

Section: Main Textmentioning

confidence: 99%

Acis-regulatory atlas in maize at single-cell resolution

Marand

Chen

Gallavotti

et al. 2020

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Cis-regulatory elements (CREs) encode the genomic blueprints for coordinating spatiotemporal gene expression programs underlying highly specialized cell functions. To identify CREs underlying cell-type specification and developmental transitions, we implemented single-cell sequencing of Assay for Transposase Accessible Chromatin in an atlas of Zea mays organs. We describe 92 distinct states of chromatin accessibility across more than 165,913 putative CREs, 56,575 cells, and 52 known cell-types in maize using a novel implementation of regularized quasibinomial logistic regression. Cell states were largely determined by combinatorial accessibility of transcription factors (TFs) and their binding sites. A neural network revealed that cell identity could be accurately predicted (>0.94) solely based on TF binding site accessibility. Co-accessible chromatin recapitulated higher-order chromatin interactions, with distinct sets of TFs coordinating cell type-specific regulatory dynamics. Pseudotime reconstruction and alignment with Arabidopsis thaliana trajectories identified conserved TFs, associated motifs, and cis-regulatory regions specifying sequential developmental progressions. Cell-type specific accessible chromatin regions were enriched with phenotype-associated genetic variants and signatures of selection, revealing the major cell-types and putative CREs targeted by modern maize breeding. Collectively, our analysis affords a comprehensive framework for understanding cellular heterogeneity, evolution, and cis-regulatory grammar of cell-type specification in a major crop species.

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Modeling chromatin state from sequence across angiosperms using recurrent convolutional neural networks

et al. 2022

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Accessible chromatin regions are critical components of gene regulation but modeling them directly from sequence remains challenging, especially within plants, whose mechanisms of chromatin remodeling are less understood than in animals. We trained an existing deep learning architecture, DanQ, on leaf ATAC-seq data from 12 angiosperm species to predict the chromatin accessibility of sequence windows within and across species. We also trained DanQ on DNA methylation data from 10 angiosperms, because unmethylated regions have been shown to overlap significantly with accessible chromatin regions in some plants. The across-species models have comparable or even superior performance to a model trained within species, suggesting strong conservation of chromatin mechanisms across angiosperms. Testing a maize held out model on a multi-tissue scATAC panel revealed our models are best at predicting constitutively-accessible chromatin regions, with diminishing performance as cell-type specificity increases. Using a combination of interpretation methods, we ranked JASPAR motifs by their importance to each model and saw that the TCP and AP2/ ERF transcription factor families consistently ranked highly. We embedded the top three JASPAR motifs for each model at all possible positions on both strands in our sequence window and observed position-and strand-specific patterns in their importance to the model. With our cross-species "a2z" model it is now feasible to predict the chromatin accessibility and methylation landscape of any angiosperm genome.

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Stable unmethylated DNA demarcates expressed genes and their cis-regulatory space in plant genomes

Cited by 82 publications

References 99 publications

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

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

Acis-regulatory atlas in maize at single-cell resolution

Modeling chromatin state from sequence across angiosperms using recurrent convolutional neural networks

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