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Li T, Xu H, Teng S, Suo M, Bahitwa R, Xu M, Qian Y, Ramstein GP, Song B, Buckler ES, Wang H. Modeling 0.6 million genes for the rational design of functional cis-regulatory variants and de novo design of cis-regulatory sequences. Proc Natl Acad Sci U S A 2024; 121:e2319811121. [PMID: 38889146 PMCID: PMC11214048 DOI: 10.1073/pnas.2319811121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 05/14/2024] [Indexed: 06/20/2024] Open
Abstract
Rational design of plant cis-regulatory DNA sequences without expert intervention or prior domain knowledge is still a daunting task. Here, we developed PhytoExpr, a deep learning framework capable of predicting both mRNA abundance and plant species using the proximal regulatory sequence as the sole input. PhytoExpr was trained over 17 species representative of major clades of the plant kingdom to enhance its generalizability. Via input perturbation, quantitative functional annotation of the input sequence was achieved at single-nucleotide resolution, revealing an abundance of predicted high-impact nucleotides in conserved noncoding sequences and transcription factor binding sites. Evaluation of maize HapMap3 single-nucleotide polymorphisms (SNPs) by PhytoExpr demonstrates an enrichment of predicted high-impact SNPs in cis-eQTL. Additionally, we provided two algorithms that harnessed the power of PhytoExpr in designing functional cis-regulatory variants, and de novo creation of species-specific cis-regulatory sequences through in silico evolution of random DNA sequences. Our model represents a general and robust approach for functional variant discovery in population genetics and rational design of regulatory sequences for genome editing and synthetic biology.
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Affiliation(s)
- Tianyi Li
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
| | - Hui Xu
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
| | - Shouzhen Teng
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
| | - Mingrui Suo
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
| | - Revocatus Bahitwa
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
- Legumes Research Program, Research and Innovation Division, Tanzania Agricultural Research Institute, Ilonga, Kilosa, Morogoro67410, Tanzania
| | - Mingchi Xu
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
| | - Yiheng Qian
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
| | - Guillaume P. Ramstein
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus8000, Denmark
| | - Baoxing Song
- National Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, People’s Republic of China
- Key Laboratory of Maize Biology and Genetic Breeding in Arid Area of Northwest Region of the Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, Shaanxi712100, People’s Republic of China
| | - Edward S. Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, NY14853
- Agricultural Research Service, United States Department of Agriculture, Ithaca, NY14853
| | - Hai Wang
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing100193, People’s Republic of China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing100193, People’s Republic of China
- Sanya Institute of China Agricultural University, Sanya572025, People’s Republic of China
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2
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Galli M, Chen Z, Ghandour T, Chaudhry A, Gregory J, Li M, Zhang X, Dong Y, Song G, Walley JW, Chuck G, Whipple C, Kaeppler HF, Huang SSC, Gallavotti A. Transcription factor binding site divergence across maize inbred lines drives transcriptional and phenotypic variation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.31.596834. [PMID: 38895211 PMCID: PMC11185568 DOI: 10.1101/2024.05.31.596834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Regulatory elements are important constituents of plant genomes that have shaped ancient and modern crops. Their identification, function, and diversity in crop genomes however are poorly characterized, thus limiting our ability to harness their power for further agricultural advances using induced or natural variation. Here, we use DNA affinity purification-sequencing (DAP-seq) to map transcription factor (TF) binding events for 200 maize TFs belonging to 30 distinct families and heterodimer pairs in two distinct inbred lines historically used for maize hybrid plant production, providing empirical binding site annotation for 5.3% of the maize genome. TF binding site comparison in B73 and Mo17 inbreds reveals widespread differences, driven largely by structural variation, that correlate with gene expression changes. TF binding site presence-absence variation helps clarify complex QTL such as vgt1, an important determinant of maize flowering time, and DICE, a distal enhancer involved in herbivore resistance. Modification of TF binding regions via CRISPR-Cas9 mediated editing alters target gene expression and phenotype. Our functional catalog of maize TF binding events enables collective and comparative TF binding analysis, and highlights its value for agricultural improvement.
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Affiliation(s)
- Mary Galli
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854-8020, USA
| | - Zongliang Chen
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854-8020, USA
| | - Tara Ghandour
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Amina Chaudhry
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854-8020, USA
| | - Jason Gregory
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854-8020, USA
| | - Miaomiao Li
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Xuan Zhang
- Department of Genetics, University of Georgia, Athens, GA, USA
| | - Yinxin Dong
- Department of Genetics, University of Georgia, Athens, GA, USA
| | - Gaoyuan Song
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University; Ames, IA, 50011
| | - Justin W. Walley
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University; Ames, IA, 50011
| | - George Chuck
- Plant Gene Expression Center, Albany, CA 94710, USA
| | - Clinton Whipple
- Department of Biology, Brigham Young University, 4102 LSB, Provo, UT 84602, USA
| | - Heidi F. Kaeppler
- Department of Agronomy, University of Wisconsin, Madison, WI, USA
- Wisconsin Crop Innovation Center, University of Wisconsin, Middleton, WI, USA
| | - Shao-shan Carol Huang
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Andrea Gallavotti
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854-8020, USA
- Department of Plant Biology, Rutgers University, New Brunswick, NJ, 08901, USA
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3
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Kindel F, Triesch S, Schlüter U, Randarevitch LA, Reichel-Deland V, Weber APM, Denton AK. Predmoter-cross-species prediction of plant promoter and enhancer regions. BIOINFORMATICS ADVANCES 2024; 4:vbae074. [PMID: 38841126 PMCID: PMC11150885 DOI: 10.1093/bioadv/vbae074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/10/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
Motivation Identifying cis-regulatory elements (CREs) is crucial for analyzing gene regulatory networks. Next generation sequencing methods were developed to identify CREs but represent a considerable expenditure for targeted analysis of few genomic loci. Thus, predicting the outputs of these methods would significantly cut costs and time investment. Results We present Predmoter, a deep neural network that predicts base-wise Assay for Transposase Accessible Chromatin using sequencing (ATAC-seq) and histone Chromatin immunoprecipitation DNA-sequencing (ChIP-seq) read coverage for plant genomes. Predmoter uses only the DNA sequence as input. We trained our final model on 21 species for 13 of which ATAC-seq data and for 17 of which ChIP-seq data was publicly available. We evaluated our models on Arabidopsis thaliana and Oryza sativa. Our best models showed accurate predictions in peak position and pattern for ATAC- and histone ChIP-seq. Annotating putatively accessible chromatin regions provides valuable input for the identification of CREs. In conjunction with other in silico data, this can significantly reduce the search space for experimentally verifiable DNA-protein interaction pairs. Availability and implementation The source code for Predmoter is available at: https://github.com/weberlab-hhu/Predmoter. Predmoter takes a fasta file as input and outputs h5, and optionally bigWig and bedGraph files.
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Affiliation(s)
- Felicitas Kindel
- Institute of Plant Biochemistry, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Sebastian Triesch
- Institute of Plant Biochemistry, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
- Cluster of Excellence on Plant Sciences (CEPLAS), Germany
| | - Urte Schlüter
- Institute of Plant Biochemistry, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Laura Alexandra Randarevitch
- Cluster of Excellence on Plant Sciences (CEPLAS), Germany
- Institute of Population Genetics, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Vanessa Reichel-Deland
- Institute of Plant Biochemistry, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Andreas P M Weber
- Institute of Plant Biochemistry, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
- Cluster of Excellence on Plant Sciences (CEPLAS), Germany
| | - Alisandra K Denton
- Institute of Plant Biochemistry, Math.-Nat. Faculty, Heinrich Heine University, Düsseldorf 40225, Germany
- Cluster of Excellence on Plant Sciences (CEPLAS), Germany
- Valence Labs, Montréal, Québec H2S 3H1, Canada
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4
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Hu G, Grover CE, Vera DL, Lung PY, Girimurugan SB, Miller ER, Conover JL, Ou S, Xiong X, Zhu D, Li D, Gallagher JP, Udall JA, Sui X, Zhang J, Bass HW, Wendel JF. Evolutionary Dynamics of Chromatin Structure and Duplicate Gene Expression in Diploid and Allopolyploid Cotton. Mol Biol Evol 2024; 41:msae095. [PMID: 38758089 PMCID: PMC11140268 DOI: 10.1093/molbev/msae095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 04/10/2024] [Accepted: 05/10/2024] [Indexed: 05/18/2024] Open
Abstract
Polyploidy is a prominent mechanism of plant speciation and adaptation, yet the mechanistic understandings of duplicated gene regulation remain elusive. Chromatin structure dynamics are suggested to govern gene regulatory control. Here, we characterized genome-wide nucleosome organization and chromatin accessibility in allotetraploid cotton, Gossypium hirsutum (AADD, 2n = 4X = 52), relative to its two diploid parents (AA or DD genome) and their synthetic diploid hybrid (AD), using DNS-seq. The larger A-genome exhibited wider average nucleosome spacing in diploids, and this intergenomic difference diminished in the allopolyploid but not hybrid. Allopolyploidization also exhibited increased accessibility at promoters genome-wide and synchronized cis-regulatory motifs between subgenomes. A prominent cis-acting control was inferred for chromatin dynamics and demonstrated by transposable element removal from promoters. Linking accessibility to gene expression patterns, we found distinct regulatory effects for hybridization and later allopolyploid stages, including nuanced establishment of homoeolog expression bias and expression level dominance. Histone gene expression and nucleosome organization are coordinated through chromatin accessibility. Our study demonstrates the capability to track high-resolution chromatin structure dynamics and reveals their role in the evolution of cis-regulatory landscapes and duplicate gene expression in polyploids, illuminating regulatory ties to subgenomic asymmetry and dominance.
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Affiliation(s)
- Guanjing Hu
- State Key Laboratory of Cotton Bio-breeding and Integrated, Chinese Academy of Agricultural Sciences, Institute of Cotton Research, Anyang 455000, China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Agricultural Genomics Institute at Shenzhen, Shenzhen 518120, China
| | - Corrinne E Grover
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Daniel L Vera
- Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA
| | - Pei-Yau Lung
- Department of Statistics, Florida State University, Tallahassee, FL 32306, USA
| | | | - Emma R Miller
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Justin L Conover
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA
| | - Shujun Ou
- Department of Molecular Genetics, Ohio State University, Columbus, OH 43210, USA
| | - Xianpeng Xiong
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Agricultural Genomics Institute at Shenzhen, Shenzhen 518120, China
| | - De Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Agricultural Genomics Institute at Shenzhen, Shenzhen 518120, China
| | - Dongming Li
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Agricultural Genomics Institute at Shenzhen, Shenzhen 518120, China
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China
| | - Joseph P Gallagher
- Forage Seed and Cereal Research Unit, USDA/Agricultural Research Service, Corvallis, OR 97331, USA
| | - Joshua A Udall
- Crop Germplasm Research Unit, USDA/Agricultural Research Service, College Station, TX 77845, USA
| | - Xin Sui
- Department of Statistics, Florida State University, Tallahassee, FL 32306, USA
| | - Jinfeng Zhang
- Department of Statistics, Florida State University, Tallahassee, FL 32306, USA
| | - Hank W Bass
- Department of Biological Science, Florida State University, Tallahassee, FL 32306, USA
| | - Jonathan F Wendel
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011, USA
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5
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Peleke FF, Zumkeller SM, Gültas M, Schmitt A, Szymański J. Deep learning the cis-regulatory code for gene expression in selected model plants. Nat Commun 2024; 15:3488. [PMID: 38664394 PMCID: PMC11045779 DOI: 10.1038/s41467-024-47744-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Elucidating the relationship between non-coding regulatory element sequences and gene expression is crucial for understanding gene regulation and genetic variation. We explored this link with the training of interpretable deep learning models predicting gene expression profiles from gene flanking regions of the plant species Arabidopsis thaliana, Solanum lycopersicum, Sorghum bicolor, and Zea mays. With over 80% accuracy, our models enabled predictive feature selection, highlighting e.g. the significant role of UTR regions in determining gene expression levels. The models demonstrated remarkable cross-species performance, effectively identifying both conserved and species-specific regulatory sequence features and their predictive power for gene expression. We illustrated the application of our approach by revealing causal links between genetic variation and gene expression changes across fourteen tomato genomes. Lastly, our models efficiently predicted genotype-specific expression of key functional gene groups, exemplified by underscoring known phenotypic and metabolic differences between Solanum lycopersicum and its wild, drought-resistant relative, Solanum pennellii.
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Affiliation(s)
- Fritz Forbang Peleke
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, D-06466 Seeland, OT, Gatersleben, Germany
| | - Simon Maria Zumkeller
- Institute of Bio- and Geosciences, IBG-4: Bioinformatics, Forschungszentrum Jülich, D-52428, Jülich, Germany
- Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich-Heine-Universität Düsseldorf, 40225, Düsseldorf, Germany
| | - Mehmet Gültas
- Faculty of Agriculture, South Westphalia University of Applied Sciences, Soest, 59494, Germany
| | - Armin Schmitt
- Breeding Informatics Group, University of Göttingen, Göttingen, 37075, Germany
- Center of Integrated Breeding Research (CiBreed), Göttingen, 37075, Germany
| | - Jędrzej Szymański
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, D-06466 Seeland, OT, Gatersleben, Germany.
- Institute of Bio- and Geosciences, IBG-4: Bioinformatics, Forschungszentrum Jülich, D-52428, Jülich, Germany.
- Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich-Heine-Universität Düsseldorf, 40225, Düsseldorf, Germany.
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6
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Chen Z, Cortes L, Gallavotti A. Genetic dissection of cis-regulatory control of ZmWUSCHEL1 expression by type B RESPONSE REGULATORS. PLANT PHYSIOLOGY 2024; 194:2240-2248. [PMID: 38060616 PMCID: PMC10980522 DOI: 10.1093/plphys/kiad652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/06/2023] [Indexed: 04/01/2024]
Abstract
Mutations in cis-regulatory regions play an important role in the domestication and improvement of crops by altering gene expression. However, assessing the in vivo impact of cis-regulatory elements (CREs) on transcriptional regulation and phenotypic outcomes remains challenging. Previously, we showed that the dominant Barren inflorescence3 (Bif3) mutant of maize (Zea mays) contains a duplicated copy of the homeobox transcription factor gene ZmWUSCHEL1 (ZmWUS1), named ZmWUS1-B. ZmWUS1-B is controlled by a spontaneously generated novel promoter region that dramatically increases its expression and alters patterning and development of young ears. Overexpression of ZmWUS1-B is caused by a unique enhancer region containing multimerized binding sites for type B RESPONSE REGULATORs (RRs), key transcription factors in cytokinin signaling. To better understand how the enhancer increases the expression of ZmWUS1 in vivo, we specifically targeted the ZmWUS1-B enhancer region by CRISPR-Cas9-mediated editing. A series of deletion events with different numbers of type B RR DNA binding motifs (AGATAT) enabled us to determine how the number of AGATAT motifs impacts in vivo expression of ZmWUS1-B and consequently ear development. In combination with dual-luciferase assays in maize protoplasts, our analysis reveals that AGATAT motifs have an additive effect on ZmWUS1-B expression, while the distance separating AGATAT motifs does not appear to have a meaningful impact, indicating that the enhancer activity derives from the sum of individual CREs. These results also suggest that in maize inflorescence development, there is a threshold of buffering capacity for ZmWUS1 overexpression.
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Affiliation(s)
- Zongliang Chen
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ 08854-8020, USA
| | - Liz Cortes
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ 08854-8020, USA
| | - Andrea Gallavotti
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ 08854-8020, USA
- Department of Plant Biology, Rutgers University, New Brunswick, NJ 08901, USA
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7
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Candela-Ferre J, Diego-Martin B, Pérez-Alemany J, Gallego-Bartolomé J. Mind the gap: Epigenetic regulation of chromatin accessibility in plants. PLANT PHYSIOLOGY 2024; 194:1998-2016. [PMID: 38236303 PMCID: PMC10980423 DOI: 10.1093/plphys/kiae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 11/07/2023] [Accepted: 11/23/2023] [Indexed: 01/19/2024]
Abstract
Chromatin plays a crucial role in genome compaction and is fundamental for regulating multiple nuclear processes. Nucleosomes, the basic building blocks of chromatin, are central in regulating these processes, determining chromatin accessibility by limiting access to DNA for various proteins and acting as important signaling hubs. The association of histones with DNA in nucleosomes and the folding of chromatin into higher-order structures are strongly influenced by a variety of epigenetic marks, including DNA methylation, histone variants, and histone post-translational modifications. Additionally, a wide array of chaperones and ATP-dependent remodelers regulate various aspects of nucleosome biology, including assembly, deposition, and positioning. This review provides an overview of recent advances in our mechanistic understanding of how nucleosomes and chromatin organization are regulated by epigenetic marks and remodelers in plants. Furthermore, we present current technologies for profiling chromatin accessibility and organization.
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Affiliation(s)
- Joan Candela-Ferre
- Instituto de Biología Molecular y Celular de Plantas (IBMCP), CSIC-Universitat Politècnica de València, Valencia, 46022Spain
| | - Borja Diego-Martin
- Instituto de Biología Molecular y Celular de Plantas (IBMCP), CSIC-Universitat Politècnica de València, Valencia, 46022Spain
| | - Jaime Pérez-Alemany
- Instituto de Biología Molecular y Celular de Plantas (IBMCP), CSIC-Universitat Politècnica de València, Valencia, 46022Spain
| | - Javier Gallego-Bartolomé
- Instituto de Biología Molecular y Celular de Plantas (IBMCP), CSIC-Universitat Politècnica de València, Valencia, 46022Spain
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8
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Bobadilla LK, Tranel PJ. Predicting the unpredictable: the regulatory nature and promiscuity of herbicide cross resistance. PEST MANAGEMENT SCIENCE 2024; 80:235-244. [PMID: 37595061 DOI: 10.1002/ps.7728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 08/14/2023] [Accepted: 08/16/2023] [Indexed: 08/20/2023]
Abstract
The emergence of herbicide-resistant weeds is a significant threat to modern agriculture. Cross resistance, a phenomenon where resistance to one herbicide confers resistance to another, is a particular concern owing to its unpredictability. Nontarget-site (NTS) cross resistance is especially challenging to predict, as it arises from genes that encode enzymes that do not directly involve the herbicide target site and can affect multiple herbicides. Recent advancements in genomic and structural biology techniques could provide new venues for predicting NTS resistance in weed species. In this review, we present an overview of the latest approaches that could be used. We discuss the use of genomic and epigenomics techniques such as ATAC-seq and DAP-seq to identify transcription factors and cis-regulatory elements associated with resistance traits. Enzyme/protein structure prediction and docking analysis are discussed as an initial step for predicting herbicide binding affinities with key enzymes to identify candidates for subsequent in vitro validation. We also provide example analyses that can be deployed toward elucidating cross resistance and its regulatory patterns. Ultimately, our review provides important insights into the latest scientific advancements and potential directions for predicting and managing herbicide cross resistance in weeds. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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Affiliation(s)
- Lucas K Bobadilla
- Department of Crop Sciences, University of Illinois, Urbana, IL, USA
| | - Patrick J Tranel
- Department of Crop Sciences, University of Illinois, Urbana, IL, USA
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9
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Manosalva Pérez N, Ferrari C, Engelhorn J, Depuydt T, Nelissen H, Hartwig T, Vandepoele K. MINI-AC: inference of plant gene regulatory networks using bulk or single-cell accessible chromatin profiles. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 117:280-301. [PMID: 37788349 DOI: 10.1111/tpj.16483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/13/2023] [Accepted: 09/16/2023] [Indexed: 10/05/2023]
Abstract
Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. Plant GRNs control transcriptional programs involved in growth, development, and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site (TFBS) information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFBS. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.
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Affiliation(s)
- Nicolás Manosalva Pérez
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium
- Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
| | - Camilla Ferrari
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium
- Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
| | - Julia Engelhorn
- Molecular Physiology Department, Heinrich-Heine University, 40225, Düsseldorf, Germany
- Max Planck Institute for Plant Breeding Research, 50829, Cologne, Germany
| | - Thomas Depuydt
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium
- Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
| | - Hilde Nelissen
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium
- Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
| | - Thomas Hartwig
- Molecular Physiology Department, Heinrich-Heine University, 40225, Düsseldorf, Germany
- Max Planck Institute for Plant Breeding Research, 50829, Cologne, Germany
- Cluster of Excellence on Plant Sciences, Düsseldorf, Germany
| | - Klaas Vandepoele
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium
- Center for Plant Systems Biology, VIB, 9052, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, 9052, Ghent, Belgium
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Myers ZA, Wootan CM, Liang Z, Zhou P, Engelhorn J, Hartwig T, Nathan SM. Conserved and variable heat stress responses of the Heat Shock Factor transcription factor family in maize and Setaria viridis. PLANT DIRECT 2023; 7:e489. [PMID: 37124872 PMCID: PMC10133983 DOI: 10.1002/pld3.489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 01/31/2023] [Accepted: 02/24/2023] [Indexed: 05/03/2023]
Abstract
The Heat Shock Factor (HSF) transcription factor family is a central and required component of plant heat stress responses and acquired thermotolerance. The HSF family has dramatically expanded in plant lineages, often including a repertoire of 20 or more genes. Here we assess and compare the composition, heat responsiveness, and chromatin profiles of the HSF families in maize and Setaria viridis (Setaria), two model C4 panicoid grasses. Both species encode a similar number of HSFs, and examples of both conserved and variable expression responses to a heat stress event were observed between the two species. Chromatin accessibility and genome-wide DNA-binding profiles were generated to assess the chromatin of HSF family members with distinct responses to heat stress. We observed significant variability for both chromatin accessibility and promoter occupancy within similarly regulated sets of HSFs between Setaria and maize, as well as between syntenic pairs of maize HSFs retained following its most recent genome duplication event. Additionally, we observed the widespread presence of TF binding at HSF promoters in control conditions, even at HSFs that are only expressed in response to heat stress. TF-binding peaks were typically near putative HSF-binding sites in HSFs upregulated in response to heat stress, but not in stable or not expressed HSFs. These observations collectively support a complex scenario of expansion and subfunctionalization within this transcription factor family and suggest that within-family HSF transcriptional regulation is a conserved, defining feature of the family.
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Affiliation(s)
- Zachary A. Myers
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
| | - Clair M. Wootan
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
| | - Zhikai Liang
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
| | - Peng Zhou
- Chinese Academy of Agricultural SciencesInstitute of Crop SciencesBeijingChina
| | - Julia Engelhorn
- Heinrich‐Heine UniversityDüsseldorfGermany
- Max Planck Institute for Plant Breeding ResearchCologneGermany
| | - Thomas Hartwig
- Heinrich‐Heine UniversityDüsseldorfGermany
- Max Planck Institute for Plant Breeding ResearchCologneGermany
| | - Springer M. Nathan
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
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11
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Zhou H, Hwarari D, Ma H, Xu H, Yang L, Luo Y. Genomic survey of TCP transcription factors in plants: Phylogenomics, evolution and their biology. Front Genet 2022; 13:1060546. [PMID: 36437962 PMCID: PMC9682074 DOI: 10.3389/fgene.2022.1060546] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 10/27/2022] [Indexed: 09/29/2023] Open
Abstract
The TEOSINTE BRANCHED1 (TBI1), CYCLOIDEA (CYC), and PROLIFERATING CELL NUCLEAR ANTIGEN FACTORS (PCF1 and PCF2) proteins truncated as TCP transcription factors carry conserved basic-helix-loop-helix (bHLH) structure, related to DNA binding functions. Evolutionary history of the TCP genes has shown their presence in early land plants. In this paper, we performed a comparative discussion on the current knowledge of the TCP Transcription Factors in lower and higher plants: their evolutionary history based on the phylogenetics of 849 TCP proteins from 37 plant species, duplication events, and biochemical roles in some of the plants species. Phylogenetics investigations confirmed the classification of TCP TFs into Class I (the PCF1/2), and Class II (the C- clade) factors; the Class II factors were further divided into the CIN- and CYC/TB1- subclade. A trace in the evolution of the TCP Factors revealed an absence of the CYC/TB1subclade in lower plants, and an independent evolution of the CYC/TB1subclade in both eudicot and monocot species. 54% of the total duplication events analyzed were biased towards the dispersed duplication, and we concluded that dispersed duplication events contributed to the expansion of the TCP gene family. Analysis in the TCP factors functional roles confirmed their involvement in various biochemical processes which mainly included promoting cell proliferation in leaves in Class I TCPs, and cell division during plant development in Class II TCP Factors. Apart from growth and development, the TCP Factors were also shown to regulate hormonal and stress response pathways. Although this paper does not exhaust the present knowledge of the TCP Transcription Factors, it provides a base for further exploration of the gene family.
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Affiliation(s)
- Haiying Zhou
- Jiangsu Key Laboratory for Eco-Agricultural Biotechnology Around Hongze Lake, Jiangsu Collaborative In-novation Center of Regional Modern Agriculture and Environmental Protection, Huaiyin Normal University, Huai’an, China
| | - Delight Hwarari
- College of Biology and the Environment, Nanjing Forestry University, Nanjing, China
| | - Hongyu Ma
- College of Plant Protection, Nanjing Agricultural University, Nanjing, China
| | - Haibin Xu
- College of Biology and the Environment, Nanjing Forestry University, Nanjing, China
| | - Liming Yang
- College of Biology and the Environment, Nanjing Forestry University, Nanjing, China
| | - Yuming Luo
- Jiangsu Key Laboratory for Eco-Agricultural Biotechnology Around Hongze Lake, Jiangsu Collaborative In-novation Center of Regional Modern Agriculture and Environmental Protection, Huaiyin Normal University, Huai’an, China
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12
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Liang Z, Myers ZA, Petrella D, Engelhorn J, Hartwig T, Springer NM. Mapping responsive genomic elements to heat stress in a maize diversity panel. Genome Biol 2022; 23:234. [PMID: 36345007 PMCID: PMC9639295 DOI: 10.1186/s13059-022-02807-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 10/29/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Many plant species exhibit genetic variation for coping with environmental stress. However, there are still limited approaches to effectively uncover the genomic region that regulates distinct responsive patterns of the gene across multiple varieties within the same species under abiotic stress. RESULTS By analyzing the transcriptomes of more than 100 maize inbreds, we reveal many cis- and trans-acting eQTLs that influence the expression response to heat stress. The cis-acting eQTLs in response to heat stress are identified in genes with differential responses to heat stress between genotypes as well as genes that are only expressed under heat stress. The cis-acting variants for heat stress-responsive expression likely result from distinct promoter activities, and the differential heat responses of the alleles are confirmed for selected genes using transient expression assays. Global footprinting of transcription factor binding is performed in control and heat stress conditions to document regions with heat-enriched transcription factor binding occupancies. CONCLUSIONS Footprints enriched near proximal regions of characterized heat-responsive genes in a large association panel can be utilized for prioritizing functional genomic regions that regulate genotype-specific responses under heat stress.
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Affiliation(s)
- Zhikai Liang
- grid.17635.360000000419368657Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108 USA
| | - Zachary A. Myers
- grid.17635.360000000419368657Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108 USA
| | - Dominic Petrella
- grid.17635.360000000419368657Department of Horticulture, University of Minnesota, Saint Paul, MN 55108 USA ,grid.261331.40000 0001 2285 7943Present address: Agricultural Technical Institute, The Ohio State University, Wooster, OH 44691 USA
| | - Julia Engelhorn
- grid.419498.90000 0001 0660 6765Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany ,grid.411327.20000 0001 2176 9917Heinrich-Heine University, 40225 Dusseldorf, Germany
| | - Thomas Hartwig
- grid.419498.90000 0001 0660 6765Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany ,grid.411327.20000 0001 2176 9917Heinrich-Heine University, 40225 Dusseldorf, Germany
| | - Nathan M. Springer
- grid.17635.360000000419368657Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108 USA
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Rozière J, Guichard C, Brunaud V, Martin ML, Coursol S. A comprehensive map of preferentially located motifs reveals distinct proximal cis-regulatory sequences in plants. FRONTIERS IN PLANT SCIENCE 2022; 13:976371. [PMID: 36311095 PMCID: PMC9597372 DOI: 10.3389/fpls.2022.976371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/21/2022] [Indexed: 06/16/2023]
Abstract
Identification of cis-regulatory sequences controlling gene expression is an arduous challenge that is being actively explored to discover key genetic factors responsible for traits of agronomic interest. Here, we used a genome-wide de novo approach to investigate preferentially located motifs (PLMs) in the proximal cis-regulatory landscape of Arabidopsis thaliana and Zea mays. We report three groups of PLMs in both the 5'- and 3'-gene-proximal regions and emphasize conserved PLMs in both species, particularly in the 3'-gene-proximal region. Comparison with resources from transcription factor and microRNA binding sites shows that 79% of the identified PLMs are unassigned, although some are supported by MNase-defined cistrome occupancy analysis. Enrichment analyses further reveal that unassigned PLMs provide functional predictions that differ from those derived from transcription factor and microRNA binding sites. Our study provides a comprehensive map of PLMs and demonstrates their potential utility for future characterization of orphan genes in plants.
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Affiliation(s)
- Julien Rozière
- Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
- Université de Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
- Université Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), Versailles, France
| | - Cécile Guichard
- Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
- Université de Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
| | - Véronique Brunaud
- Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
- Université de Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
| | - Marie-Laure Martin
- Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
- Université de Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France
- Université Paris-Saclay, INRAE, AgroParisTech, UMR MIA-Paris-Saclay, Palaiseau, France
| | - Sylvie Coursol
- Université Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), Versailles, France
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Hajheidari M, Huang SSC. Elucidating the biology of transcription factor-DNA interaction for accurate identification of cis-regulatory elements. CURRENT OPINION IN PLANT BIOLOGY 2022; 68:102232. [PMID: 35679803 PMCID: PMC10103634 DOI: 10.1016/j.pbi.2022.102232] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 05/03/2023]
Abstract
Transcription factors (TFs) play a critical role in determining cell fate decisions by integrating developmental and environmental signals through binding to specific cis-regulatory modules and regulating spatio-temporal specificity of gene expression patterns. Precise identification of functional TF binding sites in time and space not only will revolutionize our understanding of regulatory networks governing cell fate decisions but is also instrumental to uncover how genetic variations cause morphological diversity or disease. In this review, we discuss recent advances in mapping TF binding sites and characterizing the various parameters underlying the complexity of binding site recognition by TFs.
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Affiliation(s)
- Mohsen Hajheidari
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, USA
| | - Shao-Shan Carol Huang
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, USA.
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Epigenome guided crop improvement: current progress and future opportunities. Emerg Top Life Sci 2022; 6:141-151. [PMID: 35072210 PMCID: PMC9023013 DOI: 10.1042/etls20210258] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/14/2021] [Accepted: 01/04/2022] [Indexed: 12/22/2022]
Abstract
Epigenomics encompasses a broad field of study, including the investigation of chromatin states, chromatin modifications and their impact on gene regulation; as well as the phenomena of epigenetic inheritance. The epigenome is a multi-modal layer of information superimposed on DNA sequences, instructing their usage in gene expression. As such, it is an emerging focus of efforts to improve crop performance. Broadly, this might be divided into avenues that leverage chromatin information to better annotate and decode plant genomes, and into complementary strategies that aim to identify and select for heritable epialleles that control crop traits independent of underlying genotype. In this review, we focus on the first approach, which we term ‘epigenome guided’ improvement. This encompasses the use of chromatin profiles to enhance our understanding of the composition and structure of complex crop genomes. We discuss the current progress and future prospects towards integrating this epigenomic information into crop improvement strategies; in particular for CRISPR/Cas9 gene editing and precision genome engineering. We also highlight some specific opportunities and challenges for grain and horticultural crops.
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