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Gomez-Campo K, Sanchez R, Martínez-Rugerio I, Yang X, Maher T, Osborne CC, Enriquez S, Baums IB, Mackenzie SA, Iglesias-Prieto R. Phenotypic plasticity for improved light harvesting, in tandem with methylome repatterning in reef-building corals. Mol Ecol 2024; 33:e17246. [PMID: 38153177 PMCID: PMC10922902 DOI: 10.1111/mec.17246] [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: 05/15/2023] [Revised: 11/24/2023] [Accepted: 11/30/2023] [Indexed: 12/29/2023]
Abstract
Acclimatization through phenotypic plasticity represents a more rapid response to environmental change than adaptation and is vital to optimize organisms' performance in different conditions. Generally, animals are less phenotypically plastic than plants, but reef-building corals exhibit plant-like properties. They are light dependent with a sessile and modular construction that facilitates rapid morphological changes within their lifetime. We induced phenotypic changes by altering light exposure in a reciprocal transplant experiment and found that coral plasticity is a colony trait emerging from comprehensive morphological and physiological changes within the colony. Plasticity in skeletal features optimized coral light harvesting and utilization and paralleled significant methylome and transcriptome modifications. Network-associated responses resulted in the identification of hub genes and clusters associated to the change in phenotype: inter-partner recognition and phagocytosis, soft tissue growth and biomineralization. Furthermore, we identified hub genes putatively involved in animal photoreception-phototransduction. These findings fundamentally advance our understanding of how reef-building corals repattern the methylome and adjust a phenotype, revealing an important role of light sensing by the coral animal to optimize photosynthetic performance of the symbionts.
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Affiliation(s)
- Kelly Gomez-Campo
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Robersy Sanchez
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | | | - Xiaodong Yang
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Tom Maher
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - C. Cornelia Osborne
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Susana Enriquez
- Unidad Académica de Sistemas Arrecifales Puerto Morelos, Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, 77580, México
| | - Iliana B. Baums
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sally A. Mackenzie
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Plant Science, The Pennsylvania State University, University Park, PA 16802, USA
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Sanchez R, Mackenzie SA. On the thermodynamics of DNA methylation process. Sci Rep 2023; 13:8914. [PMID: 37264042 DOI: 10.1038/s41598-023-35166-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 05/13/2023] [Indexed: 06/03/2023] Open
Abstract
DNA methylation is an epigenetic mechanism that plays important roles in various biological processes including transcriptional and post-transcriptional regulation, genomic imprinting, aging, and stress response to environmental changes and disease. Consistent with thermodynamic principles acting within living systems and the application of maximum entropy principle, we propose a theoretical framework to understand and decode the DNA methylation process. A central tenet of this argument is that the probability density function of DNA methylation information-divergence summarizes the statistical biophysics underlying spontaneous methylation background and implicitly bears on the channel capacity of molecular machines conforming to Shannon's capacity theorem. On this theoretical basis, contributions from the molecular machine (enzyme) logical operations to Gibb entropy (S) and Helmholtz free energy (F) are intrinsic. Application to the estimations of S on datasets from Arabidopsis thaliana suggests that, as a thermodynamic state variable, individual methylome entropy is completely determined by the current state of the system, which in biological terms translates to a correspondence between estimated entropy values and observable phenotypic state. In patients with different types of cancer, results suggest that a significant information loss occurs in the transition from differentiated (healthy) tissues to cancer cells. This type of analysis may have important implications for early-stage diagnostics. The analysis of entropy fluctuations on experimental datasets revealed existence of restrictions on the magnitude of genome-wide methylation changes originating by organismal response to environmental changes. Only dysfunctional stages observed in the Arabidopsis mutant met1 and in cancer cells do not conform to these rules.
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Affiliation(s)
- Robersy Sanchez
- Department of Biology, The Pennsylvania State University, 361 Frear North Bldg, University Park, PA, 16802, USA.
| | - Sally A Mackenzie
- Departments of Biology and Plant Science, The Pennsylvania State University, 362 Frear North Bldg, University Park, PA, 16802, USA.
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Hafner A, Mackenzie S. Re-analysis of publicly available methylomes using signal detection yields new information. Sci Rep 2023; 13:3307. [PMID: 36849495 PMCID: PMC9971211 DOI: 10.1038/s41598-023-30422-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 02/22/2023] [Indexed: 03/01/2023] Open
Abstract
Cytosine methylation is an epigenetic mark that participates in regulation of gene expression and chromatin stability in plants. Advancements in whole genome sequencing technologies have enabled investigation of methylome dynamics under different conditions. However, the computational methods for analyzing bisulfite sequence data have not been unified. Contention remains in the correlation of differentially methylated positions with the investigated treatment and exclusion of noise, inherent to these stochastic datasets. The prevalent approaches apply Fisher's exact test, logistic, or beta regression, followed by an arbitrary cut-off for differences in methylation levels. A different strategy, the MethylIT pipeline, utilizes signal detection to determine cut-off based on a fitted generalized gamma probability distribution of methylation divergence. Re-analysis of publicly available BS-seq data from two epigenetic studies in Arabidopsis and applying MethylIT revealed additional, previously unreported results. Methylome repatterning in response to phosphate starvation was confirmed to be tissue-specific and included phosphate assimilation genes in addition to sulfate metabolism genes not implicated in the original study. During seed germination plants undergo major methylome reprogramming and use of MethylIT allowed us to identify stage-specific gene networks. We surmise from these comparative studies that robust methylome experiments must account for data stochasticity to achieve meaningful functional analyses.
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Affiliation(s)
- Alenka Hafner
- grid.29857.310000 0001 2097 4281Department of Biology, The Pennsylvania State University, 362 Frear N Bldg, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 4281Intercollege Graduate Degree Program in Plant Biology, The Pennsylvania State University, University Park, PA USA
| | - Sally Mackenzie
- Department of Biology, The Pennsylvania State University, 362 Frear N Bldg, University Park, PA, 16802, USA. .,Department of Plant Science, The Pennsylvania State University, University Park, PA, USA.
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Segregation of an MSH1 RNAi transgene produces heritable non-genetic memory in association with methylome reprogramming. Nat Commun 2020; 11:2214. [PMID: 32371941 PMCID: PMC7200659 DOI: 10.1038/s41467-020-16036-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 04/09/2020] [Indexed: 12/23/2022] Open
Abstract
MSH1 is a plant-specific protein. RNAi suppression of MSH1 results in phenotype variability for developmental and stress response pathways. Segregation of the RNAi transgene produces non-genetic msh1 ‘memory’ with multi-generational inheritance. First-generation memory versus non-memory comparison, and six-generation inheritance studies, identifies gene-associated, heritable methylation repatterning. Genome-wide methylome analysis integrated with RNAseq and network-based enrichment studies identifies altered circadian clock networks, and phytohormone and stress response pathways that intersect with circadian control. A total of 373 differentially methylated loci comprising these networks are sufficient to discriminate memory from nonmemory full sibs. Methylation inhibitor 5-azacytidine diminishes the differences between memory and wild type for growth, gene expression and methylation patterning. The msh1 reprogramming is dependent on functional HISTONE DEACETYLASE 6 and methyltransferase MET1, and transition to memory requires the RNA-directed DNA methylation pathway. This system of phenotypic plasticity may serve as a potent model for defining accelerated plant adaptation during environmental change. Segregation of an MSH1 RNAi transgene produces non-genetic memory that displays transgenerational inheritance in Arabidopsis. Here, the authors compare memory and non-memory full-sib progenies to show the involvement of DNA methylation reprogramming, involving the RdDM pathway, in transition to a heritable memory state.
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Abstract
Cytosine methylation as a reversible chromatin mark has been investigated extensively for its influence on gene silencing and the regulation of its dynamic association-disassociation at specific sites within a eukaryotic genome. With the remarkable reductions in cost and time associated with whole-genome DNA sequence analysis, coupled with the high fidelity of bisulfite-treated DNA sequencing, single nucleotide resolution of cytosine methylation repatterning within even very large genomes is increasingly achievable. What remains a challenge is the analysis of genome-wide methylome datasets and, consequently, a clear understanding of the overall influence of methylation repatterning on gene expression or vice versa. Reported data have sometimes been subject to stringent data filtering methods that can serve to skew downstream biological interpretation. These complications derive from methylome analysis procedures that vary widely in method and parameter setting. DNA methylation as a chromatin feature that influences DNA stability can be dynamic and rapidly responsive to environmental change. Consequently, methods to discriminate background "noise" of the system from biological signal in response to specific perturbation is essential in some types of experiments. We describe numerous aspects of whole-genome bisulfite sequence data that must be contemplated as well as the various steps of methylome data analysis which impact the biological interpretation of the final output.
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Sanchez R, Yang X, Maher T, Mackenzie SA. Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics. Int J Mol Sci 2019; 20:E5343. [PMID: 31717838 PMCID: PMC6862328 DOI: 10.3390/ijms20215343] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 10/09/2019] [Accepted: 10/24/2019] [Indexed: 12/29/2022] Open
Abstract
Advances in the study of human DNA methylation variation offer a new avenue for the translation of epigenetic research results to clinical applications. Although current approaches to methylome analysis have been helpful in revealing an epigenetic influence in major human diseases, this type of analysis has proven inadequate for the translation of these advances to clinical diagnostics. As in any clinical test, the use of a methylation signal for diagnostic purposes requires the estimation of an optimal cutoff value for the signal, which is necessary to discriminate a signal induced by a disease state from natural background variation. To address this issue, we propose the application of a fundamental signal detection theory and machine learning approaches. Simulation studies and tests of two available methylome datasets from autism and leukemia patients demonstrate the feasibility of this approach in clinical diagnostics, providing high discriminatory power for the methylation signal induced by disease, as well as high classification performance. Specifically, the analysis of whole biomarker genomic regions could suffice for a diagnostic, markedly decreasing its cost.
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Affiliation(s)
- Robersy Sanchez
- Departments of Biology and Plant Science, The Pennsylvania State University, University Park, PA 16802, USA; (X.Y.); (T.M.)
| | | | | | - Sally A. Mackenzie
- Departments of Biology and Plant Science, The Pennsylvania State University, University Park, PA 16802, USA; (X.Y.); (T.M.)
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Shao MR, Kumar Kenchanmane Raju S, Laurie JD, Sanchez R, Mackenzie SA. Stress-responsive pathways and small RNA changes distinguish variable developmental phenotypes caused by MSH1 loss. BMC PLANT BIOLOGY 2017; 17:47. [PMID: 28219335 PMCID: PMC5319189 DOI: 10.1186/s12870-017-0996-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 02/08/2017] [Indexed: 05/03/2023]
Abstract
BACKGROUND Proper regulation of nuclear-encoded, organelle-targeted genes is crucial for plastid and mitochondrial function. Among these genes, MutS Homolog 1 (MSH1) is notable for generating an assortment of mutant phenotypes with varying degrees of penetrance and pleiotropy. Stronger phenotypes have been connected to stress tolerance and epigenetic changes, and in Arabidopsis T-DNA mutants, two generations of homozygosity with the msh1 insertion are required before severe phenotypes begin to emerge. These observations prompted us to examine how msh1 mutants contrast according to generation and phenotype by profiling their respective transcriptomes and small RNA populations. RESULTS Using RNA-seq, we analyze pathways that are associated with MSH1 loss, including abiotic stresses such as cold response, pathogen defense and immune response, salicylic acid, MAPK signaling, and circadian rhythm. Subtle redox and environment-responsive changes also begin in the first generation, in the absence of strong phenotypes. Using small RNA-seq we further identify miRNA changes, and uncover siRNA trends that indicate modifications at the chromatin organization level. In all cases, the magnitude of changes among protein-coding genes, transposable elements, and small RNAs increases according to generation and phenotypic severity. CONCLUSION Loss of MSH1 is sufficient to cause large-scale regulatory changes in pathways that have been individually linked to one another, but rarely described all together within a single mutant background. This study enforces the recognition of organelles as critical integrators of both internal and external cues, and highlights the relationship between organelle and nuclear regulation in fundamental aspects of plant development and stress signaling. Our findings also encourage further investigation into potential connections between organelle state and genome regulation vis-á-vis small RNA feedback.
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Affiliation(s)
- Mon-Ray Shao
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE USA
| | | | - John D. Laurie
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE USA
- Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - Robersy Sanchez
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE USA
| | - Sally A. Mackenzie
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE USA
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Sanchez R, Mackenzie SA. Genome-Wide Discriminatory Information Patterns of Cytosine DNA Methylation. Int J Mol Sci 2016; 17:ijms17060938. [PMID: 27322251 PMCID: PMC4926471 DOI: 10.3390/ijms17060938] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Revised: 05/16/2016] [Accepted: 06/02/2016] [Indexed: 12/11/2022] Open
Abstract
Cytosine DNA methylation (CDM) is a highly abundant, heritable but reversible chemical modification to the genome. Herein, a machine learning approach was applied to analyze the accumulation of epigenetic marks in methylomes of 152 ecotypes and 85 silencing mutants of Arabidopsis thaliana. In an information-thermodynamics framework, two measurements were used: (1) the amount of information gained/lost with the CDM changes I R and (2) the uncertainty of not observing a SNP L C R . We hypothesize that epigenetic marks are chromosomal footprints accounting for different ontogenetic and phylogenetic histories of individual populations. A machine learning approach is proposed to verify this hypothesis. Results support the hypothesis by the existence of discriminatory information (DI) patterns of CDM able to discriminate between individuals and between individual subpopulations. The statistical analyses revealed a strong association between the topologies of the structured population of Arabidopsis ecotypes based on I R and on LCR, respectively. A statistical-physical relationship between I R and L C R was also found. Results to date imply that the genome-wide distribution of CDM changes is not only part of the biological signal created by the methylation regulatory machinery, but ensures the stability of the DNA molecule, preserving the integrity of the genetic message under continuous stress from thermal fluctuations in the cell environment.
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Affiliation(s)
- Robersy Sanchez
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68588, USA.
| | - Sally A Mackenzie
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68588, USA.
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