Sensory plastid-associated PsbP DOMAIN-CONTAINING PROTEIN 3 triggers plant growth- and defense-related epigenetic responses.

Sensory plastids are important in plant responses to environmental changes. Previous studies show that MutS HOMOLOG 1 (MSH1) perturbation in sensory plastids induces heritable epigenetic phenotype adjustment. Previously, the PsbP homolog DOMAIN-CONTAINING PROTEIN 3 (PPD3), a protein of unknown function, was postulated to be an interactor with MSH1. This study investigates the relationship of PPD3 with MSH1 and with plant environmental sensing. The ppd3 mutant displays a whole-plant phenotype variably altered in growth rate, flowering time, reactive oxygen species (ROS) modulation and response to salt, with effects on meristem growth. Present in both chloroplasts and sensory plastids, PPD3 colocalized with MSH1 in root tips but not in leaf tissues. The suppression or overexpression of PPD3 affected the plant growth rate and stress tolerance, and led to a heritable, heterogenous 'memory' state with both dwarfed and vigorous growth phenotypes. Gene expression and DNA methylome data sets from PPD3-OX and derived memory states showed enrichment in growth versus defense networks and meristem effects. Our results support a model of sensory plastid influence on nuclear epigenetic behavior and ppd3 as a second trigger, functioning within meristem plastids to recalibrate growth plasticity.

Phenotypic plasticity for improved light harvesting, in tandem with methylome repatterning in reef-building corals.

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.

Specialized Plastids Trigger Tissue-Specific Signaling for Systemic Stress Response in Plants.

Plastids comprise a complex set of organelles in plants that can undergo distinctive patterns of differentiation and redifferentiation during their lifespan. Plastids localized to the epidermis and vascular parenchyma are distinctive in size, structural features, and functions. These plastids are termed "sensory" plastids, and here we show their proteome to be distinct from chloroplasts, with specialized stress-associated features. The distinctive sensory plastid proteome in Arabidopsis (Arabidopsis thaliana) derives from spatiotemporal regulation of nuclear genes encoding plastid-targeted proteins. Perturbation caused by depletion of the sensory plastid-specific protein MutS HOMOLOG1 conditioned local, programmed changes in gene networks controlling chromatin, stress-related phytohormone, and circadian clock behavior and producing a global, systemic stress response in the plant. We posit that the sensory plastid participates in sensing environmental stress, integrating this sensory function with epigenetic and gene expression circuitry to condition heritable stress memory.

Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics.

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.

An epigenetic breeding system in soybean for increased yield and stability.

Epigenetic variation has been associated with a wide range of adaptive phenotypes in plants, but there exist few direct means for exploiting this variation. RNAi suppression of the plant-specific gene, MutS HOMOLOG1 (MSH1), in multiple plant species produces a range of developmental changes accompanied by modulation of defence, phytohormone and abiotic stress response pathways along with methylome repatterning. This msh1-conditioned developmental reprogramming is retained independent of transgene segregation, giving rise to transgene-null 'memory' effects. An isogenic memory line crossed to wild type produces progeny families displaying increased variation in adaptive traits that respond to selection. This study investigates amenability of the MSH1 system for inducing agronomically valuable epigenetic variation in soybean. We developed MSH1 epi-populations by crossing with msh1-acquired soybean memory lines. Derived soybean epi-lines showed increase in variance for multiple yield-related traits including pods per plant, seed weight and maturity time in both glasshouse and field trials. Selected epi-F2:4 and epi-F2:5 lines showed an increase in seed yield over wild type. By epi-F2:6, we observed a return of MSH1-derived enhanced growth back to wild-type levels. Epi-populations also showed evidence of reduced epitype-by-environment (e × E) interaction, indicating higher yield stability. Transcript profiling of epi-lines identified putative signatures of enhanced growth behaviour across generations. Genes related to cell cycle, abscisic acid biosynthesis and auxin response, particularly SMALL AUXIN UP RNAs (SAURs), were differentially expressed in epi-F2:4 lines that showed increased yield when compared to epi-F2:6 . These data support the potential of MSH1-derived epigenetic variation in plant breeding for enhanced yield and yield stability.

Stress-responsive pathways and small RNA changes distinguish variable developmental phenotypes caused by MSH1 loss.

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.

Genome-Wide Discriminatory Information Patterns of Cytosine DNA Methylation.

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.

On the thermodynamics of DNA methylation process.

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.

Methylome decoding of RdDM-mediated reprogramming effects in the Arabidopsis MSH1 system.

BACKGROUND: Plants undergo programmed chromatin changes in response to environment, influencing heritable phenotypic plasticity. The RNA-directed DNA methylation (RdDM) pathway is an essential component of this reprogramming process. The relationship of epigenomic changes to gene networks on a genome-wide basis has been elusive, particularly for intragenic DNA methylation repatterning. RESULTS: Epigenomic reprogramming is tractable to detailed study and cross-species modeling in the MSH1 system, where perturbation of the plant-specific gene MSH1 triggers at least four distinct nongenetic states to impact plant stress response and growth vigor. Within this system, we have defined RdDM target loci toward decoding phenotype-relevant methylome data. We analyze intragenic methylome repatterning associated with phenotype transitions, identifying state-specific cytosine methylation changes in pivotal growth-versus-stress, chromatin remodeling, and RNA spliceosome gene networks that encompass 871 genes. Over 77% of these genes, and 81% of their central network hubs, are functionally confirmed as RdDM targets based on analysis of mutant datasets and sRNA cluster associations. These dcl2/dcl3/dcl4-sensitive gene methylation sites, many present as singular cytosines, reside within identifiable sequence motifs. These data reflect intragenic methylation repatterning that is targeted and amenable to prediction. CONCLUSIONS: A prevailing assumption that biologically relevant DNA methylation variation occurs predominantly in density-defined differentially methylated regions overlooks behavioral features of intragenic, single-site cytosine methylation variation. RdDM-dependent methylation changes within identifiable sequence motifs reveal gene hubs within networks discriminating stress response and growth vigor epigenetic phenotypes. This study uncovers components of a methylome "code" for de novo intragenic methylation repatterning during plant phenotype transitions.

Implementation of Epigenetic Variation in Sorghum Selection and Implications for Crop Resilience Breeding.

Crop resilience and yield stability are complex traits essential for food security. Sorghum bicolor is an important grain crop that shows promise for its natural resilience to drought and potential for marginal land production. We have developed sorghum lines in the Tx430 genetic background suppressed for MSH1 expression as a means of inducing de novo epigenetic variation, and have used these materials to evaluate changes in plant growth vigor. Plant crossing and selection in two distinct environments revealed features of phenotypic plasticity derived from MSH1 manipulation. Introduction of an epigenetic variation to an isogenic sorghum population, in the absence of selection, resulted in 10% yield increase under ideal field conditions and 20% increase under extreme low nitrogen conditions. However, incorporation of early-stage selection amplified these outcomes to 36% yield increase under ideal conditions and 64% increase under marginal field conditions. Interestingly, the best outcomes were derived by selecting mid-range performance early-generation lines rather than highest performing. Data also suggested that phenotypic plasticity derived from the epigenetic variation was non-uniform in its response to environmental variability but served to reduce genotype × environment interaction. The MSH1-derived growth vigor appeared to be associated with enhanced seedling root growth and altered expression of auxin response pathways, and plants showed evidence of cold tolerance, features consistent with observations made previously in Arabidopsis. These data imply that the MSH1 system is conserved across plant species, pointing to the value of parallel model plant studies to help devise effective plant selection strategies for epigenetic breeding in multiple crops.

Integrative Network Analysis of Differentially Methylated and Expressed Genes for Biomarker Identification in Leukemia.

Genome-wide DNA methylation and gene expression are commonly altered in pediatric acute lymphoblastic leukemia (PALL). Integrated network analysis of cytosine methylation and expression datasets has the potential to provide deeper insights into the complex disease states and their causes than individual disconnected analyses. With the purpose of identifying reliable cancer-associated methylation signal in gene regions from leukemia patients, we present an integrative network analysis of differentially methylated (DMGs) and differentially expressed genes (DEGs). The application of a novel signal detection-machine learning approach to methylation analysis of whole genome bisulfite sequencing (WGBS) data permitted a high level of methylation signal resolution in cancer-associated genes and pathways. This integrative network analysis approach revealed that gene expression and methylation consistently targeted the same gene pathways relevant to cancer: Pathways in cancer, Ras signaling pathway, PI3K-Akt signaling pathway, and Rap1 signaling pathway, among others. Detected gene hubs and hub sub-networks were integrated by signature loci associated with cancer that include, for example, NOTCH1, RAC1, PIK3CD, BCL2, and EGFR. Statistical analysis disclosed a stochastic deterministic relationship between methylation and gene expression within the set of genes simultaneously identified as DEGs and DMGs, where larger values of gene expression changes were probabilistically associated with larger values of methylation changes. Concordance analysis of the overlap between enriched pathways in DEG and DMG datasets revealed statistically significant agreement between gene expression and methylation changes. These results support the potential identification of reliable and stable methylation biomarkers at genes for cancer diagnosis and prognosis.

MSH1-induced heritable enhanced growth vigor through grafting is associated with the RdDM pathway in plants.

Plants transmit signals long distances, as evidenced in grafting experiments that create distinct rootstock-scion junctions. Noncoding small RNA is a signaling molecule that is graft transmissible, participating in RNA-directed DNA methylation; but the meiotic transmissibility of graft-mediated epigenetic changes remains unclear. Here, we exploit the MSH1 system in Arabidopsis and tomato to introduce rootstock epigenetic variation to grafting experiments. Introducing mutations dcl2, dcl3 and dcl4 to the msh1 rootstock disrupts siRNA production and reveals RdDM targets of methylation repatterning. Progeny from grafting experiments show enhanced growth vigor relative to controls. This heritable enhancement-through-grafting phenotype is RdDM-dependent, involving 1380 differentially methylated genes, many within auxin-related gene pathways. Growth vigor is associated with robust root growth of msh1 graft progeny, a phenotype associated with auxin transport based on inhibitor assays. Large-scale field experiments show msh1 grafting effects on tomato plant performance, heritable over five generations, demonstrating the agricultural potential of epigenetic variation.

Segregation of an MSH1 RNAi transgene produces heritable non-genetic memory in association with methylome reprogramming.

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.

A novel Lie algebra of the genetic code over the Galois field of four DNA bases.

Starting from the four DNA bases order in the Boolean lattice, a novel Lie Algebra of the genetic code is proposed. Here, the main partitions of the genetic code table were obtained as equivalent classes of quotient spaces of the genetic code vector space over the Galois field of the four DNA bases. The new algebraic structure shows strong connections among algebraic relationships, codon assignments and physicochemical properties of amino acids. Moreover, a distance defined between codons expresses a physicochemical meaning. It was also noticed that the distance between wild type and mutant codons tends to be small in mutational variants of four genes: human phenylalanine hydroxylase, human beta-globin, HIV-1 protease and HIV-1 reverse transcriptase. These results strongly suggest that deterministic rules in genetic code origin must be involved.

Information Thermodynamics of Cytosine DNA Methylation.

Cytosine DNA methylation (CDM) is a stable epigenetic modification to the genome and a widespread regulatory process in living organisms that involves multicomponent molecular machines. Genome-wide cytosine methylation patterning participates in the epigenetic reprogramming of a cell, suggesting that the biological information contained within methylation positions may be amenable to decoding. Adaptation to a new cellular or organismal environment also implies the potential for genome-wide redistribution of CDM changes that will ensure the stability of DNA molecules. This raises the question of whether or not we would be able to sort out the regulatory methylation signals from the CDM background ("noise") induced by thermal fluctuations. Here, we propose a novel statistical and information thermodynamic description of the CDM changes to address the last question. The physical basis of our statistical mechanical model was evaluated in two respects: 1) the adherence to Landauer's principle, according to which molecular machines must dissipate a minimum energy ε = kBT ln2 at each logic operation, where kB is the Boltzmann constant, and T is the absolute temperature and 2) whether or not the binary stretch of methylation marks on the DNA molecule comprise a language of sorts, properly constrained by thermodynamic principles. The study was performed for genome-wide methylation data from 152 ecotypes and 40 trans-generational variations of Arabidopsis thaliana and 93 human tissues. The DNA persistence length, a basic mechanical property altered by CDM, was estimated with values from 39 to 66.9 nm. Classical methylome analysis can be retrieved by applying information thermodynamic modelling, which is able to discriminate signal from noise. Our finding suggests that the CDM signal comprises a language scheme properly constrained by molecular thermodynamic principles, which is part of an epigenomic communication system that obeys the same thermodynamic rules as do current human communication systems.

Arabidopsis MSH1 mutation alters the epigenome and produces heritable changes in plant growth.

Plant phenotypes respond to environmental change, an adaptive capacity that is at least partly transgenerational. However, epigenetic components of this interplay are difficult to measure. Depletion of the nuclear-encoded protein MSH1 causes dramatic and heritable changes in plant development, and here we show that crossing these altered plants with isogenic wild type produces epi-lines with heritable, enhanced growth vigour. Pericentromeric DNA hypermethylation occurs in a subset of msh1 mutants, indicative of heightened transposon repression, while enhanced growth epi-lines show large chromosomal segments of differential CG methylation, reflecting genome-wide reprogramming. When seedlings are treated with 5-azacytidine, root growth of epi-lines is restored to wild-type levels, implicating hypermethylation in enhanced growth. Grafts of wild-type floral stems to mutant rosettes produce progeny with enhanced growth and altered CG methylation strikingly similar to epi-lines, indicating a mobile signal when MSH1 is downregulated, and confirming the programmed nature of methylome and phenotype changes.

Evolutionary analysis of DNA-protein-coding regions based on a genetic code cube metric.

The right estimation of the evolutionary distance between DNA or protein sequences is the cornerstone of the current phylogenetic analysis based on distance methods. Herein, it is demonstrated that the Manhattan distance (dw), weighted by the evolutionary importance of the nucleotide bases in the codon, is a naturally derived metric in the standard genetic code cube inserted into the three-dimensional Euclidean space. Based on the application of distance dw, a novel evolutionary model is proposed. This model includes insertion/deletion mutations that are very important for cancer studies, but usually discarded in classical evolutionary models. In this study, the new evolutionary model was applied to the phylogenetic analysis of the DNA protein-coding regions of 13 mammal mitochondrial genomes and of four cancer genetic- susceptibility genes (ATM, BRCA1, BRCA2 and p53) from nine mammals. The opossum (a marsupial) was used as an out-group species for both sets of sequences. The new evolutionary model yielded the correct topology, while the current models failed to separate the evolutionarily distant species of mouse and opossum.

An algebraic hypothesis about the primeval genetic code architecture.

A plausible architecture of an ancient genetic code is derived from an extended base triplet vector space over the Galois field of the extended base alphabet {D,A,C,G,U}, where symbol D represents one or more hypothetical bases with unspecific pairings. We hypothesized that the high degeneration of a primeval genetic code with five bases and the gradual origin and improvement of a primeval DNA repair system could make possible the transition from ancient to modern genetic codes. Our results suggest that the Watson-Crick base pairing G identical with C and A=U and the non-specific base pairing of the hypothetical ancestral base D used to define the sum and product operations are enough features to determine the coding constraints of the primeval and the modern genetic code, as well as, the transition from the former to the latter. Geometrical and algebraic properties of this vector space reveal that the present codon assignment of the standard genetic code could be induced from a primeval codon assignment. Besides, the Fourier spectrum of the extended DNA genome sequences derived from the multiple sequence alignment suggests that the called period-3 property of the present coding DNA sequences could also exist in the ancient coding DNA sequences. The phylogenetic analyses achieved with metrics defined in the N-dimensional vector space (B(3))(N) of DNA sequences and with the new evolutionary model presented here also suggest that an ancient DNA coding sequence with five or more bases does not contradict the expected evolutionary history.

A novel algebraic structure of the genetic code over the galois field of four DNA bases.

A novel algebraic structure of the genetic code is proposed. Here, the principal partitions of the genetic code table were obtained as equivalent classes of quotient spaces of the genetic code vector space over the Galois field of the four DNA bases. The new algebraic structure shows strong connections among algebraic relationships, codon assignment and physicochemical properties of amino acids. Moreover, a distance function defined between the codon binary representations in the vector space was demonstrated to have a linear behavior respect to physical variables such as the mean of amino acids interaction energies in proteins. It was also noticed that the distance between wild type and mutant codons approach to smaller values in mutational variants of four genes, i.e., human phenylalanine hydroxylase, human beta-globin, HIV-1 protease and HIV-1 reverse transcriptase. These results strongly suggest that deterministic rules must be involved in the genetic code origin.

A genetic code Boolean structure. II. The genetic information system as a Boolean information system.

A Boolean structure of the genetic code where Boolean deductions have biological and physicochemical meanings was discussed in a previous paper. Now, from these Boolean deductions we propose to define the value of amino acid information in order to consider the genetic information system as a communication system and to introduce the semantic content of information ignored by the conventional information theory. In this proposal, the value of amino acid information is proportional to the molecular weight of amino acids with a proportional constant of about 1.96 x 10(25) bits per kg. In addition to this, for the experimental estimations of the minimum energy dissipation in genetic logic operations, we present two postulates: (1) the energy Ei (i=1,2,...,20) of amino acids in the messages conveyed by proteins is proportional to the value of information, and (2) amino acids are distributed according to their energy Ei so the amino acid population in proteins follows a Boltzmann distribution. Specifically, in the genetic message carried by the DNA from the genomes of living organisms, we found that the minimum energy dissipation in genetic logic operations was close to kTLn(2) joules per bit.