Going through changes - the role of autophagy during reprogramming and differentiation.

Somatic cell reprogramming is a complex feature that allows differentiated cells to undergo fate changes into different cell types. This process, which is conserved between plants and animals, is often achieved via dedifferentiation into pluripotent stem cells, which have the ability to generate all other types of cells and tissues of a given organism. Cellular reprogramming is thus a complex process that requires extensive modification at the epigenetic and transcriptional level, unlocking cellular programs that allow cells to acquire pluripotency. In addition to alterations in the gene expression profile, cellular reprogramming requires rearrangement of the proteome, organelles and metabolism, but these changes are comparatively less studied. In this context, autophagy, a cellular catabolic process that participates in the recycling of intracellular constituents, has the capacity to affect different aspects of cellular reprogramming, including the removal of protein signatures that might hamper reprogramming, mitophagy associated with metabolic reprogramming, and the supply of energy and metabolic building blocks to cells that undergo fate changes. In this Review, we discuss advances in our understanding of the role of autophagy during cellular reprogramming by drawing comparisons between plant and animal studies, as well as highlighting aspects of the topic that warrant further research.

Vascular optimality dictates plant morphology away from Leonardo's rule.

Metabolic scaling theory (MST) provides an understanding of scaling in organismal morphology. Empirical data on the apparently universal pattern of tip-to-base conduit widening across vascular plants motivate a set of generalized MST (gMST) relationships allowing for variable rates of conduit coalescence and taper and a transition between transport and diffusive domains. Our model, with coalescence limited to the distalmost part of the conductive system, reconciles previous MST-based models and extends their applicability to the entire plant. We derive an inverse relationship between stem volume taper and conduit widening, which implies that plant morphology is dictated by vascular optimality and not the assumption of constant sapwood area across all branching levels, contradicting Leonardo's rule. Thus, energy efficiency controls conduit coalescence rate, lowering the carbon cost needed to sustain the vascular network. Our model shows that as a plant grows taller, it must increase conduit widening and coalescence, which may make it more vulnerable to drought. We calculated how our gMST model implies a lower carbon cost to sustain a similar network compared to previous MST-based models. We also show that gMST predicts the cross-sectional area of vessels and their frequency along the relative length better than previous MST models for a range of plant types. We encourage further research obtaining data that would allow testing other gMST predictions that remain unconfirmed empirically, such as conduit coalescence rate in stems. The premise of energy efficiency can potentially become instrumental to our understanding of plant carbon allocation.

Strategies for Enhancing Plant Immunity and Resilience Using Nanomaterials for Sustainable Agriculture.

Research on plant-nanomaterial interactions has greatly advanced over the past decade. One particularly fascinating discovery encompasses the immunomodulatory effects in plants. Due to the low doses needed and the comparatively low toxicity of many nanomaterials, nanoenabled immunomodulation is environmentally and economically promising for agriculture. It may reduce environmental costs associated with excessive use of chemical pesticides and fertilizers, which can lead to soil and water pollution. Furthermore, nanoenabled strategies can enhance plant resilience against various biotic and abiotic stresses, contributing to the sustainability of agricultural ecosystems and the reduction of crop losses due to environmental factors. While nanoparticle immunomodulatory effects are relatively well-known in animals, they are still to be understood in plants. Here, we provide our perspective on the general components of the plant's immune system, including the signaling pathways, networks, and molecules of relevance for plant nanomodulation. We discuss the recent scientific progress in nanoenabled immunomodulation and nanopriming and lay out key avenues to use plant immunomodulation for agriculture. Reactive oxygen species (ROS), the mitogen-activated protein kinase (MAPK) cascade, and the calcium-dependent protein kinase (CDPK or CPK) pathway are of particular interest due to their interconnected function and significance in the response to biotic and abiotic stress. Additionally, we underscore that understanding the plant hormone salicylic acid is vital for nanoenabled applications to induce systemic acquired resistance. It is suggested that a multidisciplinary approach, incorporating environmental impact assessments and focusing on scalability, can expedite the realization of enhanced crop yields through nanotechnology while fostering a healthier environment.

Application of Single-Cell Assay for Transposase-Accessible Chromatin with High Throughput Sequencing in Plant Science: Advances, Technical Challenges, and Prospects.

The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology.

Phytotoxicity of weathered petroleum hydrocarbons in soil to boreal plant species.

Canada has extensive petroleum hydrocarbon (PHC) contamination in northern areas and the boreal forest region from historical oil and gas activities. Since the 2013 standardization of boreal forest species for plant toxicity testing in Canada, there has been a need to build the primary literature of the toxicity of weathered PHCs to these species. A series of toxicity experiments were carried out using fine-grained (<0.005-0.425 mm) background (100 total mg/kg total PHCs) and weathered contaminated soil (11,900 mg/kg total PHCs) collected from a contaminated site in northern Ontario, Canada. The PHC mixture in the contaminated site soil was characterized through Canadian Council of Ministers of the Environment Fractions, as indicated by the number equivalent normal straight-chain hydrocarbons (nC). The soil was highly contaminated with Fraction 2 (>nC10 to nC16) at 4790 mg/kg and Fraction 3 (>nC16 to nC34) at 4960 mg/kg. Five plant species (Elymus trachycaulus, Achillea millefolium, Picea mariana, Salix bebbiana, and Alnus viridis) were grown from seed in 0%, 25%, 50%, 75%, and 100% relative contamination mixtures of the PHC-contaminated and background soil from the site over 2-6 weeks. All five species showed significant inhibition in shoot length, shoot weight, root length, and/or root weight (Kruskal-Wallis Tests: p < 0.05, df = 4.0). Measurements of 25% inhibitory concentrations (IC25) following PHC toxicity experiments revealed that S. bebbiana was most significantly impaired by the PHC-contaminated soil (410-990 mg/kg total PHCs), where it showed <35% germination. This study indicates that natural weathering of Fraction 2- and Fraction 3-concentrated soil did not eliminate phytotoxicity to boreal plant species. Furthermore, it builds on the limited existing literature for toxicity of PHCs on boreal plants and supports site remediation to existing Canadian provincial PHC guidelines.

Comparative Analysis on the Codon Usage Pattern of the Chloroplast Genomes in Malus Species.

Codon usage bias of coding sequences has been usually used for exploring the evolutionary factors that affect the variation of genes. We took 20 chloroplast genomes of Malus species into account to explore the codon usage patterns, including the composition, relationship between GC3s and effective number of codons, the parity rule two analyses, the relative synonymous codon usage, the codon adaptation index, the frequency of optimal codons, the codon bias index, etc., of their coding genes. The relationship between GC3 and the ENC values showed that when the separate genes are concerned, the distribution of their GC3 contents is relatively concentrated and the distribution of the ENC values are from 35 to 61 or so. The neutrality plot showed that the correlation coefficient between GC12 and GC3 is 0.095, revealing the mutation factor played a weak role in codon pattern formation. Correspondence analysis results revealed that the codon usage patterns in the chloroplast genomes of Malus species are similar. All these results showed that all Malus chloroplast genomes are AT rich ones, the third bases of the codons are affected by the natural selection pressure, the first two nucleotide base of the codon are affected by mutation pressure. Some genes, such as the rsp7, psbA and ycf2 are of lower codon usage divergences, while the rps12, rps16 and ndhD are of higher codon usage divergences. Codon usage bias exists in the Malus genomes could be used for exploring the evolutionary characteristics in chloroplast genomes and for further study on evolutionary phenomenon in other species.

Extracting knowledge networks from plant scientific literature: potato tuber flesh color as an exemplary trait.

BACKGROUND: Scientific literature carries a wealth of information crucial for research, but only a fraction of it is present as structured information in databases and therefore can be analyzed using traditional data analysis tools. Natural language processing (NLP) is often and successfully employed to support humans by distilling relevant information from large corpora of free text and structuring it in a way that lends itself to further computational analyses. For this pilot, we developed a pipeline that uses NLP on biological literature to produce knowledge networks. We focused on the flesh color of potato, a well-studied trait with known associations, and we investigated whether these knowledge networks can assist us in formulating new hypotheses on the underlying biological processes. RESULTS: We trained an NLP model based on a manually annotated corpus of 34 full-text potato articles, to recognize relevant biological entities and relationships between them in text (genes, proteins, metabolites and traits). This model detected the number of biological entities with a precision of 97.65% and a recall of 88.91% on the training set. We conducted a time series analysis on 4023 PubMed abstract of plant genetics-based articles which focus on 4 major Solanaceous crops (tomato, potato, eggplant and capsicum), to determine that the networks contained both previously known and contemporaneously unknown leads to subsequently discovered biological phenomena relating to flesh color. A novel time-based analysis of these networks indicates a connection between our trait and a candidate gene (zeaxanthin epoxidase) already two years prior to explicit statements of that connection in the literature. CONCLUSIONS: Our time-based analysis indicates that network-assisted hypothesis generation shows promise for knowledge discovery, data integration and hypothesis generation in scientific research.

Evaluation of the trnK-matK-trnK, ycf3, and accD-psal chloroplast regions to differentiate crop type and biogeographical origin of Cannabis sativa.

Cannabis sativa (marijuana and hemp) is one of the most controversial crops worldwide. In the USA, the state-specific legalization of marijuana and recently legalized hemp pose a problem for law enforcement. This study seeks to utilize chloroplast hSTRs, INDEL, and SNPs markers to develop genotyping methods to aid in the differentiation of legal hemp from illicit marijuana and also for tracking the flow of trafficked marijuana. Three polymorphic regions: trnK-matK-trnK, ycf3, and accD-psal, of the C. sativa chloroplast genome were evaluated in order to distinguish crop type and biogeographic origin. A total of nine polymorphic sites were genotyped from five distinct populations (hemp from the USA and Canada, marijuana from Chile and USA-Mexico, and medical marijuana from Chile) with a custom fragment and SNaPshotTM assay. The study also combined genotype results from the same sample set using 21 additional polymorphic markers from previous studies. The effectiveness of these multi-locus assays to distinguish sample groups was assessed using haplotype analysis, phylogenetic analysis, pairwise comparisons, and principal component analysis. Results indicated a clear separation of Canadian hemp using only the nine polymorphic sites developed in this study. The additional 21 markers were able to separate US hemp from both marijuana groups to a significant level (p < 0.05) when assessing average Fixation Indices (FST). This study demonstrated the applicability of these organelle markers for the determination of crop type and biogeographic origin of C. sativa. However, a more extensive database is needed to evaluate the true discriminatory power of these markers.

Spatial patterns of tree yield explained by endogenous forces through a correspondence between the Ising model and ecology.

Spatial patterning of periodic dynamics is a dramatic and ubiquitous ecological phenomenon arising in systems ranging from diseases to plants to mammals. The degree to which spatial correlations in cyclic dynamics are the result of endogenous factors related to local dynamics vs. exogenous forcing has been one of the central questions in ecology for nearly a century. With the goal of obtaining a robust explanation for correlations over space and time in dynamics that would apply to many systems, we base our analysis on the Ising model of statistical physics, which provides a fundamental mechanism of spatial patterning. We show, using 5 y of data on over 6,500 trees in a pistachio orchard, that annual nut production, in different years, exhibits both large-scale synchrony and self-similar, power-law decaying correlations consistent with the Ising model near criticality. Our approach demonstrates the possibility that short-range interactions can lead to long-range correlations over space and time of cyclic dynamics even in the presence of large environmental variability. We propose that root grafting could be the common mechanism leading to positive short-range interactions that explains the ubiquity of masting, correlated seed production over space through time, by trees.

The Landscape of RNA-Protein Interactions in Plants: Approaches and Current Status.

RNAs transmit information from DNA to encode proteins that perform all cellular processes and regulate gene expression in multiple ways. From the time of synthesis to degradation, RNA molecules are associated with proteins called RNA-binding proteins (RBPs). The RBPs play diverse roles in many aspects of gene expression including pre-mRNA processing and post-transcriptional and translational regulation. In the last decade, the application of modern techniques to identify RNA-protein interactions with individual proteins, RNAs, and the whole transcriptome has led to the discovery of a hidden landscape of these interactions in plants. Global approaches such as RNA interactome capture (RIC) to identify proteins that bind protein-coding transcripts have led to the identification of close to 2000 putative RBPs in plants. Interestingly, many of these were found to be metabolic enzymes with no known canonical RNA-binding domains. Here, we review the methods used to analyze RNA-protein interactions in plants thus far and highlight the understanding of plant RNA-protein interactions these techniques have provided us. We also review some recent protein-centric, RNA-centric, and global approaches developed with non-plant systems and discuss their potential application to plants. We also provide an overview of results from classical studies of RNA-protein interaction in plants and discuss the significance of the increasingly evident ubiquity of RNA-protein interactions for the study of gene regulation and RNA biology in plants.

G-Quadruplex in Gene Encoding Large Subunit of Plant RNA Polymerase II: A Billion-Year-Old Story.

G-quadruplexes have long been perceived as rare and physiologically unimportant nucleic acid structures. However, several studies have revealed their importance in molecular processes, suggesting their possible role in replication and gene expression regulation. Pathways involving G-quadruplexes are intensively studied, especially in the context of human diseases, while their involvement in gene expression regulation in plants remains largely unexplored. Here, we conducted a bioinformatic study and performed a complex circular dichroism measurement to identify a stable G-quadruplex in the gene RPB1, coding for the RNA polymerase II large subunit. We found that this G-quadruplex-forming locus is highly evolutionarily conserved amongst plants sensu lato (Archaeplastida) that share a common ancestor more than one billion years old. Finally, we discussed a new hypothesis regarding G-quadruplexes interacting with UV light in plants to potentially form an additional layer of the regulatory network.

The social-ecological system driving effective invasive plant management: two case studies of non-native Phragmites.

Globally, the management of invasive plants is motivated by a desire to improve ecosystem services (e.g., recreation, flood mitigation, soil fertility for agriculture, aesthetics) and critical habitat for imperiled species. To reduce invader populations and impacts, it is important to document the social and ecological basis (i.e., the social-ecological system) for the management that has been employed and areas where a greater level of coordination among stakeholder groups (managers, scientists, legislators, resource users) could improve efforts. We present a conceptual model that builds on current thinking for how best to connect these four stakeholder groups-to foster stronger citizen lobbying for impacted resources, science-based governance, legislator-driven noxious weed laws and funding for management and science, knowledge co-production by scientists and managers, and co-management by managers and resource users. In light of our model, we present two case studies based in Nebraska and Utah, U.S.A. involving a common North American wetland invader, Phragmites australis (non-native common reed). In Nebraska, potential lawsuits stemming from water conveyance was strong motivation for funding management. In Utah, duck hunters and other resource users initially instigated management. Progress toward the successful management of Phragmites has been the result of manager-scientist partnerships addressing a knowing-doing gap among practitioners, the complexities of management mosaics, as well as overcoming economic and logistical constraints. Our model demonstrates how legislative initiatives can fund new research and bolster on-going management, while organically building strong partnerships among scientists, managers, and resource users that are key for successfully managing invasive species.

Estimation of the leaf chlorophyll content using multiangular spectral reflectance factor.

Chlorophyll is one of the primary pigments of plant leaves, and changes in its content can be used to characterize the physiological status of plants. Spectral indices have been devised and validated for estimating leaf chlorophyll content (LCC). However, most of the existing spectral indices do not consider the influence of angular reflection on the accuracy of the LCC estimation. In this study, the spectral reflectance factors of leaves from three plant species were measured from several observations in the principal plane. The relationship between the existing spectral indices and the LCC from different directions suggests that the directional reflection of a leaf surface impacts the accuracy of its LCC estimation. Subsequently, the ratio of reflectance differences, that is, the modified Datt index, was tested to reduce the directional reflection effect when predicting LCC. Our results indicated that the modified Datt index not only estimated LCC with high accuracy for all observation directions and plant species but also consistently predicted the LCC of each species in individual observation directions. Our method opens the possibility for optical detection of LCC using multiangular spectral reflection, which is convenient for plant science studies focused on the variation in LCC.

Characterization of new chloroplast markers to determine biogeographical origin and crop type of Cannabis sativa.

Marijuana (Cannabis sativa) is the most commonly used illicit drug in the USA. Despite its schedule I classification by the federal government, 33 states and the District of Columbia have legalized its use for medicinal or recreational purposes. This state-specific legalization has created a new problem for law enforcement: preventing and tracking the diversion of legally obtained Cannabis to states where it remains illegal. In addition, trafficking of the drug at the border with Mexico remains an issue for law enforcement agencies. C. sativa crops can be classified as marijuana (a drug containing the psychoactive chemical delta-9-tetrahydrocannabinol) or hemp (the non-drug form of the plant). Differentiation between crop types is important for forensic purposes. In addition, investigation of trafficking routes into and within the USA requires genetic association of samples from different seizures, and determining where the crop originated could provide important leads. This project seeks to exploit sequence variations in C. sativa chloroplast DNA (cpDNA) to allow genetic determination of biogeographic origin, discrimination between marijuana and hemp, and association between cases for C. sativa samples. Due to the limited discriminatory ability of common barcoding markers, the authors sought to discover more informative polymorphic regions. By comparing published whole genome cpDNA sequences, 58 polymorphisms and seven hotspot regions were identified. Hemp samples from the USA and Canada, marijuana samples from Mexico and Chile, and medical marijuana samples from Chile were evaluated using two cpDNA hotspot regions, rpl32-trnL and trnS-trnG. Principal component analysis supported some differences between the groups based on their crop type and biogeographic origin.

Psychedelic fungus (Psilocybe sp.) authentication in a case of illegal drug traffic: sporological, molecular analysis and identification of the psychoactive substance.

In nature, there are >200 species of fungi with hallucinogenic properties. These fungi are classified as Psilocybe, Gymnopilus, and Panaeolus which contain active principles with hallucinogenic properties such as ibotenic acid, psilocybin, psilocin, or baeocystin. In Chile, fungi seizures are mainly of mature specimens or spores. However, clandestine laboratories have been found that process fungus samples at the mycelium stage. In this transient stage of growth (mycelium), traditional taxonomic identification is not feasible, making it necessary to develop a new method of study. Currently, DNA analysis is the only reliable method that can be used as an identification tool for the purposes of supporting evidence, due to the high variability of DNA between species. One way to identify the species of a distinctive DNA fragment is to study PCR products analyzed by real time PCR and sequencing. One of the most popular sequencing methods of forensic interest at the generic and intra-generic levels in plants is internal transcribed spacer (ITS). With real time PCR it is possible to distinguish PCR products by differential analysis of their melting temperature (Tm) curves. This paper describes morphological, chemical, and genetic analysis of mycelia of psychedelic fungi collected from a clandestine laboratory. The fungus species were identified using scanning electron microscopy (SEM), mass spectrometry, HRM analysis, and ITS sequencing. The sporological studies showed a generally smooth surface and oval shape, with maximum length 10.1 µm and width 6.4 µm. The alkaloid Psilocyn was identified by mass spectrometry, while HRM analysis and ITS sequencing identified the species as Psilocybe cubensis. A genetic match was confirmed between the HRM curves obtained from the mycelia (evidence) and biological tissue extracted from the fruiting bodies. Mycelia recovered from the evidence and fruiting bodies (control) were genetically indistinguishable.

Massively parallel sequencing of 12 autosomal STRs in Cannabis sativa.

Massively parallel sequencing (MPS) is an emerging technology in the field of forensic genetics that provides distinct advantages compared to capillary electrophoresis. This study offers a proof of concept that MPS technologies can be applied to genotype autosomal STRs in Cannabis sativa. A custom panel for MPS was designed to interrogate 12 cannabis-specific STR loci by sequence rather than size. A simple workflow was implemented to integrate the custom PCR multiplex into a workflow compatible with the Ion Plus Fragment Library Kit, Ion™ Chef, and Ion™ S5 System. For data sorting and sequence analysis, a custom configuration file was designed for STRait Razor v3 to parse and extract STR sequence data. This study represents a preliminary investigation of sequence variation for 12 autosomal STR loci in 16 cannabis samples. Full concordance was observed between the MPS and CE data. Results revealed intra-repeat variation in eight loci where the nominal or size-based allele was identical, but variances were discovered in the sequence of the flanking region. Although only a small number of cannabis samples were evaluated, this study demonstrates that more informative STR data can be obtained via MPS.

Nuclear, chloroplast, and mitochondrial data of a US cannabis DNA database.

As Cannabis sativa (marijuana) is a controlled substance in many parts of the world, the ability to track biogeographical origin of cannabis could provide law enforcement with investigative leads regarding its trade and distribution. Population substructure and inbreeding may cause cannabis plants to become more genetically related. This genetic relatedness can be helpful for intelligence purposes. Analysis of autosomal, chloroplast, and mitochondrial DNA allows for not only prediction of biogeographical origin of a plant but also discrimination between individual plants. A previously validated, 13-autosomal STR multiplex was used to genotype 510 samples. Samples were analyzed from four different sites: 21 seizures at the US-Mexico border, Northeastern Brazil, hemp seeds purchased in the US, and the Araucania area of Chile. In addition, a previously reported multi-loci system was modified and optimized to genotype five chloroplast and two mitochondrial markers. For this purpose, two methods were designed: a homopolymeric STR pentaplex and a SNP triplex with one chloroplast (Cscp001) marker shared by both methods for quality control. For successful mitochondrial and chloroplast typing, a novel real-time PCR quantitation method was developed and validated to accurately estimate the quantity of the chloroplast DNA (cpDNA) using a synthetic DNA standard. Moreover, a sequenced allelic ladder was also designed for accurate genotyping of the homopolymeric STR pentaplex. For autosomal typing, 356 unique profiles were generated from the 425 samples that yielded full STR profiles and 25 identical genotypes within seizures were observed. Phylogenetic analysis and case-to-case pairwise comparisons of 21 seizures at the US-Mexico border, using the Fixation Index (F ST ) as genetic distance, revealed the genetic association of nine seizures that formed a reference population. For mitochondrial and chloroplast typing, subsampling was performed, and 134 samples were genotyped. Complete haplotypes (STRs and SNPs) were observed for 127 samples. As expected, extensive haplotype sharing was observed; five distinguishable haplotypes were detected. In the reference population, the same haplotype was observed 39 times and two unique haplotypes were also detected. Haplotype sharing was observed between the US border seizures, Brazil, and Chile, while the hemp samples generated a distinct haplotype. Phylogenetic analysis of the four populations was performed, and results revealed that both autosomal and lineage markers could discern population substructure.