Near telomere-to-telomere genome assemblies of two Chlorella species unveil the composition and evolution of centromeres in green algae.

BACKGROUND: Centromeres play a crucial and conserved role in cell division, although their composition and evolutionary history in green algae, the evolutionary ancestors of land plants, remains largely unknown. RESULTS: We constructed near telomere-to-telomere (T2T) assemblies for two Trebouxiophyceae species, Chlorella sorokiniana NS4-2 and Chlorella pyrenoidosa DBH, with chromosome numbers of 12 and 13, and genome sizes of 58.11 Mb and 53.41 Mb, respectively. We identified and validated their centromere sequences using CENH3 ChIP-seq and found that, similar to humans and higher plants, the centromeric CENH3 signals of green algae display a pattern of hypomethylation. Interestingly, the centromeres of both species largely comprised transposable elements, although they differed significantly in their composition. Species within the Chlorella genus display a more diverse centromere composition, with major constituents including members of the LTR/Copia, LINE/L1, and LINE/RTEX families. This is in contrast to green algae including Chlamydomonas reinhardtii, Coccomyxa subellipsoidea, and Chromochloris zofingiensis, in which centromere composition instead has a pronounced single-element composition. Moreover, we observed significant differences in the composition and structure of centromeres among chromosomes with strong collinearity within the Chlorella genus, suggesting that centromeric sequence evolves more rapidly than sequence in non-centromeric regions. CONCLUSIONS: This study not only provides high-quality genome data for comparative genomics of green algae but gives insight into the composition and evolutionary history of centromeres in early plants, laying an important foundation for further research on their evolution.

Fossil-calibrated molecular clock data enable reconstruction of steps leading to differentiated multicellularity and anisogamy in the Volvocine algae.

BACKGROUND: Throughout its nearly four-billion-year history, life has undergone evolutionary transitions in which simpler subunits have become integrated to form a more complex whole. Many of these transitions opened the door to innovations that resulted in increased biodiversity and/or organismal efficiency. The evolution of multicellularity from unicellular forms represents one such transition, one that paved the way for cellular differentiation, including differentiation of male and female gametes. A useful model for studying the evolution of multicellularity and cellular differentiation is the volvocine algae, a clade of freshwater green algae whose members range from unicellular to colonial, from undifferentiated to completely differentiated, and whose gamete types can be isogamous, anisogamous, or oogamous. To better understand how multicellularity, differentiation, and gametes evolved in this group, we used comparative genomics and fossil data to establish a geologically calibrated roadmap of when these innovations occurred. RESULTS: Our ancestral-state reconstructions, show that multicellularity arose independently twice in the volvocine algae. Our chronograms indicate multicellularity evolved during the Carboniferous-Triassic periods in Goniaceae + Volvocaceae, and possibly as early as the Cretaceous in Tetrabaenaceae. Using divergence time estimates we inferred when, and in what order, specific developmental changes occurred that led to differentiated multicellularity and oogamy. We find that in the volvocine algae the temporal sequence of developmental changes leading to differentiated multicellularity is much as proposed by David Kirk, and that multicellularity is correlated with the acquisition of anisogamy and oogamy. Lastly, morphological, molecular, and divergence time data suggest the possibility of cryptic species in Tetrabaenaceae. CONCLUSIONS: Large molecular datasets and robust phylogenetic methods are bringing the evolutionary history of the volvocine algae more sharply into focus. Mounting evidence suggests that extant species in this group are the result of two independent origins of multicellularity and multiple independent origins of cell differentiation. Also, the origin of the Tetrabaenaceae-Goniaceae-Volvocaceae clade may be much older than previously thought. Finally, the possibility of cryptic species in the Tetrabaenaceae provides an exciting opportunity to study the recent divergence of lineages adapted to live in very different thermal environments.

Physiotyping of Plants and Modeling the Soil Plant Atmospheric Continuum (SPAC).

This chapter presents a holistic and quantitative approach to the carbon cycle in plant systems biology. It includes (rapid) phenotyping and monitoring of physiological key interactions of plants with its respective soil and atmospheric environment (soil plant atmospheric continuum-SPAC). The approach aims at qualifying and quantifying key components of this microhabitat as influenced by a single plant or a local group of plants in order to contribute to a flux-based modelling approach. The toolset consists of plant biometry, gas exchange, metabolomics, ionomics, root exudate characterization as well as soil biological and physical-chemical characterization. The results are presented as a basic interaction and input-output model aka conceptual system model employing H. T. Odum-style plots based on empirical data.

Genetic Diversity Assessment in Plants from Reduced Representation Sequencing Data.

Genetic diversity refers to the variety of genetic traits within a population or a species. It is an essential aspect of both plant ecology and plant breeding because it contributes to the adaptability, survival, and resilience of populations in changing environments. This chapter outlines a pipeline for estimating genetic diversity statistics from reduced representation or whole genome sequencing data. The pipeline involves obtaining DNA sequence reads, mapping the corresponding reads to a reference genome, calling variants from the alignments, and generating an unbiased estimation of nucleotide diversity and divergence between populations. The pipeline is suitable for single-end Illumina reads and can be adjusted for paired-end reads. The resulting pipeline provides a comprehensive approach for aligning and analyzing sequencing data to estimate genetic diversity.

Identification of Novel Induced Mutations in Seed and Vegetatively Propagated Plants from Reduced Representation or Whole Genome Sequencing Data.

Treatment of plants with chemical mutagens results primarily in the production of novel single nucleotide variants. Mutagenesis is a mostly random process and as such plants derived from mutagenesis of different seeds or in vitro material are expected to accumulate different mutations. An important step in the creation of a mutant population for forward or reverse genetics is the choice of treatment conditions (e.g., dosage) such that sufficient mutations accumulate while not adversely affecting propagation of the plant. DNA sequencing provides a quick method to evaluate the effect of different treatment conditions and their effect on the density and spectrum of accumulated mutations. Whole genome sequencing or reduced representation sequencing is carried out followed by mapping to a reference genome and production of a Variant Call Format (VCF) file. We provide here a method for generating a multi-sample VCF from mutagenized plants and describe a new tool to streamline the process of recovering unique induced mutations and determining their possible effect on gene function.

Two-Dimensional Gel Electrophoresis for Protein Separation of Plant Samples.

This chapter provides a description of the procedure for two-dimensional electrophoresis that can be performed for any given gel size and isoelectric focusing range. This will enable the operator to recognize critical steps and gain sufficient information to generate 2D images suitable for computer-assisted analysis of 2D-gel, as well as mass spectrometry analysis for protein identification and characterization.

One-Dimensional Acrylamide Gel Electrophoresis for Analysis of Plant Samples.

Polyacrylamide gel electrophoresis (PAGE) is a widely used technique for separating proteins from complex plant samples. Prior to the analysis, proteins must be extracted from plant tissues, which are rather complex than other types of biological material. Different protocols have been applied depending on the protein source, such as seeds, pollen, leaves, roots, and flowers. Total protein amounts must also be determined before conducting gel electrophoresis. The most common methodologies include PAGE under native or denaturing conditions. Both procedures are used consequently for protein identification and characterization via mass spectrometry. Additionally, various staining procedures are available to visualize protein bands in the gel, facilitating the software-based digital evaluation of the gel through image acquisition.

Sample Preparation and Phosphopeptide Enrichment for Plant Phosphoproteomics via Label-Free Mass Spectrometry.

Phosphopeptide enrichment is the main bottleneck of every phosphorylation study. Therefore, in this chapter, a general workflow tries to overbridge the hurdles of plant sample handling from sample collection to protein extraction, protein solubilization, enzymatic digestion, and enrichment step prior to mass spectrometry. The workflow provides information to perform global proteomics as well as phosphoproteomics enabling the researcher to use the protocol in both fields.

Carotenoid Extraction from Plant Tissues.

Carotenoids are the natural pigments available in nature and exhibit different colors such as yellow, red, and orange. These are a class of phytonutrients that have anti-cancer, anti-inflammatory, anti-oxidant, immune-modulatory, and anti-aging properties. These were used in food, pharmaceutical, nutraceutical, and cosmetic industries. They are divided into two classes: carotenes and xanthophylls. The carotenes are non-oxygenated derivatives and xanthophylls are oxygenated derivatives. The major source of carotenoids are vegetables, fruits, and tissues. Carotenoids also perform the roles of photoprotection and photosynthesis. In addition to the roles mentioned above, they are also involved and act as precursor molecules for the biosynthesis of phytohormones such as strigolactone and abscisic acid. This chapter briefly introduces carotenoids and their extraction method from plant tissue. Proposed protocol describes the extraction of carotenoid using solvents chloroform and dichloromethane. Reverse-phase HPLC can be performed with C30 columns using gradient elution. The column C30 is preferred to the C18 column because the C30 column has salient features, which include selective nature in the separation of structural isomers and hydrophobic, long-chain compounds, and shows the best compatibility with highly aqueous mobile phases. A complete pipeline for the extraction of carotenoids from plant tissue is given in the present protocol.

Application of Integrated Computational Approaches in Prediction of Plant Virus Encoded miRNAs and Their Targeted Plant Genes.

This chapter presents a comprehensive approach to predict novel miRNAs encoded by plant viruses and identify their target plant genes, through integration of various ab initio computational approaches. The predictive process begins with the analysis of plant viral sequences using the VMir Analyzer software. VMir Viewer software is then used to extract primary hairpins from these sequences. To distinguish real miRNA precursors from pseudo miRNA precursors, MiPred web-based software is employed. Verified real pre-miRNA sequences with a minimum free energy of < -20 Kcal/mol, are further analyzed using the RNAshapes software. Validation of predictions involves comparing them with available Expressed Sequence Tags (ESTs) from the relevant plant using BlastN. Short sequences with lengths ranging from 19 to 25 nucleotides and exhibiting <5 mismatches are prioritized for miRNA prediction. The precise locations of these short sequences within pre-miRNA structures generated using RNAshapes are meticulously identified, with a focus on those situated on the 5' and 3' arms of the structures, indicating potential miRNAs. Sequences within the arms of pre-miRNA structures are used to predict target sites within the ESTs of the specific plant, facilitated by psRNA Target software, revealing genes with potential regulatory roles in the plant. To confirm the outcome of target prediction, results are individually submitted to the RNAhybrid web-based software. For practical demonstration, this approach is applied to analyze African cassava mosaic virus (ACMV) and East African cassava mosaic virus-Uganda (EACMV-UG) viruses, as well as the ESTs of Jatropha and cassava.

Sample Preparation from Plant Tissue for Gas Chromatography-Mass Spectrometry (GC-MS)we.

Metabolites are intermediate products formed during metabolism. Metabolites play different roles, including providing energy, supporting structure, transmitting signals, catalyzing reactions, enhancing defense, and interacting with other species. Plant metabolomics research aims to detect precisely all metabolites found within tissues of plants through GC-MS. This chapter primarily focuses on extracting metabolites using chemicals such as methanol, chloroform, ribitol, MSTFA, and TMCS. The metabolic analysis method is frequently used according to the specific kind of sample or matrix being investigated and the analysis objective. Chromatography (LC, GC, and CE) with mass spectrometry and NMR spectroscopy is used in modern metabolomics to analyze metabolites from plant samples. The most frequently used method for metabolites analysis is the GC-MS. It is a powerful technique that combines gas chromatography's separation capabilities with mass spectrometry, offering detailed information, including structural identification of each metabolite. This chapter contains an easy-to-follow guide to extract plant-based metabolites. The current protocol provides all the information needed for extracting metabolites from a plant, precautions, and troubleshooting.

pyPGCF: A Python Software for Phylogenomic Analysis, Species Demarcation, Identification of Core, and Fingerprint Proteins of Bacterial Genomes That Are Important for Plants.

This computational protocol describes how to use pyPGCF, a python software package that runs in the linux environment, in order to analyze bacterial genomes and perform: (i) phylogenomic analysis, (ii) species demarcation, (iii) identification of the core proteins of a bacterial genus and its individual species, (iv) identification of species-specific fingerprint proteins that are found in all strains of a species and, at the same time, are absent from all other species of the genus, (v) functional annotation of the core and fingerprint proteins with eggNOG, and (vi) identification of secondary metabolite biosynthetic gene clusters (smBGCs) with antiSMASH. This software has already been implemented to analyze bacterial genera and species that are important for plants (e.g., Pseudomonas, Bacillus, Streptomyces). In addition, we provide a test dataset and example commands showing how to analyze 165 genomes from 55 species of the genus Bacillus. The main advantages of pyPGCF are that: (i) it uses adjustable orthology cut-offs, (ii) it identifies species-specific fingerprints, and (iii) its computational cost scales linearly with the number of genomes being analyzed. Therefore, pyPGCF is able to deal with a very large number of bacterial genomes, in reasonable timescales, using widely available levels of computing power.

Gene Co-expression Network Analysis to Mine Genes Involved in Plant Secondary Metabolite Biosynthesis and Regulation.

Plants produce diverse specialized metabolites (SMs) that do not participate in plant growth and development but help them adapt to various environmental conditions. In addition to aiding in plant adaptation, different SMs serve as active ingredients for pharmaceutical and cosmetics products. However, despite their significant role in plant adaptation and industrial importance, the genes involved in the biosynthesis and regulation of many SMs remain largely unknown. This hinders deciphering the specific role of SMs in plant adaptation and limits their industrial utilization. Since many SMs pathway genes are expected to act in tight association with each other within a coexpression network, the network biology approach, such as weighted gene coexpression network analysis, could be used to identify the unknown genes. This chapter describes a workflow for constructing a gene coexpression network to identify genes that could be associated with the biosynthesis and regulation of SMs.

Studying Plant Specialized Metabolites Using Computational Metabolomics Strategies.

Plant specialized metabolites have diversified vastly over the course of plant evolution, and they are considered key players in complex interactions between plants and their environment. The chemical diversity of these metabolites has been widely explored and utilized in agriculture and crop enhancement, the food industry, and drug development, among other areas. However, the immensity of the plant metabolome can make its exploration challenging. Here we describe a protocol for exploring plant specialized metabolites that combines high-resolution mass spectrometry and computational metabolomics strategies, including molecular networking, identification of structural motifs, as well as prediction of chemical structures and metabolite classes.

Using Magnetic Fields to Enhance the Seed Germination, Growth, and Yield of Plants.

Geomagnetic field (GMF) protects living organisms on the Earth from the radiation coming from space along with other environmental factors during evolution, and it has affected the growth and development of plants. Many researchers have always been interested in investigating these effects in different aspects. In this chapter, we focus on the methods of using different types of magnetic fields (MFs) to investigate the dimensions of their biological effects on plants. The aim is to increase seed germination, growth characters, and yield of plants using the following methods: (1) Using MFs lower than GMF to study effects of GMF on the growth and yield of plants. (2) Using reversed magnetic fields (RMFs) lower than GMF to study its effects on the growth and development of plants during evolution. (3) Using static magnetic fields (SMFs) higher than GMF and reversed SMFs to study effects of the south (S) and north (N) magnetic pole on plants. (4) Using electromagnetic fields (EMFs) to increase and accelerate seed germination, growth, and yield of plants, and establish the status of plants against other environmental stresses. (5) Using magnetized water (MW) to improve plant seed germination, growth, and yield. (6) Using high gradient magnetic field (HGMF) to study magneto-tropism in plants. In this chapter, we recommend application of various types of MFs to study their biological effects on plants to improve crop production.

Vegetation dieback in the Mississippi River Delta triggered by acute drought and chronic relative sea-level rise.

Vegetation dieback and recovery may be dependent on the interplay between infrequent acute disturbances and underlying chronic stresses. Coastal wetlands are vulnerable to the chronic stress of sea-level rise, which may affect their susceptibility to acute disturbance events. Here, we show that a large-scale vegetation dieback in the Mississippi River Delta was precipitated by salt-water incursion during an extreme drought in the summer of 2012 and was most severe in areas exposed to greater flooding. Using 16 years of data (2007-2022) from a coastwide network of monitoring stations, we show that the impacts of the dieback lasted five years and that recovery was only partial in areas exposed to greater inundation. Dieback marshes experienced an increase in percent time flooded from 43% in 2007 to 75% in 2022 and a decline in vegetation cover and species richness over the same period. Thus, while drought-induced high salinities and soil saturation triggered a significant dieback event, the chronic increase in inundation is causing a longer-term decline in cover, more widespread losses, and reduced capacity to recover from acute stressors. Overall, our findings point to the importance of mitigating the underlying stresses to foster resilience to both acute and persistent causes of vegetation loss.

Genome composition and GC content influence loci distribution in reduced representation genomic studies.

BACKGROUND: Genomic architecture is a key evolutionary trait for living organisms. Due to multiple complex adaptive and neutral forces which impose evolutionary pressures on genomes, there is a huge variability of genomic features. However, their variability and the extent to which genomic content determines the distribution of recovered loci in reduced representation sequencing studies is largely unexplored. RESULTS: Here, by using 80 genome assemblies, we observed that whereas plants primarily increase their genome size by expanding their intergenic regions, animals expand both intergenic and intronic regions, although the expansion patterns differ between deuterostomes and protostomes. Loci mapping in introns, exons, and intergenic categories obtained by in silico digestion using 2b-enzymes are positively correlated with the percentage of these regions in the corresponding genomes, suggesting that loci distribution mostly mirrors genomic architecture of the selected taxon. However, exonic regions showed a significant enrichment of loci in all groups regardless of the used enzyme. Moreover, when using selective adaptors to obtain a secondarily reduced loci dataset, the percentage and distribution of retained loci also varied. Adaptors with G/C terminals recovered a lower percentage of selected loci, with a further enrichment of exonic regions, while adaptors with A/T terminals retained a higher percentage of loci and slightly selected more intronic regions than expected. CONCLUSIONS: Our results highlight how genome composition, genome GC content, RAD enzyme choice and use of base-selective adaptors influence reduced genome representation techniques. This is important to acknowledge in population and conservation genomic studies, as it determines the abundance and distribution of loci.

Variable resource allocation pattern, biased sex-ratio, and extent of sexual dimorphism in subdioecious Hippophae rhamnoides.

Evolutionary maintenance of dioecy is a complex phenomenon and varies by species and underlying pathways. Also, different sexes may exhibit variable resource allocation (RA) patterns among the vegetative and reproductive functions. Such differences are reflected in the extent of sexual dimorphism. Though rarely pursued, investigation on plant species harbouring intermediate sexual phenotypes may reveal useful information on the strategy pertaining to sex-ratios and evolutionary pathways. We studied H. rhamnoides ssp. turkestanica, a subdioecious species with polygamomonoecious (PGM) plants, in western Himalaya. The species naturally inhabits a wide range of habitats ranging from river deltas to hill slopes. These attributes of the species are conducive to test the influence of abiotic factors on sexual dimorphism, and RA strategy among different sexes. The study demonstrates sexual dimorphism in vegetative and reproductive traits. The sexual dimorphism index, aligned the traits like height, number of branches, flower production, and dry-weight of flowers with males while others including fresh-weight of leaves, number of thorns, fruit production were significantly associated with females. The difference in RA pattern is more pronounced in reproductive traits of the male and female plants, while in the PGM plants the traits overlap. In general, habitat conditions did not influence either the extent of sexual dimorphism or RA pattern. However, it seems to influence secondary sex-ratio as females show their significant association with soil moisture. Our findings on sexual dimorphism and RA pattern supports attributes of wind-pollination in the species. The observed extent of sexual dimorphism in the species reiterates limited genomic differences among the sexes and the ongoing evolution of dioecy via monoecy in the species. The dynamics of RA in the species appears to be independent of resource availability in the habitats as the species grows in a resource-limited and extreme environment.

Girdling behavior of the longhorn beetle modulates the host plant to enhance larval performance.

BACKGROUND: Preingestive behavioral modulations of herbivorous insects on the host plant are abundant over insect taxa. Those behaviors are suspected to have functions such as deactivation of host plant defenses, nutrient accumulation, or modulating plant-mediated herbivore interactions. To understand the functional consequence of behavioral modulation of insect herbivore, we studied the girdling behavior of Phytoecia rufiventris Gautier (Lamiinae; Cerambycidae) on its host plant Erigeron annuus L. (Asteraceae) that is performed before endophytic oviposition in the stem. RESULTS: The girdling behavior significantly increased the larval performance in both field monitoring and lab experiment. The upper part of the girdled stem exhibited lack of jasmonic acid induction upon larval attack, lowered protease inhibitor activity, and accumulated sugars and amino acids in compared to non-girdled stem. The girdling behavior had no effect on the larval performance of a non-girdling longhorn beetle Agapanthia amurensis, which also feeds on the stem of E. annuus during larval phase. However, the girdling behavior decreased the preference of A. amurensis females for oviposition, which enabled P. rufiventris larvae to avoid competition with A. amurensis larvae. CONCLUSIONS: In conclusion, the girdling behavior modulates plant physiology and morphology to provide a modulated food source for larva and hide it from the competitor. Our study implies that the insect behavior modulations can have multiple functions, providing insights into adaptation of insect behavior in context of plant-herbivore interaction.

Extraterrestrial agriculture: plant cultivation in space.

[Formula: see text] Researchers are using various techniques and technologies to study how plants grow in extraterrestrial conditions with the hopes of sustaining longer missions for exploring deep space as well as being able to one day cultivate crops on other planets.