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.

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.

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.

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.

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.

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.

Botany and geogenomics: Constraining geological hypotheses in the neotropics with large-scale genetic data derived from plants.

Decades of empirical research have revealed how the geological history of our planet shaped plant evolution by establishing well-known patterns (e.g., how mountain uplift resulted in high rates of diversification and replicate radiations in montane plant taxa). This follows a traditional approach where botanical data are interpreted in light of geological events. In this synthesis, I instead describe how by integrating natural history, phylogenetics, and population genetics, botanical research can be applied alongside geology and paleontology to inform our understanding of past geological and climatic processes. This conceptual shift aligns with the goals of the emerging field of geogenomics. In the neotropics, plant geogenomics is a powerful tool for the reciprocal exploration of two long standing questions in biology and geology: how the dynamic landscape of the region came to be and how it shaped the evolution of the richest flora. Current challenges that are specific to analytical approaches for plant geogenomics are discussed. I describe the scale at which various geological questions can be addressed from biological data and what makes some groups of plants excellent model systems for geogenomics research. Although plant geogenomics is discussed with reference to the neotropics, the recommendations given here for approaches to plant geogenomics can and should be expanded to exploring long-standing questions on how the earth evolved with the use of plant DNA.

KASP: a high-throughput genotyping system and its applications in major crop plants for biotic and abiotic stress tolerance.

Advances in plant molecular breeding have resulted in the development of new varieties with superior traits, thus improving the crop germplasm. Breeders can screen a large number of accessions without rigorous and time-consuming phenotyping by marker-assisted selection (MAS). Molecular markers are one of the most imperative tools in plant breeding programmes for MAS to develop new cultivars possessing multiple superior traits. Single nucleotide polymorphisms (SNPs) are ideal for MAS due to their low cost, low genotyping error rates, and reproducibility. Kompetitive Allele Specific PCR (KASP) is a globally recognized technology for SNP genotyping. KASP is an allele-specific oligo extension-based PCR assay that uses fluorescence resonance energy transfer (FRET) to detect genetic variations such as SNPs and insertions/deletions (InDels) at a specific locus. Additionally, KASP allows greater flexibility in assay design, which leads to a higher success rate and the capability to genotype a large population. Its versatility and ease of use make it a valuable tool in various fields, including genetics, agriculture, and medical research. KASP has been extensively used in various plant-breeding applications, such as the identification of germplasm resources, quality control (QC) analysis, allele mining, linkage mapping, quantitative trait locus (QTL) mapping, genetic map construction, trait-specific marker development, and MAS. This review provides an overview of the KASP assay and emphasizes its validation in crop improvement related to various biotic and abiotic stress tolerance and quality traits.

Heat stress impairs centromere structure and segregation of meiotic chromosomes in Arabidopsis.

Heat stress is a major threat to global crop production, and understanding its impact on plant fertility is crucial for developing climate-resilient crops. Despite the known negative effects of heat stress on plant reproduction, the underlying molecular mechanisms remain poorly understood. Here, we investigated the impact of elevated temperature on centromere structure and chromosome segregation during meiosis in Arabidopsis thaliana. Consistent with previous studies, heat stress leads to a decline in fertility and micronuclei formation in pollen mother cells. Our results reveal that elevated temperature causes a decrease in the amount of centromeric histone and the kinetochore protein BMF1 at meiotic centromeres with increasing temperature. Furthermore, we show that heat stress increases the duration of meiotic divisions and prolongs the activity of the spindle assembly checkpoint during meiosis I, indicating an impaired efficiency of the kinetochore attachments to spindle microtubules. Our analysis of mutants with reduced levels of centromeric histone suggests that weakened centromeres sensitize plants to elevated temperature, resulting in meiotic defects and reduced fertility even at moderate temperatures. These results indicate that the structure and functionality of meiotic centromeres in Arabidopsis are highly sensitive to heat stress, and suggest that centromeres and kinetochores may represent a critical bottleneck in plant adaptation to increasing temperatures.

Advances in the mechanisms and applications of RNA silencing in crop protection.

RNA silencing (or RNA interference, RNAi) is a conserved mechanism for regulating gene expression in eukaryotes, which plays vital roles in plant development and response to biotic and abiotic stresses. The discovery of trans-kingdom RNAi and interspecies RNAi provides a theoretical basis for exploiting RNAi-based crop protection strategies. Here, we summarize the canonical RNAi mechanisms in plants and review representative studies associated with plant-pathogen interactions. Meanwhile, we also elaborate upon the principles of host-induced gene silencing, spray-induced gene silencing and microbe-induced gene silencing, and discuss their applications in crop protection, thereby providing help to establish novel RNAi-based crop protection strategies.

Small but powerful: RALF peptides in plant adaptive and developmental responses.

Plants live in a highly dynamic environment and require to rapidly respond to a plethora of environmental stimuli, so that to maintain their optimal growth and development. A small plant peptide, rapid alkalization factor (RALF), can rapidly increase the pH value of the extracellular matrix in plant cells. RALFs always function with its corresponding receptors. Mechanistically, effective amount of RALF is induced and released at the critical period of plant growth and development or under different external environmental factors. Recent studies also highlighted the role of RALF peptides as important regulators in plant intercellular communications, as well as their operation in signal perception and as ligands for different receptor kinases on the surface of the plasma membrane, to integrate various environmental cues. In this context, understanding the fine-print of above processes may be essential to solve the problems of crop adaptation to various harsh environments under current climate trends scenarios, by genetic means. This paper summarizes the current knowledge about the structure and diversity of RALF peptides and their roles in plant development and response to stresses, highlighting unanswered questions and problems to be solved.

[Hemicellulose modification and cell wall genetic improvement in plants].

Hemicellulose, as a primary component of plant cell walls, constitutes approximately one third of cell wall dry matter and ranks as the second abundant renewable biomass resource in the nature after cellulose. Hemicellulose is tightly cross-linked with cellulose, lignin and other components in the plant cell wall, leading to lignocellulose recalcitrance. However, precise genetic modifications of plant cell walls can significantly improve the saccharification efficiency of lignocellulose while ensuring normal plant growth and development. We comprehensively review the research progress in the structural distribution of hemicellulose in plant cell walls, the cross-linking between hemicellulose and other components of the cell wall, and the impact of hemicellulose modification on the saccharification efficiency of the cell wall, proving a reference for the genetic improvement of energy crops.

[Spatial transcriptomics techniques and its applications in plant research].

The heterogeneity of gene expression in plant cells plays a crucial role in determining the functional differences among tissues. Recent advancements in spatial transcriptome (ST) technology have significantly contributed to the study of specific biological questions in plants. This technology has been successfully applied to examine cell development, identification, and stress resistance. This review aims to explore the application of ST technology in plants by reviewing three aspects: the development of ST technology, its current application in plants, and future research directions. The review provides a systematic description of the development process of ST technology, with a focus on analyzing its progress in studying plant cell growth and differentiation, plant cell identification, and stress resistance. In addition, the challenges faced by ST technology in plant applications are summarized, along with proposed future directions for plant research, including the advantages of combining other omics technologies with ST technology to tackle scientific challenges in the field of plants.

Optimizing selection based on BLUPs or BLUEs in multiple sets of genotypes differing in their population parameters.

KEY MESSAGE: Selection response in truncation selection across multiple sets of candidates hinges on their post-selection proportions, which can deviate grossly from their initial proportions. For BLUPs, using a uniform threshold for all candidates maximizes the selection response, irrespective of differences in population parameters. Plant breeding programs typically involve multiple families from either the same or different populations, varying in means, genetic variances and prediction accuracy of BLUPs or BLUEs for true genetic values (TGVs) of candidates. We extend the classical breeder's equation for truncation selection from single to multiple sets of genotypes, indicating that the expected overall selection response ( Δ G Tot ) for TGVs depends on the selection response within individual sets and their post-selection proportions. For BLUEs, we show that maximizing Δ G Tot requires thresholds optimally tailored for each set, contingent on their population parameters. For BLUPs, we prove that Δ G Tot is maximized by applying a uniform threshold across all candidates from all sets. We provide explicit formulas for the origin of the selected candidates from different sets and show that their proportions before and after selection can differ substantially, especially for sets with inferior properties and low proportion. We discuss implications of these results for (a) optimum allocation of resources to training and prediction sets and (b) the need to counteract narrowing the genetic variation under genomic selection. For genomic selection of hybrids based on BLUPs of GCA of their parent lines, selecting distinct proportions in the two parent populations can be advantageous, if these differ substantially in the variance and/or prediction accuracy of GCA. Our study sheds light on the complex interplay of selection thresholds and population parameters for the selection response in plant breeding programs, offering insights into the effective resource management and prudent application of genomic selection for improved crop development.

Divergence in regulatory mechanisms of GR-RBP genes in different plants under abiotic stress.

The IVa subfamily of glycine-rich proteins (GRPs) comprises a group of glycine-rich RNA binding proteins referred to as GR-RBPa here. Previous studies have demonstrated functions of GR-RBPa proteins in regulating stress response in plants. However, the mechanisms responsible for the differential regulatory functions of GR-RBPa proteins in different plant species have not been fully elucidated. In this study, we identified and comprehensively studied a total of 34 GR-RBPa proteins from five plant species. Our analysis revealed that GR-RBPa proteins were further classified into two branches, with proteins in branch I being relatively more conserved than those in branch II. When subjected to identical stresses, these genes exhibited intensive and differential expression regulation in different plant species, corresponding to the enrichment of cis-acting regulatory elements involving in environmental and internal signaling in these genes. Unexpectedly, all GR-RBPa genes in branch I underwent intensive alternative splicing (AS) regulation, while almost all genes in branch II were only constitutively spliced, despite having more introns. This study highlights the complex and divergent regulations of a group of conserved RNA binding proteins in different plants when exposed to identical stress conditions. These species-specific regulations may have implications for stress responses and adaptations in different plant species.

TIP aquaporins in Cyperus esculentus: genome-wide identification, expression profiles, subcellular localizations, and interaction patterns.

BACKGROUND: Tonoplast intrinsic proteins (TIPs), which typically mediate water transport across vacuolar membranes, play an essential role in plant growth, development, and stress responses. However, their characterization in tigernut (Cyperus esculentus L.), an oil-bearing tuber plant of the Cyperaceae family, is still in the infancy. RESULTS: In this study, a first genome-wide characterization of the TIP subfamily was conducted in tigernut, resulting in ten members representing five previously defined phylogenetic groups, i.e., TIP1-5. Although the gene amounts are equal to that present in two model plants Arabidopsis and rice, the group composition and/or evolution pattern were shown to be different. Except for CeTIP1;3 that has no counterpart in both Arabidopsis and rice, complex orthologous relationships of 1:1, 1:2, 1:3, 2:1, and 2:2 were observed. Expansion of the CeTIP subfamily was contributed by whole-genome duplication (WGD), transposed, and dispersed duplications. In contrast to the recent WGD-derivation of CeTIP3;1/-3;2, synteny analyses indicated that TIP4 and - 5 are old WGD repeats of TIP2, appearing sometime before monocot-eudicot divergence. Expression analysis revealed that CeTIP genes exhibit diverse expression profiles and are subjected to developmental and diurnal fluctuation regulation. Moreover, when transiently overexpressed in tobacco leaves, CeTIP1;1 was shown to locate in the vacuolar membrane and function in homo/heteromultimer, whereas CeTIP2;1 is located in the cell membrane and only function in heteromultimer. Interestingly, CeTIP1;1 could mediate the tonoplast-localization of CeTIP2;1 via protein interaction, implying complex regulatory patterns. CONCLUSIONS: Our findings provide a global view of CeTIP genes, which provide valuable information for further functional analysis and genetic improvement through manipulating key members in tigernut.

Molecular identification of Hymenopteran insects collected by using Malaise traps from Hazarganji Chiltan National Park Quetta, Pakistan.

The order Hymenoptera holds great significance for humans, particularly in tropical and subtropical regions, due to its role as a pollinator of wild and cultivated flowering plants, parasites of destructive insects and honey producers. Despite this importance, limited attention has been given to the genetic diversity and molecular identification of Hymenopteran insects in most protected areas. This study provides insights into the first DNA barcode of Hymenopteran insects collected from Hazarganji Chiltan National Park (HCNP) and contributes to the global reference library of DNA barcodes. A total of 784 insect specimens were collected using Malaise traps, out of which 538 (68.62%) specimens were morphologically identified as Hymenopteran insects. The highest abundance of species of Hymenoptera (133/538, 24.72%) was observed during August and least in November (16/538, 2.97%). Genomic DNA extraction was performed individually from 90/538 (16.73%) morphologically identified specimens using the standard phenol-chloroform method, which were subjected separately to the PCR for their molecular confirmation via the amplification of cytochrome c oxidase subunit 1 (cox1) gene. The BLAST analyses of obtained sequences showed 91.64% to 100% identities with related sequences and clustered phylogenetically with their corresponding sequences that were reported from Australia, Bulgaria, Canada, Finland, Germany, India, Israel, and Pakistan. Additionally, total of 13 barcode index numbers (BINs) were assigned by Barcode of Life Data Systems (BOLD), out of which 12 were un-unique and one was unique (BOLD: AEU1239) which was assigned for Anthidium punctatum. This indicates the potential geographical variation of Hymenopteran population in HCNP. Further comprehensive studies are needed to molecularly confirm the existing insect species in HCNP and evaluate their impacts on the environment, both as beneficial (for example, pollination, honey producers and natural enemies) and detrimental (for example, venomous stings, crop damage, and pathogens transmission).

A review of the potential involvement of small RNAs in transgenerational abiotic stress memory in plants.

Crop production is increasingly threatened by the escalating weather events and rising temperatures associated with global climate change. Plants have evolved adaptive mechanisms, including stress memory, to cope with abiotic stresses such as heat, drought, and salinity. Stress memory involves priming, where plants remember prior stress exposures, providing enhanced responses to subsequent stress events. Stress memory can manifest as somatic, intergenerational, or transgenerational memory, persisting for different durations. The chromatin, a central regulator of gene expression, undergoes modifications like DNA acetylation, methylation, and histone variations in response to abiotic stress. Histone modifications, such as H3K4me3 and acetylation, play crucial roles in regulating gene expression. Abiotic stresses like drought and salinity are significant challenges to crop production, leading to yield reductions. Plant responses to stress involve strategies like escape, avoidance, and tolerance, each influencing growth stages differently. Soil salinity affects plant growth by disrupting water potential, causing ion toxicity, and inhibiting nutrient uptake. Understanding plant responses to these stresses requires insights into histone-mediated modifications, chromatin remodeling, and the role of small RNAs in stress memory. Histone-mediated modifications, including acetylation and methylation, contribute to epigenetic stress memory, influencing plant adaptation to environmental stressors. Chromatin remodeling play a crucial role in abiotic stress responses, affecting the expression of stress-related genes. Small RNAs; miRNAs and siRNAs, participate in stress memory pathways by guiding DNA methylation and histone modifications. The interplay of these epigenetic mechanisms helps plants adapt to recurring stress events and enhance their resilience. In conclusion, unraveling the epigenetic mechanisms in plant responses to abiotic stresses provides valuable insights for developing resilient agricultural techniques. Understanding how plants utilize stress memory, histone modifications, chromatin remodeling, and small RNAs is crucial for designing strategies to mitigate the impact of climate change on crop production and global food security.