Untargeted metabolomics profiling of oat (Avena sativa L.) and wheat (Triticum aestivum L.) infested with wheat stem sawfly (Cephus cinctus Norton) reveals differences associated with plant defense and insect nutrition.

Introduction: Wheat stem sawfly (WSS), Cephus cinctus Norton, is a major pest of common bread wheat (Triticum aestivum L.) and other cultivated cereals in North America. Planting of cultivars with solid stems has been the primary management strategy to prevent yield loss due to WSS infestation, however expression of this phenotype can vary depending on environmental conditions and solid stems hinder biological control of WSS via braconid parasitoids Bracon cephi (Gahan) and Bracon lissogaster Muesebeck. In the hollow stems of oat (Avena sativa L.), WSS larvae experience 100% mortality before they reach late instars, but the mechanisms for this observed resistance have not been characterized. Objective: The objective of this study was to explore additional sources of resistance outside of the historic solid stem phenotype. Methods: Here, we use an untargeted metabolomics approach to examine the response of the metabolome of two cultivars of oat and four cultivars of spring wheat to infestation by WSS. Using liquid chromatography-mass spectrometry (LC-MS), differentially expressed metabolites were identified between oat and wheat which were associated with the phenylpropanoid pathway, phospholipid biosynthesis and signaling, the salicylic acid signaling pathway, indole-3-acetic acid (IAA) degradation, and biosynthesis of 1,4-benzoxazin-3-ones (Bxs). Several phospho- and galacto- lipids were found in higher abundance in oat, and with the exception of early stem solidness cultivar Conan, both species experienced a decrease in abundance once infested. In all wheat cultivars except Conan, an increase in abundance was observed for Bxs HMDBOA-glc and DIBOA-ß-D-glucoside after infestation, indicating that this pathway is involved in wheat response to infestation in both solid and hollow stemmed cultivars. Differences between species in compounds involved in IAA biosynthesis, degradation and inactivation suggest that wheat may respond to infestation by inactivating IAA or altering the IAA pool in stem tissue. Conclusion: We propose that the species differences found here likely affect the survival of WSS larvae and may also be associated with differences in stem architecture at the molecular level. Our findings suggest pathways to focus on for future studies in elucidating plant response to WSS infestation.

Wheat Long Noncoding RNAs from Organelle and Nuclear Genomes Carry Conserved microRNA Precursors Which May Together Comprise Intricate Networks in Insect Responses.

Long noncoding RNAs (lncRNAs) are a diverse class of noncoding RNAs that are typically longer than 200 nucleotides but lack coding potentials. Advances in deep sequencing technologies enabled a better exploration of this type of noncoding transcripts. The poor sequence conservation, however, complicates the identification and annotation of lncRNAs at a large scale. Wheat is among the leading food staples worldwide whose production is threatened by both biotic and abiotic stressors. Here, we identified putative lncRNAs from durum wheat varieties that differ in stem solidness, a major source of defense against wheat stem sawfly, a devastating insect pest. We also analyzed and annotated lncRNAs from two bread wheat varieties, resistant and susceptible to another destructive pest, orange wheat blossom midge, with and without infestation. Several putative lncRNAs contained potential precursor sequences and/or target regions for microRNAs, another type of regulatory noncoding RNAs, which may indicate functional networks. Interestingly, in contrast to lncRNAs themselves, microRNAs with potential precursors within the lncRNA sequences appeared to be highly conserved at the sequence and family levels. We also observed a few putative lncRNAs that have perfect to near-perfect matches to organellar genomes, supporting the recent observations that organellar genomes may contribute to the noncoding transcript pool of the cell.

The isothiocyanate sulforaphane induces respiratory burst oxidase homologue D-dependent reactive oxygen species production and regulates expression of stress response genes.

Sulforaphane (SFN) is an isothiocyanate-type phytomolecule present in crucifers, which is mainly synthesized in response to biotic stress. In animals, SFN incorporated in the diet has anticancer properties among others. The mechanism of action and signaling are well described in animals; however, little is known in plants. The goal in the present study is to elucidate components of the SFN signaling pathway, particularly the production of reactive oxygen species (ROS), and its effect on the transcriptome. Our results showed that in Arabidopsis, SFN causes ROS production exclusively through the action of the NADPH oxidase RBOH isoform D that requires calcium as a signaling component for the ROS production. To add to this, we also analyzed the effect of SFN on the transcriptome by RNAseq. We observed the highest expression increase for heat shock proteins (HSP) genes and also for genes associated with the response to oxidative stress. The upregulation of several genes linked to the biotic stress response confirms the interplay between SFN and this stress. In addition, SFN increases the levels of transcripts related to the response to abiotic stress, as well as phytohormones. Taken together, these results indicate that SFN induces an oxidative burst leading to signaling events. This oxidative burst may cause the increase of the expression of genes such as heat shock proteins to restore cellular homeostasis and genes that codify possible components of the signaling pathway and putative effectors.

The complete genome sequence of elite bread wheat cultivar, "Sonmez".

High-yielding crop varieties will become critical in meeting the future food demand in the face of worsening weather extremes and threatening biotic stressors. The bread wheat cultivar Sonmez-2001 is a registered variety that is notable for its performance under low-irrigation conditions, which further improves upon irrigation. Additionally, Sonmez-2001 is resilient against certain biotic stressors, particularly soil-borne pathogens. Here, we provide a reference-guided whole genome sequence of Sonmez-2001, assembled into 21 chromosomes of the A, B and D genomes and totaling 13.3 gigabase-pairs in length. Additionally, a de novo assembly of an additional 1.05 gigabase-pairs was generated that represents either Sonmez-specific sequences or sequences that considerably diverged between Sonmez and Chinese Spring. Within this de novo assembly, we identified 35 gene models, of which 11 were high-confidence, that may contribute to the favorable traits of this high-performing variety. We identified up to 24 million sequence variants, of which up to 2.4% reside in coding sequences, that can be used to develop molecular markers that should be of immediate use to the cereal community.

G4Boost: a machine learning-based tool for quadruplex identification and stability prediction.

BACKGROUND: G-quadruplexes (G4s), formed within guanine-rich nucleic acids, are secondary structures involved in important biological processes. Although every G4 motif has the potential to form a stable G4 structure, not every G4 motif would, and accurate energy-based methods are needed to assess their structural stability. Here, we present a decision tree-based prediction tool, G4Boost, to identify G4 motifs and predict their secondary structure folding probability and thermodynamic stability based on their sequences, nucleotide compositions, and estimated structural topologies. RESULTS: G4Boost predicted the quadruplex folding state with an accuracy greater then 93% and an F1-score of 0.96, and the folding energy with an RMSE of 4.28 and R2 of 0.95 only by the means of sequence intrinsic feature. G4Boost was successfully applied and validated to predict the stability of experimentally-determined G4 structures, including for plants and humans. CONCLUSION: G4Boost outperformed the three machine-learning based prediction tools, DeepG4, Quadron, and G4RNA Screener, in terms of both accuracy and F1-score, and can be highly useful for G4 prediction to understand gene regulation across species including plants and humans.

Comparative Analysis of Coding and Non-Coding Features within Insect Tolerance Loci in Wheat with Their Homologs in Cereal Genomes.

Food insecurity and malnutrition have reached critical levels with increased human population, climate fluctuations, water shortage; therefore, higher-yielding crops are in the spotlight of numerous studies. Abiotic factors affect the yield of staple food crops; among all, wheat stem sawfly (Cephus cinctus Norton) and orange wheat blossom midge (Sitodiplosis mosellana) are two of the most economically and agronomically harmful insect pests which cause yield loss in cereals, especially in wheat in North America. There is no effective strategy for suppressing this pest damage yet, and only the plants with intrinsic tolerance mechanisms such as solid stem phenotypes for WSS and antixenosis and/or antibiosis mechanisms for OWBM can limit damage. A major QTL and a causal gene for WSS resistance were previously identified in wheat, and 3 major QTLs and a causal gene for OWBM resistance. Here, we present a comparative analysis of coding and non-coding features of these loci of wheat across important cereal crops, barley, rye, oat, and rice. This research paves the way for our cloning and editing of additional WSS and OWBM tolerance gene(s), proteins, and metabolites.

Multiple Variant Calling Pipelines in Wheat Whole Exome Sequencing.

The highly challenging hexaploid wheat (Triticum aestivum) genome is becoming ever more accessible due to the continued development of multiple reference genomes, a factor which aids in the plight to better understand variation in important traits. Although the process of variant calling is relatively straightforward, selection of the best combination of the computational tools for read alignment and variant calling stages of the analysis and efficient filtering of the false variant calls are not always easy tasks. Previous studies have analyzed the impact of methods on the quality metrics in diploid organisms. Given that variant identification in wheat largely relies on accurate mining of exome data, there is a critical need to better understand how different methods affect the analysis of whole exome sequencing (WES) data in polyploid species. This study aims to address this by performing whole exome sequencing of 48 wheat cultivars and assessing the performance of various variant calling pipelines at their suggested settings. The results show that all the pipelines require filtering to eliminate false-positive calls. The high consensus among the reference SNPs called by the best-performing pipelines suggests that filtering provides accurate and reproducible results. This study also provides detailed comparisons for high sensitivity and precision at individual and population levels for the raw and filtered SNP calls.

Aegilops tauschii genome assembly Aet v5.0 features greater sequence contiguity and improved annotation.

Aegilops tauschii is the donor of the D subgenome of hexaploid wheat and an important genetic resource. The reference-quality genome sequence Aet v4.0 for Ae. tauschii acc. AL8/78 was therefore an important milestone for wheat biology and breeding. Further advances in sequencing acc. AL8/78 and release of the Aet v5.0 sequence assembly are reported here. Two new optical maps were constructed and used in the revision of pseudomolecules. Gaps were closed with Pacific Biosciences long-read contigs, decreasing the gap number by 38,899. Transposable elements and protein-coding genes were reannotated. The number of annotated high-confidence genes was reduced from 39,635 in Aet v4.0 to 32,885 in Aet v5.0. A total of 2245 biologically important genes, including those affecting plant phenology, grain quality, and tolerance of abiotic stresses in wheat, was manually annotated and disease-resistance genes were annotated by a dedicated pipeline. Disease-resistance genes encoding nucleotide-binding site domains, receptor-like protein kinases, and receptor-like proteins were preferentially located in distal chromosome regions, whereas those encoding transmembrane coiled-coil proteins were dispersed more evenly along the chromosomes. Discovery, annotation, and expression analyses of microRNA (miRNA) precursors, mature miRNAs, and phasiRNAs are reported, including miRNA target genes. Other small RNAs, such as hc-siRNAs and tRFs, were characterized. These advances enhance the utility of the Ae. tauschii genome sequence for wheat genetics, biotechnology, and breeding.

OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security.

The incredible success of crop breeding and agricultural innovation in the last century greatly contributed to the Green Revolution, which significantly increased yields and ensures food security, despite the population explosion. However, new challenges such as rapid climate change, deteriorating soil, and the accumulation of pollutants require much faster responses and more effective solutions that cannot be achieved through traditional breeding. Further prospects for increasing the efficiency of agriculture are undoubtedly associated with the inclusion in the breeding strategy of new knowledge obtained using high-throughput technologies and new tools in the future to ensure the design of new plant genomes and predict the desired phenotype. This article provides an overview of the current state of research in these areas, as well as the study of soil and plant microbiomes, and the prospective use of their potential in a new field of microbiome engineering. In terms of genomic and phenomic predictions, we also propose an integrated approach that combines high-density genotyping and high-throughput phenotyping techniques, which can improve the prediction accuracy of quantitative traits in crop species.

Pan-Genome miRNomics in Brachypodium.

Pan-genomes are efficient tools for the identification of conserved and varying genomic sequences within lineages of a species. Investigating genetic variations might lead to the discovery of genes present in a subset of lineages, which might contribute into beneficial agronomic traits such as stress resistance or yield. The content of varying genomic regions in the pan-genome could include protein-coding genes as well as microRNA(miRNAs), small non-coding RNAs playing key roles in the regulation of gene expression. In this study, we performed in silico miRNA identification from the genomic sequences of 54 lineages of Brachypodium distachyon, aiming to explore varying miRNA contents and their functional interactions. A total of 115 miRNA families were identified in 54 lineages, 56 of which were found to be present in all lineages. The miRNA families were classified based on their conservation among lineages and potential mRNA targets were identified. Obtaining information about regulatory mechanisms stemming from these miRNAs offers strong potential to provide a better insight into the complex traits that were potentially present in some lineages. Future work could lead us to introduce these traits to different lineages or other economically important plant species in order to promote their survival in different environmental conditions.

mirMachine: A One-Stop Shop for Plant miRNA Annotation.

Of different types of noncoding RNAs, microRNAs (miRNAs) have arguably been in the spotlight over the last decade. As post-transcriptional regulators of gene expression, miRNAs play key roles in various cellular pathways, including both development and response to a/biotic stress, such as drought and diseases. Having high-quality reference genome sequences enabled identification and annotation of miRNAs in several plant species, where miRNA sequences are highly conserved. As computational miRNA identification and annotation processes are mostly error-prone processes, homology-based predictions increase prediction accuracy. We developed and have improved the miRNA annotation pipeline, SUmir, in the last decade, which has been used for several plant genomes since then. This study presents a fully automated, new miRNA pipeline, mirMachine (miRNA Machine), by (i) adding an additional filtering step on the secondary structure predictions, (ii) making it fully automated, and (iii) introducing new options to predict either known miRNA based on homology or novel miRNAs based on small RNA sequencing reads using the previous pipeline. The new miRNA pipeline, mirMachine, was tested using The Arabidopsis Information Resource, TAIR10, release of the Arabidopsis genome and the International Wheat Genome Sequencing Consortium (IWGSC) wheat reference genome v2.

Regulatory non-coding RNAs: a new frontier in regulation of plant biology.

Beyond the most crucial roles of RNA molecules as a messenger, ribosomal, and transfer RNAs, the regulatory role of many non-coding RNAs (ncRNAs) in plant biology has been recognized. ncRNAs act as riboregulators by recognizing specific nucleic acid targets through homologous sequence interactions to regulate plant growth, development, and stress responses. Regulatory ncRNAs, ranging from small to long ncRNAs (lncRNAs), exert their control over a vast array of biological processes. Based on the mode of biogenesis and their function, ncRNAs evolved into different forms that include microRNAs (miRNAs), small interfering RNAs (siRNAs), miRNA variants (isomiRs), lncRNAs, circular RNAs (circRNAs), and derived ncRNAs. This article explains the different classes of ncRNAs and their role in plant development and stress responses. Furthermore, the applications of regulatory ncRNAs in crop improvement, targeting agriculturally important traits, have been discussed.

CRISPR/Cas: a Nobel Prize award-winning precise genome editing technology for gene therapy and crop improvement.

Since it was first recognized in bacteria and archaea as a mechanism for innate viral immunity in the early 2010s, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) has rapidly been developed into a robust, multifunctional genome editing tool with many uses. Following the discovery of the initial CRISPR/Cas-based system, the technology has been advanced to facilitate a multitude of different functions. These include development as a base editor, prime editor, epigenetic editor, and CRISPR interference (CRISPRi) and CRISPR activator (CRISPRa) gene regulators. It can also be used for chromatin and RNA targeting and imaging. Its applications have proved revolutionary across numerous biological fields, especially in biomedical and agricultural improvement. As a diagnostic tool, CRISPR has been developed to aid the detection and screening of both human and plant diseases, and has even been applied during the current coronavirus disease 2019 (COVID-19) pandemic. CRISPR/Cas is also being trialed as a new form of gene therapy for treating various human diseases, including cancers, and has aided drug development. In terms of agricultural breeding, precise targeting of biological pathways via CRISPR/Cas has been key to regulating molecular biosynthesis and allowing modification of proteins, starch, oil, and other functional components for crop improvement. Adding to this, CRISPR/Cas has been shown capable of significantly enhancing both plant tolerance to environmental stresses and overall crop yield via the targeting of various agronomically important gene regulators. Looking to the future, increasing the efficiency and precision of CRISPR/Cas delivery systems and limiting off-target activity are two major challenges for wider application of the technology. This review provides an in-depth overview of current CRISPR development, including the advantages and disadvantages of the technology, recent applications, and future considerations.

Genome-wide discovery of G-quadruplexes in barley.

G-quadruplexes (G4s) are four-stranded nucleic acid structures with closely spaced guanine bases forming square planar G-quartets. Aberrant formation of G4 structures has been associated with genomic instability. However, most plant species are lacking comprehensive studies of G4 motifs. In this study, genome-wide identification of G4 motifs in barley was performed, followed by a comparison of genomic distribution and molecular functions to other monocot species, such as wheat, maize, and rice. Similar to the reports on human and some plants like wheat, G4 motifs peaked around the 5' untranslated region (5' UTR), the first coding domain sequence, and the first intron start sites on antisense strands. Our comparative analyses in human, Arabidopsis, maize, rice, and sorghum demonstrated that the peak points could be erroneously merged into a single peak when large window sizes are used. We also showed that the G4 distributions around genic regions are relatively similar in the species studied, except in the case of Arabidopsis. G4 containing genes in monocots showed conserved molecular functions for transcription initiation and hydrolase activity. Additionally, we provided examples of imperfect G4 motifs.

Efficient genome editing in wheat using Cas9 and Cpf1 (AsCpf1 and LbCpf1) nucleases.

Genome editing can be used to create new wheat varieties with enhanced performance. Clustered regularly interspaced short palindromic repeat (CRISPR) is a powerful tool for knockout generation, precise modification, multiplex engineering, and the activation and repression of target genes. Targeted mutagenesis via RNA-guided genome editing using type II CRISPR-Cas9 is highly efficient in some plant species, but not in others. One possible solution is to use newly discovered variants of genome editing enzymes such as the class 2 system component Cpf1 (CRISPR from Prevotella and Francisella 1) in place of the more commonly used Cas9. We compared the editing efficiency of Cas9 and two Cpf1 orthologs, AsCpf1 (Acidaminococcus spp. BV3L6) and LbCpf1 (Lachnospiraceae bacterium ND2006) in wheat (Triticum aestivum). LbCpf1 had a higher editing efficiency for the target gene TaPDS than AsCpf1 and Cas9, and Cas9 induced more off-target mutations than AsCpf1 and LbCpf1, suggesting that CRISPR-LbCpf1 is a powerful genome editing tool for polyploid plants such as wheat.

Chromosome-scale genome assembly provides insights into rye biology, evolution and agronomic potential.

Rye (Secale cereale L.) is an exceptionally climate-resilient cereal crop, used extensively to produce improved wheat varieties via introgressive hybridization and possessing the entire repertoire of genes necessary to enable hybrid breeding. Rye is allogamous and only recently domesticated, thus giving cultivated ryes access to a diverse and exploitable wild gene pool. To further enhance the agronomic potential of rye, we produced a chromosome-scale annotated assembly of the 7.9-gigabase rye genome and extensively validated its quality by using a suite of molecular genetic resources. We demonstrate applications of this resource with a broad range of investigations. We present findings on cultivated rye's incomplete genetic isolation from wild relatives, mechanisms of genome structural evolution, pathogen resistance, low-temperature tolerance, fertility control systems for hybrid breeding and the yield benefits of rye-wheat introgressions.

LncMachine: a machine learning algorithm for long noncoding RNA annotation in plants.

Following the elucidation of the critical roles they play in numerous important biological processes, long noncoding RNAs (lncRNAs) have gained vast attention in recent years. Manual annotation of lncRNAs is restricted by known gene annotations and is prone to false prediction due to the incompleteness of available data. However, with the advent of high-throughput sequencing technologies, a magnitude of high-quality data has become available for annotation, especially for plant species such as wheat. Here, we compared prediction accuracies of several machine learning algorithms using a 10-fold cross-validation. This study includes a comprehensive feature selection step to refine irrelevant and repeated features. We present a crop-specific, alignment-free coding potential prediction tool, LncMachine, that performs at higher prediction accuracies than the currently available popular tools (CPC2, CPAT, and CNIT) when used with the Random Forest algorithm. Further, LncMachine with Random Forest performed well on human and mouse data, with an average accuracy of 92.67%. LncMachine only requires either a FASTA file or a TAB separated CSV file containing features as input files. LncMachine can deploy several user-provided algorithms in real time and therefore be effortlessly applied to a wide range of studies.

Genome-Wide Diversity of MADS-Box Genes in Bread Wheat is Associated with its Rapid Global Adaptability.

MADS-box gene family members play multifarious roles in regulating the growth and development of crop plants and hold enormous promise for bolstering grain yield potential under changing global environments. Bread wheat (Triticum aestivum L.) is a key stable food crop around the globe. Until now, the available information concerning MADS-box genes in the wheat genome has been insufficient. Here, a comprehensive genome-wide analysis identified 300 high confidence MADS-box genes from the publicly available reference genome of wheat. Comparative phylogenetic analyses with Arabidopsis and rice MADS-box genes classified the wheat genes into 16 distinct subfamilies. Gene duplications were mainly identified in subfamilies containing unbalanced homeologs, pointing towards a potential mechanism for gene family expansion. Moreover, a more rapid evolution was inferred for M-type genes, as compared with MIKC-type genes, indicating their significance in understanding the evolutionary history of the wheat genome. We speculate that subfamily-specific distal telomeric duplications in unbalanced homeologs facilitate the rapid adaptation of wheat to changing environments. Furthermore, our in-silico expression data strongly proposed MADS-box genes as active guardians of plants against pathogen insurgency and harsh environmental conditions. In conclusion, we provide an entire complement of MADS-box genes identified in the wheat genome that could accelerate functional genomics efforts and possibly facilitate bridging gaps between genotype-to-phenotype relationships through fine-tuning of agronomically important traits.