The barley pan-genome reveals the hidden legacy of mutation breeding.

Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the 'pan-genome'1). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley (Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions2. Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley-comprising landraces, cultivars and a wild barley-that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding.

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.

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.

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.

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.

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.

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.

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.

Effect of phyB and phyC loss-of-function mutations on the wheat transcriptome under short and long day photoperiods.

BACKGROUND: Photoperiod signals provide important cues by which plants regulate their growth and development in response to predictable seasonal changes. Phytochromes, a family of red and far-red light receptors, play critical roles in regulating flowering time in response to changing photoperiods. A previous study showed that loss-of-function mutations in either PHYB or PHYC result in large delays in heading time and in the differential regulation of a large number of genes in wheat plants grown in an inductive long day (LD) photoperiod. RESULTS: We found that under non-inductive short-day (SD) photoperiods, phyB-null and phyC-null mutants were taller, had a reduced number of tillers, longer and wider leaves, and headed later than wild-type (WT) plants. The delay in heading between WT and phy mutants was greater in LD than in SD, confirming the importance of PHYB and PHYC in accelerating heading date in LDs. Both mutants flowered earlier in SD than LD, the inverse response to that of WT plants. In both SD and LD photoperiods, PHYB regulated more genes than PHYC. We identified subsets of differentially expressed and alternatively spliced genes that were specifically regulated by PHYB and PHYC in either SD or LD photoperiods, and a smaller set of genes that were regulated in both photoperiods. We found that photoperiod had a contrasting effect on transcript levels of the flowering promoting genes VRN-A1 and PPD-B1 in phyB and phyC mutants compared to the WT. CONCLUSIONS: Our study confirms the major role of both PHYB and PHYC in flowering promotion in LD conditions. Transcriptome characterization revealed an unexpected reversion of the wheat LD plants into SD plants in the phyB-null and phyC-null mutants and identified flowering genes showing significant interactions between phytochromes and photoperiod that may be involved in this phenomenon. Our RNA-seq data provides insight into light signaling pathways in inductive and non-inductive photoperiods and a set of candidate genes to dissect the underlying developmental regulatory networks in wheat.

Hotspots in the genomic architecture of field drought responses in wheat as breeding targets.

Wheat can adapt to most agricultural conditions across temperate regions. This success is the result of phenotypic plasticity conferred by a large and complex genome composed of three homoeologous genomes (A, B, and D). Although drought is a major cause of yield and quality loss in wheat, the adaptive mechanisms and gene networks underlying drought responses in the field remain largely unknown. Here, we addressed this by utilizing an interdisciplinary approach involving field water status phenotyping, sampling, and gene expression analyses. Overall, changes at the transcriptional level were reflected in plant spectral traits amenable to field-level physiological measurements, although changes in photosynthesis-related pathways were found likely to be under more complex post-transcriptional control. Examining homoeologous genes with a 1:1:1 relationship across the A, B, and D genomes (triads), we revealed a complex genomic architecture for drought responses under field conditions, involving gene homoeolog specialization, multiple gene clusters, gene families, miRNAs, and transcription factors coordinating these responses. Our results provide a new focus for genomics-assisted breeding of drought-tolerant wheat cultivars.

CRISPR/Cas9 genome editing in wheat.

Genome editing has been a long-term challenge for molecular biology research, particularly for plants possess complex genome. The recently discovered Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system is a versatile tool for genome editing which enables editing of multiple genes based on the guidance of small RNAs. Even though the efficiency of CRISPR/Cas9 system has been shown with several studies from diploid plants, its application remains a challenge for plants with polyploid and complex genome. Here, we applied CRISPR/Cas9 genome editing system in wheat protoplast to conduct the targeted editing of stress-responsive transcription factor genes, wheat dehydration responsive element binding protein 2 (TaDREB2) and wheat ethylene responsive factor 3 (TaERF3). Targeted genome editing of TaDREB2 and TaERF3 was achieved with transient expression of small guide RNA and Cas9 protein in wheat protoplast.  The effectiveness of mutagenesis in wheat protoplast was confirmed with restriction enzyme digestion assay, T7 endonuclease assay, and sequencing. Furthermore, several off-target regions for designed sgRNAs were analyzed, and the specificity of genome editing was confirmed with amplicon sequencing. Overall results suggested that CRISPR/Cas9 genome editing system can easily be established on wheat protoplast and it has a huge potentiality for targeted manipulation of wheat genome for crop improvement purposes.

A large-scale multiomics analysis of wheat stem solidness and the wheat stem sawfly feeding response, and syntenic associations in barley, Brachypodium, and rice.

The wheat stem sawfly (WSS), Cephus cinctus Norton (Hymenoptera: Cephidae), is an important pest of wheat and other cereals, threatening the quality and quantity of grain production. WSS larvae feed and develop inside the stem where they are protected from the external environment; therefore, pest management strategies primarily rely on host plant resistance. A major locus on the long arm of wheat chromosome 3B underlies most of the variation in stem solidness; however, the impact of stem solidness on WSS feeding has not been completely characterized. Here, we used a multiomics approach to examine the response to WSS in both solid- and semi-solid-stemmed wheat varieties. The combined transcriptomic, proteomic, and metabolomic data revealed that two important molecular pathways, phenylpropanoid and phosphate pentose, are involved in plant defense against WSS. We also detected a general downregulation of several key defense transcripts, including those encoding secondary metabolites such as DIMBOA, tricetin, and lignin, which suggested that the WSS larva might interfere with plant defense. We comparatively analyzed the stem solidness genomic region known to be associated with WSS tolerance in wild emmer, durum, and bread wheats, and described syntenic regions in the close relatives barley, Brachypodium, and rice. Additionally, microRNAs identified from the same genomic region revealed potential regulatory pathways associated with the WSS response. We propose a model outlining the molecular responses of the WSS-wheat interactions. These findings provide insight into the link between stem solidness and WSS feeding at the molecular level.

Correction to: A large-scale multiomics analysis of wheat stem solidness and the wheat stem sawfly feeding response, and syntenic associations in barley, Brachypodium, and rice.

The original version of this article contained a mistake. The word "RefSeq v.1" was incorrectly inserted on page 7. The correct sentence should be: To identify the differentially regulated transcripts, clean RNA-Seq reads were mapped onto the T. aestivum Chinese Spring chromosome 3B pseudomolecule.

Chromosome-based survey sequencing reveals the genome organization of wild wheat progenitor Triticum dicoccoides.

Wild emmer wheat (Triticum turgidum ssp. dicoccoides) is the progenitor of wheat. We performed chromosome-based survey sequencing of the 14 chromosomes, examining repetitive sequences, protein-coding genes, miRNA/target pairs and tRNA genes, as well as syntenic relationships with related grasses. We found considerable differences in the content and distribution of repetitive sequences between the A and B subgenomes. The gene contents of individual chromosomes varied widely, not necessarily correlating with chromosome size. We catalogued candidate agronomically important loci, along with new alleles and flanking sequences that can be used to design exome sequencing. Syntenic relationships and virtual gene orders revealed several small-scale evolutionary rearrangements, in addition to providing evidence for the 4AL-5AL-7BS translocation in wild emmer wheat. Chromosome-based sequence assemblies contained five novel miRNA families, among 59 families putatively encoded in the entire genome which provide insight into the domestication of wheat and an overview of the genome content and organization.

Comparative metabolite profiling of drought stress in roots and leaves of seven Triticeae species.

BACKGROUND: Drought is a lifestyle disease. Plant metabolomics has been exercised for understanding the fine-tuning of the potential pathways to surmount the adverse effects of drought stress. A broad spectrum of morphological and metabolic responses from seven Triticeae species including wild types with different drought tolerance/susceptibility level was investigated under control and water scarcity conditions. RESULTS: Significant morphological parameters measured were root length, surface area, average root diameter and overall root development. Principal Component Analysis, Partial Least-Squares-Discriminant Analysis and Hierarchical Cluster Analysis were applied to the metabolomic data obtained by Gas Chromatography-Mass Spectrometry technique in order to determine the important metabolites of the drought tolerance across seven different Triticeae species. The metabolites showing significant accumulation under the drought stress were considered as the key metabolites and correlated with potential biochemical pathways, enzymes or gene locations for a better understanding of the tolerance mechanisms. In all tested species, 45 significantly active metabolites with possible roles in drought stress were identified. Twenty-one metabolites out of forty-five including sugars, amino acids, organic acids and low molecular weight compounds increased in both leaf and root samples of TR39477, IG132864 and Bolal under the drought stress, contrasting to TTD-22, Tosunbey, Ligustica and Meyeri samples. Three metabolites including succinate, aspartate and trehalose were selected for further genome analysis due to their increased levels in TR39477, IG132864, and Bolal upon drought stress treatment as well as their significant role in energy producing biochemical pathways. CONCLUSION: These results demonstrated that the genotypes with high drought tolerance skills, especially wild emmer wheat, have a great potential to be a genetic model system for experiments aiming to validate metabolomics-genomics networks.

MicroRNAs in model and complex organisms.

Non-coding RNAs such as microRNAs (miRNAs) are very tiny ribonucleotides having an essential role in gene regulation at both post-transcriptional and translational levels. They are very conserved and expressed in worms, flies, plants, and mammals in a sequence-specific manner. Furthermore, it is now possible to clone miRNAs using the new genome editing tool CRISPR/cas9, which shows benefit in control of untargeted effect. In this special issue, we tried to cover researches associated with functional roles of miRNAs accross model and complex organisms.

Wheat miRNA ancestors: evident by transcriptome analysis of A, B, and D genome donors.

MicroRNAs are critical players of post-transcriptional gene regulation with profound effects on the fundamental processes of cellular life. Their identification and characterization, together with their targets, hold great significance in exploring and exploiting their roles on a functional context, providing valuable clues into the regulation of important biological processes, such as stress tolerance or environmental adaptation. Wheat is a hardy crop, extensively harvested in temperate regions, and is a major component of the human diet. With the advent of the next generation sequencing technologies considerably decreasing sequencing costs per base-pair, genomic, and transcriptomic data from several wheat species, including the progenitors and wild relatives have become available. In this study, we performed in silico identification and comparative analysis of microRNA repertoires of bread wheat (Triticum aestivum L.) and its diploid progenitors and relatives, Aegilops sharonensis, Aegilops speltoides, Aegilops tauschii, Triticum monococcum, and Triticum urartu through the utilization of publicly available transcriptomic data. Over 200 miRNA families were identified, majority of which have not previously been reported. Ancestral relationships expanded our understanding of wheat miRNA evolution, while T. monococcum miRNAs delivered important clues on the effects of domestication on miRNA expression. Comparative analyses on wild Ae. sharonensis accessions highlighted candidate miRNAs that can be linked to stress tolerance. The miRNA repertoires of bread wheat and its diploid progenitors and relatives provide important insight into the diversification and distribution of miRNA genes, which should contribute to the elucidation of miRNA evolution of Poaceae family. A thorough understanding of the convergent and divergent expression profiles of miRNAs in different genetic backgrounds can provide unique opportunities to modulation of gene regulation for better crop performance.

Abiotic stress miRNomes in the Triticeae.

The continued growth in world population necessitates increases in both the quantity and quality of agricultural production. Triticeae members, particularly wheat and barley, make an important contribution to world food reserves by providing rich sources of carbohydrate and protein. These crops are grown over diverse production environments that are characterized by a range of environmental or abiotic stresses. Abiotic stresses such as drought, heat, salinity, or nutrient deficiencies and toxicities cause large yield losses resulting in economic and environmental damage. The negative effects of abiotic stresses have increased at an alarming rate in recent years and are predicted to further deteriorate due to climate change, land degradation, and declining water supply. New technologies have provided an important tool with great potential for improving crop tolerance to the abiotic stresses: microRNAs (miRNAs). miRNAs are small regulators of gene expression that act on many different molecular and biochemical processes such as development, environmental adaptation, and stress tolerance. miRNAs can act at both the transcriptional and post-transcriptional levels, although post-transcriptional regulation is the most common in plants where miRNAs can inhibit the translation of their mRNA targets via complementary binding and cleavage. To date, expression of several miRNA families such as miR156, miR159, and miR398 has been detected as responsive to environmental conditions to regulate stress-associated molecular mechanisms individually and/or together with their various miRNA partners. Manipulation of these miRNAs and their targets may pave the way to improve crop performance under several abiotic stresses. Here, we summarize the current status of our knowledge on abiotic stress-associated miRNAs in members of the Triticeae tribe, specifically in wheat and barley, and the miRNA-based regulatory mechanisms triggered by stress conditions. Exploration of further miRNA families together with their functions under stress will improve our knowledge and provide opportunities to enhance plant performance to help us meet global food demand.

A large-scale chromosome-specific SNP discovery guideline.

Single-nucleotide polymorphisms (SNPs) are the most prevalent type of variation in genomes that are increasingly being used as molecular markers in diversity analyses, mapping and cloning of genes, and germplasm characterization. However, only a few studies reported large-scale SNP discovery in Aegilops tauschii, restricting their potential use as markers for the low-polymorphic D genome. Here, we report 68,592 SNPs found on the gene-related sequences of the 5D chromosome of Ae. tauschii genotype MvGB589 using genomic and transcriptomic sequences from seven Ae. tauschii accessions, including AL8/78, the only genotype for which a draft genome sequence is available at present. We also suggest a workflow to compare SNP positions in homologous regions on the 5D chromosome of Triticum aestivum, bread wheat, to mark single nucleotide variations between these closely related species. Overall, the identified SNPs define a density of 4.49 SNPs per kilobyte, among the highest reported for the genic regions of Ae. tauschii so far. To our knowledge, this study also presents the first chromosome-specific SNP catalog in Ae. tauschii that should facilitate the association of these SNPs with morphological traits on chromosome 5D to be ultimately targeted for wheat improvement.

High-throughput SNP genotyping of modern and wild emmer wheat for yield and root morphology using a combined association and linkage analysis.

Durum wheat (Triticum turgidum var. durum Desf.) is a major world crop that is grown primarily in areas of the world that experience periodic drought, and therefore, breeding climate-resilient durum wheat is a priority. High-throughput single nucleotide polymorphism (SNP) genotyping techniques have greatly increased the power of linkage and association mapping analyses for bread wheat, but as yet there is no durum wheat-specific platform available. In this study, we evaluate the new 384HT Wheat Breeders Array for its usefulness in tetraploid wheat breeding by genotyping a breeding population of F6 hybrids, derived from multiple crosses between T. durum cultivars and wild and cultivated emmer wheat accessions. Using a combined linkage and association mapping approach, we generated a genetic map including 1345 SNP markers, and identified markers linked to 6 QTLs for coleoptile length (2), heading date (1), anthocyanin accumulation (1) and osmotic stress tolerance (2). We also developed a straightforward approach for combining genetic data from multiple families of limited size that will be useful for evaluating and mapping pre-existing breeding material.