Next-generation sequencing applications for wheat crop improvement

Genome-wide analysis for root and leaf architecture traits associated with drought tolerance at the seedling stage in a highly ecologically diverse wheat population

Drought stress occurred at early growth stages in wheat affecting the following growth stages. Therefore, selecting promising drought-tolerant genotypes with highly adapted traits at the seedling stage is an important task for wheat breeders and geneticists. Few research efforts were conducted on the genetic control for drought-adaptive traits at the seedling stage in wheat. In this study, a set of 146 highly diverse spring wheat core collections representing 28 different countries was evaluated under drought stress at the seedling stage. All genotypes were exposed to drought stress for 13 days by water withholding. Leaf traits including seedling length, leaf wilting, days to wilting, leaf area, and leaf rolling were scored. Moreover, root traits such as root length, maximum width, emergence angle, tip angle, and number of roots were scored. Considerable significant genetic variation was found among all genotypes tested in these experiments. The heritability estimates ranged from 0.74 (leaf witling) to 0.99 (root tip angle). A set of nine genotypes were selected and considered drought-tolerant genotypes. Among all leaf traits, shoot length had significant correlations with all root traits under drought stress. The 146 genotypes were genotyped using the Infinium Wheat 15 K single nucleotide polymorphism (SNP) array and diversity arrays technology (DArT) marker platform. The result of genotyping revealed 12,999 SNPs and 2150 DArT markers which were used to run a genome-wide association study (GWAS). The results of GWAS revealed 169 markers associated with leaf and root traits under drought stress. Out of the 169 markers, 82 were considered major quantitative trait loci (QTL). The GWAS revealed 95 candidate genes were identified with 53 genes showing evidence for drought tolerance in wheat, while the remaining candidate genes were considered novel. No shared markers were found between leaf and root traits. The results of the study provided mapping novel markers associated with new root traits at the seedling stage. Also, the selected genotypes from different countries could be employed in future wheat breeding programs not only for improving adaptive drought-tolerant traits but also for expanding genetic diversity.

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction

To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifically emphasized the significance of Support Vector Regression (SVR) and SHapley Additive exPlanations (SHAP) in predicting soybean branching. By using branching data (phenotype) of 1918 soybean accessions and 42 k SNP (Single Nucleotide Polymorphism) polymorphic data (genotype), this study systematically compared 11 non-linear regression AI models, including four deep learning models (DBN (deep belief network) regression, ANN (artificial neural network) regression, Autoencoders regression, and MLP (multilayer perceptron) regression) and seven machine learning models (e.g., SVR (support vector regression), XGBoost (eXtreme Gradient Boosting) regression, Random Forest regression, LightGBM regression, GPs (Gaussian processes) regression, Decision Tree regression, and Polynomial regression). After being evaluated by four valuation metrics: R2 (R-squared), MAE (Mean Absolute Error), MSE (Mean Squared Error), and MAPE (Mean Absolute Percentage Error), it was found that the SVR, Polynomial Regression, DBN, and Autoencoder outperformed other models and could obtain a better prediction accuracy when they were used for phenotype prediction. In the assessment of deep learning approaches, we exemplified the SVR model, conducting analyses on feature importance and gene ontology (GO) enrichment to provide comprehensive support. After comprehensively comparing four feature importance algorithms, no notable distinction was observed in the feature importance ranking scores across the four algorithms, namely Variable Ranking, Permutation, SHAP, and Correlation Matrix, but the SHAP value could provide rich information on genes with negative contributions, and SHAP importance was chosen for feature selection. The results of this study offer valuable insights into AI-mediated plant breeding, addressing challenges faced by traditional breeding programs. The method developed has broad applicability in phenotype prediction, minor QTL (quantitative trait loci) mining, and plant smart-breeding systems, contributing significantly to the advancement of AI-based breeding practices and transitioning from experience-based to data-based breeding.

Assessment of genetic variation among wheat genotypes for drought tolerance utilizing microsatellite markers and morpho-physiological characteristics

Drought is a major abiotic stress that severely limits sustainable wheat (Triticum aestivum L.) productivity via morphological and physio-biochemical alterations of cellular processes. The complex nature and polygenic control of drought tolerance traits make breeding tolerant genotypes quite challenging. However, naturally occurring variabilities among wheat germplasm resources could potentially help combating drought. The present study was conducted to assess the drought tolerance of 18 Bangladeshi hexaploid wheat genotypes, focusing on the identification of potent sources of diversity by combining microsatellite markers, also known as single sequence repeat markers, and morpho-physiological characteristics that might help accelerating wheat crop improvement programs. Initially, the genotypes were evaluated using 25 microsatellite markers followed by an on-field evaluation of 7 morphological traits (plant height, spike number, spike length, grains per spike, 1000-grain weight, grain yield, biological yield) and 6 physiological traits (SPAD value, membrane stability index, leaf relative water content, proline content, canopy temperature depression, and leaf K+ ion content). The field-trial was conducted in a factorial fashion of 18 wheat genotypes and two water regimes (control and drought) following a split-plot randomized complete block design. Regardless of genotype, drought was significantly damaging for all the tested traits; however, substantial variability in drought stress tolerance was evident among the genotypes. Spike length, 1000-grain weight, SPAD value, leaf relative water content, canopy temperature depression, proline content, and potassium (K+) ion content were the most representative of drought-induced growth and yield impairments and also correlated well with the contrasting ability of genotypic tolerance. Microsatellite markers amplified 244 alleles exhibiting 79% genetic diversity. Out of 25 markers, 23 was highly polymorphic showing 77% average polymorphism. Morpho-physiological trait-based hierarchical clustering and microsatellite marker-based neighbor-jointing clustering both revealed three genotypic clusters with 71% co-linearity between them. In both cases, the genotypes Kanchan, BAW-1147, BINA Gom 1, BARI Gom 22, BARI Gom 26, and BARI Gom 33 were found to be comparatively more tolerant than the other tested genotypes, showing potential for cultivation in water-deficit environments. The findings of this study would contribute to the present understanding of drought tolerance in wheat and would provide a basis for future genotype selection for drought-tolerant wheat breeding programs.

Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding

Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.

High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS)

Improvement of grain yield is the ultimate goal for wheat breeding under water-limited environments. In the present study, a high-density linkage map was developed by using genotyping-by-sequencing (GBS) of a recombinant inbred line (RIL) population derived from the cross between Iranian landrace #49 and cultivar Yecora Rojo. The population was evaluated in three locations in Iran during two years under irrigated and water deficit conditions for the agronomic traits grain yield (GY), plant height (PH), spike number per square meter (SM), 1000 kernel weight (TKW), grain number per spike (GNS), spike length (SL), biomass (BIO) and harvest index (HI). A linkage map was constructed using 5831 SNPs assigned to 21 chromosomes, spanning 3642.14 cM of the hexaploid wheat genome with an average marker density of 0.62 (markers/cM). In total, 85 QTLs were identified on 19 chromosomes (all except 5D and 6D) explaining 6.06–19.25% of the traits phenotypic variance. We could identify 20 novel QTLs explaining 8.87–19.18% of phenotypic variance on chromosomes 1A, 1B, 1D, 2B, 3A, 3B, 6A, 6B and 7A. For 35 out of 85 mapped QTLs functionally annotated genes were identified which could be related to a potential role in drought stress.

RNA-Seq Analysis of Developing Grains of Wheat to Intrigue Into the Complex Molecular Mechanism of the Heat Stress Response

Heat stress is one of the significant constraints affecting wheat production worldwide. To ensure food security for ever-increasing world population, improving wheat for heat stress tolerance is needed in the presently drifting climatic conditions. At the molecular level, heat stress tolerance in wheat is governed by a complex interplay of various heat stress-associated genes. We used a comparative transcriptome sequencing approach to study the effect of heat stress (5°C above ambient threshold temperature of 20°C) during grain filling stages in wheat genotype K7903 (Halna). At 7 DPA (days post-anthesis), heat stress treatment was given at four stages: 0, 24, 48, and 120 h. In total, 115,656 wheat genes were identified, including 309 differentially expressed genes (DEGs) involved in many critical processes, such as signal transduction, starch synthetic pathway, antioxidant pathway, and heat stress-responsive conserved and uncharacterized putative genes that play an essential role in maintaining the grain filling rate at the high temperature. A total of 98,412 Simple Sequences Repeats (SSR) were identified from de novo transcriptome assembly of wheat and validated. The miRNA target prediction from differential expressed genes was performed by psRNATarget server against 119 mature miRNA. Further, 107,107 variants including 80,936 Single nucleotide polymorphism (SNPs) and 26,171 insertion/deletion (Indels) were also identified in de novo transcriptome assembly of wheat and wheat genome Ensembl version 31. The present study enriches our understanding of known heat response mechanisms during the grain filling stage supported by discovery of novel transcripts, microsatellite markers, putative miRNA targets, and genetic variant. This enhances gene functions and regulators, paving the way for improved heat tolerance in wheat varieties, making them more suitable for production in the current climate change scenario.

QTL Analysis of Adult Plant Resistance to Stripe Rust in a Winter Wheat Recombinant Inbred Population

Stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici, is a worldwide disease of wheat that causes devastating crop losses. Resistant cultivars have been developed over the last 40 years that have significantly reduced the economic impact of the disease on growers, but in heavy infection years it is mostly controlled through the intensive application of fungicides. The Pacific Northwest of the United States has an ideal climate for stripe rust and has one of the most diverse race compositions in the country. This has resulted in many waves of epidemics that have overcome most of the resistance genes traditionally used in elite germplasm. The best way to prevent high yield losses, reduce production costs to growers, and reduce the heavy application of fungicides is to pyramid multiple stripe rust resistance genes into new cultivars. Using genotyping-by-sequencing, we identified 4662 high quality variant positions in a recombinant inbred line population of 196 individuals derived from a cross between Skiles, a highly resistant winter wheat cultivar, and Goetze, a moderately to highly susceptible winter wheat cultivar, both developed at Oregon State University. A subsequent genome wide association study identified two quantitative trait loci (QTL) on chromosomes 3B and 3D within the predicted locations of stripe rust resistance genes. Resistance QTL, when combined together, conferred high levels of stripe rust resistance above the level of Skiles in some locations, indicating that these QTL would be important additions to future breeding efforts of Pacific Northwest winter wheat cultivars.

Wheat omics: Classical breeding to new breeding technologies

Wheat is an important cereal crop, and its significance is more due to compete for dietary products in the world. Many constraints facing by the wheat crop due to environmental hazardous, biotic, abiotic stress and heavy matters factors, as a result, decrease the yield. Understanding the molecular mechanism related to these factors is significant to figure out genes regulate under specific conditions. Classical breeding using hybridization has been used to increase the yield but not prospered at the desired level. With the development of newly emerging technologies in biological sciences i.e., marker assisted breeding (MAB), QTLs mapping, mutation breeding, proteomics, metabolomics, next-generation sequencing (NGS), RNA_sequencing, transcriptomics, differential expression genes (DEGs), computational resources and genome editing techniques i.e. (CRISPR cas9; Cas13) advances in the field of omics. Application of new breeding technologies develops huge data; considerable development is needed in bioinformatics science to interpret the data. However, combined omics application to address physiological questions linked with genetics is still a challenge. Moreover, viroid discovery opens the new direction for research, economics, and target specification. Comparative genomics important to figure gene of interest processes are further discussed about considering the identification of genes, genomic loci, and biochemical pathways linked with stress resilience in wheat. Furthermore, this review extensively discussed the omics approaches and their effective use. Integrated plant omics technologies have been used viroid genomes associated with CRISPR and CRISPR-associated Cas13a proteins system used for engineering of viroid interference along with high-performance multidimensional phenotyping as a significant limiting factor for increasing stress resistance in wheat.

Tackling microbial threats in agriculture with integrative imaging and computational approaches

Pathogens and pests are one of the major threats to agricultural productivity worldwide. For decades, targeted resistance breeding was used to create crop cultivars that resist pathogens and environmental stress while retaining yields. The often decade-long process of crossing, selection, and field trials to create a new cultivar is challenged by the rapid rise of pathogens overcoming resistance. Similarly, antimicrobial compounds can rapidly lose efficacy due to resistance evolution. Here, we review three major areas where computational, imaging and experimental approaches are revolutionizing the management of pathogen damage on crops. Recognizing and scoring plant diseases have dramatically improved through high-throughput imaging techniques applicable both under well-controlled greenhouse conditions and directly in the field. However, computer vision of complex disease phenotypes will require significant improvements. In parallel, experimental setups similar to high-throughput drug discovery screens make it possible to screen thousands of pathogen strains for variation in resistance and other relevant phenotypic traits. Confocal microscopy and fluorescence can capture rich phenotypic information across pathogen genotypes. Through genome-wide association mapping approaches, phenotypic data helps to unravel the genetic architecture of stress- and virulence-related traits accelerating resistance breeding. Finally, joint, large-scale screenings of trait variation in crops and pathogens can yield fundamental insights into how pathogens face trade-offs in the adaptation to resistant crop varieties. We discuss how future implementations of such innovative approaches in breeding and pathogen screening can lead to more durable disease control.

Haplotypes-based genetic analysis: benefits and challenges

The increasing availability of Single Nucleotide Polymorphisms (SNPs) discovered by Next Generation Sequencing will enable a range of new genetic analyses in crops, which was not possible before. Concomitantly, researchers will face the challenge of handling large data sets at the whole-genome level. By grouping thousands of SNPs into a few hundred haplotype blocks, complexity of the data can be reduced with fewer statistical tests and a lower probability of spurious associations. Owing to the strong genome structure present in breeding lines of most crops, the deployment of haplotypes could be a powerful complement to improve efficiency of marker-assisted and genomic selection. This review describes in brief the commonly used approaches to construct haplotype blocks and some examples in animals and crops are cited where haplotype-based dissection of traits were proven beneficial. Some important considerations and facts while working with haplotypes in crops are reviewed at the end.

Inheritance of pre-emergent metribuzin tolerance and putative gene discovery through high-throughput SNP array in wheat (Triticum aestivum L.)

BACKGROUND

Herbicide tolerance is an important trait that allows effective weed management in wheat crops in dryland farming. Genetic knowledge of metribuzin tolerance in wheat is needed to develop new cultivars for the industry. Here, we investigated gene effects for metribuzin tolerance in nine crosses of wheat by partitioning the means and variances of six basic generations from each cross into their genetic components to assess the gene action governing the inheritance of this trait. Metribuzin tolerance was measured by a visual senescence score 21 days after treatment. The wheat 90 K iSelect SNP genotyping assay was used to identify the distribution of alleles at SNP sites in tolerant and susceptible groups.

RESULTS

The scaling and joint-scaling tests indicated that the inheritance of metribuzin tolerance in wheat was adequately described by the additive-dominance model, with additive gene action the most significant factor for tolerance. The potence ratio for all the crosses ranged between - 1 and + 1 for senescence under metribuzin-treated conditions indicating a semi-dominant gene action in the inheritance of metribuzin tolerance in wheat. The number of segregating genes governing metribuzin tolerance was estimated between 3 and 15. The consistent high heritability range (0.82 to 0.92) in F_5-7 generations of Chuan Mai 25 (tolerant) × Ritchie (susceptible) cross indicated a significant contribution of additive genetic effects to metribuzin tolerance in wheat. Several genes related to photosynthesis (e.g. photosynthesis system II assembly factor YCF48), metabolic detoxification of xenobiotics and cell growth and development (cytochrome P450, glutathione S-transferase, glycosyltransferase, ATP-binding cassette transporters and glutathione peroxidase) were identified on different chromosomes (2A, 2D, 3B, 4A, 4B, 7A, 7B, 7D) governing metribuzin tolerance.

CONCLUSIONS

The simple additive-dominance gene effects for metribuzin tolerance will help breeders to select tolerant lines in early generations and the identified genes may guide the development of functional markers for metribuzin tolerance.

RNAseq analysis reveals drought-responsive molecular pathways with candidate genes and putative molecular markers in root tissue of wheat

Drought is one of the major impediments in wheat productivity. Traditional breeding and marker assisted QTL introgression had limited success. Available wheat genomic and RNA-seq data can decipher novel drought tolerance mechanisms with putative candidate gene and marker discovery. Drought is first sensed by root tissue but limited information is available about how roots respond to drought stress. In this view, two contrasting genotypes, namely, NI5439 41 (drought tolerant) and WL711 (drought susceptible) were used to generate ~78.2 GB data for the responses of wheat roots to drought. A total of 45139 DEGs, 13820 TF, 288 miRNAs, 640 pathways and 435829 putative markers were obtained. Study reveals use of such data in QTL to QTN refinement by analysis on two model drought-responsive QTLs on chromosome 3B in wheat roots possessing 18 differentially regulated genes with 190 sequence variants (173 SNPs and 17 InDels). Gene regulatory networks showed 69 hub-genes integrating ABA dependent and independent pathways controlling sensing of drought, root growth, uptake regulation, purine metabolism, thiamine metabolism and antibiotics pathways, stomatal closure and senescence. Eleven SSR markers were validated in a panel of 18 diverse wheat varieties. For effective future use of findings, web genomic resources were developed. We report RNA-Seq approach on wheat roots describing the drought response mechanisms under field drought conditions along with genomic resources, warranted in endeavour of wheat productivity.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

Isolation and characterization of microsatellite loci for Rhododendron shanii (Ericaceae)

PREMISE OF THE STUDY

We developed microsatellite primers for Rhododendron shanii (Ericaceae), a narrowly distributed species found in the Dabie Mountains, China, to study the genetic diversity, population structure, and evolutionary history of the species.

METHODS AND RESULTS

Two terminal sequencing modes of the Illumina HiSeq platform were used to mine simple sequence repeat markers from large-scale transcriptional groups. In this study, 24 microsatellite loci were screened. The number of alleles ranged from one to 20, and the levels of observed and expected heterozygosity ranged from 0.000 to 1.000 and 0.000 to 0.918, respectively. Most of these primers were successfully amplified in eight congeneric species (R. annae, R. chihsinianum, R. decorum, R. denudatum, R. fortunei, R. neriiflorum, R. rex, and R. simiarum).

CONCLUSIONS

These newly developed microsatellite loci will be useful for studying the genetic diversity and population structure of R. shanii and congeneric species.

Resistance to Cereal Cyst Nematodes in Wheat and Barley: An Emphasis on Classical and Modern Approaches

Cereal cyst nematodes (CCNs) are among the most important nematode pests that limit production of small grain cereals like wheat and barley. These nematodes alone are estimated to reduce production of crops by 10% globally. This necessitates a huge enhancement of nematode resistance in cereal crops against CCNs. Nematode resistance in wheat and barley in combination with higher grain yields has been a preferential research area for cereal nematologists. This usually involved the targeted genetic exploitations through natural means of classical selection breeding of resistant genotypes and finding quantitative trait luci (QTLs) associated with resistance genes. These improvements were based on available genetic diversity among the crop plants. Recently, genome-wide association studies have widely been exploited to associate nematode resistance or susceptibility with particular regions of the genome. Use of biotechnological tools through the application of various transgenic strategies for enhancement of nematode resistance in various crop plants including wheat and barley had also been an important area of research. These modern approaches primarily include the use of gene silencing, exploitation of nematode effector genes, proteinase inhibitors, chemodisruptive peptides and a combination of one or more of these approaches. Furthermore, the perspective genome editing technologies including CRISPR-Cas9 could also be helpful for improving CCN resistance in wheat and barley. The information provided in this review will be helpful to enhance resistance against CCNs and will attract the attention of the scientific community towards this neglected area.

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.

A 55 K SNP array-based genetic map and its utilization in QTL mapping for productive tiller number in common wheat

A high-density genetic map constructed with a wheat 55 K SNP array was highly consistent with the physical map of this species and it facilitated the identification of a novel major QTL for productive tiller number. Productive tiller number (PTN) plays a key role in wheat grain yield. In this study, a recombinant inbred line population with 199 lines derived from a cross between '20828' and 'Chuannong16' was used to construct a high-density genetic map using wheat 55 K single nucleotide polymorphism (SNP) array. The constructed genetic map contains 12,109 SNP markers spanning 3021.04 cM across the 21 wheat chromosomes. The orders of the genetic and physical positions of these markers are generally in agreement, and they also match well with those based on the 660 K SNP array from which the one used in this study was derived. The ratios of SNPs located in each of the wheat deletion bins were similar among the wheat 9 K, 55 K, 90 K, 660 K and 820 K SNP arrays. Based on the constructed maps, a novel major quantitative trait locus QPtn.sau-4B for PTN was detected across multi-environments in a 0.55 cM interval on 4B and it explained 17.23-45.46% of the phenotypic variance. Twenty common genes in the physical interval between the flanking markers were identified on chromosome 4B of 'Chinese Spring' and wild emmer. These results indicate that wheat 55 K SNP array could be an ideal tool in primary mapping of target genes and the identification of QPtn.sau-4B laid a foundation for the following fine mapping and cloning work.

A Genome-wide View of Transcriptome Dynamics During Early Spike Development in Bread Wheat

Wheat spike development is a coordinated process of cell proliferation and differentiation with distinctive phases and architecture changes. However, the dynamic alteration of gene expression in this process remains enigmatic. Here, we characterized and dissected bread wheat spike into six developmental stages, and used genome-wide gene expression profiling, to investigate the underlying regulatory mechanisms. High gene expression correlations between any two given stages indicated that wheat early spike development is controlled by a small subset of genes. Throughout, auxin signaling increased, while cytokinin signaling decreased. Besides, many genes associated with stress responses highly expressed during the double ridge stage. Among the differentially expressed genes (DEGs), were identified 375 transcription factor (TF) genes, of which some homologs in rice or Arabidopsis are proposed to function in meristem maintenance, flowering time, meristem initiation or transition, floral organ development or response to stress. Gene expression profiling demonstrated that these genes had either similar or distinct expression pattern in wheat. Several genes regulating spike development were expressed in the early spike, of which Earliness per se 3 (Eps-3) was found might function in the initiation of spikelet meristem. Our study helps uncover important genes associated with apical meristem morphology and development in wheat.

Natural variation in genes potentially involved in plant architecture and adaptation in switchgrass (Panicum virgatum L.)

Background

Advances in genomic technologies have expanded our ability to accurately and exhaustively detect natural genomic variants that can be applied in crop improvement and to increase our knowledge of plant evolution and adaptation. Switchgrass (Panicum virgatum L.), an allotetraploid (2n = 4× = 36) perennial C4 grass (Poaceae family) native to North America and a feedstock crop for cellulosic biofuel production, has a large potential for genetic improvement due to its high genotypic and phenotypic variation. In this study, we analyzed single nucleotide polymorphism (SNP) variation in 372 switchgrass genotypes belonging to 36 accessions for 12 genes putatively involved in biomass production to investigate signatures of selection that could have led to ecotype differentiation and to population adaptation to geographic zones.

Results

A total of 11,682 SNPs were mined from ~ 15 Gb of sequence data, out of which 251 SNPs were retained after filtering. Population structure analysis largely grouped upland accessions into one subpopulation and lowland accessions into two additional subpopulations. The most frequent SNPs were in homozygous state within accessions. Sixty percent of the exonic SNPs were non-synonymous and, of these, 45% led to non-conservative amino acid changes. The non-conservative SNPs were largely in linkage disequilibrium with one haplotype being predominantly present in upland accessions while the other haplotype was commonly present in lowland accessions. Tajima’s test of neutrality indicated that PHYB, a gene involved in photoperiod response, was under positive selection in the switchgrass population. PHYB carried a SNP leading to a non-conservative amino acid change in the PAS domain, a region that acts as a sensor for light and oxygen in signal transduction.

Conclusions

Several non-conservative SNPs in genes potentially involved in plant architecture and adaptation have been identified and led to population structure and genetic differentiation of ecotypes in switchgrass. We suggest here that PHYB is a key gene involved in switchgrass natural selection. Further analyses are needed to determine whether any of the non-conservative SNPs identified play a role in the differential adaptation of upland and lowland switchgrass.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1193-2) contains supplementary material, which is available to authorized users.

Utilization of a Wheat660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number

In crop plants, a high-density genetic linkage map is essential for both genetic and genomic researches. The complexity and the large size of wheat genome have hampered the acquisition of a high-resolution genetic map. In this study, we report a high-density genetic map based on an individual mapping population using the Affymetrix Wheat660K single-nucleotide polymorphism (SNP) array as a probe in hexaploid wheat. The resultant genetic map consisted of 119 566 loci spanning 4424.4 cM, and 119 001 of those loci were SNP markers. This genetic map showed good collinearity with the 90 K and 820 K consensus genetic maps and was also in accordance with the recently released wheat whole genome assembly. The high-density wheat genetic map will provide a major resource for future genetic and genomic research in wheat. Moreover, a comparative genomics analysis among gramineous plant genomes was conducted based on the high-density wheat genetic map, providing an overview of the structural relationships among theses gramineous plant genomes. A major stable quantitative trait locus (QTL) for kernel number per spike was characterized, providing a solid foundation for the future high-resolution mapping and map-based cloning of the targeted QTL.

Utilization of a Wheat660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number

In crop plants, a high-density genetic linkage map is essential for both genetic and genomic researches. The complexity and the large size of wheat genome have hampered the acquisition of a high-resolution genetic map. In this study, we report a high-density genetic map based on an individual mapping population using the Affymetrix Wheat660K single-nucleotide polymorphism (SNP) array as a probe in hexaploid wheat. The resultant genetic map consisted of 119 566 loci spanning 4424.4 cM, and 119 001 of those loci were SNP markers. This genetic map showed good collinearity with the 90 K and 820 K consensus genetic maps and was also in accordance with the recently released wheat whole genome assembly. The high-density wheat genetic map will provide a major resource for future genetic and genomic research in wheat. Moreover, a comparative genomics analysis among gramineous plant genomes was conducted based on the high-density wheat genetic map, providing an overview of the structural relationships among theses gramineous plant genomes. A major stable quantitative trait locus (QTL) for kernel number per spike was characterized, providing a solid foundation for the future high-resolution mapping and map-based cloning of the targeted QTL.

Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions

This study determined the population structure and genome-wide marker-trait association of agronomic traits of wheat for drought-tolerance breeding. Ninety-three diverse bread wheat genotypes were genotyped using the Diversity Arrays Technology sequencing (DArTseq) protocol. The number of days-to-heading (DTH), number of days-to-maturity (DTM), plant height (PHT), spike length (SPL), number of kernels per spike (KPS), thousand kernel weight (TKW) and grain yield (GYLD), assessed under drought-stressed and non-stressed conditions, were considered for the study. Population structure analysis and genome-wide association mapping were undertaken based on 16,383 silico DArTs loci with < 10% missing data. The population evaluated was grouped into nine distinct genetic structures. Inter-chromosomal linkage disequilibrium showed the existence of linkage decay as physical distance increased. A total of 62 significant (P < 0.001) marker-trait associations (MTAs) were detected explaining more than 20% of the phenotypic variation observed under both drought-stressed and non-stressed conditions. Significant (P < 0.001) MTA event(s) were observed for DTH, PHT, SPL, SPS, and KPS; under both stressed and non-stressed conditions, while additional significant (P < 0.05) associations were observed for TKW, DTM and GYLD under non-stressed condition. The MTAs reported in this population could be useful to initiate marker-assisted selection (MAS) and targeted trait introgression of wheat under drought-stressed and non-stressed conditions, and for fine mapping and cloning of the underlying genes and QTL.

Overview of the Wheat Genetic Transformation and Breeding Status in China

In the past two decades, Chinese scientists have achieved significant progress on three aspects of wheat genetic transformation. First, the wheat transformation platform has been established and optimized to improve the transformation efficiency, shorten the time required from starting of transformation procedure to the fertile transgenic wheat plants obtained as well as to overcome the problem of genotype-dependent for wheat genetic transformation in wide range of wheat elite varieties. Second, with the help of many emerging techniques such as CRISPR/cas9 function of over 100 wheat genes has been investigated. Finally, modern technology has been combined with the traditional breeding technique such as crossing to accelerate the application of wheat transformation. Overall, the wheat end-use quality and the characteristics of wheat stress tolerance have been improved by wheat genetic engineering technique. So far, wheat transgenic lines integrated with quality-improved genes and stress tolerant genes have been on the way of Production Test stage in the field. The debates and the future studies on wheat transformation have been discussed, and the brief summary of Chinese wheat breeding research history has also been provided in this review.

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.

Identifying wrong assemblies in de novo short read primary sequence assembly contigs

With the advent of short-reads-based genome sequencing approaches, large number of organisms are being sequenced all over the world. Most of these assemblies are done using some de novo short read assemblers and other related approaches. However, the contigs produced this way are prone to wrong assembly. So far, there is a conspicuous dearth of reliable tools to identify mis-assembled contigs. Mis-assemblies could result from incorrectly deleted or wrongly arranged genomic sequences. In the present work various factors related to sequence, sequencing and assembling have been assessed for their role in causing mis-assembly by using different genome sequencing data. Finally, some mis-assembly detecting tools have been evaluated for their ability to detect the wrongly assembled primary contigs, suggesting a lot of scope for improvement in this area. The present work also proposes a simple unsupervised learning-based novel approach to identify mis-assemblies in the contigs which was found performing reasonably well when compared to the already existing tools to report mis-assembled contigs. It was observed that the proposed methodology may work as a complementary system to the existing tools to enhance their accuracy.

Seed coating with arbuscular mycorrhizal fungi as an ecotechnologicalapproach for sustainable agricultural production of common wheat (Triticum aestivum L.)

The exploitation of arbuscular mycorrhizal (AM) fungi has become of great interest in agriculture due to their potential roles in reducing the need for agrochemicals, while improving plant growth and nutrition. Nevertheless, the application of AM fungi by dispersing inocula in granular form to open agricultural fields is not feasible because nontargeted spreading of inocula over large surface areas results in high cost per plant. Seed coating has the potential to significantly reduce the amount of inoculum needed, resulting in cost reduction and increased efficiency. The aim of this study was to assess whether seed coating with AM fungal inoculum is a feasible delivery system for production of common wheat (Triticum aestivum L.). Wheat seeds were coated with inoculum of Rhizophagus irregularis BEG140 and grown under different fertilization conditions: (1) none, (2) partial, or (3) complete. Data indicated that mycorrhizal inoculation via seed coating significantly increased the dry weight of shoot and seed spikes of wheat associated with reduced fertilization. Assessment of nutritional status of wheat showed that plants inoculated with R. irregularis via seed coating displayed enhanced stem concentrations of potassium (K), sulfur (S), and zinc (Zn). There were no significant differences in root colonization between plants conventionally inoculated with R. irregularis in soil and those inoculated via seed coating. Seed coating with AM fungi may be as effective as conventional soil inoculation and may contribute to reduce the utilization of chemical fertilizers. The application of AM via seed coating is proposed as an ecotechnological approach for sustainable agricultural wheat production.

OryzaGenome: Genome Diversity Database of Wild Oryza Species

The species in the genus Oryza, encompassing nine genome types and 23 species, are a rich genetic resource and may have applications in deeper genomic analyses aiming to understand the evolution of plant genomes. With the advancement of next-generation sequencing (NGS) technology, a flood of Oryza species reference genomes and genomic variation information has become available in recent years. This genomic information, combined with the comprehensive phenotypic information that we are accumulating in our Oryzabase, can serve as an excellent genotype-phenotype association resource for analyzing rice functional and structural evolution, and the associated diversity of the Oryza genus. Here we integrate our previous and future phenotypic/habitat information and newly determined genotype information into a united repository, named OryzaGenome, providing the variant information with hyperlinks to Oryzabase. The current version of OryzaGenome includes genotype information of 446 O. rufipogon accessions derived by imputation and of 17 accessions derived by imputation-free deep sequencing. Two variant viewers are implemented: SNP Viewer as a conventional genome browser interface and Variant Table as a text-based browser for precise inspection of each variant one by one. Portable VCF (variant call format) file or tab-delimited file download is also available. Following these SNP (single nucleotide polymorphism) data, reference pseudomolecules/scaffolds/contigs and genome-wide variation information for almost all of the closely and distantly related wild Oryza species from the NIG Wild Rice Collection will be available in future releases. All of the resources can be accessed through http://viewer.shigen.info/oryzagenome/.

Potential for Genetic Improvement of Sugarcane as a Source of Biomass for Biofuels

Sugarcane (Saccharum spp. hybrids) has great potential as a major feedstock for biofuel production worldwide. It is considered among the best options for producing biofuels today due to an exceptional biomass production capacity, high carbohydrate (sugar + fiber) content, and a favorable energy input/output ratio. To maximize the conversion of sugarcane biomass into biofuels, it is imperative to generate improved sugarcane varieties with better biomass degradability. However, unlike many diploid plants, where genetic tools are well developed, biotechnological improvement is hindered in sugarcane by our current limited understanding of the large and complex genome. Therefore, understanding the genetics of the key biofuel traits in sugarcane and optimization of sugarcane biomass composition will advance efficient conversion of sugarcane biomass into fermentable sugars for biofuel production. The large existing phenotypic variation in Saccharum germplasm and the availability of the current genomics technologies will allow biofuel traits to be characterized, the genetic basis of critical differences in biomass composition to be determined, and targets for improvement of sugarcane for biofuels to be established. Emerging options for genetic improvement of sugarcane for the use as a bioenergy crop are reviewed. This will better define the targets for potential genetic manipulation of sugarcane biomass composition for biofuels.

Application of Population Sequencing (POPSEQ) for Ordering and Imputing Genotyping-by-Sequencing Markers in Hexaploid Wheat

The advancement of next-generation sequencing technologies in conjunction with new bioinformatics tools enabled fine-tuning of sequence-based, high-resolution mapping strategies for complex genomes. Although genotyping-by-sequencing (GBS) provides a large number of markers, its application for association mapping and genomics-assisted breeding is limited by a large proportion of missing data per marker. For species with a reference genomic sequence, markers can be ordered on the physical map. However, in the absence of reference marker order, the use and imputation of GBS markers is challenging. Here, we demonstrate how the population sequencing (POPSEQ) approach can be used to provide marker context for GBS in wheat. The utility of a POPSEQ-based genetic map as a reference map to create genetically ordered markers on a chromosome for hexaploid wheat was validated by constructing an independent de novo linkage map of GBS markers from a Synthetic W7984 × Opata M85 recombinant inbred line (SynOpRIL) population. The results indicated that there is strong agreement between the independent de novo linkage map and the POPSEQ mapping approach in mapping and ordering GBS markers for hexaploid wheat. After ordering, a large number of GBS markers were imputed, thus providing a high-quality reference map that can be used for QTL mapping for different traits. The POPSEQ-based reference map and whole-genome sequence assemblies are valuable resources that can be used to order GBS markers and enable the application of highly accurate imputation methods to leverage the application GBS markers in wheat.

Exploring the tertiary gene pool of bread wheat: sequence assembly and analysis of chromosome 5M(g) of Aegilops geniculata

Next-generation sequencing (NGS) provides a powerful tool for the discovery of important genes and alleles in crop plants and their wild relatives. Despite great advances in NGS technologies, whole-genome shotgun sequencing is cost-prohibitive for species with complex genomes. An attractive option is to reduce genome complexity to a single chromosome prior to sequencing. This work describes a strategy for studying the genomes of distant wild relatives of wheat by isolating single chromosomes from addition or substitution lines, followed by chromosome sorting using flow cytometry and sequencing of chromosomal DNA by NGS technology. We flow-sorted chromosome 5M(g) from a wheat/Aegilops geniculata disomic substitution line [DS5M(g) (5D)] and sequenced it using an Illumina HiSeq 2000 system at approximately 50 × coverage. Paired-end sequences were assembled and used for structural and functional annotation. A total of 4236 genes were annotated on 5M(g) , in close agreement with the predicted number of genes on wheat chromosome 5D (4286). Single-gene FISH indicated no major chromosomal rearrangements between chromosomes 5M(g) and 5D. Comparing chromosome 5M(g) with model grass genomes identified synteny blocks in Brachypodium distachyon, rice (Oryza sativa), sorghum (Sorghum bicolor) and barley (Hordeum vulgare). Chromosome 5M(g) -specific SNPs and cytogenetic probe-based resources were developed and validated. Deletion bin-mapped and ordered 5M(g) SNP markers will be useful to track 5M-specific introgressions and translocations. This study provides a detailed sequence-based analysis of the composition of a chromosome from a distant wild relative of bread wheat, and opens up opportunities to develop genomic resources for wild germplasm to facilitate crop improvement.

Recent trends and perspectives of molecular markers against fungal diseases in wheat

Wheat accounts for 19% of the total production of major cereal crops in the world. In view of ever increasing population and demand for global food production, there is an imperative need of 40-60% increase in wheat production to meet the requirement of developing world in coming 40 years. However, both biotic and abiotic stresses are major hurdles for attaining the goal. Among the most important diseases in wheat, fungal diseases pose serious threat for widening the gap between actual and attainable yield. Fungal disease management, mainly, depends on the pathogen detection, genetic and pathological variability in population, development of resistant cultivars and deployment of effective resistant genes in different epidemiological regions. Wheat protection and breeding of resistant cultivars using conventional methods are time-consuming, intricate and slow processes. Molecular markers offer an excellent alternative in development of improved disease resistant cultivars that would lead to increase in crop yield. They are employed for tagging the important disease resistance genes and provide valuable assistance in increasing selection efficiency for valuable traits via marker assisted selection (MAS). Plant breeding strategies with known molecular markers for resistance and functional genomics enable a breeder for developing resistant cultivars of wheat against different fungal diseases.

Image-based phenotyping of plant disease symptoms

Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in the host. A variety of quantitative high-throughput image-based methods for phenotyping plant growth and development are currently being developed. These methods range from detailed analysis of a single plant over time to broad assessment of the crop canopy for thousands of plants in a field and employ a wide variety of imaging technologies. Application of these methods to the study of plant disease offers the ability to study quantitatively how host physiology is altered by pathogen infection. These approaches have the potential to provide insight into the physiological mechanisms underlying disease symptom development. Furthermore, imaging techniques that detect the electromagnetic spectrum outside of visible light allow us to quantify disease symptoms that are not visible by eye, increasing the range of symptoms we can observe and potentially allowing for earlier and more thorough symptom detection. In this review, we summarize current progress in plant disease phenotyping and suggest future directions that will accelerate the development of resistant crop varieties.

Skim-based genotyping by sequencing

Genotyping by sequencing (GBS) is a relatively new method used to determine the differences in the genetic makeup of individuals. Its novelty stems from a combination of two already available methods: genotyping and next-generation sequencing. Depending on the individual study design GBS protocols can take multiple forms, however most share a sequence of core steps that have to be undertaken. These include: sequencing of the DNA from the individuals of interest (usually two parents of a mapping population and their progeny), mapping of the sequencing reads to the reference sequence, SNP calling and filtering, SNP genotyping and imputation, followed by haplotype identification and downstream analysis. GBS has a range of applications from general marker discovery, haplotype identification, and recombination characterization to quantitative trait locus (QTL) analysis, genome-wide association studies (GWAS), and genomic selection (GS). It has already been applied to a range of plant species including: rice, maize, artichoke, and Arabidopsis thaliana. It is a promising approach which is likely to provide new and important insights into plant biology.

Bioinformatics: identification of markers from next-generation sequence data

With the advent of sequencing technology, next-generation sequencing (NGS) technology has dramatically revolutionized plant genomics. NGS technology combined with new software tools enables the discovery, validation, and assessment of genetic markers on a large scale. Among different markers systems, simple sequence repeats (SSRs) and Single nucleotide polymorphisms (SNPs) are the markers of choice for genetics and plant breeding. SSR markers have been a choice for large-scale characterization of germplasm collections, construction of genetic maps, and QTL identification. Similarly, SNPs are the most abundant genetic variations with higher frequencies throughout the genome of plant species. This chapter discusses various tools available for genome assembly and widely focuses on SSR and SNP marker discovery.

Molecular marker applications in plants

Individuals within a population of a sexually reproducing species will have some degree of heritable genomic variation caused by mutations, insertion/deletions (INDELS), inversions, duplications, and translocations. Such variation can be detected and screened using molecular, or genetic, markers. By definition, molecular markers are genetic loci that can be easily tracked and quantified in a population and may be associated with a particular gene or trait of interest. This chapter will review the current major applications of molecular markers in plants.

Application of next-generation sequencing technology to study genetic diversity and identify unique SNP markers in bread wheat from Kazakhstan

BACKGROUND

New SNP marker platforms offer the opportunity to investigate the relationships between wheat cultivars from different regions and assess the mechanism and processes that have led to adaptation to particular production environments. Wheat breeding has a long history in Kazakhstan and the aim of this study was to explore the relationship between key varieties from Kazakhstan and germplasm from breeding programs for other regions.

RESULTS

The study revealed 5,898 polymorphic markers amongst ten cultivars, of which 2,730 were mapped in the consensus genetic map. Mapped SNP markers were distributed almost equally across the A and B genomes, with between 279 and 484 markers assigned to each chromosome. Marker coverage was approximately 10-fold lower in the D genome. There were 863 SNP markers identified as unique to specific cultivars, and clusters of these markers (regions containing more than three closely mapped unique SNPs) showed specific patterns on the consensus genetic map for each cultivar. Significant intra-varietal genetic polymorphism was identified in three cultivars (Tzelinnaya 3C, Kazakhstanskaya rannespelaya and Kazakhstanskaya 15). Phylogenetic analysis based on inter-varietal polymorphism showed that the very old cultivar Erythrospermum 841 was the most genetically distinct from the other nine cultivars from Kazakhstan, falling in a clade together with the American cultivar Sonora and genotypes from Central and South Asia. The modern cultivar Kazakhstanskaya 19 also fell into a separate clade, together with the American cultivar Thatcher. The remaining eight cultivars shared a single sub-clade but were categorised into four clusters.

CONCLUSION

The accumulated data for SNP marker polymorphisms amongst bread wheat genotypes from Kazakhstan may be used for studying genetic diversity in bread wheat, with potential application for marker-assisted selection and the preparation of a set of genotype-specific markers.

A chromosomal genomics approach to assess and validate the desi and kabuli draft chickpea genome assemblies

With the expansion of next-generation sequencing technology and advanced bioinformatics, there has been a rapid growth of genome sequencing projects. However, while this technology enables the rapid and cost-effective assembly of draft genomes, the quality of these assemblies usually falls short of gold standard genome assemblies produced using the more traditional BAC by BAC and Sanger sequencing approaches. Assembly validation is often performed by the physical anchoring of genetically mapped markers, but this is prone to errors and the resolution is usually low, especially towards centromeric regions where recombination is limited. New approaches are required to validate reference genome assemblies. The ability to isolate individual chromosomes combined with next-generation sequencing permits the validation of genome assemblies at the chromosome level. We demonstrate this approach by the assessment of the recently published chickpea kabuli and desi genomes. While previous genetic analysis suggests that these genomes should be very similar, a comparison of their chromosome sizes and published assemblies highlights significant differences. Our chromosomal genomics analysis highlights short defined regions that appear to have been misassembled in the kabuli genome and identifies large-scale misassembly in the draft desi genome. The integration of chromosomal genomics tools within genome sequencing projects has the potential to significantly improve the construction and validation of genome assemblies. The approach could be applied both for new genome assemblies as well as published assemblies, and complements currently applied genome assembly strategies.

Structural variations in plant genomes

Differences between plant genomes range from single nucleotide polymorphisms to large-scale duplications, deletions and rearrangements. The large polymorphisms are termed structural variants (SVs). SVs have received significant attention in human genetics and were found to be responsible for various chronic diseases. However, little effort has been directed towards understanding the role of SVs in plants. Many recent advances in plant genetics have resulted from improvements in high-resolution technologies for measuring SVs, including microarray-based techniques, and more recently, high-throughput DNA sequencing. In this review we describe recent reports of SV in plants and describe the genomic technologies currently used to measure these SVs.

SNP Discovery for mapping alien introgressions in wheat

Background

Monitoring alien introgressions in crop plants is difficult due to the lack of genetic and molecular mapping information on the wild crop relatives. The tertiary gene pool of wheat is a very important source of genetic variability for wheat improvement against biotic and abiotic stresses. By exploring the 5M^g short arm (5M^gS) of Aegilops geniculata, we can apply chromosome genomics for the discovery of SNP markers and their use for monitoring alien introgressions in wheat (Triticum aestivum L).

Results

The short arm of chromosome 5M^g of Ae. geniculata Roth (syn. Ae. ovata L.; 2n = 4x = 28, U^gU^gM^gM^g) was flow-sorted from a wheat line in which it is maintained as a telocentric chromosome. DNA of the sorted arm was amplified and sequenced using an Illumina Hiseq 2000 with ~45x coverage. The sequence data was used for SNP discovery against wheat homoeologous group-5 assemblies. A total of 2,178 unique, 5M^gS-specific SNPs were discovered. Randomly selected samples of 59 5M^gS-specific SNPs were tested (44 by KASPar assay and 15 by Sanger sequencing) and 84% were validated. Of the selected SNPs, 97% mapped to a chromosome 5M^g addition to wheat (the source of t5M^gS), and 94% to 5M^g introgressed from a different accession of Ae. geniculata substituting for chromosome 5D of wheat. The validated SNPs also identified chromosome segments of 5M^gS origin in a set of T5D-5M^g translocation lines; eight SNPs (25%) mapped to TA5601 [T5DL · 5DS-5M^gS(0.75)] and three (8%) to TA5602 [T5DL · 5DS-5M^gS (0.95)]. SNPs (gsnp_5ms83 and gsnp_5ms94), tagging chromosome T5DL · 5DS-5M^gS(0.95) with the smallest introgression carrying resistance to leaf rust (Lr57) and stripe rust (Yr40), were validated in two released germplasm lines with Lr57 and Yr40 genes.

Conclusion

This approach should be widely applicable for the identification of species/genome-specific SNPs. The development of a large number of SNP markers will facilitate the precise introgression and monitoring of alien segments in crop breeding programs and further enable mapping and cloning novel genes from the wild relatives of crop plants.

New technologies for ultrahigh-throughput genotyping in plant taxonomy

Molecular genetic markers represent one of the most powerful tools for the analysis of variation between plant genomes. Molecular marker technology has developed rapidly over the last decade, with the introduction of new DNA sequencing methods and the development of high-throughput genotyping methods. Single nucleotide polymorphisms (SNPs) now dominate applications in modern plant genetic analysis. The reducing cost of DNA sequencing and increasing availability of large sequence data sets permit the mining of this data for large numbers of SNPs. These may then be used in applications such as genetic linkage analysis and trait mapping, diversity analysis, association studies, and marker-assisted selection. Here we describe automated methods for the discovery of SNP molecular markers and new technologies for high-throughput, low-cost molecular marker genotyping. Examples include SNP discovery using autoSNPdb and wheatgenome.info as well as SNP genotyping using Illumina's GoldenGate™ and Infinium™ methods.

Applications and challenges of next-generation sequencing in Brassica species

Next-generation sequencing (NGS) produces numerous (often millions) short DNA sequence reads, typically varying between 25 and 400 bp in length, at a relatively low cost and in a short time. This revolutionary technology is being increasingly applied in whole-genome, transcriptome, epigenome and small RNA sequencing, molecular marker and gene discovery, comparative and evolutionary genomics, and association studies. The Brassica genus comprises some of the most agro-economically important crops, providing abundant vegetables, condiments, fodder, oil and medicinal products. Many Brassica species have undergone the process of polyploidization, which makes their genomes exceptionally complex and can create difficulties in genomics research. NGS injects new vigor into Brassica research, yet also faces specific challenges in the analysis of complex crop genomes and traits. In this article, we review the advantages and limitations of different NGS technologies and their applications and challenges, using Brassica as an advanced model system for agronomically important, polyploid crops. Specifically, we focus on the use of NGS for genome resequencing, transcriptome sequencing, development of single-nucleotide polymorphism markers, and identification of novel microRNAs and their targets. We present trends and advances in NGS technology in relation to Brassica crop improvement, with wide application for sophisticated genomics research into agronomically important polyploid crops.

Next generation characterisation of cereal genomes for marker discovery

Cereal crops form the bulk of the world’s food sources, and thus their importance cannot be understated. Crop breeding programs increasingly rely on high-resolution molecular genetic markers to accelerate the breeding process. The development of these markers is hampered by the complexity of some of the major cereal crop genomes, as well as the time and cost required. In this review, we address current and future methods available for the characterisation of cereal genomes, with an emphasis on faster and more cost effective approaches for genome sequencing and the development of markers for trait association and marker assisted selection (MAS) in crop breeding programs.

Syntenic relationships between the U and M genomes of Aegilops, wheat and the model species Brachypodium and rice as revealed by COS markers

Diploid Aegilops umbellulata and Ae. comosa and their natural allotetraploid hybrids Ae. biuncialis and Ae. geniculata are important wild gene sources for wheat. With the aim of assisting in alien gene transfer, this study provides gene-based conserved orthologous set (COS) markers for the U and M genome chromosomes. Out of the 140 markers tested on a series of wheat-Aegilops chromosome introgression lines and flow-sorted subgenomic chromosome fractions, 100 were assigned to Aegilops chromosomes and six and seven duplications were identified in the U and M genomes, respectively. The marker-specific EST sequences were BLAST-ed to Brachypodium and rice genomic sequences to investigate macrosyntenic relationships between the U and M genomes of Aegilops, wheat and the model species. Five syntenic regions of Brachypodium identified genome rearrangements differentiating the U genome from the M genome and from the D genome of wheat. All of them seem to have evolved at the diploid level and to have been modified differentially in the polyploid species Ae. biuncialis and Ae. geniculata. A certain level of wheat-Aegilops homology was detected for group 1, 2, 3 and 5 chromosomes, while a clearly rearranged structure was showed for the group 4, 6 and 7 Aegilops chromosomes relative to wheat. The conserved orthologous set markers assigned to Aegilops chromosomes promise to accelerate gene introgression by facilitating the identification of alien chromatin. The syntenic relationships between the Aegilops species, wheat and model species will facilitate the targeted development of new markers specific for U and M genomic regions and will contribute to the understanding of molecular processes related to allopolyploidization.

Discovery and development of exome-based, co-dominant single nucleotide polymorphism markers in hexaploid wheat (Triticum aestivum L.)

Globally, wheat is the most widely grown crop and one of the three most important crops for human and livestock feed. However, the complex nature of the wheat genome has, until recently, resulted in a lack of single nucleotide polymorphism (SNP)-based molecular markers of practical use to wheat breeders. Recently, large numbers of SNP-based wheat markers have been made available via the use of next-generation sequencing combined with a variety of genotyping platforms. However, many of these markers and platforms have difficulty distinguishing between heterozygote and homozygote individuals and are therefore of limited use to wheat breeders carrying out commercial-scale breeding programmes. To identify exome-based co-dominant SNP-based assays, which are capable of distinguishing between heterozygotes and homozygotes, we have used targeted re-sequencing of the wheat exome to generate large amounts of genomic sequences from eight varieties. Using a bioinformatics approach, these sequences have been used to identify 95 266 putative single nucleotide polymorphisms, of which 10 251 were classified as being putatively co-dominant. Validation of a subset of these putative co-dominant markers confirmed that 96% were true polymorphisms and 65% were co-dominant SNP assays. The new co-dominant markers described here are capable of genotypic classification of a segregating locus in polyploid wheat and can be used on a variety of genotyping platforms; as such, they represent a powerful tool for wheat breeders. These markers and related information have been made publically available on an interactive web-based database to facilitate their use on genotyping programmes worldwide.

Predicting polymorphic EST-SSRs in silico

The public availability of large quantities of gene sequence data provides a valuable resource of the mining of Simple Sequence Repeat (SSR) molecular genetic markers for genetic analysis. These markers are inexpensive, require minimal labour to produce and can frequently be associated with functionally annotated genes. This study presents the characterization of barley EST-SSRs and the identification of putative polymorphic SSRs from EST data. Polymorphic SSRs are distinguished from monomorphic SSRs by the representation of varying motif lengths within an alignment of sequence reads. Two measures of confidence are calculated, redundancy of a polymorphism and co-segregation with accessions. The utility of this method is demonstrated through the discovery of 597 candidate polymorphic SSRs, from a total of 452 642 consensus expressed sequences. PCR amplification primers were designed for the identified SSRs. Ten primer pairs were validated for polymorphism in barley and for transferability across species. Analysis of the polymorphisms in relation to SSR motif, length, position and annotation is discussed.

Accessing complex crop genomes with next-generation sequencing

Many important crop species have genomes originating from ancestral or recent polyploidisation events. Multiple homoeologous gene copies, chromosomal rearrangements and amplification of repetitive DNA within large and complex crop genomes can considerably complicate genome analysis and gene discovery by conventional, forward genetics approaches. On the other hand, ongoing technological advances in molecular genetics and genomics today offer unprecedented opportunities to analyse and access even more recalcitrant genomes. In this review, we describe next-generation sequencing and data analysis techniques that vastly improve our ability to dissect and mine genomes for causal genes underlying key traits and allelic variation of interest to breeders. We focus primarily on wheat and oilseed rape, two leading examples of major polyploid crop genomes whose size or complexity present different, significant challenges. In both cases, the latest DNA sequencing technologies, applied using quite different approaches, have enabled considerable progress towards unravelling the respective genomes. Our ability to discover the extent and distribution of genetic diversity in crop gene pools, and its relationship to yield and quality-related traits, is swiftly gathering momentum as DNA sequencing and the bioinformatic tools to deal with growing quantities of genomic data continue to develop. In the coming decade, genomic and transcriptomic sequencing, discovery and high-throughput screening of single nucleotide polymorphisms, presence-absence variations and other structural chromosomal variants in diverse germplasm collections will give detailed insight into the origins, domestication and available trait-relevant variation of polyploid crops, in the process facilitating novel approaches and possibilities for genomics-assisted breeding.

Evolutionary dynamics of retrotransposons assessed by high-throughput sequencing in wild relatives of wheat

Transposable elements (TEs) represent a major fraction of plant genomes and drive their evolution. An improved understanding of genome evolution requires the dynamics of a large number of TE families to be considered. We put forward an approach bypassing the required step of a complete reference genome to assess the evolutionary trajectories of high copy number TE families from genome snapshot with high-throughput sequencing. Low coverage sequencing of the complex genomes of Aegilops cylindrica and Ae. geniculata using 454 identified more than 70% of the sequences as known TEs, mainly long terminal repeat (LTR) retrotransposons. Comparing the abundance of reads as well as patterns of sequence diversity and divergence within and among genomes assessed the dynamics of 44 major LTR retrotransposon families of the 165 identified. In particular, molecular population genetics on individual TE copies distinguished recently active from quiescent families and highlighted different evolutionary trajectories of retrotransposons among related species. This work presents a suite of tools suitable for current sequencing data, allowing to address the genome-wide evolutionary dynamics of TEs at the family level and advancing our understanding of the evolution of nonmodel genomes.

CerealsDB 2.0: an integrated resource for plant breeders and scientists

BACKGROUND

Food security is an issue that has come under renewed scrutiny amidst concerns that substantial yield increases in cereal crops are required to feed the world's booming population. Wheat is of fundamental importance in this regard being one of the three most important crops for both human consumption and livestock feed; however, increase in crop yields have not kept pace with the demands of a growing world population. In order to address this issue, plant breeders require new molecular tools to help them identify genes for important agronomic traits that can be introduced into elite varieties. Studies of the genome using next-generation sequencing enable the identification of molecular markers such as single nucleotide polymorphisms that may be used by breeders to identify and follow genes when breeding new varieties. The development and application of next-generation sequencing technologies has made the characterisation of SNP markers in wheat relatively cheap and straightforward. There is a growing need for the widespread dissemination of this information to plant breeders.

DESCRIPTION

CerealsDB is an online resource containing a range of genomic datasets for wheat (Triticum aestivum) that will assist plant breeders and scientists to select the most appropriate markers for marker assisted selection. CerealsDB includes a database which currently contains in excess of 100,000 putative varietal SNPs, of which several thousand have been experimentally validated. In addition, CerealsDB contains databases for DArT markers and EST sequences, and links to a draft genome sequence for the wheat variety Chinese Spring.

CONCLUSION

CerealsDB is an open access website that is rapidly becoming an invaluable resource within the wheat research and plant breeding communities.