GrainGenes: a data-rich repository for small grains genetics and genomics

On the evolution and genetic diversity of the bread wheat D genome

Bread wheat (Triticum aestivum) became a globally dominant crop after incorporating the D genome from the donor species Aegilops tauschii, but the evolutionary history that shaped the D genome during this process remains to be clarified. Here, we propose a renewed evolutionary model linking Ae. tauschii and the hexaploid wheat D genome by constructing an ancestral haplotype map covering 762 Ae. tauschii and hexaploid wheat accessions. We dissected the evolutionary trajectories of Ae. tauschii lineages and reported a few independent intermediate accessions, demonstrating that low-frequency inter-sublineage gene flow had enriched the diversity of Ae. tauschii. We discovered that the D genome of hexaploid wheat was inherited from a unified ancestral template, but with a mosaic composition that was highly mixed and derived mainly from three Ae. tauschii L2 sublineages located in the Caspian coastal region. This result suggests that early agricultural activities facilitated innovations in D-genome composition and finalized the success of hexaploidization. We found that the majority (51.4%) of genetic diversity was attributed to novel mutations absent in Ae. tauschii, and we identified large Ae. tauschii introgressions from various lineages, which expanded the diversity of the wheat D genome and introduced beneficial alleles. This work sheds light on the process of wheat hexaploidization and highlights the evolutionary significance of the multi-layered genetic diversity of the bread wheat D genome.

An island of receptor-like genes at the Rrs13 locus on barley chromosome 6HS co-locate with three novel sources of scald resistance

Three Hordeum spontaneum-derived resistances (referred to as 145L2, 41T1 and 40Y5) have demonstrated long-term effectiveness against barley scald, caused by Rhynchosporium commune, in western Canada. Genetic mapping of these resistances in three populations, and the use of five barley genome assemblies, revealed they co-located to a narrowly defined 0.58-1.2 Mbp region of chromosome 6HS containing the Rrs13 scald resistance gene. Differential disease reactions among the three resistances and a Rrs13 carrier (AB6) to a panel of 24 scald isolates indicated that the four resistances were unique from one another. A marker created to target the 6HS scald locus was screened across a panel of barley germplasm that included H. vulgare, H. spontaneum and H. bulbosum lines. The marker showed specificity to H. vulgare lines known to carry the 6HS scald resistances and to two H. spontaneum lines that trace their origins to Jordan. Within the 0.58-1.2 Mbp region were 2-7 tandemly repeated leucine-rich repeat receptor-like proteins (LRR-RLP) and one lectin receptor-like kinase (Lec-RLK) genes with abundant sequence variation between them. The well-defined role that RLP and RLK genes play in plant defense responses make them logical candidate resistance genes, with one possible hypothesis being that each unique scald resistance may be encoded by a different RLP that interacts with a common RLK. It is suggested the three scald resistances be temporarily named Rrs13145L2, Rrs1341T1 and Rrs1340Y5 to recognize their co-location to the Rrs13 locus until it is determined whether these resistances represent unique genes or alleles of the same gene.

Identification of Genomic Regions Conferring Enhanced Zn and Fe Concentration in Wheat Varieties and Introgression Lines Derived from Wild Relatives

Wild and cultivated relatives of wheat are an important source of genetic factors for improving the mineral composition of wheat. In this work, a wheat panel consisting of modern bread wheat varieties, landraces, and introgression lines with genetic material of the wheat species Triticum timopheevii, T. durum, T. dicoccum, and T. dicoccoides and the synthetic line T. kiharae was used to identify loci associated with the grain zinc (GZnC) and iron (GFeC) content. Using a BLINK model, we identified 31 and 73 marker-trait associations (MTAs) for GZnC and GFeC, respectively, of which 19 were novel. Twelve MTAs distributed on chromosomes 1B, 2A, 2B, 5A, and 5B were significantly associated with GZnC, five MTAs on 2A, 2B, and 5D chromosomes were significantly associated with GFeC, and two SNPs located on 2A and 2B were related to the grain concentration of both trace elements. Meanwhile, most of these MTAs were inherited from At and G genomes of T. timopheevii and T. kiharae and positively affected GZnC and GFeC. Eight genes related to iron or zinc transporters, representing diverse gene families, were proposed as the best candidates. Our findings provide an understanding of the genetic basis of grain Zn and Fe accumulation in species of the Timopheevi group and could help in selecting new genotypes containing valuable loci.

​Fusarium Protein Toolkit: a web-based resource for structural and variant analysis of Fusarium species

BACKGROUND

​​The genus Fusarium poses significant threats to food security and safety worldwide because numerous species of the fungus cause destructive diseases and/or mycotoxin contamination in crops. The adverse effects of climate change are exacerbating some existing threats and causing new problems. These challenges highlight the need for innovative solutions, including the development of advanced tools to identify targets for control strategies.

DESCRIPTION

In response to these challenges, we developed the Fusarium Protein Toolkit (FPT), a web-based tool that allows users to interrogate the structural and variant landscape within the Fusarium pan-genome. The tool displays both AlphaFold and ESMFold-generated protein structure models from six Fusarium species. The structures are accessible through a user-friendly web portal and facilitate comparative analysis, functional annotation inference, and identification of related protein structures. Using a protein language model, FPT predicts the impact of over 270 million coding variants in two of the most agriculturally important species, Fusarium graminearum and F. verticillioides. To facilitate the assessment of naturally occurring genetic variation, FPT provides variant effect scores for proteins in a Fusarium pan-genome based on 22 diverse species. The scores indicate potential functional consequences of amino acid substitutions and are displayed as intuitive heatmaps using the PanEffect framework.

CONCLUSION

FPT fills a knowledge gap by providing previously unavailable tools to assess structural and missense variation in proteins produced by Fusarium. FPT has the potential to deepen our understanding of pathogenic mechanisms in Fusarium, and aid the identification of genetic targets for control strategies that reduce crop diseases and mycotoxin contamination. Such targets are vital to solving the agricultural problems incited by Fusarium, particularly evolving threats resulting from climate change. Thus, FPT has the potential to contribute to improving food security and safety worldwide.

Exploring Evolutionary Pathways and Abiotic Stress Responses through Genome-Wide Identification and Analysis of the Alternative Oxidase (AOX) Gene Family in Common Oat (Avena sativa)

The alternative oxidase (AOX), a common terminal oxidase in the electron transfer chain (ETC) of plants, plays a crucial role in stress resilience and plant growth and development. Oat (Avena sativa), an important crop with high nutritional value, has not been comprehensively studied regarding the AsAOX gene family. Therefore, this study explored the responses and potential functions of the AsAOX gene family to various abiotic stresses and their potential evolutionary pathways. Additionally, we conducted a genome-wide analysis to explore the evolutionary conservation and divergence of AOX gene families among three Avena species (Avena sativa, Avena insularis, Avena longiglumis) and four Poaceae species (Avena sativa, Oryza sativa, Triticum aestivum, and Brachypodium distachyon). We identified 12 AsAOX, 9 AiAOX, and 4 AlAOX gene family members. Phylogenetic, motif, domain, gene structure, and selective pressure analyses revealed that most AsAOXs, AiAOXs, and AlAOXs are evolutionarily conserved. We also identified 16 AsAOX segmental duplication pairs, suggesting that segmental duplication may have contributed to the expansion of the AsAOX gene family, potentially preserving these genes through subfunctionalization. Chromosome polyploidization, gene structural variations, and gene fragment recombination likely contributed to the evolution and expansion of the AsAOX gene family as well. Additionally, we hypothesize that AsAOX2 may have potential function in resisting wounding and heat stresses, while AsAOX4 could be specifically involved in mitigating wounding stress. AsAOX11 might contribute to resistance against chromium and waterlogging stresses. AsAOX8 may have potential fuction in mitigating ABA-mediated stress. AsAOX12 and AsAOX5 are most likely to have potential function in mitigating salt and drought stresses, respectively. This study elucidates the potential evolutionary pathways of the AsAOXs gene family, explores their responses and potential functions to various abiotic stresses, identifies potential candidate genes for future functional studies, and facilitates molecular breeding applications in A. sativa.

Conversion of superior bread wheat genotype HD3209 carrying Lr19/Sr25 into CMS line for development of rust-resistant wheat hybrids

Hybrid development is one of the most promising strategies for boosting crop yields. Parental lines used to create hybrids must have good per se performance and disease resistance for developing superior hybrids. Indian wheat line HD3209 was developed by introducing the rust resistance genes Lr19/Sr25 into the background of popular wheat variety HD2932. The wheat line HD3209 carrying Lr19/Sr25 has been successfully and rapidly converted to the CMS line A-HD3209, with 96.01% background genome recovery, based on selection for agro-morphological traits, rust resistance, pollen sterility, and foreground and background analyses utilizing SSR markers. The converted CMS line A-HD3209 was completely sterile and nearly identical to the recurrent parent HD3209. Based on high per se performance and rust resistance, the study concludes that the derived CMS line A-HD3209 is promising and can be employed successfully in hybrid development.

Fine mapping of QYrsv.swust-1BL for resistance to stripe rust in durum wheat Svevo

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a serious disease that affects wheat worldwide. There is a great need to develop cultivars with combinations of all-stage resistance (ASR) and adult-plant resistance (APR) genes for sustainable control of the disease. QYrsv.swust-1BL in the Italian durum wheat (Triticum turgidum ssp. durum) cultivar Svevo is effective against Pst races in China and Israel, and the gene has been previously mapped to the long arm of chromosome 1B. The gene is flanked by SNP (single nucleotide polymorphism) markers IWB5732 and IWB4839 (0.75 cM). In the present study, we used high-density 660K SNP array genotyping and the phenotypes of 137 recombinant inbred lines (RILs) to fine map the QYrsv.swust-1BL locus within a 1.066 Mb region in durum wheat Svevo (RefSeq Rel. 1.0) on chromosome arm 1BL. The identified 1.066 Mb region overlaps with a previously described map of Yr29/QYr.ucw-1BL, a stripe rust APR gene. Twenty-five candidate genes for QYrsv.swut-1BL were identified through comparing polymorphic genes within the 1.066 Mb region in the resistant cultivar. SNP markers were selected and converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers. Five KASP markers based on SNP were validated in a F2 and F2:3 breeding population, providing further compelling evidence for the significant effects of QYrsv.swut-1BL. These markers should be useful in marker-assisted selection for incorporating Yr29/QYrsv.swust-1BL into new durum and common wheat cultivars for resistance to stripe rust.

Implementing multi-trait genomic selection to improve grain milling quality in oats (Avena sativa L.)

Oats (Avena sativa L.) provide unique nutritional benefits and contribute to sustainable agricultural systems. Breeding high-value oat varieties that meet milling industry standards is crucial for satisfying the demand for oat-based food products. Test weight, thins, and groat percentage are primary traits that define oat milling quality and the final price of food-grade oats. Conventional selection for milling quality is costly and burdensome. Multi-trait genomic selection (MTGS) combines information from genome-wide markers and secondary traits genetically correlated with primary traits to predict breeding values of primary traits on candidate breeding lines. MTGS can improve prediction accuracy and significantly accelerate the rate of genetic gain. In this study, we evaluated different MTGS models that used morphometric grain traits to improve prediction accuracy for primary grain quality traits within the constraints of a breeding program. We evaluated 558 breeding lines from the University of Illinois Oat Breeding Program across 2 years for primary milling traits, test weight, thins, and groat percentage, and secondary grain morphometric traits derived from kernel and groat images. Kernel morphometric traits were genetically correlated with test weight and thins percentage but were uncorrelated with groat percentage. For test weight and thins percentage, the MTGS model that included the kernel morphometric traits in both training and candidate sets outperformed single-trait models by 52% and 59%, respectively. In contrast, MTGS models for groat percentage were not significantly better than the single-trait model. We found that incorporating kernel morphometric traits can improve the genomic selection for test weight and thins percentage.

Deacclimation and reacclimation processes in winter wheat: novel perspectives from time-series transcriptome analysis

Winter wheat achieves freezing tolerance (FT) through cold acclimation (CA) - a process which is induced by low positive temperatures in autumn. The increasing occurrences of temperature fluctuations in winter lead to deacclimation (DEA), causing premature loss of FT, and the cultivars capable of reacclimation (REA) are more likely to survive the subsequent cold spells. The genetic mechanisms of DEA and REA remain poorly understood, necessitating further research to bolster climate resilience in winter wheat. Here, we selected two winter wheat genotypes with contrasting levels of FT and conducted a ten-week-long experiment imitating low-temperature fluctuations after CA under controlled conditions. Crown and leaf tissue samples for RNA-sequencing were collected at CA, DEA, and REA time-points. It is the first transcriptomic study covering both short- and long-term responses to DEA and REA in winter wheat. The study provides novel knowledge regarding CA, DEA, and REA and discusses the gene expression patterns conferring FT under temperature fluctuations. The freezing-tolerant genotype "Lakaja DS" showed elevated photosynthetic activity in leaf tissue and upregulated cryoprotective protein-encoding genes in crowns after CA when compared to the freezing-susceptible "KWS Ferrum". "Lakaja DS" also expressed cold acclimation-associated transcripts at a significantly higher level after 1 week of DEA. Following REA, "Lakaja DS" continued to upregulate dehydrin-related genes in crowns and exhibited significantly higher expression of chitinase transcripts in leaves, when compared to "KWS Ferrum". The findings of this study shed light on the genetic mechanisms governing DEA and REA in winter wheat, thus addressing the gaps in knowledge regarding FT under low-temperature fluctuations. The identified genes should be further examined as potential molecular markers for breeding strategies focused on developing freezing-tolerant winter-type crops. Publicly available datasets generated in this study are valuable resources for further research into DEA and REA, contributing towards the enhancement of winter wheat under global climate change.

Are cereal grasses a single genetic system?

In 1993, a passionate and provocative call to arms urged cereal researchers to consider the taxon they study as a single genetic system and collaborate with each other. Since then, that group of scientists has seen their discipline blossom. In an attempt to understand what unity of genetic systems means and how the notion was borne out by later research, we survey the progress and prospects of cereal genomics: sequence assemblies, population-scale sequencing, resistance gene cloning and domestication genetics. Gene order may not be as extraordinarily well conserved in the grasses as once thought. Still, several recurring themes have emerged. The same ancestral molecular pathways defining plant architecture have been co-opted in the evolution of different cereal crops. Such genetic convergence as much as cross-fertilization of ideas between cereal geneticists has led to a rich harvest of genes that, it is hoped, will lead to improved varieties.

Temperature-Caused Changes in Raman Pattern and Protein Profiles of Winter Triticale (x Triticosecale, Wittm.) Field-Grown Seedlings

Climate change, which causes periods with relatively high temperatures in winter in Poland, can lead to a shortening or interruption of the cold hardening of crops. Previous research indicates that cold acclimation is of key importance in the process of acquiring cereal tolerance to stress factors. The objective of this work was to verify the hypothesis that both natural temperature fluctuations and the plant genotype influence the content of metabolites as well as proteins, including antioxidant enzymes and photosystem proteins. The research material involved four winter triticale genotypes, differing in their tolerance to stress under controlled conditions. The values of chlorophyll a fluorescence parameters and antioxidant activity were measured in their seedlings. Subsequently, the contribution of selected proteins was verified using specific antibodies. In parallel, the profiling of the contents of chlorophylls, carotenoids, phenolic compounds, and proteins was carried out by Raman spectroscopy. The obtained results indicate that a better PSII performance along with a higher photosystem II proteins content and thioredoxin reductase abundance were accompanied by a higher antioxidant activity in the field-grown triticale seedlings. The Raman studies showed that the cold hardening led to a variation in photosynthetic dyes and an increase in the phenolic to carotenoids ratio in all DH lines.

Chromosome-scale genome assembly of bread wheat's wild relative Triticum timopheevii

Wheat (Triticum aestivum) is one of the most important food crops with an urgent need for increase in its production to feed the growing world. Triticum timopheevii (2n = 4x = 28) is an allotetraploid wheat wild relative species containing the At and G genomes that has been exploited in many pre-breeding programmes for wheat improvement. In this study, we report the generation of a chromosome-scale reference genome assembly of T. timopheevii accession PI 94760 based on PacBio HiFi reads and chromosome conformation capture (Hi-C). The assembly comprised a total size of 9.35 Gb, featuring a contig N50 of 42.4 Mb and included the mitochondrial and plastid genome sequences. Genome annotation predicted 166,325 gene models including 70,365 genes with high confidence. DNA methylation analysis showed that the G genome had on average more methylated bases than the At genome. In summary, the T. timopheevii genome assembly provides a valuable resource for genome-informed discovery of agronomically important genes for food security.

CAP-RNAseq: an integrated pipeline for functional annotation and prioritization of co-expression clusters

Cluster analysis is one of the most widely used exploratory methods for visualization and grouping of gene expression patterns across multiple samples or treatment groups. Although several existing online tools can annotate clusters with functional terms, there is no all-in-one webserver to effectively prioritize genes/clusters using gene essentiality as well as congruency of mRNA-protein expression. Hence, we developed CAP-RNAseq that makes possible (1) upload and clustering of bulk RNA-seq data followed by identification, annotation and network visualization of all or selected clusters; and (2) prioritization using DepMap gene essentiality and/or dependency scores as well as the degree of correlation between mRNA and protein levels of genes within an expression cluster. In addition, CAP-RNAseq has an integrated primer design tool for the prioritized genes. Herein, we showed using comparisons with the existing tools and multiple case studies that CAP-RNAseq can uniquely aid in the discovery of co-expression clusters enriched with essential genes and prioritization of novel biomarker genes that exhibit high correlations between their mRNA and protein expression levels. CAP-RNAseq is applicable to RNA-seq data from different contexts including cancer and available at http://konulabapps.bilkent.edu.tr:3838/CAPRNAseq/ and the docker image is downloadable from https://hub.docker.com/r/konulab/caprnaseq.

Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review

The explosive growth of biomedical Big Data presents both significant opportunities and challenges in the realm of knowledge discovery and translational applications within precision medicine. Efficient management, analysis, and interpretation of big data can pave the way for groundbreaking advancements in precision medicine. However, the unprecedented strides in the automated collection of large-scale molecular and clinical data have also introduced formidable challenges in terms of data analysis and interpretation, necessitating the development of novel computational approaches. Some potential challenges include the curse of dimensionality, data heterogeneity, missing data, class imbalance, and scalability issues. This overview article focuses on the recent progress and breakthroughs in the application of big data within precision medicine. Key aspects are summarized, including content, data sources, technologies, tools, challenges, and existing gaps. Nine fields-Datawarehouse and data management, electronic medical record, biomedical imaging informatics, Artificial intelligence-aided surgical design and surgery optimization, omics data, health monitoring data, knowledge graph, public health informatics, and security and privacy-are discussed.

PhosBoost: Improved phosphorylation prediction recall using gradient boosting and protein language models

Protein phosphorylation is a dynamic and reversible post-translational modification that regulates a variety of essential biological processes. The regulatory role of phosphorylation in cellular signaling pathways, protein-protein interactions, and enzymatic activities has motivated extensive research efforts to understand its functional implications. Experimental protein phosphorylation data in plants remains limited to a few species, necessitating a scalable and accurate prediction method. Here, we present PhosBoost, a machine-learning approach that leverages protein language models and gradient-boosting trees to predict protein phosphorylation from experimentally derived data. Trained on data obtained from a comprehensive plant phosphorylation database, qPTMplants, we compared the performance of PhosBoost to existing protein phosphorylation prediction methods, PhosphoLingo and DeepPhos. For serine and threonine prediction, PhosBoost achieved higher recall than PhosphoLingo and DeepPhos (.78, .56, and .14, respectively) while maintaining a competitive area under the precision-recall curve (.54, .56, and .42, respectively). PhosphoLingo and DeepPhos failed to predict any tyrosine phosphorylation sites, while PhosBoost achieved a recall score of .6. Despite the precision-recall tradeoff, PhosBoost offers improved performance when recall is prioritized while consistently providing more confident probability scores. A sequence-based pairwise alignment step improved prediction results for all classifiers by effectively increasing the number of inferred positive phosphosites. We provide evidence to show that PhosBoost models are transferable across species and scalable for genome-wide protein phosphorylation predictions. PhosBoost is freely and publicly available on GitHub.

An online database for einkorn wheat to aid in gene discovery and functional genomics studies

Diploid A-genome wheat (einkorn wheat) presents a nutrition-rich option as an ancient grain crop and a resource for the improvement of bread wheat against abiotic and biotic stresses. Realizing the importance of this wheat species, reference-level assemblies of two einkorn wheat accessions were generated (wild and domesticated). This work reports an einkorn genome database that provides an interface to the cereals research community to perform comparative genomics, applied genetics and breeding research. It features queries for annotated genes, the use of a recent genome browser release, and the ability to search for sequence alignments using a modern BLAST interface. Other features include a comparison of reference einkorn assemblies with other wheat cultivars through genomic synteny visualization and an alignment visualization tool for BLAST results. Altogether, this resource will help wheat research and breeding. Database URL  https://wheat.pw.usda.gov/GG3/pangenome.

Identification of genetic loci for early maturity in spring bread wheat using the association analysis and gene dissection

Background

Early maturity in spring bread wheat is highly desirable in the regions where it enables the plants to evade high temperatures and plant pathogens at the end of the growing season.

Methods

To reveal the genetic loci responsible for the maturity time association analysis was carried out based on phenotyping for an 11-year period and high-throughput SNP genotyping of a panel of the varieties contrasting for this trait. The expression of candidate genes was verified using qPCR. The association between the SNP markers and the trait was validated using the biparental F2:3 population.

Results

Our data showed that under long-day conditions, the period from seedling to maturity is mostly influenced by the time from heading to maturity, rather than the heading time. The QTLs associated with the trait were located on 2A, 3B, 4A, 5B, 7A and 7B chromosomes with the 7BL locus being the most significant and promising for its SNPs accelerated the maturity time by about 9 days. Gene dissection in this locus detected a number of candidates, the best being TraesCS7B02G391800 (bZIP9) and TraesCS7B02G412200 (photosystem II reaction center). The two genes are predominantly expressed in the flag leaf while flowering. The effect of the SNPs was verified in F2:3 population and confirmed the association of the 4A, 5B and 7BL loci with the maturity time.

Exploring GWAS and genomic prediction to improve Septoria tritici blotch resistance in wheat

Septoria tritici blotch (STB) is a destructive foliar diseases threatening wheat grain yield. Wheat breeding for STB disease resistance has been identified as the most sustainable and environment-friendly approach. In this work, a panel of 316 winter wheat breeding lines from a commercial breeding program were evaluated for STB resistance at the seedling stage under controlled conditions followed by genome-wide association study (GWAS) and genomic prediction (GP). The study revealed a significant genotypic variation for STB seedling resistance, while disease severity scores exhibited a normal frequency distribution. Moreover, we calculated a broad-sense heritability of 0.62 for the trait. Nine single- and multi-locus GWAS models identified 24 marker-trait associations grouped into 20 quantitative trait loci (QTLs) for STB seedling-stage resistance. The seven QTLs located on chromosomes 1B, 2A, 2B, 5B (two), 7A, and 7D are reported for the first time and could potentially be novel. The GP cross-validation analysis in the RR-BLUP model estimated the genomic-estimated breeding values (GEBVs) of STB resistance with a prediction accuracy of 0.49. Meanwhile, the GWAS assisted wRR-BLUP model improved the accuracy to 0.58. The identified QTLs can be used for marker-assisted backcrossing against STB in winter wheat. Moreover, the higher prediction accuracy recorded from the GWAS-assisted GP analysis implies its power to successfully select superior candidate lines based on their GEBVs for STB resistance.

Wheat (Triticum aestivum) chromosome 6D harbours the broad spectrum common bunt resistance gene Bt11

KEY MESSAGE

A major QTL on chromosome 6DL corresponding to bunt resistance gene Bt11 was identified in four mapping populations generated through crosses with Bt11-carriers PI 166910 and M822123. Common bunt in wheat has witnessed a renaissance with the rise of organic agriculture that began in the 1980s. The abandonment of systemic fungicides in organic farming, together with a lack of resistant cultivars, has led to wide-spread problems due to common bunt infections. Knowledge about genetic sources for resistance is still scarce and only few of the known bunt resistance factors are currently used in breeding. We therefore aimed to map the resistance factor harboured by the Turkish landrace PI 166910, which is the resistance donor for the Bt11 bunt differential line. Four mapping populations (MPs) with 96-132 recombinant inbred lines (RILs) were phenotyped for common bunt resistance over 2, 3 or 4 years with one or two local bunt populations and genotyped with the 25K SNP array. A major bunt resistance locus on the distal end of chromosome 6D designated QBt.ifa-6DL was identified in all MPs and experiments. Additional QTL contributing to resistance were detected on chromosomes 4B, 1A, 1B, 2A and 7B. QBt.ifa-6DL mapped to a region overlapping with the Bt9-locus identified in previous studies, but results indicate that QBt.ifa-6DL is different from Bt9 and convincing evidence from haplotype comparisons suggests that it represents the Bt11 resistance allele. Markers for the distal region of chromosome 6D between 492.6 and 495.2 Mbp can be used to select for QBt.ifa-6DL. This resistance factor confers high and stable resistance against common bunt and should be integrated into organic and low-input wheat breeding programs.

DivBrowse-interactive visualization and exploratory data analysis of variant call matrices

BACKGROUND

The sequencing of whole genomes is becoming increasingly affordable. In this context, large-scale sequencing projects are generating ever larger datasets of species-specific genomic diversity. As a consequence, more and more genomic data need to be made easily accessible and analyzable to the scientific community.

FINDINGS

We present DivBrowse, a web application for interactive visualization and exploratory analysis of genomic diversity data stored in Variant Call Format (VCF) files of any size. By seamlessly combining BLAST as an entry point together with interactive data analysis features such as principal component analysis in one graphical user interface, DivBrowse provides a novel and unique set of exploratory data analysis capabilities for genomic biodiversity datasets. The capability to integrate DivBrowse into existing web applications supports interoperability between different web applications. Built-in interactive computation of principal component analysis allows users to perform ad hoc analysis of the population structure based on specific genetic elements such as genes and exons. Data interoperability is supported by the ability to export genomic diversity data in VCF and General Feature Format 3 files.

CONCLUSION

DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.

Genome-Wide Identification and Characterization of the Oat (Avena sativa L.) WRKY Transcription Factor Family

The WRKY family is widely involved in the regulation of plant growth and stress response and is one of the largest gene families related to plant environmental adaptation. However, no systematic studies on the WRKY family in oat (Avena sativa L.) have been conducted to date. The recently published complete genome sequence of oat enables the systematic analysis of the AsWRKYs. Based on a genome-wide study of oat, we identified 162 AsWRKYs that were unevenly distributed across 21 chromosomes; a phylogenetic tree of WRKY domains divided these genes into three groups (I, II, and III). We also analyzed the gene duplication events and identified a total of 111 gene pairs that showed strong purifying selection during the evolutionary process. Surprisingly, almost all genes evolved after the completion of subgenomic differentiation of hexaploid oat. Further studies on the functional analysis indicated that AsWRKYs were widely involved in various biological processes. Notably, expression patterns of 16 AsWRKY genes revealed that the response of AsWRKYs were affected by stress level and time. In conclusion, this study provides a reference for further analysis of the role of WRKY transcription factors in species evolution and functional differentiation.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.