SUMMARYRust, caused by the fungus Puccinia helianthi Schwein., is one of the most devastating diseases of sunflower (Helianthus annuus L.), affecting global production. The rust R gene R11 in sunflower line HA‐R9 shows broad‐spectrum resistance to P. helianthi virulent races and was previously mapped to an interval on sunflower chromosome 13 encompassing three candidate genes annotated in the XRQr1.0 reference genome assembly. In the current study, we combined ethyl methane sulfonate (EMS) mutagenesis with targeted region capture and PacBio long‐read sequencing to clone the R11 gene. Sequencing of a 60‐kb region spanning the R11 locus from the R11‐HA‐R9 rust‐resistant line and three EMS‐induced susceptible mutants facilitated the identification of R11 and definition of induced mutations. The R11 gene is predicted to have a single 3996‐bp open reading frame and encodes a protein of 1331 amino acids with CC‐NBS‐LRR domains typical of genes conferring plant resistance to biotrophic pathogens. Point mutations identified in the R11 rust‐susceptible mutants resulted in premature stop codons, consistent with loss of function leading to rust susceptibility. Additional functional studies using comparative RNA sequencing of the resistant line R11‐HA‐R9 and R11‐susceptible mutants revealed substantial differences in gene expression patterns associated with R11‐mediated resistance at 7 days post‐inoculation with rust, and uncovered the potential roles of terpenoid biosynthesis and metabolism in sunflower rust resistance.

We report an update of the Hymenoptera Genome Database (HGD; http://HymenopteraGenome.org), a genomic database of hymenopteran insect species. The number of species represented in HGD has nearly tripled, with fifty-eight hymenopteran species, including twenty bees, twenty-three ants, eleven wasps and four sawflies. With a reorganized website, HGD continues to provide the HymenopteraMine genomic data mining warehouse and JBrowse/Apollo genome browsers integrated with BLAST. We have computed Gene Ontology (GO) annotations for all species, greatly enhancing the GO annotation data gathered from UniProt with more than a ten-fold increase in the number of GO-annotated genes. We have also generated orthology datasets that encompass all HGD species and provide orthologue clusters for fourteen taxonomic groups. The new GO annotation and orthology data are available for searching in HymenopteraMine, and as bulk file downloads.

Tomato yellow leaf curl virus (TYLCV), a monopartite begomovirus in the family Geminiviridae, is efficiently transmitted by the whitefly, Bemisia tabaci, and causes serious economic losses to tomato crops around the world. TYLCV-infected tomato plants develop distinctive symptoms of yellowing and leaf upward cupping. In recent years, excellent progress has been made in the characterization of TYLCV C4 protein function as a pathogenicity determinant in experimental plants, including Nicotiana benthamiana and Arabidopsis thaliana. However, the molecular mechanism leading to disease symptom development in the natural host plant, tomato, has yet to be characterized. The aim of the current study was to generate transgenic tomato plants expressing the TYLCV C4 gene and evaluate differential gene expression through comparative transcriptome analysis between the transgenic C4 plants and the transgenic green fluorescent protein (Gfp) gene control plants. Transgenic tomato plants expressing TYLCV C4 developed phenotypes, including leaf upward cupping and yellowing, that are similar to the disease symptoms expressed on tomato plants infected with TYLCV. In a total of 241 differentially expressed genes identified in the transcriptome analysis, a series of plant development-related genes, including transcription factors, glutaredoxins, protein kinases, R-genes and microRNA target genes, were significantly altered. These results provide further evidence to support the important function of the C4 protein in begomovirus pathogenicity. These transgenic tomato plants could serve as basic genetic materials for further characterization of plant receptors that are interacting with the TYLCV C4.

The nuclear fertility restorer gene Rf5 in HA-R9, originating from the wild sunflower species Helianthus annuus , is able to restore the widely used PET1 cytoplasmic male sterility in sunflowers. Previous mapping placed Rf5 at an interval of 5.8 cM on sunflower chromosome 13, distal to a rust resistance gene R 11 at a 1.6 cM genetic distance in an SSR map. In the present study, publicly available SNP markers were further mapped around Rf5 and R 11 using 192 F 2 individuals, reducing the Rf5 interval from 5.8 to 0.8 cM. Additional SNP markers were developed in the target region of the two genes from the whole-genome resequencing of HA-R9, a donor line carrying Rf5 and R 11 . Fine mapping using 3517 F 3 individuals placed Rf5 at a 0.00071 cM interval and the gene co-segregated with SNP marker S13_216392091. Similarly, fine mapping performed using 8795 F 3 individuals mapped R 11 at an interval of 0.00210 cM, co-segregating with two SNP markers, S13_225290789 and C13_181790141. Sequence analysis identified Rf5 as a pentatricopeptide repeat-encoding gene. The high-density map and diagnostic SNP markers developed in this study will accelerate the use of Rf5 and R 11 in sunflower breeding.

Background The functional genome of agronomically important plant species remains largely unexplored, yet presents a virtually untapped resource for targeted crop improvement. Functional elements of regulatory DNA revealed through profiles of chromatin accessibility can be harnessed for fine-tuning gene expression to optimal phenotypes in specific environments. Result Here, we investigate the non-coding regulatory space in the maize ( Zea mays ) genome during early reproductive development of pollen- and grain-bearing inflorescences. Using an assay for differential sensitivity of chromatin to micrococcal nuclease (MNase) digestion, we profile accessible chromatin and nucleosome occupancy in these largely undifferentiated tissues and classify at least 1.6% of the genome as accessible, with the majority of MNase hypersensitive sites marking proximal promoters, but also 3′ ends of maize genes. This approach maps regulatory elements to footprint-level resolution. Integration of complementary transcriptome profiles and transcription factor occupancy data are used to annotate regulatory factors, such as combinatorial transcription factor binding motifs and long non-coding RNAs, that potentially contribute to organogenesis, including tissue-specific regulation between male and female inflorescence structures. Finally, genome-wide association studies for inflorescence architecture traits based solely on functional regions delineated by MNase hypersensitivity reveals new SNP-trait associations in known regulators of inflorescence development as well as new candidates. Conclusions These analyses provide a comprehensive look into the cis -regulatory landscape during inflorescence differentiation in a major cereal crop, which ultimately shapes architecture and influences yield potential.

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.

With the availability of a new highly contiguous Bos taurus reference genome assembly (ARS-UCD1.2), it is the opportune time to upgrade the bovine gene set by seeking input from researchers. Furthermore, advances in graphical genome annotation tools now make it possible for researchers to leverage sequence data generated with the latest technologies to collaboratively curate genes. For many years the Bovine Genome Database (BGD) has provided tools such as the Apollo genome annotation editor to support manual bovine gene curation. The goal of this paper is to explain the reasoning behind the decisions made in the manual gene curation process while providing examples using the existing BGD tools. We will describe the sources of gene annotation evidence provided at the BGD, including RNA-seq and Iso-Seq data. We will also explain how to interpret various data visualizations when curating gene models, and will demonstrate the value of manual gene annotation. The process described here can be applied to manual gene curation for other species with similar tools. With a better understanding of manual gene annotation, researchers will be encouraged to edit gene models and contribute to the enhancement of livestock gene sets.

Additional file 10 Dataset S9. Distance matrix between ABI3 motifs and FEA4 binding sites, closest gene models and annotations associated with these combinatorial cis-element modules, and functional enrichment analysis using maize-GAMER GO for genes within 1 kb of FEA4-ABI3 cis-element modules.

The whitefly Bemisia tabaci (Gennadius) is a notorious insect vector that transmits hundreds of plant viruses, affecting food and fiber crops worldwide, and results in the equivalent of billions of U.S. dollars in crop loss annually. To gain a better understanding of the mechanism in virus transmission, we conducted deep sequencing of small RNAs on the whitefly B. tabaci MEAM1 (Middle East-Asia Minor 1) that fed on tomato plants infected with tomato yellow leaf curl virus (TYLCV). Overall, 160 miRNAs were identified, 66 of which were conserved and 94 were B. tabaci-specific. Among the B. tabaci-specific miRNAs, 67 were newly described in the present study. Two miRNAs, with predicted targets encoding a nuclear receptor (Bta05482) and a very-long-chain (3R)-3-hydroxyacyl-CoA dehydratase 2 (Bta10702), respectively, were differentially expressed in whiteflies that fed on TYLCV-infected versus uninfected plants. To better understand the regulatory effects of identified miRNAs and their target genes, we correlated expression profiles of miRNAs and their target transcripts and found that, interestingly, miRNA expression was inversely correlated with the expression of ~50% of the predicted target genes. These analyses could serve as a model to study gene regulation in other systems involving arthropod transmission of viruses to plants and animals.

The whitefly Bemisia tabaci MEAM1 is a notorious vector capable of transmitting many plant viruses, resulting in serious crop loss and food shortage around the world. To investigate potential sRNA-mediated regulatory mechanisms in whiteflies that are affected by virus acquisition and transmission, we conducted small RNA (sRNA) deep sequencing and performed genome-wide profiling of piwi-interacting RNAs (piRNAs) in whiteflies that were fed on tomato yellow leaf curl virus (TYLCV)-infected or non-infected tomato plants for 24, 48, and 72 h. In the present study, piRNA reads ranging from 564,395 to 1,715,652 per library were identified and shown to distribute unevenly in clusters (57 to 96 per library) on the whitefly (B. tabaci MEAM1) genome. Among them, 53 piRNA clusters were common for all treatments. Comparative analysis between libraries generated from viruliferous and non-viruliferous whiteflies identified five TYLCV-induced and 24 TYLCV-suppressed piRNA clusters. Approximately 62% of piRNAs were derived from non-coding sequences including intergenic regions, introns, and untranslated regions (UTRs). The remaining 38% were derived from coding sequences (CDS) or repeat elements. Interestingly, six protein coding genes were targeted by the TYLCV-induced piRNAs. We identified a large number of piRNAs that were distributed in clusters across the whitefly genome, with 60% being derived from non-coding regions. Comparative analysis revealed that feeding on a virus-infected host caused induction and suppression of only a small number of piRNA clusters in whiteflies. Although piRNAs primarily regulate the activity of transposable elements, our results suggest that they may have additional functions in regulating protein coding genes and in insect-virus interactions.

Cucumber green mottle mosaic virus (CGMMV), an emerging tobamovirus, has caused serious disease outbreaks to cucurbit crops in several countries, including the United States. Although CGMMV is seed borne, the mechanism of its transmission from a contaminated seed to germinating seedling is still not fully understood, and the most suitable seed health assay method has not been well established. To evaluate the mechanism of seed transmissibility, using highly contaminated watermelon seeds collected from CGMMV-infected experimental plants, bioassays were conducted in a greenhouse through seedling grow-out and by mechanical inoculation. Through natural seedling grow-out, we did not observe seed transmission of CGMMV to germinating seedlings. However, efficient transmission of CGMMV was observed using bioassays on melon plants through mechanical inoculation of seed extract prepared from CGMMV-contaminated seeds. Understanding the seed borne property and the ease of mechanical transmission of CGMMV from a contaminated seed to seedling is an important finding. In comparative evaluation of various laboratory techniques for seed health assays, we found that enzyme-linked immunosorbent assay and loop-mediated isothermal amplification were the most sensitive and reliable methods to detect CGMMV on cucurbit seeds. Because CGMMV is a seed borne and highly contagious virus, a new infection might not result in a natural seedling grow-out; it could occur through mechanical transmission from contaminated seeds. Therefore, a sensitive seed health test is necessary to ensure CGMMV-free seed lots are used for planting.

The Bovine Genome Database (BGD) (http://bovinegenome.org) has been the key community bovine genomics database for more than a decade. To accommodate the increasing amount and complexity of bovine genomics data, BGD continues to advance its practices in data acquisition, curation, integration and efficient data retrieval. BGD provides tools for genome browsing (JBrowse), genome annotation (Apollo), data mining (BovineMine) and sequence database searching (BLAST). To augment the BGD genome annotation capabilities, we have developed a new Apollo plug-in, called the Locus-Specific Alternate Assembly (LSAA) tool, which enables users to identify and report potential genome assembly errors and structural variants. BGD now hosts both the newest bovine reference genome assembly, ARS-UCD1.2, as well as the previous reference genome, UMD3.1.1, with cross-genome navigation and queries supported in JBrowse and BovineMine, respectively. Other notable enhancements to BovineMine include the incorporation of genomes and gene annotation datasets for non-bovine ruminant species (goat and sheep), support for multiple assemblies per organism in the Regions Search tool, integration of additional ontologies and development of many new template queries. To better serve the research community, we continue to focus on improving existing tools, developing new tools, adding new datasets and encouraging researchers to use these resources.

To understand translational capacity on a genome-wide scale across three developmental stages of immature soybean seed cotyledons, ribosome profiling was performed in combination with RNA sequencing and cluster analysis. Transcripts representing 216 unique genes demonstrated a higher level of translational activity in at least one stage by exhibiting higher translational efficiencies (TEs) in which there were relatively more ribosome footprint sequence reads mapping to the transcript than were present in the control total RNA sample. The majority of these transcripts were more translationally active at the early stage of seed development and included 12 unique serine or cysteine proteases and 16 2S albumin and low molecular weight cysteine-rich proteins that may serve as substrates for turnover and mobilization early in seed development. It would appear that the serine proteases and 2S albumins play a vital role in the early stages. In contrast, our investigation of profiles of 19 genes encoding high abundance seed storage proteins, such as glycinins, beta-conglycinins, lectin, and Kunitz trypsin inhibitors, showed that they all had similar patterns in which the TE values started at low levels and increased approximately 2 to 6-fold during development. The highest levels of these seed protein transcripts were found at the mid-developmental stage, whereas the highest ribosome footprint levels of only up to 1.6 TE were found at the late developmental stage. These experimental findings suggest that the major seed storage protein coding genes are primarily regulated at the transcriptional level during normal soybean cotyledon development. Finally, our analyses also identified a total of 370 unique gene models that showed very low TE values including over 48 genes encoding ribosomal family proteins and 95 gene models that are related to energy and photosynthetic functions, many of which have homology to the chloroplast genome. Additionally, we showed that genes of the chloroplast were relatively translationally inactive during seed development.