A Cytological Analysis of Wheat Meiosis Targeted by Virus-Induced Gene Silencing (VIGS)

Virus-induced gene silencing (VIGS) is a rapid and cost-effective reverse genetic technology that can be used to assess gene function in wheat. This chapter contains a detailed description of how to target wheat meiotic genes by VIGS. The timing of this technique is critical and has been optimized to silence meiotic genes at peak expression, evidenced by silencing of Triticum aestivum disrupted meiotic cDNA1 (TaDMC1). We also describe cytological techniques that have been adapted for the preparation and analysis of meiocytes in wheat, including fluorescent in situ hybridization (FISH) with directly labeled, synthetic oligonucleotide probes, and immunolocalization on spread material

Integrating genomic resources to present full gene and putative promoter capture probe sets for bread wheat

BACKGROUND: Whole-genome shotgun resequencing of wheat is expensive because of its large, repetitive genome. Moreover, sequence data can fail to map uniquely to the reference genome, making it difficult to unambiguously assign variation. Resequencing using target capture enables sequencing of large numbers of individuals at high coverage to reliably identify variants associated with important agronomic traits. Previous studies have implemented complementary DNA/exon or gene-based probe sets in which the promoter and intron sequence is largely missing alongside newly characterized genes from the recent improved reference sequences. RESULTS: We present and validate 2 gold standard capture probe sets for hexaploid bread wheat, a gene and a putative promoter capture, which are designed using recently developed genome sequence and annotation resources. The captures can be combined or used independently. We demonstrate that the capture probe sets effectively enrich the high-confidence genes and putative promoter regions that were identified in the genome alongside a large proportion of the low-confidence genes and associated promoters. Finally, we demonstrate successful sample multiplexing that allows generation of adequate sequence coverage for single-nucleotide polymorphism calling while significantly reducing cost per sample for gene and putative promoter capture. CONCLUSIONS: We show that a capture design employing an "island strategy" can enable analysis of the large gene/putative promoter space of wheat with only 2 × 160 Mbp probe sets. Furthermore, these assays extend the regions of the wheat genome that are amenable to analyses beyond its exome, providing tools for detailed characterization of these regulatory regions in large populations

Genome distribution of differential homoeologue contributions to leaf gene expression in bread wheat

Using a combination of de novo transcriptome assembly, a newly-developed 9495-marker transcriptome SNP genetic linkage map and comparative genomics approaches, we developed an ordered set of non-redundant transcripts for each of the sub-genomes of hexaploid wheat: A (47,160 unigenes), B (59,663 unigenes) and D (40,588 unigenes). We used these as reference sequences against which to map Illumina mRNA-seq reads derived from young leaf tissue. Transcript abundance was quantified for each unigene. Using a 3-way reciprocal BLAST approach, 15,527 triplet sets of homoeologues (one from each genome) were identified. Differential expression (P<0.05) was identified for 5,248 unigenes, with 2906 represented at greater abundance than their two homoeologues and 2342 represented at lower abundance than their two homoeologues. Analysis of gene ontology terms revealed no biases between homoeologues. There was no evidence of genome-wide dominance effects, rather the more highly transcribed individual genes were distributed throughout all three genomes. Transcriptome Display Tile Plot (TDTP), a visualization approach based on CMYK colourspace, was developed and used to assess the genome for regions of skewed homoeologue transcript abundance. Extensive striation was revealed, indicative of many small regions of genome dominance (transcripts of homoeologues from one genome more abundant than the others) and many larger regions of genome repression (transcripts of homoeologues from one genome less abundant than the others)

High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool

In wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheat's secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra-high-density Axiom(®) genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site

A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

Citation: Chapman, J. A., Mascher, M., Buluç, A., Barry, K., Georganas, E., Session, A., . . . Rokhsar, D. S. (2015). A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome. Genome Biology, 16(1). doi:10.1186/s13059-015-0582-8Polyploid species have long been thought to be recalcitrant to whole-genome assembly. By combining high-throughput sequencing, recent developments in parallel computing, and genetic mapping, we derive, de novo, a sequence assembly representing 9.1 Gbp of the highly repetitive 16 Gbp genome of hexaploid wheat, Triticum aestivum, and assign 7.1 Gb of this assembly to chromosomal locations. The genome representation and accuracy of our assembly is comparable or even exceeds that of a chromosome-by-chromosome shotgun assembly. Our assembly and mapping strategy uses only short read sequencing technology and is applicable to any species where it is possible to construct a mapping population. © 2015 Chapman et al. licensee BioMed Central.Additional Authors: Muehlbauer, G. J.;Stein, N.;Rokhsar, D. S

PAREsnip2: A tool for high-throughput prediction of small RNA targets from degradome sequencing data using configurable targeting rules

Small RNAs (sRNAs) are short, non-coding RNAs that play critical roles in many important biological pathways. They suppress the translation of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to their sequence-specific mRNA target(s). In plants, this typically results in mRNA cleavage and subsequent degradation of the mRNA. The resulting mRNA fragments, or degradome, provide evidence for these interactions, and thus degradome analysis has become an important tool for sRNA target prediction. Even so, with the continuing advances in sequencing technologies, not only are larger and more complex genomes being sequenced, but also degradome and associated datasets are growing both in number and read count. As a result, existing degradome analysis tools are unable to process the volume of data being produced without imposing huge resource and time requirements. Moreover, these tools use stringent, non-configurable targeting rules, which reduces their flexibility. Here, we present a new and user configurable software tool for degradome analysis, which employs a novel search algorithm and sequence encoding technique to reduce the search space during analysis. The tool significantly reduces the time and resources required to perform degradome analysis, in some cases providing more than two orders of magnitude speed-up over current methods

A modified sequence capture approach allowing standard and methylation analyses of the same enriched genomic DNA sample

Background: Bread wheat has a large complex genome that makes whole genome resequencing costly. Therefore, genome complexity reduction techniques such as sequence capture make re-sequencing cost effective. With a high-quality draft wheat genome now available it is possible to design capture probe sets and to use them to accurately genotype and anchor SNPs to the genome. Furthermore, in addition to genetic variation, epigenetic variation provides a source of natural variation contributing to changes in gene expression and phenotype that can be profiled at the base pair level using sequence capture coupled with bisulphite treatment. Here, we present a new 12 Mbp wheat capture probe set, that allows both the profiling of genotype and methylation from the same DNA sample. Furthermore, we present a method, based on Agilent SureSelect Methyl-Seq, that will use a single capture assay as a starting point to allow both DNA sequencing and methyl-seq. Results: Our method uses a single capture assay that is sequentially split and used for both DNA sequencing and methyl-seq. The resultant genotype and epi-type data is highly comparable in terms of coverage and SNP/methylation site identification to that generated from separate captures for DNA sequencing and methyl-seq. Furthermore, by defining SNP frequencies in a diverse landrace from the Watkins collection we highlight the importance of having genotype data to prevent false positive methylation calls. Finally, we present the design of a new 12 Mbp wheat capture and demonstrate its successful application to re-sequence wheat. Conclusions: We present a cost-effective method for performing both DNA sequencing and methyl-seq from a single capture reaction thus reducing reagent costs, sample preparation time and DNA requirements for these complementary analyses

A high-density, SNP-based consensus map of tetraploid wheat as a bridge to integrate durum and bread wheat genomics and breeding

Consensus linkage maps are important tools in crop genomics. We have assembled a highdensity tetraploid wheat consensus map by integrating 13 data sets from independent biparental populations involving durum wheat cultivars (Triticum turgidum ssp. durum), cultivated emmer (T. turgidum ssp. dicoccum) and their ancestor (wild emmer, T. turgidum ssp. dicoccoides). The consensus map harboured 30 144 markers (including 26 626 SNPs and 791 SSRs) half of which were present in at least two component maps. The final map spanned 2631 cM of all 14 durum wheat chromosomes and, differently from the individual component maps, all markers fell within the 14 linkage groups. Marker density per genetic distance unit peaked at centromeric regions, likely due to a combination of low recombination rate in the centromeric regions and even gene distribution along the chromosomes. Comparisons with bread wheat indicated fewer regions with recombination suppression, making this consensus map valuable for mapping in the A and B genomes of both durum and bread wheat. Sequence similarity analysis allowed us to relate mapped gene-derived SNPs to chromosome-specific transcripts. Dense patterns of homeologous relationships have been established between the A- and B-genome maps and between nonsyntenic homeologous chromosome regions as well, the latter tracing to ancient translocation events. The gene-based homeologous relationships are valuable to infer the map location of homeologs of target loci/QTLs. Because most SNP and SSR markers were previously mapped in bread wheat, this consensus map will facilitate a more effective integration and exploitation of genes and QTL for wheat breeding purposes