Jessica Dalton-Morgan

The Fate of Chromosomes and Alleles in an Allohexaploid Brassica Population

Production of allohexaploid Brassica (2n = AABBCC) is a promising goal for plant breeders due to the potential for hybrid heterosis and useful allelic contributions from all three of the Brassica genomes present in the cultivated diploid (2n = AA, 2n = BB, 2n = CC) and allotetraploid (2n = AABB, 2n = AACC, and 2n = BBCC) crop species (canola, cabbages, mustards). We used high-throughput SNP molecular marker assays, flow cytometry, and fluorescent in situ hybridization (FISH) to characterize a population of putative allohexaploids derived from self-pollination of a hybrid from the novel cross (B. napus × B. carinata) × B. juncea to investigate whether fertile, stable allohexaploid Brassica can be produced. Allelic segregation in the A and C genomes generally followed Mendelian expectations for an F2 population, with minimal nonhomologous chromosome pairing. However, we detected no strong selection for complete 2n = AABBCC chromosome complements, with weak correlations between DNA content and fertility (r2 = 0.11) and no correlation between missing chromosomes or chromosome segments and fertility. Investigation of next-generation progeny resulting from one highly fertile F2 plant using FISH revealed general maintenance of high chromosome numbers but severe distortions in karyotype, as evidenced by recombinant chromosomes and putative loss/duplication of A- and C-genome chromosome pairs. Our results show promise for the development of meiotically stable allohexaploid lines, but highlight the necessity of selection for 2n = AABBCC karyotypes.

High-throughput genotyping for species identification and diversity assessment in germplasm collections

Germplasm collections provide an extremely valuable resource for breeders and researchers. However, misclassification of accessions by species often hinders the effective use of these collections. We propose that use of high‐throughput genotyping tools can provide a fast, efficient and cost‐effective way of confirming species in germplasm collections, as well as providing valuable genetic diversity data. We genotyped 180 Brassicaceae samples sourced from the Australian Grains Genebank across the recently released Illumina Infinium Brassica 60K SNP array. Of these, 76 were provided on the basis of suspected misclassification and another 104 were sourced independently from the germplasm collection. Presence of the A‐ and C‐genomes combined with principle components analysis clearly separated Brassica rapa, B. oleracea, B. napus, B. carinata and B. juncea samples into distinct species groups. Several lines were further validated using chromosome counts. Overall, 18% of samples (32/180) were misclassified on the basis of species. Within these 180 samples, 23/76 (30%) supplied on the basis of suspected misclassification were misclassified, and 9/105 (9%) of the samples randomly sourced from the Australian Grains Genebank were misclassified. Surprisingly, several individuals were also found to be the product of interspecific hybridization events. The SNP (single nucleotide polymorphism) array proved effective at confirming species, and provided useful information related to genetic diversity. As similar genomic resources become available for different crops, high‐throughput molecular genotyping will offer an efficient and cost‐effective method to screen germplasm collections worldwide, facilitating more effective use of these valuable resources by breeders and researchers.

Genome wide analysis of flowering time trait in multiple environments via high-throughput genotyping technique in Brassica napus L

The prediction of the flowering time (FT) trait in Brassica napus based on genome-wide markers and the detection of underlying genetic factors is important not only for oilseed producers around the world but also for the other crop industry in the rotation system in China. In previous studies the low density and mixture of biomarkers used obstructed genomic selection in B. napus and comprehensive mapping of FT related loci. In this study, a high-density genome-wide SNP set was genotyped from a double-haploid population of B. napus. We first performed genomic prediction of FT traits in B. napus using SNPs across the genome under ten environments of three geographic regions via eight existing genomic predictive models. The results showed that all the models achieved comparably high accuracies, verifying the feasibility of genomic prediction in B. napus. Next, we performed a large-scale mapping of FT related loci among three regions, and found 437 associated SNPs, some of which represented known FT genes, such as AP1 and PHYE. The genes tagged by the associated SNPs were enriched in biological processes involved in the formation of flowers. Epistasis analysis showed that significant interactions were found between detected loci, even among some known FT related genes. All the results showed that our large scale and high-density genotype data are of great practical and scientific values for B. napus. To our best knowledge, this is the first evaluation of genomic selection models in B. napus based on a high-density SNP dataset and large-scale mapping of FT loci.

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.

Complete Nucleotide Sequence of an Australian Isolate of Turnip mosaic virus before and after Seven Years of Serial Passaging

ABSTRACT The complete genome sequence of an Australian isolate of Turnip mosaic virus was determined by Sanger sequencing. After seven years of serial passaging by mechanical inoculation, the isolate was resequenced by RNA sequencing (RNA-Seq). Eighteen single nucleotide polymorphisms were identified between the isolates. Both isolates had 96% identity to isolate AUST10.

First fully sequenced genome of an Australian isolate of Cauliflower mosaic virus

We report the first fully sequenced genome of an Australian isolate of Cauliflower mosaic virus. The circular genome is 8022 base pairs in length. A phylogenetic analysis suggests recent common ancestry of this virus isolate with those from Japan and the USA, and origins of the clade in western Europe.

Advances in plant genotyping: where the future will take us.

Genetic diversity between individuals can be tracked and monitored using a range of molecular markers. These markers can detect variation ranging in scale from a single base pair up to duplications and translocations of entire chromosomal regions. The genotyping of individuals allows the detection of this variation and it has been successfully applied in plant science for many years. The increasing amounts of sequence data able to be generated using next-generation sequencing (NGS) technologies have produced a vast expansion in the rate of discovery of polymorphisms, with single nucleotide polymorphisms (SNPs) predominating as the marker of choice. This increase in polymorphic marker resources through efficient discovery, coupled with the utility of SNPs, has enabled the shift to high-throughput genotyping assays and these methods are reviewed and discussed here, alongside the recent innovations allowing increased throughput.

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 Illuminas GoldenGate™ and Infinium™ methods.

An Optimized Transient Dual Luciferase Assay for Quantifying MicroRNA Directed Repression of Targeted Sequences

Studies investigating the action of small RNAs on computationally predicted target genes require some form of experimental validation. Classical molecular methods of validating microRNA action on target genes are laborious, while approaches that tag predicted target sequences to qualitative reporter genes encounter technical limitations. The aim of this study was to address the challenge of experimentally validating large numbers of computationally predicted microRNA-target transcript interactions using an optimized, quantitative, cost-effective, and scalable approach. The presented method combines transient expression via agroinfiltration of Nicotiana benthamiana leaves with a quantitative dual luciferase reporter system, where firefly luciferase is used to report the microRNA-target sequence interaction and Renilla luciferase is used as an internal standard to normalize expression between replicates. We report the appropriate concentration of N. benthamiana leaf extracts and dilution factor to apply in order to avoid inhibition of firefly LUC activity. Furthermore, the optimal ratio of microRNA precursor expression construct to reporter construct and duration of the incubation period post-agroinfiltration were determined. The optimized dual luciferase assay provides an efficient, repeatable and scalable method to validate and quantify microRNA action on predicted target sequences. The optimized assay was used to validate five predicted targets of rice microRNA miR529b, with as few as six technical replicates. The assay can be extended to assess other small RNA-target sequence interactions, including assessing the functionality of an artificial miRNA or an RNAi construct on a targeted sequence.