Mapping the Anthocyaninless (anl) Locus in Rapid-Cycling Brassica rapa (RBr) to Linkage Group R9

<p>Abstract</p> <p>Background</p> <p>Anthocyanins are flavonoid pigments that are responsible for purple coloration in the stems and leaves of a variety of plant species. <it>Anthocyaninless </it>(<it>anl</it>) mutants of <it>Brassica rapa </it>fail to produce anthocyanin pigments. In rapid-cycling <it>Brassica rapa</it>, also known as Wisconsin Fast Plants, the anthocyaninless trait, also called non-purple stem, is widely used as a model recessive trait for teaching genetics. Although anthocyanin genes have been mapped in other plants such as <it>Arabidopsis thaliana</it>, the <it>anl </it>locus has not been mapped in any <it>Brassica </it>species.</p> <p>Results</p> <p>We tested primer pairs known to amplify microsatellites in <it>Brassicas </it>and identified 37 that amplified a product in rapid-cycling <it>Brassica rapa</it>. We then developed three-generation pedigrees to assess linkage between the microsatellite markers and <it>anl</it>. 22 of the markers that we tested were polymorphic in our crosses. Based on 177 F₂offspring, we identified three markers linked to <it>anl </it>with LOD scores ≥ 5.0, forming a linkage group spanning 46.9 cM. Because one of these markers has been assigned to a known <it>B. rapa </it>linkage group, we can now assign the <it>anl </it>locus to <it>B. rapa </it>linkage group R9.</p> <p>Conclusion</p> <p>This study is the first to identify the chromosomal location of an anthocyanin pigment gene among the <it>Brassicas</it>. It also connects a classical mutant frequently used in genetics education with molecular markers and a known chromosomal location.</p

Construction of an integrated genetic linkage map for the A genome of Brassica napus using SSR markers derived from sequenced BACs in B. rapa

Background The Multinational Brassica rapa Genome Sequencing Project (BrGSP) has developed valuable genomic resources, including BAC libraries, BAC-end sequences, genetic and physical maps, and seed BAC sequences for Brassica rapa. An integrated linkage map between the amphidiploid B. napus and diploid B. rapa will facilitate the rapid transfer of these valuable resources from B. rapa to B. napus (Oilseed rape, Canola). Results In this study, we identified over 23,000 simple sequence repeats (SSRs) from 536 sequenced BACs. 890 SSR markers (designated as BrGMS) were developed and used for the construction of an integrated linkage map for the A genome in B. rapa and B. napus. Two hundred and nineteen BrGMS markers were integrated to an existing B. napus linkage map (BnaNZDH). Among these mapped BrGMS markers, 168 were only distributed on the A genome linkage groups (LGs), 18 distrubuted both on the A and C genome LGs, and 33 only distributed on the C genome LGs. Most of the A genome LGs in B. napus were collinear with the homoeologous LGs in B. rapa, although minor inversions or rearrangements occurred on A2 and A9. The mapping of these BAC-specific SSR markers enabled assignment of 161 sequenced B. rapa BACs, as well as the associated BAC contigs to the A genome LGs of B. napus. Conclusion The genetic mapping of SSR markers derived from sequenced BACs in B. rapa enabled direct links to be established between the B. napus linkage map and a B. rapa physical map, and thus the assignment of B. rapa BACs and the associated BAC contigs to the B. napus linkage map. This integrated genetic linkage map will facilitate exploitation of the B. rapa annotated genomic resources for gene tagging and map-based cloning in B. napus, and for comparative analysis of the A genome within Brassica species

Dynamic modelling of ammonia biofiltration from waste gases

A dynamic model to describe ammonia removal in a gas-phase biofilter was developed. The math-ematical model is based on discretized mass balances and detailed nitrification kinetics that includeinhibitory effects caused by free ammonia (FA) and free nitrous acid (FNA). The model was able to pre-dict experimental results operation under different loading rates (from 3.2 to 13.2 g NH3h-1m-3). In par-ticular the model was capable of reproducing inhibition caused by high inlet ammonia concentrations. Alsoelimination capacity was accurately predicted. Experimental data was also used to optimize certain modelparameters such as the concentration of ammonia- and nitrite-oxidizing biomass.Peer ReviewedPostprint (published version

Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.Shichen Wang, Debbie Wong, Kerrie Forrest, Alexandra Allen, Shiaoman Chao, Bevan E. Huang, Marco Maccaferri, Silvio Salvi, Sara G. Milner, Luigi Cattivelli, Anna M. Mastrangelo, Alex Whan, Stuart Stephen, Gary Barker, Ralf Wieseke, Joerg Plieske, International Wheat Genome Sequencing Consortium, Morten Lillemo, Diane Mather, Rudi Appels, Rudy Dolferus, Gina Brown-Guedira, Abraham Korol, Alina R. Akhunova, Catherine Feuillet, Jerome Salse, Michele Morgante, Curtis Pozniak, Ming-Cheng Luo, Jan Dvorak, Matthew Morell, Jorge Dubcovsky, Martin Ganal, Roberto Tuberosa, Cindy Lawley, Ivan Mikoulitch, Colin Cavanagh, Keith J. Edwards, Matthew Hayden, and Eduard Akhuno