Ontology-driven International Maize Information System (IMIS) for Phenotypic and Genotypic Data Exchange

The Consultative Group on International Agricultural Research (CGIAR; http://www.cgiar.org/) centres have developed the International Crop Information System (ICIS; http://www.icis.cgiar.org) for the management and integration of global information on genetic resources, and germplasm improvement for any crop. The Maize breeding programs at CIMMYT (http://beta.cimmyt.org/) have different software tools to manage phenotypic, genotypic, and environmental information for their experiments generated worldwide. These tools have the capacity of collecting information in the field, wet lab, and store it into different relational databases. The IMIS (http://imis.cimmyt.org/confluence/display/IMIS/Crop+Finder) is an implementation of the ICIS, which is a computerized database system for general, integrated management and utilization of genealogy, nomenclature, genetic, phenotypic and characterization data for maize. Data exchange within and between databases as well as retrieving information are often hampered by the variability of terms used to describe comparable objects. To overcome this problem, the Crop Ontology (CO) database (http://cropontology.org/) is developed. It provides controlled vocabulary sets for several economically important plant species and facilitates biocurators working in genebanks of plant genetic resources (PGR) and crop breeding data curation and annotation. The maize trait ontology is developed as one of subclasses of CO trait ontology providing standardized trait descriptions, scales and scale values implemented into the IMIS. This ontology-driven IMIS will allow researchers who wish to exploit comparative phenotypic and genotypic information of maize to elucidate functional aspects of each trait

Precision-mapping and statistical validation of quantitative trait loci by machine learning

<p>Abstract</p> <p>Background</p> <p>We introduce a QTL-mapping algorithm based on Statistical Machine Learning (SML) that is conceptually quite different to existing methods as there is a strong focus on generalisation ability. Our approach combines ridge regression, recursive feature elimination, and estimation of generalisation performance and marker effects using bootstrap resampling. Model performance and marker effects are determined using independent testing samples (individuals), thus providing better estimates. We compare the performance of SML against Composite Interval Mapping (CIM), Bayesian Interval Mapping (BIM) and single Marker Regression (MR) on synthetic datasets and a multi-trait and multi-environment dataset of the progeny for a cross between two barley cultivars.</p> <p>Results</p> <p>In an analysis of the synthetic datasets, SML accurately predicted the number of QTL underlying a trait while BIM tended to underestimate the number of QTL. The QTL identified by SML for the barley dataset broadly coincided with known QTL locations. SML reported approximately half of the QTL reported by either CIM or MR, not unexpected given that neither CIM nor MR incorporates independent testing. The latter makes these two methods susceptible to producing overly optimistic estimates of QTL effects, as we demonstrate for MR. The QTL resolution (peak definition) afforded by SML was consistently superior to MR, CIM and BIM, with QTL detection power similar to BIM. The precision of SML was underscored by repeatedly identifying, at ≤ 1-cM precision, three QTL for four partially related traits (heading date, plant height, lodging and yield). The set of QTL obtained using a 'raw' and a 'curated' version of the same genotypic dataset were more similar to each other for SML than for CIM or MR.</p> <p>Conclusion</p> <p>The SML algorithm produces better estimates of QTL effects because it eliminates the optimistic bias in the predictive performance of other QTL methods. It produces narrower peaks than other methods (except BIM) and hence identifies QTL with greater precision. It is more robust to genotyping and linkage mapping errors, and identifies markers linked to QTL in the absence of a genetic map.</p

Molecular Pathogenesis of MALT Lymphoma

Approximately 8% of all non-Hodgkin lymphomas are extranodal marginal zone B cell lymphoma of mucosa associated lymphoid tissue (MALT), also known as MALT lymphoma, which was first described in 1983 by Isaacson and Wright. MALT lymphomas arise at a wide range of different extranodal sites, with the highest frequency in the stomach, followed by lung, ocular adnexa, and thyroid, and with a low percentage in the small intestine. Interestingly, at least 3 different, apparently site-specific, chromosomal translocations and missense and frameshift mutations, all pathway-related genes affecting the NF-κB signal, have been implicated in the development and progression of MALT lymphoma. However, these genetic abnormalities alone are not sufficient for malignant transformation. There is now increasing evidence suggesting that the oncogenic product of translocation cooperates with immunological stimulation in oncogenesis, that is, the association with chronic bacterial infection or autoaggressive process. This review mainly discusses MALT lymphomas in terms of their genetic aberration and association with chronic infections and summarizes recent advances in their molecular pathogenesis

A DArT platform for quantitative bulked segregant analysis

<p>Abstract</p> <p>Background</p> <p>Bulked segregant analysis (BSA) identifies molecular markers associated with a phenotype by screening two DNA pools of phenotypically distinct plants for markers with skewed allele frequencies. In contrast to gel-based markers, hybridization-based markers such as SFP, DArT or SNP generate quantitative allele-frequency estimates. Only DArT, however, combines this advantage with low development and assay costs and the ability to be deployed for any plant species irrespective of its ploidy level. Here we investigate the suitability of DArT for BSA applications using a barley array as an example.</p> <p>Results</p> <p>In a first test experiment, we compared two bulks of 40 Steptoe/Morex DH plants with contrasting pubescent leaves (mPub) alleles on chromosome 3H. At optimized levels of experimental replication and marker-selection threshold, the BSA scan identified 433 polymorphic markers. The relative hybridization contrast between bulks accurately reflected the between-bulk difference in the frequency of the mPub allele (r = 0.96). The 'platform noise' of DArT assays, estimated by comparing two identical aliquots of a DNA mixture, was significantly lower than the 'pooling noise' reflecting the binomial sampling variance of the bulking process. The allele-frequency difference on chromosome 3H increased in the vicinity of mPub and peaked at the marker with the smallest distance from mPub (4.6 cM). In a validation experiment with only 20 plants per bulk we identified an aluminum (Al) tolerance locus in a Dayton/Zhepi2 DH population on chromosome 4H with < 0.8 cM precision, the same Al-tolerance locus that had been mapped before in other barley populations.</p> <p>Conclusion</p> <p>DArT-BSA identifies genetic loci that influence phenotypic characters in barley with at least 5 cM accuracy and should prove useful as a generic tool for high-throughput, quantitative BSA in plants irrespective of their ploidy level.</p

A historical appraisal of the tropical forages collection conserved at CIAT

A report on the tropical forage germplasm collection conserved in the CIAT genebank is presented. Emphasis is firstly on the assembling of the collection during 1972−1993 through about 70 major and minor collecting missions in tropical America, Africa and Southeast Asia. Along with introductions from existing collections, currently some 1,600 accessions of 134 grass species and 21,000 accessions of 637 legume species are being maintained. Secondly, information on the utilization of the collection, with emphasis on cultivar development based on selection of accessions from the CIAT collection, is presented. Worldwide, a total of 44 grass and 34 legume cultivars derived from germplasm maintained at CIAT are reported. Information on germplasm distribution and knowledge sharing during the last four decades is also presented as well as a brief discussion on future needs

DArT markers for the rye genome - genetic diversity and mapping

<p>Abstract</p> <p>Background</p> <p>Implementation of molecular breeding in rye (<it>Secale cereale </it>L.) improvement programs depends on the availability of high-density molecular linkage maps. However, the number of sequence-specific PCR-based markers available for the species is limited. Diversity Arrays Technology (DArT) is a microarray-based method allowing for detection of DNA polymorphism at several thousand loci in a single assay without relying on DNA sequence information. The objective of this study was the development and application of Diversity Arrays technology for rye.</p> <p>Results</p> <p>Using the <it>Pst</it>I/<it>Taq</it>I method of complexity reduction we created a rye diversity panel from DNA of 16 rye varieties and 15 rye inbred lines, including parents of a mapping population consisting of 82 recombinant inbred lines. The usefulness of a wheat diversity panel for identification of DArT markers for rye was also demonstrated. We identified 1022 clones that were polymorphic in the genotyped ILs and varieties and 1965 clones that differentiated the parental lines L318 and L9 and segregated in the mapping population. Hierarchical clustering and ordination analysis were performed based on the 1022 DArT markers to reveal genetic relationships between the rye varieties and inbred lines included in the study. Chromosomal location of 1872 DArT markers was determined using wheat-rye addition lines and 1818 DArT markers (among them 1181 unique, non-cosegregating) were placed on a genetic linkage map of the cross L318 × L9, providing an average density of one unique marker every 2.68 cM. This is the most saturated rye linkage map based solely on transferable markers available at the moment, providing rye breeders and researches with a better choice of markers and a higher probability of finding polymorphic markers in the region of interest.</p> <p>Conclusion</p> <p>The Diversity Arrays Technology can be efficiently and effectively used for rye genome analyses - assessment of genetic similarity and linkage mapping. The 11520-clone rye genotyping panel with several thousand markers with determined chromosomal location and accessible through an inexpensive genotyping service is a valuable resource for studies on rye genome organization and in molecular breeding of the species.</p

Multipitched plasmonic nanoparticle grating for broadband light enhancement in white light‑emitting organic diodes

We apply regular arrays of plasmonic nanodisks to enhance light emission from an organic white light-emitting diode (WOLED). To achieve broadband enhancement, we apply, first, aluminum as a nanodisk material with moderate loss throughout the whole visible spectral range. Second, broadband light coupling is mediated by surface lattice resonances from a multipitch array built from two superimposed gratings with different grating constants formed by elliptic and circular nanodisks. To demonstrate the viability of this concept, the grating structure was embedded in the hole transport layer of a solution-processed phosphorescent WOLED exhibiting a current efficiency of 2.1 cd/A at 1000 cd/m2. The surface lattice resonances in the grating raise the current efficiency of the device by 23% to 2.6 cd/A at 1000 cd/m2, while the device emission changes from a neutral white to a warm white appearance with CIE1931 (x,y) coordinates of (0.361, 0.352) and (0.404, 0.351), respectively. The WOLED was characterized in detail optically by extinction and angle-resolved photoluminescence and as well by electroluminescence measurements for its opto-electronic characteristics. The experimental results agree well with finite-difference time domain simulations that aim at a better understanding of the underlying physical mechanisms. In summary, our work presents a novel versatile approach for achieving broadband enhancement of light emission in WOLEDs over a wide spectral range.Peer Reviewe