Search

Chrysanthemum morifolium Ramat. (2n=6x=54) is an hexaploid ornamental crop that is thought to be originating from up to 10 wild species in the domestication process. Although it has an expected allopolyploid origin, segregation tested in populations mainly showed a random segregation. To make a start in understanding the complex nature of the hexaploid genome and the use of genomics for breeding, diploid wild species genomes provide a valuable resource. The completion of the de novo genome assemblies of both C. makinoi and C. seticuspe allowed us to look at the synteny between the two species and compared it also to genomes of other Asteraceae. Using resequencing data of other wild species and a hexaploid cultivar provided a first attempt to test the presence of signals from the wild species in the hexaploid gene pool.

The increasing nutritional demands of the world as well as the need for crops that perform reliably, in spite of diverse environmental conditions (abiotic and biotic stresses and variable weather conditions), put the plant sciences at the forefront of domains where progress is urgently needed. To be able to do so, plant phenotyping and genotyping are extremely important. Especially in plant phenotyping, research is met with challenges related to poor data management, and thereby inefficient exploitation - let alone reuse of datasets. The challenges to phenotypic data reuse and integration arise due to the highly distributed nature of data in the domain (as there are no central plant phenotypic data repositories) and their multifaceted heterogeneity. The variety of experimental goals and the sheer number of species studied may necessitate different approaches (e.g. for crops, model organisms, forest trees). Experiments may be conducted in open fields, greenhouses or other locations, follow different designs and produce different types of data (e.g. visual observation of a score, images, manual and automatic measurements, molecular assays). Even when everything else matches, the data files produced may have different formats and structures, which is a challenge for data integration. Moreover, good data documentation practices are often lacking, which hinders interpretation and reuse. In the vast majority of cases, plant phenotyping datasets are used only once, solely to address the research question for which they were originally generated. It is the exception, rather than the rule, when different datasets, produced by different, uncoordinated parties, are analyzed to generate further knowledge. Even rarer, though much more useful, are cases where independently created datasets are integrated for the purpose of meta-analyses or improvement of statistical and predictive models. Such work is crucial, for example, for multi-environment studies investigating the adaptabil

One of the major global challenges of today is to meet the food demands of an ever increasing population (food demand will increase by 50% in 2030). One approach to address this challenge is to breed new crop varieties that yield more even under unfavorable conditions e.g. have improved tolerance to drought and/or resistance to pathogens. However, designing a breeding program is a laborious and time consuming effort that often lacks the capacity to generate new cultivars quickly in response to the required traits. Recent advances in biotechnology and genomics data science have the potential to accelerate and precise breeding programs greatly. As large-scale genomic data sets for crop species are available in multiple independent data sources and scientific literature, this thesis provides innovative technologies that use natural language processing (NLP) and semantic web technologies to address challenges of integrating genomic data for improving plant breeding. Firstly, in this research study, we developed a supervised Natural language processing (NLP) model with the help of IBM Watson, to extract knowledge networks containing genotypic-phenotypic associations of potato tuber flesh color from the scientific literature. Secondly, a table mining tool called QTLTableMiner++ (QTM) was developed which enables knowledge discovery of novel genomic regions (such as QTL regions), which positively or negatively affect the traits of interest. The objective of both above mentioned, NLP techniques was to extract information which is implicitly described in the literature and is not available in structured resources, like databases. Thirdly, with the help of semantic web technology, a linked-data platform called Solanaceae linked data platform(pbg-ld) was developed, to semantically integrates geno- and pheno-typic data of Solanaceae species. This platform combines both unstructured data from scientific literature and structured data from publicly available biological databases u

Background: A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental info

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

In 2012 publiceerde Nature de genomische sequentie van de tomaat. Maar daarmee is het werk niet af, zegt Richard Finkers. Hij bepaalde de basenvolgorde van nog eens 150 verwanten van de modeltomaat, om plantenveredelaars in staat te stellen op zoek te gaan naar nieuwe genen in oude rassen.

Resistentie tegen Botrytis cinerea is gevonden in wilde verwanten van tomaat en deze resistentie was meestal kwantitatief. Het doel van dit promotieonderzoek was om kwantitatieve loci (QTLs) te identificeren die bijdragen aan resistentie tegen B. cinerea. Met behulp van DNA-merkertechnologie en een populatie van introgressie-lijnen zijn tien QTLs geïdentificeerd. Geen van de afzonderlijke QTLs resulteerde in een niveau van resistentie dat overeen kwam de resistente ouder Solanum habrochaites LYC4. Dit betekent dat QTLs gecombineerd zullen moeten worden om Botrytis cinerea-resistente tomaten te verkrijgen. Dankzij de ontwikkelde DNA-merkers kunnen de geïdentificeerde chromosoomfragmenten met resistentiegenen nu gericht ingekruist worden.