Search bioRxiv⌕ Search

Biology subjects

Guignon, V.

Publications and source records attributed to Guignon, V..

3 recordsLinked to original sources

Painting the diversity of a world's favourite fruit: A next generation catalogue of cultivated bananas

Societal impact statementBananas are nutritious fruits of major importance in the tropics and subtropics. Characterizing their diversity is essential to ensure their conservation and use. A catalogue showcasing cultivated bananas genomic diversity was compiled and is to be used as a tool to support the classification of banana cultivars. This research revealed that cultivated banana groups are not all made of identical clones. Materials from recent collecting missions indicated that more banana diversity is expected to be found as the exploration of the banana gene pool continues. These discoveries will drive dynamic conservation strategies for banana genetic resources and will increase their use. SummaryO_LIBanana is an important food crop cultivated in many tropical and subtropical regions around the world. Due to their low fertility, banana landraces are clonally propagated. However, different factors, such as synonymy and the effects of environment, make their assignment to described sets of clones, or cultivar groups, difficult. Consequently, passport data of accessions in genebanks is often uncomplete and sometimes inaccurate. C_LIO_LIWith the recent advances in genomics, a new powerful tool was developed enabling the fine-scale characterization of bananas ancestry along chromosomes, i.e. in silico chromosome painting. We applied this method to a high-throughput genotyping data set obtained from 317 banana accessions spanning most of the known cultivar groups. This set included both genebank and new uncharacterized materials. C_LIO_LIBy comparing curated morphological assignation to the genomic patterns resulting from in silico chromosome painting, we were able to compile a catalogue referencing the chromosome painting patterns of most of the described cultivar groups. C_LIO_LIExamining the genomic patterns obtained, we discovered intra-cultivar group variability. In some cultivar groups, mitotic recombination or deletions were clonally accumulated in cultivars. In addition, we identified at least 4 cultivar groups in which cultivars likely resulting from distinct sexual events co-existed, notably Pisang Awak in which 5 distinct genomic patterns of two ploidy levels were identified. New patterns were also discovered in the newest materials of the set, showing that a wider diversity of clones still exist on farm. C_LI

genomics↗

Benchmarking Database Systems for Genomic Selection Implementation

MotivationWith high-throughput genotyping systems now available, it has become feasible to fully integration genotyping information into breeding programs [22]. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize them in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs one would need an efficient genotype data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems.\n\nResultsWe found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix.\n\nAvailabilityhttp://gobiinx1.bti.cornell.edu:6083/projects/GBM/repos/benchmarking/browse\n\nContactyn259@cornell.edu

genomics↗

Agronomic Linked Data (AgroLD): a Knowledge-based System to Enable Integrative Biology in Agronomy

Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have developed the Agronomic Linked Data (AgroLD - www.agrold.org), a knowledge-based system relying on Semantic Web technologies and exploiting standard domain ontologies, to integrate data about plant species of high interest for the plant science community e.g., rice, wheat, arabidopsis. We present some integration results of the project, which initially focused on genomics, proteomics and phenomics. AgroLD is now an RDF (Resource Description Format) knowledge base of 100M triples created by annotating and integrating more than 50 datasets coming from 10 data sources -such as Gramene.org and TropGeneDB- with 10 ontologies -such as the Gene Ontology and Plant Trait Ontology. Our evaluation results show users appreciate the multiple query modes which support different use cases. AgroLDs objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes/proteins in, for instances, plant disease resistance or high yield traits. We expect the resolution of these questions to facilitate the formulation of new scientific hypotheses to be validated with a knowledge-oriented approach.

bioinformatics↗