Pierre-Yves Chibon

Genetic analysis of metabolites in apple fruits indicates an mQTL hotspot for phenolic compounds on linkage group 16

Apple (Malus×domestica Borkh) is among the main sources of phenolic compounds in the human diet. The genetic basis of the quantitative variations of these potentially beneficial phenolic compounds was investigated. A segregating F1 population was used to map metabolite quantitative trait loci (mQTLs). Untargeted metabolic profiling of peel and flesh tissues of ripe fruits was performed using liquid chromatography–mass spectrometry (LC-MS), resulting in the detection of 418 metabolites in peel and 254 in flesh. In mQTL mapping using MetaNetwork, 669 significant mQTLs were detected: 488 in the peel and 181 in the flesh. Four linkage groups (LGs), LG1, LG8, LG13, and LG16, were found to contain mQTL hotspots, mainly regulating metabolites that belong to the phenylpropanoid pathway. The genetics of annotated metabolites was studied in more detail using MapQTL®. A number of quercetin conjugates had mQTLs on LG1 or LG13. The most important mQTL hotspot with the largest number of metabolites was detected on LG16: mQTLs for 33 peel-related and 17 flesh-related phenolic compounds. Structural genes involved in the phenylpropanoid biosynthetic pathway were located, using the apple genome sequence. The structural gene leucoanthocyanidin reductase (LAR1) was in the mQTL hotspot on LG16, as were seven transcription factor genes. The authors believe that this is the first time that a QTL analysis was performed on such a high number of metabolites in an outbreeding plant species.

MetaBase—the wiki-database of biological databases

Biology is generating more data than ever. As a result, there is an ever increasing number of publicly available databases that analyse, integrate and summarize the available data, providing an invaluable resource for the biological community. As this trend continues, there is a pressing need to organize, catalogue and rate these resources, so that the information they contain can be most effectively exploited. MetaBase (MB) (http://MetaDatabase.Org) is a community-curated database containing more than 2000 commonly used biological databases. Each entry is structured using templates and can carry various user comments and annotations. Entries can be searched, listed, browsed or queried. The database was created using the same MediaWiki technology that powers Wikipedia, allowing users to contribute on many different levels. The initial release of MB was derived from the content of the 2007 Nucleic Acids Research (NAR) Database Issue. Since then, approximately 100 databases have been manually collected from the literature, and users have added information for over 240 databases. MB is synchronized annually with the static Molecular Biology Database Collection provided by NAR. To date, there have been 19 significant contributors to the project; each one is listed as an author here to highlight the community aspect of the project.

Organ specificity and transcriptional control of metabolic routes revealed by expression QTL profiling of source-sink tissues in a segregating potato population

BackgroundWith the completion of genome sequences belonging to some of the major crop plants, new challenges arise to utilize this data for crop improvement and increased food security. The field of genetical genomics has the potential to identify genes displaying heritable differential expression associated to important phenotypic traits. Here we describe the identification of expression QTLs (eQTLs) in two different potato tissues of a segregating potato population and query the potato genome sequence to differentiate between cis- and trans-acting eQTLs in relation to gene subfunctionalization.ResultsLeaf and tuber samples were analysed and screened for the presence of conserved and tissue dependent eQTLs. Expression QTLs present in both tissues are predominantly cis-acting whilst for tissue specific QTLs, the percentage of trans-acting QTLs increases. Tissue dependent eQTLs were assigned to functional classes and visualized in metabolic pathways. We identified a potential regulatory network on chromosome 10 involving genes crucial for maintaining circadian rhythms and controlling clock output genes. In addition, we show that the type of genetic material screened and sampling strategy applied, can have a high impact on the output of genetical genomics studies.ConclusionsIdentification of tissue dependent regulatory networks based on mapped differential expression not only gives us insight in tissue dependent gene subfunctionalization but brings new insights into key biological processes and delivers targets for future haplotyping and genetic marker development.

Marker2sequence, mine your QTL regions for candidate genes

UNLABELLED Marker2sequence (M2S) aims at mining quantitative trait loci (QTLs) for candidate genes. For each gene, within the QTL region, M2S uses data integration technology to integrate putative gene function with associated gene ontology terms, proteins, pathways and literature. As a typical QTL region easily contains several hundreds of genes, this gene list can then be further filtered using a keyword-based query on the aggregated annotations. M2S will help breeders to identify potential candidate genes for their traits of interest. AVAILABILITY Marker2sequence is freely accessible at http://www.plantbreeding.wur.nl/BreeDB/marker2seq/. The source code can be obtained at https://github.com/PBR/Marker2Sequence. CONTACT richard.finkers@wur.nl

MQ2: visualizing multi-trait mapped QTL results

Quantitative trait loci (QTL) mapping tools such as MapQTL and R/qtl allow easy and fast analysis of more than one trait at the same time. However, for experiments with large datasets, such as high-throughput metabolite QTL analysis, these tools do not provide an easy-to-inspect summary of the results. The ability to have an overview of the distribution of the identified QTL becomes a key factor. MQ2 fills this need by providing a command line tool and a web application that summarizes and visualizes the results of multi-trait QTL analysis. MQ2 can use the output of commonly used QTL analysis tools, such as MapQTL and R/qtl, as input. MQ2 can be used for free at: http://www.plantbreeding.wur.nl/mq2/.

Genebanks and genomics: how to interconnect data from both communities?

Genebanks are important suppliers of genetic resources to the genomics research community, and access to the resulting information will allow traditional genebank users to better select genetic material for their breeding and scientific programmes. We discuss herein a possible solution to interconnect these data automatically based on semantic web technology.