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

Background With 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. Results Leaf 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. Conclusions Identification 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

MQ2: Visualize 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/

Marker2sequence, mine your QTL regions for candidate genes

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

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

Arachis pintoi in the humid tropics of Colombia : A forage legume success story

Background Recent advances in ~omics technologies such as transcriptomics, metabolomics and proteomics along with genotypic profiling have permitted the genetic dissection of complex traits such as quality traits in non-model species. To get more insight into the genetic factors underlying variation in quality traits related to carbohydrate and starch metabolism and cold sweetening, we determined the protein content and composition in potato tubers using 2D–gel electrophoresis in a diploid potato mapping population. Upon analyzing we made sure that the proteins from the patatin family were excluded to ensure a better representation of the other proteins. Results We subsequently performed pQTL analyses for all other proteins with a sufficient representation in the population and established a relationship between proteins and 26 potato tuber quality traits (e.g. flesh colour, enzymatic discoloration) by co-localization on the genetic map and a direct correlation study of protein abundances and phenotypic traits. Over 1643 unique protein spots were detected in total over the two harvests. We were able to map pQTLs for over 300 different protein spots some of which co-localized with traits such as starch content and cold sweetening. pQTLs were observed on every chromosome although not evenly distributed over the chromosomes. The largest number of pQTLs was found for chromosome 8 and the lowest for chromosome number 10. For some 20 protein spots multiple QTLs were observed. Conclusions From this analysis, hotspot areas for protein QTLs were identified on chromosomes three, five, eight and nine. The hotspot on chromosome 3 coincided with a QTL previously identified for total protein content and had more than 23 pQTLs in the region from 70 to 80 cM. Some of the co-localizing protein spots associated with some of the most interesting tuber quality traits were identified, albeit far less than we had anticipated at the onset of the experiments

Metabolic diversity in apple germplasm

We analysed metabolic diversity in apples from wild species, elite material and a F1 population, using liquid chromatography–mass spectrometry (LC-QTOF-MS). The evaluated elite material appeared to have strongly reduced levels of phenolic compounds, down to 1% of the concentrations in the investigated wild germplasm. In one quarter of the F1 population, the concentrations of phenolic compounds such as quercetin derivatives, procyanidin, catechin and epicatechin were further significantly reduced, due to accumulation of recessive alleles of putatively leucoanthocyanidin reductase, a structural gene that is located at the top of LG16. In another part of F1 progeny, putatively glycosylated forms of ß-glycols were up to 50 times more abundant compared to both parents. These metabolites were mapped with high logarithm of odds (LOD) scores at the top of LG8, and progeny that was homozygous recessive for the candidate gene showed the elevated levels. We hypothesize that this was caused by inheritance of non-functional alleles of enoyl-CoA hydratase gene. Both examples o

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 F(1) 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