A system-level analysis of patient disease trajectories based on clinical, phenotypic and molecular similarities.

MOTIVATION: Incorporating the temporal dimension into multimorbidity studies has shown to be crucial for achieving a better understanding of the disease associations. Furthermore, due to the multifactorial nature of human disease, exploring disease associations from different perspectives can provide a holistic view to support the study of their aetiology. RESULTS: In this work, a temporal systems-medicine approach is proposed for identifying time-dependent multimorbidity patterns from patient disease trajectories, by integrating data from electronic health records with genetic and phenotypic information. Specifically, the disease trajectories are clustered using an unsupervised algorithm based on dynamic time warping and three disease similarity metrics: clinical, genetic and phenotypic. An evaluation method is also presented for quantitatively assessing, in the different disease spaces, both the cluster homogeneity and the respective similarities between the associated diseases within individual trajectories. The latter can facilitate exploring the origin(s) in the identified disease patterns. The proposed integrative methodology can be applied to any longitudinal cohort and disease of interest. In this article, prostate cancer is selected as a use case of medical interest to demonstrate, for the first time, the identification of temporal disease multimorbidities in different disease spaces. AVAILABILITY AND IMPLEMENTATION: https://gitlab.com/agiannoula/diseasetrajectories. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The DisGeNET knowledge platform for disease genomics: 2019 update.

One of the most pressing challenges in genomic medicine is to understand the role played by genetic variation in health and disease. Thanks to the exploration of genomic variants at large scale, hundreds of thousands of disease-associated loci have been uncovered. However, the identification of variants of clinical relevance is a significant challenge that requires comprehensive interrogation of previous knowledge and linkage to new experimental results. To assist in this complex task, we created DisGeNET (http://www.disgenet.org/), a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, including the scientific literature. DisGeNET covers the full spectrum of human diseases as well as normal and abnormal traits. The current release covers more than 24 000 diseases and traits, 17 000 genes and 117 000 genomic variants. The latest developments of DisGeNET include new sources of data, novel data attributes and prioritization metrics, a redesigned web interface and recently launched APIs. Thanks to the data standardization, the combination of expert curated information with data automatically mined from the scientific literature, and a suite of tools for accessing its publicly available data, DisGeNET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.

DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants.

The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.

Interspecific and intraspecific gene variability in a 1-Mb region containing the highest density of NBS-LRR genes found in the melon genome.

BACKGROUND: Plant NBS-LRR -resistance genes tend to be found in clusters, which have been shown to be hot spots of genome variability. In melon, half of the 81 predicted NBS-LRR genes group in nine clusters, and a 1 Mb region on linkage group V contains the highest density of R-genes and presence/absence gene polymorphisms found in the melon genome. This region is known to contain the locus of Vat, an agronomically important gene that confers resistance to aphids. However, the presence of duplications makes the sequencing and annotation of R-gene clusters difficult, usually resulting in multi-gapped sequences with higher than average errors. RESULTS: A 1-Mb sequence that contains the largest NBS-LRR gene cluster found in melon was improved using a strategy that combines Illumina paired-end mapping and PCR-based gap closing. Unknown sequence was decreased by 70% while about 3,000 SNPs and small indels were corrected. As a result, the annotations of 18 of a total of 23 NBS-LRR genes found in this region were modified, including additional coding sequences, amino acid changes, correction of splicing boundaries, or fussion of ORFs in common transcription units. A phylogeny analysis of the R-genes and their comparison with syntenic sequences in other cucurbits point to a pattern of local gene amplifications since the diversification of cucurbits from other families, and through speciation within the family. A candidate Vat gene is proposed based on the sequence similarity between a reported Vat gene from a Korean melon cultivar and a sequence fragment previously absent in the unrefined sequence. CONCLUSIONS: A sequence refinement strategy allowed substantial improvement of a 1 Mb fragment of the melon genome and the re-annotation of the largest cluster of NBS-LRR gene homologues found in melon. Analysis of the cluster revealed that resistance genes have been produced by sequence duplication in adjacent genome locations since the divergence of cucurbits from other close families, and through the process of speciation within the family a candidate Vat gene was also identified using sequence previously unavailable, which demonstrates the advantages of genome assembly refinements when analyzing complex regions such as those containing clusters of highly similar genes.

High presence/absence gene variability in defense-related gene clusters of Cucumis melo.

BACKGROUND: Changes in the copy number of DNA sequences are one of the main mechanisms generating genome variability in eukaryotes. These changes are often related to phenotypic effects such as genetic disorders or novel pathogen resistance. The increasing availability of genome sequences through the application of next-generation massive sequencing technologies has allowed the study of genomic polymorphisms at both the interspecific and intraspecific levels, thus helping to understand how species adapt to changing environments through genome variability. RESULTS: Data on gene presence/absence variation (PAV) in melon was obtained by resequencing a cultivated accession and an old-relative melon variety, and using previously obtained resequencing data from three other melon cultivars, among them DHL92, on which the current draft melon genome sequence is based. A total of 1,697 PAV events were detected, involving 4.4% of the predicted melon gene complement. In all, an average 1.5% of genes were absent from each analyzed cultivar as compared to the DHL92 reference genome. The most populated functional category among the 304 PAV genes of known function was that of stress response proteins (30% of all classified PAVs). Our results suggest that genes from multi-copy families are five times more likely to be affected by PAV than singleton genes. Also, the chance of genes present in the genome in tandem arrays being affected by PAV is double that of isolated genes, with PAV genes tending to be in longer clusters. The highest concentration of PAV events detected in the melon genome was found in a 1.1 Mb region of linkage group V, which also shows the highest density of melon stress-response genes. In particular, this region contains the longest continuous gene-containing PAV sequence so far identified in melon. CONCLUSIONS: The first genome-wide report of PAV variation among several melon cultivars is presented here. Multi-copy and clustered genes, especially those with putative stress-response functions, were found to be particularly affected by PAV polymorphisms. As cucurbits are known to possess a significantly lower number of defense-related genes compared to other plant species, PAV variation may play an important role in generating new pathogen resistances at the subspecies level. In addition, these results show the limitations of single reference genome sequences as the only basis for characterization and cloning of resistance genes.

The eTRANSAFE Project on Translational Safety Assessment through Integrative Knowledge Management: Achievements and Perspectives.

eTRANSAFE is a research project funded within the Innovative Medicines Initiative (IMI), which aims at developing integrated databases and computational tools (the eTRANSAFE ToxHub) that support the translational safety assessment of new drugs by using legacy data provided by the pharmaceutical companies that participate in the project. The project objectives include the development of databases containing preclinical and clinical data, computational systems for translational analysis including tools for data query, analysis and visualization, as well as computational models to explain and predict drug safety events.

Genome-wide BAC-end sequencing of Cucumis melo using two BAC libraries.

BACKGROUND: Although melon (Cucumis melo L.) is an economically important fruit crop, no genome-wide sequence information is openly available at the current time. We therefore sequenced BAC-ends representing a total of 33,024 clones, half of them from a previously described melon BAC library generated with restriction endonucleases and the remainder from a new random-shear BAC library. RESULTS: We generated a total of 47,140 high-quality BAC-end sequences (BES), 91.7% of which were paired-BES. Both libraries were assembled independently and then cross-assembled to obtain a final set of 33,372 non-redundant, high-quality sequences. These were grouped into 6,411 contigs (4.5 Mb) and 26,961 non-assembled BES (14.4 Mb), representing ~4.2% of the melon genome. The sequences were used to screen genomic databases, identifying 7,198 simple sequence repeats (corresponding to one microsatellite every 2.6 kb) and 2,484 additional repeats of which 95.9% represented transposable elements. The sequences were also used to screen expressed sequence tag (EST) databases, revealing 11,372 BES that were homologous to ESTs. This suggests that ~30% of the melon genome consists of coding DNA. We observed regions of microsynteny between melon paired-BES and six other dicotyledonous plant genomes. CONCLUSION: The analysis of nearly 50,000 BES from two complementary genomic libraries covered ~4.2% of the melon genome, providing insight into properties such as microsatellite and transposable element distribution, and the percentage of coding DNA. The observed synteny between melon paired-BES and six other plant genomes showed that useful comparative genomic data can be derived through large scale BAC-end sequencing by anchoring a small proportion of the melon genome to other sequenced genomes.

Distinct triterpene synthases in the laticifers of Euphorbia lathyris.

Euphorbia lathyris was proposed about fifty years ago as a potential agroenergetic crop. The tremendous amounts of triterpenes present in its latex has driven investigations for transforming this particular biological fluid into an industrial hydrocarbon source. The huge accumulation of terpenes in the latex of many plant species represent a challenging question regarding cellular homeostasis. In fact, the enzymes, the mechanisms and the controllers that tune the amount of products accumulated in specialized compartments (to fulfill ecological roles) or deposited at important sites (as essential factors) are not known. Here, we have isolated oxidosqualene cyclases highly expressed in the latex of Euphorbia lathyris. This triterpene biosynthetic machinery is made of distinct paralogous enzymes responsible for the massive accumulation of steroidal and non-steroidal tetracyclic triterpenes. More than eighty years after the isolation of butyrospermol from shea butter (Heilbronn IM, Moffet GL, and Spring FS J. Chem. Soc. 1934, 1583), a butyrospermol synthase is characterized in this work using yeast and in folia heterologous expression assays.

The use of massive sequencing to detect differences between immature embryos of MON810 and a comparable non-GM maize variety.

The insect resistant maize YieldGard MON810 was studied to assess the extent to which introduction of a transgene may putatively alter the expression of endogenous genes by comparison of various GM lines vs. their non-transgenic counterparts. To assess the extent to which introduction of a transgene may putatively alter the expression of endogenous genes, GM lines of the insect resistant maize YieldGard MON810 were compared with non-transgenic counterparts. For a more in-depth study, high-throughput deep sequencing together with microarrays were used to compare the transcriptomes of immature embryos of the MON810 variety DKC6575, with a cryIA(b) transgene, and its near-isogenic variety Tietar, grown under controlled environmental conditions. This technique also allows characterisation of the transgenic mRNAs produced. 3'UTR-anchored mRNA-seq produced 1,802,571 sequences from DKC6575 and 1,170,973 from Tietar, which mapped to 14,712 and 14,854 unigenes, respectively. Up to 32 reads from the transgenic embryos matched to the synthetic cry1A(b) sequence, similar to medium-abundant mRNAs. Gene expression analysis, using the R-bioconductor packages EdgeR and DEseq, revealed 140 differentially expressed genes mainly involved in carbohydrate metabolism, protein metabolism and chromatin organisation. Comparison of the expression of 30 selected genes in two additional MON810 and near-isogenic variety pairs showed that most of them were differentially expressed in the three pairs of varieties analysed. Analysis of functional annotation and the precise moment of expression of the differentially expressed genes and physiological data obtained suggest a slight but significant delay in seed and plant maturation of MON810 plants. However, these transcriptomic changes were not associated to undesirable changes in the global phenotype or plant behaviour. Moreover, while most expression changes in MON810 immature embryos were maintained in other transgenic varieties, some gene expression was found to be modulated by the genetic background in which the transgene was introduced through conventional breeding programs.