Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Comparative genomic analyses of multiple backcross mouse populations suggest SGCG as a novel potential obesity-modifier gene.

To nominate novel disease genes for obesity and type 2 diabetes (T2D), we recently generated two mouse backcross populations of the T2D-susceptible New Zealand Obese (NZO/HI) mouse strain and two genetically different, lean and T2D-resistant strains, 129P2/OlaHsd and C3HeB/FeJ. Comparative linkage analysis of our two female backcross populations identified seven novel body fat-associated quantitative trait loci (QTL). Only the locus Nbw14 (NZO body weight on chromosome 14) showed linkage to obesity-related traits in both backcross populations, indicating that the causal gene variant is likely specific for the NZO strain as NZO allele carriers in both crosses displayed elevated body weight and fat mass. To identify candidate genes for Nbw14, we used a combined approach of gene expression and haplotype analysis to filter for NZO-specific gene variants in gonadal white adipose tissue, defined as the main QTL-target tissue. Only two genes, Arl11 and Sgcg, fulfilled our candidate criteria. In addition, expression QTL analysis revealed cis-signals for both genes within the Nbw14 locus. Moreover, retroviral overexpression of Sgcg in 3T3-L1 adipocytes resulted in increased insulin-stimulated glucose uptake. In humans, mRNA levels of SGCG correlated with body mass index and body fat mass exclusively in diabetic subjects, suggesting that SGCG may present a novel marker for metabolically unhealthy obesity. In conclusion, our comparative-cross analysis could substantially improve the mapping resolution of the obesity locus Nbw14. Future studies will throw light on the mechanism by which Sgcg may protect from the development of obesity.

IsoTools: a flexible workflow for long-read transcriptome sequencing analysis.

MOTIVATION: Long-read transcriptome sequencing (LRTS) has the potential to enhance our understanding of alternative splicing and the complexity of this process requires the use of versatile computational tools, with the ability to accommodate various stages of the workflow with maximum flexibility. RESULTS: We introduce IsoTools, a Python-based LRTS analysis framework that offers a wide range of functionality for transcriptome reconstruction and quantification of transcripts. Furthermore, we integrate a graph-based method for identifying alternative splicing events and a statistical approach based on the beta-binomial distribution for detecting differential events. To demonstrate the effectiveness of our methods, we applied IsoTools to PacBio LRTS data of human hepatocytes treated with the histone deacetylase inhibitor valproic acid. Our results indicate that LRTS can provide valuable insights into alternative splicing, particularly in terms of complex and differential splicing patterns, in comparison to short-read RNA-seq. AVAILABILITY AND IMPLEMENTATION: IsoTools is available on GitHub and PyPI, and its documentation, including tutorials, CLI, and API references, can be found at https://isotools.readthedocs.io/.

ConsensusPathDB 2022: molecular interactions update as a resource for network biology.

Molecular interactions are key drivers of biological function. Providing interaction resources to the research community is important since they allow functional interpretation and network-based analysis of molecular data. ConsensusPathDB (http://consensuspathdb.org) is a meta-database combining interactions of diverse types from 31 public resources for humans, 16 for mice and 14 for yeasts. Using ConsensusPathDB, researchers commonly evaluate lists of genes, proteins and metabolites against sets of molecular interactions defined by pathways, Gene Ontology and network neighborhoods and retrieve complex molecular neighborhoods formed by heterogeneous interaction types. Furthermore, the integrated protein-protein interaction network is used as a basis for propagation methods. Here, we present the 2022 update of ConsensusPathDB, highlighting content growth, additional functionality and improved database stability. For example, the number of human molecular interactions increased to 859 848 connecting 200 499 unique physical entities such as genes/proteins, metabolites and drugs. Furthermore, we integrated regulatory datasets in the form of transcription factor-, microRNA- and enhancer-gene target interactions, thus providing novel functionality in the context of overrepresentation and enrichment analyses. We specifically emphasize the use of the integrated protein-protein interaction network as a scaffold for network inferences, present topological characteristics of the network and discuss strengths and shortcomings of such approaches.

Different RONS Generation in MTC-SK and NSCL Cells Lead to Varying Antitumoral Effects of Alpha-Ketoglutarate + 5-HMF.

BACKGROUND: Carbonylated proteins (CPs) serve as specific indicators of increased reactive oxygen and nitrogen species (RONS) production in cancer cells, attributed to the dysregulated mitochondrial energy metabolism known as the Warburg effect. The aim of this study was to investigate the potential of alpha-ketoglutarate (aKG), 5-hydroxymethylfurfural (5-HMF), and their combination as mitochondrial-targeting antioxidants in MTC-SK or NCI-H23 cancer cells. METHODS: MTC-SK and NCI-H23 cells were cultured in the absence or presence of varying concentrations (0-500 µg/mL) of aKG, 5-HMF, and the combined aKG + 5-HMF solutions. After 0, 24, 48, and 72 h, mitochondrial activity, cancer cell membrane CP levels, cell growth, and caspase-3 activity were assessed in aliquots of MTC-SK and NCI-H23 cells. RESULTS: The mitochondrial activity of MTC-SK cells exhibited a concentration- and time-dependent reduction upon treatment with aKG, 5-HMF, or the combined aKG + 5-HMF. The half-maximal inhibitory concentration (IC50%) for mitochondrial activity was achieved at 500 µg/mL aKG, 200 µg/mL 5-HMF, and 200 µg/mL aKG + 66.7 µg/mL 5-HMF after 72 h. In contrast, NCI-H23 cells showed a minimal reduction (10%) in mitochondrial activity even at the highest combined concentration of aKG + 5-HMF. The CP levels in MTC-SK cells were measured at 8.7 nmol/mg protein, while NCI-H23 cells exhibited CP levels of 1.4 nmol/mg protein. The combination of aKG + 5-HMF led to a decrease in CP levels specifically in MTC-SK cells. The correlation between mitochondrial activity and CP levels in the presence of different concentrations of combined aKG + 5-HMF in MTC-SK cells demonstrated a linear and concentration-dependent decline in CP levels and mitochondrial activity. Conversely, the effect was less pronounced in NCI-H23 cells. Cell growth of MTC-CK cells was reduced to 60% after 48 h and maintained at 50% after 72 h incubation when treated with 500 µg/mL aKG (IC50%). Addition of 500 µg/mL 5-HMF inhibited cell growth completely regardless of the incubation time. The IC50% for 5-HMF on MTC-CK cell growth was calculated at 375 µg/mL after 24 h incubation and 200 µg/mL 5-HMF after 72 h. MTC-SK cells treated with 500 µg/mL aKG + 167 µg/mL 5-HMF showed no cell growth. The calculated IC50% for the combined substances was 250 µg/mL aKG + 83.3 µg/mL 5-HMF (48 h incubation) and 200 µg/mL aKG + 66.7 µg/mL 5-HMF (72 h incubation). None of the tested concentrations of aKG, 5-HMF, or the combined solution had any effect on NCI-H23 cell growth at any incubation time. Caspase-3 activity increased to 21% in MTC-CK cells in the presence of 500 µg/mL aKG, while an increase to 59.6% was observed using 500 µg/mL 5-HMF. The combination of 500 µg/mL aKG + 167.7 µg/mL 5-HMF resulted in a caspase-3 activity of 55.2%. No caspase-3 activation was observed in NCI-H23 cells when treated with aKG, 5-HMF, or the combined solutions. CONCLUSION: CPs may serve as potential markers for distinguishing between cancer cells regulated by RONS. The combination of aKG + 5-HMF showed induced cell death in high-RONS-generating cancer cells compared to low-RONS-generating cancer cells.

E96V Mutation in the Kdelr3 Gene Is Associated with Type 2 Diabetes Susceptibility in Obese NZO Mice.

Type 2 diabetes (T2D) represents a multifactorial metabolic disease with a strong genetic predisposition. Despite elaborate efforts in identifying the genetic variants determining individual susceptibility towards T2D, the majority of genetic factors driving disease development remain poorly understood. With the aim to identify novel T2D risk genes we previously generated an N2 outcross population using the two inbred mouse strains New Zealand obese (NZO) and C3HeB/FeJ (C3H). A linkage study performed in this population led to the identification of the novel T2D-associated quantitative trait locus (QTL) Nbg15 (NZO blood glucose on chromosome 15, Logarithm of odds (LOD) 6.6). In this study we used a combined approach of positional cloning, gene expression analyses and in silico predictions of DNA polymorphism on gene/protein function to dissect the genetic variants linking Nbg15 to the development of T2D. Moreover, we have generated congenic strains that associated the distal sublocus of Nbg15 to mechanisms altering pancreatic beta cell function. In this sublocus, Cbx6, Fam135b and Kdelr3 were nominated as potential causative genes associated with the Nbg15 driven effects. Moreover, a putative mutation in the Kdelr3 gene from NZO was identified, negatively influencing adaptive responses associated with pancreatic beta cell death and induction of endoplasmic reticulum stress. Importantly, knockdown of Kdelr3 in cultured Min6 beta cells altered insulin granules maturation and pro-insulin levels, pointing towards a crucial role of this gene in islets function and T2D susceptibility.

NetCore: a network propagation approach using node coreness.

We present NetCore, a novel network propagation approach based on node coreness, for phenotype-genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.

Alpha-Ketoglutarate or 5-HMF: Single Compounds Effectively Eliminate Leukemia Cells via Caspase-3 Apoptosis and Antioxidative Pathways.

BACKGROUND: We recently showed that a combined solution containing alpha-ketoglutarate (aKG) and 5-hydroxymethyl-furfural (5-HMF) has a solid antitumoral effect on the Jurkat cell line due to the fact of its antioxidative, caspase-3 and apoptosis activities, but no negative effect on human fibroblasts was obtained. The question arises how the single compounds, aKG and 5-HMF, affect peroxynitrite (ONOO-) and nitration of tyrosine residues, Jurkat cell proliferation and caspase-activated apoptosis. METHODS: The ONOO- luminol-induced chemiluminescence reaction was used to measure the ONOO- scavenging function of aKG or 5-HMF, and their protection against nitration of tyrosine residues on bovine serum albumin was estimated with the ELISA technique. The Jurkat cell line was cultivated in the absence or presence of aKG or 5-HMF solutions between 0 and 3.5 µM aKG or 0 and 4 µM 5-HMF. Jurkat cells were tested for cell proliferation, mitochondrial activity and caspase-activated apoptosis. RESULTS: aKG showed a concentration-dependent reduction in ONOO-, resulting in a 90% elimination of ONOO- using 200 mM aKG. In addition, 20 and 200 mM 5-HMF were able to reduce ONOO- only by 20%, while lower concentrations of 5-HMF remained stable in the presence of ONOO-. Nitration of tyrosine residues was inhibited 4 fold more effectively with 5-HMF compared to aKG measuring the IC50%. Both substances, aKG and 5-HMF, were shown to cause a reduction in Jurkat cell growth that was dependent on the dose and incubation time. The aKG effectively reduced Jurkat cell growth down to 50% after 48 and 72 h of incubation using the highest concentration of 3.5 µM, and 1, 1.6, 2, 3 and 4 µM 5-HMF inhibited any cell growth within (i) 24 h; 1.6, 2, 3 and 4 µM 5-HMF within 48 h (ii); 2, 3 and 4 µM 5-HMF within 72 h (iii). Furthermore, 4 µM was able to eliminate the starting cell number of 20,000 cells after 48 and 72 h down to 11,233 cells. The mitochondrial activity measurements supported the data on aKG or 5-HMF regarding cell growth in Jurkat cells, in both a dose- and incubation-time-dependent manner: the highest concentration of 3.5 µM aKG reduced the mitochondrial activity over 24 h (67.7%), 48 h (57.9%) and 72 h (46.8%) of incubation with Jurkat cells compared to the control incubation without aKG (100%). 5-HMF was more effective compared to aKG; the mitochondrial activity in the presence of 4 µM 5-HMF decreased after 24 h down to 68.4%, after 48 h to 42.9% and after 72 h to 32.0%. Moreover, 1.7 and 3.4 µM aKG had no effect on caspase-3-activated apoptosis (0.58% and 0.56%) in the Jurkat cell line. However, 2 and 4 µM 5-HMF increased the caspase-3-activated apoptosis up to 22.1% and 42.5% compared to the control (2.9%). A combined solution of 1.7 µM aKG + 0.7 µM 5-HMF showed a higher caspase-3-activated apoptosis (15.7%) compared to 1.7 µM aKG or 2 µM 5-HMF alone. In addition, 3.5 µM µg/mL aKG + 1.7 µM 5-HMF induced caspase-activated apoptosis up to 55.6% compared to 4.5% or 35.6% caspase-3 activity using 3.5 µM aKG or 4 µM 5-HMF. CONCLUSION: Both substances showed high antioxidative potential in eliminating either peroxynitrite or nitration of tyrosine residues, which results in a better inhibition of cell growth and mitochondrial activity of 5-HMF compared to aKG. However, caspase-3-activated apoptosis measurements revealed that the combination of both substances synergistically is the most effective compared to single compounds.

Alternative exon splicing and differential expression in pancreatic islets reveals candidate genes and pathways implicated in early diabetes development.

Type 2 diabetes (T2D) has a strong genetic component. Most of the gene variants driving the pathogenesis of T2D seem to target pancreatic ß-cell function. To identify novel gene variants acting at early stage of the disease, we analyzed whole transcriptome data to identify differential expression (DE) and alternative exon splicing (AS) transcripts in pancreatic islets collected from two metabolically diverse mouse strains at 6 weeks of age after three weeks of high-fat-diet intervention. Our analysis revealed 1218 DE and 436 AS genes in islets from NZO/Hl vs C3HeB/FeJ. Whereas some of the revealed genes present well-established markers for ß-cell failure, such as Cd36 or Aldh1a3, we identified numerous DE/AS genes that have not been described in context with ß-cell function before. The gene Lgals2, previously associated with human T2D development, was DE as well as AS and localizes in a quantitative trait locus (QTL) for blood glucose on Chr.15 that we reported recently in our N2(NZOxC3H) population. In addition, pathway enrichment analysis of DE and AS genes showed an overlap of only half of the revealed pathways, indicating that DE and AS in large parts influence different pathways in T2D development. PPARG and adipogenesis pathways, two well-established metabolic pathways, were overrepresented for both DE and AS genes, probably as an adaptive mechanism to cope for increased cellular stress. Our results provide guidance for the identification of novel T2D candidate genes and demonstrate the presence of numerous AS transcripts possibly involved in islet function and maintenance of glucose homeostasis.

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types.

BACKGROUND: There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. METHODS: In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. RESULTS: We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap . CONCLUSIONS: Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.

Significant abundance of cis configurations of coding variants in diploid human genomes.

To fully understand human genetic variation and its functional consequences, the specific distribution of variants between the two chromosomal homologues of genes must be known. The 'phase' of variants can significantly impact gene function and phenotype. To assess patterns of phase at large scale, we have analyzed 18 121 autosomal genes in 1092 statistically phased genomes from the 1000 Genomes Project and 184 experimentally phased genomes from the Personal Genome Project. Here we show that genes with cis-configurations of coding variants are more frequent than genes with trans-configurations in a genome, with global cis/trans ratios of ∼60:40. Significant cis-abundance was observed in virtually all genomes in all populations. Moreover, we identified a large group of genes exhibiting cis-configurations of protein-changing variants in excess, so-called 'cis-abundant genes', and a smaller group of 'trans-abundant genes'. These two gene categories were functionally distinguishable, and exhibited strikingly different distributional patterns of protein-changing variants. Underlying these phenomena was a shared set of phase-sensitive genes of importance for adaptation and evolution. This work establishes common patterns of phase as key characteristics of diploid human exomes and provides evidence for their functional significance, highlighting the importance of phase for the interpretation of protein-coding genetic variation and gene function.

Altered DNA Methylation Profiles in SF3B1 Mutated CLL Patients.

Mutations in splicing factor genes have a severe impact on the survival of cancer patients. Splicing factor 3b subunit 1 (SF3B1) is one of the most frequently mutated genes in chronic lymphocytic leukemia (CLL); patients carrying these mutations have a poor prognosis. Since the splicing machinery and the epigenome are closely interconnected, we investigated whether these alterations may affect the epigenomes of CLL patients. While an overall hypomethylation during CLL carcinogenesis has been observed, the interplay between the epigenetic stage of the originating B cells and SF3B1 mutations, and the subsequent effect of the mutations on methylation alterations in CLL, have not been investigated. We profiled the genome-wide DNA methylation patterns of 27 CLL patients with and without SF3B1 mutations and identified local decreases in methylation levels in SF3B1mut CLL patients at 67 genomic regions, mostly in proximity to telomeric regions. These differentially methylated regions (DMRs) were enriched in gene bodies of cancer-related signaling genes, e.g., NOTCH1, HTRA3, and BCL9L. In our study, SF3B1 mutations exclusively emerged in two out of three epigenetic stages of the originating B cells. However, not all the DMRs could be associated with the methylation programming of B cells during development, suggesting that mutations in SF3B1 cause additional epigenetic aberrations during carcinogenesis.

Genetics of intellectual disability in consanguineous families.

Autosomal recessive (AR) gene defects are the leading genetic cause of intellectual disability (ID) in countries with frequent parental consanguinity, which account for about 1/7th of the world population. Yet, compared to autosomal dominant de novo mutations, which are the predominant cause of ID in Western countries, the identification of AR-ID genes has lagged behind. Here, we report on whole exome and whole genome sequencing in 404 consanguineous predominantly Iranian families with two or more affected offspring. In 219 of these, we found likely causative variants, involving 77 known and 77 novel AR-ID (candidate) genes, 21 X-linked genes, as well as 9 genes previously implicated in diseases other than ID. This study, the largest of its kind published to date, illustrates that high-throughput DNA sequencing in consanguineous families is a superior strategy for elucidating the thousands of hitherto unknown gene defects underlying AR-ID, and it sheds light on their prevalence.

Effective Increase of Serum Vitamin D3 by IV Application of a Cholecalciferol-N-Acetyl-Galactosamine-Stabilized Dimer: a Clinical Murine Trial Study.

BACKGROUND: Pre-clinical toxicology studies of human Gc-protein (vitamin D binding protein) are of special interest as to the transport of vitamin D and its biological activities. We have demonstrated that the oral application of a special dimeric vitamin D complex reduces oxidative stress and increases the quality of life in autistic children. Therefore, safety and toxic effects of two dimeric cholecalciferol-N-acetyl-galactosamine-albumin complexes were evaluated in increasing intravenous (iv.) vitamin D levels administered in a pre-clinical trial in mice over a 5-week period. METHODS: Over a period of 5 weeks, two times a week, mice received iv. administration of one of the following: (a) 1.2 IE of vitamin D-N-acetyl-galactosamine-albumin (Vitamin D3 NAGA, ImmunoD® group), (b) 1.2 IE of vitamin-D-poly-N-acetyl-galactosamine-albumin (Poly-Nac group), or (c) isotonic saline solution (sham group). Before and after the trial, red and white blood cell panels (RBS, WBC and platelets) were determined. Furthermore, vitamin D levels, electrolytes, and C-reactive protein levels were measured directly before sacrificing. RESULTS: No toxic effects were observed during iv. injection with dimeric vitamin D complexes, neither in the sham group, nor in the two treatment groups. Vitamin D levels increased significantly within 5 weeks in the Poly-Nac group (26.6 ± 8.8 ng/mL; p = 0.001) compared to the sham group (3.1 ± 0.9 ng/mL), and the Poly-Nac group to the ImmunoD group (7.0 ± 3.6 ng/mL; p = 0.003). A significant increase of vitamin D was also obtained in favor of the ImmunoD group compared to the sham (p = 0.03). Electrolytes (K, Na, Cl, Mg, Ca) and C-reactive protein showed no significant differences after administration in all three mice groups. Also, no significant differences were observed between these three groups in the WBC and RBC blood panels. CONCLUSIONS: The two dimeric vitamin D complexes used in this pre-clinical study showed no side or toxic effects after iv. administration in mice, but a sole increase in vitamin D levels without any change in electrolytes or blood cells. Therefore, we assume this newly developed composition to be safe in oral or iv.-administration and further pre-clinical studies can be conducted to evaluate the value in treatment of various diseases related to vitamin D deficiencies.

QSEA-modelling of genome-wide DNA methylation from sequencing enrichment experiments.

Genome-wide enrichment of methylated DNA followed by sequencing (MeDIP-seq) offers a reasonable compromise between experimental costs and genomic coverage. However, the computational analysis of these experiments is complex, and quantification of the enrichment signals in terms of absolute levels of methylation requires specific transformation. In this work, we present QSEA, Quantitative Sequence Enrichment Analysis, a comprehensive workflow for the modelling and subsequent quantification of MeDIP-seq data. As the central part of the workflow we have developed a Bayesian statistical model that transforms the enrichment read counts to absolute levels of methylation and, thus, enhances interpretability and facilitates comparison with other methylation assays. We suggest several calibration strategies for the critical parameters of the model, either using additional data or fairly general assumptions. By comparing the results with bisulfite sequencing (BS) validation data, we show the improvement of QSEA over existing methods. Additionally, we generated a clinically relevant benchmark data set consisting of methylation enrichment experiments (MeDIP-seq), BS-based validation experiments (Methyl-seq) as well as gene expression experiments (RNA-seq) derived from non-small cell lung cancer patients, and show that the workflow retrieves well-known lung tumour methylation markers that are causative for gene expression changes, demonstrating the applicability of QSEA for clinical studies. QSEA is implemented in R and available from the Bioconductor repository 3.4 (www.bioconductor.org/packages/qsea).

diXa: a data infrastructure for chemical safety assessment.

MOTIVATION: The field of toxicogenomics (the application of '-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. RESULTS: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. AVAILABILITY AND IMPLEMENTATION: http://www.dixa-fp7.eu CONTACT: d.hendrickx@maastrichtuniversity.nl; info@dixa-fp7.eu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ARH-seq: identification of differential splicing in RNA-seq data.

The computational prediction of alternative splicing from high-throughput sequencing data is inherently difficult and necessitates robust statistical measures because the differential splicing signal is overlaid by influencing factors such as gene expression differences and simultaneous expression of multiple isoforms amongst others. In this work we describe ARH-seq, a discovery tool for differential splicing in case-control studies that is based on the information-theoretic concept of entropy. ARH-seq works on high-throughput sequencing data and is an extension of the ARH method that was originally developed for exon microarrays. We show that the method has inherent features, such as independence of transcript exon number and independence of differential expression, what makes it particularly suited for detecting alternative splicing events from sequencing data. In order to test and validate our workflow we challenged it with publicly available sequencing data derived from human tissues and conducted a comparison with eight alternative computational methods. In order to judge the performance of the different methods we constructed a benchmark data set of true positive splicing events across different tissues agglomerated from public databases and show that ARH-seq is an accurate, computationally fast and high-performing method for detecting differential splicing events.

DNA-methylome analysis of mouse intestinal adenoma identifies a tumour-specific signature that is partly conserved in human colon cancer.

Aberrant CpG methylation is a universal epigenetic trait of cancer cell genomes. However, human cancer samples or cell lines preclude the investigation of epigenetic changes occurring early during tumour development. Here, we have used MeDIP-seq to analyse the DNA methylome of APC(Min) adenoma as a model for intestinal cancer initiation, and we present a list of more than 13,000 recurring differentially methylated regions (DMRs) characterizing intestinal adenoma of the mouse. We show that Polycomb Repressive Complex (PRC) targets are strongly enriched among hypermethylated DMRs, and several PRC2 components and DNA methyltransferases were up-regulated in adenoma. We further demonstrate by bisulfite pyrosequencing of purified cell populations that the DMR signature arises de novo in adenoma cells rather than by expansion of a pre-existing pattern in intestinal stem cells or undifferentiated crypt cells. We found that epigenetic silencing of tumour suppressors, which occurs frequently in colon cancer, was rare in adenoma. Quite strikingly, we identified a core set of DMRs, which is conserved between mouse adenoma and human colon cancer, thus possibly revealing a global panel of epigenetically modified genes for intestinal tumours. Our data allow a distinction between early conserved epigenetic alterations occurring in intestinal adenoma and late stochastic events promoting colon cancer progression, and may facilitate the selection of more specific clinical epigenetic biomarkers.