Ten simple rules for computational biologists collaborating with wet lab researchers.

Computational biologists are frequently engaged in collaborative data analysis with wet lab researchers. These interdisciplinary projects, as necessary as they are to the scientific endeavor, can be surprisingly challenging due to cultural differences in operations and values. In this Ten Simple Rules guide, we aim to help dry lab researchers identify sources of friction and provide actionable tools to facilitate respectful, open, transparent, and rewarding collaborations.

A model of human neural networks reveals NPTX2 pathology in ALS and FTLD.

Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms2-5 that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors6. Single-cell transcriptomics and comparison to independent neural stem cells7 showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids8. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3' untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.

Loss of TDP-43 oligomerization or RNA binding elicits distinct aggregation patterns.

Aggregation of the RNA-binding protein TAR DNA-binding protein 43 (TDP-43) is the key neuropathological feature of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). In physiological conditions, TDP-43 is predominantly nuclear, forms oligomers, and is contained in biomolecular condensates assembled by liquid-liquid phase separation (LLPS). In disease, TDP-43 forms cytoplasmic or intranuclear inclusions. How TDP-43 transitions from physiological to pathological states remains poorly understood. Using a variety of cellular systems to express structure-based TDP-43 variants, including human neurons and cell lines with near-physiological expression levels, we show that oligomerization and RNA binding govern TDP-43 stability, splicing functionality, LLPS, and subcellular localization. Importantly, our data reveal that TDP-43 oligomerization is modulated by RNA binding. By mimicking the impaired proteasomal activity observed in ALS/FTLD patients, we found that monomeric TDP-43 forms inclusions in the cytoplasm, whereas its RNA binding-deficient counterpart aggregated in the nucleus. These differentially localized aggregates emerged via distinct pathways: LLPS-driven aggregation in the nucleus and aggresome-dependent inclusion formation in the cytoplasm. Therefore, our work unravels the origins of heterogeneous pathological species reminiscent of those occurring in TDP-43 proteinopathy patients.

Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability.

Computational methods represent the lifeblood of modern molecular biology. Benchmarking is important for all methods, but with a focus here on computational methods, benchmarking is critical to dissect important steps of analysis pipelines, formally assess performance across common situations as well as edge cases, and ultimately guide users on what tools to use. Benchmarking can also be important for community building and advancing methods in a principled way. We conducted a meta-analysis of recent single-cell benchmarks to summarize the scope, extensibility, and neutrality, as well as technical features and whether best practices in open data and reproducible research were followed. The results highlight that while benchmarks often make code available and are in principle reproducible, they remain difficult to extend, for example, as new methods and new ways to assess methods emerge. In addition, embracing containerization and workflow systems would enhance reusability of intermediate benchmarking results, thus also driving wider adoption.

Flanking sequence preference modulates de novo DNA methylation in the mouse genome.

Mammalian de novo DNA methyltransferases (DNMT) are responsible for the establishment of cell-type-specific DNA methylation in healthy and diseased tissues. Through genome-wide analysis of de novo methylation activity in murine stem cells we uncover that DNMT3A prefers to methylate CpGs followed by cytosines or thymines, while DNMT3B predominantly methylates CpGs followed by guanines or adenines. These signatures are further observed at non-CpG sites, resembling methylation context observed in specialised cell types, including neurons and oocytes. We further show that these preferences result from structural differences in the catalytic domains of the two de novo DNMTs and are not a consequence of differential recruitment to the genome. Molecular dynamics simulations suggest that, in case of human DNMT3A, the preference is due to favourable polar interactions between the flexible Arg836 side chain and the guanine that base-pairs with the cytosine following the CpG. By exchanging arginine to a lysine, the corresponding side chain in DNMT3B, the sequence preference is reversed, confirming the requirement for arginine at this position. This context-dependent enzymatic activity provides additional insights into the complex regulation of DNA methylation patterns.

Long-term self-renewing stem cells in the adult mouse hippocampus identified by intravital imaging.

Neural stem cells (NSCs) generate neurons throughout life in the mammalian hippocampus. However, the potential for long-term self-renewal of individual NSCs within the adult brain remains unclear. We used two-photon microscopy and followed NSCs that were genetically labeled through conditional recombination driven by the regulatory elements of the stem cell-expressed genes GLI family zinc finger 1 (Gli1) or achaete-scute homolog 1 (Ascl1). Through intravital imaging of NSCs and their progeny, we identify a population of Gli1-targeted NSCs showing long-term self-renewal in the adult hippocampus. In contrast, once activated, Ascl1-targeted NSCs undergo limited proliferative activity before they become exhausted. Using single-cell RNA sequencing, we show that Gli1- and Ascl1-targeted cells have highly similar yet distinct transcriptional profiles, supporting the existence of heterogeneous NSC populations with diverse behavioral properties. Thus, we here identify long-term self-renewing NSCs that contribute to the generation of new neurons in the adult hippocampus.

Tissue and cancer-specific expression of DIEXF is epigenetically mediated by an Alu repeat.

Alu repeats constitute a major fraction of human genome and for a small subset of them a role in gene regulation has been described. The number of studies focused on the functional characterization of particular Alu elements is very limited. Most Alu elements are DNA methylated and then assumed to lie in repressed chromatin domains. We hypothesize that Alu elements with low or variable DNA methylation are candidates for a functional role. In a genome-wide study in normal and cancer tissues, we pinpointed an Alu repeat (AluSq2) with differential methylation located upstream of the promoter region of the DIEXF gene. DIEXF encodes a highly conserved factor essential for the development of zebrafish digestive tract. To characterize the contribution of the Alu element to the regulation of DIEXF we analysed the epigenetic landscapes of the gene promoter and flanking regions in different cell types and cancers. Alternate epigenetic profiles (DNA methylation and histone modifications) of the AluSq2 element were associated with DIEXF transcript diversity as well as protein levels, while the epigenetic profile of the CpG island associated with the DIEXF promoter remained unchanged. These results suggest that AluSq2 might directly contribute to the regulation of DIEXF transcription and protein expression. Moreover, AluSq2 was DNA hypomethylated in different cancer types, pointing out its putative contribution to DIEXF alteration in cancer and its potential as tumoural biomarker.

Aging-like Spontaneous Epigenetic Silencing Facilitates Wnt Activation, Stemness, and BrafV600E-Induced Tumorigenesis.

We addressed the precursor role of aging-like spontaneous promoter DNA hypermethylation in initiating tumorigenesis. Using mouse colon-derived organoids, we show that promoter hypermethylation spontaneously arises in cells mimicking the human aging-like phenotype. The silenced genes activate the Wnt pathway, causing a stem-like state and differentiation defects. These changes render aged organoids profoundly more sensitive than young ones to transformation by BrafV600E, producing the typical human proximal BRAFV600E-driven colon adenocarcinomas characterized by extensive, abnormal gene-promoter CpG-island methylation, or the methylator phenotype (CIMP). Conversely, CRISPR-mediated simultaneous inactivation of a panel of the silenced genes markedly sensitizes to BrafV600E-induced transformation. Our studies tightly link aging-like epigenetic abnormalities to intestinal cell fate changes and predisposition to oncogene-driven colon tumorigenesis.

The Pancancer DNA Methylation Trackhub: A Window to The Cancer Genome Atlas Epigenomics Data.

The Cancer Genome Atlas (TCGA) epigenome data includes the DNA methylation status of tumor and normal tissues of large cohorts for dozens of cancer types. Due to the moderately large data sizes, retrieving and analyzing them requires basic programming skills. Simple data browsing (e.g., candidate gene search) is hampered by the scarcity of easy-to-use data browsers addressed to the broad community of biomedical researchers. We propose a new visualization method depicting the overall DNA methylation status at each TCGA cohort while emphasizing its heterogeneity, thus facilitating the evaluation of the cohort variability and the normal versus tumor differences. Implemented as a trackhub integrated to the University of California Santa Cruz (UCSC) genome browser, it can be easily added to any genome-wide annotation layer.To exemplify the trackhub usage we evaluate local DNA methylation boundaries, the aberrant DNA methylation of a CpG island located at the estrogen receptor 1 (ESR1) in breast and colon cancer, and the hypermethylation of the Homeobox HOXA gene cluster and the EN1 gene in multiple cancer types. The DNA methylation pancancer trackhub is freely available at http://maplab.cat/tcga_450k_trackhub .

Kallikreins Stepwise Scoring Reveals Three Subtypes of Papillary Thyroid Cancer with Prognostic Implications.

BACKGROUND: Papillary thyroid cancer (PTC) is the most common type of thyroid cancer. Unlike most cancers, its incidence has dramatically increased in the last decades mainly due to increased diagnosis of indolent PTCs. Adequate risk stratification is crucial to avoid the over-treatment of low-risk patients, as well as the under-treatment of high-risk patients, but the currently available markers are still insufficient. Kallikreins (KLKs) are emergent biomarkers in cancer, but their involvement in PTC is unknown. METHODS: This study analyzed DNA methylation (HumanMethylation arrays) and gene expression (RNA-Seq) of KLKs, BRAF and RAS mutations, and clinical data from four published thyroid cancer data sets including normal and tumor tissues (n = 73, n = 475, n = 20, and n = 82) as discovery, training, and validation series. The C4.5 classification algorithm was used to generate a decision tree. Disease-free survival was estimated using Kaplan-Meier and Cox approaches. Specific analyses were performed using real-time polymerase chain reaction and immunohistochemistry. RESULTS: The entire KLK family was deregulated in PTC, displaying a specific epigenetic and transcriptional profile strongly associated with BRAFV600E or RAS mutations. Thus, a decision-tree algorithm was developed based on three KLKs with >80% sensitivity and >95% specificity, identifying BRAF- and RAS-mutated tumors. Notably, tumors lacking these mutations were classified as BRAF- or RAS-like. Most importantly, the KLK algorithm uncovered a novel PTC subtype showing favorable prognostic features. CONCLUSIONS: The KLK algorithm could lead to a new clinically applicable strategy with important implications for the risk stratification of PTC and the management of patients.

Chainy: an universal tool for standardized relative quantification in real-time PCR.

Summary: Chainy is a cross-platform web tool providing systematic pipelines and steady criteria to process real-time PCR data, including the calculation of efficiencies from raw data by kinetic methods, evaluation of the suitability of multiple references, standardized normalization using one or more references, and group-wise relative quantification statistical testing. We illustrate the utility of Chainy for differential expression and chromatin immunoprecipitation enrichment (ChIP-QPCR) analysis. Availability and Implementation: Chainy is open source and freely available at http://maplab.cat/chainy. Contact: imallona@igtp.cat. Supplementary information: Supplementary data are available at Bioinformatics online.

Truke, a web tool to check for and handle excel misidentified gene symbols.

BACKGROUND: Genomic datasets accompanying scientific publications show a surprisingly high rate of gene name corruption. This error is generated when files and tables are imported into Microsoft Excel and certain gene symbols are automatically converted into dates. RESULTS: We have developed Truke, a fexible Web tool to detect, tag and fix, if possible, such misconversions. Aside, Truke is language and regional locale-aware, providing file format customization (decimal symbol, field sepator, etc.) following user's preferences. CONCLUSIONS: Truke is a data format conversion tool with a unique corrupted gene symbol detection utility. Truke is freely available without registration at http://maplab.cat/truke .

The epigenetic landscape of Alu repeats delineates the structural and functional genomic architecture of colon cancer cells.

Cancer cells exhibit multiple epigenetic changes with prominent local DNA hypermethylation and widespread hypomethylation affecting large chromosomal domains. Epigenome studies often disregard the study of repeat elements owing to technical complexity and their undefined role in genome regulation. We have developed NSUMA (Next-generation Sequencing of UnMethylated Alu), a cost-effective approach allowing the unambiguous interrogation of DNA methylation in more than 130,000 individual Alu elements, the most abundant retrotransposon in the human genome. DNA methylation profiles of Alu repeats have been analyzed in colon cancers and normal tissues using NSUMA and whole-genome bisulfite sequencing. Normal cells show a low proportion of unmethylated Alu (1%-4%) that may increase up to 10-fold in cancer cells. In normal cells, unmethylated Alu elements tend to locate in the vicinity of functionally rich regions and display epigenetic features consistent with a direct impact on genome regulation. In cancer cells, Alu repeats are more resistant to hypomethylation than other retroelements. Genome segmentation based on high/low rates of Alu hypomethylation allows the identification of genomic compartments with differential genetic, epigenetic, and transcriptomic features. Alu hypomethylated regions show low transcriptional activity, late DNA replication, and its extent is associated with higher chromosomal instability. Our analysis demonstrates that Alu retroelements contribute to define the epigenetic landscape of normal and cancer cells and provides a unique resource on the epigenetic dynamics of a principal, but largely unexplored, component of the primate genome.

A knowledgebase of the human Alu repetitive elements.

Alu elements are the most abundant retrotransposons in the human genome with more than one million copies. Alu repeats have been reported to participate in multiple processes related with genome regulation and compartmentalization. Moreover, they have been involved in the facilitation of pathological mutations in many diseases, including cancer. The contribution of Alus and other repeats in genomic regulation is often overlooked because their study poses technical and analytical challenges hardly attainable with conventional strategies. Here we propose the integration of ontology-based semantic methods to query a knowledgebase for the human Alus. The knowledgebase for the human Alus leverages Sequence (SO) and Gene Ontologies (GO) and is devoted to address functional and genetic information in the genomic context of the Alus. For each Alu element, the closest gene and transcript are stored, as well their functional annotation according to GO, the state of the chromatin and the transcription factors binding sites inside the Alu. The model uses Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL). As a case of use and to illustrate the utility of the tool, we have evaluated the epigenetic states of Alu repeats associated with gene promoters according to their transcriptional activity. The ontology is easily extendable, offering a scaffold for the inclusion of new experimental data. The RDF/XML formalization is freely available at http://aluontology.sourceforge.net/.

Quantification of unmethylated Alu (QUAlu): a tool to assess global hypomethylation in routine clinical samples.

Hypomethylation of DNA is a hallmark of cancer and its analysis as tumor biomarker has been proposed, but its determination in clinical settings is hampered by lack of standardized methodologies. Here, we present QUAlu (Quantification of Unmethylated Alu), a new technique to estimate the Percentage of UnMethylated Alu (PUMA) as a surrogate for global hypomethylation. QUAlu consists in the measurement by qPCR of Alu repeats after digestion of genomic DNA with isoschizomers with differential sensitivity to DNA methylation. QUAlu performance has been evaluated for reproducibility, trueness and specificity, and validated by deep sequencing. As a proof of use, QUAlu has been applied to a broad variety of pathological examination specimens covering five cancer types. Major findings of the preliminary application of QUAlu to clinical samples include: (1) all normal tissues displayed similar PUMA; (2) tumors showed variable PUMA with the highest levels in lung and colon and the lowest in thyroid cancer; (3) stools from colon cancer patients presented higher PUMA than those from control individuals; (4) lung squamous cell carcinomas showed higher PUMA than lung adenocarcinomas, and an increasing hypomethylation trend associated with smoking habits. In conclusion, QUAlu is a simple and robust method to determine Alu hypomethylation in human biospecimens and may be easily implemented in research and clinical settings.

Wanderer, an interactive viewer to explore DNA methylation and gene expression data in human cancer.

BACKGROUND: The Cancer Genome Atlas (TCGA) offers a multilayered view of genomics and epigenomics data of many human cancer types. However, the retrieval of expression and methylation data from TCGA is a cumbersome and time-consuming task. RESULTS: Wanderer is an intuitive Web tool allowing real time access and visualization of gene expression and DNA methylation profiles from TCGA. Given a gene query and selection of a TCGA dataset (e.g., colon adenocarcinomas), the Web resource provides the expression profile, at the single exon level, and the DNA methylation levels of HumanMethylation450 BeadChip loci inside or in the vicinity of the queried gene. Graphic and table outputs include individual and summary data as well as statistical tests, allowing the comparison of tumor and normal profiles and the exploration along the genomic locus and across tumor collections. CONCLUSIONS: Wanderer offers a simple interface to straightforward access to TCGA data, amenable to experimentalists and clinicians without bioinformatics expertise. Wanderer may be accessed at http://maplab.cat/wanderer.

Deconstruction of DNA methylation patterns during myogenesis reveals specific epigenetic events in the establishment of the skeletal muscle lineage.

The progressive restriction of differentiation potential from pluripotent embryonic stem cells (ESCs) to tissue-specific stem cells involves widespread epigenetic reprogramming, including modulation of DNA methylation patterns. Skeletal muscle stem cells are required for the growth, maintenance, and regeneration of skeletal muscle. To investigate the contribution of DNA methylation to the establishment of the myogenic program, we analyzed ESCs, skeletal muscle stem cells in proliferating (myoblasts) and differentiating conditions (myotubes), and mature myofibers. About 1.000 differentially methylated regions were identified during muscle-lineage determination and terminal differentiation, mainly located in gene bodies and intergenic regions. As a whole, myogenic stem cells showed a gain of DNA methylation, while muscle differentiation was accompanied by loss of DNA methylation in CpG-poor regions. Notably, the hypomethylated regions in myogenic stem cells were neighbored by enhancer-type chromatin, suggesting the involvement of DNA methylation in the regulation of cell-type specific enhancers. Interestingly, we demonstrated the hypomethylation of the muscle cell-identity Myf5 super-enhancer only in muscle cells. Furthermore, we observed that upstream stimulatory factor 1 binding to Myf5 super-enhancer occurs upon DNA demethylation in myogenic stem cells. Taken altogether, we characterized the unique DNA methylation signature of skeletal muscle stem cells and highlighted the importance of DNA methylation-mediated regulation of cell identity Myf5 super-enhancer during cellular differentiation.

Methylation plotter: a web tool for dynamic visualization of DNA methylation data.

Methylation plotter is a Web tool that allows the visualization of methylation data in a user-friendly manner and with publication-ready quality. The user is asked to introduce a file containing the methylation status of a genomic region. This file can contain up to 100 samples and 100 CpGs. Optionally, the user can assign a group for each sample (i.e. whether a sample is a tumoral or normal tissue). After the data upload, the tool produces different graphical representations of the results following the most commonly used styles to display this type of data. They include an interactive plot that summarizes the status of every CpG site and for every sample in lollipop or grid styles. Methylation values ranging from 0 (unmethylated) to 1 (fully methylated) are represented using a gray color gradient. A practical feature of the tool allows the user to choose from different types of arrangement of the samples in the display: for instance, sorting by overall methylation level, by group, by unsupervised clustering or just following the order in which data were entered. In addition to the detailed plot, Methylation plotter produces a methylation profile plot that summarizes the status of the scrutinized region, a boxplot that sums up the differences between groups (if any) and a dendrogram that classifies the data by unsupervised clustering. Coupled with this analysis, descriptive statistics and testing for differences at both CpG and group levels are provided. The implementation is based in R/shiny, providing a highly dynamic user interface that generates quality graphics without the need of writing R code. Methylation plotter is freely available at http://gattaca.imppc.org:3838/methylation_plotter/.

pcrEfficiency: a Web tool for PCR amplification efficiency prediction.

BACKGROUND: Relative calculation of differential gene expression in quantitative PCR reactions requires comparison between amplification experiments that include reference genes and genes under study. Ignoring the differences between their efficiencies may lead to miscalculation of gene expression even with the same starting amount of template. Although there are several tools performing PCR primer design, there is no tool available that predicts PCR efficiency for a given amplicon and primer pair. RESULTS: We have used a statistical approach based on 90 primer pair combinations amplifying templates from bacteria, yeast, plants and humans, ranging in size between 74 and 907 bp to identify the parameters that affect PCR efficiency. We developed a generalized additive model fitting the data and constructed an open source Web interface that allows the obtention of oligonucleotides optimized for PCR with predicted amplification efficiencies starting from a given sequence. CONCLUSIONS: pcrEfficiency provides an easy-to-use web interface allowing the prediction of PCR efficiencies prior to web lab experiments thus easing quantitative real-time PCR set-up. A web-based service as well the source code are provided freely at http://srvgen.upct.es/efficiency.html under the GPL v2 license.