BSXplorer: analytical framework for exploratory analysis of BS-seq data.

BACKGROUND: Bisulfite sequencing detects and quantifies DNA methylation patterns, contributing to our understanding of gene expression regulation, genome stability maintenance, conservation of epigenetic mechanisms across divergent taxa, epigenetic inheritance and, eventually, phenotypic variation. Graphical representation of methylation data is crucial in exploring epigenetic regulation on a genome-wide scale in both plants and animals. This is especially relevant for non-model organisms with poorly annotated genomes and/or organisms where genome sequences are not yet assembled on chromosome level. Despite being a technology of choice to profile DNA methylation for many years now there are surprisingly few lightweight and robust standalone tools available for efficient graphical analysis of data in non-model systems. This significantly limits evolutionary studies and agrigenomics research. BSXplorer is a tool specifically developed to fill this gap and assist researchers in explorative data analysis and in visualising and interpreting bisulfite sequencing data more easily. RESULTS: BSXplorer provides in-depth graphical analysis of sequencing data encompassing (a) profiling of methylation levels in metagenes or in user-defined regions using line plots and heatmaps, generation of summary statistics charts, (b) enabling comparative analyses of methylation patterns across experimental samples, methylation contexts and species, and (c) identification of modules sharing similar methylation signatures at functional genomic elements. The tool processes methylation data quickly and offers API and CLI capabilities, along with the ability to create high-quality figures suitable for publication. CONCLUSIONS: BSXplorer facilitates efficient methylation data mining, contrasting and visualization, making it an easy-to-use package that is highly useful for epigenetic research.

Pygenomics: manipulating genomic intervals and data files in Python.

SUMMARY: We present pygenomics, a Python package for working with genomic intervals and bioinformatic data files. The package implements interval operations, provides both API and CLI, and supports reading and writing data in widely used bioinformatic formats, including BAM, BED, GFF3, and VCF. The source code of pygenomics is provided with in-source documentation and type annotations and adheres to the functional programming paradigm. These features facilitate seamless integration of pygenomics routines into scripts and pipelines. The package is implemented in pure Python using its standard library only and contains the property-based testing framework. Comparison of pygenomics with other Python bioinformatic packages with relation to features and performance is presented. The performance comparison covers operations with genomic intervals, read alignments, and genomic variants and demonstrates that pygenomics is suitable for computationally effective analysis. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://gitlab.com/gtamazian/pygenomics.

Transcriptomic Analysis of Flowering Time Genes in Cultivated Chickpea and Wild Cicer.

Chickpea (Cicer arietinum L.) is a major grain legume and a good source of plant-based protein. However, comprehensive knowledge of flowering time control in Cicer is lacking. In this study, we acquire high-throughput transcriptome sequencing data and analyze changes in gene expression during floral transition in the early flowering cultivar ICCV 96029, later flowering C. arietinum accessions, and two wild species, C. reticulatum and C. echinospermum. We identify Cicer orthologs of A. thaliana flowering time genes and analyze differential expression of 278 genes between four species/accessions, three tissue types, and two conditions. Our results show that the differences in gene expression between ICCV 96029 and other cultivated chickpea accessions are vernalization-dependent. In addition, we highlight the role of FTa3, an ortholog of FLOWERING LOCUS T in Arabidopsis, in the vernalization response of cultivated chickpea. A common set of differentially expressed genes was found for all comparisons between wild species and cultivars. The direction of expression change for different copies of the FT-INTERACTING PROTEIN 1 gene was variable in different comparisons, which suggests complex mechanisms of FT protein transport. Our study makes a contribution to the understanding of flowering time control in Cicer, and can provide genetic strategies to further improve this important agronomic trait.

Genomic Regions Associated with Fusarium Wilt Resistance in Flax.

Modern flax cultivars are susceptible to many diseases; arguably, the most economically damaging of these is the Fusarium wilt fungal disease. Over the past decades international flax breeding initiatives resulted in the development of resistant cultivars. However, much remains to be learned about the mechanisms of resistance to Fusarium infection in flax. As a first step to uncover the genetic factors associated with resistance to Fusarium wilt disease, we performed a genome-wide association study (GWAS) using 297 accessions from the collection of the Federal Research Centre of the Bast Fiber Crops, Torzhok, Russia. These genotypes were infected with a highly pathogenic Fusarium oxysporum f.sp. lini MI39 strain; the wilt symptoms were documented in the course of three successive years. Six different single-locus models implemented in GAPIT3 R package were applied to a selected subset of 72,526 SNPs. A total of 15 QTNs (Quantitative Trait Nucleotides) were detected during at least two years of observation, while eight QTNs were found during all three years of the experiment. Of these, ten QTNs occupied a region of 640 Kb at the start of chromosome 1, while the remaining QTNs mapped to chromosomes 8, 11 and 13. All stable QTNs demonstrate a statistically significant allelic effect across 3 years of the experiment. Importantly, several QTNs spanned regions that harbored genes involved in the pathogen recognition and plant immunity response, including the KIP1-like protein (Lus10025717) and NBS-LRR protein (Lus10025852). Our results provide novel insights into the genetic architecture of flax resistance to Fusarium wilt and pinpoint potential candidate genes for further in-depth studies.

A Genomic Blueprint of Flax Fungal Parasite Fusarium oxysporum f. sp. lini.

Fusarium wilt of flax is an aggressive disease caused by the soil-borne fungal pathogen Fusarium oxysporum f. sp. lini. It is a challenging pathogen presenting a constant threat to flax production industry worldwide. Previously, we reported chromosome-level assemblies of 5 highly pathogenic F. oxysporum f. sp. lini strains. We sought to characterize the genomic architecture of the fungus and outline evolutionary mechanisms shaping the pathogen genome. Here, we reveal the complex multi-compartmentalized genome organization and uncover its diverse evolutionary dynamics, which boosts genetic diversity and facilitates host adaptation. In addition, our results suggest that host of functions implicated in the life cycle of mobile genetic elements are main contributors to dissimilarity between proteomes of different Fusaria. Finally, our experiments demonstrate that mobile genetics elements are expressed in planta upon infection, alluding to their role in pathogenicity. On the whole, these results pave the way for further in-depth studies of evolutionary forces shaping the host-pathogen interaction.

The Genome Sequence of Five Highly Pathogenic Isolates of Fusarium oxysporum f. sp. lini.

Fusarium wilt is the most destructive fungal disease in flax, limiting flax cultivation in all the main flax and linseed growing countries. The causative agent is seedborne and soilborne fungus F. oxysporum f. sp. lini. Here, we report, for the first time, genome assemblies of five highly pathogenic isolates of Fusarium oxysporum f. sp. lini, namely monoisolate 39 and strains F329, F324, F282, F287. In addition, syntenic analysis provided a powerful approach to distinguish between core and lineage-specific parts of the genome. These results lay a solid foundation for comparative genomics studies of plant fungal pathogens, evolution of pathogenicity, and virulence factors underlying the dynamics of host-pathogen interactions, thus eventually offering solutions to Fusarium disease control.

Diversity and dynamics of the Drosophila transcriptome.

Animal transcriptomes are dynamic, with each cell type, tissue and organ system expressing an ensemble of transcript isoforms that give rise to substantial diversity. Here we have identified new genes, transcripts and proteins using poly(A)+ RNA sequencing from Drosophila melanogaster in cultured cell lines, dissected organ systems and under environmental perturbations. We found that a small set of mostly neural-specific genes has the potential to encode thousands of transcripts each through extensive alternative promoter usage and RNA splicing. The magnitudes of splicing changes are larger between tissues than between developmental stages, and most sex-specific splicing is gonad-specific. Gonads express hundreds of previously unknown coding and long non-coding RNAs (lncRNAs), some of which are antisense to protein-coding genes and produce short regulatory RNAs. Furthermore, previously identified pervasive intergenic transcription occurs primarily within newly identified introns. The fly transcriptome is substantially more complex than previously recognized, with this complexity arising from combinatorial usage of promoters, splice sites and polyadenylation sites.

Development and validation of response markers to predict survival and pleurodesis success in patients with malignant pleural effusion (PROMISE): a multicohort analysis.

BACKGROUND: The prevalence of malignant pleural effusion is increasing worldwide, but prognostic biomarkers to plan treatment and to understand the underlying mechanisms of disease progression remain unidentified. The PROMISE study was designed with the objectives to discover, validate, and prospectively assess biomarkers of survival and pleurodesis response in malignant pleural effusion and build a score that predicts survival. METHODS: In this multicohort study, we used five separate and independent datasets from randomised controlled trials to investigate potential biomarkers of survival and pleurodesis. Mass spectrometry-based discovery was used to investigate pleural fluid samples for differential protein expression in patients from the discovery group with different survival and pleurodesis outcomes. Clinical, radiological, and biological variables were entered into least absolute shrinkage and selection operator regression to build a model that predicts 3-month mortality. We evaluated the model using internal and external validation. FINDINGS: 17 biomarker candidates of survival and seven of pleurodesis were identified in the discovery dataset. Three independent datasets (n=502) were used for biomarker validation. All pleurodesis biomarkers failed, and gelsolin, macrophage migration inhibitory factor, versican, and tissue inhibitor of metalloproteinases 1 (TIMP1) emerged as accurate predictors of survival. Eight variables (haemoglobin, C-reactive protein, white blood cell count, Eastern Cooperative Oncology Group performance status, cancer type, pleural fluid TIMP1 concentrations, and previous chemotherapy or radiotherapy) were validated and used to develop a survival score. Internal validation with bootstrap resampling and external validation with 162 patients from two independent datasets showed good discrimination (C statistic values of 0·78 [95% CI 0·72-0·83] for internal validation and 0·89 [0·84-0·93] for external validation of the clinical PROMISE score). INTERPRETATION: To our knowledge, the PROMISE score is the first prospectively validated prognostic model for malignant pleural effusion that combines biological and clinical parameters to accurately estimate 3-month mortality. It is a robust, clinically relevant prognostic score that can be applied immediately, provide important information on patient prognosis, and guide the selection of appropriate management strategies. FUNDING: European Respiratory Society, Medical Research Funding-University of Oxford, Slater & Gordon Research Fund, and Oxfordshire Health Services Research Committee Research Grants.

Clinical whole-genome sequencing from routine formalin-fixed, paraffin-embedded specimens: pilot study for the 100,000 Genomes Project.

PURPOSE: Fresh-frozen (FF) tissue is the optimal source of DNA for whole-genome sequencing (WGS) of cancer patients. However, it is not always available, limiting the widespread application of WGS in clinical practice. We explored the viability of using formalin-fixed, paraffin-embedded (FFPE) tissues, available routinely for cancer patients, as a source of DNA for clinical WGS. METHODS: We conducted a prospective study using DNAs from matched FF, FFPE, and peripheral blood germ-line specimens collected from 52 cancer patients (156 samples) following routine diagnostic protocols. We compared somatic variants detected in FFPE and matching FF samples. RESULTS: We found the single-nucleotide variant agreement reached 71% across the genome and somatic copy-number alterations (CNAs) detection from FFPE samples was suboptimal (0.44 median correlation with FF) due to nonuniform coverage. CNA detection was improved significantly with lower reverse crosslinking temperature in FFPE DNA extraction (80 °C or 65 °C depending on the methods). Our final data showed somatic variant detection from FFPE for clinical decision making is possible. We detected 98% of clinically actionable variants (including 30/31 CNAs). CONCLUSION: We present the first prospective WGS study of cancer patients using FFPE specimens collected in a routine clinical environment proving WGS can be applied in the clinic.

SmD1 Modulates the miRNA Pathway Independently of Its Pre-mRNA Splicing Function.

microRNAs (miRNAs) are a class of endogenous regulatory RNAs that play a key role in myriad biological processes. Upon transcription, primary miRNA transcripts are sequentially processed by Drosha and Dicer ribonucleases into ~22-24 nt miRNAs. Subsequently, miRNAs are incorporated into the RNA-induced silencing complexes (RISCs) that contain Argonaute (AGO) family proteins and guide RISC to target RNAs via complementary base pairing, leading to post-transcriptional gene silencing by a combination of translation inhibition and mRNA destabilization. Select pre-mRNA splicing factors have been implicated in small RNA-mediated gene silencing pathways in fission yeast, worms, flies and mammals, but the underlying molecular mechanisms are not well understood. Here, we show that SmD1, a core component of the Drosophila small nuclear ribonucleoprotein particle (snRNP) implicated in splicing, is required for miRNA biogenesis and function. SmD1 interacts with both the microprocessor component Pasha and pri-miRNAs, and is indispensable for optimal miRNA biogenesis. Depletion of SmD1 impairs the assembly and function of the miRISC without significantly affecting the expression of major canonical miRNA pathway components. Moreover, SmD1 physically and functionally associates with components of the miRISC, including AGO1 and GW182. Notably, miRNA defects resulting from SmD1 silencing can be uncoupled from defects in pre-mRNA splicing, and the miRNA and splicing machineries are physically and functionally distinct entities. Finally, photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) analysis identifies numerous SmD1-binding events across the transcriptome and reveals direct SmD1-miRNA interactions. Our study suggests that SmD1 plays a direct role in miRNA-mediated gene silencing independently of its pre-mRNA splicing activity and indicates that the dual roles of splicing factors in post-transcriptional gene regulation may be evolutionarily widespread.

Regulators of autophagosome formation in Drosophila muscles.

Given the diversity of autophagy targets and regulation, it is important to characterize autophagy in various cell types and conditions. We used a primary myocyte cell culture system to assay the role of putative autophagy regulators in the specific context of skeletal muscle. By treating the cultures with rapamycin (Rap) and chloroquine (CQ) we induced an autophagic response, fully suppressible by knockdown of core ATG genes. We screened D. melanogaster orthologs of a previously reported mammalian autophagy protein-protein interaction network, identifying several proteins required for autophagosome formation in muscle cells, including orthologs of the Rab regulators RabGap1 and Rab3Gap1. The screen also highlighted the critical roles of the proteasome and glycogen metabolism in regulating autophagy. Specifically, sustained proteasome inhibition inhibited autophagosome formation both in primary culture and larval skeletal muscle, even though autophagy normally acts to suppress ubiquitin aggregate formation in these tissues. In addition, analyses of glycogen metabolic genes in both primary cultured and larval muscles indicated that glycogen storage enhances the autophagic response to starvation, an important insight given the link between glycogen storage disorders, autophagy, and muscle function.

Integrating protein-protein interaction networks with phenotypes reveals signs of interactions.

A major objective of systems biology is to organize molecular interactions as networks and to characterize information flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the 'signs' of interactions (i.e., activation-inhibition relationships). We constructed a Drosophila melanogaster signed PPI network consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes enolase and aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation-inhibition relationships between physically interacting proteins within signaling pathways will affect our understanding of many biological functions, including signal transduction and mechanisms of disease.

Deep annotation of Drosophila melanogaster microRNAs yields insights into their processing, modification, and emergence.

Since the initial annotation of miRNAs from cloned short RNAs by the Ambros, Tuschl, and Bartel groups in 2001, more than a hundred studies have sought to identify additional miRNAs in various species. We report here a meta-analysis of short RNA data from Drosophila melanogaster, aggregating published libraries with 76 data sets that we generated for the modENCODE project. In total, we began with more than 1 billion raw reads from 187 libraries comprising diverse developmental stages, specific tissue- and cell-types, mutant conditions, and/or Argonaute immunoprecipitations. We elucidated several features of known miRNA loci, including multiple phased byproducts of cropping and dicing, abundant alternative 5' termini of certain miRNAs, frequent 3' untemplated additions, and potential editing events. We also identified 49 novel genomic locations of miRNA production, and 61 additional candidate loci with limited evidence for miRNA biogenesis. Although these loci broaden the Drosophila miRNA catalog, this work supports the notion that a restricted set of cellular transcripts is competent to be specifically processed by the Drosha/Dicer-1 pathway. Unexpectedly, we detected miRNA production from coding and untranslated regions of mRNAs and found the phenomenon of miRNA production from the antisense strand of known loci to be common. Altogether, this study lays a comprehensive foundation for the study of miRNA diversity and evolution in a complex animal model.

The transcriptional diversity of 25 Drosophila cell lines.

Drosophila melanogaster cell lines are important resources for cell biologists. Here, we catalog the expression of exons, genes, and unannotated transcriptional signals for 25 lines. Unannotated transcription is substantial (typically 19% of euchromatic signal). Conservatively, we identify 1405 novel transcribed regions; 684 of these appear to be new exons of neighboring, often distant, genes. Sixty-four percent of genes are expressed detectably in at least one line, but only 21% are detected in all lines. Each cell line expresses, on average, 5885 genes, including a common set of 3109. Expression levels vary over several orders of magnitude. Major signaling pathways are well represented: most differentiation pathways are "off" and survival/growth pathways "on." Roughly 50% of the genes expressed by each line are not part of the common set, and these show considerable individuality. Thirty-one percent are expressed at a higher level in at least one cell line than in any single developmental stage, suggesting that each line is enriched for genes characteristic of small sets of cells. Most remarkable is that imaginal disc-derived lines can generally be assigned, on the basis of expression, to small territories within developing discs. These mappings reveal unexpected stability of even fine-grained spatial determination. No two cell lines show identical transcription factor expression. We conclude that each line has retained features of an individual founder cell superimposed on a common "cell line" gene expression pattern.

Pangenomics of flax fungal parasite Fusarium oxysporum f. sp. lini.

To assess the genomic diversity of Fusarium oxysporum f. sp. lini strains and compile a comprehensive gene repertoire, we constructed a pangenome using 13 isolates from four different clonal lineages, each exhibiting distinct levels of virulence. Syntenic analyses of two selected genomes revealed significant chromosomal rearrangements unique to each genome. A comprehensive examination of both core and accessory pangenome content and diversity points at an open genome state. Additionally, Gene Ontology (GO) enrichment analysis indicated that non-core pangenome genes are associated with pathogen recognition and immune signaling. Furthermore, the Folini pansecterome, encompassing secreted proteins critical for fungal pathogenicity, primarily consists of three functional classes: effector proteins, CAZYmes, and proteases. These three classes account for approximately 3.5% of the pangenome. Each functional class within the pansecterome was meticulously annotated and characterized with respect to pangenome category distribution, PFAM domain frequency, and strain virulence assessment. This analysis revealed that highly virulent isolates have specific types of PFAM domains that are exclusive to them. Upon examining the repertoire of SIX genes known for virulence in other formae speciales, it was found that all isolates had a similar gene content except for two, which lacked SIX genes entirely.

Sustained cancer-relevant alternative RNA splicing events driven by PRMT5 in high-risk neuroblastoma.

Protein arginine methyltransferase 5 (PRMT5) is over-expressed in a wide variety of cancers and is implicated as having a key oncogenic role, achieved in part through its control of the master transcription regulator E2F1. We investigated the relevance of PRMT5 and E2F1 in neuroblastoma (NB) and found that elevated expression of PRMT5 and E2F1 occurs in poor prognosis high-risk disease and correlates with an amplified Myelocytomatosis viral-related oncogene, neuroblastoma-derived (MYCN) gene. Our results show that MYCN drives the expression of splicing factor genes that, together with PRMT5 and E2F1, lead to a deregulated alternative RNA splicing programme that impedes apoptosis. Pharmacological inhibition of PRMT5 or inactivation of E2F1 restores normal splicing and renders NB cells sensitive to apoptosis. Our findings suggest that a sustained cancer-relevant alternative RNA splicing programme desensitises NB cells to apoptosis, and identify PRMT5 as a potential therapeutic target for high-risk disease.

A collection of read depth profiles at structural variant breakpoints.

SWaveform, a newly created open genome-wide resource for read depth signal in the vicinity of structural variant (SV) breakpoints, aims to boost development of computational tools and algorithms for discovery of genomic rearrangement events from sequencing data. SVs are a dominant force shaping genomes and substantially contributing to genetic diversity. Still, there are challenges in reliable and efficient genotyping of SVs from whole genome sequencing data, thus delaying translation into clinical applications and wasting valuable resources. SWaveform includes a database containing ~7 M of read depth profiles at SV breakpoints extracted from 911 sequencing samples generated by the Human Genome Diversity Project, generalised patterns of the signal at breakpoints, an interface for navigation and download, as well as a toolbox for local deployment with user's data. The dataset can be of immense value to bioinformatics and engineering communities as it empowers smooth application of intelligent signal processing and machine learning techniques for discovery of genomic rearrangement events and thus opens the floodgates for development of innovative algorithms and software.

Long non-coding RNA-derived peptides are immunogenic and drive a potent anti-tumour response.

Protein arginine methyltransferase (PRMT) 5 is over-expressed in a variety of cancers and the master transcription regulator E2F1 is an important methylation target. We have explored the role of PRMT5 and E2F1 in regulating the non-coding genome and report here a striking effect on long non-coding (lnc) RNA gene expression. Moreover, many MHC class I protein-associated peptides were derived from small open reading frames in the lncRNA genes. Pharmacological inhibition of PRMT5 or adjusting E2F1 levels qualitatively altered the repertoire of lncRNA-derived peptide antigens displayed by tumour cells. When presented to the immune system as either ex vivo-loaded dendritic cells or expressed from a viral vector, lncRNA-derived peptides drove a potent antigen-specific CD8 T lymphocyte response, which translated into a significant delay in tumour growth. Thus, lncRNA genes encode immunogenic peptides that can be deployed as a cancer vaccine.

An account of Fusarium wilt resistance in flax Linum usitatissimum: The disease severity data.

A collection of flax accessions maintained by the Russian Federal Research Center for Bast Fiber Crops was characterized to evaluate its resistance to Fusarium wilt. 297 samples representing different morphotypes and selection status were infected with highly virulent MI39 strain of Fusarium oxysporum f. sp. lini. Evaluation of disease symptoms was performed at the full emergence stage in a greenhouse. The experiment lasted for 3 successive years. The disease severity index (DSI) record was obtained for every genotype in each year of the experiment. The data set was produced in a framework of a project focused on both a) deciphering the mechanisms of plant immunity, and b) development of flax cultivars resistant to Fusarium wilt. The data is available via Figshare repository.

False negative rates in Drosophila cell-based RNAi screens: a case study.

BACKGROUND: High-throughput screening using RNAi is a powerful gene discovery method but is often complicated by false positive and false negative results. Whereas false positive results associated with RNAi reagents has been a matter of extensive study, the issue of false negatives has received less attention. RESULTS: We performed a meta-analysis of several genome-wide, cell-based Drosophila RNAi screens, together with a more focused RNAi screen, and conclude that the rate of false negative results is at least 8%. Further, we demonstrate how knowledge of the cell transcriptome can be used to resolve ambiguous results and how the number of false negative results can be reduced by using multiple, independently-tested RNAi reagents per gene. CONCLUSIONS: RNAi reagents that target the same gene do not always yield consistent results due to false positives and weak or ineffective reagents. False positive results can be partially minimized by filtering with transcriptome data. RNAi libraries with multiple reagents per gene also reduce false positive and false negative outcomes when inconsistent results are disambiguated carefully.