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.

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

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. 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. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Context-aware transcript quantification from long-read RNA-seq data with Bambu.

Most approaches to transcript quantification rely on fixed reference annotations; however, the transcriptome is dynamic and depending on the context, such static annotations contain inactive isoforms for some genes, whereas they are incomplete for others. Here we present Bambu, a method that performs machine-learning-based transcript discovery to enable quantification specific to the context of interest using long-read RNA-sequencing. To identify novel transcripts, Bambu estimates the novel discovery rate, which replaces arbitrary per-sample thresholds with a single, interpretable, precision-calibrated parameter. Bambu retains the full-length and unique read counts, enabling accurate quantification in presence of inactive isoforms. Compared to existing methods for transcript discovery, Bambu achieves greater precision without sacrificing sensitivity. We show that context-aware annotations improve quantification for both novel and known transcripts. We apply Bambu to quantify isoforms from repetitive HERVH-LTR7 retrotransposons in human embryonic stem cells, demonstrating the ability for context-specific transcript expression analysis.

Antisense RNAs Influence Promoter Usage of Their Counterpart Sense Genes in Cancer.

Multiple noncoding natural antisense transcripts (ncNAT) are known to modulate key biological events such as cell growth or differentiation. However, the actual impact of ncNATs on cancer progression remains largely unknown. In this study, we identified a complete list of differentially expressed ncNATs in hepatocellular carcinoma. Among them, a previously undescribed ncNAT HNF4A-AS1L suppressed cancer cell growth by regulating its sense gene HNF4A, a well-known cancer driver, through a promoter-specific mechanism. HNF4A-AS1L selectively activated the HNF4A P1 promoter via HNF1A, which upregulated expression of tumor suppressor P1-driven isoforms, while having no effect on the oncogenic P2 promoter. RNA-seq data from 23 tissue and cancer types identified approximately 100 ncNATs whose expression correlated specifically with the activity of one promoter of their associated sense gene. Silencing of two of these ncNATs ENSG00000259357 and ENSG00000255031 (antisense to CERS2 and CHKA, respectively) altered the promoter usage of CERS2 and CHKA. Altogether, these results demonstrate that promoter-specific regulation is a mechanism used by ncNATs for context-specific control of alternative isoform expression of their counterpart sense genes. SIGNIFICANCE: This study characterizes a previously unexplored role of ncNATs in regulation of isoform expression of associated sense genes, highlighting a mechanism of alternative promoter usage in cancer.

From Modules to Networks: a Systems-Level Analysis of the Bacitracin Stress Response in Bacillus subtilis.

Bacterial resistance against antibiotics often involves multiple mechanisms that are interconnected to ensure robust protection. So far, the knowledge about underlying regulatory features of those resistance networks is sparse, since they can hardly be determined by experimentation alone. Here, we present the first computational approach to elucidate the interplay between multiple resistance modules against a single antibiotic and how regulatory network structure allows the cell to respond to and compensate for perturbations of resistance. Based on the response of Bacillus subtilis toward the cell wall synthesis-inhibiting antibiotic bacitracin, we developed a mathematical model that comprehensively describes the protective effect of two well-studied resistance modules (BceAB and BcrC) on the progression of the lipid II cycle. By integrating experimental measurements of expression levels, the model accurately predicts the efficacy of bacitracin against the B. subtilis wild type as well as mutant strains lacking one or both of the resistance modules. Our study reveals that bacitracin-induced changes in the properties of the lipid II cycle itself control the interplay between the two resistance modules. In particular, variations in the concentrations of UPP, the lipid II cycle intermediate that is targeted by bacitracin, connect the effect of the BceAB transporter and the homeostatic response via BcrC to an overall resistance response. We propose that monitoring changes in pathway properties caused by a stressor allows the cell to fine-tune deployment of multiple resistance systems and may serve as a cost-beneficial strategy to control the overall response toward this stressor.IMPORTANCE Antibiotic resistance poses a major threat to global health, and systematic studies to understand the underlying resistance mechanisms are urgently needed. Although significant progress has been made in deciphering the mechanistic basis of individual resistance determinants, many bacterial species rely on the induction of a whole battery of resistance modules, and the complex regulatory networks controlling these modules in response to antibiotic stress are often poorly understood. In this work we combined experiments and theoretical modeling to decipher the resistance network of Bacillus subtilis against bacitracin, which inhibits cell wall biosynthesis in Gram-positive bacteria. We found a high level of cross-regulation between the two major resistance modules in response to bacitracin stress and quantified their effects on bacterial resistance. To rationalize our experimental data, we expanded a previously established computational model for the lipid II cycle through incorporating the quantitative action of the resistance modules. This led us to a systems-level description of the bacitracin stress response network that captures the complex interplay between resistance modules and the essential lipid II cycle of cell wall biosynthesis and accurately predicts the minimal inhibitory bacitracin concentration in all the studied mutants. With this, our study highlights how bacterial resistance emerges from an interlaced network of redundant homeostasis and stress response modules.

BceAB-Type Antibiotic Resistance Transporters Appear To Act by Target Protection of Cell Wall Synthesis.

Resistance against cell wall-active antimicrobial peptides in bacteria is often mediated by transporters. In low-GC-content Gram-positive bacteria, a common type of such transporters is BceAB-like systems, which frequently provide high-level resistance against peptide antibiotics that target intermediates of the lipid II cycle of cell wall synthesis. How a transporter can offer protection from drugs that are active on the cell surface, however, has presented researchers with a conundrum. Multiple theories have been discussed, ranging from removal of the peptides from the membrane and internalization of the drug for degradation to removal of the cellular target rather than the drug itself. To resolve this much-debated question, we here investigated the mode of action of the transporter BceAB of Bacillus subtilis We show that it does not inactivate or import its substrate antibiotic bacitracin. Moreover, we present evidence that the critical factor driving transport activity is not the drug itself but instead the concentration of drug-target complexes in the cell. Our results, together with previously reported findings, lead us to propose that BceAB-type transporters act by transiently freeing lipid II cycle intermediates from the inhibitory grip of antimicrobial peptides and thus provide resistance through target protection of cell wall synthesis. Target protection has so far only been reported for resistance against antibiotics with intracellular targets, such as the ribosome. However, this mechanism offers a plausible explanation for the use of transporters as resistance determinants against cell wall-active antibiotics in Gram-positive bacteria where cell wall synthesis lacks the additional protection of an outer membrane.

Global population genomics of the forest pathogen Dothistroma septosporum reveal chromosome duplications in high dothistromin-producing strains.

Dothistroma needle blight is one of the most devastating pine tree diseases worldwide. New and emerging epidemics have been frequent over the last 25 years, particularly in the Northern Hemisphere, where they are in part associated with changing weather patterns. One of the main Dothistroma needle blight pathogens, Dothistroma septosporum, has a global distribution but most molecular plant pathology research has been confined to Southern Hemisphere populations that have limited genetic diversity. Extensive genomic and transcriptomic data are available for a D. septosporum reference strain from New Zealand, where an introduced clonal population of the pathogen predominates. Due to the global importance of this pathogen, we determined whether the genome of this reference strain is representative of the species worldwide by sequencing the genomes of 18 strains sampled globally from different pine hosts. Genomic polymorphism shows substantial variation within the species, clustered into two distinct groups of strains with centres of diversity in Central and South America. A reciprocal chromosome translocation uniquely identifies the New Zealand strains. Globally, strains differ in their production of the virulence factor dothistromin, with extremely high production levels in strain ALP3 from Germany. Comparisons with the New Zealand reference revealed that several strains are aneuploids; for example, ALP3 has duplications of three chromosomes. Increased gene copy numbers therefore appear to contribute to increased production of dothistromin, emphasizing that studies of population structure are a necessary adjunct to functional analyses of genetic polymorphisms to identify the molecular basis of virulence in this important forest pathogen.

Evolution of polyketide synthesis in a Dothideomycete forest pathogen.

Fungal secondary metabolites have many important biological roles and some, like the toxic polyketide aflatoxin, have been intensively studied at the genetic level. Complete sets of polyketide synthase (PKS) genes can now be identified in fungal pathogens by whole genome sequencing and studied in order to predict the biosynthetic potential of those fungi. The pine needle pathogen Dothistroma septosporum is predicted to have only three functional PKS genes, a small number for a hemibiotrophic fungus. One of these genes is required for production of dothistromin, a polyketide virulence factor related to aflatoxin, whose biosynthetic genes are dispersed across one chromosome rather than being clustered. Here we evaluated the evolution of the other two genes, and their predicted gene clusters, using phylogenetic and population analyses. DsPks1 and its gene cluster are quite conserved amongst related fungi, whilst DsPks2 appears to be novel. The DsPks1 protein was predicted to be required for dihydroxynaphthalene (DHN) melanin biosynthesis but functional analysis of DsPks1 mutants showed that D. septosporum produced mainly dihydroxyphenylalanine (DOPA) melanin, which is produced by a PKS-independent pathway. Although the secondary metabolites made by these two PKS genes are not known, comparisons between strains of D. septosporum from different regions of the world revealed that both PKS core genes are under negative selection and we suggest they may have important cryptic roles in planta.

The venom gland transcriptome of the parasitoid wasp Nasonia vitripennis highlights the importance of novel genes in venom function.

BACKGROUND: Prior to egg laying the parasitoid wasp Nasonia vitripennis envenomates its pupal host with a complex mixture of venom peptides. This venom induces several dramatic changes in the host, including developmental arrest, immunosuppression, and altered metabolism. The diverse and potent bioactivity of N. vitripennis venom provides opportunities for the development of novel acting pharmaceuticals based on these molecules. However, currently very little is known about the specific functions of individual venom peptides or what mechanisms underlie the hosts response to envenomation. Many of the venom peptides also lack bioinformatically derived annotations because no homologs can be identified in the sequences databases. The RNA interference system of N. vitripennis provides a method for functional characterisation of venom protein encoding genes, however working with the current list of 79 candidates represents a daunting task. For this reason we were interested in determining the expression levels of venom encoding genes in the venom gland, as this information could be used to rank candidates for further study. To do this we carried out deep transcriptome sequencing of the venom gland and ovary tissue and used RNA-seq to rank the venom protein encoding genes by expression level. The generation of a specific venom gland transcriptome dataset also provides further opportunities to investigate novel features of this specialised organ. RESULTS: RNA-seq revealed that the highest expressed venom encoding gene in the venom gland was 'Venom protein Y'. The highest expressed annotated gene in this tissue was serine protease Nasvi2EG007167, which has previously been implicated in the apoptotic activity of N. vitripennis venom. As expected the RNA-seq confirmed that venom encoding genes are almost exclusively expressed in the venom gland relative to the neighbouring ovary tissue. Novel genes appear to perform key roles in N. vitripennis venom function, with over half of the 15 highest expressed venom encoding loci lacking bioinformatic annotations. The high throughput sequencing data also provided evidence for the existence of an additional 472 previously undescribed transcribed regions in the N. vitripennis genome. Finally, metatranscriptomic analysis of the venom gland transcriptome finds little evidence for the role of Wolbachia in the venom system. CONCLUSIONS: The expression level information provided here for the N. vitripennis venom protein encoding genes represents a valuable dataset that can be used by the research community to rank candidates for further functional characterisation. These candidates represent bioactive peptides valuable in the development of new pharmaceuticals.

Small Traditional Human Communities Sustain Genomic Diversity over Microgeographic Scales despite Linguistic Isolation.

At least since the Neolithic, humans have largely lived in networks of small, traditional communities. Often socially isolated, these groups evolved distinct languages and cultures over microgeographic scales of just tens of kilometers. Population genetic theory tells us that genetic drift should act quickly in such isolated groups, thus raising the question: do networks of small human communities maintain levels of genetic diversity over microgeographic scales? This question can no longer be asked in most parts of the world, which have been heavily impacted by historical events that make traditional society structures the exception. However, such studies remain possible in parts of Island Southeast Asia and Oceania, where traditional ways of life are still practiced. We captured genome-wide genetic data, together with linguistic records, for a case-study system-eight villages distributed across Sumba, a small, remote island in eastern Indonesia. More than 4,000 years after these communities were established during the Neolithic period, most speak different languages and can be distinguished genetically. Yet their nuclear diversity is not reduced, instead being comparable to other, even much larger, regional groups. Modeling reveals a separation of time scales: while languages and culture can evolve quickly, creating social barriers, sporadic migration averaged over many generations is sufficient to keep villages linked genetically. This loosely-connected network structure, once the global norm and still extant on Sumba today, provides a living proxy to explore fine-scale genome dynamics in the sort of small traditional communities within which the most recent episodes of human evolution occurred.

Genome-wide gene expression dynamics of the fungal pathogen Dothistroma septosporum throughout its infection cycle of the gymnosperm host Pinus radiata.

We present genome-wide gene expression patterns as a time series through the infection cycle of the fungal pine needle blight pathogen, Dothistroma septosporum, as it invades its gymnosperm host, Pinus radiata. We determined the molecular changes at three stages of the disease cycle: epiphytic/biotrophic (early), initial necrosis (mid) and mature sporulating lesion (late). Over 1.7 billion combined plant and fungal reads were sequenced to obtain 3.2 million fungal-specific reads, which comprised as little as 0.1% of the sample reads early in infection. This enriched dataset shows that the initial biotrophic stage is characterized by the up-regulation of genes encoding fungal cell wall-modifying enzymes and signalling proteins. Later necrotrophic stages show the up-regulation of genes for secondary metabolism, putative effectors, oxidoreductases, transporters and starch degradation. This in-depth through-time transcriptomic study provides our first snapshot of the gene expression dynamics that characterize infection by this fungal pathogen in its gymnosperm host.