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.

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.

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.

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.