3' Untranslated regions mediate transcriptional interference between convergent genes both locally and ectopically in Saccharomyces cerevisiae

Morphogenesis, starvation, and light responses in a mushroom-forming fungus revealed by long-read sequencing and extensive expression profiling

Mushroom-forming fungi (Agaricomycetes) are emerging as pivotal players in several fields of science and industry. Genomic data for Agaricomycetes are accumulating rapidly; however, this is not paralleled by improvements of gene annotations, which leave gene function notoriously poorly understood. We set out to improve our functional understanding of the model mushroom Coprinopsis cinerea by integrating a new, chromosome-level assembly, high-quality gene predictions, and functional information derived from broad gene-expression profiling data. The new annotation includes 5' and 3' untranslated regions (UTRs), polyadenylation sites (PASs), upstream open reading frames (uORFs), splicing isoforms, and microexons, as well as core gene sets corresponding to carbon starvation, light response, and hyphal differentiation. As a result, the genome of C. cinerea has now become the most comprehensively annotated genome among mushroom-forming fungi, which will contribute to multiple rapidly expanding fields, including research on their life history, light and stress responses, as well as multicellular development.

Identification of cell-type specific alternative transcripts in the multicellular alga Volvox carteri

BACKGROUND

Cell type specialization is a hallmark of complex multicellular organisms and is usually established through implementation of cell-type-specific gene expression programs. The multicellular green alga Volvox carteri has just two cell types, germ and soma, that have previously been shown to have very different transcriptome compositions which match their specialized roles. Here we interrogated another potential mechanism for differentiation in V. carteri, cell type specific alternative transcript isoforms (CTSAI).

METHODS

We used pre-existing predictions of alternative transcripts and de novo transcript assembly with HISAT2 and Ballgown software to compile a list of loci with two or more transcript isoforms, identified a small subset that were candidates for CTSAI, and manually curated this subset of genes to remove false positives. We experimentally verified three candidates using semi-quantitative RT-PCR to assess relative isoform abundance in each cell type.

RESULTS

Of the 1978 loci with two or more predicted transcript isoforms 67 of these also showed cell type isoform expression biases. After curation 15 strong candidates for CTSAI were identified, three of which were experimentally verified, and their predicted gene product functions were evaluated in light of potential cell type specific roles. A comparison of genes with predicted alternative splicing from Chlamydomonas reinhardtii, a unicellular relative of V. carteri, identified little overlap between ortholog pairs with alternative splicing in both species. Finally, we interrogated cell type expression patterns of 126 V. carteri predicted RNA binding protein (RBP) encoding genes and found 40 that showed either somatic or germ cell expression bias. These RBPs are potential mediators of CTSAI in V. carteri and suggest possible pre-adaptation for cell type specific RNA processing and a potential path for generating CTSAI in the early ancestors of metazoans and plants.

CONCLUSIONS

We predicted numerous instances of alternative transcript isoforms in Volvox, only a small subset of which showed cell type specific isoform expression bias. However, the validated examples of CTSAI supported existing hypotheses about cell type specialization in V. carteri, and also suggested new hypotheses about mechanisms of functional specialization for their gene products. Our data imply that CTSAI operates as a minor but important component of V. carteri cellular differentiation and could be used as a model for how alternative isoforms emerge and co-evolve with cell type specialization.

Inter-dependent Centrosomal Co-localization of the cen and ik2 cis-Natural Antisense mRNAs in Drosophila

Overlapping genes are prevalent in most genomes, but the extent to which this organization influences regulatory events operating at the post-transcriptional level remains unclear. Studying the cen and ik2 genes of Drosophila melanogaster, which are convergently transcribed as cis-natural antisense transcripts (cis-NATs) with overlapping 3' UTRs, we found that their encoded mRNAs strikingly co-localize to centrosomes. These transcripts physically interact in a 3' UTR-dependent manner, and the targeting of ik2 requires its 3' UTR sequence and the presence of cen mRNA, which serves as the main driver of centrosomal co-localization. The cen transcript undergoes localized translation in proximity to centrosomes, and its localization is perturbed by polysome-disrupting drugs. By interrogating global fractionation-sequencing datasets generated from Drosophila and human cellular models, we find that RNAs expressed as cis-NATs tend to co-localize to specific subcellular fractions. This work suggests that post-transcriptional interactions between RNAs with complementary sequences can dictate their localization fate in the cytoplasm.

Refining the transcriptome of the human malaria parasite Plasmodium falciparum using amplification-free RNA-seq

Background

Plasmodium parasites undergo several major developmental transitions during their complex lifecycle, which are enabled by precisely ordered gene expression programs. Transcriptomes from the 48-h blood stages of the major human malaria parasite Plasmodium falciparum have been described using cDNA microarrays and RNA-seq, but these assays have not always performed well within non-coding regions, where the AT-content is often 90–95%.

Results

We developed a directional, amplification-free RNA-seq protocol (DAFT-seq) to reduce bias against AT-rich cDNA, which we have applied to three strains of P. falciparum (3D7, HB3 and IT). While strain-specific differences were detected, overall there is strong conservation between the transcriptional profiles. For the 3D7 reference strain, transcription was detected from 89% of the genome, with over 78% of the genome transcribed into mRNAs. We also find that transcription from bidirectional promoters frequently results in non-coding, antisense transcripts. These datasets allowed us to refine the 5′ and 3′ untranslated regions (UTRs), which can be variable, long (> 1000 nt), and often overlap those of adjacent transcripts.

Conclusions

The approaches applied in this study allow a refined description of the transcriptional landscape of P. falciparum and demonstrate that very little of the densely packed P. falciparum genome is inactive or redundant. By capturing the 5′ and 3′ ends of mRNAs, we reveal both constant and dynamic use of transcriptional start sites across the intraerythrocytic developmental cycle that will be useful in guiding the definition of regulatory regions for use in future experimental gene expression studies.

A High-Quality Grapevine Downy Mildew Genome Assembly Reveals Rapidly Evolving and Lineage-Specific Putative Host Adaptation Genes

Downy mildews are obligate biotrophic oomycete pathogens that cause devastating plant diseases on economically important crops. Plasmopara viticola is the causal agent of grapevine downy mildew, a major disease in vineyards worldwide. We sequenced the genome of Pl. viticola with PacBio long reads and obtained a new 92.94 Mb assembly with high contiguity (359 scaffolds for a N50 of 706.5 kb) due to a better resolution of repeat regions. This assembly presented a high level of gene completeness, recovering 1,592 genes encoding secreted proteins involved in plant–pathogen interactions. Plasmopara viticola had a two-speed genome architecture, with secreted protein-encoding genes preferentially located in gene-sparse, repeat-rich regions and evolving rapidly, as indicated by pairwise dN/dS values. We also used short reads to assemble the genome of Plasmopara muralis, a closely related species infecting grape ivy (Parthenocissus tricuspidata). The lineage-specific proteins identified by comparative genomics analysis included a large proportion of RxLR cytoplasmic effectors and, more generally, genes with high dN/dS values. We identified 270 candidate genes under positive selection, including several genes encoding transporters and components of the RNA machinery potentially involved in host specialization. Finally, the Pl. viticola genome assembly generated here will allow the development of robust population genomics approaches for investigating the mechanisms involved in adaptation to biotic and abiotic selective pressures in this species.

A High-Quality Grapevine Downy Mildew Genome Assembly Reveals Rapidly Evolving and Lineage-Specific Putative Host Adaptation Genes

Downy mildews are obligate biotrophic oomycete pathogens that cause devastating plant diseases on economically important crops. Plasmopara viticola is the causal agent of grapevine downy mildew, a major disease in vineyards worldwide. We sequenced the genome of Pl. viticola with PacBio long reads and obtained a new 92.94 Mb assembly with high contiguity (359 scaffolds for a N50 of 706.5 kb) due to a better resolution of repeat regions. This assembly presented a high level of gene completeness, recovering 1,592 genes encoding secreted proteins involved in plant-pathogen interactions. Plasmopara viticola had a two-speed genome architecture, with secreted protein-encoding genes preferentially located in gene-sparse, repeat-rich regions and evolving rapidly, as indicated by pairwise dN/dS values. We also used short reads to assemble the genome of Plasmopara muralis, a closely related species infecting grape ivy (Parthenocissus tricuspidata). The lineage-specific proteins identified by comparative genomics analysis included a large proportion of RxLR cytoplasmic effectors and, more generally, genes with high dN/dS values. We identified 270 candidate genes under positive selection, including several genes encoding transporters and components of the RNA machinery potentially involved in host specialization. Finally, the Pl. viticola genome assembly generated here will allow the development of robust population genomics approaches for investigating the mechanisms involved in adaptation to biotic and abiotic selective pressures in this species.

Natural Antisense Transcripts at the Interface between Host Genome and Mobile Genetic Elements

Non-coding RNAs are involved in epigenetic processes, playing a role in the regulation of gene expression at the transcriptional and post-transcriptional levels. A particular group of ncRNA are natural antisense transcripts (NATs); these are transcribed in the opposite direction to protein coding transcripts and are widespread in eukaryotes. Their abundance, evidence of phylogenetic conservation and an increasing number of well-characterized examples of antisense-mediated gene regulation are indicative of essential biological roles of NATs. There is evidence to suggest that they interfere with their corresponding sense transcript to elicit concordant and discordant regulation. The main mechanisms involved include transcriptional interference as well as dsRNA formation. Sense–antisense hybrid formation can trigger RNA interference, RNA editing or protein kinase R. However, the exact molecular mechanisms elicited by NATs in the context of these regulatory roles are currently poorly understood. Several examples confirm that ectopic expression of antisense transcripts trigger epigenetic silencing of the related sense transcript. Genomic approaches suggest that the antisense transcriptome carries a broader biological significance which goes beyond the physiological regulation of the directly related sense transcripts. Because NATs show evidence of conservation we speculate that they played a role in evolution, with early eukaryotes gaining selective advantage through the regulatory effects. With the surge of genome and transcriptome sequencing projects, there is promise of a more comprehensive understanding of the biological role of NATs and the regulatory mechanisms involved.

Epitope-tagged yeast strains reveal promoter driven changes to 3'-end formation and convergent antisense-transcription from common 3' UTRs

Epitope-tagging by homologous recombination is ubiquitously used to study gene expression, protein localization and function in yeast. This is generally thought to insulate the regulation of gene expression to that mediated by the promoter and coding regions because native 3′ UTR are replaced. Here we show that the 3′ UTRs, CYC1 and ADH1, contain cryptic promoters that generate abundant convergent antisense-transcription in Saccharomyces cerevisiae. Moreover we show that aberrant, truncating 3′ –end formation is often associated with regulated transcription in TAP-tagged strains. Importantly, the steady-state level of both 3′ –truncated and antisense transcription products is locus dependent. Using TAP and GFP-tagged strains we show that the transcriptional state of the gene-of-interest induces changes to 3′ –end formation by alternative polyadenylation and antisense transcription from a universal 3′ UTR. This means that these 3′ UTRs contains plastic features that can be molded to reflect the regulatory architecture of the locus rather than bringing their own regulatory paradigm to the gene-fusions as would be expected. Our work holds a cautionary note for studies utilizing tagged strains for quantitative biology, but also provides a new model for the study of promoter driven rewiring of 3′ –end formation and regulatory non-coding transcription.

An antisense RNA-mediated mechanism eliminates a meiosis-specific copper-regulated transcript in mitotic cells

Sense and antisense transcripts produced from convergent gene pairs could interfere with the expression of either partner gene. In Schizosaccharomyces pombe, we found that the iss1(+) gene produces two transcript isoforms, including a long antisense mRNA that is complementary to the meiotic cum1(+) sense transcript, inhibiting cum1(+) expression in vegetative cells. Inhibition of cum1(+) transcription was not at the level of its initiation because fusion of the cum1(+) promoter to the lacZ gene showed that activation of the reporter gene occurs in response to low copper conditions. Further analysis showed that the transcription factor Cuf1 and conserved copper-signaling elements (CuSEs) are required for induction of cum1(+)-lacZ transcription under copper deficiency. Insertion of a multipartite polyadenylation signal immediately downstream of iss1(+) led to the exclusive production of a shorter iss1(+) mRNA isoform, thereby allowing accumulation of cum1(+) sense mRNA in copper-limited vegetative cells. This finding suggested that the long iss1(+) antisense mRNA could pair with cum1(+) sense mRNA, thereby producing double-stranded RNA molecules that could induce RNAi. We consistently found that mutant strains for RNAi (dcr1Δ, ago1Δ, rdp1Δ, and clr4Δ) are defective in selectively eliminating cum1(+) sense transcript in the G1 phase of the cell cycle. Taken together, these results describe the first example of a copper-regulated meiotic gene repressed by an antisense transcription mechanism in vegetative cells.

Cytoplasmic Control of Sense-Antisense mRNA Pairs

Transcriptome analyses have revealed that convergent gene transcription can produce many 3'-overlapping mRNAs in diverse organisms. Few studies have examined the fate of 3'-complementary mRNAs in double-stranded RNA-dependent nuclear phenomena, and nothing is known about the cytoplasmic destiny of 3'-overlapping messengers or their impact on gene expression. Here, we demonstrate that the complementary tails of 3'-overlapping mRNAs can interact in the cytoplasm and promote post-transcriptional regulatory events including no-go decay (NGD) in Saccharomyces cerevisiae. Genome-wide experiments confirm that these messenger-interacting mRNAs (mimRNAs) form RNA duplexes in wild-type cells and thus have potential roles in modulating the mRNA levels of their convergent gene pattern under different growth conditions. We show that the post-transcriptional fate of hundreds of mimRNAs is controlled by Xrn1, revealing the extent to which this conserved 5'-3' cytoplasmic exoribonuclease plays an unexpected but key role in the post-transcriptional control of convergent gene expression.

Strand-specific RNA sequencing in Plasmodium falciparum malaria identifies developmentally regulated long non-coding RNA and circular RNA

Background

The human malaria parasite Plasmodium falciparum has a complex and multi-stage life cycle that requires extensive and precise gene regulation to allow invasion and hijacking of host cells, transmission, and immune escape. To date, the regulatory elements orchestrating these critical parasite processes remain largely unknown. Yet it is becoming increasingly clear that long non-coding RNAs (lncRNAs) could represent a missing regulatory layer across a broad range of organisms.

Results

To investigate the regulatory capacity of lncRNA in P. falciparum, we harvested fifteen samples from two time-courses. Our sample set profiled 56 h of P. falciparum blood stage development. We then developed and validated strand-specific, non-polyA-selected RNA sequencing methods, and pursued the first assembly of P. falciparum strand-specific transcript structures from RNA sequencing data. This approach enabled the annotation of over one thousand lncRNA transcript models and their comprehensive global analysis: coding prediction, periodicity, stage-specificity, correlation, GC content, length, location relative to annotated transcripts, and splicing. We validated the complete splicing structure of three lncRNAs with compelling properties. Non-polyA-selected deep sequencing also enabled the prediction of hundreds of intriguing P. falciparum circular RNAs, six of which we validated experimentally.

Conclusions

We found that a subset of lncRNAs, including all subtelomeric lncRNAs, strongly peaked in expression during invasion. By contrast, antisense transcript levels significantly dropped during invasion. As compared to neighboring mRNAs, the expression of antisense-sense pairs was significantly anti-correlated during blood stage development, indicating transcriptional interference. We also validated that P. falciparum produces circRNAs, which is notable given the lack of RNA interference in the organism, and discovered that a highly expressed, five-exon antisense RNA is poised to regulate P. falciparum gametocyte development 1 (PfGDV1), a gene required for early sexual commitment events.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1603-4) contains supplementary material, which is available to authorized users.

CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

BACKGROUND

The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study.

RESULTS

CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes.

CONCLUSIONS

We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available ( https://sourceforge.net/projects/codingquarry/ ), and suitable for incorporation into genome annotation pipelines.

Transcription interference and ORF nature strongly affect promoter strength in a reconstituted metabolic pathway

Fine tuning of individual enzyme expression level is necessary to alleviate metabolic imbalances in synthetic heterologous pathways. A known approach consists of choosing a suitable combination of promoters, based on their characterized strengths in model conditions. We questioned whether each step of a multiple-gene synthetic pathway could be independently tunable at the transcription level. Three open reading frames, coding for enzymes involved in a synthetic pathway, were combinatorially associated to different promoters on an episomal plasmid in Saccharomyces cerevisiae. We quantified the mRNA levels of the three genes in each strain of our generated combinatorial metabolic library. Our results evidenced that the ORF nature, position, and orientation induce strong discrepancies between the previously reported promoters' strengths and the observed ones. We conclude that, in the context of metabolic reconstruction, the strength of usual promoters can be dramatically affected by many factors. Among them, transcriptional interference and ORF nature seem to be predominant.

Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors

The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen's advantage. Proteinaceous effectors are synthesized intracellularly and must be externalized to interact with host cells. Computational prediction of secreted proteins from genomic sequences is an important technique to narrow down the candidate effector repertoire for subsequent experimental validation. In this study, we benchmark secretion prediction tools on experimentally validated fungal and oomycete effectors. We observe that for a set of fungal SwissProt protein sequences, SignalP 4 and the neural network predictors of SignalP 3 (D-score) and SignalP 2 perform best. For effector prediction in particular, the use of a sensitive method can be desirable to obtain the most complete candidate effector set. We show that the neural network predictors of SignalP 2 and 3, as well as TargetP were the most sensitive tools for fungal effector secretion prediction, whereas the hidden Markov model predictors of SignalP 2 and 3 were the most sensitive tools for oomycete effectors. Thus, previous versions of SignalP retain value for oomycete effector prediction, as the current version, SignalP 4, was unable to reliably predict the signal peptide of the oomycete Crinkler effectors in the test set. Our assessment of subcellular localization predictors shows that cytoplasmic effectors are often predicted as not extracellular. This limits the reliability of secretion predictions that depend on these tools. We present our assessment with a view to informing future pathogenomics studies and suggest revised pipelines for secretion prediction to obtain optimal effector predictions in fungi and oomycetes.