ExUTR: a novel pipeline for large-scale prediction of 3'-UTR sequences from NGS data

In silico identification and characterization of microRNAs from rotifers, cladocerans, and copepods

MicroRNAs (miRNAs) are short non-coding RNA molecules that regulate post-transcription and influence various biological processes across species. Despite various studies of miRNAs in vertebrates, plants, and other organisms, miRNA data in aquatic invertebrates are insufficient. In this study, we identified miRNAs from four aquatic invertebrate species that are widely used in aquatic toxicology: the rotifer Brachionus koreanus, the water flea Daphnia magna, the cyclopoid copepod Paracyclopina nana, and the harpacticoid copepod Tigriopus japonicus, using next-generation sequencing and in silico analysis. We identified total 188, 41, 47, and 100 miRNAs from each species, and target genes were predicted based on 3'-untranslated region information. Target prediction and functional annotation results provided the biological processes of these miRNAs in various development-related mechanisms, signaling transduction, and metabolism-related pathways. Moreover, the network between the miRNAs and their targets concerning defense-related and antioxidant genes suggests the suitability of miRNAs as biomarkers in ecotoxicological studies.

Mitochondrially mediated RNA interference, a retrograde signaling system affecting nuclear gene expression

Several functional classes of short noncoding RNAs are involved in manifold regulatory processes in eukaryotes, including, among the best characterized, miRNAs. One of the most intriguing regulatory networks in the eukaryotic cell is the mito-nuclear crosstalk: recently, miRNA-like elements of mitochondrial origin, called smithRNAs, were detected in a bivalve species, Ruditapes philippinarum. These RNA molecules originate in the organelle but were shown in vivo to regulate nuclear genes. Since miRNA genes evolve easily de novo with respect to protein-coding genes, in the present work we estimate the probability with which a newly arisen smithRNA finds a suitable target in the nuclear transcriptome. Simulations with transcriptomes of 12 bivalve species suggest that this probability is high and not species specific: one in a hundred million (1 × 10-8) if five mismatches between the smithRNA and the 3' mRNA are allowed, yet many more are allowed in animals. We propose that novel smithRNAs may easily evolve as exaptation of the pre-existing mitochondrial RNAs. In turn, the ability of evolving novel smithRNAs may have played a pivotal role in mito-nuclear interactions during animal evolution, including the intriguing possibility of acting as speciation trigger.

PolyAMiner-Bulk is a deep learning-based algorithm that decodes alternative polyadenylation dynamics from bulk RNA-seq data

Alternative polyadenylation (APA) is a key post-transcriptional regulatory mechanism; yet, its regulation and impact on human diseases remain understudied. Existing bulk RNA sequencing (RNA-seq)-based APA methods predominantly rely on predefined annotations, severely impacting their ability to decode novel tissue- and disease-specific APA changes. Furthermore, they only account for the most proximal and distal cleavage and polyadenylation sites (C/PASs). Deconvoluting overlapping C/PASs and the inherent noisy 3' UTR coverage in bulk RNA-seq data pose additional challenges. To overcome these limitations, we introduce PolyAMiner-Bulk, an attention-based deep learning algorithm that accurately recapitulates C/PAS sequence grammar, resolves overlapping C/PASs, captures non-proximal-to-distal APA changes, and generates visualizations to illustrate APA dynamics. Evaluation on multiple datasets strongly evinces the performance merit of PolyAMiner-Bulk, accurately identifying more APA changes compared with other methods. With the growing importance of APA and the abundance of bulk RNA-seq data, PolyAMiner-Bulk establishes a robust paradigm of APA analysis.

Long noncoding RNA study: Genome-wide approaches

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.

Differential expression of mRNA 3'-end isoforms in cervical and ovarian cancers

Early diagnosis and therapeutic targeting are continuing challenges for gynecological cancers. Here, we focus on cancer transcriptomes and describe the differential expression of 3'UTR isoforms in patients using an algorithm to detect differential poly(A) site usage. We find primarily 3'UTR shortening cases in cervical cancers compared with the normal cervix. We show differential expression of alternate 3'-end isoforms of FOXP1, VPS4B, and OGT in HPV16-positive patients who develop high-grade cervical lesions compared with the infected but non-progressing group. In contrast, in ovarian cancers, 3'UTR lengthening is more evident compared with normal ovary tissue. Nevertheless, highly malignant ovarian tumors have unique 3'UTR shortening events (e.g., CHRAC1, SLC16A1, and TOP2A), some of which correlate with upregulated protein levels in tumors. Overall, our study shows isoform level deregulation in gynecological cancers and highlights the complexity of the transcriptome. This transcript diversity could help identify novel cancer genes and provide new possibilities for diagnosis and therapy.

Evidence-Based Guide to Using Artificial Introns for Tissue-Specific Knockout in Mice

Up until recently, methods for generating floxed mice either conventionally or by CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas9 (CRISPR-associated protein 9) editing have been technically challenging, expensive and error-prone, or time-consuming. To circumvent these issues, several labs have started successfully using a small artificial intron to conditionally knockout (KO) a gene of interest in mice. However, many other labs are having difficulty getting the technique to work. The key problem appears to be either a failure in achieving correct splicing after the introduction of the artificial intron into the gene or, just as crucial, insufficient functional KO of the gene's protein after Cre-induced removal of the intron's branchpoint. Presented here is a guide on how to choose an appropriate exon and where to place the recombinase-regulated artificial intron (rAI) in that exon to prevent disrupting normal gene splicing while maximizing mRNA degradation after recombinase treatment. The reasoning behind each step in the guide is also discussed. Following these recommendations should increase the success rate of this easy, new, and alternative technique for producing tissue-specific KO mice.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.

Symbiosis preservation: Putative regulation of fatty acyl-CoA reductase by miR-31a within the symbiont harboring bacteriome through tsetse evolution

Tsetse flies are the sole vectors of African trypanosomes. In addition to trypanosomes, tsetse harbor obligate Wigglesworthia glossinidia bacteria that are essential to tsetse biology. The absence of Wigglesworthia results in fly sterility, thus offering promise for population control strategies. Here, microRNA (miRNAs) and mRNA expression are characterized and compared between the exclusive Wigglesworthia-containing bacteriome and adjacent aposymbiotic tissue in females of two evolutionarily distant tsetse species (Glossina brevipalpis and G. morsitans). A total of 193 miRNAs were expressed in either species, with 188 of these expressed in both species, 166 of these were novel to Glossinidae, and 41 miRNAs exhibited comparable expression levels between species. Within bacteriomes, 83 homologous mRNAs demonstrated differential expression between G. morsitans aposymbiotic and bacteriome tissues, with 21 of these having conserved interspecific expression. A large proportion of these differentially expressed genes are involved in amino acid metabolism and transport, symbolizing the essential nutritional role of the symbiosis. Further bioinformatic analyses identified a sole conserved miRNA::mRNA interaction (miR-31a::fatty acyl-CoA reductase) within bacteriomes likely catalyzing the reduction of fatty acids to alcohols which comprise components of esters and lipids involved in structural maintenance. The Glossina fatty acyl-CoA reductase gene family is characterized here through phylogenetic analyses to further understand its evolutionary diversification and the functional roles of members. Further research to characterize the nature of the miR-31a::fatty acyl-CoA reductase interaction may find novel contributions to the symbiosis to be exploited for vector control.

Integrated analysis of miRNA and mRNA expression profiles in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis

Insect gut microbiota has been reported to participate in regulating host multiple biological processes including metabolism and reproduction. However, the corresponding molecular mechanisms remain largely unknown. Recent studies suggest that microRNAs (miRNAs) are involved in complex interactions between the gut microbiota and the host. Here, we used next-generation sequencing technology to characterize miRNA and mRNA expression profiles and construct the miRNA-gene regulatory network in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis. A total of 3016 differentially expressed genes (DEGs) and 18 differentially expressed miRNAs (DEMs) were identified. Based on the integrated analysis of miRNA and mRNA sequencing data, 229 negatively correlated miRNA-gene pairs were identified from the miRNA-mRNA network. Gene ontology enrichment analysis indicated that DEMs could target several genes involved in the metabolic process, oxidation-reduction process, oogenesis, and insulin signaling pathway. Finally, real-time quantitative polymerase chain reaction further verified the accuracy of RNA sequencing results. In conclusion, our study provides the profiles of miRNA and mRNA expressions under antibiotics treatment and provides an insight into the roles of miRNAs and their target genes in the interaction between the gut microbiota and its host.

peaks2utr: a robust Python tool for the annotation of 3' UTRs

SUMMARY

Annotation of nonmodel organisms is an open problem, especially the detection of untranslated regions (UTRs). Correct annotation of UTRs is crucial in transcriptomic analysis to accurately capture the expression of each gene yet is mostly overlooked in annotation pipelines. Here we present peaks2utr, an easy-to-use Python command line tool that uses the UTR enrichment of single-cell technologies, such as 10× Chromium, to accurately annotate 3' UTRs for a given canonical annotation.

AVAILABILITY AND IMPLEMENTATION

peaks2utr is implemented in Python 3 (≥3.8). It is available via PyPI at https://pypi.org/project/peaks2utr and GitHub at https://github.com/haessar/peaks2utr. It is licensed under GNU GPLv3.

A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3' untranslated region, tissue-specific, cross-species, and single-cell pA prediction.

Identification of miRNAs of Strongyloides stercoralis L1 and iL3 larvae isolated from human stool

Strongyloidiasis is a neglected tropical disease caused by the soil-transmitted nematode by Strongyloides stercoralis, that affects approximately 600 million people worldwide. In immunosuppressed individuals disseminated strongyloidiasis can rapidly lead to fatal outcomes. There is no gold standard for diagnosing strongyloidiasis, and infections are frequently misdiagnosed. A better understanding of the molecular biology of this parasite can be useful for example for the discovery of potential new biomarkers. Interestingly, recent evidence showed the presence of small RNAs in Strongyloididae, but no data was provided for S. stercoralis. In this study, we present the first identification of miRNAs of both L1 and iL3 larval stages of S. stercoralis. For our purpose, the aims were: (i) to analyse the miRNome of L1 and iL3 S. stercoralis and to identify potential miRNAs of this nematode, (ii) to obtain the mRNAs profiles in these two larval stages and (iii) to predict potential miRNA target sites in mRNA sequences. Total RNA was isolated from L1 and iL3 collected from the stool of 5 infected individuals. For the miRNAs analysis, we used miRDeep2 software and a pipeline of bio-informatic tools to construct a catalog of a total of 385 sequences. Among these, 53% were common to S. ratti, 19% to S. papillosus, 1% to Caenorhabditis elegans and 44% were novel. Using a differential analysis between the larval stages, we observed 6 suggestive modulated miRNAs (STR-MIR-34A-3P, STR-MIR-8397-3P, STR-MIR-34B-3P and STR-MIR-34C-3P expressed more in iL3, and STR-MIR-7880H-5P and STR-MIR-7880M-5P expressed more in L1). Along with this analysis, we obtained also the mRNAs profiles in the same samples of larvae. Multiple testing found 81 statistically significant mRNAs of the total 1553 obtained (FDR < 0.05; 32 genes expressed more in L1 than iL3; 49 genes expressed more in L3 than iL1). Finally, we found 33 predicted mRNA targets of the modulated miRNAs, providing relevant data for a further validation to better understand the role of these small molecules in the larval stages and their valuein clinical diagnostics.

Leveraging omic features with F3UTER enables identification of unannotated 3'UTRs for synaptic genes

There is growing evidence for the importance of 3' untranslated region (3'UTR) dependent regulatory processes. However, our current human 3'UTR catalogue is incomplete. Here, we develop a machine learning-based framework, leveraging both genomic and tissue-specific transcriptomic features to predict previously unannotated 3'UTRs. We identify unannotated 3'UTRs associated with 1,563 genes across 39 human tissues, with the greatest abundance found in the brain. These unannotated 3'UTRs are significantly enriched for RNA binding protein (RBP) motifs and exhibit high human lineage-specificity. We find that brain-specific unannotated 3'UTRs are enriched for the binding motifs of important neuronal RBPs such as TARDBP and RBFOX1, and their associated genes are involved in synaptic function. Our data is shared through an online resource F3UTER ( https://astx.shinyapps.io/F3UTER/ ). Overall, our data improves 3'UTR annotation and provides additional insights into the mRNA-RBP interactome in the human brain, with implications for our understanding of neurological and neurodevelopmental diseases.

Amino Acids and IGF1 Regulation of Fish Muscle Growth Revealed by Transcriptome and microRNAome Integrative Analyses of Pacu (Piaractus mesopotamicus) Myotubes

Amino acids (AA) and IGF1 have been demonstrated to play essential roles in protein synthesis and fish muscle growth. The myoblast cell culture is useful for studying muscle regulation, and omics data have contributed enormously to understanding its molecular biology. However, to our knowledge, no study has performed the large-scale sequencing of fish-cultured muscle cells stimulated with pro-growth signals. In this work, we obtained the transcriptome and microRNAome of pacu (Piaractus mesopotamicus)-cultured myotubes treated with AA or IGF1. We identified 1228 and 534 genes differentially expressed by AA and IGF1. An enrichment analysis showed that AA treatment induced chromosomal changes, mitosis, and muscle differentiation, while IGF1 modulated IGF/PI3K signaling, metabolic alteration, and matrix structure. In addition, potential molecular markers were similarly modulated by both treatments. Muscle-miRNAs (miR-1, -133, -206 and -499) were up-regulated, especially in AA samples, and we identified molecular networks with omics integration. Two pairs of genes and miRNAs demonstrated a high-level relationship, and involvement in myogenesis and muscle growth: marcksb and miR-29b in AA, and mmp14b and miR-338-5p in IGF1. Our work helps to elucidate fish muscle physiology and metabolism, highlights potential molecular markers, and creates a perspective for improvements in aquaculture and in in vitro meat production.

Computational Detection of MicroRNA Targets

MicroRNAs (miRNAs) are small noncoding RNAs that are recognized as posttranscriptional regulators of gene expression. These molecules have been shown to play important roles in several cellular processes. MiRNAs act on their target by guiding the RISC complex and binding to the mRNA molecule. Thus, it is recognized that the function of a miRNA is determined by the function of its target (s). By using high-throughput methodologies, novel miRNAs are being identified, but their functions remain uncharted. Target validation is crucial to properly understand the specific role of a miRNA in a cellular pathway. However, molecular techniques for experimental validation of miRNA-target interaction are expensive, time-consuming, laborious, and can be not accurate in inferring true interactions. Thus, accurate miRNA target predictions are helpful to understand the functions of miRNAs. There are several algorithms proposed for target prediction and databases containing miRNA-target information. However, these available computational tools for prediction still generate a large number of false positives and fail to detect a considerable number of true targets, which indicates the necessity of highly confident approaches to identify bona fide miRNA-target interactions. This chapter focuses on tools and strategies used for miRNA target prediction, by providing practical insights and outlooks.

Genome annotation with long RNA reads reveals new patterns of gene expression and improves single-cell analyses in an ant brain

BACKGROUND

Functional genomic analyses rely on high-quality genome assemblies and annotations. Highly contiguous genome assemblies have become available for a variety of species, but accurate and complete annotation of gene models, inclusive of alternative splice isoforms and transcription start and termination sites, remains difficult with traditional approaches.

RESULTS

Here, we utilized full-length isoform sequencing (Iso-Seq), a long-read RNA sequencing technology, to obtain a comprehensive annotation of the transcriptome of the ant Harpegnathos saltator. The improved genome annotations include additional splice isoforms and extended 3' untranslated regions for more than 4000 genes. Reanalysis of RNA-seq experiments using these annotations revealed several genes with caste-specific differential expression and tissue- or caste-specific splicing patterns that were missed in previous analyses. The extended 3' untranslated regions afforded great improvements in the analysis of existing single-cell RNA-seq data, resulting in the recovery of the transcriptomes of 18% more cells. The deeper single-cell transcriptomes obtained with these new annotations allowed us to identify additional markers for several cell types in the ant brain, as well as genes differentially expressed across castes in specific cell types.

CONCLUSIONS

Our results demonstrate that Iso-Seq is an efficient and effective approach to improve genome annotations and maximize the amount of information that can be obtained from existing and future genomic datasets in Harpegnathos and other organisms.

Transcriptome Profiling of Atlantic Salmon Adherent Head Kidney Leukocytes Reveals That Macrophages Are Selectively Enriched During Culture

The Atlantic salmon (Salmo salar) is an economically important fish, both in aquaculture and in the wild. In vertebrates, macrophages are some of the first cell types to respond to pathogen infection and disease. While macrophage biology has been characterized in mammals, less is known in fish. Our previous work identified changes in the morphology, phagocytic ability, and miRNA profile of Atlantic salmon adherent head kidney leukocytes (HKLs) from predominantly “monocyte-like” at Day 1 of in vitro culture to predominantly “macrophage-like” at Day 5 of culture. Therefore, to further characterize these two cell populations, we examined the mRNA transcriptome profile in Day 1 and Day 5 HKLs using a 44K oligonucleotide microarray. Large changes in the transcriptome were revealed, including changes in the expression of macrophage and immune-related transcripts (e.g. csf1r, arg1, tnfa, mx2), lipid-related transcripts (e.g. fasn, dhcr7, fabp6), and transcription factors involved in macrophage differentiation and function (e.g. klf2, klf9, irf7, irf8, stat1). The in silico target prediction analysis of differentially expressed genes (DEGs) using miRNAs known to change expression in Day 5 HKLs, followed by gene pathway enrichment analysis, supported that these miRNAs may be involved in macrophage maturation by targeting specific DEGs. Elucidating how immune cells, such as macrophages, develop and function is a key step in understanding the Atlantic salmon immune system. Overall, the results indicate that, without the addition of exogenous factors, the adherent HKL cell population differentiates in vitro to become macrophage-like.

Integrated miRNA and transcriptome profiling to explore the molecular determinism of convergent adaptation to corn in two lepidopteran pests of agriculture

Background

The degree to which adaptation to same environment is determined by similar molecular mechanisms, is a topic of broad interest in evolutionary biology, as an indicator of evolutionary predictability. We wished to address if adaptation to the same host plant in phytophagous insects involved related gene expression patterns. We compared sRNA-Seq and RNA-Seq data between two pairs of taxa of Ostrinia and Spodoptera frugiperda sharing maize as host-plant. For the latter, we had previously carried out a reciprocal transplant experiment by feeding of the larvae of the Corn strain (Sf-C) and the Rice strain (Sf-R) on corn versus rice and characterized the mRNA and miRNA responses.

Results

First, we predicted the genes encoding miRNA in Ostrinia nubilalis (On) and O. scapulalis (Os). Respectively 67 and 65 known miRNA genes, as well as 196 and 190 novel ones were predicted with Os genome using sncRNAs extracted from whole larvae feeding on corn or mugwort. In On, a read counts analysis showed that 37 (55.22%) known miRNAs and 19 (9.84%) novel miRNAs were differentially expressed (DE) on mugwort compared to corn (in Os, 25 known miRs (38.46%) and 8 novel ones (4.34%)). Between species on corn, 8 (12.5%) known miRNAs and 8 (6.83%) novel ones were DE while only one novel miRNA showed expression variation between species on mugwort. Gene target prediction led to the identification of 2953 unique target genes in On and 2719 in Os, among which 11.6% (344) were DE when comparing species on corn. 1.8% (54) of On miR targets showed expression variation upon a change of host-plant.

We found molecular changes matching convergent phenotype, i.e., a set of nine miRNAs that are regulated either according to the host-plant both in On and Sf-C or between them on the same plant, corn. Among DE miR target genes between taxa, 13.7% shared exactly the same annotation between the two pairs of taxa and had function related to insect host-plant interaction.

Conclusion

There is some similarity in underlying genetic mechanisms of convergent evolution of two distant Lepidopteran species having adopted corn in their host range, highlighting possible adaptation genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07905-7.

The microRNA target site landscape is a novel molecular feature associating alternative polyadenylation with immune evasion activity in breast cancer

Alternative polyadenylation (APA) in breast tumor samples results in the removal/addition of cis-regulatory elements such as microRNA (miRNA) target sites in the 3'-untranslated region (3'-UTRs) of genes. Although previous computational APA studies focused on a subset of genes strongly affected by APA (APA genes), we identify miRNAs of which widespread APA events collectively increase or decrease the number of target sites [probabilistic inference of microRNA target site modification through APA (PRIMATA-APA)]. Using PRIMATA-APA on the cancer genome atlas (TCGA) breast cancer data, we found that the global APA events change the number of the target sites of particular microRNAs [target sites modified miRNA (tamoMiRNA)] enriched for cancer development and treatments. We also found that when knockdown (KD) of NUDT21 in HeLa cells induces a different set of widespread 3'-UTR shortening than TCGA breast cancer data, it changes the target sites of the common tamoMiRNAs. Since the NUDT21 KD experiment previously demonstrated the tumorigenic role of APA events in a miRNA dependent fashion, this result suggests that the APA-initiated tumorigenesis is attributable to the miRNA target site changes, not the APA events themselves. Further, we found that the miRNA target site changes identify tumor cell proliferation and immune cell infiltration to the tumor microenvironment better than the miRNA expression levels or the APA events themselves. Altogether, our computational analyses provide a proof-of-concept demonstration that the miRNA target site information indicates the effect of global APA events with a potential as predictive biomarker.

High-throughput insertional mutagenesis reveals novel targets for enhancing lipid accumulation in Nannochloropsis oceanica

The microalga Nannochloropsis oceanica is considered a promising platform for the sustainable production of high-value lipids and biofuel feedstocks. However, current lipid yields of N. oceanica are too low for economic feasibility. Gaining fundamental insights into the lipid metabolism of N. oceanica could open up various possibilities for the optimization of this species through genetic engineering. Therefore, the aim of this study was to discover novel genes associated with an elevated neutral lipid content. We constructed an insertional mutagenesis library of N. oceanica, selected high lipid mutants by five rounds of fluorescence-activated cell sorting, and identified disrupted genes using a novel implementation of a rapid genotyping procedure. One particularly promising mutant (HLM23) was disrupted in a putative APETALA2-like transcription factor gene. HLM23 showed a 40%-increased neutral lipid content, increased photosynthetic performance, and no growth impairment. Furthermore, transcriptome analysis revealed an upregulation of genes related to plastidial fatty acid biosynthesis, glycolysis and the Calvin-Benson-Bassham cycle in HLM23. Insights gained in this work can be used in future genetic engineering strategies for increased lipid productivity of Nannochloropsis.

Differential expression of microRNAs and tRNA fragments mediate the adaptation of the liver fluke Fasciola gigantica to its intermediate snail and definitive mammalian hosts

The tropical liver fluke Fasciola gigantica affects livestock and humans in many Asian countries, large parts of Africa, and parts of Europe. Despite the public health and economic impacts of F. gigantica, understanding of F. gigantica biology and how the complex lifecycle of this liver fluke is transcriptionally regulated remain unknown. Here, we tested the hypothesis that the regulatory small non-coding RNAs (sncRNAs), microRNAs (miRNAs) and tRNA-derived fragments (tRFs) play roles in the adaptation of F. gigantica to its intermediate and definitive hosts. We sequenced sncRNAs of eight lifecycle stages of F. gigantica. In total, 56 miRNAs from 33 conserved families and four Fasciola-specific miRNAs were identified. Expression analysis of miRNAs suggested clear stage-related patterns. By leveraging the existing transcriptomic data, we predicted a miRNA-based regulation of metabolism, transport, growth and developmental processes. Also, by comparing miRNA complement of F. gigantica with that of Fasciola hepatica, we detected a high level of conservation and identified differences in some miRNAs, which can be used to distinguish the two species. Moreover, we found that tRFs at each lifecycle stage were predominantly derived by tRNA^-Lys and tRNA^-Gly at 5' half sites, but relatively high expression was related to the buffalo-infecting stages. Taken together, we provided a comprehensive overview of the dynamic transcriptional changes of small RNAs that occur during the developmental stages of F. gigantica. This global analysis of F. gigantica lifecycle stages revealed new roles of miRNAs and tRFs in parasite development and will facilitate future research into understanding of fasciolosis pathobiology.

Profiling Alternative 3' Untranslated Regions in Sorghum using RNA-seq Data

Sorghum is an important crop widely used for food, feed, and fuel. Transcriptome-wide studies of 3′ untranslated regions (3′UTR) using regular RNA-seq remain scarce in sorghum, while transcriptomes have been characterized extensively using Illumina short-read sequencing platforms for many sorghum varieties under various conditions or developmental contexts. 3′UTR is a critical regulatory component of genes, controlling the translation, transport, and stability of messenger RNAs. In the present study, we profiled the alternative 3′UTRs at the transcriptome level in three genetically related but phenotypically contrasting lines of sorghum: Rio, BTx406, and R9188. A total of 1,197 transcripts with alternative 3′UTRs were detected using RNA-seq data. Their categorization identified 612 high-confidence alternative 3′UTRs. Importantly, the high-confidence alternative 3′UTR genes significantly overlapped with the genesets that are associated with RNA N⁶-methyladenosine (m⁶A) modification, suggesting a clear indication between alternative 3′UTR and m⁶A methylation in sorghum. Moreover, taking advantage of sorghum genetics, we provided evidence of genotype specificity of alternative 3′UTR usage. In summary, our work exemplifies a transcriptome-wide profiling of alternative 3′UTRs using regular RNA-seq data in non-model crops and gains insights into alternative 3′UTRs and their genotype specificity.

A Day in the Life: Identification of Developmentally Regulated MicroRNAs in the Colorado Potato Beetle (Leptinotarsa decemlineata; Coleoptera: Chrysomelidae)

The Colorado potato beetle (Leptinotarsa decemlineata (Say)) is an important pest of the cultivated potato (Solanum tuberosum (L.) [Solanales: Solanaceae]). With its broad resistance toward commonly used insecticides, it is clear that more sophisticated control strategies are needed. Due to their importance in insect development, microRNAs (miRNAs) represent a potential tool to employ in insect control strategies. However, most studies conducted in this area have focused on model species with well-annotated genomes. In this study, next-generation sequencing was used to catalogue the miRNAs produced by L. decemlineata across all eight stages of its development, from eggs to adults. For most stages, the length of miRNAs peaked between 21 and 22 nt, though it was considerably longer for the egg stage (26 nt). Global profiling of miRNAs revealed three distinct developmental clusters: 1) egg stage; 2) early stage (first, second, and third instar); and 3) late stage (fourth instar, prepupae, pupae, and adult). We identified 86 conserved miRNAs and 33 bonafide novel miRNAs, including stage-specific miRNAs and those not previously identified in L. decemlineata. Most of the conserved miRNAs were found in multiple developmental stages, whereas the novel miRNAs were often stage specific with the bulk identified in the egg stage. The identified miRNAs have a myriad of putative functions, including growth, reproduction, and insecticide resistance. We discuss the putative roles of some of the most notable miRNAs in the regulation of L. decemlineata development, as well as the potential applications of this research in Colorado potato beetle management.

CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts

Motivation

Characterization of the coding sequences (CDSs) is an essential step in transcriptome annotation. Incorrect identification of CDSs can lead to the prediction of non-existent proteins that can eventually compromise knowledge if databases are populated with similar incorrect predictions made in different genomes. Also, the correct identification of CDSs is important for the characterization of the untranslated regions (UTRs), which are known to be important regulators of the mRNA translation process. Considering this, we present CodAn (Coding sequence Annotator), a new approach to predict confident CDS and UTR regions in full or partial transcriptome sequences in eukaryote species.

Results

Our analysis revealed that CodAn performs confident predictions on full-length and partial transcripts with the strand sense of the CDS known or unknown. The comparative analysis showed that CodAn presents better overall performance than other approaches, mainly when considering the correct identification of the full CDS (i.e. correct identification of the start and stop codons). In this sense, CodAn is the best tool to be used in projects involving transcriptomic data.

Availability

CodAn is freely available at https://github.com/pedronachtigall/CodAn.

Contact

aland@usp.br

Supplementary information

Supplementary data are available at Briefings in Bioinformatics online.

Clues of in vivo nuclear gene regulation by mitochondrial short non-coding RNAs

Gene expression involves multiple processes, from transcription to translation to the mature, functional peptide, and it is regulated at multiple levels. Small RNA molecules are known to bind RNA messengers affecting their fate in the cytoplasm (a process generically termed ‘RNA interference’). Such small regulatory RNAs are well-known to be originated from the nuclear genome, while the role of mitochondrial genome in RNA interference was largely overlooked. However, evidence is growing that mitochondrial DNA does provide the cell a source of interfering RNAs. Small mitochondrial highly transcribed RNAs (smithRNAs) have been proposed to be transcribed from the mitochondrion and predicted to regulate nuclear genes. Here, for the first time, we show in vivo clues of the activity of two smithRNAs in the Manila clam, Ruditapes philippinarum. Moreover, we show that smithRNAs are present and can be annotated in representatives of the three main bilaterian lineages; in some cases, they were already described and assigned to a small RNA category (e.g., piRNAs) given their biogenesis, while in other cases their biogenesis remains unclear. If mitochondria may affect nuclear gene expression through RNA interference, this opens a plethora of new possibilities for them to interact with the nucleus and makes metazoan mitochondrial DNA a much more complex genome than previously thought.

A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data

Alternative polyadenylation (APA) has been implicated to play an important role in post-transcriptional regulation by regulating mRNA abundance, stability, localization and translation, which contributes considerably to transcriptome diversity and gene expression regulation. RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.

Analysis of alternative cleavage and polyadenylation in mature and differentiating neurons using RNA-seq data

Background

Most eukaryotic protein-coding genes exhibit alternative cleavage and polyadenylation (APA), resulting in mRNA isoforms with different 3' untranslated regions (3' UTRs). Studies have shown that brain cells tend to express long 3' UTR isoforms using distal cleavage and polyadenylation sites (PASs).

Methods

Using our recently developed, comprehensive PAS database PolyA_DB, we developed an efficient method to examine APA, named Significance Analysis of Alternative Polyadenylation using RNA-seq (SAAP-RS). We applied this method to study APA in brain cells and neurogenesis.

Results

We found that neurons globally express longer 3' UTRs than other cell types in brain, and microglia and endothelial cells express substantially shorter 3' UTRs. We show that the 3' UTR diversity across brain cells can be corroborated with single cell sequencing data. Further analysis of APA regulation of 3' UTRs during differentiation of embryonic stem cells into neurons indicates that a large fraction of the APA events regulated in neurogenesis are similarly modulated in myogenesis, but to a much greater extent.

Conclusion

Together, our data delineate APA profiles in different brain cells and indicate that APA regulation in neurogenesis is largely an augmented process taking place in other types of cell differentiation.