De novo transcriptome assembly: A comprehensive cross-species comparison of short-read RNA-Seq assemblers

Trans2express - de novo transcriptome assembly pipeline optimized for gene expression analysis

BACKGROUND

As genomes of many eukaryotic species, especially plants, are large and complex, their de novo sequencing and assembly is still a difficult task despite progress in sequencing technologies. An alternative to genome assembly is the assembly of transcriptome, the set of RNA products of the expressed genes. While a bunch of de novo transcriptome assemblers exists, the challenges of transcriptomes (the existence of isoforms, the uneven expression levels across genes) complicates the generation of high-quality assemblies suitable for downstream analyses.

RESULTS

We developed Trans2express - a web-based tool and a pipeline of de novo hybrid transcriptome assembly and postprocessing based on rnaSPAdes with a set of subsequent filtrations. The pipeline was tested on Arabidopsis thaliana cDNA sequencing data obtained using Illumina and Oxford Nanopore Technologies platforms and three non-model plant species. The comparison of structural characteristics of the transcriptome assembly with reference Arabidopsis genome revealed the high quality of assembled transcriptome with 86.1% of Arabidopsis expressed genes assembled as a single contig. We tested the applicability of the transcriptome assembly for gene expression analysis. For both Arabidopsis and non-model species the results showed high congruence of gene expression levels and sets of differentially expressed genes between analyses based on genome and based on the transcriptome assembly.

CONCLUSIONS

We present Trans2express - a protocol for de novo hybrid transcriptome assembly aimed at recovering of a single transcript per gene. We expect this protocol to promote the characterization of transcriptomes and gene expression analysis in non-model plants and web-based tool to be of use to a wide range of plant biologists.

Endogenous Bornavirus-like Elements in Bats: Evolutionary Insights from the Conserved Riboviral L-Gene in Microbats and Its Antisense Transcription in Myotis daubentonii

Bats are ecologically diverse vertebrates characterized by their ability to host a wide range of viruses without apparent illness and the presence of numerous endogenous viral elements (EVEs). EVEs are well preserved, expressed, and may affect host biology and immunity, but their role in bat immune system evolution remains unclear. Among EVEs, endogenous bornavirus-like elements (EBLs) are bornavirus sequences integrated into animal genomes. Here, we identified a novel EBL in the microbat Myotis daubentonii, EBLL-Cultervirus.10-MyoDau (short name is CV.10-MyoDau) that shows protein-level conservation with the L-protein of a Cultervirus (Wuhan sharpbelly bornavirus). Surprisingly, we discovered a transcript on the antisense strand comprising three exons, which we named AMCR-MyoDau. The active transcription in Myotis daubentonii tissues of AMCR-MyoDau, confirmed by RNA-Seq analysis and RT-PCR, highlights its potential role during viral infections. Using comparative genomics comprising 63 bat genomes, we demonstrate nucleotide-level conservation of CV.10-MyoDau and AMCR-MyoDau across various bat species and its detection in 22 Yangochiropera and 12 Yinpterochiroptera species. To the best of our knowledge, this marks the first occurrence of a conserved EVE shared among diverse bat species, which is accompanied by a conserved antisense transcript. This highlights the need for future research to explore the role of EVEs in shaping the evolution of bat immunity.

LSTrAP-denovo: Automated Generation of Transcriptome Atlases for Eukaryotic Species Without Genomes

Despite the abundance of species with transcriptomic data, a significant number of species still lack sequenced genomes, making it difficult to study gene function and expression in these organisms. While de novo transcriptome assembly can be used to assemble protein-coding transcripts from RNA-sequencing (RNA-seq) data, the datasets used often only feature samples of arbitrarily selected or similar experimental conditions, which might fail to capture condition-specific transcripts. We developed the Large-Scale Transcriptome Assembly Pipeline for de novo assembled transcripts (LSTrAP-denovo) to automatically generate transcriptome atlases of eukaryotic species. Specifically, given an NCBI TaxID, LSTrAP-denovo can (1) filter undesirable RNA-seq accessions based on read data, (2) select RNA-seq accessions via unsupervised machine learning to construct a sample-balanced dataset for download, (3) assemble transcripts via over-assembly, (4) functionally annotate coding sequences (CDS) from assembled transcripts and (5) generate transcriptome atlases in the form of expression matrices for downstream transcriptomic analyses. LSTrAP-denovo is easy to implement, written in Python, and is freely available at https://github.com/pengkenlim/LSTrAP-denovo/.

Transcriptome sequencing of the endangered land snail Karaftohelix adamsi from the Island Ulleung: De novo assembly, annotation, valuation of fitness genes and SSR markers

BACKGROUND

The Bradybaenidae snail Karaftohelix adamsi is endemic to Korea, with the species tracked from Island Ulleung in North Gyeongsang Province of South Korea. K. adamsi has been classified under the Endangered Wildlife Class II species of Korea and poses a severe risk of extinction following habitat disturbances. With no available information at the DNA (genome) or mRNA (transcriptome) level for the species, conservation by utilizing informed molecular resources seems difficult.

OBJECTIVE

In this study, we used the Illumina short-read sequencing and Trinity de novo assembly to draft the reference transcriptome of K. adamsi.

RESULTS

After assembly, 13,753 unigenes were obtained of which 10,511 were annotated to public databases (a maximum of 10,165 unigenes found homologs in PANM DB). A total of 6,351, 3,535, 358, and 3,407 unigenes were ascribed to the functional categories under KOG, GO, KEGG, and IPS, respectively. The transcripts such as the HSP 70, aquaporin, TLR, and MAPK, among others, were screened as putative functional resources for adaptation. DNA transposons were found to be thickly populated in comparison to retrotransposons in the assembled unigenes. Further, 2,164 SSRs were screened with the promiscuous presence of dinucleotide repeats such as AC/GT and AG/CT.

CONCLUSION

The transcriptome-guided discovery of molecular resources in K. adamsi will not only serve as a basis for functional genomics studies but also provide sustainable tools to be utilized for the protection of the species in the wild. Moreover, the development of polymorphic SSRs is valuable for the identification of species from newer habitats and cross-species genotyping.

De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide

Many questions in biology benefit greatly from the use of a variety of model systems. High-throughput sequencing methods have been a triumph in the democratization of diverse model systems. They allow for the economical sequencing of an entire genome or transcriptome of interest, and with technical variations can even provide insight into genome organization and the expression and regulation of genes. The analysis and biological interpretation of such large datasets can present significant challenges that depend on the 'scientific status' of the model system. While high-quality genome and transcriptome references are readily available for well-established model systems, the establishment of such references for an emerging model system often requires extensive resources such as finances, expertise and computation capabilities. The de novo assembly of a transcriptome represents an excellent entry point for genetic and molecular studies in emerging model systems as it can efficiently assess gene content while also serving as a reference for differential gene expression studies. However, the process of de novo transcriptome assembly is non-trivial, and as a rule must be empirically optimized for every dataset. For the researcher working with an emerging model system, and with little to no experience with assembling and quantifying short-read data from the Illumina platform, these processes can be daunting. In this guide we outline the major challenges faced when establishing a reference transcriptome de novo and we provide advice on how to approach such an endeavor. We describe the major experimental and bioinformatic steps, provide some broad recommendations and cautions for the newcomer to de novo transcriptome assembly and differential gene expression analyses. Moreover, we provide an initial selection of tools that can assist in the journey from raw short-read data to assembled transcriptome and lists of differentially expressed genes.

Probiotic Insights from the Genomic Exploration of Lacticaseibacillus paracasei Strains Isolated from Fermented Palm Sap

This study focused on L. paracasei strains isolated from fermented palm sap in southern Thailand that exhibit potential probiotic characteristics, including antibiotic susceptibility, resistance to gastrointestinal stresses, and antimicrobial activity against various pathogens. However, a thorough investigation of the whole genome sequences of L. paracasei isolates is required to ensure their safety and probiotic properties for human applications. This study aimed to sequence the genome of L. paracasei isolated from fermented palm sap, to assess its safety profile, and to conduct a comprehensive comparative genomic analysis with other Lacticaseibacillus species. The genome sizes of the seven L. paracasei strains ranged from 3,070,747 bp to 3,131,129 bp, with a GC content between 46.11% and 46.17% supporting their classification as nomadic lactobacilli. In addition, the minimal presence of cloud genes and a significant number of core genes suggest a high degree of relatedness among the strains. Meanwhile, phylogenetic analysis of core genes revealed that the strains possessed distinct genes and were grouped into two distinct clades. Genomic analysis revealed key genes associated with probiotic functions, such as those involved in gastrointestinal, oxidative stress resistance, vitamin synthesis, and biofilm disruption. This study is consistent with previous studies that used whole-genome sequencing and bioinformatics to assess the safety and potential benefits of probiotics in various food fermentation processes. Our findings provide valuable insights into the potential use of seven L. paracasei strains isolated from fermented palm sap as probiotic and postbiotic candidates in functional foods and pharmaceuticals.

A cloud-based training module for efficient de novo transcriptome assembly using Nextflow and Google cloud

This study describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" (https://github.com/NIGMS/NIGMS-Sandbox). The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on de novo transcriptome assembly using Nextflow in an interactive format that uses appropriate cloud resources for data access and analysis. Cloud computing is a powerful new means by which biomedical researchers can access resources and capacity that were previously either unattainable or prohibitively expensive. To take advantage of these resources, however, the biomedical research community needs new skills and knowledge. We present here a cloud-based training module, developed in conjunction with Google Cloud, Deloitte Consulting, and the NIH STRIDES Program, that uses the biological problem of de novo transcriptome assembly to demonstrate and teach the concepts of computational workflows (using Nextflow) and cost- and resource-efficient use of Cloud services (using Google Cloud Platform). Our work highlights the reduced necessity of on-site computing resources and the accessibility of cloud-based infrastructure for bioinformatics applications.

Assessment and Partial Characterization of Candidate Genes in Dihydrochalcone and Arbutin Biosynthesis in an Apple-Pear Hybrid by De Novo Transcriptome Assembly

Apples (Malus × domestica Borkh.) and pears (Pyrus communis L.) are valuable crops closely related within the Rosaceae family with reported nutraceutical properties derived from secondary metabolites including phloridzin and arbutin, which are distinctive phenolic metabolites characterizing apples and pears, respectively. Here, we generated a de novo transcriptome assembly of an intergeneric hybrid between apple and pear, accumulating intermediate levels of phloridzin and arbutin. Combining RNA-seq, in silico functional annotation prediction, targeted gene expression analysis, and expression-metabolite correlations, we identified candidate genes for functional characterization, resulting in the identification of active arbutin synthases in the hybrid and parental genotypes. Despite exhibiting an active arbutin synthase in vitro, the natural lack of arbutin in apples is reasoned by the absence of the substrate and broad substrate specificity. Altogether, our study serves as the basis for future assessment of potential physiological roles of identified genes by genome editing of hybrids and pears.

Effect of feeding frequency on the anaerobic digestion of berry fruit waste

On-site anaerobic digesters for small agricultural farms typically have feeding schedules that fluctuate according to farm operations. Shocks in feeding, particularly for putrescible waste can disrupt the stable operation of a digester. The effect of intermittent feeding on the anaerobic digestion of rejected raspberries was investigated in four 3L reactors operated in semicontinuous mode for 350 days at 38 °C with a hydraulic retention time of 25 days and an organic loading rate (OLR) of 1gVS/L/d. During the acclimatisation period (147 days) the organic loading was 5 feeds per week. The feeding regime of two reactors was then changed while maintaining the same OLR and HRT to one weekly feed event in one reactor and 3 equal feeds per week in another. The feeding regime did not significantly affect specific methane yield (369 ± 47 L/kgVS on average) despite very different weekly patterns in methane production. Volatile fatty acids (VFA) comprised >83 % of the organics in the effluent, while the rest included non-inhibitory concentrations of phenolic compounds (515-556 mg gallic acid/L). The microbial composition and relative abundance of predominant groups in all reactors were the archaeal genera Methanobacterium and Methanolinea and the bacterial phyla Bacteridota and Firmicutes. Increasing the OLR to 2gVS/L/d on day 238 resulted in failure of all reactors, attributed to the insufficient alkalinity to counterbalance the VFA produced, and the pH decrease below 6. Overall results suggests that optimal digestion of raspberry waste is maintained despite variations in feeding frequency, but acidification can occur with OLR changes.

Lessons from assembling UCEs: A comparison of common methods and the case of Clavinomia (Halictidae)

Sequence data assembly is a foundational step in high-throughput sequencing, with untold consequences for downstream analyses. Despite this, few studies have interrogated the many methods for assembling phylogenomic UCE data for their comparative efficacy, or for how outputs may be impacted. We study this by comparing the most commonly used assembly methods for UCEs in the under-studied bee lineage Nomiinae and a representative sampling of relatives. Data for 63 UCE-only and 75 mixed taxa were assembled with five methods, including ABySS, HybPiper, SPAdes, Trinity and Velvet, and then benchmarked for their relative performance in terms of locus capture parameters and phylogenetic reconstruction. Unexpectedly, Trinity and Velvet trailed the other methods in terms of locus capture and DNA matrix density, whereas SPAdes performed favourably in most assessed metrics. In comparison with SPAdes, the guided-assembly approach HybPiper generally recovered the highest quality loci but in lower numbers. Based on our results, we formally move Clavinomia to Dieunomiini and render Epinomia once more a subgenus of Dieunomia. We strongly advise that future studies more closely examine the influence of assembly approach on their results, or, minimally, use better-performing assembly methods such as SPAdes or HybPiper. In this way, we can move forward with phylogenomic studies in a more standardized, comparable manner.

Enhancing transcriptome analysis in medicinal plants: multiple unigene sets in Astragalus membranaceus

Astragalus membranaceus is a medicinal plant mainly used in East Asia and contains abundant secondary metabolites. Despite the importance of this plant, the available genomic and genetic information is still limited. De novo transcriptome construction is recognized as an essential method for transcriptome research when reference genome information is incomplete. In this study, we constructed three individual transcriptome sets (unigene sets) for detailed analysis of the phenylpropanoid biosynthesis pathway, a major metabolite of A. membranaceus. Set-1 was a circular consensus sequence (CCS) generated using PacBio sequencing (PacBio-seq). Set-2 consisted of hybridized assembled unigenes with Illumina sequencing (Illumina-seq) reads and PacBio CCS using rnaSPAdes. Set-3 unigenes were assembled from Illumina-seq reads using the Trinity software. Construction of multiple unigene sets provides several advantages for transcriptome analysis. First, it provides an appropriate expression filtering threshold for assembly-based unigenes: a threshold transcripts per million (TPM) ≥ 5 removed more than 88% of assembly-based unigenes, which were mostly short and low-expressing unigenes. Second, assembly-based unigenes compensated for the incomplete length of PacBio CCSs: the ends of the 5`/3` untranslated regions of phenylpropanoid-related unigenes derived from set-1 were incomplete, which suggests that PacBio CCSs are unlikely to be full-length transcripts. Third, more isoform unigenes could be obtained from multiple unigene sets; isoform unigenes missing in Set-1 were detected in set-2 and set-3. Finally, gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that phenylpropanoid biosynthesis and carbohydrate metabolism were highly activated in A. membranaceus roots. Various sequencing technologies and assemblers have been developed for de novo transcriptome analysis. However, no technique is perfect for de novo transcriptome analysis, suggesting the need to construct multiple unigene sets. This method enables efficient transcript filtering and detection of longer and more diverse transcripts.

Transcriptome analysis of reproductive tract tissues of male river prawn Macrobrachium americanum

BACKGROUND

The river prawn, Macrobrachium americanum (M. americanum), is one of the largest prawns of the genus in Latin America and is an amphidromous species distributed along the Pacific coast of America. This prawn has commercial value due to its size and taste, making it a good option for aquaculture production. Its culture has been attempted in ponds and concrete tanks, but no successful technique can still support commercial production. Understanding the mechanisms that regulate reproduction at the molecular level is very important. This knowledge can provide tools for manipulating transcripts, which could increase the number or size of animals in the culture. Our understanding of the mechanism that regulates the reproduction of M. americanum at the molecular level is limited.

AIM

Perform and analyze the transcriptome assembly of the testes, vas deferens, and terminal ampulla of M. americanum. to provide new molecular information about its reproduction.

METHODS AND RESULTS

The cDNA library was constructed and sequenced for each tissue to identify novel transcripts. A combined transcriptome with the three tissues was assembled using Trinity software. Unigenes were annotated using BLASTx and BLAST2GO. The transcriptome assembly generated 1,059,447 unigenes, of which 7222 genes had significant hits (e-value < 1 × 10-5) when compared against the Swiss-Prot database. Around 75 genes were related to sex determination, testis development, spermatogenesis, spermiogenesis, fertilization, maturation of testicular cells, neuropeptides, hormones, hormone receptors, and/or embryogenesis.

CONCLUSIONS

These results provide new molecular information about M. americanum reproduction, representing a reference point for further genetic studies of this species.

De novo transcriptome sequencing and annotation of the Antarctic polychaete Microspio moorei (Spionidae) with its characterization of the heat stress-related proteins (HSP, SOD & CAT)

We present a de novo transcriptome assembly for the non-model Antarctic polychaete worm Microspio moorei (Spionidae) collected during Antarctic field expedition in Fildes Bay, King George Island, Antarctic Peninsula, in 2017. Here, we report the first transcriptome reference array for Microspio spp. The gene sequences of the spionid worm were annotated from a wide range of functions (i.e., biological, and metabolic processes, catalytic processes, and catalytic activity). HSP70, HSP90 SOD and CAT families were compared to reported annelid transcriptomes and proteomes. The phylogenetic analysis using COI, 16S, and 18S markers effectively clusters the species within the family. However, it also casts uncertainty on the monophyletic nature of the Microspio genera, indicating the necessity for additional data and potentially requiring a reevaluation of its grouping. Within these protein families, 3D model software was used to create one representative of their protein structures. Structural predictions were compared with related reported annelids living at different temperatures and a human X-ray reference. We found structural differences (RMSE >1.8) between the human HSP proteins but no significant differences between the polychaete-predicted proteins (RMSE <1.2). These results encourage further research of heat stress-related proteins, the development of genetic markers for climate change-induced temperature stress, and the study of the underlying mechanisms of the heat response. Moreover, these results motivate the extension of these findings to congeneric species.

ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs

BACKGROUND

Transcriptome assembly from RNA-sequencing data in species without a reliable reference genome has to be performed de novo, but studies have shown that de novo methods often have inadequate ability to reconstruct transcript isoforms. We address this issue by constructing an assembly pipeline whose main purpose is to produce a comprehensive set of transcript isoforms.

RESULTS

We present the de novo transcript isoform assembler ClusTrast, which takes short read RNA-seq data as input, assembles a primary assembly, clusters a set of guiding contigs, aligns the short reads to the guiding contigs, assembles each clustered set of short reads individually, and merges the primary and clusterwise assemblies into the final assembly. We tested ClusTrast on real datasets from six eukaryotic species, and showed that ClusTrast reconstructed more expressed known isoforms than any of the other tested de novo assemblers, at a moderate reduction in precision. For recall, ClusTrast was on top in the lower end of expression levels (<15% percentile) for all tested datasets, and over the entire range for almost all datasets. Reference transcripts were often (35-69% for the six datasets) reconstructed to at least 95% of their length by ClusTrast, and more than half of reference transcripts (58-81%) were reconstructed with contigs that exhibited polymorphism, measuring on a subset of reliably predicted contigs. ClusTrast recall increased when using a union of assembled transcripts from more than one assembly tool as primary assembly.

CONCLUSION

We suggest that ClusTrast can be a useful tool for studying isoforms in species without a reliable reference genome, in particular when the goal is to produce a comprehensive transcriptome set with polymorphic variants.

GTax: improving de novo transcriptome assembly by removing foreign RNA contamination

The cost and complexity of generating a complete reference genome means that many organisms lack an annotated reference. An alternative is to use a de novo reference transcriptome. This technology is cost-effective but is susceptible to off-target RNA contamination. In this manuscript, we present GTax, a taxonomy-structured database of genomic sequences that can be used with BLAST to detect and remove foreign contamination in RNA sequencing samples before assembly. In addition, we use a de novo transcriptome assembly of Solanum lycopersicum (tomato) to demonstrate that removing foreign contamination in sequencing samples reduces the number of assembled chimeric transcripts.

A reference transcriptome for walnut anthracnose pathogen, Ophiognomonia leptostyla, guides the discovery of candidate virulence genes

Despite the economic losses due to the walnut anthracnose, Ophiognomonia leptostyla is an orphan fungus with respect to genomic resources. In the present study, the transcriptome of O. leptostyla was assembled for the first time. RNA sequencing was conducted for the fungal mycelia grown in a liquid media, and the inoculated leaf samples of walnut with the fungal conidia sampled at 48, 96 and 144 h post inoculation (hpi). The completeness, correctness, and contiguity of the de novo transcriptome assemblies generated with Trinity, Oases, SOAPdenovo-Trans and Bridger were compared to identify a single superior reference assembly. In most of the assessment criteria including N50, Transrate score, number of ORFs with known description in gene bank, the percentage of reads mapped back to the transcript (RMBT), BUSCO score, Swiss-Prot coverage bin and RESM-EVAL score, the Bridger assembly was the superior and thus used as a reference for profiling the O. leptostyla transcriptome in liquid media vs. during walnut infection. The k-means clustering of transcripts resulted in four distinct transcription patterns across the three sampling time points. Most of the detected CAZy transcripts had elevated transcription at 96 hpi that is hypothetically concurrent with the start of intracellular growth. The in-silico analysis revealed 103 candidate effectors of which six were members of Necrosis and Ethylene Inducing Like Protein (NLP) gene family belonging to three distinct k-means clusters. This study provided a complex and temporal pattern of the CAZys and candidate effectors transcription during six days post O. leptostyla inoculation on walnut leaves, introducing a list of candidate virulence genes for validation in future studies.

VIGA: a one-stop tool for eukaryotic virus identification and genome assembly from next-generation-sequencing data

Identification of viruses and further assembly of viral genomes from the next-generation-sequencing data are essential steps in virome studies. This study presented a one-stop tool named VIGA (available at https://github.com/viralInformatics/VIGA) for eukaryotic virus identification and genome assembly from NGS data. It was composed of four modules, namely, identification, taxonomic annotation, assembly and novel virus discovery, which integrated several third-party tools such as BLAST, Trinity, MetaCompass and RagTag. Evaluation on multiple simulated and real virome datasets showed that VIGA assembled more complete virus genomes than its competitors on both the metatranscriptomic and metagenomic data and performed well in assembling virus genomes at the strain level. Finally, VIGA was used to investigate the virome in metatranscriptomic data from the Human Microbiome Project and revealed different composition and positive rate of viromes in diseases of prediabetes, Crohn's disease and ulcerative colitis. Overall, VIGA would help much in identification and characterization of viromes, especially the known viruses, in future studies.

Functional comparisons of the virus sensor RIG-I from humans, the microbat Myotis daubentonii, and the megabat Rousettus aegyptiacus, and their response to SARS-CoV-2 infection

IMPORTANCE

A common hypothesis holds that bats (order Chiroptera) are outstanding reservoirs for zoonotic viruses because of a special antiviral interferon (IFN) system. However, functional studies about key components of the bat IFN system are rare. RIG-I is a cellular sensor for viral RNA signatures that activates the antiviral signaling chain to induce IFN. We cloned and functionally characterized RIG-I genes from two species of the suborders Yangochiroptera and Yinpterochiroptera. The bat RIG-Is were conserved in their sequence and domain organization, and similar to human RIG-I in (i) mediating virus- and IFN-activated gene expression, (ii) antiviral signaling, (iii) temperature dependence, and (iv) recognition of RNA ligands. Moreover, RIG-I of Rousettus aegyptiacus (suborder Yinpterochiroptera) and of humans were found to recognize SARS-CoV-2 infection. Thus, members of both bat suborders encode RIG-Is that are comparable to their human counterpart. The ability of bats to harbor zoonotic viruses therefore seems due to other features.

Comparative transcriptomics and gene expression divergence associated with homoploid hybrid speciation in Argyranthemum

Ecological isolation is increasingly thought to play an important role in speciation, especially for the origin and reproductive isolation of homoploid hybrid species. However, the extent to which divergent and/or transgressive gene expression changes are involved in speciation is not well studied. In this study, we employ comparative transcriptomics to investigate gene expression changes associated with the origin and evolution of two homoploid hybrid plant species, Argyranthemum sundingii and A. lemsii (Asteraceae). As there is no standard methodology for comparative transcriptomics, we examined five different pipelines for data assembly and analysing gene expression across the four species (two hybrid and two parental). We note biases and problems with all pipelines, and the approach used affected the biological interpretation of the data. Using the approach that we found to be optimal, we identify transcripts showing DE between the parental taxa and between the homoploid hybrid species and their parents; in several cases, putative functions of these DE transcripts have a plausible role in ecological adaptation and could be the cause or consequence of ecological speciation. Although independently derived, the homoploid hybrid species have converged on similar expression phenotypes, likely due to adaptation to similar habitats.

JCcirc: circRNA full-length sequence assembly through integrated junction contigs

Recent studies have shed light on the potential of circular RNA (circRNA) as a biomarker for disease diagnosis and as a nucleic acid vaccine. The exploration of these functionalities requires correct circRNA full-length sequences; however, existing assembly tools can only correctly assemble some circRNAs, and their performance can be further improved. Here, we introduce a novel feature known as the junction contig (JC), which is an extension of the back-splice junction (BSJ). Leveraging the strengths of both BSJ and JC, we present a novel method called JCcirc (https://github.com/cbbzhang/JCcirc). It enables efficient reconstruction of all types of circRNA full-length sequences and their alternative isoforms using splice graphs and fragment coverage. Our findings demonstrate the superiority of JCcirc over existing methods on human simulation datasets, and its average F1 score surpasses CircAST by 0.40 and outperforms both CIRI-full and circRNAfull by 0.13. For circRNAs below 400 bp, 400-800 bp, 800 bp-1200 bp and above 1200 bp, the correct assembly rates are 0.13, 0.09, 0.04 and 0.03 higher, respectively, than those achieved by existing methods. Moreover, JCcirc also outperforms existing assembly tools on other five model species datasets and real sequencing datasets. These results show that JCcirc is a robust tool for accurately assembling circRNA full-length sequences, laying the foundation for the functional analysis of circRNAs.

The endohyphal microbiome: current progress and challenges for scaling down integrative multi-omic microbiome research

As microbiome research has progressed, it has become clear that most, if not all, eukaryotic organisms are hosts to microbiomes composed of prokaryotes, other eukaryotes, and viruses. Fungi have only recently been considered holobionts with their own microbiomes, as filamentous fungi have been found to harbor bacteria (including cyanobacteria), mycoviruses, other fungi, and whole algal cells within their hyphae. Constituents of this complex endohyphal microbiome have been interrogated using multi-omic approaches. However, a lack of tools, techniques, and standardization for integrative multi-omics for small-scale microbiomes (e.g., intracellular microbiomes) has limited progress towards investigating and understanding the total diversity of the endohyphal microbiome and its functional impacts on fungal hosts. Understanding microbiome impacts on fungal hosts will advance explorations of how "microbiomes within microbiomes" affect broader microbial community dynamics and ecological functions. Progress to date as well as ongoing challenges of performing integrative multi-omics on the endohyphal microbiome is discussed herein. Addressing the challenges associated with the sample extraction, sample preparation, multi-omic data generation, and multi-omic data analysis and integration will help advance current knowledge of the endohyphal microbiome and provide a road map for shrinking microbiome investigations to smaller scales. Video Abstract.

DANGER analysis: risk-averse on/off-target assessment for CRISPR editing without a reference genome

Motivation

The CRISPR-Cas9 system has successfully achieved site-specific gene editing in organisms ranging from humans to bacteria. The technology efficiently generates mutants, allowing for phenotypic analysis of the on-target gene. However, some conventional studies did not investigate whether deleterious off-target effects partially affect the phenotype.

Results

Herein, we present a novel phenotypic assessment of CRISPR-mediated gene editing: Deleterious and ANticipatable Guides Evaluated by RNA-sequencing (DANGER) analysis. Using RNA-seq data, this bioinformatics pipeline can elucidate genomic on/off-target sites on mRNA-transcribed regions related to expression changes and then quantify phenotypic risk at the gene ontology term level. We demonstrated the risk-averse on/off-target assessment in RNA-seq data from gene-edited samples of human cells and zebrafish brains. Our DANGER analysis successfully detected off-target sites, and it quantitatively evaluated the potential contribution of deleterious off-targets to the transcriptome phenotypes of the edited mutants. Notably, DANGER analysis harnessed de novo transcriptome assembly to perform risk-averse on/off-target assessments without a reference genome. Thus, our resources would help assess genome editing in non-model organisms, individual human genomes, and atypical genomes from diseases and viruses. In conclusion, DANGER analysis facilitates the safer design of genome editing in all organisms with a transcriptome.

Availability and implementation

The Script for the DANGER analysis pipeline is available at https://github.com/KazukiNakamae/DANGER_analysis. In addition, the software provides a tutorial on reproducing the results presented in this article on the Readme page. The Docker image of DANGER_analysis is also available at https://hub.docker.com/repository/docker/kazukinakamae/dangeranalysis/general.

Genome annotation: From human genetics to biodiversity genomics

Within the next decade, the genomes of 1.8 million eukaryotic species will be sequenced. Identifying genes in these sequences is essential to understand the biology of the species. This is challenging due to the transcriptional complexity of eukaryotic genomes, which encode hundreds of thousands of transcripts of multiple types. Among these, a small set of protein-coding mRNAs play a disproportionately large role in defining phenotypes. Due to their sequence conservation, orthology can be established, making it possible to define the universal catalog of eukaryotic protein-coding genes. This catalog should substantially contribute to uncovering the genomic events underlying the emergence of eukaryotic phenotypes. This piece briefly reviews the basics of protein-coding gene prediction, discusses challenges in finalizing annotation of the human genome, and proposes strategies for producing annotations across the eukaryotic Tree of Life. This lays the groundwork for obtaining the catalog of all genes-the Earth's code of life.

Divergence of cochlear transcriptomics between reference‑based and reference‑free transcriptome analyses among Rhinolophus ferrumequinum populations

Differences in gene expression within tissues can lead to differences in tissue function. Understanding the transcriptome of a species helps elucidate the molecular mechanisms underlying phenotypic divergence. According to the presence or absence of a reference genome of for a studied species, transcriptome analyses can be divided into reference‑based and reference‑free methods, respectively. Presently, comparisons of complete transcriptome analysis results between those two methods are still rare. In this study, we compared the cochlear transcriptome analysis results of greater horseshoe bats (Rhinolophus ferrumequinum) from three lineages in China with different acoustic phenotypes using reference‑based and reference‑free methods to explore their differences in subsequent analysis. The results gained by reference-based results had lower false-positive rates and were more accurate because differentially expressed genes among the three populations obtained by this method had greater reliability and a higher annotation rate. Some phenotype-related enrichment terms, including those related to inorganic molecules and proton transmembrane channels, were also obtained only by the reference-based method. However, the reference‑based method might have the limitation of incomplete information acquisition. Thus, we believe that a combination of reference‑free and reference‑based methods is ideal for transcriptome analyses. The results of our study provided a reference for the selection of transcriptome analysis methods in the future.

Redefining normal breast cell populations using long noncoding RNAs

Single-cell RNAseq has allowed unprecedented insight into gene expression across different cell populations in normal tissue and disease states. However, almost all studies rely on annotated gene sets to capture gene expression levels and sequencing reads that do not align to known genes are discarded. Here, we discover thousands of long noncoding RNAs (lncRNAs) expressed in human mammary epithelial cells and analyze their expression in individual cells of the normal breast. We show that lncRNA expression alone can discriminate between luminal and basal cell types and define subpopulations of both compartments. Clustering cells based on lncRNA expression identified additional basal subpopulations, compared to clustering based on annotated gene expression, suggesting that lncRNAs can provide an additional layer of information to better distinguish breast cell subpopulations. In contrast, these breast-specific lncRNAs poorly distinguish brain cell populations, highlighting the need to annotate tissue-specific lncRNAs prior to expression analyses. We also identified a panel of 100 breast lncRNAs that could discern breast cancer subtypes better than protein-coding markers. Overall, our results suggest that lncRNAs are an unexplored resource for new biomarker and therapeutic target discovery in the normal breast and breast cancer subtypes.

Comparative transcriptomics reveals the role of altered energy metabolism in the establishment of single-cell C4 photosynthesis in Bienertia sinuspersici

Single-cell C₄ photosynthesis (SCC₄) in terrestrial plants without Kranz anatomy involves three steps: initial CO₂ fixation in the cytosol, CO₂ release in mitochondria, and a second CO₂ fixation in central chloroplasts. Here, we investigated how the large number of mechanisms underlying these processes, which occur in three different compartments, are orchestrated in a coordinated manner to establish the C₄ pathway in Bienertia sinuspersici, a SCC₄ plant. Leaves were subjected to transcriptome analysis at three different developmental stages. Functional enrichment analysis revealed that SCC₄ cycle genes are coexpressed with genes regulating cyclic electron flow and amino/organic acid metabolism, two key processes required for the production of energy molecules in C₃ plants. Comparative gene expression profiling of B. sinuspersici and three other species (Suaeda aralocaspica, Amaranthus hypochondriacus, and Arabidopsis thaliana) showed that the direction of metabolic flux was determined via an alteration in energy supply in peripheral chloroplasts and mitochondria via regulation of gene expression in the direction of the C₄ cycle. Based on these results, we propose that the redox homeostasis of energy molecules via energy metabolism regulation is key to the establishment of the SCC₄ pathway in B. sinuspersici.

ExpressAnalyst: A unified platform for RNA-sequencing analysis in non-model species

The increasing application of RNA sequencing to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst ( www.expressanalyst.ca ), a web-based platform for processing, analyzing, and interpreting RNA-sequencing data from any eukaryotic species. ExpressAnalyst contains a series of modules that cover from processing and annotation of FASTQ files to statistical and functional analysis of count tables or gene lists. All modules are integrated with EcoOmicsDB, an ortholog database that enables comprehensive analysis for species without a reference transcriptome. By coupling ultra-fast read mapping algorithms with high-resolution ortholog databases through a user-friendly web interface, ExpressAnalyst allows researchers to obtain global expression profiles and gene-level insights from raw RNA-sequencing reads within 24 h. Here, we present ExpressAnalyst and demonstrate its utility with a case study of RNA-sequencing data from multiple non-model salamander species, including two that do not have a reference transcriptome.

Integrated transcriptome catalog of Tenualosa ilisha as a resource for gene discovery and expression profiling

The silver pride of Bangladesh, migratory shad, Tenualosa ilisha (Hilsa), makes the highest contribution to the total fish production of Bangladesh. Despite its noteworthy contribution, a well-annotated transcriptome data is not available. Here we report a transcriptomic catalog of Hilsa, constructed by assembling RNA-Seq reads from different tissues of the fish including brain, gill, kidney, liver, and muscle. Hilsa fish were collected from different aquatic habitats (fresh, brackish, and sea water) and the sequencing was performed in the next generation sequencing (NGS) platform. De novo assembly of the sequences obtained from 46 cDNA libraries revealed 462,085 transcript isoforms that were subsequently annotated using the Universal Protein Resource Knowledgebase (UniPortKB) as a reference. Starting from the sampling to final annotation, all the steps along with the workflow are reported here. This study will provide a significant resource for ongoing and future research on Hilsa for transcriptome based expression profiling and identification of candidate genes.

transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation

BACKGROUND

RNA-seq followed by de novo transcriptome assembly has been a transformative technique in biological research of non-model organisms, but the computational processing of RNA-seq data entails many different software tools. The complexity of these de novo transcriptomics workflows therefore presents a major barrier for researchers to adopt best-practice methods and up-to-date versions of software.

RESULTS

Here we present a streamlined and universal de novo transcriptome assembly and annotation pipeline, transXpress, implemented in Snakemake. transXpress supports two popular assembly programs, Trinity and rnaSPAdes, and allows parallel execution on heterogeneous cluster computing hardware.

CONCLUSIONS

transXpress simplifies the use of best-practice methods and up-to-date software for de novo transcriptome assembly, and produces standardized output files that can be mined using SequenceServer to facilitate rapid discovery of new genes and proteins in non-model organisms.

ElasticBLAST: accelerating sequence search via cloud computing

BACKGROUND

Biomedical researchers use alignments produced by BLAST (Basic Local Alignment Search Tool) to categorize their query sequences. Producing such alignments is an essential bioinformatics task that is well suited for the cloud. The cloud can perform many calculations quickly as well as store and access large volumes of data. Bioinformaticians can also use it to collaborate with other researchers, sharing their results, datasets and even their pipelines on a common platform.

RESULTS

We present ElasticBLAST, a cloud native application to perform BLAST alignments in the cloud. ElasticBLAST can handle anywhere from a few to many thousands of queries and run the searches on thousands of virtual CPUs (if desired), deleting resources when it is done. It uses cloud native tools for orchestration and can request discounted instances, lowering cloud costs for users. It is supported on Amazon Web Services and Google Cloud Platform. It can search BLAST databases that are user provided or from the National Center for Biotechnology Information.

CONCLUSION

We show that ElasticBLAST is a useful application that can efficiently perform BLAST searches for the user in the cloud, demonstrating that with two examples. At the same time, it hides much of the complexity of working in the cloud, lowering the threshold to move work to the cloud.

Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly

BACKGROUND

Diverse communities of microbial eukaryotes in the global ocean provide a variety of essential ecosystem services, from primary production and carbon flow through trophic transfer to cooperation via symbioses. Increasingly, these communities are being understood through the lens of omics tools, which enable high-throughput processing of diverse communities. Metatranscriptomics offers an understanding of near real-time gene expression in microbial eukaryotic communities, providing a window into community metabolic activity.

RESULTS

Here we present a workflow for eukaryotic metatranscriptome assembly, and validate the ability of the pipeline to recapitulate real and manufactured eukaryotic community-level expression data. We also include an open-source tool for simulating environmental metatranscriptomes for testing and validation purposes. We reanalyze previously published metatranscriptomic datasets using our metatranscriptome analysis approach.

CONCLUSION

We determined that a multi-assembler approach improves eukaryotic metatranscriptome assembly based on recapitulated taxonomic and functional annotations from an in-silico mock community. The systematic validation of metatranscriptome assembly and annotation methods provided here is a necessary step to assess the fidelity of our community composition measurements and functional content assignments from eukaryotic metatranscriptomes.

Embryogenesis of a calanoid copepod analyzed by transcriptomics

The calanoid copepod Acartia tonsa (Dana) has attracted interest because of its use as a copepod model organism as well as its potential economic role as live fish larval feed. While the adult genome and transcriptome of A. tonsa has been investigated, no studies have been performed investigating the genome-wide transcriptional changes during the normal subitaneous embryogenesis. Thus, the aim of the current study was to investigate said transcriptional changes throughout A. tonsa embryonic development. RNA extraction and de novo transcriptome assembly for the subitaneous embryogenesis of the copepod was conducted. The assembly includes for the first-time samples describing quiescent development and overall helps establishing a framework for future studies on the molecular biology of our species of interest. Among the findings reported, sequences annotated to well-known developmental genes, were identified. At the same time are described the molecular changes and gene expression levels throughout the entire 42 h the embryonic development lasts. In conclusion, here we present the most complete genome-wide transcriptional map of early copepod embryonic development to date, enabling further use of A. tonsa as a model organism for crustacean development. Keywords: enrichment of pathways; subitaneous embryogenesis, comparative genomics; transcriptome assembly; invertebrate genomics.

Inference of Ancient Polyploidy Using Transcriptome Data

Polyploidizations, or whole-genome duplications (WGDs), in plants have increased biological complexity, facilitated evolutionary innovation, and likely enabled adaptation under harsh conditions. Besides genomic data, transcriptome data have been widely employed to detect WGDs, due to their efficient accessibility to the gene space of a species. Age distributions based on synonymous substitutions (so-called K_S age distributions) for paralogs assembled from transcriptome data have identified numerous WGDs in plants, paving the way for further studies on the importance of WGDs for the evolution of seed and flowering plants. However, it is still unclear how transcriptome-based age distributions compare to those based on genomic data. In this chapter, we implemented three different de novo transcriptome assembly pipelines with two popular assemblers, i.e., Trinity and SOAPdenovo-Trans. We selected six plant species with published genomes and transcriptomes to evaluate how assembled transcripts from different pipelines perform when using K_S distributions to detect previously documented WGDs in the six species. Further, using genes predicted in each genome as references, we evaluated the effects of missing genes, gene family clustering, and de novo assembled transcripts on the transcriptome-based K_S distributions. Our results show that, although the transcriptome-based K_S distributions differ from the genome-based ones with respect to their shapes and scales, they are still reasonably reliable for unveiling WGDs, except in species where most duplicates originated from a recent WGD. We also discuss how to overcome some possible pitfalls when using transcriptome data to identify WGDs.

Optimization and application of non-native Phragmites australis transcriptome assemblies

Phragmites australis (common reed) has a cosmopolitan distribution and has been suggested as a model organism for the study of invasive plant species. In North America, the non-native subspecies (ssp. australis) is widely distributed across the contiguous 48 states in the United States and large parts of Canada. Even though millions of dollars are spent annually on Phragmites management, insufficient knowledge of P. australis impeded the efficiency of management. To solve this problem, transcriptomic information generated from multiple types of tissue could be a valuable resource for future studies. Here, we constructed forty-nine P. australis transcriptomes assemblies via different assembly tools and multiple parameter settings. The optimal transcriptome assembly for functional annotation and downstream analyses was selected among these transcriptome assemblies by comprehensive assessments. For a total of 422,589 transcripts assembled in this transcriptome assembly, 319,046 transcripts (75.5%) have at least one functional annotation. Within the transcriptome assembly, we further identified 1,495 transcripts showing tissue-specific expression pattern, 10,828 putative transcription factors, and 72,165 candidates for simple sequence repeats markers. The identification and analyses of predicted transcripts related to herbicide- and salinity-resistant genes were shown as two applications of the transcriptomic information to facilitate further research on P. australis. Transcriptome assembly and selection would be important for the transcriptome annotation. With this optimal transcriptome assembly and all relative information from downstream analyses, we have helped to establish foundations for future studies on the mechanisms underlying the invasiveness of non-native P. australis subspecies.

ElasticBLAST: Accelerating Sequence Search via Cloud Computing

Background

Biomedical researchers use alignments produced by BLAST (Basic Local Alignment Search Tool) to categorize their query sequences. Producing such alignments is an essential bioinformatics task that is well suited for the cloud. The cloud can perform many calculations quickly as well as store and access large volumes of data. Bioinformaticians can also use it to collaborate with other researchers, sharing their results, datasets and even their pipelines on a common platform.

Results

We present ElasticBLAST, a cloud native application to perform BLAST alignments in the cloud. ElasticBLAST can handle anywhere from a few to many thousands of queries and run the searches on thousands of virtual CPUs (if desired), deleting resources when it is done. It uses cloud native tools for orchestration and can request discounted instances, lowering cloud costs for users. It is supported on Amazon Web Services and Google Cloud Platform. It can search BLAST databases that are user provided or from the National Center for Biotechnology Information.

Conclusion

We show that ElasticBLAST is a useful application that can efficiently perform BLAST searches for the user in the cloud, demonstrating that with two examples. At the same time, it hides much of the complexity of working in the cloud, lowering the threshold to move work to the cloud.

De novo transcriptome assembly and functional analysis reveal a dihydrochalcone 3-hydroxylase(DHC3H) of wild Malus species that produces sieboldin in vivo

Sieboldin is a specialised secondary metabolite of the group of dihydrochalcones (DHC), found in high concentrations only in some wild Malus species, closely related to the domesticated apple (Malus × domestica L.). To date, the first committed step towards the biosynthesis of sieboldin remains unknown. In this study, we combined transcriptomic analysis and a de novo transcriptome assembly to identify two putative 3-hydroxylases in two wild Malus species (Malus toringo (K. Koch) Carriere syn. sieboldii Rehder, Malus micromalus Makino) whose DHC profile is dominated by sieboldin. We assessed the in vivo activity of putative candidates to produce 3-hydroxyphloretin and sieboldin by de novo production in Saccharomyces cerevisiae. We found that CYP98A proteins of wild Malus accessions (CYP98A195, M. toringo and CYP98A196, M. micromalus) were able to produce 3-hydroxyphloretin, ultimately leading to sieboldin accumulation by co-expression with PGT2. CYP98A197-198 genes of M. × domestica, however, were unable to hydroxylate phloretin in vivo. CYP98A195-196 proteins exerting 3-hydroxylase activity co-localised with an endoplasmic reticulum marker. CYP98A protein model from wild accessions showed mutations in key residues close to the ligand pocket predicted using phloretin for protein docking modelling. These mutations are located within known substrate recognition sites of cytochrome P450s, which could explain the acceptance of phloretin in CYP98A protein of wild accessions. Screening a Malus germplasm collection by HRM marker analysis for CYP98A genes identified three clusters that correspond to the alleles of domesticated and wild species. Moreover, CYP98A isoforms identified in M. toringo and M. micromalus correlate with the accumulation of sieboldin in other wild and hybrid Malus genotypes. Taken together, we provide the first evidence of an enzyme producing sieboldin in vivo that could be involved in the key hydroxylation step towards the synthesis of sieboldin in Malus species.

Discovering novel reproductive genes in a non-model fly using de novo GridION transcriptomics

Gene discovery has important implications for investigating phenotypic trait evolution, adaptation, and speciation. Male reproductive tissues, such as accessory glands (AGs), are hotspots for recruitment of novel genes that diverge rapidly even among closely related species/populations. These genes synthesize seminal fluid proteins that often affect post-copulatory sexual selection-they can mediate male-male sperm competition, ejaculate-female interactions that modify female remating and even influence reproductive incompatibilities among diverging species/populations. Although de novo transcriptomics has facilitated gene discovery in non-model organisms, reproductive gene discovery is still challenging without a reference database as they are often novel and bear no homology to known proteins. Here, we use reference-free GridION long-read transcriptomics, from Oxford Nanopore Technologies (ONT), to discover novel AG genes and characterize their expression in the widespread dung fly, Sepsis punctum. Despite stark population differences in male reproductive traits (e.g.: Body size, testes size, and sperm length) as well as female re-mating, the male AG genes and their secretions of S. punctum are still unknown. We implement a de novo ONT transcriptome pipeline incorporating quality-filtering and rigorous error-correction procedures, and we evaluate gene sequence and gene expression results against high-quality Illumina short-read data. We discover highly-expressed reproductive genes in AG transcriptomes of S. punctum consisting of 40 high-quality and high-confidence ONT genes that cross-verify against Illumina genes, among which 26 are novel and specific to S. punctum. Novel genes account for an average of 81% of total gene expression and may be functionally relevant in seminal fluid protein production. For instance, 80% of genes encoding secretory proteins account for 74% total gene expression. In addition, median sequence similarities of ONT nucleotide and protein sequences match within-Illumina sequence similarities. Read-count based expression quantification in ONT is congruent with Illumina's Transcript per Million (TPM), both in overall pattern and within functional categories. Rapid genomic innovation followed by recruitment of de novo genes for high expression in S. punctum AG tissue, a pattern observed in other insects, could be a likely mechanism of evolution of these genes. The study also demonstrates the feasibility of adapting ONT transcriptomics for gene discovery in non-model systems.

Simulation Tests of Methods in Evolution, Ecology, and Systematics: Pitfalls, Progress, and Principles

Complex statistical methods are continuously developed across the fields of ecology, evolution, and systematics (EES). These fields, however, lack standardized principles for evaluating methods, which has led to high variability in the rigor with which methods are tested, a lack of clarity regarding their limitations, and the potential for misapplication. In this review, we illustrate the common pitfalls of method evaluations in EES, the advantages of testing methods with simulated data, and best practices for method evaluations. We highlight the difference between method evaluation and validation and review how simulations, when appropriately designed, can refine the domain in which a method can be reliably applied. We also discuss the strengths and limitations of different evaluation metrics. The potential for misapplication of methods would be greatly reduced if funding agencies, reviewers, and journals required principled method evaluation.

De novo assembly and annotation of the transcriptome of the endangered seagrass Zostera capensis: Insights from differential gene expression under thermal stress

Seagrasses are important marine ecosystem engineers but anthropogenic impacts and climate change have led to numerous population declines globally. In South Africa, Zostera capensis is endangered due to fragmented populations and heavy anthropogenic pressures on estuarine ecosystems that house the core of the populations. Addressing questions of how pressures such as climate change affect foundational species, including Z. capensis are crucial to supporting their conservation and underpin restoration efforts. Here we use ecological transcriptomics to study key functional responses of Z. capensis through quantification of gene expression after thermal stress and present the first reference transcriptome of Z. capensis. Four de novo reference assemblies (Trinity, IDBA-tran, RNAspades, SOAPdenovo) filtered through the EvidentialGene pipeline resulted in 153,755 transcripts with a BUSCO score of 66.1% for completeness. Differential expression analysis between heat stressed (32 °C for three days) and pre-warming plants identified genes involved in photosynthesis, oxidative stress, translation, metabolic and biosynthetic processes in the Z. capensis thermal stress response. This reference transcriptome is a significant contribution to the limited available genomic resources for Z. capensis and represents a vital tool for addressing questions around the species restoration and potential functional responses to warming marine environments.

Normalized Workflow to Optimize Hybrid De Novo Transcriptome Assembly for Non-Model Species: A Case Study in Lilium ledebourii (Baker) Boiss

A high-quality transcriptome is required to advance numerous bioinformatics workflows. Nevertheless, the effectuality of tools for de novo assembly and real precision assembled transcriptomes looks somewhat unexplored, particularly for non-model organisms with complicated (very long, heterozygous, polyploid) genomes. To disclose the performance of various transcriptome assembly programs, this study built 11 single assemblies and analyzed their performance on some significant reference-free and reference-based criteria. As well as to reconfirm the outputs of benchmarks, 55 BLAST were performed and compared using 11 constructed transcriptomes. Concisely, normalized benchmarking demonstrated that Velvet–Oases suffer from the worst results, while the EvidentialGene strategy can provide the most comprehensive and accurate transcriptome of Lilium ledebourii (Baker) Boiss. The BLAST results also confirmed the superiority of EvidentialGene, so it could capture even up to 59% more (than Velvet–Oases) unique gene hits. To promote assembly optimization, with the help of normalized benchmarking, PCA and AHC, it is emphasized that each metric can only provide part of the transcriptome status, and one should never settle for just a few evaluation criteria. This study supplies a framework for benchmarking and optimizing the efficiency of assembly approaches to analyze RNA-Seq data and reveals that selecting an inefficient assembly strategy might result in less identification of unique gene hits.

Metagenomics versus total RNA sequencing: most accurate data-processing tools, microbial identification accuracy and perspectives for ecological assessments

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.

Proteotranscriptomics - A facilitator in omics research

Applications in omics research, such as comparative transcriptomics and proteomics, require the knowledge of the species-specific gene sequence and benefit from a comprehensive high-quality annotation of the coding genes to achieve high coverage. While protein-coding genes can in simple cases be detected by scanning the genome for open reading frames, in more complex genomes exonic sequences are separated by introns. Despite advances in sequencing technologies that allow for ever-growing numbers of genomes, the quality of many of the provided genome assemblies do not reach reference quality. These non-contiguous assemblies with gaps and the necessity to predict splice sites limit accurate gene annotation from solely genomic data. In contrast, the transcriptome only contains transcribed gene regions, is devoid of introns and thus provides the optimal basis for the identification of open reading frames. The additional integration of proteomics data to validate predicted protein-coding genes further enriches for accurate gene models. This review outlines the principles of the proteotranscriptomics approach, discusses common challenges and suggests methods for improvement.

Women in the European Virus Bioinformatics Center

Viruses are the cause of a considerable burden to human, animal and plant health, while on the other hand playing an important role in regulating entire ecosystems. The power of new sequencing technologies combined with new tools for processing "Big Data" offers unprecedented opportunities to answer fundamental questions in virology. Virologists have an urgent need for virus-specific bioinformatics tools. These developments have led to the formation of the European Virus Bioinformatics Center, a network of experts in virology and bioinformatics who are joining forces to enable extensive exchange and collaboration between these research areas. The EVBC strives to provide talented researchers with a supportive environment free of gender bias, but the gender gap in science, especially in math-intensive fields such as computer science, persists. To bring more talented women into research and keep them there, we need to highlight role models to spark their interest, and we need to ensure that female scientists are not kept at lower levels but are given the opportunity to lead the field. Here we showcase the work of the EVBC and highlight the achievements of some outstanding women experts in virology and viral bioinformatics.

A thorough annotation of the krill transcriptome offers new insights for the study of physiological processes

The krill species Euphausia superba plays a critical role in the food chain of the Antarctic ecosystem. Significant changes in climate conditions observed in the Antarctic Peninsula region in the last decades have already altered the distribution of krill and its reproductive dynamics. A deeper understanding of the adaptation capabilities of this species is urgently needed. The availability of a large body of RNA-seq assays allowed us to extend the current knowledge of the krill transcriptome. Our study covered the entire developmental process providing information of central relevance for ecological studies. Here we identified a series of genes involved in different steps of the krill moulting cycle, in the reproductive process and in sexual maturation in accordance with what was already described in previous works. Furthermore, the new transcriptome highlighted the presence of differentially expressed genes previously unknown, playing important roles in cuticle development as well as in energy storage during the krill life cycle. The discovery of new opsin sequences, specifically rhabdomeric opsins, one onychopsin, and one non-visual arthropsin, expands our knowledge of the krill opsin repertoire. We have collected all these results into the KrillDB2 database, a resource combining the latest annotation of the krill transcriptome with a series of analyses targeting genes relevant to krill physiology. KrillDB2 provides in a single resource a comprehensive catalog of krill genes; an atlas of their expression profiles over all RNA-seq datasets publicly available; a study of differential expression across multiple conditions. Finally, it provides initial indications about the expression of microRNA precursors, whose contribution to krill physiology has never been reported before.

Discovering functional motifs in long noncoding RNAs

Long noncoding RNAs (lncRNAs) are products of pervasive transcription that closely resemble messenger RNAs on the molecular level, yet function through largely unknown modes of action. The current model is that the function of lncRNAs often relies on specific, typically short, conserved elements, connected by linkers in which specific sequences and/or structures are less important. This notion has fueled the development of both computational and experimental methods focused on the discovery of functional elements within lncRNA genes, based on diverse signals such as evolutionary conservation, predicted structural elements, or the ability to rescue loss-of-function phenotypes. In this review, we outline the main challenges that the different methods need to overcome, describe the recently developed approaches, and discuss their respective limitations. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Improving the Annotation of the Venom Gland Transcriptome of Pamphobeteus verdolaga, Prospecting Novel Bioactive Peptides

Spider venoms constitute a trove of novel peptides with biotechnological interest. Paucity of next-generation-sequencing (NGS) data generation has led to a description of less than 1% of these peptides. Increasing evidence supports the underestimation of the assembled genes a single transcriptome assembler can predict. Here, the transcriptome of the venom gland of the spider Pamphobeteus verdolaga was re-assembled, using three free access algorithms, Trinity, SOAPdenovo-Trans, and SPAdes, to obtain a more complete annotation. Assembler's performance was evaluated by contig number, N50, read representation on the assembly, and BUSCO's terms retrieval against the arthropod dataset. Out of all the assembled sequences with all software, 39.26% were common between the three assemblers, and 27.88% were uniquely assembled by Trinity, while 27.65% were uniquely assembled by SPAdes. The non-redundant merging of all three assemblies' output permitted the annotation of 9232 sequences, which was 23% more when compared to each software and 28% more when compared to the previous P. verdolaga annotation; moreover, the description of 65 novel theraphotoxins was possible. In the generation of data for non-model organisms, as well as in the search for novel peptides with biotechnological interest, it is highly recommended to employ at least two different transcriptome assemblers.

Comparative transcriptomics reveals the molecular toolkit used by an algivorous protist for cell wall perforation

Microbial eukaryotes display a stunning diversity of feeding strategies, ranging from generalist predators to highly specialized parasites. The unicellular "protoplast feeders" represent a fascinating mechanistic intermediate, as they penetrate other eukaryotic cells (algae and fungi) like some parasites but then devour their cell contents by phagocytosis.¹ Besides prey recognition and attachment, this complex behavior involves the local, pre-phagocytotic dissolution of the prey cell wall, which results in well-defined perforations of species-specific size and structure.² Yet the molecular processes that enable protoplast feeders to overcome cell walls of diverse biochemical composition remain unknown. We used the flagellate Orciraptor agilis (Viridiraptoridae, Rhizaria) as a model protoplast feeder and applied differential gene expression analysis to examine its penetration of green algal cell walls. Besides distinct expression changes that reflect major cellular processes (e.g., locomotion and cell division), we found lytic carbohydrate-active enzymes that are highly expressed and upregulated during the attack on the alga. A putative endocellulase (family GH5_5) with a secretion signal is most prominent, and a potential key factor for cell wall dissolution. Other candidate enzymes (e.g., lytic polysaccharide monooxygenases) belong to families that are largely uncharacterized, emphasizing the potential of non-fungal microeukaryotes for enzyme exploration. Unexpectedly, we discovered various chitin-related factors that point to an unknown chitin metabolism in Orciraptor agilis, potentially also involved in the feeding process. Our findings provide first molecular insights into an important microbial feeding behavior and new directions for cell biology research on non-model eukaryotes.

Designing libraries for pooled CRISPR functional screens of long noncoding RNAs

Human and other genomes encode tens of thousands of long noncoding RNAs (lncRNAs), the vast majority of which remain uncharacterised. High-throughput functional screening methods, notably those based on pooled CRISPR-Cas perturbations, promise to unlock the biological significance and biomedical potential of lncRNAs. Such screens are based on libraries of single guide RNAs (sgRNAs) whose design is critical for success. Few off-the-shelf libraries are presently available, and lncRNAs tend to have cell-type-specific expression profiles, meaning that library design remains in the hands of researchers. Here we introduce the topic of pooled CRISPR screens for lncRNAs and guide readers through the three key steps of library design: accurate annotation of transcript structures, curation of optimal candidate sets, and design of sgRNAs. This review is a starting point and reference for researchers seeking to design custom CRISPR screening libraries for lncRNAs.

Modern venomics-Current insights, novel methods, and future perspectives in biological and applied animal venom research

Venoms have evolved >100 times in all major animal groups, and their components, known as toxins, have been fine-tuned over millions of years into highly effective biochemical weapons. There are many outstanding questions on the evolution of toxin arsenals, such as how venom genes originate, how venom contributes to the fitness of venomous species, and which modifications at the genomic, transcriptomic, and protein level drive their evolution. These questions have received particularly little attention outside of snakes, cone snails, spiders, and scorpions. Venom compounds have further become a source of inspiration for translational research using their diverse bioactivities for various applications. We highlight here recent advances and new strategies in modern venomics and discuss how recent technological innovations and multi-omic methods dramatically improve research on venomous animals. The study of genomes and their modifications through CRISPR and knockdown technologies will increase our understanding of how toxins evolve and which functions they have in the different ontogenetic stages during the development of venomous animals. Mass spectrometry imaging combined with spatial transcriptomics, in situ hybridization techniques, and modern computer tomography gives us further insights into the spatial distribution of toxins in the venom system and the function of the venom apparatus. All these evolutionary and biological insights contribute to more efficiently identify venom compounds, which can then be synthesized or produced in adapted expression systems to test their bioactivity. Finally, we critically discuss recent agrochemical, pharmaceutical, therapeutic, and diagnostic (so-called translational) aspects of venoms from which humans benefit.