Current and Future Methods for mRNA Analysis: A Drive Toward Single Molecule Sequencing

Molecular biomarkers identification and applications in CHO bioprocessing

Biomarkers are valuable tools in clinical research where they allow to predict susceptibility to diseases, or response to specific treatments. Likewise, biomarkers can be extremely useful in the biomanufacturing of therapeutic proteins. Indeed, constraints such as short timelines and the need to find hyper-productive cells could benefit from a data-driven approach during cell line and process development. Many companies still rely on large screening capacities to develop productive cell lines, but as they reach a limit of production, there is a need to go from empirical to rationale procedures. Similarly, during bioprocessing runs, substrate consumption and metabolism wastes are commonly monitored. None of them possess the ability to predict the culture behavior in the bioreactor. Big data driven approaches are being adapted to the study of industrial mammalian cell lines, enabled by the publication of Chinese hamster and CHO genome assemblies which allowed the use of next-generation sequencing with these cells, as well as continuous proteome and metabolome annotation. However, if these different -omics technologies contributed to the characterization of CHO cells, there is a significant effort remaining to apply this knowledge to biomanufacturing methods. The correlation of a complex phenotype such as high productivity or rapid growth to the presence or expression level of a specific biomarker could save time and effort in the screening of manufacturing cell lines or culture conditions. In this review we will first discuss the different biological molecules that can be identified and quantified in cells, their detection techniques, and associated challenges. We will then review how these markers are used during the different steps of cell line and bioprocess development, and the inherent limitations of this strategy.

Transcriptome Profiling Reveals the Gene Network Responding to Low Nitrogen Stress in Wheat

As one of the essential nutrients for plants, nitrogen (N) has a major impact on the yield and quality of wheat worldwide. Due to chemical fertilizer pollution, it has become increasingly important to improve crop yield by increasing N use efficiency (NUE). Therefore, understanding the response mechanisms to low N (LN) stress is essential for the regulation of NUE in wheat. In this study, LN stress significantly accelerated wheat root growth, but inhibited shoot growth. Further transcriptome analysis showed that 8468 differentially expressed genes (DEGs) responded to LN stress. The roots and shoots displayed opposite response patterns, of which the majority of DEGs in roots were up-regulated (66.15%; 2955/4467), but the majority of DEGs in shoots were down-regulated (71.62%; 3274/4565). GO and KEGG analyses showed that nitrate reductase activity, nitrate assimilation, and N metabolism were significantly enriched in both the roots and shoots. Transcription factor (TF) and protein kinase analysis showed that genes such as MYB-related (38/38 genes) may function in a tissue-specific manner to respond to LN stress. Moreover, 20 out of 107 N signaling homologous genes were differentially expressed in wheat. A total of 47 transcriptome datasets were used for weighted gene co-expression network analysis (17,840 genes), and five TFs were identified as the potential hub regulatory genes involved in the response to LN stress in wheat. Our findings provide insight into the functional mechanisms in response to LN stress and five candidate regulatory genes in wheat. These results will provide a basis for further research on promoting NUE in wheat.

LncHLEF promotes hepatic lipid synthesis through miR-2188-3p/GATA6 axis and encoding peptides and enhances intramuscular fat deposition via exosome

Long noncoding RNAs (lncRNAs) have emergingly been implicated in mammalian lipid metabolism. However, their biological functions and regulatory mechanisms underlying adipogenesis remain largely elusive in chicken. Here, we systematically characterized the genome-wide full-length lncRNAs in the livers of pre- and peak-laying hens, and identified a novel intergenic lncRNA, lncHLEF, an RNA macromolecule with a calculated molecular weight of 433 kDa. lncHLEF was primarily distributed in cytoplasm of chicken hepatocyte and significantly up-regulated in livers of peak-laying hens. Functionally, lncHLEF could promote hepatocyte lipid droplet formation, triglycerides and total cholesterol contents. Mechanistically, lncHLEF could not only serve as a competitive endogenous RNA to modulate miR-2188-3p/GATA6 axis, but also encode three small functional polypeptides that directly interact with ACLY protein to enable its stabilization. Importantly, adeno-associated virus-mediated liver-specific lncHLEF overexpression resulted in increased hepatic lipid synthesis and intramuscular fat (IMF) deposition, but did not alter abdominal fat (AbF) deposition. Furthermore, hepatocyte lncHLEF could be delivered into intramuscular and abdominal preadipocytes via hepatocyte-secreted exosome to enhance intramuscular preadipocytes differentiation without altering abdominal preadipocytes differentiation. In conclusion, this study revealed that the lncHLEF could promote hepatic lipid synthesis through two independent regulatory mechanisms, and could enhance IMF deposition via hepatocyte-adipocyte communications mediated by exosome.

A long-read and short-read transcriptomics approach provides the first high-quality reference transcriptome and genome annotation for Pseudotsuga menziesii (Douglas-fir)

Douglas-fir (Pseudotsuga menziesii) is native to western North America. It grows in a wide range of environmental conditions and is an important timber tree. Although there are several studies on the gene expression responses of Douglas-fir to abiotic cues, the absence of high-quality transcriptome and genome data is a barrier to further investigation. Like for most conifers, the available transcriptome and genome reference dataset for Douglas-fir remains fragmented and requires refinement. We aimed to generate a highly accurate, and complete reference transcriptome and genome annotation. We deep-sequenced the transcriptome of Douglas-fir needles from seedlings that were grown under nonstress control conditions or a combination of heat and drought stress conditions using long-read (LR) and short-read (SR) sequencing platforms. We used 2 computational approaches, namely de novo and genome-guided LR transcriptome assembly. Using the LR de novo assembly, we identified 1.3X more high-quality transcripts, 1.85X more "complete" genes, and 2.7X more functionally annotated genes compared to the genome-guided assembly approach. We predicted 666 long noncoding RNAs and 12,778 unique protein-coding transcripts including 2,016 putative transcription factors. We leveraged the LR de novo assembled transcriptome with paired-end SR and a published single-end SR transcriptome to generate an improved genome annotation. This was conducted with BRAKER2 and refined based on functional annotation, repetitive content, and transcriptome alignment. This high-quality genome annotation has 51,419 unique gene models derived from 322,631 initial predictions. Overall, our informatics approach provides a new reference Douglas-fir transcriptome assembly and genome annotation with considerably improved completeness and functional annotation.

The Botrytis cinerea Gene Expression Browser

For comprehensive gene expression analyses of the phytopathogenic fungus Botrytis cinerea, which infects a number of plant taxa and is a cause of substantial agricultural losses worldwide, we developed BEB, a web-based B. cinerea gene Expression Browser. This computationally inexpensive web-based application and its associated database contain manually curated RNA-Seq data for B. cinerea. BEB enables expression analyses of genes of interest under different culture conditions by providing publication-ready heatmaps depicting transcript levels, without requiring advanced computational skills. BEB also provides details of each experiment and user-defined gene expression clustering and visualization options. If needed, tables of gene expression values can be downloaded for further exploration, including, for instance, the determination of differentially expressed genes. The BEB implementation is based on open-source computational technologies that can be deployed for other organisms. In this case, the new implementation will be limited only by the number of transcriptomic experiments that are incorporated into the platform. To demonstrate the usability and value of BEB, we analyzed gene expression patterns across different conditions, with a focus on secondary metabolite gene clusters, chromosome-wide gene expression, previously described virulence factors, and reference genes, providing the first comprehensive expression overview of these groups of genes in this relevant fungal phytopathogen. We expect this tool to be broadly useful in B. cinerea research, providing a basis for comparative transcriptomics and candidate gene identification for functional assays.

Long read single cell RNA sequencing reveals the isoform diversity of Plasmodium vivax transcripts

Plasmodium vivax infections often consist of heterogenous populations of parasites at different developmental stages and with distinct transcriptional profiles, which complicates gene expression analyses. The advent of single cell RNA sequencing (scRNA-seq) enabled disentangling this complexity and has provided robust and stage-specific characterization of Plasmodium gene expression. However, scRNA-seq information is typically derived from the end of each mRNA molecule (usually the 3'-end) and therefore fails to capture the diversity in transcript isoforms documented in bulk RNA-seq data. Here, we describe the sequencing of scRNA-seq libraries using Pacific Biosciences (PacBio) chemistry to characterize full-length Plasmodium vivax transcripts from single cell parasites. Our results show that many P. vivax genes are transcribed into multiple isoforms, primarily through variations in untranslated region (UTR) length or splicing, and that the expression of many isoforms is developmentally regulated. Our findings demonstrate that long read sequencing can be used to characterize mRNA molecules at the single cell level and provides an additional resource to better understand the regulation of gene expression throughout the Plasmodium life cycle.

Improved Nanopore full-length cDNA sequencing by PCR-suppression

Full-length transcript sequencing remains a main goal of RNA sequencing. However, even the application of long-read sequencing technologies such as Oxford Nanopore Technologies still fail to yield full-length transcript sequencing for a significant portion of sequenced reads. Since these technologies can sequence reads that are far longer than the longest known processed transcripts, the lack of efficiency to obtain full-length transcripts from good quality RNAs stems from library preparation inefficiency rather than the presence of degraded RNA molecules. It has previously been shown that addition of inverted terminal repeats in cDNA during reverse transcription followed by single-primer PCR creates a PCR suppression effect that prevents amplification of short molecules thus enriching the library for longer transcripts. We adapted this method for Nanopore cDNA library preparation and show that not only is PCR efficiency increased but gene body coverage is dramatically improved. The results show that implementation of this simple strategy will result in better quality full-length RNA sequencing data and make full-length transcript sequencing possible for most of sequenced reads.

Long-Read Transcriptome of Equine Bronchoalveolar Cells

We used Pacific Biosciences long-read isoform sequencing to generate full-length transcript sequences in equine bronchoalveolar lavage fluid (BALF) cells. Our dataset consisted of 313,563 HiFi reads comprising 805 Mb of polished sequence information. The resulting equine BALF transcriptome consisted of 14,234 full-length transcript isoforms originating from 7017 unique genes. These genes consisted of 6880 previously annotated genes and 137 novel genes. We identified 3428 novel transcripts in addition to 10,806 previously known transcripts. These included transcripts absent from existing genome annotations, transcripts mapping to putative novel (unannotated) genes and fusion transcripts incorporating exons from multiple genes. We provide transcript-level data for equine BALF cells as a resource to the scientific community.

The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome

Investigating the functions and activities of genes requires proper annotation of the transcribed units. However, transcript assembly efforts have produced a surprisingly large variation in the number of transcripts, and especially so for noncoding transcripts. This heterogeneity in assembled transcript sets might be partially explained by sequencing depth. Here, we used real and simulated short-read sequencing data as well as long-read data to systematically investigate the impact of sequencing depths on the accuracy of assembled transcripts. We assembled and analyzed transcripts from 671 human short-read data sets and four long-read data sets. At the first level, there is a positive correlation between the number of reads and the number of recovered transcripts. However, the effect of the sequencing depth varied based on cell or tissue type, the type of read and the nature and expression levels of the transcripts. The detection of coding transcripts saturated rapidly with both short and long-reads, however, there was no sign of early saturation for noncoding transcripts at any sequencing depth. Increasing long-read sequencing depth specifically benefited transcripts containing transposable elements. Finally, we show how single-cell RNA-seq can be guided by transcripts assembled from bulk long-read samples, and demonstrate that noncoding transcripts are expressed at similar levels to coding transcripts but are expressed in fewer cells. This study highlights the impact of sequencing depth on transcript assembly.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

EST-SSR Marker Development and Full-Length Transcriptome Sequence Analysis of Tiger Lily (Lilium lancifolium Thunb)

The fast advancement and deployment of sequencing technologies after the Human Genome Project have greatly increased our knowledge of the eukaryotic genome sequences. However, due to technological concerns, high-quality genomic data has been confined to a few key organisms. Moreover, our understanding of which portions of genomes make up genes and which transcript isoforms synthesize these genes is scarce. Therefore, the current study has been designed to explore the reliability of the tiger lily (Lilium lancifolium Thunb) transcriptome. The PacBio-SMRT was used for attaining the complete transcriptomic profile. We obtained a total of 815,624 CCS (Circular Consensus Sequence) reads with an average length of 1295 bp. The tiger lily transcriptome has been sequenced for the first time using third-generation long-read technology. Furthermore, unigenes (38,707), lncRNAs (6852), and TF members (768) were determined based on the transcriptome data, followed by evaluating SSRs (3319). It has also been revealed that 105 out of 128 primer pairs effectively amplified PCR products. Around 15,608 transcripts were allocated to 25 distinct KOG Clusters, and 10,706 unigenes were grouped into 52 functional categories in the annotated transcripts. Until now, no tiger lily lncRNAs have been discovered. Results of this study may serve as an extensive set of reference transcripts and help us learn more about the transcriptomes of tiger lilies and pave the path for further research.

Possible Role of Accessory Proteins in the Viral Replication for the 20I/501Y.V1 (B.1.1.7) SARS CoV-2 Variant

The emergence of new severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) has been a global concern. The B.1.1.7 variant of SARS CoV-2 is reported to cause higher transmission. The study investigates the replication cycle and transcriptional pattern of the B.1.1.7 to hypothesis the possible role of different genes in viral replication. It was observed that the B.1.1.7 variant required a longer maturation time. The transcriptional response demonstrated higher expression of ORF6 and ORF8 compared to nucleocapsid transcript till the eclipse period which might influence higher viral replication. The number of infectious viruses titer is higher in the B.1.1.7, despite a lesser copy number than B.1, indicating higher transmissibility. The experimental evidence published linked ORF6 and ORF8 to play important role in replication and we also observed their higher expression. This leads us to hypothesis the possible role of ORF6 and ORF8 in B.1.1.7 higher replication which causes higher transmission.

Epigenome-wide association studies: current knowledge, strategies and recommendations

The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.

Unraveling the complexity of faba bean (Vicia faba L.) transcriptome to reveal cold-stress-responsive genes using long-read isoform sequencing technology

Faba bean (Vicia faba L.), a globally important grain legume providing a stable source of dietary protein, was one of the earliest plant cytogenetic models. However, the lack of draft genome annotations and unclear structural information on mRNA transcripts have impeded its genetic improvement. To address this, we sequenced faba bean leaf transcriptome using the PacBio single-molecule long-read isoform sequencing platform. We identified 28,569 nonredundant unigenes, ranging from 108 to 9669 bp, with a total length of 94.5 Mb. Many unigenes (3597, 12.5%) had 2-20 isoforms, indicating a highly complex transcriptome. Approximately 96.5% of the unigenes matched sequences in public databases. The predicted proteins and transcription factors included NB-ARC, Myb_domain, C3H, bHLH, and heat shock proteins, implying that this genome has an abundance of stress resistance genes. To validate our results, we selected WCOR413-15785, DHN2-12403, DHN2-14197, DHN2-14797, COR15-14478, and HVA22-15 unigenes from the ICE-CBF-COR pathway to analyze their expression patterns in cold-treated samples via qRT-PCR. The expression of dehydrin-related genes was induced by cold stress. The assembled data provide the first insights into the deep sequencing of full-length RNA from faba bean at the single-molecule level. This study provides an important foundation to improve gene modeling and protein prediction.

Full-length transcriptome analysis and identification of transcript structures in Eimeria necatrix from different developmental stages by single-molecule real-time sequencing

Background

Eimeria necatrix is one of the most pathogenic parasites, causing high mortality in chickens. Although its genome sequence has been published, the sequences and complete structures of its mRNA transcripts remain unclear, limiting exploration of novel biomarkers, drug targets and genetic functions in E. necatrix.

Methods

Second-generation merozoites (MZ-2) of E. necatrix were collected using Percoll density gradients, and high-quality RNA was extracted from them. Single-molecule real-time (SMRT) sequencing and Illumina sequencing were combined to generate the transcripts of MZ-2. Combined with the SMRT sequencing data of sporozoites (SZ) collected in our previous study, the transcriptome and transcript structures of E. necatrix were studied.

Results

SMRT sequencing yielded 21,923 consensus isoforms in MZ-2. A total of 17,151 novel isoforms of known genes and 3918 isoforms of novel genes were successfully identified. We also identified 2752 (SZ) and 3255 (MZ-2) alternative splicing (AS) events, 1705 (SZ) and 1874 (MZ-2) genes with alternative polyadenylation (APA) sites, 4019 (SZ) and 2588 (MZ-2) fusion transcripts, 159 (SZ) and 84 (MZ-2) putative transcription factors (TFs) and 3581 (SZ) and 2039 (MZ-2) long non-coding RNAs (lncRNAs). To validate fusion transcripts, reverse transcription-PCR was performed on 16 candidates, with an accuracy reaching up to 87.5%. Sanger sequencing of the PCR products further confirmed the authenticity of chimeric transcripts. Comparative analysis of transcript structures revealed a total of 3710 consensus isoforms, 815 AS events, 1139 genes with APA sites, 20 putative TFs and 352 lncRNAs in both SZ and MZ-2.

Conclusions

We obtained many long-read isoforms in E. necatrix SZ and MZ-2, from which a series of lncRNAs, AS events, APA events and fusion transcripts were identified. Information on TFs will improve understanding of transcriptional regulation, and fusion event data will greatly improve draft versions of gene models in E. necatrix. This information offers insights into the mechanisms governing the development of E. necatrix and will aid in the development of novel strategies for coccidiosis control.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-021-05015-7.

Comprehensive Analysis of mRNA Expression Profiling and Identification of Potential Diagnostic Biomarkers in Coronary Artery Disease

The aim of this study is to investigate mRNA expression profiling by RNA sequencing (RNA-seq) in patients with coronary artery disease (CAD) and validate differentially expressed genes (DEGs) as novel biomarkers for CAD. Transcriptome-wide mRNA expression analysis of peripheral blood mononuclear cells was performed in five CAD patients and five controls. Functional enrichment analyses, protein-protein interaction network construction, and hub gene selection were further conducted. Relative expression levels of hub genes were validated by quantitative reverse transcription PCR in larger cohorts. Spearman correlation test and multiple linear regression analysis were applied to examine the relationship between confounding factors with severity of coronary artery atherosclerosis. Receiver operating characteristic (ROC) curve analysis was adopted to identify potentially diagnostic biomarkers for CAD. A total of 527 upregulated and 653 downregulated mRNAs were identified as DEGs in CAD patients. The relative expression levels of beta-transducin repeat containing E3 ubiquitin protein ligase (BTRC), F-box and leucine-rich repeat protein 4 (FBXL4), ubiquitin conjugating enzyme E2 D2 (UBE2D2), and ankyrin repeat and SOCS box containing 1 (ASB1) were significantly different between two groups (all p ≤ 0.05). The severity of coronary artery atherosclerosis was negatively associated with the BTRC gene relative expression level (r = -0.323, p < 0.001) and positively with UBE2D2 (r = 0.285, p < 0.001). ROC analysis of BTRC and UBE2D2 genes showed that the areas under the curve were 0.782 (95% CI: 0.720-0.845, p < 0.001) and 0.753 (95% CI: 0.681-0.824, p < 0.001), respectively. We described the characteristics of mRNA expression in the peripheral blood of CAD patients and controls by RNA-seq. Combined with Spearman correlation analysis and ROC analyses, BTRC and UBE2D2 genes had significantly diagnostic values, which may have potential to act as novel diagnostic biomarkers and therapeutic targets for CAD.

Long-chain polyphosphates impair SARS-CoV-2 infection and replication

Long-chain, inorganic polyphosphates (polyPs), which are found in many cells in the blood, have cytoprotective and antiviral activities, particularly against HIV-1 infection. Ferrucci et al. tested the effects of polyPs of various lengths on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro. Molecular docking and binding analyses showed that polyPs bound to the host receptor ACE2, which facilitates viral entry, and a viral RNA polymerase required for replication. Both proteins underwent proteasomal degradation in cells incubated with polyP120, the optimal species tested, resulting in inhibition of SARS-CoV-2 replication and a reduced inflammatory response. Given that polyPs have low toxicity, these results suggest that their potential therapeutic use should be further explored.

Inorganic polyphosphates (polyPs) are linear polymers composed of repeated phosphate (PO₄³⁻) units linked together by multiple high-energy phosphoanhydride bonds. In addition to being a source of energy, polyPs have cytoprotective and antiviral activities. Here, we investigated the antiviral activities of long-chain polyPs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In molecular docking analyses, polyPs interacted with several conserved amino acid residues in angiotensin-converting enzyme 2 (ACE2), the host receptor that facilitates virus entry, and in viral RNA-dependent RNA polymerase (RdRp). ELISA and limited proteolysis assays using nano– LC-MS/MS mapped polyP120 binding to ACE2, and site-directed mutagenesis confirmed interactions between ACE2 and SARS-CoV-2 RdRp and identified the specific amino acid residues involved. PolyP120 enhanced the proteasomal degradation of both ACE2 and RdRp, thus impairing replication of the British B.1.1.7 SARS-CoV-2 variant. We thus tested polyPs for functional interactions with the virus in SARS-CoV-2–infected Vero E6 and Caco2 cells and in primary human nasal epithelial cells. Delivery of a nebulized form of polyP120 reduced the amounts of viral positive-sense genomic and subgenomic RNAs, of RNA transcripts encoding proinflammatory cytokines, and of viral structural proteins, thereby presenting SARS-CoV-2 infection in cells in vitro.

Gene Expression and Isoform Identification of PacBio Full-Length cDNA Sequences for Berberine Biosynthesis in Berberis koreana

Berberis koreana is a medicinal plant containing berberine, which is a bioactive compound of the benzylisoquinoline alkaloid (BIA) class. BIA is widely used in the food and drug industry for its health benefits. To investigate the berberine biosynthesis pathway, gene expression analysis was performed in leaves, flowers, and fruits at different stages of growth. This was followed by full-length cDNA sequencing analysis using the PacBio sequencer platform to determine the number of isoforms of those expressed genes. We identified 23,246 full-length unigenes, among which 8479 had more than one isoform. The number of isoforms ranged between two to thirty-one among all genes. Complete isoform analysis was carried out on the unigenes encoding BIA synthesis. Thirteen of the sixteen genes encoding enzymes for berberine synthesis were present in more than one copy. This demonstrates that gene duplication and translation into isoforms may contribute to the functional specificity of the duplicated genes and isoforms in plant alkaloid synthesis. Our study also demonstrated the streamlining of berberine biosynthesis via the absence of genes for enzymes of other BIAs, but the presence of all the genes for berberine biosynthesize in B. koreana. In addition to genes encoding enzymes for the berberine biosynthesis pathway, the genes encoding enzymes for other BIAs were not present in our dataset except for those encoding corytuberine synthase (CTS) and berbamunine synthase (BS). Therefore, this explains how B. koreana produces berberine by blocking the pathways leading to other BIAs, effectively only allowing the pathway to lead to berberine synthesis.

Large-Scale Multiplexing Permits Full-Length Transcriptome Annotation of 32 Bovine Tissues From a Single Nanopore Flow Cell

A comprehensive annotation of transcript isoforms in domesticated species is lacking. Especially considering that transcriptome complexity and splicing patterns are not well-conserved between species, this presents a substantial obstacle to genomic selection programs that seek to improve production, disease resistance, and reproduction. Recent advances in long-read sequencing technology have made it possible to directly extrapolate the structure of full-length transcripts without the need for transcript reconstruction. In this study, we demonstrate the power of long-read sequencing for transcriptome annotation by coupling Oxford Nanopore Technology (ONT) with large-scale multiplexing of 93 samples, comprising 32 tissues collected from adult male and female Hereford cattle. More than 30 million uniquely mapping full-length reads were obtained from a single ONT flow cell, and used to identify and characterize the expression dynamics of 99,044 transcript isoforms at 31,824 loci. Of these predicted transcripts, 21% exactly matched a reference transcript, and 61% were novel isoforms of reference genes, substantially increasing the ratio of transcript variants per gene, and suggesting that the complexity of the bovine transcriptome is comparable to that in humans. Over 7,000 transcript isoforms were extremely tissue-specific, and 61% of these were attributed to testis, which exhibited the most complex transcriptome of all interrogated tissues. Despite profiling over 30 tissues, transcription was only detected at about 60% of reference loci. Consequently, additional studies will be necessary to continue characterizing the bovine transcriptome in additional cell types, developmental stages, and physiological conditions. However, by here demonstrating the power of ONT sequencing coupled with large-scale multiplexing, the task of exhaustively annotating the bovine transcriptome - or any mammalian transcriptome - appears significantly more feasible.

Nanopore-based full-length transcriptome sequencing of Muscovy duck (Cairina moschata) ovary

Unlike mammals, studies on mechanisms that regulate waterfowl ovulation have been rarely reported. To advance our understanding of the ovulation differences in Muscovy duck, we utilized the Oxford Nanopore Technologies (ONT) to generate transcriptome data from 3 groups of female duck ovaries with ovulation differences (i.e., preovulation [PO], consecutive ovulation [CO], and inconsecutive ovulation [IO]). In this study, the full-length transcriptome data qualitative analysis showed that a total of 24,504 nonredundant full-length transcripts were generated, 19,060 new transcripts were discovered and 14,848 novel transcripts were successfully annotated. For the quantitative analysis, differentially expressed genes (DEGs) between the 3 groups were identified and functional properties were characterized. CTNNB1, IGF1, FOXO3, HSPA2, PTEN and SMC4 may be potential hub genes that regulate ovulation. Adhesion-related pathway, mTOR pathway, TGF-β signaling pathway and FoxO signaling pathway have been considered as important pathways that affect follicular development and ovulation. These results provide a more complete data source of full-length transcriptome for the further study of gene expression and genetics in Muscovy duck. The hub genes and potential mechanisms that affect the ovulation of Muscovy duck have been screened out to provide a scientific basis for breeding work to improve the reproduction performance of Muscovy duck.

Methodologies for Transcript Profiling Using Long-Read Technologies

RNA sequencing using next-generation sequencing technologies (NGS) is currently the standard approach for gene expression profiling, particularly for large-scale high-throughput studies. NGS technologies comprise high throughput, cost efficient short-read RNA-Seq, while emerging single molecule, long-read RNA-Seq technologies have enabled new approaches to study the transcriptome and its function. The emerging single molecule, long-read technologies are currently commercially available by Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), while new methodologies based on short-read sequencing approaches are also being developed in order to provide long range single molecule level information-for example, the ones represented by the 10x Genomics linked read methodology. The shift toward long-read sequencing technologies for transcriptome characterization is based on current increases in throughput and decreases in cost, making these attractive for de novo transcriptome assembly, isoform expression quantification, and in-depth RNA species analysis. These types of analyses were challenging with standard short sequencing approaches, due to the complex nature of the transcriptome, which consists of variable lengths of transcripts and multiple alternatively spliced isoforms for most genes, as well as the high sequence similarity of highly abundant species of RNA, such as rRNAs. Here we aim to focus on single molecule level sequencing technologies and single-cell technologies that, combined with perturbation tools, allow the analysis of complete RNA species, whether short or long, at high resolution. In parallel, these tools have opened new ways in understanding gene functions at the tissue, network, and pathway levels, as well as their detailed functional characterization. Analysis of the epi-transcriptome, including RNA methylation and modification and the effects of such modifications on biological systems is now enabled through direct RNA sequencing instead of classical indirect approaches. However, many difficulties and challenges remain, such as methodologies to generate full-length RNA or cDNA libraries from all different species of RNAs, not only poly-A containing transcripts, and the identification of allele-specific transcripts due to current error rates of single molecule technologies, while the bioinformatics analysis on long-read data for accurate identification of 5' and 3' UTRs is still in development.

De novo assembly of the olive fruit fly (Bactrocera oleae) genome with linked-reads and long-read technologies minimizes gaps and provides exceptional Y chromosome assembly

BACKGROUND

The olive fruit fly, Bactrocera oleae, is the most important pest in the olive fruit agribusiness industry. This is because female flies lay their eggs in the unripe fruits and upon hatching the larvae feed on the fruits thus destroying them. The lack of a high-quality genome and other genomic and transcriptomic data has hindered progress in understanding the fly's biology and proposing alternative control methods to pesticide use.

RESULTS

Genomic DNA was sequenced from male and female Demokritos strain flies, maintained in the laboratory for over 45 years. We used short-, mate-pair-, and long-read sequencing technologies to generate a combined male-female genome assembly (GenBank accession GCA_001188975.2). Genomic DNA sequencing from male insects using 10x Genomics linked-reads technology followed by mate-pair and long-read scaffolding and gap-closing generated a highly contiguous 489 Mb genome with a scaffold N50 of 4.69 Mb and L50 of 30 scaffolds (GenBank accession GCA_001188975.4). RNA-seq data generated from 12 tissues and/or developmental stages allowed for genome annotation. Short reads from both males and females and the chromosome quotient method enabled identification of Y-chromosome scaffolds which were extensively validated by PCR.

CONCLUSIONS

The high-quality genome generated represents a critical tool in olive fruit fly research. We provide an extensive RNA-seq data set, and genome annotation, critical towards gaining an insight into the biology of the olive fruit fly. In addition, elucidation of Y-chromosome sequences will advance our understanding of the Y-chromosome's organization, function and evolution and is poised to provide avenues for sterile insect technique approaches.

Screening candidate microR-15a- IRAK2 regulatory pairs for predicting the response to Staphylococcus aureus-induced mastitis in dairy cows

We established a mastitis model using exogenous infection of the mammary gland of Chinese Holstein cows with Staphylococcus aureus and extracted total RNA from S. aureus-infected and healthy mammary quarters. Differential expression of genes due to mastitis was evaluated using Affymetrix technology and results revealed a total of 1230 differentially expressed mRNAs. A subset of affected genes was verified via Q-PCR and pathway analysis. In addition, Solexa high-throughput sequencing technology was used to analyze profiles of miRNA in infected and healthy quarters. These analyses revealed a total of 52 differentially expressed miRNAs. A subset of those results was verified via Q-PCR. Bioinformatics techniques were used to predict and analyze the correlations among differentially expressed miRNA and mRNA. Results revealed a total of 329 pairs of negatively associated miRNA/mRNA, with 31 upregulated pairs of mRNA and 298 downregulated pairs of mRNA. Differential expression of miR-15a and interleukin-1 receptor-associated kinase-like 2 (IRAK2), were evaluated by western blot and luciferase reporter assays. We conclude that miR-15a and miR-15a target genes (IRAK2) constitute potential miRNA-mRNA regulatory pairs for use as biomarkers to predict a mastitis response.

Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts

The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers have sought to gather more insights from the data, these new technologies have also increased the computational analysis burden. In this review, we describe typical computational pipelines for RNA-Seq analysis and discuss their strengths and weaknesses for the assembly, quantification and analysis of coding and non-coding RNAs. We also discuss the assembly of transposable elements into transcripts, and the difficulty these repetitive elements pose. In summary, RNA-Seq is a powerful technology that is likely to remain a key asset in the biologist's toolkit.

Analysis of Transcriptome and Epitranscriptome in Plants Using PacBio Iso-Seq and Nanopore-Based Direct RNA Sequencing

Nanopore sequencing from Oxford Nanopore Technologies (ONT) and Pacific BioSciences (PacBio) single-molecule real-time (SMRT) long-read isoform sequencing (Iso-Seq) are revolutionizing the way transcriptomes are analyzed. These methods offer many advantages over most widely used high-throughput short-read RNA sequencing (RNA-Seq) approaches and allow a comprehensive analysis of transcriptomes in identifying full-length splice isoforms and several other post-transcriptional events. In addition, direct RNA-Seq provides valuable information about RNA modifications, which are lost during the PCR amplification step in other methods. Here, we present a comprehensive summary of important applications of these technologies in plants, including identification of complex alternative splicing (AS), full-length splice variants, fusion transcripts, and alternative polyadenylation (APA) events. Furthermore, we discuss the impact of the newly developed nanopore direct RNA-Seq in advancing epitranscriptome research in plants. Additionally, we summarize computational tools for identifying and quantifying full-length isoforms and other co/post-transcriptional events and discussed some of the limitations with these methods. Sequencing of transcriptomes using these new single-molecule long-read methods will unravel many aspects of transcriptome complexity in unprecedented ways as compared to previous short-read sequencing approaches. Analysis of plant transcriptomes with these new powerful methods that require minimum sample processing is likely to become the norm and is expected to uncover novel co/post-transcriptional gene regulatory mechanisms that control biological outcomes during plant development and in response to various stresses.

Tissue-Based Mapping of the Fathead Minnow (Pimephales promelas) Transcriptome and Proteome

Omics approaches are broadly used to explore endocrine and toxicity-related pathways and functions. Nevertheless, there is still a significant gap in knowledge in terms of understanding the endocrine system and its numerous connections and intricate feedback loops, especially in non-model organisms. The fathead minnow (Pimephales promelas) is a widely used small fish model for aquatic toxicology and regulatory testing, particularly in North America. A draft genome has been published, but the amount of available genomic or transcriptomic information is still far behind that of other more broadly studied species, such as the zebrafish. Here, we used a proteogenomics approach to survey the tissue-specific proteome and transcriptome profiles in adult male fathead minnow. To do so, we generated a draft transcriptome using short and long sequencing reads from liver, testis, brain, heart, gill, head kidney, trunk kidney, and gastrointestinal tract. We identified 30,378 different putative transcripts overall, with the assembled contigs ranging in size from 264 to over 9,720 nts. Over 17,000 transcripts were >1,000 nts, suggesting a robust transcriptome that can be used to interpret RNA sequencing data in the future. We also performed RNA sequencing and proteomics analysis on four tissues, including the telencephalon, hypothalamus, liver, and gastrointestinal tract of male fish. Transcripts ranged from 0 to 600,000 copies per gene and a large portion were expressed in a tissue-specific manner. Specifically, the telencephalon and hypothalamus shared the most expressed genes, while the gastrointestinal tract and the liver were quite distinct. Using protein profiling techniques, we identified a total of 4,045 proteins in the four tissues investigated, and their tissue-specific expression pattern correlated with the transcripts at the pathway level. Similarly to the findings with the transcriptomic data, the hypothalamus and telencephalon had the highest degree of similarity in the proteins detected. The main purpose of this analysis was to generate tissue-specific omics data in order to support future aquatic ecotoxicogenomic and endocrine-related studies as well as to improve our understanding of the fathead minnow as an ecological model.