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• W2917631923 abstract "Long-read sequencing (LRS) has revolutionized genomics and transcriptomics. These third-generation approaches have a relatively low throughput compared to short-read sequencing, but they can solve problems that used to be a challenge for earlier techniques.The PacBio and ONT sequencing are able to read full-length transcripts and allow the direct study of base modifications on both DNA and RNA molecules. Nanopore technology is able to sequence RNA directly.LRS has revealed a much more complex viral transcriptome. Among other capabilities, these techniques allow the discrimination between multispliced transcript variants, RNA length isoforms, embedded RNAs, and polycistronic RNA molecules.The viral genomes express a highly complex pattern of transcriptional overlaps, the function of which continues to remain unknown. Long-read sequencing (LRS) has become increasingly popular due to its strengths in de novo assembly and in resolving complex DNA regions as well as in determining full-length RNA molecules. Two important LRS technologies have been developed during the past few years, including single-molecule, real-time sequencing by Pacific Biosciences, and nanopore sequencing by Oxford Nanopore Technologies. Although current LRS methods produce lower coverage, and are more error prone than short-read sequencing, these methods continue to be superior in identifying transcript isoforms including multispliced RNAs and transcript-length variants as well as overlapping transcripts and alternative polycistronic RNA molecules. Viruses have small, compact genomes and therefore these organisms are ideal subjects for transcriptome analysis with the relatively low-throughput LRS techniques. Recent LRS studies have multiplied the number of previously known transcripts and have revealed complex networks of transcriptional overlaps in the examined viruses. Long-read sequencing (LRS) has become increasingly popular due to its strengths in de novo assembly and in resolving complex DNA regions as well as in determining full-length RNA molecules. Two important LRS technologies have been developed during the past few years, including single-molecule, real-time sequencing by Pacific Biosciences, and nanopore sequencing by Oxford Nanopore Technologies. Although current LRS methods produce lower coverage, and are more error prone than short-read sequencing, these methods continue to be superior in identifying transcript isoforms including multispliced RNAs and transcript-length variants as well as overlapping transcripts and alternative polycistronic RNA molecules. Viruses have small, compact genomes and therefore these organisms are ideal subjects for transcriptome analysis with the relatively low-throughput LRS techniques. Recent LRS studies have multiplied the number of previously known transcripts and have revealed complex networks of transcriptional overlaps in the examined viruses. Viruses represent a diverse class of microorganisms with polyphyletic origin. Compared to cellular organisms, even the largest DNA viruses have small genomes with closely-spaced genes. This feature makes viruses excellent model systems in molecular biology to explore the general principles of genetic regulation and transcriptome organization. Alternative splicing increases the coding potential of the genome through the production of multiple RNA and protein molecules from a single gene. Similarly, alternative transcription initiation and termination also contribute to the genomic complexity. Polycistronism is a common phenomenon in bacteria and in their viruses but it is extremely rare in eukaryotes. The reason for this is that, in prokaryotes, the Shine–Dalgarno sequences allow the translation of each gene in the mRNA [1.Shine J. Dalgarno L. Determinant of cistron specificity in bacterial ribosomes.Nature. 1975; 254: 34-38Crossref PubMed Scopus (881) Google Scholar]. Nevertheless, in eukaryotes only the most upstream gene of a polygenic transcript is translated because of the Cap-dependent initiation system. Some small RNA viruses have evolved miscellaneous strategies to solve the problem of translation of multiple (generally two) proteins from a single transcript, which includes the utilization of an internal ribosome entry site (IRES), or mechanisms to bypass the 5′-proximal AUG to enable downstream initiation, such as the leaky ribosomal scanning mechanisms and ribosomal frameshifting [2.Firth A.E. Brierley I. Non-canonical translation in RNA viruses.J. Gen. Virol. 2012; 93: 1385-1409Crossref PubMed Scopus (316) Google Scholar]. Nonetheless, in the majority of DNA viruses no such mechanisms have been described so far. The canonical termination sequences are not always efficient in stopping the RNA polymerase (RNP); therefore, transcription is continued until the next termination site is reached, which results in transcriptional readthrough (TRT) producing readthrough (rt)RNAs. Transcriptional overlaps (TOs), in most cases produced by TRT, have been shown to represent a common phenomenon in diverse organisms [3.Yuan C. et al.It is imperative to establish a pellucid definition of chimeric RNA and to clear up a lot of confusion in the relevant research.Int. J. Mol. Sci. 2017; 18: E714Crossref PubMed Scopus (11) Google Scholar]. The latest studies have also shown an intricate meshwork of TRTs and TOs in various viruses. The next-generation short-read sequencing (SRS) technology, released in the mid-2000s, has revolutionized genomic and transcriptomic sciences due to its massively parallel nature, which has enabled sequencing of millions of DNA fragments simultaneously at a relatively low cost. The Illumina platform is by far the most widely applied SRS technique. The enormous number of reads generated by SRS enabled the sequencing of entire genomes of various organisms at an unprecedented speed. The currently running genome programs are mainly based on the SRS approach [4.Weimer B.C. 100K Pathogen genome project.Genome Announc. 2017; 5: e00594-17Crossref PubMed Scopus (25) Google Scholar, 5.Turnbull C. et al.The 100000 Genomes Project: bringing whole genome sequencing to the NHS.BMJ. 2018; k1687: 361Google Scholar]. This technique has also been extensively used to study the transcriptomes of various organisms [6.Wang E.T. et al.Alternative isoform regulation in human tissue transcriptomes.Nature. 2008; 456: 470-476Crossref PubMed Scopus (3567) Google Scholar, 7.Goodwin S. et al.Coming of age: ten years of next-generation sequencing technologies.Nat. Rev. Genet. 2016; 17: 333-351Crossref PubMed Scopus (2176) Google Scholar]. The third-generation LRS technology emerged in 2011, when Pacific Biosciences (PacBio) commercialized the single-molecule real-time (SMRT®) technology [8.McCarthy A. Third generation DNA sequencing: Pacific Biosciences’ single molecule real time technology.Chem. Biol. 2010; 17: 675-676Abstract Full Text Full Text PDF PubMed Scopus (146) Google Scholar]. Currently, two LRS technologies are in use: the PacBio and the Oxford Nanopore Technology (ONT) platforms. MinION, the first prototype of ONT was released in 2014 [9.Ip C.L.C. et al.MinION Analysis and Reference Consortium: phase 1 data release and analysis.F1000Research. 2015; 4: 1075Crossref PubMed Scopus (173) Google Scholar]. Both LRS techniques are based on the development of novel biochemistry, which enables the direct capture of long DNA sequences or cDNAs from full-length transcripts. ONT has also developed a method for sequencing native RNAs [10.Garalde D.R. et al.Highly parallel direct RNA sequencing on an array of nanopores.Nat. Methods. 2018; 15: 201-206Crossref PubMed Scopus (473) Google Scholar] and, since Helicos [11.Ozsolak F. et al.Direct RNA sequencing.Nature. 2009; 461: 814-818Crossref PubMed Scopus (336) Google Scholar] has withdrawn from the market, nanopore sequencing is the only commercially available direct (d)RNA sequencing method. SRS, however, is still outstanding for producing high-quality, deep-coverage datasets. This technique is more cost-effective and has a lower per-base error rate than the LRS approaches [12.Rhoads A. Au K.F. PacBio sequencing and its applications.Genomics Proteomics Bioinformatics. 2015; 13: 278-289Crossref PubMed Scopus (1096) Google Scholar, 13.Quick J. et al.A reference bacterial genome dataset generated on the MinIONTM portable single-molecule nanopore sequencer.Gigascience. 2014; 3 (2047-217X-3-22): 22Crossref PubMed Scopus (157) Google Scholar]. Complex genomic regions, including sequences with a high GC content, as well as repetitive sequences, cannot be efficiently resolved by SRS. The short read length also makes computations difficult or impossible for the determination of exon connectivity and for the identification of transcript isoforms, such as multispliced RNAs as well as transcription start site (TSS) and transcription end site (TES) variants [14.Steijger T. et al.Assessment of transcript reconstruction methods for RNA-seq.Nat. Methods. 2013; 10: 1177-1184Crossref PubMed Scopus (446) Google Scholar]. Furthermore, alternative polycistronism and TOs, especially between embedded RNA (eRNA) molecules, pose challenges for the SRS platforms. These challenges can be overcome by the LRS technology since it is able to provide full contig information about transcripts. In recent years, LRS has been widely utilized in the analysis of the genomes of various organisms including prokaryotic [15.Chin C.-S. et al.Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data.Nat. Methods. 2013; 10: 563-569Crossref PubMed Scopus (2960) Google Scholar] and eukaryotic [16.Pendleton M. et al.Assembly and diploid architecture of an individual human genome via single-molecule technologies.Nat. Methods. 2015; 12: 780-786Crossref PubMed Scopus (323) Google Scholar] species as well as viruses [17.Szűcs A. et al.Long-read sequencing reveals a GC pressure during the evolution of porcine endogenous retrovirus.Genome Announc. 2017; 5: e01040-17Crossref PubMed Scopus (3) Google Scholar, 18.Tombácz D. et al.Strain Kaplan of pseudorabies virus genome sequenced by PacBio single-molecule real-time sequencing technology.Genome Announc. 2014; 2: e00628-14Crossref PubMed Scopus (25) Google Scholar, 19.Nakano K. et al.Advantages of genome sequencing by long-read sequencer using SMRT technology in medical area.Hum. Cell. 2017; 30: 149-161Crossref PubMed Scopus (101) Google Scholar, 20.Dilernia D.A. et al.Multiplexed highly-accurate DNA sequencing of closely-related HIV-1 variants using continuous long reads from single molecule, real-time sequencing.Nucleic Acids Res. 2015; 43: e129Crossref PubMed Scopus (40) Google Scholar, 21.Bull R.A. et al.A method for near full-length amplification and sequencing for six hepatitis C virus genotypes.BMC Genomics. 2016; 17: 247Crossref PubMed Scopus (47) Google Scholar, 22.Prazsák I. et al.Full genome sequence of the Western Reserve strain of vaccinia virus determined by third-generation sequencing.Genome Announc. 2018; 6: e01570-17Crossref PubMed Scopus (11) Google Scholar]. Nevertheless, current LRS techniques are only able to characterize small genomes and transcriptomes in high depth due to the comparatively low throughput. Viral transcriptomes used to be investigated by traditional techniques, including Northern blotting [23.Mankertz J. et al.Transcription analysis of porcine circovirus (PCV).Virus Genes. 1998; 16: 267-276Crossref PubMed Scopus (58) Google Scholar, 24.Farrell M.J. et al.Herpes simplex virus latency-associated transcript is a stable intron.Proc. Natl. Acad. Sci. U. S. A. 1991; 88: 790-794Crossref PubMed Scopus (248) Google Scholar], quantitative PCR [25.Nagel M.A. et al.Varicella-zoster virus transcriptome in latently infected human ganglia.J. Virol. 2011; 85: 2276-2287Crossref PubMed Scopus (56) Google Scholar, 26.Tombácz D. et al.Whole-genome analysis of pseudorabies virus gene expression by real-time quantitative RT-PCR assay.BMC Genomics. 2009; 10: 491Crossref PubMed Scopus (59) Google Scholar], RACE analysis [27.Sadler R.H. Raab-Traub N. Structural analyses of the Epstein–Barr virus BamHI A transcripts.J. Virol. 1995; 69: 1132-1141PubMed Google Scholar], and microarray studies [28.Aguilar J.S. et al.Quantitative comparison of the HSV-1 and HSV-2 transcriptomes using DNA microarray analysis.Virology. 2006; 348: 233-241Crossref PubMed Scopus (31) Google Scholar, 29.Lacaze P. et al.Temporal profiling of the coding and noncoding murine cytomegalovirus transcriptomes.J. Virol. 2011; 85: 6065-6076Crossref PubMed Scopus (24) Google Scholar]. The introduction of Illumina sequencing [30.Oláh P. et al.Characterization of pseudorabies virus transcriptome by Illumina sequencing.BMC Microbiol. 2015; 15: 130Crossref PubMed Scopus (27) Google Scholar, 31.O’Grady T. et al.Global bidirectional transcription of the Epstein–Barr virus genome during reactivation.J. Virol. 2014; 88: 1604-1616Crossref PubMed Scopus (46) Google Scholar, 32.Chen Y.-R. et al.The transcriptome of the baculovirus Autographa californica multiple nucleopolyhedrovirus in Trichoplusia ni cells.J. Virol. 2013; 87: 6391-6405Crossref PubMed Scopus (137) Google Scholar] to virus research has led to a significant progress in the discovery and precise annotation of viral transcripts. Currently, the global transcriptome of several viruses belonging to different families has been analyzed by using various techniques of PacBio and ONT platforms [33.Tombácz D. et al.Full-length isoform sequencing reveals novel transcripts and substantial transcriptional overlaps in a herpesvirus.PLoS One. 2016; 11e0162868Crossref PubMed Scopus (56) Google Scholar, 34.O’Grady T. et al.Global transcript structure resolution of high gene density genomes through multi-platform data integration.Nucleic Acids Res. 2016; 44: e145Crossref PubMed Scopus (54) Google Scholar, 35.Moldován N. et al.Multi-platform sequencing approach reveals a novel transcriptome profile in pseudorabies virus.Front. Microbiol. 2017; 8: 2708Crossref PubMed Scopus (38) Google Scholar, 36.Tombácz D. et al.Long-read isoform sequencing reveals a hidden complexity of the transcriptional landscape of herpes simplex virus type 1.Front. Microbiol. 2017; 8: 1079Crossref PubMed Scopus (47) Google Scholar, 37.Balázs Z. et al.Long-read sequencing of human cytomegalovirus transcriptome reveals RNA isoforms carrying distinct coding potentials.Sci. Rep. 2017; 715989Crossref PubMed Scopus (45) Google Scholar]. Our review aims to provide an overview of the potentials and limitations of LRS methods, to present the transcriptome diversity that has been detected by long-read sequencing, and to discuss future paths of viral genomics opened up by this technology. Similar to the Illumina approach, PacBio also adopts a sequencing-by-synthesis strategy, but while Illumina detects augmented signals from amplified DNA fragments, the PacBio technique captures a single DNA molecule (Figure 1 and Table 1). The PacBio SMRT® sequencing utilizes zero-mode waveguides (ZMW) [38.Levene M.J. et al.Zero-mode waveguides for single-molecule analysis at high concentrations.Science. 2003; 299: 682-686Crossref PubMed Scopus (1095) Google Scholar] for single-molecule analysis, which allows the detection of fluorescent signals emitted during the incorporation of labeled nucleotides. A single DNA polymerase molecule, fixed at the bottom of a ZMW, reads the circularized template multiple times. When a nucleotide is incorporated in the growing DNA strand, the fluorescent tag is cleaved off, and it gets out of the observation area. The base-call is made by the detection of the fluorescent signal of the nucleotide incorporated within the ZMW [39.Eid J. et al.Real-time DNA sequencing from single polymerase molecules.Science. 2009; 323: 133-138Crossref PubMed Scopus (2434) Google Scholar]. The accuracy of the obtained consensus sequence (reads of inserts, ROI) depends upon the number of polymerase passes around the circular template [12.Rhoads A. Au K.F. PacBio sequencing and its applications.Genomics Proteomics Bioinformatics. 2015; 13: 278-289Crossref PubMed Scopus (1096) Google Scholar]. Sequel, the newest PacBio platform, launched in 2015, has a capacity sevenfold greater than the former RS II platform [40.Lin H.-H. Liao Y.-C. Evaluation and validation of assembling corrected PacBio long reads for microbial genome completion via hybrid approaches.PLoS One. 2015; 10e0144305Crossref PubMed Scopus (22) Google Scholar]. Additionally, the Sequel system has a considerably decreased loading bias compared to RS II; therefore, it does not require size-selectioni. SMRT® sequencing generates subreads, thereby resulting in multiple base coverage in a given base, which leads to increased precision. The base-calling accuracy depends on the read length and on the movie length. The PacBio Isoform sequencing (Iso-Seq®) allows the generation of full-length cDNA sequences without the need for contig assembly, and thus it is suitable for the confident characterization of the full complement of transcript isoforms across an entire transcriptome or within the targeted genes.Table 1Comparison of the Various Sequencing Platforms.IlluminaPacific BiosciencesOxford Nanopore TechnologiesHiSeqMiSeqRSIISequelMinION 1DdRNA-SeqRequired amount of input material (ng)1–501–50–10001000500–775Mapped read length (bp)Mean92175208813 8001503.50968Median––1720–1439713Standard deviation––1438.14–969.18–Maximum1012508006–934521 866Average percentage of mapped reads84.184.490.29–69.2796.5Substitutions per base0.00530.01420.02120.0050.07540.024INDELs per base7.2 × 10–6–0.02310.0010.08560.0435Sample typegDNAgDNAcDNAgDNAcDNARNAMapping software used in the studyBWA-MEMBWA-MEMGMAP–GMAPMinimap2Refs41.Schirmer M. et al.Illumina error profiles: resolving fine-scale variation in metagenomic sequencing data.BMC Bioinf. 2016; 17: 125Crossref PubMed Scopus (186) Google Scholar41.Schirmer M. et al.Illumina error profiles: resolving fine-scale variation in metagenomic sequencing data.BMC Bioinf. 2016; 17: 125Crossref PubMed Scopus (186) Google Scholar42.Weirather J.L. et al.Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis.F1000Research. 2017; 6: 100Crossref PubMed Scopus (237) Google Scholar43.Hebert P.D.N. et al.A sequel to Sanger: amplicon sequencing that scales.BMC Genomics. 2018; 19: 219Crossref PubMed Scopus (119) Google Scholar42.Weirather J.L. et al.Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis.F1000Research. 2017; 6: 100Crossref PubMed Scopus (237) Google Scholar44.Workman R.E. et al.Nanopore native RNA sequencing of a human poly(A) transcriptome.2018Crossref Google Scholar Open table in a new tab The nanopore technology is based on monitoring the transit of DNA or RNA molecules through a protein pore; it measures variations in electric currents produced by the nucleotides that are threaded through the nanopores aided by a molecular motor protein. Nanopore sequencing is able to determine very long nucleic acid sequences [45.Jain M. et al.Nanopore sequencing and assembly of a human genome with ultra-long reads.Nat. Biotechnol. 2018; 36: 338-345Crossref PubMed Scopus (883) Google Scholar]. ONT 1D sequencing has low accuracy (approximately 85%) [46.Lu H. et al.Oxford Nanopore MinION sequencing and genome assembly.Genomics Proteomics Bioinformatics. 2016; 14: 265-279Crossref PubMed Scopus (408) Google Scholar]. The 1D2 technology improves this accuracy by ligating an adapter to the end of the reads, which increases the probability that a strand and its complementary strand pass through a pore consecutively. The base-calling algorithm creates a consensus of the two reads, and it has an average quality of over 95%. ONT can also identify the nucleotide modifications of RNA molecules by native RNA sequencing [10.Garalde D.R. et al.Highly parallel direct RNA sequencing on an array of nanopores.Nat. Methods. 2018; 15: 201-206Crossref PubMed Scopus (473) Google Scholar]. The advantages of nanopore sequencing over the PacBio platform are the longer read length, the higher throughput, and the lower costs [42.Weirather J.L. et al.Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis.F1000Research. 2017; 6: 100Crossref PubMed Scopus (237) Google Scholar]. The two LRS techniques are prone to similar errors, such as homopolymer bias and indel errors. High sequencing error rate makes accurate DNA sequencing difficult, including de novo sequencing and variant calling. Sequencing errors, however, do not represent a major obstacle in transcriptome research if well-annotated genome sequences to which the transcript reads can be aligned are available. The lower throughput compared to the SRS approach means that LRS can only characterize abundant transcripts and that technical by-products are more difficult to filter out from LRS data. Ligation and template switching are common causes of such artifacts. Template switching is caused by the release of the template strand by the polymerase molecule during synthesis followed by binding to another template that shares homology with the original template and can occur at both the reverse-transcription (RT) [47.Cocquet J. et al.Reverse transcriptase template switching and false alternative transcripts.Genomics. 2006; 88: 127-131Crossref PubMed Scopus (165) Google Scholar] and the PCR [48.Kebschull J.M. Zador A.M. Sources of PCR-induced distortions in high-throughput sequencing data sets.Nucleic Acids Res. 2015; 43: e143Crossref PubMed Scopus (11) Google Scholar] steps. The advantage of dRNA sequencing of ONT is that it is free from RT and PCR artifacts. The shortcomings of the current dRNA technique are its demand for the starting material (at least 500 ng PolyA+ RNA), very low throughput, and that the produced reads lack short sequences at both the 5′ and 3′ termini [35.Moldován N. et al.Multi-platform sequencing approach reveals a novel transcriptome profile in pseudorabies virus.Front. Microbiol. 2017; 8: 2708Crossref PubMed Scopus (38) Google Scholar]; therefore it does not resolve isoforms with base-pair precision. The cDNA sequencing methods require slightly less starting material (at least 250 ng PolyA+ RNA without PCR or 200 ng amplicon after PCR using ONT protocols or 2 ng total RNA using the Iso-Seq® protocol) and have a higher throughput, although not as high as SRS techniques. To date, the majority of LRS protocols have focused on full-length polyA-selected RNAs [49.Zhu Y.Y. et al.Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction.Biotechniques. 2001; 30: 892-897Crossref PubMed Scopus (580) Google Scholar]. Cap-selection of RNA molecules can also be used to enrich full-length RNA molecules [50.Edery I. et al.An efficient strategy to isolate full-length cDNAs based on an mRNA cap retention procedure (CAPture).Mol. Cell. Biol. 1995; 15: 3363-3371Crossref PubMed Scopus (82) Google Scholar]. It has been demonstrated that SRS coupled with the so-called synthetic long-read sequencing method (SLR-Seq) can represent an alternative approach for full-length characterization of transcripts [51.Tilgner H. et al.Comprehensive transcriptome analysis using synthetic long-read sequencing reveals molecular co-association of distant splicing events.Nat. Biotechnol. 2015; 33: 736-742Crossref PubMed Scopus (125) Google Scholar] at the cost of reducing the sequencing yields. SLR-Seq is also afflicted by SRS biases, such as poor characterization of GC-rich regions. LRS is definitely superior to SRS regarding isoform detection and the differential quantitation of isoforms; SRS still offers many advantages and could be used alongside LRS techniques [52.Depledge D.P. et al.Going the distance: optimizing RNA-Seq strategies for transcriptomic analysis of complex viral genomes.J. Virol. 2019; 93: e01342-18Crossref PubMed Scopus (24) Google Scholar]. For example, ChIP-Seq [53.Park P.J. ChIP–seq: advantages and challenges of a maturing technology.Nat. Rev. Genet. 2009; 10: 669-680Crossref PubMed Scopus (1305) Google Scholar] and ribosome profiling [54.Stern-Ginossar N. et al.Decoding human cytomegalovirus.Science. 2012; 338: 1088-1093Crossref PubMed Scopus (421) Google Scholar, 55.Arias C. et al.KSHV 2.0: a comprehensive annotation of the Kaposi’s sarcoma-associated herpesvirus genome using next-generation sequencing reveals novel genomic and functional features.PLoS Pathog. 2014; 10e1003847Crossref PubMed Scopus (200) Google Scholar] are methods which provide valuable information and are not well suited for current LRS technologies. SRS can also be used to improve LRS not only through error correction (Box 1) but also through the precise characterization of transcript features, which can be helpful in isoform identification. PRO seq [56.Mahat D.B. et al.Base-pair-resolution genome-wide mapping of active RNA polymerases using precision nuclear run-on (PRO-seq).Nat. Protoc. 2016; 11: 1455-1476Crossref PubMed Scopus (212) Google Scholar] identifies TSSs, whereas technologies such as 3′READS+ [57.Zheng D. et al.3′READS+, a sensitive and accurate method for 3′ end sequencing of polyadenylated RNA.RNA. 2016; 22: 1631-1639Crossref PubMed Scopus (46) Google Scholar] characterize TESs with higher sensitivity and specificity than is possible with current LRS technologies. Concurrently, LRS can be used for the precise quantitative analysis of the viral transcriptome at the isoform level [58.Tombácz D. et al.Characterization of the dynamic transcriptome of a herpesvirus with long-read single molecule real-time sequencing.Sci. Rep. 2017; 743751Crossref PubMed Scopus (35) Google Scholar]. Using a non-amplified Iso-Seq® technique, the results of the kinetic categorization of PRV transcripts have been in agreement with earlier observations obtained by real-time RT-PCR analysis [26.Tombácz D. et al.Whole-genome analysis of pseudorabies virus gene expression by real-time quantitative RT-PCR assay.BMC Genomics. 2009; 10: 491Crossref PubMed Scopus (59) Google Scholar]. The ability of LRS methods to sequence PCR-free cDNA or RNA provides more accurate quantitation that is devoid of amplification bias. However, due to the low throughput of such LRS methods, SRS is still more efficient in characterizing host transcription. When combined with microfluidic technologies provided by 10x Genomics, LRS can differentiate between transcript isoforms whereas SRS can characterize gene expression at the level of a single cell [59.Gupta I. et al.Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells.Nat. Biotechnol. 2018; 36: 1197-1202Crossref Scopus (134) Google Scholar], resulting in a more specific analysis of the viral–host interactions. Using LRS and SRS coupled with other techniques can eschew the deficiencies of each approach and opens the possibility of a wider analysis of the viral transcriptome.Box 1Technology Corner: The Bioinformatic Challenges of LRSOwing to the higher error rate but greater length of long reads, different tools are needed to analyze LRS and SRS data. The preprocessing of the reads is platform-specific. SMRT Link from PacBio creates accurate consensus reads and also assembles consensus isoforms which can be mapped to the genome or can be analyzed further without the need for a genome sequence [90.Workman R.E. et al.Single-molecule, full-length transcript sequencing provides insight into the extreme metabolism of the ruby-throated hummingbird Archilochus colubris.Gigascience. 2018; 7: giy009Crossref Scopus (37) Google Scholar]. Such consensus isoforms are usually highly accurate, and no further error correction is necessary. The processing of nanopore reads is less standardized. Guppy has recently been declared to be the recommended base caller by ONT. For genome sequencing, the next step would be error correction either by using short reads or based solely on the nanopore sequencing [91.Madoui M.-A. et al.Genome assembly using nanopore-guided long and error-free DNA reads.BMC Genomics. 2015; 16: 327Crossref PubMed Scopus (124) Google Scholar, 92.Salmela L. Rivals E. LoRDEC: accurate and efficient long read error correction.Bioinformatics. 2014; 30: 3506-3514Crossref PubMed Scopus (392) Google Scholar, 93.Koren S. et al.Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation.Genome Res. 2017; 27: 722-736Crossref PubMed Scopus (3144) Google Scholar]. For transcriptome sequencing, however, error correction does not appear to be beneficial prior to isoform identification as it may interfere with both the qualitative and the quantitative analysis [94.Lima L.I.S. de et al.Comparative assessment of long-read error-correction software applied to RNA-sequencing data.2018Crossref Google Scholar]. A novel method which uses rolling-circle amplification to produce concatemers of cDNA molecules (R2C2) greatly improves the quality of nanopore reads while preserving the benefits of single-molecule sequencing [95.Volden R. et al.Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA.Proc. Natl. Acad. Sci. U. S. A. 2018; 115: 9726-9731Crossref PubMed Scopus (91) Google Scholar]. Minimap2 is used for the alignment of reads from both sequencing technologies [96.Li H. Minimap2: pairwise alignment for nucleotide sequences.Bioinformatics. 2018; 34: 3094-3100Crossref PubMed Scopus (3070) Google Scholar]. Recently, a number of software programs have been developed for the task of isoform discovery. Mandalorion was designed for isoform detection in 2D reads [97.Byrne A. et al.Nanopore long-read RNAseq reveals widespread" @default.
• W2917631923 created "2019-03-02" @default.
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• W2917631923 date "2019-07-01" @default.
• W2917631923 modified "2023-10-18" @default.
• W2917631923 title "Long-Read Sequencing – A Powerful Tool in Viral Transcriptome Research" @default.
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