Abstract
Advances in transcriptomics have provided an exceptional opportunity to study functional implications of the genetic variability. Technologies such as RNA-Seq have emerged as state-of-the-art techniques for transcriptome analysis that take advantage of high-throughput next-generation sequencing. However, similar to their predecessors, these approaches continue to impose major challenges on full-length transcript structure identification, primarily due to inherent limitations of read length. With the development of single-molecule sequencing (SMS) from PacBio, a growing number of studies on the transcriptome of different organisms have been reported. SMS has emerged as advantageous for comprehensive genome annotation including identification of novel genes/isoforms, long non-coding RNAs and fusion transcripts. This approach can be used across a broad spectrum of species to better interpret the coding information of the genome, and facilitate the biological function study. We provide an overview of SMS platform and its diverse applications in various biological studies, and our perspective on the challenges associated with the transcriptome studies.
Highlights
The last few decades have witnessed an explosive growth in the genomic sequencing technologies (Shendure et al, 2017)
While single-molecule long read sequencing based approaches have identified a wide array of novel transcripts which were generated from different splicing patterns (Figure 3A), they need to be validated and characterized since not all of them have a meaningful impact on the cellular biological processes of the cell
Recent studies in maize and sorghum (Wang et al, 2018) showed that ā¼45% of the isoforms could undergo Non-Sense Mediated Decay (NMD) after mRNA processing; that being said, a large number of the transcripts potentially will be degraded before transportation to the cell and the rest of transcripts are more likely to have biological functions
Summary
The last few decades have witnessed an explosive growth in the genomic sequencing technologies (Shendure et al, 2017). Single-molecule long-read sequencing based transcript profiling techniques have the inherent advantage of rendering, in vitro and without ambiguity, a full-length transcript sequence without depending on the errorprone, computational step of assembly (Abdel-Ghany et al, 2016; Wang et al, 2016; Cheng et al, 2017). As a result, they allow a more precise detection of alternative splicing events and eventually novel isoforms, making it easier to build gene models for species which are poorly studied or have an incomplete or missing reference genome. Http://research- pub.gene.com/gmap/ http://atgc.lirmm.fr/lordec https://github.com/lfaino/LoReAn http://augroup.org/LSC/LSC_download.html https://github.com/lh3/minimap https://pasapipeline.github.io/ https://github.com/BioInf- Wuerzburg/proovread https://github.com/PacificBiosciences/ GenomicConsensus http://splicegrapher.sourceforge.net/ https://bitbucket.org/ConesaLab/sqanti https://github.com/alexdobin/STAR/releases https://bitbucket.org/regulatorygenomicsupf/suppa https://bitbucket.org/comp_bio/tapis https://github.com/PacificBiosciences/IsoSeq_SA3nUP
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