Nanopore direct RNA sequencing maps the complexity of Arabidopsis mRNA processing and m6A modification

Parker, Matthew; Knop, Katarzyna; Sherwood, Anna V.; Schurch, Nicholas J.; Mackinnon, Katarzyna; Gould, Peter D; Hall, Anthony; Barton, Geoffrey J.; Simpson, Gordon G.

doi:10.7554/elife.49658

Cited by 394 publications

(601 citation statements)

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“…Another type of transcripts that we and other teams observed in hen2-2 and se-2 plants are truncated or misprocessed transcripts spanning the first intron (14,15,35,68). Similar 5′ transcript derived from protein coding genes have also been observed in human cells depleted from ARS2 and result from premature transcription termination rather than from compromised splicing of full-length pre-mRNAs (19,34,69).…”

Section: Discussionmentioning

confidence: 69%

SERRATE interacts with the nuclear exosome targeting (NEXT) complex to degrade primary miRNA precursors in Arabidopsis

Bajczyk

Lange

Bielewicz

et al. 2020

Preprint

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SERRATE/ARS2 is a conserved RNA effector protein involved in transcription, processing and export of different types of RNAs. In Arabidopsis, the best-studied function of SERRATE (SE) is to promote miRNA processing. Here, we report that SE interacts with the Nuclear Exosome Targeting (NEXT) complex, comprising the RNA helicase HEN2, the RNA binding protein RBM7 and one of the two zincknuckle proteins ZCCHC8A/ZCCHC8B. The identification of common targets of SE and HEN2 by RNAseq supports the idea that SE cooperates with NEXT for RNA surveillance by the nuclear exosome.Among the RNA targets accumulating in absence of SE or NEXT are miRNA precursors. Loss of NEXT components results in the accumulation of pri-miRNAs without affecting levels of miRNAs, indicating that NEXT is, unlike SE, not required for miRNA processing. As compared to se-2, se-2 hen2-2 double mutants showed increased accumulation of pri-miRNAs, but partially restored levels of mature miRNAs and attenuated developmental defects. We propose that the slow degradation of pri-miRNAs caused by loss of HEN2 compensates for the poor miRNA processing efficiency in se-2 mutants, and that SE regulates miRNA biogenesis through its double contribution in promoting miRNA processing but also pri-miRNA degradation through the recruitment of the NEXT complex. IntroductionIn plants, many miRNAs are encoded by independent RNA polymerase II transcription units. The primary transcripts contain a 5' cap structure as well as a poly(A) tail at the 3' end (1), and sometimes introns. The primary or spliced pri-miRNAs adopt stem loop structures which are processed by the nuclear endonuclease Dicer like 1 (DCL1) (2) in two sequential reactions. The first step creates shorter miRNA precursors called pre-miRNAs. The second step produces miRNA/miRNA* duplexes of mostly 21 nt with 2 nt overhangs at both 3' ends. DCL1 associates with the double stranded RNA binding 2 protein HYPONASTIC LEAVES 1 (HYL1) and the zinc finger domain-containing RNA effector protein SERRATE (3-5). Both HYL1 and SE interact with DCL1 as well as with each other (6-8). DCL1, SE and HYL1 form the core of the plant Microprocessor complex and co-localize within the nucleus in special structures known as dicing bodies (D-bodies) (7). In absence of HYL1 or upon reduced activity of SE, dicing by DCL1 is not completely abolished but less efficient and less accurate (3-5). The importance of SE for the biogenesis of miRNAs is illustrated by the phenotype of se mutants. Complete loss of SE expression as in the null mutant se-4 is embryonic lethal, while the se-1 mutation, which results in the expression of a truncated SE lacking 20 amino acids at its C-terminus, severely affects developmental timing, phylotaxy, meristem function and patterning of leaves and flowers (4,9). The se-2 mutation, in which the SE protein is truncated by 40 amino acids from the C-terminus, additionally displays the hyponastic leave shape that is characteristic for many miRNA biogenesis mutants including hyl1-2, hst-1 and ago1-25 (10-13).In ad...

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Section: Discussionmentioning

confidence: 69%

SERRATE interacts with the nuclear exosome targeting (NEXT) complex to degrade primary miRNA precursors in Arabidopsis

Bajczyk

Lange

Bielewicz

et al. 2020

Preprint

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“…Direct RNA-Seq has been used to analyse m6A in yeast (Garalde et al 2018;H. Liu et al 2019) , Arabidopsis (Parker et al 2020) , RNA virus genomes (Kim et al 2020) and in human cells (Workman et al 2019;Leger et al 2019;Lorenz et al 2020) . Here we showed that differential RNA modifications can be identified across a larger number of genetically diverse human cancer cell lines.…”

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confidence: 99%

Detection of differential RNA modifications from direct RNA sequencing of human cell lines

Pratanwanich

Yao

Chen

et al. 2020

Preprint

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Differences in RNA expression can provide insights into the molecular identity of a cell, pathways involved in human diseases, and variation in RNA levels across patients associated with clinical phenotypes. RNA modifications such as m6A have been found to contribute to molecular functions of RNAs. However, quantification of differences in RNA modifications has been challenging. Here we develop a computational method (xPore) to identify differential RNA modifications from direct RNA sequencing data. We evaluate our method on transcriptome-wide m6A profiling data, demonstrating that xPore identifies positions of m6A sites at single base resolution, estimates the fraction of modified RNAs in the cell, and quantifies the differential modification rate across conditions. We apply the method to direct RNA-Sequencing data from 6 cell lines and find that many m6A sites are preserved, while a subset of m6A sites show significant differences in their modification rates across cell types. Together, we show that RNA modifications can be identified from direct RNA-sequencing with high accuracy, enabling the analysis of differential modifications and expression from a single high throughput experiment.Availability : xPore is available as open source software ( https://github.com/GoekeLab/xpore )

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“…Given the recent discovery of numerous novel functional transcripts in multiple organs (3,58), the re-evaluation of transcript diversity and complexity in model organisms (4,5,59,60) and the growing interest in Oxford Nanopore direct-RNA multiple assets in viral transcriptome research (61-64), TALC's capacity to correct the entire gamut of transcripts, and preserve the correct transcript structure may prove increasingly valuable. Table 1: Usual alignment-based statistics for the 7 correction methods tested: primary alignment rates and base accuracy (real LR data corrected by real SR data).…”

Section: Discussionmentioning

confidence: 99%

TALC: Transcript-level Aware Long Read Correction

Broseus

Thomas

Oldfield

et al. 2020

Preprint

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Long-read sequencing technologies are invaluable for determining complex RNA transcript architectures but are error-prone. Numerous "hybrid correction" algorithms have been developed for genomic data that correct long reads by exploiting the accuracy and depth of short reads sequenced from the same sample. These algorithms are not suited for correcting more complex transcriptome sequencing data. We have created a novel algorithm called TALC (Transcription Aware Long Read Correction) which models changes in RNA expression and isoform representation in a weighted De-Bruijn graph to correct long reads from transcriptome studies. We tested TALC on a dataset of short and long reads generated for this study. TALC correction results in more accurate reads with less structural errors than existing methods. TALC is implemented in C++ and available at https://gitlab.igh.cnrs.fr/lbroseus/TALC. INTRODUCTIONRecent advances in RNA sequencing (RNA-seq) technologies have revealed that transcription is more pervasive(1), more diverse (2) and more cryptic (3) than expected. Given the major role that RNA processing plays in disease and normal biology, it is crucial to ascertain the existence of novel isoforms and to accurately quantify their abundance. Second generation RNA-seq technologies such as Illumina are well suited to the tasks of assessing gene expression levels and determining proximal exon connectivity. They produce numerous sequencing reads at a low cost ensuring sufficient representation of most transcripts. However, because the RNA or cDNA is fragmented during short RNA-seq protocols, long range connectivity can only be computationally inferred. These predictions based on short reads struggle to correctly identify transcript isoforms that contain multiple alternative exons (4) or that contain retained introns (5). In these cases, long-read (LR) sequencing technologies are invaluable because they can sequence entire molecules in one pass and thus capture long-range connectivity of complex isoforms. LR technologies however produce less reads than short read (SR) sequencing approaches (6) for similar costs and have higher error rates. In many cases these higher error rates can prevent the correct identification of isoforms.Although several alignment software (7-9) are optimized to handle long erroneous sequences, they still display several issues which confound transcript identification and annotation. Many reads fail to be aligned and regions where the sequencing error rates are higher such as UTRs frequently produce ambiguous alignments. Secondly, they struggle to identify splice junctions, notably those flanking small structural variants such as small exons or alternative 5' and 3' splice sites. This impacts the evaluation of exon skipping events and worsens the quality of . CC-BY-NC-ND 4.0

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Nanopore direct RNA sequencing maps the complexity of Arabidopsis mRNA processing and m6A modification

Cited by 394 publications

References 98 publications

SERRATE interacts with the nuclear exosome targeting (NEXT) complex to degrade primary miRNA precursors in Arabidopsis

SERRATE interacts with the nuclear exosome targeting (NEXT) complex to degrade primary miRNA precursors in Arabidopsis

Detection of differential RNA modifications from direct RNA sequencing of human cell lines

TALC: Transcript-level Aware Long Read Correction

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