Ribosome profiling at isoform level reveals an evolutionary conserved impact of differential splicing on the proteome

Reixachs‐Solé, Marina; Ruiz-Orera, Jorge; Albà, M. Mar; Eyras, Eduardo

doi:10.1101/582031

Cited by 5 publications

(4 citation statements)

References 63 publications

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“…Several models have been proposed to explain what marks a stop codon as authentic, where termination of translation occurs normally, versus a premature termination codon (PTC), which leads to NMD in animals, yeast and plants (Nagy & Maquat, 1998; Amrani et al, 2004; Bühler et al, 2006; Behm-Ansmant et al, 2007; Kérenyi et al, 2008; Singh et al, 2008; Hogg & Goff, 2010; Drechsel et al, 2013; Lloyd et al, 2018). Alternative splicing has a well known role in altering the coding potential of transcripts, but can also alter the translation efficiency of the transcript (Floor & Doudna, 2016; Weatheritt et al, 2016; Blair et al, 2017; Fagg et al, 2017; Reixachs-Sole et al, 2019) or change the stability of transcripts by targeting them to NMD (Jumaa & Nielsen, 1997; Hilleren & Parker, 1999; Lejeune et al, 2001; Lewis et al, 2003; Lareau et al, 2007; Ni et al, 2007; Floor & Doudna, 2016; Reixachs-Sole et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Polysome fractionation analysis reveals features important for human nonsense-mediated mRNA decay

Lloyd

French

Brenner

2020

Preprint

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Nonsense-mediated mRNA decay (NMD) is a translation-dependent mRNA surveillance pathway that eliminates transcripts with premature termination codons. Several studies have tried defined the features governing which transcripts are targeted to NMD. However, these approaches often rely on inhibiting core NMD factors, which often have roles in non-NMD processes within the cell. Based on reports that NMD-targeted transcripts are often bound by a single ribosome, we analyzed RNA-Seq data from a polysome fractionation experiment (TrlP-Seq) to characterize the features of NMD-targeted transcripts in human cells. This approach alleviates the need to inhibit the NMD pathway. We found that the exon junction complex (EJC) model, wherein an exon-exon junction located ≥50 nucleotides downstream of a stop codon is predicted to elicit NMD, was a powerful predictor of transcripts with high abundance in the monosome fraction (bound by a single ribosome). This was also true for the presence of an upstream open reading frame. In contrast, as 3’ UTR lengths increase, the proportion of transcripts that are most abundant in the monosome fraction does not increase. This suggests that either longer 3’ UTRs do not consistently act as potent triggers of NMD or that the degradation of these transcripts is mechanistically different to other NMD-targeted transcripts. Of the ribosome-associated transcripts annotated as “non-coding”, we find that a majority are bound by a single ribosome. Many of these transcripts increase in response to NMD inhibition, including the oncogenic SHNG15, suggesting many might be NMD targets. Finally, we found that retained intron transcripts without a premature termination codon are over-represented in the monosome fraction, suggesting an alternative mechanism is responsible for the low level of translation of these transcripts. In summary, our analysis finds that the EJC model is a powerful predictor of NMD-targeted transcripts, while the presence of a long 3’ UTR is not.

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Section: Introductionmentioning

confidence: 99%

Polysome fractionation analysis reveals features important for human nonsense-mediated mRNA decay

Lloyd

French

Brenner

2020

Preprint

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“…We utilized RNA-seq and Ribo-seq datasets obtained from 52 common Yoruba individuals among the RNA-seq dataset derived from the GEUVADIS project (Lappalainen et al, 2013) (EMBL-EBI, E-GEUV-1) and the Ribo-seq dataset deposited in GEO under GSE61742 (Battle et al, 2015), respectively. To calculate translational efficiency at the isoform level, trimmed reads were aligned to the de novo transcriptome sequences generated from long-read sequencing for 29 immune cell subsets using STAR (Dobin et al, 2013) as with tools developed for the same purpose (Reixachs-Solé et al, 2020;Wang et al, 2016). Then, we applied generated bam files to the coverageDepth and translationalEfficiency functions with corrections using the maximum translational efficiency value in the 90 most highly ribosome-occupied nucleotides window within the feature in ribosomeProfilingQC R package (Ingolia et al, 2009;Ou J and Hoye M, 2022).…”

Section: Translational Efficiencymentioning

confidence: 99%

Immune Isoform Atlas: Landscape of alternative splicing in human immune cells

Inamo

Suzuki

Ueda

et al. 2022

Preprint

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Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generated a comprehensive full-length isoform annotation of human immune cells, Immune Isoform Atlas, by long-read sequencing for 29 cell subsets. Our atlas contained a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE. We profiled functional characteristics of isoforms including encoded domains, inserted repetitive elements, and translational efficiency, and we showed that repetitive elements significantly explained the diversity of unannotated isoforms. Some of the isoforms are expressed in a cell-type specific manner, whose alternative 3'-UTRs usage contributed to their specificity. Further, we identified a number of disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the pathomechanism of diseases via alternative splicing.

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“…However, 5′ leaders/3′ trailers are not taken into account here, meaning multiple isoforms that differ only in their noncoding regions would all be annotated as the principal isoform. In an attempt to move away from these heuristic approaches and their shortcomings, software has been developed which takes Ribo‐Seq data into account to do transcript isoform level quantification, that is, Ribomap (Wang, McManus, & Kingsford, ), ORQAS (Reixachs‐Solé, Ruiz‐Orera, Alba, & Eyras, ), and SaTann (Calviello, Hirsekorn, & Ohler, ), see Table . However, these tools assign footprints to different isoforms under the premise that their protein synthesis input is directly proportional to their RNA levels, that is, they are translated with the same efficiency.…”

Section: Differential Gene Expressionmentioning

confidence: 99%

Computational methods for ribosome profiling data analysis

2019

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Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. This article is characterized under: Translation > Ribosome Structure/Function RNA Evolution and Genomics > Computational Analyses of RNA Translation > Translation Mechanisms Translation > Translation Regulation

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Ribosome profiling at isoform level reveals an evolutionary conserved impact of differential splicing on the proteome

Cited by 5 publications

References 63 publications

Polysome fractionation analysis reveals features important for human nonsense-mediated mRNA decay

Polysome fractionation analysis reveals features important for human nonsense-mediated mRNA decay

Immune Isoform Atlas: Landscape of alternative splicing in human immune cells

Computational methods for ribosome profiling data analysis

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