mRNAs, proteins and the emerging principles of gene expression control

Buccitelli, Christopher; Selbach, Matthias

doi:10.1038/s41576-020-0258-4

Cited by 804 publications

(601 citation statements)

References 158 publications

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“…In addition to the overall stochasticity of isoform choice, we observed cell type specific isoform usage for genes that are enriched for common functions such as mRNA splicing and ribosome biogenesis. The expression of ribosomal and spliceosome proteins has low correlation with their gene-level expression 37 , indicating some protein expression levels might be regulated by alternative splicing. Genes encoding cellsurface proteins such as CD44 and CD47 often have cell-type-specific splice variants, some of which have not been previously annotated, and may result in different functions 36 .…”

Section: Discussionmentioning

confidence: 99%

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

Tian

Jabbari

Thijssen

et al. 2020

Preprint

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Alternative splicing shapes the phenotype of cells in development and disease. Long-read RNA-sequencing recovers full-length transcripts but has limited throughput at the single-cell level. Here we developed single-cell full-length transcript sequencing by sampling (FLT-seq), together with the computational pipeline FLAMES to overcome these issues and perform isoform discovery and quantification, splicing analysis and mutation detection in single cells. With FLT-seq and FLAMES, we performed the first comprehensive characterization of the full-length isoform landscape in single cells of different types and species and identified thousands of unannotated isoforms. We found conserved functional modules that were enriched for alternative transcript usage in different cell populations, including ribosome biogenesis and mRNA splicing. Analysis at the transcript-level allowed data integration with scATAC-seq on individual promoters, improved correlation with protein expression data and linked mutations known to confer drug resistance to transcriptome heterogeneity. Our methods reveal previously unseen isoform complexity and provide a better framework for multi-omics data integration.

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Section: Discussionmentioning

confidence: 99%

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

Tian

Jabbari

Thijssen

et al. 2020

Preprint

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“…Two-sample MR linking pQTL and GWAS has already uncovered 30 metabolite features with evidence of causal effects on at least one disease (Qin et al, 2020), and a recent pQTL study of hepatic proteins reported a median of 4.5 local pQTL variants per protein (He et al, 2020), suggesting that there are loci with sufficient number of LD-independent clusters for MR analysis. Alternatively, pQTL could be used in place of the downstream GWAS trait in order to study mediation from gene expression to protein abundance (Buccitelli & Selbach, 2020), as previous work has found pQTL effect size to be positively correlated with eQTL effect size for variants ascertained through eQTL in human (Battle et al, 2015;Li et al, 2016), and that colocalized eQTL and pQTL signal leads to higher observed RNA-protein correlations in mice (Chick et al, 2016). Given MRLocus' improved performance with respect to interval coverage in the simulation, we feel that accurate estimation of uncertainty is an advantage to MRLocus, and the focus in developing a new method was on specificity for prioritization of gene targets for functional follow-up experiments.…”

Section: Discussionmentioning

confidence: 99%

MRLocus: identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity

Zhu

Matoba

Wilson

et al. 2020

Preprint

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Expression quantitative trait loci (eQTL) studies are used to understand the regulatory function of non-coding genome-wide association study (GWAS) risk loci, but colocalization alone does not demonstrate a causal relationship of gene expression affecting a trait. Evidence for mediation, that perturbation of gene expression in a given tissue or developmental context will induce a change in the downstream GWAS trait, can be provided by two-sample Mendelian Randomization (MR). Here, we introduce a new statistical method, MRLocus, for Bayesian estimation of the gene-to-trait effect from eQTL and GWAS summary data for loci displaying allelic heterogeneity, that is, containing multiple LD-independent eQTLs. MRLocus makes use of a colocalization step applied to each eQTL, followed by an MR analysis step across eQTLs. Additionally, our method involves estimation of allelic heterogeneity through a dispersion parameter, indicating variable mediation effects from each individual eQTL on the downstream trait. Our method is evaluated against state-of-the-art methods for estimation of the gene-to-trait mediation effect, using an existing simulation framework. In simulation, MRLocus often has the highest accuracy among competing methods, and in each case provides more accurate estimation of uncertainty as assessed through interval coverage. MRLocus is then applied to five causal candidate genes for mediation of particular GWAS traits, where gene-to-trait effects are concordant with those previously reported. We find that MRLocus' estimation of the causal effect across eQTLs within a locus provides useful information for determining how perturbation of gene expression or individual regulatory elements will affect downstream traits. The MRLocus method is implemented as an R package available at https://mikelove.github.io/mrlocus.

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“…We also found that the divergent protein levels are likely due to post-translational molecular mechanisms. While we cannot directly test the mechanism here, we hypothesize that APA could lead to variation in protein levels as a consequence of protein autoregulation, by differentially including RNA and protein binding motifs (Buccitelli & Selbach, 2020;de Bie & Ciechanover, 2011;Müller-McNicoll et al, 2019). Alternatively, APA could contribute to temporal and spatial differences in protein expression, which would affect our ability to quantify protein with traditional techniques (Buccitelli & Selbach, 2020;Tian & Manley, 2017).…”

Section: Inter-species Differences In Apa Explain Protein-specific Rementioning

confidence: 93%

“…Though genes are ultimately expressed as proteins, many studies (including current studies by our group) still measure mRNA expression as an implicit proxy for protein expression levels. As a justification for this approach, we typically point to the fact that after accounting for technical considerations, the correlation between mRNA levels and protein abundance is quite high genome-wide, specifically, across genes (Buccitelli & Selbach, 2020;Csárdi et al, 2015). However, we also know that at the level of a single gene, across individuals or tissues, the correlation between mRNA and protein measurements tends to be much lower (Battle et al, 2015;Buccitelli & Selbach, 2020).…”

Section: Inter-species Differences In Apa Explain Protein-specific Rementioning

confidence: 99%

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Divergence in alternative polyadenylation contributes to gene regulatory differences between humans and chimpanzees

Mittleman

Pott

Warland

et al. 2020

Preprint

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Comparative functional genomic studies have shown that differences in gene expression between species can often be explained by corresponding inter-species differences in genetic and epigenetic regulatory mechanisms. In the quest to understand gene regulatory evolution in primates, the role of co-transcriptional regulatory mechanisms, such as alternative polyadenylation (APA), have so far received little attention. To begin addressing this gap, we studied APA in lymphoblastoid cell lines from six humans and six chimpanzees, and estimated usage for 44,432 polyadenylation sites (PAS) in 9,518 genes in both species. While APA is largely conserved in humans and chimpanzees, we identified 1,705 genes with significantly different PAS usage (FDR of 0.05) between the two species. We found that genes with divergent APA patterns are enriched among differentially expressed genes, as well as among genes that show differences in protein translation between species. In particular, differences in APA between humans and chimpanzees can explain a subset of observed inter-species protein expression differences that do not display corresponding differences at the transcript level. Finally, we focused on genes that have a dominant PAS, namely a PAS that is used more often than all others. Dominant PAS are highly conserved, and inter-species differences in dominant PAS are particularly enriched for genes that also show expression differences between the species. This study establishes APA as another key mechanism underlying the genetic regulation of transcript and protein expression levels in primates.

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mRNAs, proteins and the emerging principles of gene expression control

Cited by 804 publications

References 158 publications

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

Comprehensive characterization of single cell full-length isoforms in human and mouse with long-read sequencing

MRLocus: identifying causal genes mediating a trait through Bayesian estimation of allelic heterogeneity

Divergence in alternative polyadenylation contributes to gene regulatory differences between humans and chimpanzees

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