Codon usage biases co-evolve with transcription termination machinery to suppress premature cleavage and polyadenylation

Zhou, Zhipeng; Dang, Yunkun; Zhou, Mian; Yuan, Haiyan; Liu, Yi

doi:10.7554/elife.33569

Cited by 60 publications

(54 citation statements)

References 99 publications

(192 reference statements)

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“…Interestingly, in a separate study in Neurospora, gene expression modulated by codon usage was shown to be due to the effects of transcription rather than translation [67]. In a follow-up study, the group also demonstrated C/G bias is able to promote gene expression by suppressing premature transcription termination [68]. In addition, several other studies have demonstrated that in mammalian cells, GC-rich genes are transcribed with increased efficiency, resulting in higher levels of transcripts independent of mRNA degradation [69,70].…”

Section: Investigating the System Of Codon Bias In Humansmentioning

confidence: 96%

Codon bias confers stability to humanmRNAs

et al. 2019

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Codon bias has been implicated as one of the major factors contributing to mRNA stability in several model organisms. However, the molecular mechanisms of codon bias on mRNA stability remain unclear in humans. Here, we show that human cells possess a mechanism to modulate RNA stability through a unique codon bias. Bioinformatics analysis showed that codons could be clustered into two distinct groups-codons with G or C at the third base position (GC3) and codons with either A or T at the third base position (AT3): the former stabilizing while the latter destabilizing mRNA. Quantification of codon bias showed that increased GC3-content entails proportionately higher GC-content. Through bioinformatics, ribosome profiling, and in vitro analysis, we show that decoupling the effects of codon bias reveals two modes of mRNA regulation, one GC3-and one GC-content dependent. Employing an immunoprecipitation-based strategy, we identify ILF2 and ILF3 as RNA-binding proteins that differentially regulate global mRNA abundances based on codon bias. Our results demonstrate that codon bias is a two-pronged system that governs mRNA abundance.

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Section: Investigating the System Of Codon Bias In Humansmentioning

confidence: 96%

Codon bias confers stability to humanmRNAs

et al. 2019

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“…To test whether S. cerevisiae coding sequences might be depleted of splicing signals, we compared their frequency in the ORF set of the extant S. cerevisiae genome with that in 10,000 synthetic ORF sets derived by randomizing the order of codons for each ORF. This approach maintains ORF length, integrity, GC content, and codon usage in the permuted ORF sets while generating partially randomized nucleotide sequences that can be used as a background sequence set for comparison, and has been used to evaluate co-evolution of RNA processing signals within coding sequence [58].…”

Section: Coding Regions Are Depleted Of Sequences Required For Splicingmentioning

confidence: 99%

Rapidly evolving protointrons inSaccharomycesgenomes revealed by a hungry spliceosome

Talkish

Igel²,

Perriman³

et al. 2019

Preprint

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20Introns are a prevalent feature of eukaryotic genomes, yet their origins and contributions to genome 21 function and evolution remain mysterious. In budding yeast, repression of the highly transcribed 22 intron-containing ribosomal protein genes (RPGs) globally increases splicing of non-RPG transcripts 23 through reduced competition for the spliceosome. We show that under these "hungry spliceosome" 24 conditions, splicing occurs at more than 150 previously unannotated locations we call protointrons 25 that do not overlap known introns. Protointrons use a less constrained set of splice sites and 26 branchpoints than standard introns, including in one case AT-AC in place of GT-AG. Protointrons 27 are not conserved in all closely related species, suggesting that most are not under selection. Some 28 are found in non-coding RNAs (e. g. CUTs and SUTs), where they may contribute to the creation of 29 new genes. Others are found across boundaries between noncoding and coding sequences, or within 30 coding sequences, where they offer pathways to the creation of new protein variants, or new 31 regulatory controls for existing genes. We define protointrons as (1) nonconserved intron-like 32 sequences that are (2) infrequently spliced, and importantly (3) are not currently understood to 33 contribute to gene expression or regulation in the way that standard introns function. A very few 34 protointrons in S. cerevisiae challenge this classification by their increased splicing frequency and 35 potential function, consistent with the proposed evolutionary process of "intronization", whereby 36 new standard introns are created. This snapshot of intron evolution highlights the important role of 37 the spliceosome in the expansion of transcribed genomic sequence space, providing a pathway for 38 the rare events that may lead to the birth of new eukaryotic genes and the refinement of existing gene 39 function. 40 41 3 Author Summary 42The protein coding information in eukaryotic genes is broken by intervening sequences called 43 introns that are removed from RNA during transcription by a large protein-RNA complex called the 44 spliceosome. Where introns come from and how the spliceosome contributes to genome evolution 45 are open questions. In this study, we find more than 150 new places in the yeast genome that are 46 recognized by the spliceosome and spliced out as introns. Since they appear to have arisen very 47 recently in evolution by sequence drift and do not appear to contribute to gene expression or its 48 regulation, we call these protointrons. Protointrons are found in both protein-coding and non-coding 49RNAs and are not efficiently removed by the splicing machinery. Although most protointrons are 50 not conserved, a few are spliced more efficiently, and are located where they might begin to play 51 functional roles in gene expression, as predicted by the proposed process of intronization. The 52 challenge now is to understand how spontaneously appearing splicing events like protointrons might 53 contribute to the cr...

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“…Although the effect of codon usage on overall transcription has been widely studied and debated [60][61][62] , their surprisingly strong effects on transcription, also supported by our results (Fig 2B), have only recently started coming to light. The hypothesized mechanisms through which codons affect transcription are: (i) effects on nucleosome positioning 37 , (ii) premature termination of transcription, usually by mimicking poly-A signals 63 , or (iii) mRNA toxicity 64 . Generally, the differences in codon usage between bacterial species can be explained from the dinucleotide content in their non-coding regions 65 and it is widely assumed that most inter-species variation in codon usage is attributed to mutational mechanisms 60,66 .…”

Section: Discussionmentioning

confidence: 99%

Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Zrimec

Buric

Muhammad

et al. 2019

Preprint

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Understanding the genetic regulatory code that governs gene expression is a primary, yet challenging aspiration in molecular biology that opens up possibilities to cure human diseases and solve biotechnology problems. However, the fundamental question of how each of the individual coding and non-coding regions of the gene regulatory structure interact and contribute to the mRNA expression levels remains unanswered. Considering that all the information for gene expression regulation is already present in living cells, here we applied deep learning on over 20,000 mRNA datasets to learn the genetic regulatory code controlling mRNA expression in 7 model organisms ranging from bacteria to human.We show that in all organisms, mRNA abundance can be predicted directly from the DNA sequence with high accuracy, demonstrating that up to 82% of the variation of gene expression levels is encoded in the gene regulatory structure. Coding and non-coding regions carry both overlapping and orthogonal information and additively contribute to gene expression levels. By searching for DNA regulatory motifs present across the whole gene regulatory structure, we discover that motif interactions can regulate gene expression levels in a range of over three orders of magnitude. The uncovered co-evolution of coding and non-coding regions challenges the current paradigm that single motifs or regions are solely responsible for gene expression levels. Instead, we propose a holistic system that spans all regions of the gene structure and is required to analyse, understand, and design any future gene expression systems.

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Codon usage biases co-evolve with transcription termination machinery to suppress premature cleavage and polyadenylation

Cited by 60 publications

References 99 publications

Codon bias confers stability to humanmRNAs

Codon bias confers stability to humanmRNAs

Rapidly evolving protointrons inSaccharomycesgenomes revealed by a hungry spliceosome

Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

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