Assessing cell-specific effects of genetic variations using tRNA microarrays

Polte, Christine; Wedemeyer, Daniel; Oliver, Kathryn E.; Wagner, Johannes Maximilian; Bijvelds, Marcel J. C.; Mahoney, J.A.; Jonge, Hugo R. de; Sorscher, Eric J.; Ignatova, Zoya

doi:10.1186/s12864-019-5864-1

Cited by 22 publications

(24 citation statements)

References 75 publications

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“…Development of high-throughput tools, including tRNAbased microarrays (Dittmar et al, 2004;Polte et al, 2019), and more recently, optimized methods for high-throughput tRNA sequencing (Zheng et al, 2015;Gogakos et al, 2017;Shigematsu et al, 2017;Erber et al, 2020;Pinkard et al, 2020) have provided more efficient means for detection of individual tRNA-level fluctuations and enabled the discovery of key trends that regulate cell homeostasis in a tRNAdependent way. These studies revealed that tissue-specific tRNA expression generally reflects codon preference of highly expressed genes in human, indicating the importance of translation regulation via tRNA abundance in different tissues (Dittmar et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology

Avcilar-Kucukgoze

Kashina

2020

Front. Mol. Biosci.

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Transfer tRNAs (tRNAs) are small non-coding RNAs that are highly conserved in all kingdoms of life. Originally discovered as the molecules that deliver amino acids to the growing polypeptide chain during protein synthesis, tRNAs have been believed for a long time to play exclusive role in translation. However, recent studies have identified key roles for tRNAs and tRNA-derived small RNAs in multiple other processes, including regulation of transcription and translation, posttranslational modifications, stress response, and disease. These emerging roles suggest that tRNAs may be central players in the complex machinery of biological regulatory pathways. Here we overview these non-canonical roles of tRNA in normal physiology and disease, focusing largely on eukaryotic and mammalian systems.

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Section: Introductionmentioning

confidence: 99%

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology

Avcilar-Kucukgoze

Kashina

2020

Front. Mol. Biosci.

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“…Although synonymous site may changing the RNA secondary structure (23), we observed only one synonymous site appeared in the stem-loop regions overlapped with the ORF1ab gene in one genome (20). A tendency of mutation to rare codons shown by the negative value of log2 FCTE of the ORF1ab:A fragment (Fig.…”

Section: Discussionmentioning

confidence: 68%

“…Although such an estimation may be even more suitable for evaluation of adaptation of virus genome, because the codon usage frequency also reflects the stability of interactions between mRNA and anticodon in addition to tRNA abundance( 12), an direct measurement of tRNA abundance may help to further address various effects of translation kinetics. FCTE in the M and N genes confirm the adaptation of the genome of SARS-CoV-2 to the target tissue (12,20). Translation products of the M and N genes, both the most abundant structural proteins, interact with the genomic RNA intimately in the viral replication and virion packaging (21,22).…”

Section: Discussionmentioning

confidence: 76%

Synonymous sites in SARS-CoV-2 genes display trends affecting translational efficiency

Huang

Gao

Zheng

et al. 2020

Preprint

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11A novel coronavirus, SARS-CoV-2, has caused a pandemic of COVID-19. The 12 evolutionary trend of the virus genome may have implications for infection control policy 13 but remains obscure. We introduce an estimation of fold change of translational 14 efficiency based on synonymous variant sites to characterize the adaptation of the virus to 15 hosts. The increased translational efficiency of the M and N genes suggests that the 16 population of SARS-CoV-2 benefits from mutations toward favored codons, while the 17 ORF1ab gene has slightly decreased the translational efficiency. In the coding region of 18 the ORF1ab gene upstream of the -1 frameshift site, the decreasing of the translational 19 efficiency has been weakening parallel to the growth of the epidemic, indicating 20 inhibition of synthesis of RNA-dependent RNA polymerase and promotion of replication 21 of the genome. Such an evolutionary trend suggests that multiple infections increased 22 virulence in the absence of social distancing. 23 24 42 genomes of SARS-CoV-2 precludes the traditional methods, which were designed for 43 comparison between distant species, from extracting the subtle trend. Here, we introduce 44 a method based on fold change of translational efficiency (FCTE), which accumulates the 45 effects of synonymous SNV distributed sparsely in the genome of SARS-CoV-2 and 46 characterize the adaptation to hosts in the epidemic in China. 47 RESULTS 48 Density of SNV in the coding regions of SARS-CoV-2 49In 12 ORFs of SARS-CoV-2, there are on average only 0.021 nonsynonymous sites and 50 0.012 synonymous sites per 1000 nt per genome (Fig. 1A). The numbers of synonymous 51 3 and nonsynonymous sites in a coding region are both correlated with the length of the 52 coding region (Fig. 1B). Compare to the average mutation density, ORF1ab:A, which is 53 the coding region of the ORF1ab gene upstream of the -1 frameshift site, contains slightly 54 more synonymous sites, while ORF1ab:B, which is downstrem of the -1 frameshift site, 55 contains less synonymous sites. 57 FCTE measures the effect of mutation on the translation of the residing gene. We 58 estimated FCTE by the fold change of codon usage frequencies of the codon pair before 59 and after a synonymous mutation (Table S1). The codon usage frequency was calibrated 60 by the codon frequency averaged over a repertoire of genes weighted by their expression 61 levels in the type II alveolar (AT2) cells of lung tissue, which is probably the target cells 62 of SARS-CoV-2(15). Two topologies of phylogenetic trees of the genomes of SARS- 63 CoV-2 were examined. The first topology is star-like, in which the central ancestor is the 64 consensus sequence ( Fig. 2A). The second topology is a maximum likelihood tree rooted 65 131 protein starts synthesizing the complementary strand from the 3' end of the genomic RNA 132 and disrupts long distance pairing of RNA secondary structure, preventing the 133 frameshifting in later translation(24). So the ribosome will encounter a stop codon soon 134 and t...

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“…qRT-PCR assays displayed a linear range over five (R 2 = 0.99969, efficiency = 91%) or four (R 2 = 0.998; efficiency = 93%) orders of magnitude for CFTR or NPT, respectively. tRNA microarrays were performed as previously described (13,44). Fluorescent stem-loop RNA/DNA oligonucleotide bearing a Cy3 fluorescent dye (Microsynth) was ligated to total tRNA from CFBE41o − or FRT cells and compared to HeLa tRNA labeled with Atto647 stem-loop RNA/DNA oligonucleotide.…”

Section: Methodsmentioning

confidence: 99%

Positive epistasis between disease-causing missense mutations and silent polymorphism with effect on mRNA translation velocity

Rauscher

Bampi

Guevara-Ferrer

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Epistasis refers to the dependence of a mutation on other mutation(s) and the genetic context in general. In the context of human disorders, epistasis complicates the spectrum of disease symptoms and has been proposed as a major contributor to variations in disease outcome. The nonadditive relationship between mutations and the lack of complete understanding of the underlying physiological effects limit our ability to predict phenotypic outcome. Here, we report positive epistasis between intragenic mutations in the cystic fibrosis transmembrane conductance regulator (CFTR)—the gene responsible for cystic fibrosis (CF) pathology. We identified a synonymous single-nucleotide polymorphism (sSNP) that is invariant for the CFTR amino acid sequence but inverts translation speed at the affected codon. This sSNP in cis exhibits positive epistatic effects on some CF disease–causing missense mutations. Individually, both mutations alter CFTR structure and function, yet when combined, they lead to enhanced protein expression and activity. The most robust effect was observed when the sSNP was present in combination with missense mutations that, along with the primary amino acid change, also alter the speed of translation at the affected codon. Functional studies revealed that synergistic alteration in ribosomal velocity is the underlying mechanism; alteration of translation speed likely increases the time window for establishing crucial domain–domain interactions that are otherwise perturbed by each individual mutation.

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Assessing cell-specific effects of genetic variations using tRNA microarrays

Cited by 22 publications

References 75 publications

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology

Synonymous sites in SARS-CoV-2 genes display trends affecting translational efficiency

Positive epistasis between disease-causing missense mutations and silent polymorphism with effect on mRNA translation velocity

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