scholarly journals Predicting transfer RNA gene activity from sequence and genome context

2019 ◽  
Author(s):  
Bryan Thornlow ◽  
Joel Armstrong ◽  
Andrew Holmes ◽  
Russell Corbett-Detig ◽  
Todd Lowe
Keyword(s):  
Gene Expression ◽  
Trna Gene ◽  
Gene Expression Regulation ◽  
Gene Families ◽  
Transfer Rna ◽  
Gene Activity ◽  
Comparative Genomic ◽  
Trna Genes ◽  
Genomic Context ◽  
High Sequence Identity

ABSTRACTTransfer RNA (tRNA) genes are among the most highly transcribed genes in the genome due to their central role in protein synthesis. However, there is evidence for a broad range of gene expression across tRNA loci. This complexity, combined with difficulty in measuring transcript abundance and high sequence identity across transcripts, has severely limited our collective understanding of tRNA gene expression regulation and evolution. We establish sequence-based correlates to tRNA gene expression and develop a tRNA gene classification method that does not require, but benefits from comparative genomic information, and achieves accuracy comparable to molecular assays. We observe that guanine+cytosine (G+C) content and CpG density surrounding tRNA loci is exceptionally well correlated with tRNA gene activity, supporting a prominent regulatory role of the local genomic context in combination with internal sequence features. We use our tRNA gene activity predictions in conjunction with a comprehensive tRNA gene ortholog set spanning 29 placental mammals to infer the frequency of changes to tRNA gene expression among orthologs. Our method adds an important new dimension to tRNA annotation and will help focus the study of natural tRNA variants. Its simplicity and robustness enables facile application to other clades and timescales, as well as exploration of functional diversification of tRNAs and other large gene families.

scholarly journals Large, rapidly evolving gene families are at the forefront of host–parasite interactions inApicomplexa

Parasitology ◽  
2014 ◽  
Vol 142 (S1) ◽  
pp. S57-S70 ◽  
Author(s):  
ADAM J REID
Keyword(s):  
Gene Expression ◽  
Malaria Parasite ◽  
Gene Expression Regulation ◽  
Protein Localization ◽  
Animal Health ◽  
Gene Families ◽  
Sequence Diversity ◽  
Genomic Context ◽  
Host Parasite Interactions ◽  
Host Parasite

SUMMARYTheApicomplexais a phylum of parasitic protozoa, which includes the malaria parasitePlasmodium, amongst other species that can devastate human and animal health. The past decade has seen the release of genome sequences for many of the most important apicomplexan species, providing an excellent basis for improving our understanding of their biology. One of the key features of each genome is a unique set of large, variant gene families. Although closely related species share the same families, even different types of malaria parasite have distinct families. In some species they tend to be found at the ends of chromosomes, which may facilitate aspects of gene expression regulation and generation of sequence diversity. In others they are scattered apparently randomly across chromosomes. For some families there is evidence they are involved in antigenic variation, immune regulation and immune evasion. For others there are no known functions. Even where function is unknown these families are most often predicted to be exposed to the host, contain much sequence diversity and evolve rapidly. Based on these properties it is clear that they are at the forefront of host–parasite interactions. In this review I compare and contrast the genomic context, gene structure, gene expression, protein localization and function of these families across different species.

An Integrated Epigenomic Analysis Approach To Determine the Molecular Basis of Acute Leukemias.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3276-3276
Author(s):  
Maria E. Figueroa ◽  
Kenny M. Ye ◽  
Elisabeth Paietta ◽  
John M. Greally ◽  
Ari M. Melnick
Keyword(s):  
Gene Expression ◽  
Molecular Basis ◽  
Expression Profiles ◽  
Gene Activity ◽  
Gene Copy ◽  
Comparative Genomic ◽  
Acute Leukemias ◽  
Expression Arrays ◽  
Genome Wide ◽  
Depth Analysis

Abstract Acute leukemias are classified based on their immunologic, cytogenetic and morphologic characteristics. However, in most instances, response to treatment and survival probability cannot be accurately predicted, suggesting that the disease is even more complex and heterogeneous than can be shown with current techniques. Although prognostic value has been shown for certain gene expression profiles, expression profile studies are limited by the fact that only a snapshot of mRNA content is obtained in a basal state, failing to represent how genes will respond to different stresses, also failing to detect the roles of genes expressed at lower levels for which major changes in expression levels are often lost in the “noise” of expression arrays. In order to overcome these issues and to provide a more accurate molecular phenotype of acute leukemias, we established an integrated epigenomic and genomic high-throughput platform using novel techniques and custom high-density oligonucleotide arrays. We combine studies of i) genome-wide cytosine methylation using a novel technique we developed that provides accurate quantitative determination of DNA methylation levels, using genome-wide custom oligo arrays, ii) chromatin structure by ChIP on chip for histone code settings associated with active or repressed genes using 24 K promoter tiling arrays, iii) gene copy number by array-based comparative genomic hybridization (array CGH) at 6 kb resolution genome-wide and iv) 36 K gene expression arrays. Results are validated by single locus quantitative PCR techniques. Cross platform integration is facilitated by use of NimbleGen oligo arrays for all studies and analysis using novel bioinformatics and statistical models. We used this integrative analysis platform to perform an in-depth analysis of the epigenomic basis of AML and ALL using primary patient samples and cell lines. The data allowed us to generate a “gene activity index” which identified the ability of genes to be expressed to be characterized genome-wide in AML and ALL cells. This data also allowed a much more comprehensive analysis of pathways active in these cells to be identified in comparison to expression arrays alone. Our current studies apply integrative platform and gene activity indexing to large series of patients enrolled in multicenter clinical trials in order to provide high-resolution analysis of the molecular basis of acute leukemia.

scholarly journals AmpDI Is Involved in Expression of the Chromosomal L1 and L2 β-Lactamases of Stenotrophomonas maltophilia

2009 ◽  
Vol 53 (7) ◽  
pp. 2902-2907 ◽  
Author(s):  
Tsuey-Ching Yang ◽  
Yi-Wei Huang ◽  
Rouh-Mei Hu ◽  
Shao-Cheng Huang ◽  
Yu-Tzu Lin
Keyword(s):  
Gene Expression ◽  
Pseudomonas Aeruginosa ◽  
Stenotrophomonas Maltophilia ◽  
Genomic Analysis ◽  
Comparative Genomic Analysis ◽  
Comparative Genomic ◽  
Genomic Context ◽  
One Step ◽  
L1 And L2

ABSTRACT Two ampD homologues, ampD I and ampD II, of Stenotrophomonas maltophilia have been cloned and analyzed. Comparative genomic analysis revealed that the genomic context of the ampD II genes is quite different, whereas that of the ampD I genes is more conserved in S. maltophilia strains. The ampD system of S. maltophilia is distinct from that of the Enterobacteriaceae and Pseudomonas aeruginosa in three respects. (i) AmpDI of S. maltophilia is not encoded in an ampDE operon, in contrast to what happens in the Enterobacteriaceae and P. aeruginosa. (ii) The AmpD systems of the Enterobacteriaceae and P. aeruginosa are generally involved in the regulation of ampR-linked ampC gene expression, while AmpDI of S. maltophilia is responsible for the regulation of two intrinsic β-lactamase genes, of which the L2 gene, but not the L1 gene, is linked to ampR. (iii) S. maltophilia exhibits a one-step L1 and L2 gene derepression model involving ampD I, distinct from the two- or three-step derepression of the Enterobacteriaceae and P. aeruginosa. Moreover, the ampD I and ampD II genes are constitutively expressed and not regulated by the inducer and AmpR protein, and the expression of ampD II is weaker than that of ampD I. Finally, AmpDII is not associated with the derepression of β-lactamases, and its role in S. maltophilia remains unclear.

scholarly journals Transfer RNA genes experience exceptionally elevated mutation rates

2017 ◽  
Author(s):  
Bryan P. Thornlow ◽  
Josh Hough ◽  
Jacquelyn M. Roger ◽  
Henry Gong ◽  
Todd M. Lowe ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Sequence Variation ◽  
Trna Gene ◽  
Purifying Selection ◽  
Transfer Rna ◽  
Mutation Rates ◽  
Biological Synthesis ◽  
Human Populations ◽  
Trna Genes ◽  
Mutational Load

AbstractTransfer RNAs (tRNAs) are a central component for the biological synthesis of proteins, and they are among the most highly conserved and frequently transcribed genes in all living things. Despite their clear significance for fundamental cellular processes, the forces governing tRNA evolution are poorly understood. We present evidence that transcription-associated mutagenesis and strong purifying selection are key determinants of patterns of sequence variation within and surrounding tRNA genes in humans and diverse model organisms. Remarkably, the mutation rate at broadly expressed cytosolic tRNA loci is likely between seven and ten times greater than the nuclear genome average. Furthermore, evolutionary analyses provide strong evidence that tRNA genes, but not their flanking sequences, experience strong purifying selection, acting against this elevated mutation rate. We also find a strong correlation between tRNA expression levels and the mutation rates in their immediate flanking regions, suggesting a simple new method for estimating individual tRNA gene activity. Collectively, this study illuminates the extreme competing forces in tRNA gene evolution, and implies that mutations at tRNA loci contribute disproportionately to mutational load and have unexplored fitness consequences in human populations.Significance StatementWhile transcription-associated mutagenesis (TAM) has been demonstrated for protein coding genes, its implications in shaping genome structure at transfer RNA (tRNA) loci in metazoans have not been fully appreciated. We show that cytosolic tRNAs are a striking example of TAM because of their variable rates of transcription, well-defined boundaries and internal promoter sequences. tRNA loci have a mutation rate approximately seven-to tenfold greater than the genome-wide average, and these mutations are consistent with signatures of TAM. These observations indicate that tRNA loci are disproportionately large contributors to mutational load in the human genome. Furthermore, the correlations between tRNA locus variation and transcription implicate that prediction of tRNA gene expression based on sequence variation data is possible.

scholarly journals Cloning and nucleotide sequence analysis of transfer RNA genes from Mycoplasma mycoides

1985 ◽  
Vol 232 (1) ◽  
pp. 223-228 ◽  
Author(s):  
T Samuelsson ◽  
P Elias ◽  
F Lustig ◽  
Y S Guindy
Keyword(s):  
Sequence Analysis ◽  
Nucleotide Sequence ◽  
Trna Gene ◽  
Transfer Rna ◽  
Nucleotide Sequences ◽  
Transcriptional Unit ◽  
Nucleotide Sequence Analysis ◽  
Trna Genes ◽  
Mycoplasma Mycoides ◽  
Rna Genes

As part of an investigation of the tRNA genes of Mycoplasma mycoides, two HindIII fragments of mycoplasma DNA comprising 0.4 and 2.5 kilobases (kb), respectively, were cloned in pBR322 and their nucleotide sequences determined. Only one tRNA gene was found in the 0.4 kb fragment, the gene for tRNAArg with the anticodon TCT, while the 2.5 kb fragment contained nine different tRNA genes arranged in a cluster which presumably constitutes a transcriptional unit. The clustered tRNA genes, with their respective anticodons, were as follows: Arg (ACG), Pro (TGG), Ala (TGC), Met (CAT), Ile (CAT), Ser (TGA), fMet (CAT), Asp (GTC), and Phe (GAA).

scholarly journals Differential expression of human tRNA genes drives the abundance of tRNA-derived fragments

2019 ◽  
Vol 116 (17) ◽  
pp. 8451-8456 ◽  
Author(s):  
Adrian Gabriel Torres ◽  
Oscar Reina ◽  
Camille Stephan-Otto Attolini ◽  
Lluís Ribas de Pouplana
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Trna Gene ◽  
Single Gene ◽  
Somatic Tissue ◽  
Trna Genes ◽  
Individual Contribution ◽  
Tissue Samples ◽  
Cultured Human Cells

The human genome encodes hundreds of transfer RNA (tRNA) genes but their individual contribution to the tRNA pool is not fully understood. Deep sequencing of tRNA transcripts (tRNA-Seq) can estimate tRNA abundance at single gene resolution, but tRNA structures and posttranscriptional modifications impair these analyses. Here we present a bioinformatics strategy to investigate differential tRNA gene expression and use it to compare tRNA-Seq datasets from cultured human cells and human brain. We find that sequencing caveats affect quantitation of only a subset of human tRNA genes. Unexpectedly, we detect several cases where the differences in tRNA expression among samples do not involve variations at the level of isoacceptor tRNA sets (tRNAs charged with the same amino acid but using different anticodons), but rather among tRNA genes within the same isodecoder set (tRNAs having the same anticodon sequence). Because isodecoder tRNAs are functionally equal in terms of genetic translation, their differential expression may be related to noncanonical tRNA functions. We show that several instances of differential tRNA gene expression result in changes in the abundance of tRNA-derived fragments (tRFs) but not of mature tRNAs. Examples of differentially expressed tRFs include PIWI-associated RNAs, tRFs present in tissue samples but not in cells cultured in vitro, and somatic tissue-specific tRFs. Our data support that differential expression of tRNA genes regulate noncanonical tRNA functions performed by tRFs.

scholarly journals Enjoy the Silence: Nearly Half of Human tRNA Genes Are Silent

2019 ◽  
Vol 13 ◽  
pp. 117793221986845 ◽  
Author(s):  
Adrian Gabriel Torres
Keyword(s):  
Gene Expression ◽  
Small Rna ◽  
Trna Gene ◽  
Trna Genes ◽  
Messenger Rnas ◽  
Rna Seq ◽  
Cell Type ◽  
Transfer Rnas ◽  
Gene Contribution ◽  
Generation Sequencing

Transfer RNAs (tRNAs) are key components of the translation machinery. They read codons on messenger RNAs (mRNAs) and deliver the appropriate amino acid to the ribosome for protein synthesis. The human genome encodes more than 500 tRNA genes but their individual contribution to the cellular tRNA pool is unclear. In recent years, novel methods were developed to improve the quantification of tRNA gene expression, most of which rely on next-generation sequencing such as small RNA-Seq applied to tRNAs (tRNA-Seq). In a previous study, we presented a bioinformatics strategy to analyse tRNA-Seq datasets that we named ‘isodecoder-specific tRNA gene contribution profiling’ (Iso-tRNA-CP). Using Iso-tRNA-CP, we showed that tRNA gene expression is cell type- and tissue-specific and that this process can regulate tRNA-derived fragments abundance. An additional observation that stems from that work is that approximately half of human tRNA genes appeared silent or poorly expressed. In this commentary, I discuss this finding in light of the current literature and speculate on potential functions that transcriptionally silent tRNA genes may play. Studying silent tRNA genes may offer a unique opportunity to unravel novel mechanisms of cell regulation associated to tRNA biology.

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