scholarly journals Intragenic MicroRNAs Autoregulate Their Host Genes in Both Direct and Indirect Ways—A Cross-Species Analysis

Cells ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 232 ◽  
Author(s):  
Maximilian Zeidler ◽  
Alexander Hüttenhofer ◽  
Michaela Kress ◽  
Kai K. Kummer
Keyword(s):  
Target Prediction ◽  
Gene Clusters ◽  
Host Gene ◽  
Gene Interactions ◽  
Protein Coding ◽  
Species Analysis ◽  
Recognition Elements ◽  
Autoregulatory Mechanism ◽  
Host Genes ◽  
Entire Gene

MicroRNAs (miRNAs) function as master switches for post-transcriptional gene expression. Their genes are either located in the extragenic space or within host genes, but these intragenic miRNA::host gene interactions are largely enigmatic. The aim of this study was to investigate the location and co-regulation of all to date available miRNA sequences and their host genes in an unbiased computational approach. The majority of miRNAs were located within intronic regions of protein-coding and non-coding genes. These intragenic miRNAs exhibited both increased target probability as well as higher target prediction scores as compared to a model of randomly permutated genes. This was associated with a higher number of miRNA recognition elements for the hosted miRNAs within their host genes. In addition, strong indirect autoregulation of host genes through modulation of functionally connected gene clusters by intragenic miRNAs was demonstrated. In addition to direct miRNA-to-host gene targeting, intragenic miRNAs also appeared to interact with functionally related genes, thus affecting their host gene function through an indirect autoregulatory mechanism. This strongly argues for the biological relevance of autoregulation not only for the host genes themselves but, more importantly, for the entire gene cluster interacting with the host gene.

scholarly journals Annotation of snoRNA abundance across human tissues reveals complex snoRNA-host gene relationships

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Étienne Fafard-Couture ◽  
Danny Bergeron ◽  
Sonia Couture ◽  
Sherif Abou-Elela ◽  
Michelle S. Scott
Keyword(s):  
Housekeeping Genes ◽  
Host Gene ◽  
Rna Modification ◽  
Human Tissues ◽  
Rna Seq ◽  
Healthy Human ◽  
Protein Coding ◽  
Conservation Level ◽  
Nucleolar Rnas ◽  
Host Genes

Abstract Background Small nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA abundance patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions. Results We used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues (breast, ovary, prostate, testis, skeletal muscle, liver, and brain). We identify 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level, and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. Fifty-nine percent of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, compared to only 16% of the correlated non-coding host gene/snoRNA pairs. Conclusions Our results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues.

scholarly journals Are spliced ncRNA host genes distinct classes of lncRNAs?

2020 ◽  
Vol 139 (4) ◽  
pp. 349-359
Author(s):  
Rituparno Sen ◽  
Jörg Fallmann ◽  
Maria Emília M. T. Walter ◽  
Peter F. Stadler
Keyword(s):  
Gene Function ◽  
Negative Answer ◽  
Positive Answer ◽  
Host Gene ◽  
Small Nucleolar Rnas ◽  
Biological Functions ◽  
Protein Coding ◽  
Non Coding Rnas ◽  
Nucleolar Rnas ◽  
Host Genes

AbstractMany small nucleolar RNAs and many of the hairpin precursors of miRNAs are processed from long non-protein-coding host genes. In contrast to their highly conserved and heavily structured payload, the host genes feature poorly conserved sequences. Nevertheless, there is mounting evidence that the host genes have biological functions beyond their primary task of carrying a ncRNA as payload. So far, no connections between the function of the host genes and the function of their payloads have been reported. Here we investigate whether there is evidence for an association of host gene function or mechanisms with the type of payload. To assess this hypothesis we test whether the miRNA host genes (MIRHGs), snoRNA host genes (SNHGs), and other lncRNA host genes can be distinguished based on sequence and/or structure features unrelated to their payload. A positive answer would imply a functional and mechanistic correlation between host genes and their payload, provided the classification does not depend on the presence and type of the payload. A negative answer would indicate that to the extent that secondary functions are acquired, they are not strongly constrained by the prior, primary function of the payload. We find that the three classes can be distinguished reliably when the classifier is allowed to extract features from the payloads. They become virtually indistinguishable, however, as soon as only sequence and structure of parts of the host gene distal from the snoRNAs or miRNA payload is used for classification. This indicates that the functions of MIRHGs and SNHGs are largely independent of the functions of their payloads. Furthermore, there is no evidence that the MIRHGs and SNHGs form coherent classes of long non-coding RNAs distinguished by features other than their payloads.

scholarly journals Dynamics and modulation of the human snoRNome

2021 ◽  
Author(s):  
Étienne Fafard-Couture ◽  
Danny Bergeron ◽  
Sonia Couture ◽  
Sherif Abou Elela ◽  
Michelle S Scott
Keyword(s):  
Expression Patterns ◽  
Housekeeping Genes ◽  
Host Gene ◽  
Rna Modification ◽  
Human Tissues ◽  
Healthy Human ◽  
Protein Coding ◽  
Conservation Level ◽  
Nucleolar Rnas ◽  
Host Genes

AbstractBackgroundSmall nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA expression patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions.ResultsWe used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues (breast, ovary, prostate, testis, skeletal muscle, liver and brain). We identified 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. 59% of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, as opposed to only 16% of the correlated non-coding host gene/snoRNA pairs.ConclusionsOur results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues.

scholarly journals Supervised and Unsupervised Classification of lncRNA Subtypes

2020 ◽  
Author(s):  
Rituparno Sen ◽  
Jörg Fallmann ◽  
Maria Emília M. T. Walter ◽  
Peter F. Stadler
Keyword(s):  
Unsupervised Classification ◽  
Positive Answer ◽  
Host Gene ◽  
Small Nucleolar Rnas ◽  
Biological Functions ◽  
Protein Coding ◽  
Non Coding Rnas ◽  
Nucleolar Rnas ◽  
Host Genes

AbstractMany small nucleolar RNAs and many of the hairpin precursors of miRNAs are processed from long non-protein-coding (lncRNA) host genes. In contrast to their highly conserved and heavily structured payload, the host genes feature poorly conserved sequences. Nevertheless there is mounting evidence that the host genes have biological functions. No obvious connections between the function of the host genes and the function of their payloads have been reported. Here we inverstigate whether there is an association of host gene function or mechanisms with the type of payload. To assess this hypothesis we test whether the miRNA host genes (MIRHGs), snoRNA host genes (SNHGs), and other lncRNAs host genes can be distinguished based on sequence and structure features. A positive answer would imply a correlation between host genes and their payload. While the three classes can be distinguished reliably when the classifier is allowed to extract features from the payloads, this is no longer the case when only sequence and structure of parts of the host gene distal from the snoRNAs or miRNA payload is used for classification. Our data indicate that the functions of MIRHGs and SNHGs are largely independent of the functions of their payloads. Furthermore, there is no evidence that the MIRHGs and SNHGs form coherent classes of long non-coding RNAs distinguished by features other than their payloads.

scholarly journals Gene recruitments and dismissals in argonaut octopus genome provide insights to pelagic lifestyle adaptation and shell-like eggcase reacquisition

2021 ◽  
Author(s):  
Masa-aki Yoshida ◽  
Kazuki Hirota ◽  
Junichi Imoto ◽  
Miki Okuno ◽  
Hiroyuki Tanaka ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Average Length ◽  
Draft Genome ◽  
Gene Clusters ◽  
Draft Genome Sequence ◽  
Shell Formation ◽  
Protein Coding ◽  
Homologous Genes ◽  
Phenotypic Structure ◽  
Comparative Genomics Analysis

The paper nautilus, Argonauta argo, also known as the greater argonaut, is a species of octopods distinctly characterized by its pelagic lifestyle and by the presence of a spiral-shaped shell-like eggcase in females. The eggcase functions by protecting the eggs laid inside it, and by building and keeping air intakes for buoyancy. To reveal the genomic background of the species′ adaptation to pelagic lifestyle and the acquisition of its shell-like eggcase, we sequenced the draft genome sequence of the species. The genome size was 1.1 Gb, which is the smallest among the cephalopods known to date, with the top 215 scaffolds (average length 5,064,479 bp) covering 81% (1.09 Gb) of the total assembly. A total of 26,433 protein-coding genes were predicted from 16,802 assembled scaffolds. From these, we identified nearly intact HOX, Parahox, Wnt clusters and some gene clusters probably related to the pelagic lifestyle, such as reflectin, tyrosinase, and opsin. For example, opsin might have undergone an extensive duplication in order to adapt to the pelagic lifestyle, as opposed to other octopuses, which are mostly the benthic. Our gene models also discovered several genes homologous to those related to calcified shell formation in Conchiferan Mollusks, such as Pif-like, SOD, and TRX. Interestingly, comparative genomics analysis revealed that the homologous genes for such genes were also found in the genome of the octopus, which does not have a shell, as well as the basal cephalopods Nautilus. Therefore, the draft genome sequence of A. argo we presented here had not only helped us to gain further insights into the genetic background of the dynamic recruitment and dismissal of genes for the formation of an important, converging extended phenotypic structure such as the shell and the shell-like eggcase, but also the evolution of lifestyles in Cephalopods and the octopods, from benthic to pelagic.

scholarly journals The Draft Genome Sequence of The Endophytic Streptomyces Strain VITGV156

2021 ◽  
Author(s):  
Veilumuthu P ◽  
Nagarajan T ◽  
Sasikumar S ◽  
Siva R ◽  
J Godwin Christopher
Keyword(s):  
Secondary Metabolites ◽  
Draft Genome ◽  
Gc Content ◽  
Gene Clusters ◽  
Dominant Group ◽  
Protein Coding ◽  
Peptide Synthetase ◽  
The Family ◽  
Modified Peptides ◽  
Endophytic Streptomyces

Abstract Streptomyces species is one among the dominant group of bacteria in the family Actinobacteria with a rich repertoire of secondary metabolites. Secondary metabolites with antimicrobial activity and plant growth promotor have been isolated from various Streptomyces sp. Here in this investigation, we present the draft genome of a new species, Streptomyces sp. VITGV156 isolated from healthy tomato plant (Lycopersicon esculentum) which has some rare antimicrobial secondary metabolites, like coelichelin, fluostatins, vicenistatin, nystatin, sipanmycin, and informatipeptin. The genome is 8.18 Mb in size with 6,259 protein coding genes. The average GC content of the genome is 72.61 %. Preliminary analysis with antiSMASH 6.0 revealed the presence of 29 biosynthetic gene clusters for the synthesis of potential secondary metabolites. These includes 4 NRPS (non – ribosomal peptide synthetase), 7 PKS (Polyketide Synthases), 2 RiPP (Ribosomally synthesized and post-translationally modified peptides) clusters. When we look into genes associated with secondary metabolites, 406 genes are present which includes 184 genes for cofactor and vitamins, 72 genes for terpenoids and polyketides, 70 genes for xenobiotics and 80 genes for other metabolites are present. Comparative genome analysis of VITGV156 with its closest neighbor Streptomyces luteus strain TRM45540 revealed ANI 91.22% and dDDH value 44.00%.

scholarly journals Draft Genome Sequence of Streptomyces cavourensis YBQ59, an Endophytic Producer of Antibiotics Bafilomycin D, Nonactic Acid, Prelactone B, and 5,11-Epoxy-10-Cadinanol

2018 ◽  
Vol 7 (11) ◽  
Author(s):  
Huy Quang Nguyen ◽  
Nguyen Thi-Hanh Vu ◽  
Ha Hoang Chu ◽  
Son Ky Chu ◽  
Ha Hoang ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Draft Genome ◽  
Gc Content ◽  
Gene Clusters ◽  
Draft Genome Sequence ◽  
Biosynthetic Pathways ◽  
Protein Coding ◽  
Content Type ◽  
Protein Coding Genes

This study reports the draft genome sequence of the endophytic Streptomyces cavourensis strain YBQ59, produces the antibiotics bafilomycin D, nonactic acid, prelactone B, and 5,11-epoxy-10-cadinanol. The draft genome sequence comprises ∼10.2 Mb, with a GC content of 64% and 8,958 predicted protein-coding genes, of which 14 gene clusters were found to associate with antibiotic biosynthetic pathways.

Bioinformatics Methods for Studying MicroRNA and ARE-Mediated Regulation of Post-Transcriptional Gene Expression

2010 ◽  
Vol 1 (3) ◽  
pp. 97-112 ◽  
Author(s):  
Richipal Singh Bindra ◽  
Jason T. L. Wang ◽  
Paramjeet Singh Bagga
Keyword(s):  
Mirna Target ◽  
Target Prediction ◽  
Untranslated Regions ◽  
Regulatory Rna ◽  
Rna Motifs ◽  
Protein Coding ◽  
Rna Molecules ◽  
Cellular Processes ◽  
Target Sites ◽  
Transcriptional Gene Regulation

MicroRNAs (miRNAs) are short single-stranded RNA molecules with 21-22 nucleotides known to regulate post-transcriptional expression of protein-coding genes involved in most of the cellular processes. Prediction of miRNA targets is a challenging bioinformatics problem. AU-rich elements (AREs) are regulatory RNA motifs found in the 3’ untranslated regions (UTRs) of mRNAs, and they play dominant roles in the regulated decay of short-lived human mRNAs via specific interactions with proteins. In this paper, the authors review several miRNA target prediction tools and data sources, as well as computational methods used for the prediction of AREs. The authors discuss the connection between miRNA and ARE-mediated post-transcriptional gene regulation. Finally, a data mining method for identifying the co-occurrences of miRNA target sites in ARE containing genes is presented.

scholarly journals Interplay between miRNAs and host genes and their role in cancer

2019 ◽  
Vol 18 (4) ◽  
pp. 255-266 ◽  
Author(s):  
Baohong Liu ◽  
Yu Shyr ◽  
Jianping Cai ◽  
Qi Liu
Keyword(s):  
Tumor Suppressors ◽  
Target Genes ◽  
Epithelial Mesenchymal Transition ◽  
Fine Tuning ◽  
Data Sets ◽  
Protein Coding ◽  
Mesenchymal Transition ◽  
Damage Repair ◽  
Cancer Types ◽  
Host Genes

Abstract MicroRNAs (miRNAs) are small endogenous non-coding functional RNAs that post-transcriptionally regulate gene expression. They play essential roles in nearly all biological processes including cell development and differentiation, DNA damage repair, cell death as well as intercellular communication. They are highly involved in cancer, acting as tumor suppressors and/or promoters to modulate cell proliferation, epithelial-mesenchymal transition and tumor invasion and metastasis. Recent studies have shown that more than half of miRNAs are located within protein-coding or non-coding genes. Intragenic miRNAs and their host genes either share the promoter or have independent transcription. Meanwhile, miRNAs work as partners or antagonists of their host genes by fine-tuning their target genes functionally associated with host genes. This review outlined the complicated relationship between intragenic miRNAs and host genes. Focusing on miRNAs known as oncogenes or tumor suppressors in specific cancer types, it studied co-expression relationships between these miRNAs and host genes in the cancer types using TCGA data sets, which validated previous findings and revealed common, tumor-specific and even subtype-specific patterns. These observations will help understand the function of intragenic miRNAs and further develop miRNA therapeutics in cancer.

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