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  • 1
    Online Resource
    Online Resource
    Assessing the functional association of intronic miRNAs with their host genes
    Cold Spring Harbor Laboratory ; 2018
    In:  RNA Vol. 24, No. 8 ( 2018-08), p. 991-1004
    Details
    In: RNA, Cold Spring Harbor Laboratory, Vol. 24, No. 8 ( 2018-08), p. 991-1004
    Abstract: In human, nearly half of the known microRNAs (miRNAs) are encoded within the introns of protein-coding genes. The embedment of these miRNA genes within the sequences of protein-coding genes alludes to a possible functional relationship between intronic miRNAs and their hosting genes. Several studies, using predicted targets, suggested that intronic miRNAs influence their hosts’ function either antagonistically or synergistically. New experimental data of miRNA expression patterns and targets enable exploring this putative association by relying on actual data rather than on predictions. Here, our analysis based on currently available experimental data implies that the potential functional association between intronic miRNAs and their hosting genes is limited. For host-miRNA examples where functional associations were detected, it was manifested by either autoregulation, common targets of the miRNA and hosting gene, or through the targeting of transcripts participating in pathways in which the host gene is involved. This low prevalence of functional association is consistent with our observation that many intronic miRNAs have independent transcription start sites and are not coexpressed with the hosting gene. Yet, the intronic miRNAs that do show functional association with their hosts were found to be more evolutionarily conserved compared to other intronic miRNAs. This might suggest a selective pressure to maintain this architecture when it has a functional consequence.
    Type of Medium: Online Resource
    ISSN: 1355-8382 , 1469-9001
    URL: Article
    DOI: 10.1261/rna.064386.117
    Language: English
    Publisher: Cold Spring Harbor Laboratory
    Publication Date: 2018
    detail.hit.zdb_id: 1475737-0
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    Evolutionary patterns of Escherichia coli small RNAs and their regulatory interactions
    Cold Spring Harbor Laboratory ; 2014
    In:  RNA Vol. 20, No. 7 ( 2014-07), p. 994-1003
    Details
    In: RNA, Cold Spring Harbor Laboratory, Vol. 20, No. 7 ( 2014-07), p. 994-1003
    Abstract: Most bacterial small RNAs (sRNAs) are post-transcriptional regulators of gene expression, exerting their regulatory function by base-pairing with their target mRNAs. While it has become evident that sRNAs play central regulatory roles in the cell, little is known about their evolution and the evolution of their regulatory interactions. Here we used the prokaryotic phylogenetic tree to reconstruct the evolutionary history of Escherichia coli sRNAs and their binding sites on target mRNAs. We discovered that sRNAs currently present in E. coli mainly accumulated inside the Enterobacteriales order, succeeding the appearance of other types of noncoding RNAs and concurrently with the evolution of a variant of the Hfq protein exhibiting a longer C-terminal region. Our analysis of the evolutionary ages of sRNA–mRNA interactions revealed that while all sRNAs were evolutionarily older than most of their known binding sites on mRNA targets, for quite a few sRNAs there was at least one binding site that coappeared with or preceded them. It is conceivable that the establishment of these first interactions forced selective pressure on the sRNAs, after which additional targets were acquired by fitting a binding site to the active region of the sRNA. This conjecture is supported by the appearance of many binding sites on target mRNAs only after the sRNA gain, despite the prior presence of the target gene in ancestral genomes. Our results suggest a selective mechanism that maintained the sRNAs across the phylogenetic tree, and shed light on the evolution of E. coli post-transcriptional regulatory network.
    Type of Medium: Online Resource
    ISSN: 1355-8382 , 1469-9001
    URL: Article
    DOI: 10.1261/rna.043133.113
    Language: English
    Publisher: Cold Spring Harbor Laboratory
    Publication Date: 2014
    detail.hit.zdb_id: 1475737-0
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Common Adaptive Strategies Underlie Within-Host Evolution of Bacterial Pathogens
    Oxford University Press (OUP) ; 2021
    In:  Molecular Biology and Evolution Vol. 38, No. 3 ( 2021-03-09), p. 1101-1121
    Details
    In: Molecular Biology and Evolution, Oxford University Press (OUP), Vol. 38, No. 3 ( 2021-03-09), p. 1101-1121
    Abstract: Within-host adaptation is a hallmark of chronic bacterial infections, involving substantial genomic changes. Recent large-scale genomic data from prolonged infections allow the examination of adaptive strategies employed by different pathogens and open the door to investigate whether they converge toward similar strategies. Here, we compiled extensive data of whole-genome sequences of bacterial isolates belonging to miscellaneous species sampled at sequential time points during clinical infections. Analysis of these data revealed that different species share some common adaptive strategies, achieved by mutating various genes. Although the same genes were often mutated in several strains within a species, different genes related to the same pathway, structure, or function were changed in other species utilizing the same adaptive strategy (e.g., mutating flagellar genes). Strategies exploited by various bacterial species were often predicted to be driven by the host immune system, a powerful selective pressure that is not species specific. Remarkably, we find adaptive strategies identified previously within single species to be ubiquitous. Two striking examples are shifts from siderophore-based to heme-based iron scavenging (previously shown for Pseudomonas aeruginosa) and changes in glycerol-phosphate metabolism (previously shown to decrease sensitivity to antibiotics in Mycobacterium tuberculosis). Virulence factors were often adaptively affected in different species, indicating shifts from acute to chronic virulence and virulence attenuation during infection. Our study presents a global view on common within-host adaptive strategies employed by different bacterial species and provides a rich resource for further studying these processes.
    Type of Medium: Online Resource
    ISSN: 1537-1719
    URL: Article
    DOI: 10.1093/molbev/msaa278
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2024221-9
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  • 4
    Online Resource
    Online Resource
    Host Immune System Gene Targeting by a Viral miRNA
    American Association for the Advancement of Science (AAAS) ; 2007
    In:  Science Vol. 317, No. 5836 ( 2007-07-20), p. 376-381
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 317, No. 5836 ( 2007-07-20), p. 376-381
    Abstract: Virally encoded microRNAs (miRNAs) have recently been discovered in herpesviruses. However, their biological roles are mostly unknown. We developed an algorithm for the prediction of miRNA targets and applied it to human cytomegalovirus miRNAs, resulting in the identification of the major histocompatibility complex class I–related chain B (MICB) gene as a top candidate target of hcmv-miR-UL112. MICB is a stress-induced ligand of the natural killer (NK) cell activating receptor NKG2D and is critical for the NK cell killing of virus-infected cells and tumor cells. We show that hcmv-miR-UL112 specifically down-regulates MICB expression during viral infection, leading to decreased binding of NKG2D and reduced killing by NK cells. Our results reveal a miRNA-based immunoevasion mechanism that appears to be exploited by human cytomegalovirus.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.1140956
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2007
    detail.hit.zdb_id: 128410-1
    detail.hit.zdb_id: 2066996-3
    detail.hit.zdb_id: 2060783-0
    SSG: 11
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  • 5
    Online Resource
    Online Resource
    Identification and characterization of E.coli ribosomal binding sites by free energy computation
    Oxford University Press (OUP) ; 1993
    In:  Nucleic Acids Research Vol. 21, No. 17 ( 1993), p. 4019-4023
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 21, No. 17 ( 1993), p. 4019-4023
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/21.17.4019
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 1993
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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  • 6
    Online Resource
    Online Resource
    Markovian domain fingerprinting: statistical segmentation of protein sequences
    Oxford University Press (OUP) ; 2001
    In:  Bioinformatics Vol. 17, No. 10 ( 2001-10-01), p. 927-934
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 17, No. 10 ( 2001-10-01), p. 927-934
    Abstract: Motivation: Characterization of a protein family by its distinct sequence domains is crucial for functional annotation and correct classification of newly discovered proteins. Conventional Multiple Sequence Alignment (MSA) based methods find difficulties when faced with heterogeneous groups of proteins. However, even many families of proteins that do share a common domain contain instances of several other domains, without any common underlying linear ordering. Ignoring this modularity may lead to poor or even false classification results. An automated method that can analyze a group of proteins into the sequence domains it contains is therefore highly desirable. Results: We apply a novel method to the problem of protein domain detection. The method takes as input an unaligned group of protein sequences. It segments them and clusters the segments into groups sharing the same underlying statistics. A Variable Memory Markov (VMM) model is built using a Prediction Suffix Tree (PST) data structure for each group of segments. Refinement is achieved by letting the PSTs compete over the segments, and a deterministic annealing framework infers the number of underlying PST models while avoiding many inferior solutions. We show that regions of similar statistics correlate well with protein sequence domains, by matching a unique signature to each domain. This is done in a fully automated manner, and does not require or attempt an MSA. Several representative cases are analyzed. We identify a protein fusion event, refine an HMM superfamily classification into the underlying families the HMM cannot separate, and detect all 12 instances of a short domain in a group of 396 sequences. Contact: jill@cs.huji.ac.il; tishby@cs.huji.ac.il * To whom correspondence should be addressed.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/17.10.927
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2001
    detail.hit.zdb_id: 1468345-3
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Protein Antigenic Structures Recognized by T Cells; Potential Applications to Vaccine Design
    Wiley ; 1987
    In:  Immunological Reviews Vol. 98, No. 1 ( 1987-08), p. 9-52
    Details
    In: Immunological Reviews, Wiley, Vol. 98, No. 1 ( 1987-08), p. 9-52
    Type of Medium: Online Resource
    ISSN: 0105-2896 , 1600-065X
    URL: Issue
    URL: Article
    DOI: 10.1111/imr.1987.98.issue-1
    DOI: 10.1111/j.1600-065X.1987.tb00518.x
    Language: English
    Publisher: Wiley
    Publication Date: 1987
    detail.hit.zdb_id: 2038276-5
    SSG: 12
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  • 8
    Online Resource
    Online Resource
    Table_6.xlsx
    Frontiers Media SA ; 2021
    In:  Frontiers in Microbiology Vol. 12 ( 2021-5-21)
    Details
    In: Frontiers in Microbiology, Frontiers Media SA, Vol. 12 ( 2021-5-21)
    Abstract: The genomic revolution and subsequent advances in large-scale genomic and transcriptomic technologies highlighted hidden genomic treasures. Among them stand out non-coding small RNAs (sRNAs), shown to play important roles in post-transcriptional regulation of gene expression in both pro- and eukaryotes. Bacterial sRNA-encoding genes were initially identified in intergenic regions, but recent evidence suggest that they can be encoded within other, well-defined, genomic elements. This notion was strongly supported by data generated by RIL-seq, a RNA-seq-based methodology we recently developed for deciphering chaperon-dependent sRNA-target networks in bacteria. Applying RIL-seq to Hfq-bound RNAs in Escherichia coli , we found that ∼64% of the detected RNA pairs involved known sRNAs, suggesting that yet unknown sRNAs may be included in the ∼36% remaining pairs. To determine the latter, we first tested and refined a set of quantitative features derived from RIL-seq data, which distinguish between Hfq-dependent sRNAs and “other RNAs”. We then incorporated these features in a machine learning-based algorithm that predicts novel sRNAs from RIL-seq data, and identified high-scoring candidates encoded in various genomic regions, mostly intergenic regions and 3′ untranslated regions, but also 5′ untranslated regions and coding sequences. Several candidates were further tested and verified by northern blot analysis as Hfq-dependent sRNAs. Our study reinforces the emerging concept that sRNAs are encoded within various genomic elements, and provides a computational framework for the detection of additional sRNAs in Hfq RIL-seq data of E. coli grown under different conditions and of other bacteria manifesting Hfq-mediated sRNA-target interactions.
    Type of Medium: Online Resource
    ISSN: 1664-302X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fmicb.2021.635070
    DOI: 10.3389/fmicb.2021.635070.s001
    DOI: 10.3389/fmicb.2021.635070.s002
    DOI: 10.3389/fmicb.2021.635070.s003
    DOI: 10.3389/fmicb.2021.635070.s004
    DOI: 10.3389/fmicb.2021.635070.s005
    DOI: 10.3389/fmicb.2021.635070.s006
    DOI: 10.3389/fmicb.2021.635070.s007
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2587354-4
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  • 9
    Online Resource
    Online Resource
    Zinc Fingers: Conserved Properties that Can Distinguish Between Spurious and Actual DNA-Binding Motifs
    Informa UK Limited ; 1993
    In:  Journal of Biomolecular Structure and Dynamics Vol. 11, No. 3 ( 1993-12), p. 557-570
    Details
    In: Journal of Biomolecular Structure and Dynamics, Informa UK Limited, Vol. 11, No. 3 ( 1993-12), p. 557-570
    Type of Medium: Online Resource
    ISSN: 0739-1102 , 1538-0254
    URL: Article
    DOI: 10.1080/07391102.1993.10508015
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 1993
    detail.hit.zdb_id: 2085732-9
    SSG: 12
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  • 10
    Online Resource
    Online Resource
    Accessibility and Evolutionary Conservation Mark Bacterial Small-RNA Target-Binding Regions
    American Society for Microbiology ; 2011
    In:  Journal of Bacteriology Vol. 193, No. 7 ( 2011-04), p. 1690-1701
    Details
    In: Journal of Bacteriology, American Society for Microbiology, Vol. 193, No. 7 ( 2011-04), p. 1690-1701
    Abstract: Bacterial small noncoding RNAs have attracted much interest in recent years as posttranscriptional regulators of genes involved in diverse pathways. Small RNAs (sRNAs) are 50 to 400 nucleotides long and exert their regulatory function by directly base pairing with mRNA targets to alter their stability and/or affect their translation. This base pairing is achieved through a region of about 10 to 25 nucleotides, which may be located at various positions along different sRNAs. By compiling a data set of experimentally determined target-binding regions of sRNAs and systematically analyzing their properties, we reveal that they are both more evolutionarily conserved and more accessible than random regions. We demonstrate the use of these properties for computational identification of sRNA target-binding regions with high specificity and sensitivity. Our results show that these predicted regions are likely to base pair with known targets of an sRNA, suggesting that pointing out these regions in a specific sRNA can help in searching for its targets.
    Type of Medium: Online Resource
    ISSN: 0021-9193 , 1098-5530
    URL: Article
    DOI: 10.1128/JB.01419-10
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2011
    detail.hit.zdb_id: 1481988-0
    SSG: 12
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