A search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequence

The mouse metallothionein II (MT-II) gene is located approximately 6 kilobases upstream of the MT-I gene. A comparison of the sequences of mouse MT-I and MT-II genes (as well as those of other mammals) reveals that the coding regions are highly conserved even at "silent" positions but that the noncoding regions and introns are extremely divergent between primates and rodents. There are four blocks of conserved sequences in the promoters of mouse MT-I, mouse MT-II, and human MT-IIA genes; one includes the TATAAA sequence, and another has been implicated in regulation by heavy metals. Mouse MT-I and MT-II mRNAs are induced to approximately the same extent in vivo in response to cadmium, dexamethasone, or lipopolysaccharide. Mouse MT-I and MT-II genes are regulated by metals but not by glucocorticoids after transfection into HeLa cells.

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Protein Binding to Cis-Motifs in mRNAs Coding Sequence Is Common and Regulates Transcript Stability and the Rate of Translation

Cells ◽

10.3390/cells10112910 ◽

2021 ◽

Vol 10 (11) ◽

pp. 2910

Author(s):

Ewa A. Grzybowska ◽

Maciej Wakula

Keyword(s):

Protein Binding ◽

High Throughput ◽

Mrna Stability ◽

Regulatory Network ◽

Rna Binding ◽

Rna Binding Proteins ◽

Translational Efficiency ◽

Coding Sequence ◽

Transcript Stability ◽

Coding Regions

Protein binding to the non-coding regions of mRNAs is relatively well characterized and its functionality has been described in many examples. New results obtained by high-throughput methods indicate that binding to the coding sequence (CDS) by RNA-binding proteins is also quite common, but the functions thereof are more obscure. As described in this review, CDS binding has a role in the regulation of mRNA stability, but it has also a more intriguing role in the regulation of translational efficiency. Global approaches, which suggest the significance of CDS binding along with specific examples of CDS-binding RBPs and their modes of action, are outlined here, pointing to the existence of a relatively less-known regulatory network controlling mRNA stability and translation on yet another level.

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Estradiol and estrogen receptor-dependent stabilization of a minivitellogenin mRNA lacking 5,100 nucleotides of coding sequence

Molecular and Cellular Biology ◽

10.1128/mcb.10.1.371-376.1990 ◽

1990 ◽

Vol 10 (1) ◽

pp. 371-376

Author(s):

D A Nielsen ◽

D J Shapiro

Keyword(s):

Estrogen Receptor ◽

Receptor Expression ◽

Receptor Complex ◽

Positive Regulation ◽

Expression Plasmid ◽

Coding Sequence ◽

Coding Regions ◽

Culture Cells ◽

Tissue Culture Cells ◽

Transfection Assay

We have developed a transfection assay to investigate the estrogen-mediated stabilization of cytoplasmic vitellogenin mRNA. A minivitellogenin (MV5) gene containing the 5' and 3' untranslated and coding regions but lacking 5,075 nucleotides of internal coding sequence was constructed. Cotransfection of the MV5 plasmid and a Xenopus estrogen receptor expression plasmid into Xenopus liver tissue culture cells yielded a 529-nucleotide MV5 mRNA, which was specifically stabilized by estrogen. MV5 mRNA exhibited the increased stability indicative of positive regulation when the estradiol-estrogen receptor complex was present and was not destabilized by unliganded estrogen receptor. Transfected estrogen receptor, estradiol, and 529 nucleotides of the 5,604-nucleotide vitellogenin B1 mRNA were sufficient for stabilization.

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Regulation, linkage, and sequence of mouse metallothionein I and II genes.

Molecular and Cellular Biology ◽

10.1128/mcb.4.7.1221 ◽

1984 ◽

Vol 4 (7) ◽

pp. 1221-1230 ◽

Cited By ~ 215

Author(s):

P F Searle ◽

B L Davison ◽

G W Stuart ◽

T M Wilkie ◽

G Norstedt ◽

...

Keyword(s):

Heavy Metals ◽

Hela Cells ◽

Conserved Sequences ◽

Noncoding Regions ◽

Coding Regions ◽

Four Blocks ◽

I Gene

The mouse metallothionein II (MT-II) gene is located approximately 6 kilobases upstream of the MT-I gene. A comparison of the sequences of mouse MT-I and MT-II genes (as well as those of other mammals) reveals that the coding regions are highly conserved even at "silent" positions but that the noncoding regions and introns are extremely divergent between primates and rodents. There are four blocks of conserved sequences in the promoters of mouse MT-I, mouse MT-II, and human MT-IIA genes; one includes the TATAAA sequence, and another has been implicated in regulation by heavy metals. Mouse MT-I and MT-II mRNAs are induced to approximately the same extent in vivo in response to cadmium, dexamethasone, or lipopolysaccharide. Mouse MT-I and MT-II genes are regulated by metals but not by glucocorticoids after transfection into HeLa cells.

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Molecular phylogenetics of Acacia subgenera Acacia and Aculeiferum (Fabaceae : Mimosoideae), based on the chloroplast matK coding sequence and flanking trnK intron spacer regions

Australian Systematic Botany ◽

10.1071/sb01035 ◽

2003 ◽

Vol 16 (1) ◽

pp. 27 ◽

Cited By ~ 26

Author(s):

Joseph T. Miller ◽

Randall J. Bayer

Keyword(s):

Sequence Analysis ◽

Molecular Phylogenetics ◽

New World ◽

Coding Region ◽

Coding Sequence ◽

Coding Regions ◽

Close Affinity ◽

Molecular Studies ◽

Cladistic Analyses ◽

Trnk Intron

The genus Acacia is subdivided into the following three subgenera: subg. Acacia, subg. Aculeiferum and the predominantly Australian subg. Phyllodineae. Morphological and molecular studies have suggested that the tribe Acacieae and genus Acacia are artificial and have a close affinity to the tribe Ingeae. Sequence analysis of the chloroplast trnK intron, including the matK coding region and flanking non-coding regions, were undertaken to examine taxon relationships within Acacia subgenera Acacia and Aculeiferum. Subgenus Acacia is monophyletic while subgenus Aculeiferum is paraphyletic. Within the subgenera, major divisions are found based on biogeography, New World versus African–Asian taxa. These data suggest that characters such as inflorescence and prickle and/or stipule type are polymorphic and homoplasious in cladistic analyses within the subgenera.

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A Common Class of Transcripts with 5′-Intron Depletion, Distinct Early Coding Sequence Features, and N1-Methyladenosine Modification

10.1101/057455 ◽

2016 ◽

Author(s):

Can Cenik ◽

Hon Nian Chua ◽

Guramrit Singh ◽

Abdalla Akef ◽

Michael P Snyder ◽

...

Keyword(s):

Start Codon ◽

Exon Junction Complex ◽

Translation Efficiency ◽

Coding Region ◽

Coding Sequence ◽

Rna Sequence ◽

Sequence Features ◽

Coding Regions ◽

Exon Junction ◽

Sequence Elements

AbstractIntrons are found in 5’ untranslated regions (5’UTRs) for 35% of all human transcripts. These 5’UTR introns are not randomly distributed: genes that encode secreted, membrane-bound and mitochondrial proteins are less likely to have them. Curiously, transcripts lacking 5’UTR introns tend to harbor specific RNA sequence elements in their early coding regions. To model and understand the connection between coding-region sequence and 5’UTR intron status, we developed a classifier that can predict 5’UTR intron status with >80% accuracy using only sequence features in the early coding region. Thus, the classifier identifies transcripts with 5’ proximal-intron-minus-like-coding regions (“5IM” transcripts). Unexpectedly, we found that the early coding sequence features defining 5IM transcripts are widespread, appearing in 21% of all human RefSeq transcripts. The 5IM class of transcripts is enriched for non-AUG start codons, more extensive secondary structure both preceding the start codon and near the 5’ cap, greater dependence on eIF4E for translation, and association with ER-proximal ribosomes. 5IM transcripts are bound by the Exon Junction Complex (EJC) at non-canonical 5’ proximal positions. Finally, N1-methyladenosines are specifically enriched in the early coding regions of 5IM transcripts. Taken together, our analyses point to the existence of a distinct 5IM class comprising ∼20% of human transcripts. This class is defined by depletion of 5’ proximal introns, presence of specific RNA sequence features associated with low translation efficiency, N1-methyladenosines in the early coding region, and enrichment for non-canonical binding by the Exon Junction Complex.

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Structural-Statistical Properties of the Flavivirus Genomes

Математическая биология и биоинформатика ◽

10.17537/2017.12.343 ◽

2017 ◽

Vol 12 (2) ◽

pp. 343-353 ◽

Cited By ~ 1

Author(s):

Ж.С. Тюлько ◽

Zh.S. Tyulko

Keyword(s):

Mutation Rate ◽

Statistical Approach ◽

Simple Structure ◽

Statistical Properties ◽

Structural Proteins ◽

Genome Sequences ◽

Coding Sequences ◽

Coding Sequence ◽

Coding Regions ◽

Eukaryotic Genomes

Essential structural-statistical properties of coding regions in the genomes of flaviviruses are investigated on base of the Spectral-statistical approach. Both full-length polyprotein coding sequences and their separated structural segments are analyzed. On the whole, structural-statistical properties of the flavivirus genome sequences are shown to be similar to the properties of 3-regularity and latent triplet profile periodicity revealed earlier in the coding regions of prokaryotic and eukaryotic genomes. However, two-level organization of coding is not occurred in discrete segments coding for structural proteins in the flavivirus genomes and property of sequence homogeneity is manifested in significant part of such the segments. These coding sequence particularities are explained by simple structure and high mutation rate of the flavivirus genomes.

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An improvement of ComiR algorithm for microRNA target prediction by exploiting coding region sequences of mRNAs

BMC Bioinformatics ◽

10.1186/s12859-020-3519-5 ◽

2020 ◽

Vol 21 (S8) ◽

Cited By ~ 1

Author(s):

Giorgio Bertolazzi ◽

Panayiotis V. Benos ◽

Michele Tumminello ◽

Claudia Coronnello

Keyword(s):

Binding Sites ◽

Target Prediction ◽

Prediction Algorithm ◽

Messenger Rnas ◽

Microrna Target ◽

Coding Region ◽

Web Tool ◽

Coding Regions ◽

Microrna Target Prediction ◽

Microrna Targets

Abstract MicroRNA are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR is a web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR was trained with the information regarding binding sites in the 3’utr region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein--a component of the microRNA induced silencing complex. In this work, we tested whether including coding region binding sites in ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3’utr information. On the other hand, we show that 3’utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3’utr and coding regions, should be considered in comprehensive analysis. Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3’utr based one.

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Estradiol and estrogen receptor-dependent stabilization of a minivitellogenin mRNA lacking 5,100 nucleotides of coding sequence.

Molecular and Cellular Biology ◽

10.1128/mcb.10.1.371 ◽

1990 ◽

Vol 10 (1) ◽

pp. 371-376 ◽

Cited By ~ 35

Author(s):

D A Nielsen ◽

D J Shapiro

Keyword(s):

Estrogen Receptor ◽

Receptor Expression ◽

Receptor Complex ◽

Positive Regulation ◽

Expression Plasmid ◽

Coding Sequence ◽

Coding Regions ◽

Culture Cells ◽

Tissue Culture Cells ◽

Transfection Assay

We have developed a transfection assay to investigate the estrogen-mediated stabilization of cytoplasmic vitellogenin mRNA. A minivitellogenin (MV5) gene containing the 5' and 3' untranslated and coding regions but lacking 5,075 nucleotides of internal coding sequence was constructed. Cotransfection of the MV5 plasmid and a Xenopus estrogen receptor expression plasmid into Xenopus liver tissue culture cells yielded a 529-nucleotide MV5 mRNA, which was specifically stabilized by estrogen. MV5 mRNA exhibited the increased stability indicative of positive regulation when the estradiol-estrogen receptor complex was present and was not destabilized by unliganded estrogen receptor. Transfected estrogen receptor, estradiol, and 529 nucleotides of the 5,604-nucleotide vitellogenin B1 mRNA were sufficient for stabilization.

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A Universal Probe Set for Targeted Sequencing of 353 Nuclear Genes from Any Flowering Plant Designed Using k-medoids Clustering

10.1101/361618 ◽

2018 ◽

Cited By ~ 5

Author(s):

Matthew G. Johnson ◽

Lisa Pokorny ◽

Steven Dodsworth ◽

Laura R. Botigue ◽

Robyn S. Cowan ◽

...

Keyword(s):

Flowering Plants ◽

Targeted Sequencing ◽

Probe Design ◽

Sequence Alignments ◽

Coding Sequence ◽

Coding Regions ◽

Phylogenetic Studies ◽

Orthologous Loci ◽

The Cost ◽

Probe Set

AbstractSequencing of target-enriched libraries is an efficient and cost-effective method for obtaining DNA sequence data from hundreds of nuclear loci for phylogeny reconstruction. Much of the cost associated with developing targeted sequencing approaches is preliminary data needed for identifying orthologous loci for probe design. In plants, identifying orthologous loci has proven difficult due to a large number of whole-genome duplication events, especially in the angiosperms (flowering plants). We used multiple sequence alignments from over 600 angiosperms for 353 putatively single-copy protein-coding genes to design a set of targeted sequencing probes for phylogenetic studies of any angiosperm lineage. To maximize the phylogenetic potential of the probes while minimizing the cost of production, we introduce a k-medoids clustering approach to identify the minimum number of sequences necessary to represent each coding sequence in the final probe set. Using this method, five to 15 representative sequences were selected per orthologous locus, representing the sequence diversity of angiosperms more efficiently than if probes were designed using available sequenced genomes alone. To test our approximately 80,000 probes, we hybridized libraries from 42 species spanning all higher-order lineages of angiosperms, with a focus on taxa not present in the sequence alignments used to design the probes. Out of a possible 353 coding sequences, we recovered an average of 283 per species and at least 100 in all species. Differences among taxa in sequence recovery could not be explained by relatedness to the representative taxa selected for probe design, suggesting that there is no phylogenetic bias in the probe set. Our probe set, which targeted 260 kbp of coding sequence, achieved a median recovery of 137 kbp per taxon in coding regions, a maximum recovery of 250 kbp, and an additional median of 212 kbp per taxon in flanking non-coding regions across all species. These results suggest that the Angiosperms353 probe set described here is effective for any group of flowering plants and would be useful for phylogenetic studies from the species level to higher-order lineages, including all angiosperms.

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