Dataset Information

Dcp2 Decaps m2,2,7GpppN-capped RNAs, and its activity is sequence and context dependent.

ABSTRACT: Hydrolysis of the mRNA cap plays a pivotal role in initiating and completing mRNA turnover. In nematodes, mRNA metabolism and cap-interacting proteins must deal with two populations of mRNAs, spliced leader trans-spliced mRNAs with a trimethylguanosine cap and non-trans-spliced mRNAs with a monomethylguanosine cap. We describe here the characterization of nematode Dcp1 and Dcp2 proteins. Dcp1 was inactive in vitro on both free cap and capped RNA and did not significantly enhance Dcp2 activity. Nematode Dcp2 is an RNA-decapping protein that does not bind cap and is not inhibited by cap analogs but is effectively inhibited by competing RNA irrespective of RNA sequence and cap. Nematode Dcp2 activity is influenced by both 5' end sequence and its context. The trans-spliced leader sequence on mRNAs reduces Dcp2 activity approximately 10-fold, suggesting that 5'-to-3' turnover of trans-spliced RNAs may be regulated. Nematode Dcp2 decaps both m(7)GpppG- and m(2,2,7)GpppG-capped RNAs. Surprisingly, both budding yeast and human Dcp2 are also active on m(2,2,7)GpppG-capped RNAs. Overall, the data suggest that Dcp2 activity can be influenced by both sequence and context and that Dcp2 may contribute to gene regulation in multiple RNA pathways, including monomethyl- and trimethylguanosine-capped RNAs.

SUBMITTER: Cohen LS

PROVIDER: S-EPMC1265788 | biostudies-literature | 2005 Oct

REPOSITORIES: biostudies-literature

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Dcp2 Decaps m2,2,7GpppN-capped RNAs, and its activity is sequence and context dependent.

Cohen Leah S LS Mikhli Claudette C Jiao Xinfu X Kiledjian Megerditch M Kunkel Glenna G Davis Richard E RE

Molecular and cellular biology 20051001 20

Hydrolysis of the mRNA cap plays a pivotal role in initiating and completing mRNA turnover. In nematodes, mRNA metabolism and cap-interacting proteins must deal with two populations of mRNAs, spliced leader trans-spliced mRNAs with a trimethylguanosine cap and non-trans-spliced mRNAs with a monomethylguanosine cap. We describe here the characterization of nematode Dcp1 and Dcp2 proteins. Dcp1 was inactive in vitro on both free cap and capped RNA and did not significantly enhance Dcp2 activity. N ...[more]

PMID: 16199859

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Project description:One way to better understand the structure in DNA is by learning to predict the sequence. Here, we trained a model to predict the missing base at any given position, given its left and right flanking contexts. Our best-performing model was a neural network that obtained an accuracy close to 54% on the human genome, which is 2% points better than modelling the data using a Markov model. In likelihood-ratio tests, the neural network performed significantly better than any of the alternative models by a large margin. We report on where the accuracy was obtained, first observing that the performance appeared to be uniform over the chromosomes. The models performed best in repetitive sequences, as expected, although their performance far from random in the more difficult coding sections, the proportions being ~70:40%. We further explored the sources of the accuracy, Fourier transforming the predictions revealed weak but clear periodic signals. In the human genome the characteristic periods hinted at connections to nucleosome positioning. We found similar periodic signals in GC/AT content in the human genome, which to the best of our knowledge have not been reported before. On other large genomes similarly high accuracy was found, while lower predictive accuracy was observed on smaller genomes. Only in the mouse genome did we see periodic signals in the same range as in the human genome, though weaker and of a different type. This indicates that the sources of these signals are other or more than nucleosome arrangement. Interestingly, applying a model trained on the mouse genome to the human genome resulted in a performance far below that of the human model, except in the difficult coding regions. Despite the clear outcomes of the likelihood-ratio tests, there is currently a limited superiority of the neural network methods over the Markov model. We expect, however, that there is great potential for better modelling DNA using different neural network architectures.

Dataset Information

Dcp2 Decaps m2,2,7GpppN-capped RNAs, and its activity is sequence and context dependent.

Publications

Dcp2 Decaps m2,2,7GpppN-capped RNAs, and its activity is sequence and context dependent.

Similar Datasets

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