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Biosynthesis and genetic encoding of phosphothreonine through parallel selection and deep sequencing.

ABSTRACT: The phosphorylation of threonine residues in proteins regulates diverse processes in eukaryotic cells, and thousands of threonine phosphorylations have been identified. An understanding of how threonine phosphorylation regulates biological function will be accelerated by general methods to biosynthesize defined phosphoproteins. Here we describe a rapid approach for directly discovering aminoacyl-tRNA synthetase-tRNA pairs that selectively incorporate non-natural amino acids into proteins; our method uses parallel positive selections combined with deep sequencing and statistical analysis and enables the direct, scalable discovery of aminoacyl-tRNA synthetase-tRNA pairs with mutually orthogonal substrate specificity. By combining a method to biosynthesize phosphothreonine in cells with this selection approach, we discover a phosphothreonyl-tRNA synthetase-tRNACUA pair and create an entirely biosynthetic route to incorporating phosphothreonine in proteins. We biosynthesize several phosphoproteins and demonstrate phosphoprotein structure determination and synthetic protein kinase activation.

SUBMITTER: Zhang MS

PROVIDER: S-EPMC5493988 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Biosynthesis and genetic encoding of phosphothreonine through parallel selection and deep sequencing.

Zhang Michael Shaofei MS Brunner Simon F SF Huguenin-Dezot Nicolas N Liang Alexandria D AD Schmied Wolfgang H WH Rogerson Daniel T DT Chin Jason W JW

Nature methods 20170529 7

The phosphorylation of threonine residues in proteins regulates diverse processes in eukaryotic cells, and thousands of threonine phosphorylations have been identified. An understanding of how threonine phosphorylation regulates biological function will be accelerated by general methods to biosynthesize defined phosphoproteins. Here we describe a rapid approach for directly discovering aminoacyl-tRNA synthetase-tRNA pairs that selectively incorporate non-natural amino acids into proteins; our me ...[more]

PMID: 28553966

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Project description:BACKGROUND: Artificial selection has caused rapid evolution in domesticated species. The identification of selection footprints across domesticated genomes can contribute to uncover the genetic basis of phenotypic diversity. METHODOLOGY/MAIN FINDINGS: Genome wide footprints of pig domestication and selection were identified using massive parallel sequencing of pooled reduced representation libraries (RRL) representing ?2% of the genome from wild boar and four domestic pig breeds (Large White, Landrace, Duroc and Pietrain) which have been under strong selection for muscle development, growth, behavior and coat color. Using specifically developed statistical methods that account for DNA pooling, low mean sequencing depth, and sequencing errors, we provide genome-wide estimates of nucleotide diversity and genetic differentiation in pig. Widespread signals suggestive of positive and balancing selection were found and the strongest signals were observed in Pietrain, one of the breeds most intensively selected for muscle development. Most signals were population-specific but affected genomic regions which harbored genes for common biological categories including coat color, brain development, muscle development, growth, metabolism, olfaction and immunity. Genetic differentiation in regions harboring genes related to muscle development and growth was higher between breeds than between a given breed and the wild boar. CONCLUSIONS/SIGNIFICANCE: These results, suggest that although domesticated breeds have experienced similar selective pressures, selection has acted upon different genes. This might reflect the multiple domestication events of European breeds or could be the result of subsequent introgression of Asian alleles. Overall, it was estimated that approximately 7% of the porcine genome has been affected by selection events. This study illustrates that the massive parallel sequencing of genomic pools is a cost-effective approach to identify footprints of selection.

Dataset Information

Biosynthesis and genetic encoding of phosphothreonine through parallel selection and deep sequencing.

Publications

Biosynthesis and genetic encoding of phosphothreonine through parallel selection and deep sequencing.

Similar Datasets

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