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Model-driven generation of artificial yeast promoters

ABSTRACT: Model-driven generation of artificial yeast promoters

PROVIDER: PRJNA558976 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR9911030_1.fastq.gz	Fastqsanger.gz
	SRR9911030_2.fastq.gz	Fastqsanger.gz
	SRR9911040.fastq.gz	Fastqsanger.gz
	SRR9911050_1.fastq.gz	Fastqsanger.gz
	SRR9911050_2.fastq.gz	Fastqsanger.gz

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Model-driven generation of artificial yeast promoters

Project description:Promoters play a central role in controlling gene regulation; however, a small set of promoters is used for most genetic construct design in the yeast Saccharomyces cerevisiae. The ability to generate and utilize models that accurately predict protein expression from promoter sequence may enable rapid generation of novel useful promoters, facilitating synthetic biology efforts in this model organism. We measured the activity of over 675,000 unique sequences in a constitutive promoter library, and over 327,000 sequences in a library of inducible promoters. Training an ensemble of convolutional neural networks jointly on the two datasets enabled very high (R2 > 0.79) predictive accuracies on multiple prediction tasks. We developed model-guided design strategies which yielded large, sequence-diverse sets of novel promoters exhibiting activities similar to current best-in-class sequences. In addition to providing large sets of new promoters, our results show the value of model-guided design as an approach for generating DNA parts.

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Model-driven generation of artificial yeast promoters.

Project description:Promoters play a central role in controlling gene regulation; however, a small set of promoters is used for most genetic construct design in the yeast Saccharomyces cerevisiae. Generating and utilizing models that accurately predict protein expression from promoter sequences would enable rapid generation of useful promoters and facilitate synthetic biology efforts in this model organism. We measure the gene expression activity of over 675,000 sequences in a constitutive promoter library and over 327,000 sequences in an inducible promoter library. Training an ensemble of convolutional neural networks jointly on the two data sets enables very high (R2?>?0.79) predictive accuracies on multiple sequence-activity prediction tasks. We describe model-guided design strategies that yield large, sequence-diverse sets of promoters exhibiting activities higher than those represented in training data and similar to current best-in-class sequences. Our results show the value of model-guided design as an approach for generating useful DNA parts.

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Project description:We identify the cis and trans determinants of nucleosome positioning using a functional evolutionary approach involving S. cerevisiae strains containing large genomic regions from other yeast species. In a foreign species, nucleosome depletion at promoters is maintained over poly(dA:dT) tracts, whereas internucleosome spacing and all other aspects of nucleosome positioning tested are not. Interestingly, the locations of the +1 nucleosome and RNA start sites shift in concert. Strikingly, in a foreign species, nucleosome-depleted regions occur fortuitously in coding regions, and they often act as promoters that are associated with a positioned nucleosome array linked to the length of the transcription unit. nucleosome mapping for 3 strains bearing yeast artificial chromosomes from Kluyveromyces lactis and 2 strains with Debaryomyces hansenii artificial chromosomes in Saccharomyces cerevisiae

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Project description:The core promoter is the regulatory sequence to which RNA polymerase is recruited and where it acts to initiate transcription. Here, we present the first comprehensive study of yeast core promoters, providing massively parallel measurements of core promoter activity and of TSS locations and relative usage for thousands of native and designed sequences. We found core promoter activity to be highly correlated to the activity of the entire promoter, and that sequence variation in different core promoter regions substantially tunes its activity in a predictable way. We also show that location, orientation and flanking bases critically affect TATA element function, that transcription initiation in highly active core promoters is focused within a narrow region, that poly(dA:dT) orientation has functional consequence at the 3' end of promoters, and that orthologous core promoters across yeast species have conserved activities. Our results demonstrate the importance of core promoters in the quantitative study of gene regulation.

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