Human 5′ UTR design and variant effect prediction from a massively parallel translation assay
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE114002 | GEO | 2018/05/03
REPOSITORIES: GEO
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Project description:Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the translational efficiency of the 5’ untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide- long random 5’ UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on translation of Kozak sequence composition, upstream open reading frames (uORFs) and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the translational efficiency of both a held-out set of the random 5’ UTRs as well as native S. cerevisiae 5’ UTRs. The model additionally was used to computationally evolve highly translating 5’ UTRs. We confirmed experimentally that the great majority of the evolved sequences lead to higher translation rates than the starting sequences, demonstrating the predictive power of this model. The sequences were assayed in the context of a constant promoter and downstream coding sequence. Cell growth was used as a proxy for protein expression. Growth was measured by determining the ratio of sequence counts before and after growth selection.
2017-09-27 | GSE104252 | GEO
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.
2019-12-01 | GSE135464 | GEO
Project description:Post-transcriptional gene regulation controls the amount of a protein produced from an individual mRNA transcript by altering mRNA decay and translation rates. Many putative post-transcriptional cis-regulatory elements have been identified from computational, molecular biology, and biochemical studies studies; however, identifying which sequence elements are sufficient to regulate expression remains challenging. We created a high-throughput, cell-based screen that tested the post-transcriptional regulatory potential for thousands of short sequence elements. Sequences with known effects have the expected performance in this screen, showing this methodology is robust. Hundreds of novel short sequences were identified as being able to alter gene expression, both by increasing and decreasing protein production from the fluorescence reporter, and we validated the effects for fifty of these sequences. Importantly, sequences discovered in this screen are conserved in human 3′UTRs, and furthermore, the sequences can regulate expression in the context of those endogenous 3′UTRs. Hundreds of previously unknown post-transcriptional cis-regulatory elements exist, many of which increase gene expression. These results suggest that each human 3′UTR has many small cis-regulatory elements that interact with RNA binding proteins, and these interactions control the fate of an mRNA transcript.
2016-03-07 | GSE75136 | GEO
Project description:Post-transcriptional gene regulation controls the amount of a protein produced from an individual mRNA transcript by altering mRNA decay and translation rates. Many putative post-transcriptional cis-regulatory elements have been identified from computational, molecular biology, and biochemical studies studies; however, identifying which sequence elements are sufficient to regulate expression remains challenging. We created a high-throughput, cell-based screen that tested the post-transcriptional regulatory potential for thousands of short sequence elements. Sequences with known effects have the expected performance in this screen, showing this methodology is robust. Hundreds of novel short sequences were identified as being able to alter gene expression, both by increasing and decreasing protein production from the fluorescence reporter, and we validated the effects for fifty of these sequences. Importantly, sequences discovered in this screen are conserved in human 3?UTRs, and furthermore, the sequences can regulate expression in the context of those endogenous 3?UTRs. Hundreds of previously unknown post-transcriptional cis-regulatory elements exist, many of which increase gene expression. These results suggest that each human 3?UTR has many small cis-regulatory elements that interact with RNA binding proteins, and these interactions control the fate of an mRNA transcript.
2016-03-07 | GSE75135 | GEO
Project description:Accurate annotations of protein coding regions are essential for understanding how genetic information is translated into biological functions. The recent development of ribosome footprint profiling provides an important new tool for measuring translation. Here we describe riboHMM, a new method that uses ribosome footprint data along with gene expression and sequence information to accurately infer translated sequences. We applied our method to human lymphoblastoid cell lines and identified 7,863 previously unannotated coding sequences, including 445 translated sequences in pseudogenes and 2,442 translated upstream open reading frames. We observed an enrichment of harringtonine-treated ribosome footprints at the inferred initiation sites, validating many of the novel coding sequences. In aggregate, the novel sequences exhibit significant signatures of purifying selection indicative of protein-coding function, suggesting that many of the novel sequences are functional. We observed that nearly 40% of bicistronic transcripts showed significant negative correlation in the levels of translation of their two coding sequences, suggesting a key regulatory role for these novel translated sequences. Despite evidence for their functional importance, the novel peptide sequences were detected by mass spectrometry at a lower rate than predicted based on data from annotated proteins, thus suggesting that many of the novel peptide products may be relatively short-lived. Our work illustrates the value of ribosome profiling for improving coding annotations, and significantly expands the set of known coding regions.
2015-12-25 | GSE75290 | GEO
Project description:We report an efficient, high-throughput method to optimize translation initiation from modified mRNAs. Using direct analysis of ribosome targeting, DART, we identify 5′ untranslated sequences that mediate 250-fold effects on ribosome recruitment, show that incorporation of m1Ψ significantly affects activity, and identify more active 5′ UTRs that surpass current mRNA vaccines. DART is broadly applicable to dissect translation initiation mechanisms of human genes and optimize mRNA regulatory sequences for desired protein outputs
2024-12-19 | GSE256185 | GEO
Project description:We present a ribosome profiling data set from S. cerevisiae as part of a larger study that models the elongation rate along transcripts as a function of local sequence neighborhoods. We then apply this model to design coding sequences that are optimized for translational output.
2017-11-07 | GSE106572 | GEO
Project description:U87MG is a commonly studied grade IV glioma cell line that has been analyzed in at least 1,700 publications over four decades. In order to comprehensively characterize the genome of this cell line and to serve as a model of broad cancer genome sequencing, we have generated greater than 30x genomic sequence coverage using a novel 50-base mate paired strategy with a 1.4kb mean insert library. A total of 1,014,984,286 mate-end and 120,691,623 single-end two-base encoded reads were generated from five slides. All data were aligned using a custom designed tool called BFAST, allowing optimal color space read alignment and accurate identification of DNA variants. The aligned sequence reads and mate pair information identified 35 interchromosomal translocation events, 1,315 structural variations (>100bp), 191,743 small (<21bp) insertions and deletions (indels), and 2,384,470 single nucleotide variations (SNVs). Among these observations, the known homozygous mutation in PTEN was robustly identified, and genes involved in cell adhesion were overrepresented in the mutated gene list. Data were compared to 219,187 heterozygous single nucleotide polymorphisms assayed by Illumina 1M Duo genotyping array to assess accuracy: 93.83% of all SNPs were reliably detected at filtering thresholds that yield greater than 99.99% sequence accuracy. Protein coding sequences were disrupted predominantly in this cancer cell line due to small indels, large deletions and translocations. In total, 512 genes were homozygously mutated, including 154 by SNVs, 178 by small indels, 145 by large microdeletions and 35 by interchromosomal translocations to reveal a highly mutated cell line genome. Of the small homozygously mutated variants, 8 SNVs and 99 indels were novel events not present in dbSNP. These data demonstrate that routine generation of broad cancer genome sequence is possible outside of genome centers. The sequence analysis of U87MG provides an unparalleled level of mutational resolution compared to any cell line to date. Whole genome sequencing of the U87MG brain cancer cell line using the AB SOLiD3 sequencer and genotyping using the Illumina Human1M-Duov3 DNA Analysis BeadChip
2010-01-24 | E-GEOD-19986 | biostudies-arrayexpress
Project description:The stability of mRNAs is regulated by signals within their sequences, but a systematic and predictive understanding of the underlying sequence rules remains elusive. Here, we introduce UTR-Seq, a combination of massively parallel reporter assays and regression models, to survey the dynamics of tens-of-thousands of 3’UTR sequences during early zebrafish embryogenesis. UTR-Seq revealed two temporal degradation programs: a maternally encoded early-onset program and a late-onset program that accelerated degradation after zygotic genome activation. Three signals regulated early-onset rates: stabilizing poly-U and UUAG sequences, and destabilizing GC-rich signals. Three signals explained late-onset degradation: miR-430 seeds, AU-rich sequences and Pumilio recognition sites. Sequence based regression models translated 3’UTRs into their unique decay patterns, and predicted the in vivo impact of sequence signals on mRNA stability. Their application led to the successful design of artificial 3’UTRs that conferred specific mRNA dynamics. UTR-Seq provides a general strategy to uncover the rules of RNA cis-regulation.
2017-12-12 | GSE106677 | GEO
Project description:For the past decade, extensive studies of translation have produced a vast amount of ribosome profiling data, an insightful resource for mining of critical details about the dynamics of translation regulation under various biological contexts. Previously, Rocaglamide A (RocA), an anti-tumor heterotricyclic natural compound, has been shown to selectively inhibit translation initiation of a large group of mRNA species by clamping eukaryotic translation initiation factor 4A (eIF4A) onto poly-purine motifs in the 5’ un-translational regions (5’UTRs). However, re-analysis of the previous ribosome profiling datasets revealed an unexpected shift of the ribosome occupancy pattern during early translation elongation upon RocA treatment in various types of cells, for a specific group of mRNA transcripts without poly-purine motifs over-presented in their 5’UTRs. Such perturbation of the translation elongation dynamics can be attributed to the blockage of translating ribosomes due to the binding of eIF4A to the poly-purine sequence in coding sequences. This new mode of action of RocA, which is complementary to the canonical function inhibiting translation initiation, selectively interfere with the translation of the genes involved in fundamental processes such as ATP synthase, mitochondrial respiratory chain complex, et al. In summary, re-analyses of previous ribosome profiling data has revealed the complete dual modes of RocA in blocking translation and thus underlying the potent anti-tumor effect
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