Unraveling the determinants of microRNA mediated regulation using a massively parallel reporter assay

Abstract

Despite extensive research, the sequence features affecting microRNA-mediated regulation are not well understood, limiting our ability to predict gene expression levels in both native and synthetic sequences. Here we employed a massively parallel reporter assay to investigate the effect of over 14,000 rationally designed 3′ UTR sequences on reporter construct repression. We found that multiple factors, including microRNA identity, hybridization energy, target accessibility, and target multiplicity, can be manipulated to achieve a predictable, up to 57-fold, change in protein repression. Moreover, we predict protein repression and RNA levels with high accuracy (R = 0.84 and R = 0.80, respectively) using only 3′ UTR sequence, as well as the effect of mutation in native 3′ UTRs on protein repression (R = 0.63). Taken together, our results elucidate the effect of different sequence features on miRNA-mediated regulation and demonstrate the predictability of their effect on gene expression with applications in regulatory genomics and synthetic biology.

Overcoming the design, build, test (DBT) bottleneck for synthesis of nonrepetitive protein-RNA binding cassettes for RNA applications

“…Specifically, the field is still lacking computational methods that will enable users to reliably design their system of choice without going through multiple time-consuming DBT cycles before arriving at the desired solution. Recent studies are emerging to tackle this challenge and to devise such methods for diverse RNA-, DNA-and protein-based applications, with varying degrees of success [1][2][3] . Perhaps the best known methods are the Cello algorithm and RBS calculator, which are limited to bacterial chassis 4,5 at the present time.…”

Dissecting splicing decisions and cell-to-cell variability with designed sequence libraries

“…We previously demonstrated that similar approaches are highly accurate and reproducible (Weingarten-Gabbay et al, 2017, Vainberg Slutskin et al, 2018.…”

“…The cloning steps were performed essentially as described previously (Vainberg Slutskin et al, 2018). We used Agilent oligo library synthesis technology to produce a pool of 55,000 different fully designed single-stranded 210-oligomers (Agilent Technologies, Santa Clara, CA), which was provided as a single pool of oligonucleotides (10 pmol).…”

Characterising the genetic basis of immune response variation to identify causal mechanisms underlying disease susceptibility

“…86,87 For instance, dissection of regulatory mechanisms at a 87 nucleotide-long IFNB1 enhancer indicated that 83 substitutions, out the 261 possible, resulted in altered activity in virus-infected cells. 86 Massively parallel assays have also been used in the context of both splicing 88,89 and miRNA-mediated regulation, 90,91 showing, for instance, that up to 16% of splice disrupting variants are located in deep intronic regions. 88 With the development of deep learning frameworks for sequence-based predictions, 92,93 data generated by these assays, will now fuel the construction of predictive models.…”

“…These models will, in turn, allow quantifying the regulatory impact of novel genetic variants on transcriptional activity, 86 alternative splicing, 94 or miRNA-mediated regulation. 91…”