In two-dimensional parameter spaces, nonlinear systems producing solutions of a fixed periodicity form islands of a characteristic shape, called "shrimp"-shaped domains (SSDs). In simulations of electronic circuits, SSDs of different periodicities were recently found to be connected along spirals. By means of a hardware realization of the simulations, we provide a first direct proof of the real-world existence of this phenomenon. An improved description establishes a close experiment-simulation correspondence, and a simplified circuit family demonstrates the homoclinic saddle-focus origin of the phenomenon.

We present the software Condition-specific Regulatory Units Prediction (CRUP) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell types and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.

The binding of transcription factors to short recognition sequences plays a pivotal role in controlling the expression of genes. The sequence and shape characteristics of binding sites influence DNA binding specificity and have also been implicated in modulating the activity of transcription factors downstream of binding. To quantitatively assess the transcriptional activity of tens of thousands of designed synthetic sites in parallel, we developed a synthetic version of STARR-seq (synSTARR-seq). We used the approach to systematically analyze how variations in the recognition sequence of the glucocorticoid receptor (GR) affect transcriptional regulation. Our approach resulted in the identification of a novel highly active functional GR binding sequence and revealed that sequence variation both within and flanking GR’s core binding site can modulate GR activity without apparent changes in DNA binding affinity. Notably, we found that the sequence composition of variants with similar activity profiles was highly diverse. In contrast, groups of variants with similar activity profiles showed specific DNA shape characteristics indicating that DNA shape may be a better predictor of activity than DNA sequence. Finally, using single cell experiments with individual enhancer variants, we obtained clues indicating that the architecture of the response element can independently tune expression mean and cell-to cell variability in gene expression (noise). Together, our studies establish synSTARR as a powerful method to systematically study how DNA sequence and shape modulate transcriptional output and noise.

26The binding of transcription factors to short recognition sequences plays a pivotal role in 27 controlling the expression of genes. The sequence and shape characteristics of binding sites 28 influence DNA binding specificity and have also been implicated in modulating the activity 29 of transcription factors downstream of binding. To quantitatively assess the transcriptional 30 activity of dozens of thousands of designed synthetic sites in parallel, we developed a 31 synthetic version of STARR-seq (synSTARR-seq). We used the approach to systematically 32 analyze how variations in the recognition sequence of the glucocorticoid receptor (GR) 33 affect transcriptional regulation. Our approach resulted in the identification of a novel 34 highly active functional GR binding sequence and revealed that sequence variation both 35 within and flanking GR's core binding site can modulate GR activity without apparent 36 changes in DNA binding affinity. Notably, we found that the sequence composition of 37 variants with similar activity profiles was highly diverse. In contrast, groups of variants 38 with similar activity profiles showed distinct DNA shape characteristics indicating that DNA 39 shape may be a better predictor of activity than DNA sequence. Finally, using single cell 40 experiments with individual enhancer variants, we obtained clues indicating that the 41 architecture of the response element can independently tune expression mean and cell-to 42 cell variability in gene expression (noise). Together, our studies establish synSTARR as a 43 powerful method to systematically study how DNA sequence and shape modulate 44 transcriptional output and noise. 45 46 47 48 3 Keywords 49 Enhancers, transcriptional regulation, glucocorticoid receptor, transcriptional noise, DNA 50 shape 51 52 53The interplay between transcription factors (TFs) and genomically encoded cis-54 regulatory elements plays a key role in specifying where and when genes are expressed. In 55 addition, the architecture of cis-regulatory elements influences the expression level of 56 individual genes. For example, transcriptional output can be tuned by varying the number 57 of TF binding sites, either for a given TF or for distinct TFs, present at an enhancer [1, 2]. 58 Moreover, differences in its DNA-binding sites can modulate the magnitude of 59 transcriptional activation, as exemplified by the glucocorticoid receptor (GR), a hormone-60 activated TF [3][4][5]. The sequence differences can reside within the 15 base pair (bp) core GR 61 binding sequence (GBS) consisting of two imperfect 6 bp palindromic half-sites separated 62 by a 3 bp spacer. Moreover, sequences directly flanking the core also modulate GR activity 63 [3]. However, these sequence-induced changes in activity cannot be explained by affinity 64 [3]. Instead, the flanking nucleotides induce structural changes in both DNA and the DNA 65 binding domain of GR, arguing for their role in tuning GR activity [3]. 66 Notably, the expression level of a gene is typically measured for p...

Shrimps are islands of periodicity within a chaotic sea in phase and parameter spaces of dimensions larger than one. Islands of different periodicities have recently been shown to be connected by spirals that emanate from a joint focal point, paving ways to wander around in parameter space without ever crossing the chaotic sea. We discuss the shrimp building and scaling principles as well as the influence of individual system properties. While the emergence of shrimps has abundantly been demonstrated for artificial systems, we discuss here in detail evidence of rich hierarchies of shrimps in experimental systems. We finally pinpoint the importance of shrimps in the field of bioinformatics.