A distance difference matrix approach to identifying transcription factors that regulate differential gene expression

Novel expression cassettes for increasing apolipoprotein AI transgene expression in vascular endothelial cells

Transduction of endothelial cells (EC) with a vector that expresses apolipoprotein A-I (APOAI) reduces atherosclerosis in arteries of fat-fed rabbits. However, the effects on atherosclerosis are partial and might be enhanced if APOAI expression could be increased. With a goal of developing an expression cassette that generates higher levels of APOAI mRNA in EC, we tested 4 strategies, largely in vitro: addition of 2 types of enhancers, addition of computationally identified EC-specific cis-regulatory modules (CRM), and insertion of the rabbit APOAI gene at the transcription start site (TSS) of sequences cloned from genes that are highly expressed in cultured EC. Addition of a shear stress-responsive enhancer did not increase APOAI expression. Addition of 2 copies of a Mef2c enhancer increased APOAI expression from a moderately active promoter/enhancer but decreased APOAI expression from a highly active promoter/enhancer. Of the 11 CRMs, 3 increased APOAI expression from a moderately active promoter (2-7-fold; P < 0.05); none increased expression from a highly active promoter/enhancer. Insertion of the APOAI gene into the TSS of highly expressed EC genes did not increase expression above levels obtained with a moderately active promoter/enhancer. New strategies are needed to further increase APOAI transgene expression in EC.

Emergence of co-expression in gene regulatory networks

Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the fact that highly coexpressed groups of genes tend to be enriched in genes involved in common functions and biological processes. While gene co-expression is widely assumed to reflect close regulatory proximity, the validity of this assumption remains unclear. Here we use a simple synthetic gene regulatory network (GRN) model and contrast the resulting co-expression structure produced by these networks with their known regulatory architecture and with the co-expression structure measured in available human expression data. Using randomization tests, we found that the levels of co-expression observed in simulated expression data were, just as with empirical data, significantly higher than expected by chance. When examining the source of correlated expression, we found that individual regulators, both in simulated and experimental data, fail, on average, to display correlated expression with their immediate targets. However, highly correlated gene pairs tend to share at least one common regulator, while most gene pairs sharing common regulators do not necessarily display correlated expression. Our results demonstrate that widespread co-expression naturally emerges in regulatory networks, and that it is a reliable and direct indicator of active co-regulation in a given cellular context.

Next-generation AAV vectors—do not judge a virus (only) by its cover

Recombinant adeno-associated viruses (AAV) are under intensive investigation in numerous clinical trials after they have emerged as a highly promising vector for human gene therapy. Best exemplifying their power and potential is the authorization of three gene therapy products based on wild-type AAV serotypes, comprising Glybera (AAV1), Luxturna (AAV2) and, most recently, Zolgensma (AAV9). Nonetheless, it has also become evident that the current AAV vector generation will require improvements in transduction potency, antibody evasion and cell/tissue specificity to allow the use of lower and safer vector doses. To this end, others and we devoted substantial previous research to the implementation and application of key technologies for engineering of next-generation viral capsids in a high-throughput ‘top-down’ or (semi-)rational ‘bottom-up’ approach. Here, we describe a set of recent complementary strategies to enhance features of AAV vectors that act on the level of the recombinant cargo. As examples that illustrate the innovative and synergistic concepts that have been reported lately, we highlight (i) novel synthetic enhancers/promoters that provide an unprecedented degree of AAV tissue specificity, (ii) pioneering genetic circuit designs that harness biological (microRNAs) or physical (light) triggers as regulators of AAV gene expression and (iii) new insights into the role of AAV DNA structures on vector genome stability, integrity and functionality. Combined with ongoing capsid engineering and selection efforts, these and other state-of-the-art innovations and investigations promise to accelerate the arrival of the next generation of AAV vectors and to solidify the unique role of this exciting virus in human gene therapy.

Next-generation muscle-directed gene therapy by in silico vector design

There is an urgent need to develop the next-generation vectors for gene therapy of muscle disorders, given the relatively modest advances in clinical trials. These vectors should express substantially higher levels of the therapeutic transgene, enabling the use of lower and safer vector doses. In the current study, we identify potent muscle-specific transcriptional cis-regulatory modules (CRMs), containing clusters of transcription factor binding sites, using a genome-wide data-mining strategy. These novel muscle-specific CRMs result in a substantial increase in muscle-specific gene transcription (up to 400-fold) when delivered using adeno-associated viral vectors in mice. Significantly higher and sustained human micro-dystrophin and follistatin expression levels are attained than when conventional promoters are used. This results in robust phenotypic correction in dystrophic mice, without triggering apoptosis or evoking an immune response. This multidisciplinary approach has potentially broad implications for augmenting the efficacy and safety of muscle-directed gene therapy.

Adeno-associated viral vectors (AAV) are being developed for gene therapy of skeletal muscle, but it is a challenge to achieve robust gene expression. Here, the authors identify muscle-specific cisregulatory elements that lead to a substantial increase in micro-dystrophin and follistatin expression, resulting in a safe and sustainable rescue of the dystrophic phenotype in mouse models.

Genome-wide computational analysis reveals cardiomyocyte-specific transcriptional Cis-regulatory motifs that enable efficient cardiac gene therapy

Gene therapy is a promising emerging therapeutic modality for the treatment of cardiovascular diseases and hereditary diseases that afflict the heart. Hence, there is a need to develop robust cardiac-specific expression modules that allow for stable expression of the gene of interest in cardiomyocytes. We therefore explored a new approach based on a genome-wide bioinformatics strategy that revealed novel cardiac-specific cis-acting regulatory modules (CS-CRMs). These transcriptional modules contained evolutionary-conserved clusters of putative transcription factor binding sites that correspond to a "molecular signature" associated with robust gene expression in the heart. We then validated these CS-CRMs in vivo using an adeno-associated viral vector serotype 9 that drives a reporter gene from a quintessential cardiac-specific α-myosin heavy chain promoter. Most de novo designed CS-CRMs resulted in a >10-fold increase in cardiac gene expression. The most robust CRMs enhanced cardiac-specific transcription 70- to 100-fold. Expression was sustained and restricted to cardiomyocytes. We then combined the most potent CS-CRM4 with a synthetic heart and muscle-specific promoter (SPc5-12) and obtained a significant 20-fold increase in cardiac gene expression compared to the cytomegalovirus promoter. This study underscores the potential of rational vector design to improve the robustness of cardiac gene therapy.

Liver-specific transcriptional modules identified by genome-wide in silico analysis enable efficient gene therapy in mice and non-human primates

The robustness and safety of liver-directed gene therapy can be substantially improved by enhancing expression of the therapeutic transgene in the liver. To achieve this, we developed a new approach of rational in silico vector design. This approach relies on a genome-wide bio-informatics strategy to identify cis-acting regulatory modules (CRMs) containing evolutionary conserved clusters of transcription factor binding site motifs that determine high tissue-specific gene expression. Incorporation of these CRMs into adeno-associated viral (AAV) and non-viral vectors enhanced gene expression in mice liver 10 to 100-fold, depending on the promoter used. Furthermore, these CRMs resulted in robust and sustained liver-specific expression of coagulation factor IX (FIX), validating their immediate therapeutic and translational relevance. Subsequent translational studies indicated that therapeutic FIX expression levels could be attained reaching 20–35% of normal levels after AAV-based liver-directed gene therapy in cynomolgus macaques. This study underscores the potential of rational vector design using computational approaches to improve their robustness and therefore allows for the use of lower and thus safer vector doses for gene therapy, while maximizing therapeutic efficacy.

Computationally designed liver-specific transcriptional modules and hyperactive factor IX improve hepatic gene therapy

The development of the next-generation gene therapy vectors for hemophilia requires using lower and thus potentially safer vector doses and augmenting their therapeutic efficacy. We have identified hepatocyte-specific transcriptional cis-regulatory modules (CRMs) by using a computational strategy that increased factor IX (FIX) levels 11- to 15-fold. Vector efficacy could be enhanced by combining these hepatocyte-specific CRMs with a synthetic codon-optimized hyperfunctional FIX-R338L Padua transgene. This Padua mutation boosted FIX activity up to sevenfold, with no apparent increase in thrombotic risk. We then validated this combination approach using self-complementary adenoassociated virus serotype 9 (scAAV9) vectors in hemophilia B mice. This resulted in sustained supraphysiologic FIX activity (400%), correction of the bleeding diathesis at clinically relevant, low vector doses (5 × 10(10) vector genomes [vg]/kg) that are considered safe in patients undergoing gene therapy. Moreover, immune tolerance could be induced that precluded induction of inhibitory antibodies to FIX upon immunization with recombinant FIX protein.

Oncogenic ETS fusions deregulate E2F3 target genes in Ewing sarcoma and prostate cancer

Deregulated E2F transcription factor activity occurs in the vast majority of human tumors and has been solidly implicated in disturbances of cell cycle control, proliferation, and apoptosis. Aberrant E2F regulatory activity is often caused by impairment of control through pRB function, but little is known about the interplay of other oncoproteins with E2F. Here we show that ETS transcription factor fusions resulting from disease driving rearrangements in Ewing sarcoma (ES) and prostate cancer (PC) are one such class of oncoproteins. We performed an integrative study of genome-wide DNA-binding and transcription data in EWSR1/FLI1 expressing ES and TMPRSS2/ERG containing PC cells. Supported by promoter activity and mutation analyses, we demonstrate that a large fraction of E2F3 target genes are synergistically coregulated by these aberrant ETS proteins. We propose that the oncogenic effect of ETS fusion oncoproteins is in part mediated by the disruptive effect of the E2F–ETS interaction on cell cycle control. Additionally, a detailed analysis of the regulatory targets of the characteristic EWSR1/FLI1 fusion in ES identifies two functionally distinct gene sets. While synergistic regulation in concert with E2F in the promoter of target genes has a generally activating effect, EWSR1/FLI1 binding independent of E2F3 is predominantly associated with repressed differentiation genes. Thus, EWSR1/FLI1 appears to promote oncogenesis by simultaneously promoting cell proliferation and perturbing differentiation.

Mechanisms and evolution of control logic in prokaryotic transcriptional regulation

A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.

Relationship between gene co-expression and sharing of transcription factor binding sites in Drosophila melanogaster

MOTIVATION

In functional genomics, it is frequently useful to correlate expression levels of genes to identify transcription factor binding sites (TFBS) via the presence of common sequence motifs. The underlying assumption is that co-expressed genes are more likely to contain shared TFBS and, thus, TFBS can be identified computationally. Indeed, gene pairs with a very high expression correlation show a significant excess of shared binding sites in yeast. We have tested this assumption in a more complex organism, Drosophila melanogaster, by using experimentally determined TFBS and microarray expression data. We have also examined the reverse relationship between the expression correlation and the extent of TFBS sharing.

RESULTS

Pairs of genes with shared TFBS show, on average, a higher degree of co-expression than those with no common TFBS in Drosophila. However, the reverse does not hold true: gene pairs with high expression correlations do not share significantly larger numbers of TFBS. Exception to this observation exists when comparing expression of genes from the earliest stages of embryonic development. Interestingly, semantic similarity between gene annotations (Biological Process) is much better associated with TFBS sharing, as compared to the expression correlation. We discuss these results in light of reverse engineering approaches to computationally predict regulatory sequences by using comparative genomics.

Statistical detection of cooperative transcription factors with similarity adjustment

Motivation: Statistical assessment of cis-regulatory modules (CRMs) is a crucial task in computational biology. Usually, one concludes from exceptional co-occurrences of DNA motifs that the corresponding transcription factors (TFs) are cooperative. However, similar DNA motifs tend to co-occur in random sequences due to high probability of overlapping occurrences. Therefore, it is important to consider similarity of DNA motifs in the statistical assessment.

Results: Based on previous work, we propose to adjust the window size for co-occurrence detection. Using the derived approximation, one obtains different window sizes for different sets of DNA motifs depending on their similarities. This ensures that the probability of co-occurrences in random sequences are equal. Applying the approach to selected similar and dissimilar DNA motifs from human TFs shows the necessity of adjustment and confirms the accuracy of the approximation by comparison to simulated data. Furthermore, it becomes clear that approaches ignoring similarities strongly underestimate P-values for cooperativity of TFs with similar DNA motifs. In addition, the approach is extended to deal with overlapping windows. We derive Chen–Stein error bounds for the approximation. Comparing the error bounds for similar and dissimilar DNA motifs shows that the approximation for similar DNA motifs yields large bounds. Hence, one has to be careful using overlapping windows. Based on the error bounds, one can precompute the approximation errors and select an appropriate overlap scheme before running the analysis.

Availability: Software to perform the calculation for pairs of position frequency matrices (PFMs) is available at http://mosta.molgen.mpg.de as well as C++ source code for downloading.

Contact:utz.pape@molgen.mpg.de