Tbx20 regulates a genetic program essential to adult mouse cardiomyocyte function.

Human mutations in or variants of TBX20 are associated with congenital heart disease, cardiomyopathy, and arrhythmias. To investigate whether cardiac disease in patients with these conditions results from an embryonic or ongoing requirement for Tbx20 in myocardium, we ablated Tbx20 specifically in adult cardiomyocytes in mice. This ablation resulted in the onset of severe cardiomyopathy accompanied by arrhythmias, with death ensuing within 1 to 2 weeks of Tbx20 ablation. Accounting for this dramatic phenotype, we identified molecular signatures that posit Tbx20 as a central integrator of a genetic program that maintains cardiomyocyte function in the adult heart. Expression of a number of genes encoding critical transcription factors, ion channels, and cytoskeletal/myofibrillar proteins was downregulated consequent to loss of Tbx20. Genome-wide ChIP analysis of Tbx20-binding regions in the adult heart revealed that many of these genes were direct downstream targets of Tbx20 and uncovered a previously undescribed DNA-binding site for Tbx20. Bioinformatics and in vivo functional analyses revealed a cohort of transcription factors that, working with Tbx20, integrated multiple environmental signals to maintain ion channel gene expression in the adult heart. Our data provide insight into the mechanisms by which mutations in TBX20 cause adult heart disease in humans.

Homotypic clusters of transcription factor binding sites are a key component of human promoters and enhancers.

Clustering of multiple transcription factor binding sites (TFBSs) for the same transcription factor (TF) is a common feature of cis-regulatory modules in invertebrate animals, but the occurrence of such homotypic clusters of TFBSs (HCTs) in the human genome has remained largely unknown. To explore whether HCTs are also common in human and other vertebrates, we used known binding motifs for vertebrate TFs and a hidden Markov model-based approach to detect HCTs in the human, mouse, chicken, and fugu genomes, and examined their association with cis-regulatory modules. We found that evolutionarily conserved HCTs occupy nearly 2% of the human genome, with experimental evidence for individual TFs supporting their binding to predicted HCTs. More than half of the promoters of human genes contain HCTs, with a distribution around the transcription start site in agreement with the experimental data from the ENCODE project. In addition, almost half of the 487 experimentally validated developmental enhancers contain them as well--a number more than 25-fold larger than expected by chance. We also found evidence of negative selection acting on TFBSs within HCTs, as the conservation of TFBSs is stronger than the conservation of sequences separating them. The important role of HCTs as components of developmental enhancers is additionally supported by a strong correlation between HCTs and the binding of the enhancer-associated coactivator protein Ep300 (also known as p300). Experimental validation of HCT-containing elements in both zebrafish and mouse suggest that HCTs could be used to predict both the presence of enhancers and their tissue specificity, and are thus a feature that can be effectively used in deciphering the gene regulatory code. In conclusion, our results indicate that HCTs are a pervasive feature of human cis-regulatory modules and suggest that they play an important role in gene regulation in the human and other vertebrate genomes.

Genome-wide discovery of human heart enhancers.

The various organogenic programs deployed during embryonic development rely on the precise expression of a multitude of genes in time and space. Identifying the cis-regulatory elements responsible for this tightly orchestrated regulation of gene expression is an essential step in understanding the genetic pathways involved in development. We describe a strategy to systematically identify tissue-specific cis-regulatory elements that share combinations of sequence motifs. Using heart development as an experimental framework, we employed a combination of Gibbs sampling and linear regression to build a classifier that identifies heart enhancers based on the presence and/or absence of various sequence features, including known and putative transcription factor (TF) binding specificities. In distinguishing heart enhancers from a large pool of random noncoding sequences, the performance of our classifier is vastly superior to four commonly used methods, with an accuracy reaching 92% in cross-validation. Furthermore, most of the binding specificities learned by our method resemble the specificities of TFs widely recognized as key players in heart development and differentiation, such as SRF, MEF2, ETS1, SMAD, and GATA. Using our classifier as a predictor, a genome-wide scan identified over 40,000 novel human heart enhancers. Although the classifier used no gene expression information, these novel enhancers are strongly associated with genes expressed in the heart. Finally, in vivo tests of our predictions in mouse and zebrafish achieved a validation rate of 62%, significantly higher than what is expected by chance. These results support the existence of underlying cis-regulatory codes dictating tissue-specific transcription in mammalian genomes and validate our enhancer classifier strategy as a method to uncover these regulatory codes.