Positives and negatives of methylated CpG: When the DNA bases cytosine and guanine are next to each other, a methyl group is generally added to the pyrimidine, generating a mCpG dinucleotide. This modification alters DNA structure but can also affect function by inhibiting transcription factor (TF) binding. Yin et al. systematically analyzed the effect of CpG methylation on the binding of 542 human TFs (see the Perspective by Hughes and Lambert). In addition to inhibiting binding of some TFs, they found that mCpGs can promote binding of others, particularly TFs involved in development, such as homeodomain proteins. Science , this issue p. eaaj2239 ; see also p. 489

Uterine leiomyomas, or fibroids, are benign tumors that affect millions of women worldwide and that can cause considerable morbidity. To study the genetic basis of this tumor type, we examined 18 uterine leiomyomas derived from 17 different patients by exome sequencing and identified tumor-specific mutations in the mediator complex subunit 12 (MED12) gene in 10. Through analysis of 207 additional tumors, we determined that MED12 is altered in 70% (159 of 225) of tumors from a total of 80 patients. The Mediator complex is a 26-subunit transcriptional regulator that bridges DNA regulatory sequences to the RNA polymerase II initiation complex. All mutations resided in exon 2, suggesting that aberrant function of this region of MED12 contributes to tumorigenesis.

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The genetic code—the binding specificity of all transfer-RNAs—defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the ∼1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.