Local genomic features predict the distinct and overlapping binding patterns of the bHLH‐Zip family oncoproteins MITF and MYC‐MAX

Abstract

MITF and MYC are well‐known oncoproteins and members of the basic helix–loop–helix leucine zipper (bHLH‐Zip) family of transcription factors (TFs) recognizing hexamer E‐box motifs. MITF and MYC not only share the core binding motif, but are also the two most highly expressed bHLH‐Zip transcription factors in melanocytes, raising the possibility that they may compete for the same binding sites in select oncogenic targets. Mechanisms determining the distinct and potentially overlapping binding modes of these critical oncoproteins remain uncharacterized. We introduce computational predictive models using local sequence features, including a boosted convolutional decision tree framework, to distinguish MITF versus MYC‐MAX binding sites with up to 80% accuracy genomewide. Select E‐box locations that can be bound by both MITF and MYC‐MAX form a separate class of MITF binding sites characterized by differential sequence content in the flanking region, diminished interaction with SOX10, higher evolutionary conservation, and less tissue‐specific chromatin organization.

MITF—the first 25 years

“…The requirement for the flanking 5 ′ T-3 ′ A may be to restrict binding to many MITF recognition motifs by MYC, which has a preference for sites lacking the T-A flanking sequences, and other bHLH-LZ factors able to recognize similar 6-bp elements as heterodimers with MAX (Fisher et al 1993;Solomon et al 1993). Indeed, recent genome-wide analysis has confirmed that the flanking sequences represent major discriminators between MYC-MAX binding and MITF, although a restricted subset of E-box motifs is able to bind both MYC and MITF (Hejna et al 2018). Collectively, these studies indicate that sequence specificity of MITF means that it has a largely complementary repertoire of targets to MYC (Fig.…”

Tuning Transcription Factor Availability through Acetylation-Mediated Genomic Redistribution

“…It also suppresses senescence ( Giuliano et al., 2010 ). Like other bHLH or bHLH-LZ family members, MITF recognizes 6-bp E-box motifs, with flanking sequences permitting MITF and other E-box-binding factors to discriminate between related target sites ( Aksan and Goding, 1998 , Blackwell and Weintraub, 1990 , Fisher et al., 1993 , Fisher and Goding, 1992 , Hejna et al., 2019 , Solomon et al., 1993 ). Despite the key role of MITF in melanoma progression, surprisingly little is known about how its target gene selectivity is modulated.…”

Boosted Convolutional Decision Trees for Translationally Invariant Pattern Recognition and Transfer Learning

“…These distinct advantages of the BCDT model over the CNN model are particularly important in situations such as protein-DNA interaction prediction where extracting the biologically relevant information from the model is just as important as maximizing prediction accuracy. Along this line, we have recently demonstrated the utility of our method in the context of learning biological sequence features that can help distinguish the in-vivo binding patterns of two important oncogenic transcription factors in the same protein family (Hejna et al, 2019).…”