SMiLE-seq: Selective Microfluidics-based Ligand Enrichment followed by sequencing
Selective Microfluidics-based Ligand Enrichment followed by sequencing (SMiLE-seq) is a rapid, semi-automated method aimed at resolving the DNA binding specificities of full-length transcription factors (TFs). The core of SMiLE-seq is a cross talk-devoid microfluidic platform that performs selection of DNA that is specifically bound to TFs from a pool of randomized DNA. Coupled to high-throughput sequencing, this platform allows the characterization of TF DNA binding preferences at an unprecedented resolution in just a single day. Unlike other, already established in vitro technologies that also aim to determine TF binding specificities, SMiLE-seq operates at micro scale and requires minute amounts of biological material. Moreover, it produces specificity models that characterize even low-affinity and transient molecular interactions and that have equal to superior predictive power than previously reported motifs. Finally, SMiLE-seq enables motif detection for monomers, homodimers, as well as heterodimers. SMiLE-seq should therefore prove highly valuable in deriving unbiased quantitative specificity models for single and dimeric, full-length TFs.
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Posted 17 Jan, 2017
SMiLE-seq: Selective Microfluidics-based Ligand Enrichment followed by sequencing
Posted 17 Jan, 2017
Selective Microfluidics-based Ligand Enrichment followed by sequencing (SMiLE-seq) is a rapid, semi-automated method aimed at resolving the DNA binding specificities of full-length transcription factors (TFs). The core of SMiLE-seq is a cross talk-devoid microfluidic platform that performs selection of DNA that is specifically bound to TFs from a pool of randomized DNA. Coupled to high-throughput sequencing, this platform allows the characterization of TF DNA binding preferences at an unprecedented resolution in just a single day. Unlike other, already established in vitro technologies that also aim to determine TF binding specificities, SMiLE-seq operates at micro scale and requires minute amounts of biological material. Moreover, it produces specificity models that characterize even low-affinity and transient molecular interactions and that have equal to superior predictive power than previously reported motifs. Finally, SMiLE-seq enables motif detection for monomers, homodimers, as well as heterodimers. SMiLE-seq should therefore prove highly valuable in deriving unbiased quantitative specificity models for single and dimeric, full-length TFs.
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