Dataset Information

Trinucleotide Base Pair Stacking Free Energy for Understanding TF-DNA Recognition and the Functions of SNPs.

ABSTRACT: Single nucleotide polymorphisms (SNPs) affect base pair stacking, which is the primary factor for maintaining the stability of DNA. However, the mechanism of how SNPs lead to phenotype variations is still unclear. In this work, we connected SNPs and base pair stacking by a 3-mer base pair stacking free energy matrix. The SNPs with large base pair stacking free energy differences led to phenotype variations. A molecular dynamics (MD) simulation was then applied. Our results showed that base pair stacking played an important role in the transcription factor (TF)-DNA interaction. Changes in DNA structure mainly originate from TF-DNA interactions, and with the increased base pair stacking free energy, the structure of DNA approaches its free type, although its binding affinity was increased by the SNP. In addition, quantitative models using base pair stacking features revealed that base pair stacking can be used to predict TF binding specificity. As such, our work combined knowledge from bioinformatics and structural biology and provided a new understanding of the relationship between SNPs and phenotype variations. The 3-mer base pair stacking free energy matrix is useful in high-throughput screening of SNPs and predicting TF-DNA binding affinity.

SUBMITTER: Li G

PROVIDER: S-EPMC6345724 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Trinucleotide Base Pair Stacking Free Energy for Understanding TF-DNA Recognition and the Functions of SNPs.

Li Gen G Quan Yuan Y Wang Xiaocong X Liu Rong R Bie Lihua L Gao Jun J Zhang Hong-Yu HY

Frontiers in chemistry 20190118

Single nucleotide polymorphisms (SNPs) affect base pair stacking, which is the primary factor for maintaining the stability of DNA. However, the mechanism of how SNPs lead to phenotype variations is still unclear. In this work, we connected SNPs and base pair stacking by a 3-mer base pair stacking free energy matrix. The SNPs with large base pair stacking free energy differences led to phenotype variations. A molecular dynamics (MD) simulation was then applied. Our results showed that base pair ...[more]

PMID: 30713839

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Project description:Until now, it has been reasonably assumed that specific base-pair recognition is the only mechanism controlling the specificity of transcription factor (TF)M-bM-^HM-^RDNA binding. Contrary to this assumption, here we show that nonspecific DNA sequences possessing certain repeat symmetries, when present outside of specific TF binding sites (TFBSs), statistically control TFM-bM-^HM-^RDNA binding preferences. We used high-throughput proteinM-bM-^HM-^RDNA binding assays to measure the binding levels and free energies of binding for several human TFs to tens of thousands of short DNA sequences with varying re- peat symmetries. Based on statistical mechanics modeling, we iden- tify a new proteinM-bM-^HM-^RDNA binding mechanism induced by DNA se- quence symmetry in the absence of specific base-pair recognition, and experimentally demonstrate that this mechanism indeed gov- erns proteinM-bM-^HM-^RDNA binding preferences. Four custom protein binding microarray (PBM) experiments of human transcription factors were performed. Briefly, the PBMs involved binding his-tagged transcription factors c-Myc, Max, and Mad1(Mxd1) to double-stranded 180K Agilent microarrays in order to determine their binding specificity for GTCACGTGAC DNA binding sites flanked by repetitive DNA elements with different symmetries and correlation length scales. Briefly, we represent three categories of 36-bp sequences: 1) 28800 probes centered at a GTCACGTGAC site and flanked by repetitive elements (probe names starting with Ariel_); 2) Unbound probes (or negative controls); and 3) Bound probes, which correspond to randomly selected genomic regions bound in vivo by c-Myc, Max, or Mad2 (ChIP-seq P < 10^(-10) in HeLaS3 or K562 celld (ENCODE)), which contain at least two consecutive 8-mers with universal PBM E-score > 0.4 (Munteanu and Gordan, LNCS 2013). Each DNA sequence represented on the array is present in 6 replicate spots. We report the gcPBM signal intensity for each spot (raw files) as well as the median intensity over the 6 replicate spots (normalized data). The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).

Dataset Information

Trinucleotide Base Pair Stacking Free Energy for Understanding TF-DNA Recognition and the Functions of SNPs.

Publications

Trinucleotide Base Pair Stacking Free Energy for Understanding TF-DNA Recognition and the Functions of SNPs.

Similar Datasets

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