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An improved SELEX-Seq strategy for characterizing DNA-binding specificity of transcription factor: NF-κB as an example.

Gu G, Wang T, Yang Y, Xu X, Wang J - PLoS ONE (2013)

Bottom Line: In this study, we introduced an improved EMSA-based SELEX-Seq strategy with several advantages.The reliability of the strategy was demonstrated by performing a successful SELEX-Seq of a well-known transcription factor, NF-κB.Therefore, this study provided a useful SELEX-Seq strategy for characterizing DNA-binding specificities of transcription factors.

View Article: PubMed Central - PubMed

Affiliation: The State Key Laboratory of Bioelectronics, Southeast University, Nanjing, China.

ABSTRACT
SELEX-Seq is now the optimal high-throughput technique for characterizing DNA-binding specificities of transcription factors. In this study, we introduced an improved EMSA-based SELEX-Seq strategy with several advantages. The improvements of this strategy included: (1) using a FAM-labeled probe to track protein-DNA complex in polyacrylamide gel for rapidly recovering the protein-bound dsDNA without relying on traditional radioactive labeling or ethidium bromide staining; (2) monitoring the specificity of SELEX selection by detecting a positive and negative sequence doped into the input DNAs used in each round with PCR amplification; (3) using nested PCR to ensure the specificity of PCR amplification of the selected DNAs after each round; (4) using the nucleotides added at the 5' end of the nested PCR primers as the split barcode to code DNAs from various rounds for multiplexing sequencing samples. The split barcode minimized selection times and thus greatly simplified the current SELEX-Seq procedure. The reliability of the strategy was demonstrated by performing a successful SELEX-Seq of a well-known transcription factor, NF-κB. Therefore, this study provided a useful SELEX-Seq strategy for characterizing DNA-binding specificities of transcription factors.

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Related in: MedlinePlus

Finding motifs with reads from Round 4 by using MEME.Five motifs were extracted for each of five samples containing various numbers of non-overlapping 16-mer reads from Round 4. The top four motifs were displayed above the histogram of their fold enrichments. M1 to M4, Motif 1 to motif 4. FE, fold enrichment. The title of Y-axis of motif logos was “bits” and the labels were 0, 1 and 2. The labels under the motif logos were “1” to “10” from left to right that referred to the positions of nucleotides in a motif.
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pone-0076109-g005: Finding motifs with reads from Round 4 by using MEME.Five motifs were extracted for each of five samples containing various numbers of non-overlapping 16-mer reads from Round 4. The top four motifs were displayed above the histogram of their fold enrichments. M1 to M4, Motif 1 to motif 4. FE, fold enrichment. The title of Y-axis of motif logos was “bits” and the labels were 0, 1 and 2. The labels under the motif logos were “1” to “10” from left to right that referred to the positions of nucleotides in a motif.

Mentions: Due to large reads data, motif analysis was performed with small amount of reads that were randomly sampled from reads of each round. To determine the optimal sample size, five samples containing non-overlapping 1000, 5000, 7500, 10000 and 15000 reads from Round 4 were firstly used to perform de novo motif analysis. Because most previous studies identified NF-κB binding sites as 10-bp sequence [40], five motifs at the length of 10 bp were extracted. The results were shown in Figure 5. The fold enrichment of each motif was also calculated as describe in Materials and Methods. It was found that the motifs and their fold enrichments of the samples containing 7500, 10000 and 15000 reads were similar. The most enriched motifs of these samples were similar to the known κB motif (Table S2 in File S1). Therefore, the samples with 10000 reads were used to perform subsequent de novo motif analysis.


An improved SELEX-Seq strategy for characterizing DNA-binding specificity of transcription factor: NF-κB as an example.

Gu G, Wang T, Yang Y, Xu X, Wang J - PLoS ONE (2013)

Finding motifs with reads from Round 4 by using MEME.Five motifs were extracted for each of five samples containing various numbers of non-overlapping 16-mer reads from Round 4. The top four motifs were displayed above the histogram of their fold enrichments. M1 to M4, Motif 1 to motif 4. FE, fold enrichment. The title of Y-axis of motif logos was “bits” and the labels were 0, 1 and 2. The labels under the motif logos were “1” to “10” from left to right that referred to the positions of nucleotides in a motif.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3794954&req=5

pone-0076109-g005: Finding motifs with reads from Round 4 by using MEME.Five motifs were extracted for each of five samples containing various numbers of non-overlapping 16-mer reads from Round 4. The top four motifs were displayed above the histogram of their fold enrichments. M1 to M4, Motif 1 to motif 4. FE, fold enrichment. The title of Y-axis of motif logos was “bits” and the labels were 0, 1 and 2. The labels under the motif logos were “1” to “10” from left to right that referred to the positions of nucleotides in a motif.
Mentions: Due to large reads data, motif analysis was performed with small amount of reads that were randomly sampled from reads of each round. To determine the optimal sample size, five samples containing non-overlapping 1000, 5000, 7500, 10000 and 15000 reads from Round 4 were firstly used to perform de novo motif analysis. Because most previous studies identified NF-κB binding sites as 10-bp sequence [40], five motifs at the length of 10 bp were extracted. The results were shown in Figure 5. The fold enrichment of each motif was also calculated as describe in Materials and Methods. It was found that the motifs and their fold enrichments of the samples containing 7500, 10000 and 15000 reads were similar. The most enriched motifs of these samples were similar to the known κB motif (Table S2 in File S1). Therefore, the samples with 10000 reads were used to perform subsequent de novo motif analysis.

Bottom Line: In this study, we introduced an improved EMSA-based SELEX-Seq strategy with several advantages.The reliability of the strategy was demonstrated by performing a successful SELEX-Seq of a well-known transcription factor, NF-κB.Therefore, this study provided a useful SELEX-Seq strategy for characterizing DNA-binding specificities of transcription factors.

View Article: PubMed Central - PubMed

Affiliation: The State Key Laboratory of Bioelectronics, Southeast University, Nanjing, China.

ABSTRACT
SELEX-Seq is now the optimal high-throughput technique for characterizing DNA-binding specificities of transcription factors. In this study, we introduced an improved EMSA-based SELEX-Seq strategy with several advantages. The improvements of this strategy included: (1) using a FAM-labeled probe to track protein-DNA complex in polyacrylamide gel for rapidly recovering the protein-bound dsDNA without relying on traditional radioactive labeling or ethidium bromide staining; (2) monitoring the specificity of SELEX selection by detecting a positive and negative sequence doped into the input DNAs used in each round with PCR amplification; (3) using nested PCR to ensure the specificity of PCR amplification of the selected DNAs after each round; (4) using the nucleotides added at the 5' end of the nested PCR primers as the split barcode to code DNAs from various rounds for multiplexing sequencing samples. The split barcode minimized selection times and thus greatly simplified the current SELEX-Seq procedure. The reliability of the strategy was demonstrated by performing a successful SELEX-Seq of a well-known transcription factor, NF-κB. Therefore, this study provided a useful SELEX-Seq strategy for characterizing DNA-binding specificities of transcription factors.

Show MeSH
Related in: MedlinePlus