Single-Nucleotide Mutation Matrix: A New Model for Predicting the NF-κB DNA Binding Sites

<div><p>In this study, we established a single nucleotide mutation matrix (SNMM) model based on the relative binding affinities of NF-κB p50 homodimer to a wild-type binding site (GGGACTTTCC) and its all single-nucleotide mutants detected with the double-stranded DNA microarray. We evaluated this model by scoring different groups of 10-bp DNA sequences with this model and analyzing the correlations between the scores and the relative binding affinities detected with three wet experiments, including the electrophoresis mobility shift assay (EMSA), the protein-binding microarray (PBM) and the systematic evolution of ligands by exponential enrichment-sequencing (SELEX-Seq). The results revealed that the SNMM scores were strongly correlated with the detected binding affinities. We also scored the DNA sequences with other three models, including the principal coordinate (PC) model, the position weight matrix scoring algorithm (PWMSA) model and the Match model, and analyzed the correlations between the scores and the detected binding affinities. In comparison with these models, the SNMM model achieved reliable results. We finally determined 0.747 as the optimal threshold for predicting the NF-κB DNA-binding sites with the SNMM model. The SNMM model thus provides a new alternative model for scoring the relative binding affinities of NF-κB to the 10-bp DNA sequences and predicting the NF-κB DNA-binding sites.</p></div

The single-nucleotide mutant matrix (SNMM).

a<p>Base of the reference sequence (GGGACTTTCC). 1 to 10, base position in the 10-bp NF-κB DBS.</p

The relative binding affinities of the NF-κB p50 homodimer to four variant sequences.

<p>A, The binding affinities of the NF-κB p50 homodimer to four sequences detected with the radioactive EMSA (R-EMSA), NIRF-EMSA (N-EMSA) and SELEX-Seq (SELEX), respectively, and scored with the SNMM, PWMSA, Match and PC models, respectively. B, The correlation between the EMSA-detected values and the model scores. *, <i>p</i><0.05; no *, <i>p</i>>0.05. P value refers to the confidence interval of Pearson's <i>r</i>.</p

Correlation analysis.

<p>A, Correlations between the EMSA values and the scores of the PC, SNMM, PWMSA, and Match models, respectively. B, Correlations between the PBM <i>z</i> scores and the scores of the PC, SNMM, PWMSA, and Match models, respectively. C, Correlations between the SELEX-Seq values and the scores of the SNMM, PWMSA, Match, and PC models, respectively. Correlation between the SELEX-Seq values and the EMSA values. **, <i>p</i><0.01. P value refers to the confidence interval of Pearson's <i>r</i>. The number under the abscissa refers to the number of values or sequences used in the corresponding correlation analysis.</p

Detection of the DNA-binding affinities of the NF-κB p50 homodimer to four sequences with NIRF-EMSA.

<p>A, A representative image of the NIRF-EMSA detections. B, The quantified signal intensities of the shifted bands (labeled as DNA/p50 complex in Image A). a, GGGGATTCCC; b, GGGATCTCCC; c, GGGATACCCC; d, GGGAGGCCCC.</p

Iron Nanoparticles Significantly Affect the <i>In Vitro</i> and <i>In Vivo</i> Expression of <i>Id</i> Genes

In recent DNA microarray studies, we found that the transcription of the <i>Id3</i> gene was significantly down-regulated in five cell lines (RAW264.7, Hepa1–6, THP-1, HepG2, and HL7702) treated with two doses (50 and 100 μg/mL) of a DMSA-coated magnetite nanoparticle. Given the regulatory roles of <i>Id</i> genes in the cell cycle, growth, and differentiation, we wanted to do more investigations on the effect of the nanoparticle upon the <i>Id</i> genes. This study detected the expression of <i>Id</i> genes in six cell lines (the above cell lines plus HeLa) treated with the nanoparticle at the same doses using quantitative PCR. The results revealed that the expression of <i>Id</i> genes was significantly affected by the nanoparticle in these cell lines. Under each treatment, the <i>Id3</i> gene was significantly (<i>p</i> < 0.01) down-regulated in all cell lines, the <i>Id1</i> gene was significantly down-regulated in all cell lines except the RAW264.7 cells, and the <i>Id2</i> gene was significantly down-regulated in the HepG2, HL7702, and HeLa cells. Because the <i>Id1</i>, <i>Id2</i>, and <i>Id3</i> genes were significantly down-regulated in three liver-derived cell lines (Hepa1–6, HepG2, and HL7702) in both microarray and PCR detections, this study then detected the expression of <i>Id</i> genes in the liver tissues of mice that were intravenously injected with the nanoparticle at two doses (2 and 5 mg/kg body weight). The results revealed that the expression of <i>Id1</i>, <i>Id2</i>, and <i>Id3</i> genes was also significantly down-regulated in the liver tissues under each treatment. Another <i>Id</i> gene, <i>Id4</i>, was also significantly regulated in some cells or liver tissues treated with the nanoparticle. These results reveal that the nanoparticle exerts a significant effect on the <i>in vitro</i> and <i>in vivo</i> expression of <i>Id</i> genes. This study thus provides new insights into the <i>Id</i>-related nanotoxicity of the nanoparticle and the close relationship between the regulation of <i>Id</i> genes and iron

Additional file 10: of Correction to: SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states

Figure S6. Comparison of the distribution of Hind III digestion library reads density and Hind III restriction sites through the whole genome. (DOCX 444 kb

Additional file 3: of SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states

Figure S1. Validation of SALP method. (DOCX 15 kb

Additional file 8: of SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states

Figure S4. Comparison of fold enrichment of two types of GM12878 SALP-seq peaks. (DOCX 187 kb

Characterization of Liaoning Cashmere Goat Transcriptome: Sequencing, <i>De Novo</i> Assembly, Functional Annotation and Comparative Analysis

<div><p>Background</p><p>Liaoning cashmere goat is a famous goat breed for cashmere wool. In order to increase the transcriptome data and accelerate genetic improvement for this breed, we performed <i>de</i><i>novo</i> transcriptome sequencing to generate the first expressed sequence tag dataset for the Liaoning cashmere goat, using next-generation sequencing technology.</p> <p>Results</p><p>Transcriptome sequencing of Liaoning cashmere goat on a Roche 454 platform yielded 804,601 high-quality reads. Clustering and assembly of these reads produced a non-redundant set of 117,854 unigenes, comprising 13,194 isotigs and 104,660 singletons. Based on similarity searches with known proteins, 17,356 unigenes were assigned to 6,700 GO categories, and the terms were summarized into three main GO categories and 59 sub-categories. 3,548 and 46,778 unigenes had significant similarity to existing sequences in the KEGG and COG databases, respectively. Comparative analysis revealed that 42,254 unigenes were aligned to 17,532 different sequences in NCBI non-redundant nucleotide databases. 97,236 (82.51%) unigenes were mapped to the 30 goat chromosomes. 35,551 (30.17%) unigenes were matched to 11,438 reported goat protein-coding genes. The remaining non-matched unigenes were further compared with cattle and human reference genes, 67 putative new goat genes were discovered. Additionally, 2,781 potential simple sequence repeats were initially identified from all unigenes.</p> <p>Conclusion</p><p>The transcriptome of Liaoning cashmere goat was deep sequenced, <i>de</i><i>novo</i> assembled, and annotated, providing abundant data to better understand the Liaoning cashmere goat transcriptome. The potential simple sequence repeats provide a material basis for future genetic linkage and quantitative trait loci analyses.</p> </div