Determining DNA Global Structure and DNA Bending by Application of NMR Residual Dipolar Couplings

The local structure of nucleic acids can be determined from traditional solution NMR techniques, but it is usually not possible to uniquely define the global conformation of DNA or RNA double helices. This results from the short-range nature of the NOE-distance and torsion angle constraints used in generating the solution structures. However, new alignment techniques make it possible to readily measure residual dipolar couplings, which provide information on the relative orientation of individual bond vectors in the molecule. To determine the effects of incorporating dipolar couplings in the structure determinations of nucleic acids, molecular dynamics calculations were performed with simulated constraints derived from two DNA duplex target molecules. Refinements that included NOE, torsion angle, and dipolar coupling constraints were compared to refinements without dipolar couplings. These results show that dipolar couplings significantly improved the local structure while also dramatically improving the global structure of DNA duplexes. The model simulations also illustrate that molecular dynamics calculations induce changes in the local structure before the global structure, which can have important implications for refinements with dipolar coupling constraints. Results are presented that show that the inclusion of dipolar coupling constraints makes it possible to accurately and precisely reproduce the overall helical bend in a DNA duplex. The implications of including dipolar coupling constraints in defining DNA global structure and DNA bending in solution will be discussed

Comparison of the Global Structure and Dynamics of Native and Unmodified tRNA^val^†

The effects of post-transcriptional modifications on the structure and dynamics of Escherichia coli tRNAval were studied by NMR spectroscopy. NMR chemical shift data and residual dipolar couplings were used to show that the local secondary and tertiary structures are very similar in native and unmodified tRNAval. Rigid body restrained molecular dynamics calculations showed that the global structure of tRNA is unchanged by the post-transcriptional modifications. Deuterium exchange NMR experiments were used to probe the dynamics and flexibility of native and unmodified tRNAval. A similar set of slowly exchanging (t1/2 > 3 min) imino protons were observed in both tRNAs, but the rates of exchange for the slowest exchanging imino protons were ∼20 times faster in unmodified than in native tRNA. These results demonstrate that the dynamics and flexibility of tRNAval, but not the local or global structure, are significantly affected by post-transcriptional modifications

Effect of shRNA fold representation on reproducibility of a HEK293T viability screen using microarray analysis.

<p>Viability screens in HEK293T cells were performed using an average shRNA fold representation of either 100 (S100) or 500 (S500) at transduction and the change of the relative abundance of shRNA in T₁ compared to T₀ was analyzed by competitive microarray hybridizations. Scatter plot of log₁₀(T₁/T₀) of the biological replicates of the S100 (A) and S500 (B) screens are shown with Pearson correlation values indicated in the corner of each plot. Probes were filtered to remove those which did not pass T₀ signal>two-fold median background. Primary hits (probes that passed fold change criteria of (T₁/T₀) greater than two and FDR rate of ≤0.05 in both screening (biological) replicates are depicted in red. Signal (log₂Mean Signal) for S100 (C) and S500 (D) screens are plotted as a function of log ratio (log₂(T₁/T₀)). Primary hits are color coded with hits identified in both S100 and S500 screens (red), hits identified in the S100 screen only (blue) and hits identified in the S500 screen only (green). The complete data set is presented in the small insert.</p

PCR template amount and cycle number affect screen technical data reproducibility.

<p>A. Scatter plots of log₁₀(T₁/T₀) of technical PCR replicates. T₁ sample was generated from gDNA isolated from HeLa cells transduced with a pooled library of 10 000 lentiviral shRNAs with an average shRNA representation of 100-fold and cultured under puromycin selection. T₀ reference sample was generated from a pool of plasmids used to create the lentiviral library. Barcode sequences were PCR amplified in technical duplicates for 25 and 30 cycles from the gDNA or the plasmid pool with input DNA corresponding to 50 and 150 template copies per shRNA. Analysis of shRNA abundance in T₁ samples compared to T₀ samples was performed using competitive microarray hybridization. Pearson correlation values for each graph are indicated in the corner of each scatter plot. B. Graphical representation of the Pearson correlation values as a function of template copies per shRNA and number of PCR cycles.</p

Optimized PCR Conditions and Increased shRNA Fold Representation Improve Reproducibility of Pooled shRNA Screens

<div><p>RNAi screening using pooled shRNA libraries is a valuable tool for identifying genetic regulators of biological processes. However, for a successful pooled shRNA screen, it is imperative to thoroughly optimize experimental conditions to obtain reproducible data. Here we performed viability screens with a library of ∼10 000 shRNAs at two different fold representations (100- and 500-fold at transduction) and report the reproducibility of shRNA abundance changes between screening replicates determined by microarray and next generation sequencing analyses. We show that the technical reproducibility between PCR replicates from a pooled screen can be drastically improved by ensuring that PCR amplification steps are kept within the exponential phase and by using an amount of genomic DNA input in the reaction that maintains the average template copies per shRNA used during library transduction. Using these optimized PCR conditions, we then show that higher reproducibility of biological replicates is obtained by both microarray and next generation sequencing when screening with higher average shRNA fold representation. shRNAs that change abundance reproducibly in biological replicates (primary hits) are identified from screens performed with both 100- and 500-fold shRNA representation, however a higher percentage of primary hit overlap between screening replicates is obtained from 500-fold shRNA representation screens. While strong hits with larger changes in relative abundance were generally identified in both screens, hits with smaller changes were identified only in the screens performed with the higher shRNA fold representation at transduction.</p> </div

Hit reproducibility between experiments.

1<p>Microarray experiment where two technical replicates were combined for each biological replicate in Rosetta Resolver to identify hits (Fold change >2, p≤0.05).</p>2<p>Microarray experiment where two technical and two biological replicates (A & B) were combined for either S100 screen with 100 copies per shRNA in PCR or S500 screen with 500 copies per shRNA in PCR using Rosetta Resolver to identify hits (Fold change >2, p≤0.05).</p>3<p>Next generation experiment where one biological replicate (no technical replicates) was analyzed using DESeq to identify hits (Fold change >2, p≤0.05).</p>4<p>Next generation experiment where two biological replicates (A & B) were combined for either S100 screen with 100 copies per shRNA or S500 screen with 500 copies per shRNA using DESeq to identify hits analyzed using DESeq to identify hits (Fold change >2, p≤0.05).</p>5<p>Next generation experiment where two biological replicates (A & B) were combined for either S100 screen with 100 copies per shRNA or S500 screen with 500 copies per shRNA using DESeq to identify hits analyzed using DESeq to identify hits (Fold change >2, p≤0.05). For comparison, hits were filtered to only include hits that were detectable on the microarray.</p

Effect of fold representation of shRNA at transduction on HEK293T viability screen reproducibility using NGS analysis.

<p>Viability screens performed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042341#pone-0042341-g003" target="_blank">Figure 3</a> analyzed by NGS. Scatter plot of log₁₀(T₁/T₀) of the biological replicates of the S100 (A) and S500 (B) screens are shown with Pearson correlation values indicated in the corner of each plot. Primary hits (shRNA that passed fold change criteria of (T₁/T₀) greater than two and FDR rate of ≤0.05 in both screening (biological) replicates) are depicted in red. Signal (log₂Mean Counts) for S100 (C) and S500 (D) screens are plotted as a function of log ratio (log ₂(T₁/T₀)). Primary hits are color coded with hits identified in both S100 and S500 screens (red), hits identified in the S100 screen only (blue) and hits identified in the S500 screen only (green). The complete data set is presented in the small insert.</p

Identification of the exponential phase during PCR amplification of barcode sequences.

<p>A. Schematic of the strategy used to identify the transition point from exponential to linear PCR amplification. gDNA isolated from HEK293T cells transduced with the pooled shRNA library were amplified in replicate PCR reactions. A replicate reaction was stopped at each cycle from 15 to 27 cycles. Subsequently, PCR products were used as templates for SYBR qPCR reactions using nested primers targeting a common sequence (outside of the barcode region) to examine the ΔC_q between cycles. B. Difference of C_q obtained in the qPCR on diluted amplicons from every cycle of the Phusion HS II polymerase PCR reaction (C_qN+1−C_qN) as a function of the Phusion PCR cycle number (N). C. Gel analysis of the PCR product generated from amplification cycles 22 to 25. Sizes of DNA bands in DNA marker (lane M) are indicated on the left.</p