Sequence-specific error profile of Illumina sequencers

We identified the sequence-specific starting positions of consecutive miscalls in the mapping of reads obtained from the Illumina Genome Analyser (GA). Detailed analysis of the miscall pattern indicated that the underlying mechanism involves sequence-specific interference of the base elongation process during sequencing. The two major sequence patterns that trigger this sequence-specific error (SSE) are: (i) inverted repeats and (ii) GGC sequences. We speculate that these sequences favor dephasing by inhibiting single-base elongation, by: (i) folding single-stranded DNA and (ii) altering enzyme preference. This phenomenon is a major cause of sequence coverage variability and of the unfavorable bias observed for population-targeted methods such as RNA-seq and ChIP-seq. Moreover, SSE is a potential cause of false single-nucleotide polymorphism (SNP) calls and also significantly hinders de novo assembly. This article highlights the importance of recognizing SSE and its underlying mechanisms in the hope of enhancing the potential usefulness of the Illumina sequencers

Modeling complex structures in nucleic acids.

University of Minnesota Ph.D. dissertation. April 2012. Major: Chemical Engineering. Advisor: Kevin D. Dorfman. 1 computer file (PDF); ix, 210 pages.Since the discovery of DNA, researchers have been attempting to decode the detailed structure, properties, and abilities of this molecule. At first approximation, DNA can be thought of as a long, regular, double-stranded helix encoding the genomic information of life. However, on closer analysis DNA has been found to take on a wide variety of complex shapes and functions both in vitro and in vivo. DNA can be single-, double-, triple-, and even quadruple-stranded in nature and can bind in both the Watson-Crick conformations and also in a variety of non-canonical con- figurations that add to its inherent flexibility, structure, and activity. Elucidating the varied structures and behaviors of DNA has historically been an experimental endeavor, due in large part to the difficulties in capturing nucleic acid's complex mo- tions and function in a tractable computational model. However, as the applications of DNA expand and computation power increases, simulation models are playing an increasingly important role in DNA understanding and engineering. In this thesis, we simulate short DNA and RNA (less than 100 nucleotides) and examine their complex structures. In particular, we will (i) experimentally evaluate previous DNA coarse grained models for their ability to capture complex nucleic acid structures, and (ii) develop a new model that can better capture both canonical and non-canonical in- teractions and show its utility in the study of several known structures. Further, we will use our understanding of the intricate interactions of short oligonucleotides to unravel a hereto experimentally inaccessible mechanistic pathway for a catalytically active DNA molecule. The model developed and the importance of non-canonical interactions in nucleic acid systems will be useful in the continued understanding and engineering of DNA and RNA molecules for nanotechnology, genetic engineering, and therapeutic applications

Analysis of a DNA simulation model through hairpin melting experiments

We compare the predictions of a two-bead Brownian dynamics simulation model to melting experiments of DNA hairpins with complementary AT or GC stems and noninteracting loops in buffer A. This system emphasizes the role of stacking and hydrogen bonding energies, which are characteristics of DNA, rather than backbone bending, stiffness, and excluded volume interactions, which are generic characteristics of semiflexible polymers. By comparing high throughput data on the open-close transition of various DNA hairpins to the corresponding simulation data, we (1) establish a suitable metric to compare the simulations to experiments, (2) find a conversion between the simulation and experimental temperatures, and (3) point out several limitations of the model, including the lack of G-quartets and cross stacking effects. Our approach and experimental data can be used to validate similar coarse-grained simulation models