Relative Position Distributions Research Articles

Analysis on the interactions between the first introns and other introns in mitochondrial ribosomal protein genes.

It is realized that the first intron plays a key role in regulating gene expression, and the interactions between the first introns and other introns must be related to the regulation of gene expression. In this paper, the sequences of mitochondrial ribosomal protein genes were selected as the samples, based on the Smith-Waterman method, the optimal matched segments between the first intron and the reverse complementary sequences of other introns of each gene were obtained, and the characteristics of the optimal matched segments were analyzed. The results showed that the lengths and the ranges of length distributions of the optimal matched segments are increased along with the evolution of eukaryotes. For the distributions of the optimal matched segments with different GC contents, the peak values are decreased along with the evolution of eukaryotes, but the corresponding GC content of the peak values are increased along with the evolution of eukaryotes, it means most introns of higher organisms interact with each other though weak bonds binding. By comparing the lengths and matching rates of optimal matched segments with those of siRNA and miRNA, it is found that some optimal matched segments may be related to non-coding RNA with special biological functions, just like siRNA and miRNA, they may play an important role in the process of gene expression and regulation. For the relative position of the optimal matched segments, the peaks of relative position distributions of optimal matched segments are increased during the evolution of eukaryotes, and the positions of the first two peaks exhibit significant conservatism.

Nanoscale Pattern Extraction from Relative Positions of Sparse 3D Localizations.

Inferring the organization of fluorescently labeled nanosized structures from single molecule localization microscopy (SMLM) data, typically obscured by stochastic noise and background, remains challenging. To overcome this, we developed a method to extract high-resolution ordered features from SMLM data that requires only a low fraction of targets to be localized with high precision. First, experimentally measured localizations are analyzed to produce relative position distributions (RPDs). Next, model RPDs are constructed using hypotheses of how the molecule is organized. Finally, a statistical comparison is used to select the most likely model. This approach allows pattern recognition at sub-1% detection efficiencies for target molecules, in large and heterogeneous samples and in 2D and 3D data sets. As a proof-of-concept, we infer ultrastructure of Nup107 within the nuclear pore, DNA origami structures, and α-actinin-2 within the cardiomyocyte Z-disc and assess the quality of images of centrioles to improve the averaged single-particle reconstruction.

Statistics of loop formation along double helix DNAs

We compute relative position distributions of distant sites along discretized semiflexible polymers, focusing on encounter statistics for pairs of sites along a double-stranded DNA molecule (dsDNA), using a transfer-matrix approach. We generalize the usual semiflexible polymer, considering nonlinear elasticity effects arising from inhomogeneities which either appear at any position via thermal fluctuation, or which occur at specific "quenched" locations. We apply our theory to two problems associated with dsDNA looping. First, we discuss how local flexible defects in double-helix structure facilitate cyclization of short dsDNA molecules. Flexible defects greatly enhance cyclization rate, and strongly modify its dependence on the closure orientational boundary condition. This effect is relevant to free-solution cyclization experiments, and to loop formation in vivo. Second, we present calculations of force dependence of the probability of formation of loops along single dsDNAs which show how the probability of loop formation is suppressed by tension.