Global precedence changes by environment: A systematic review and meta-analysis on effect of perceptual field variables on global-local visual processing.

Perceptual organization and, in particular, visual processing have been debated for many years. The global precedence effect in local-global visual processing, as introduced by David Navon, refers to the condition that global aspects of a scene are processed more rapidly than are local details. This perceptual dynamic is influenced by many factors that can be divided into two major categories: subjective or internal factors (e.g., age, disorder, culture) and the external factors called perceptual field variables (PFVs; e.g., stimulus size, eccentricity, sparsity). The aim of the current study was to identify the latter factors using a meta-analysis followed by a systematic literature review. In accordance of the standard framework suggested by PRISMA, 28 PFVs were observed through a literature search on articles published from 1982 to 2019, among which 10 factors have been qualified to be included in a meta-analysis. Subsequently, the random effects model proposed by Hedges and Olkin was used to estimate pooled effect sizes of PFVs. These effect sizes were used to compare and sort the PFVs on the basis of their intensity. According to Cohen's index, our analyses show that relevance, sparsity, and solidness type are categorized as small effects; visual field, level repetition, spatial frequency, and shape type are categorized as medium effects; and congruency, eccentricity, and size as large effect PFVs on global precedence.

miRNA target recognition using features of suboptimal alignments.

MicroRNAs (miRNAs) are a class of short RNA molecules that regulate gene expression by binding directly to messenger RNAs. Conventional approaches to miRNA target prediction estimate the accessibility of target sites and the strength of the binding miRNA by finding optimums of some energy models, which involves O(n3) computations. Alternatively, we narrow down potential binding sites of miRNAs to suboptimal hits of a pairwise alignment algorithm called Fitting Alignment in O(n2). We invoke a same algorithm, once for all candidate sites to measure the site accessibilities. These features are applied to a binary classifier being learned to predict true associations between miRNAs and target genes. Training the classifier requires the negative samples indicating non-affected genes. The experiments verifying such negative associations have been rarely performed, so we exploit tissue-specific gene expression data to impute the negative associations. The recall rate of our method is above 70% (at precision 85%).

Effect of PITX2 knockdown on transcriptome of primary human trabecular meshwork cell cultures.

PURPOSE: To identify genes whose expressions in primary human trabecular meshwork (TM) cell cultures are affected by the transcription factor pituitary homeobox 2 (PITX2) and to identify genes that may have roles in glaucoma. Known glaucoma causing genes account for disease in a small fraction of patients, and we aimed at identification of other genes that may have subtle and accumulative effects not easily identifiable by a genetic approach. METHODS: Expression profiles derived using microarrays were compared between TM control cells and cells treated with PITX2 siRNAs using three protocols so as to minimize false positive and negative results. The first protocol was based on the commonly used B statistic. The second and third protocols were based on fold change in expression. The second protocol used a threshold of at least 2 fold change in expression, whereas the third protocol used ranking in fold change without setting a threshold. The likelihood of a selected gene being a true positive was considered to correlate with the number of protocols by which it was selected. By considering all genes that were selected by at least one protocol, the likelihood of false negatives was expected to decrease. Effects on a subset of selected genes were verified by real time PCR, western blots, and immunocytochemistry. Effects on ALDH1A1, were further pursued because its protein product, aldehyde dehydrogenase 1 family, member A1, has roles in oxidative stress and because oxidative stress is known to be relevant to the etiology of glaucoma. RESULTS: The expression level of 41 genes was assessed by to be possibly affected by PITX2 knockdown. Twenty one genes were down-regulated and twenty were upregulated. The expression of five genes was assessed to be altered by all three analysis protocols. The five genes were DIRAS3 (DIRAS family, GTP-binding RAS-like 3), CXCL6 (chemokine (C-X-C motif) ligand 6), SAMD5 (sterile alpha motif domain containing 5), CBFB (core-binding factor, beta subunit), and MEIS2 (meis homeobox 2). Real time PCR experiments verified results on a subset of genes tested. Notably, the results were also confirmed in two independent TMs. Effects on CXCL6 and ALDH1A1 were also confirmed by western blots, and effects on ALDH1A1 were further shown by immunocytochemistry. Data consistent with PITX2 involvement in ALDH1A1 mediated response to oxidative stress were presented. CONCLUSIONS: Bioinformatics tools revealed that the genes identified affect functions and pathways relevant to glaucoma. Involvement of PITX2 in expression of some of the genes and in some of the pathways is being reported here for the first time. As many of the genes identified have not been studied vis-à-vis glaucoma, we feel they introduce new candidates for understanding this devastating disease.

Global haplotype partitioning for maximal associated SNP pairs.

BACKGROUND: Global partitioning based on pairwise associations of SNPs has not previously been used to define haplotype blocks within genomes. Here, we define an association index based on LD between SNP pairs. We use the Fisher's exact test to assess the statistical significance of the LD estimator. By this test, each SNP pair is characterized as associated, independent, or not-statistically-significant. We set limits on the maximum acceptable proportion of independent pairs within all blocks and search for the partitioning with maximal proportion of associated SNP pairs. Essentially, this model is reduced to a constrained optimization problem, the solution of which is obtained by iterating a dynamic programming algorithm. RESULTS: In comparison with other methods, our algorithm reports blocks of larger average size. Nevertheless, the haplotype diversity within the blocks is captured by a small number of tagSNPs. Resampling HapMap haplotypes under a block-based model of recombination showed that our algorithm is robust in reproducing the same partitioning for recombinant samples. Our algorithm performed better than previously reported models in a case-control association study aimed at mapping a single locus trait, based on simulation results that were evaluated by a block-based statistical test. Compared to methods of haplotype block partitioning, we performed best on detection of recombination hotspots. CONCLUSION: Our proposed method divides chromosomes into the regions within which allelic associations of SNP pairs are maximized. This approach presents a native design for dimension reduction in genome-wide association studies. Our results show that the pairwise allelic association of SNPs can describe various features of genomic variation, in particular recombination hotspots.

A tale of two symmetrical tails: structural and functional characteristics of palindromes in proteins.

BACKGROUND: It has been previously shown that palindromic sequences are frequently observed in proteins. However, our knowledge about their evolutionary origin and their possible importance is incomplete. RESULTS: In this work, we tried to revisit this relatively neglected phenomenon. Several questions are addressed in this work. (1) It is known that there is a large chance of finding a palindrome in low complexity sequences (i.e. sequences with extreme amino acid usage bias). What is the role of sequence complexity in the evolution of palindromic sequences in proteins? (2) Do palindromes coincide with conserved protein sequences? If yes, what are the functions of these conserved segments? (3) In case of conserved palindromes, is it always the case that the whole conserved pattern is also symmetrical? (4) Do palindromic protein sequences form regular secondary structures? (5) Does sequence similarity of the two "sides" of a palindrome imply structural similarity? For the first question, we showed that the complexity of palindromic peptides is significantly lower than randomly generated palindromes. Therefore, one can say that palindromes occur frequently in low complexity protein segments, without necessarily having a defined function or forming a special structure. Nevertheless, this does not rule out the possibility of finding palindromes which play some roles in protein structure and function. In fact, we found several palindromes that overlap with conserved protein Blocks of different functions. However, in many cases we failed to find any symmetry in the conserved regions of corresponding Blocks. Furthermore, to answer the last two questions, the structural characteristics of palindromes were studied. It is shown that palindromes may have a great propensity to form alpha-helical structures. Finally, we demonstrated that the two sides of a palindrome generally do not show significant structural similarities. CONCLUSION: We suggest that the puzzling abundance of palindromic sequences in proteins is mainly due to their frequent concurrence with low-complexity protein regions, rather than a global role in the protein function. In addition, palindromic sequences show a relatively high tendency to form helices, which might play an important role in the evolution of proteins that contain palindromes. Moreover, reverse similarity in peptides does not necessarily imply significant structural similarity. This observation rules out the importance of palindromes for forming symmetrical structures. Although palindromes frequently overlap with conserved Blocks, we suggest that palindromes overlap with Blocks only by coincidence, rather than being involved with a certain structural fold or protein domain.

Evolution of 'ligand-diffusion chreodes' on protein-surface models: a genetic-algorithm study.

Lattice models have been previously used to model ligand diffusion on protein surfaces. Using such models, it has been shown that the presence of pathways (or 'chreodes') of consecutive residues with certain properties can decrease the number of steps required for the arrival of a ligand at the active site. In this work, we show that, based on a genetic algorithm, ligand-diffusion pathways can evolve on a protein surface, when this surface is selected for shortening the travel length toward the active site. Biological implications of these results are discussed.

Solvent accessibility, residue charge and residue volume, the three ingredients of a robust amino acid substitution matrix.

Cost measure matrices or different amino acid indices have been widely used for studies in many fields of biology. One major criticism of these studies might be based on the unavailability of an unbiased and yet effective amino acid substitution matrix. Throughout this study we have devised a cost measure matrix based on the solvent accessibility, residue charge, and residue volume indices. Performed analyses on this novel substitution matrix (i.e. solvent accessibility charge volume (SCV) matrix) support the uncontaminated nature of this matrix regarding the genetic code. Although highly similar to a number of previously available cost measure matrices, the SCV matrix results in a more significant optimality in the error-buffering capacity of the genetic code when compared to many other amino acid substitution matrices. Besides, a method to compare an SCV-based scoring matrix with a number of widely used matrices has been devised, the results of which highlights the robustness of this matrix in protein family discrimination.