Deep RNA-Seq profile reveals biodiversity, plant-microbe interactions and a large family of NBS-LRR resistance genes in walnut (Juglans regia) tissues.

Deep RNA-Seq profiling, a revolutionary method used for quantifying transcriptional levels, often includes non-specific transcripts from other co-existing organisms in spite of stringent protocols. Using the recently published walnut genome sequence as a filter, we present a broad analysis of the RNA-Seq derived transcriptome profiles obtained from twenty different tissues to extract the biodiversity and possible plant-microbe interactions in the walnut ecosystem in California. Since the residual nature of the transcripts being analyzed does not provide sufficient information to identify the exact strain, inferences made are constrained to the genus level. The presence of the pathogenic oomycete Phytophthora was detected in the root through the presence of a glyceraldehyde-3-phosphate dehydrogenase. Cryptococcus, the causal agent of cryptococcosis, was found in the catkins and vegetative buds, corroborating previous work indicating that the plant surface supported the sexual cycle of this human pathogen. The RNA-Seq profile revealed several species of the endophytic nitrogen fixing Actinobacteria. Another bacterial species implicated in aerobic biodegradation of methyl tert-butyl ether (Methylibium petroleiphilum) is also found in the root. RNA encoding proteins from the pea aphid were found in the leaves and vegetative buds, while a serine protease from mosquito with significant homology to a female reproductive tract protease from Drosophila mojavensis in the vegetative bud suggests egg-laying activities. The comprehensive analysis of RNA-seq data present also unraveled detailed, tissue-specific information of ~400 transcripts encoded by the largest family of resistance (R) genes (NBS-LRR), which possibly rationalizes the resistance of the specific walnut plant to the pathogens detected. Thus, we elucidate the biodiversity and possible plant-microbe interactions in several walnut (Juglans regia) tissues in California using deep RNA-Seq profiling

Contracting edges to destroy a pattern: A complexity study

Given a graph G and an integer k, the objective of the $\Pi$-Contraction problem is to check whether there exists at most k edges in G such that contracting them in G results in a graph satisfying the property $\Pi$. We investigate the problem where $\Pi$ is `H-free' (without any induced copies of H). It is trivial that H-free Contraction is polynomial-time solvable if H is a complete graph of at most two vertices. We prove that, in all other cases, the problem is NP-complete. We then investigate the fixed-parameter tractability of these problems. We prove that whenever H is a tree, except for seven trees, H-free Contraction is W[2]-hard. This result along with the known results leaves behind three unknown cases among trees.Comment: 30 pages, 10 figures, a short version is accepted to FCT 202

The electrostatic profile of consecutive Cβ atoms applied to protein structure quality assessment.

The structure of a protein provides insight into its physiological interactions with other components of the cellular soup. Methods that predict putative structures from sequences typically yield multiple, closely-ranked possibilities. A critical component in the process is the model quality assessing program (MQAP), which selects the best candidate from this pool of structures. Here, we present a novel MQAP based on the physical properties of sidechain atoms. We propose a method for assessing the quality of protein structures based on the electrostatic potential difference (EPD) of Cβ atoms in consecutive residues. We demonstrate that the EPDs of Cβ atoms on consecutive residues provide unique signatures of the amino acid types. The EPD of Cβ atoms are learnt from a set of 1000 non-homologous protein structures with a resolution cuto of 1.6 Å obtained from the PISCES database. Based on the Boltzmann hypothesis that lower energy conformations are proportionately sampled more, and on Annsen's thermodynamic hypothesis that the native structure of a protein is the minimum free energy state, we hypothesize that the deviation of observed EPD values from the mean values obtained in the learning phase is minimized in the native structure. We achieved an average specificity of 0.91, 0.94 and 0.93 on hg_structal, 4state_reduced and ig_structal decoy sets, respectively, taken from the Decoys `R' Us database. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134

IMACULAT - an open access package for the quantitative analysis of chromosome localization in the nucleus

The alteration in the location of the chromosomes within the nucleus upon action of internal or external stimuli has been implicated in altering genome function. The effect of stimuli at a whole genome level is studied by using two-dimensional fluorescence in situ hybridization (FISH) to delineate whole chromosome territories within a cell nucleus, followed by a quantitative analysis of the spatial distribution of the chromosome. However, to the best of our knowledge, open access software capable of quantifying spatial distribution of whole chromosomes within cell nucleus is not available. In the current work, we present a software package that computes localization of whole chromosomes - Image Analysis of Chromosomes for computing localization (IMACULAT). We partition the nucleus into concentric elliptical compartments of equal area and the variance in the quantity of any chromosome in these shells is used to determine its localization in the nucleus. The images are pre-processed to remove the smudges outside the cell boundary. Automation allows high throughput analysis for deriving statistics. Proliferating normal human dermal fibroblasts were subjected to standard a two-dimensional FISH to delineate territories for all human chromosomes. Approximately 100 images from each chromosome were analyzed using IMACULAT. The analysis corroborated that these chromosome territories have non-random gene density based organization within the interphase nuclei of human fibroblasts. The ImageMagick Perl API has been used for pre-processing the images

Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator

Phylogenetic analysis of proteins using multiple sequence alignment (MSA) assumes an underlying evolutionary relationship in these proteins which occasionally remains undetected due to considerable sequence divergence. Structural alignment programs have been developed to unravel such fuzzy relationships. However, none of these structure based methods have used electrostatic properties to discriminate between spatially equivalent residues. We present a methodology for MSA of a set of related proteins with known structures using electrostatic properties as an additional discriminator (STEEP). STEEP first extracts a profile, then generates a multiple structural superimposition providing a consolidated spatial framework for comparing residues and finally emits the MSA. Residues that are aligned differently by including or excluding electrostatic properties can be targeted by directed evolution experiments to transform the enzymatic properties of one protein into another. We have compared STEEP results to those obtained from a MSA program (ClustalW) and a structural alignment method (MUSTANG) for chymotrypsin serine proteases. Subsequently, we used PhyML to generate phylogenetic trees for the serine and metallo-β-lactamase superfamilies from the STEEP generated MSA, and corroborated the accepted relationships in these superfamilies. We have observed that STEEP acts as a functional classifier when electrostatic congruence is used as a discriminator, and thus identifies potential targets for directed evolution experiments. In summary, STEEP is unique among phylogenetic methods for its ability to use electrostatic congruence to specify mutations that might be the source of the functional divergence in a protein family. Based on our results, we also hypothesize that the active site and its close vicinity contains enough information to infer the correct phylogeny for related proteins

On Petri Nets with Hierarchical Special Arcs

We investigate the decidability of termination, reachability, coverability and deadlock-freeness of Petri nets endowed with a hierarchy of places, and with inhibitor arcs, reset arcs and transfer arcs that respect this hierarchy. We also investigate what happens when we have a mix of these special arcs, some of which respect the hierarchy, while others do not. We settle the decidability status of the above four problems for all combinations of hierarchy, inhibitor, reset and transfer arcs, except the termination problem for two combinations. For both these combinations, we show that deciding termination is as hard as deciding the positivity problem on linear recurrence sequences -- a long-standing open problem