Kalign – an accurate and fast multiple sequence alignment algorithm

Background  

The alignment of multiple protein sequences is a fundamental step in the analysis of biological data. It has traditionally been applied to analyzing protein families for conserved motifs, phylogeny, structural properties, and to improve sensitivity in homology searching. The availability of complete genome sequences has increased the demands on multiple sequence alignment (MSA) programs. Current MSA methods suffer from being either too inaccurate or too computationally expensive to be applied effectively in large-scale comparative genomics.     

RNA global alignment in the joint sequence–structure space using elastic shape analysis

The functions of RNAs, like proteins, are determined by their structures, which, in turn, are determined by their sequences. Comparison/alignment of RNA molecules provides an effective means to predict their functions and understand their evolutionary relationships. For RNA sequence alignment, most methods developed for protein and DNA sequence alignment can be directly applied. RNA 3-dimensional structure alignment, on the other hand, tends to be more difficult than protein structure alignment due to the lack of regular secondary structures as observed in proteins. Most of the existing RNA 3D structure alignment methods use only the backbone geometry and ignore the sequence information. Using both the sequence and backbone geometry information in RNA alignment may not only produce more accurate classification, but also deepen our understanding of the sequence–structure–function relationship of RNA molecules. In this study, we developed a new RNA alignment method based on elastic shape analysis (ESA). ESA treats RNA structures as three dimensional curves with sequence information encoded on additional dimensions so that the alignment can be performed in the joint sequence–structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. Based on ESA, a rigorous mathematical framework can be built for RNA structure comparison. Means and covariances of full structures can be defined and computed, and probability distributions on spaces of such structures can be constructed for a group of RNAs. Our method was further applied to predict functions of RNA molecules and showed superior performance compared with previous methods when tested on benchmark datasets. The programs are available at http://stat.fsu.edu/ ∼jinfeng/ESA.html.     

Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.     

Transglycosylation: a mechanism for RNA modification (and editing?)

The vast majority of the ca. 100 chemically distinct modified nucleosides in RNA appear to arise via the chemical transformation of a genetically encoded nucleoside. Two notable exceptions are queuosine and pseudouridine, which are incorporated into tRNA via transglycosylation. Transglycosylation is an extremely efficient process for incorporating highly modified bases such as queuine into RNA. Transglycosylation is also a requisite process for "isomerizing" an N-nucleoside into a C-nucleoside as is the case for pseudouridine formation. Finally, transglycosylation is an attractive possibility for certain RNA editing events (e.g., pyrimidine to purine conversions) that cannot occur via the known, more straightforward enzymatic reactions (e.g., deaminations). This review discusses what is known about the mechanisms of transglycosylation for the queuine and pseudouridine RNA modifications and will speculate about a potential role for transglycosylation in certain RNA editing events.     

How much is secondary structure responsible for resistance of double-stranded RNA to pancreatic ribonuclease A?

1. Double-stranded f2 sus11 or Qbeta RNAs, resistant to bovine pancreatic RNAase A in 0.15 M NaCl/0.015 M sodium citrate (SSC), are quickly and completely degraded at 10-fold lower ionic strength (0.1 X SSC) under otherwise similar conditions. At this ionic strength the secondary structure of double-stranded RNA is maintained, as judged by the following: (a) the unchanged resistance of double-stranded RNA and DNA, under similar low ionic strength conditions, to nuclease S1 from Aspergillus oryzae, in contrast with the sensitivity of the corresponding denatured nucleic acids to this enzyme, specific for single-stranded RNA and DNA; (b) the co-operative pattern of the thermal-transition profile of double-stranded RNA (with a Tm of 89 degrees C) in 0.1 X SSC. 2. Whereas in SSC bovine seminal RNAase (RNAase BS-1) and whale pancreatic RNAase show an activity on double-stranded RNA significantly higher than that of RNAase A, in 0.1 X SSC the activity of the latter enzyme on this substrate becomes distinctly higher than that of RNAase BS-1, and similar to that of whale RNAase. 3. From these results it is deduced that the secondary structure is probably not the only nor the most important variable in determining the susceptibility double-stranded RNA to ribonuclease. Other factors, such as the effect of ionic strength on the enzyme and/or the binding of enzyme to nucleic acids, may play an important role in the process of double-stranded RNA degradation by ribonucleases specific for single-stranded RNA.     

Is the Trypanosoma brucei REL1 RNA ligase specific for U-deletion RNA editing,and is the REL2 RNA ligase specific for U-insertion editing?

It was shown previously that the REL1 mitochondrial RNA ligase in Trypanosoma brucei was a vital gene and disruption affected RNA editing in vivo, whereas the REL2 RNA ligase gene could be down-regulated with no effect on cell growth or on RNA editing. We performed down-regulation of REL1 in procyclic T. brucei (midgut insect forms) by RNA interference and found a 40-50% inhibition of Cyb editing, which has only U-insertions, as well as a similar inhibition of ND7 editing, which has both U-insertions and U-deletions. In addition, both U-insertion and U-deletion in vitro pre-cleaved editing were inhibited to similar extents. We also found little if any effect of REL1 down-regulation on the sedimentation coefficient or abundance of the RNA ligase-containing L-complex (Aphasizhev, R., Aphasizheva, I., Nelson, R. E., Gao, G., Simpson, A. M., Kang, X., Falick, A. M., Sbicego, S., and Simpson, L. (2003) EMBO J. 22, 913-924), suggesting that the inhibition of both insertion and deletion editing was not due to a disruption of the L-complex. Together with the evidence that down-regulation of REL2 has no effect on cell growth or on RNA editing in vivo or in vitro, these data suggest that the REL1 RNA ligase may be active in vivo in both U-insertion and U-deletion editing. The in vivo biological role of REL2 remains obscure.     

CGHPRO – A comprehensive data analysis tool for array CGH

Background  

Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for the genome wide detection of chromosomal imbalances. It is based on the co-hybridisation of differentially labelled test and reference DNA onto arrays of genomic BAC clones, cDNAs or oligonucleotides, and after correction for various intervening variables, loss or gain in the test DNA can be indicated from spots showing aberrant signal intensity ratios.     

The sequence and secondary structure of the 3′-UTR affect 3′-end maturation,RNA accumulation,and translation in tobacco chloroplasts

RNA maturation and modulation of RNA stability play important roles in chloroplast gene expression. In vitro and in vivo studies have shown that both the 5- and 3-untranslated regions (UTRs) contain sequence and structural elements that guide these processes, and interact with specific proteins. We have previously characterized the spinach chloroplast petD 3-UTR in detail by in vitro approaches. This stem-loop forming sequence is a weak terminator but is required for RNA maturation and also exhibits sequence-specific protein binding. To test petD 3-UTR function in vivo, tobacco chloroplast transformants were generated containing uidA reporter genes flanked by variants of the petD 3-UTR, including one which does not form an RNA-protein complex in vitro, and one which lacks a stem-loop structure. Analysis of uidA mRNA indicated that a stable secondary structure is required to accumulate a discrete mRNA, and that changes in the 3-UTR sequence which affect protein binding in vitro can also affect RNA metabolism in vivo. The 3-UTR also influenced -glucuronidase protein accumulation, but not in proportion to RNA levels. These results raise the possibility that in tobacco chloroplasts, the 3-UTR may influence translational yield.     

easyExon – A Java-based GUI tool for processing and visualization of Affymetrix exon array data

Background  

Alternative RNA splicing greatly increases proteome diversity and thereby contribute to species- or tissue-specific functions. The possibility to study alternative splicing (AS) events on a genomic scale using splicing-sensitive microarrays, including the Affymetrix GeneChip Exon 1.0 ST microarray (exon array), has appeared very recently. However, the application of this new technology is hindered by the lack of free and user-friendly software devoted to these novel platforms.     

Volumetric modulated arc therapy for synchronous bilateral whole breast irradiation – A case study

PurposeThe treatment planning of bilateral breast irradiation (BBI) is a challenging task. The overlapping of tangential fields is usually unavoidable without compromising the target coverage. The purpose of this study was to investigate the technical feasibility and benefits of a single isocentre volumetric modulated arc therapy (VMAT) in BBI.Methods and materialsTwo women with bilateral breast cancer were included in this case study. The first patient (Pat#1) underwent a bilateral breast-conserving surgery and sentinel lymph node biopsy. The second patient (Pat#2) underwent a bilateral ablation and axillary lymph node dissection. Planning target volumes (PTV) and organs at risk were delineated on CT images. VMAT plans were created with four (two for both sides, Pat#1) or two (one for each breast, Pat#2) separate VMAT fields. Subsequently, traditional tangential field plans were generated for each patient and the dosimetric parameters were compared.ResultsThe treatment times of the patients with VMAT were less than 15 min with daily CBCT imaging. When compared to the standard tangential field technique, the VMAT plans improved the PTV dose coverage and dose homogeneity with improved sparing of lungs and heart. With traditional field arrangement, the overlapping of the tangential fields was inevitable without significantly compromising the target coverage, whereas with VMAT the hotspots were avoided. The patients were treated with the VMAT technique and no acute skin toxicity was observed with either of the patients.ConclusionsA single isocentre VMAT technique has been implemented clinically for BBI. With the VMAT techniques, the dose delivery was quick and the hotspots in the field overlapping areas were avoided. The PTV dose coverage was superior in VMAT plans when compared with conventional tangential technique plans.     

Near identity of 3′ RNA secondary structure in bromoviruses and cucumber mosaic virus

The 3′ terminal sequences of RNAs 1, 2, 3 and 4 from each of the three bromoviruses (brome mosaic, cowpea chlorotic mottle and broad bean mottle viruses) and also from cucumber mosaic virus display interviral sequence similarity in addition to strong intraviral homology. Interviral similarity is much more evident when RNA secondary, rather than primary, structures are compared. The last 190 bases of the various RNAs can fold into strikingly similar, extensively base-paired secondary structures whose common features are supported by RNA structure mapping. The extreme 3′ end of each viral RNA can base-pair in two distinct configurations. Bromovirus RNA 3s each contain an unusually accessible internal oligo(A) sequence which, in brome mosaic virus at least, is located in the intercistronic noncoding region. Functional implications of these structural features are discussed.     

MolTalk – a programming library for protein structures and structure analysis

Background  

Two of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn.     

A Markov chain model for N-linked protein glycosylation – towards a low-parameter tool for model-driven glycoengineering

Glycosylation is a critical quality attribute of most recombinant biotherapeutics. Consequently, drug development requires careful control of glycoforms to meet bioactivity and biosafety requirements. However, glycoengineering can be extraordinarily difficult given the complex reaction networks underlying glycosylation and the vast number of different glycans that can be synthesized in a host cell. Computational modeling offers an intriguing option to rationally guide glycoengineering, but the high parametric demands of current modeling approaches pose challenges to their application. Here we present a novel low-parameter approach to describe glycosylation using flux-balance and Markov chain modeling. The model recapitulates the biological complexity of glycosylation, but does not require user-provided kinetic information. We use this method to predict and experimentally validate glycoprofiles on EPO, IgG as well as the endogenous secretome following glycosyltransferase knock-out in different Chinese hamster ovary (CHO) cell lines. Our approach offers a flexible and user-friendly platform that can serve as a basis for powerful computational engineering efforts in mammalian cell factories for biopharmaceutical production.     

A highly efficient in vivo plasmid editing tool based on CRISPR-Cas12a and phage λ Red recombineering

<正>Plasmids are useful tools for studying genetic information in living cells,as well as heterologous expression of genes and pathways in cells (Lauritsen et al.,2018).Various methods have been developed for plasmid manipulation both in vivo and in vitro(Aslanidis and de Jong,1990;Li and Elledge,2007;Xia et al.,2018).However,large plasmids,such as P1-based artificial chromosomes (PACs),bacterial artificial chromosomes (BACs),and fosmids,     

YANA – a software tool for analyzing flux modes,gene-expression and enzyme activities

Background  

A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA) has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest.     

“dendRoAnalyst”: A tool for processing and analysing dendrometer data

Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package ‘dendRoAnalyst’ based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.     

Predicting structure and stability for RNA complexes with intermolecular loop–loop base-pairing

RNA loop–loop interactions are essential for genomic RNA dimerization and regulation of gene expression. In this article, a statistical mechanics-based computational method that predicts the structures and thermodynamic stabilities of RNA complexes with loop–loop kissing interactions is described. The method accounts for the entropy changes for the formation of loop–loop interactions, which is a notable advancement that other computational models have neglected. Benchmark tests with several experimentally validated systems show that the inclusion of the entropy parameters can indeed improve predictions for RNA complexes. Furthermore, the method can predict not only the native structures of RNA/RNA complexes but also alternative metastable structures. For instance, the model predicts that the SL1 domain of HIV-1 RNA can form two different dimer structures with similar stabilities. The prediction is consistent with experimental observation. In addition, the model predicts two different binding sites for hTR dimerization: One binding site has been experimentally proposed, and the other structure, which has a higher stability, is structurally feasible and needs further experimental validation.