Complete chloroplast genome sequence of Holoparasite Cistanche Deserticola (Orobanchaceae) reveals gene loss and horizontal gene transfer from Its host Haloxylon Ammodendron (Chenopodiaceae)

The central function of chloroplasts is to carry out photosynthesis, and its gene content and structure are highly conserved across land plants. Parasitic plants, which have reduced photosynthetic ability, suffer gene losses from the chloroplast (cp) genome accompanied by the relaxation of selective constraints. Compared with the rapid rise in the number of cp genome sequences of photosynthetic organisms, there are limited data sets from parasitic plants. The authors report the complete sequence of the cp genome of Cistanche deserticola, a holoparasitic desert species belonging to the family Orobanchaceae

Can Clustal-style progressive pairwise alignment of multiple sequences be used in RNA secondary structure prediction?

<p>Abstract</p> <p>Background</p> <p>In ribonucleic acid (RNA) molecules whose function depends on their final, folded three-dimensional shape (such as those in ribosomes or spliceosome complexes), the secondary structure, defined by the set of internal basepair interactions, is more consistently conserved than the primary structure, defined by the sequence of nucleotides.</p> <p>Results</p> <p>The research presented here investigates the possibility of applying a progressive, pairwise approach to the alignment of multiple RNA sequences by simultaneously predicting an energy-optimized consensus secondary structure. We take an existing algorithm for finding the secondary structure common to two RNA sequences, Dynalign, and alter it to align profiles of multiple sequences. We then explore the relative successes of different approaches to designing the tree that will guide progressive alignments of sequence profiles to create a multiple alignment and prediction of conserved structure.</p> <p>Conclusion</p> <p>We have found that applying a progressive, pairwise approach to the alignment of multiple ribonucleic acid sequences produces highly reliable predictions of conserved basepairs, and we have shown how these predictions can be used as constraints to improve the results of a single-sequence structure prediction algorithm. However, we have also discovered that the amount of detail included in a consensus structure prediction is highly dependent on the order in which sequences are added to the alignment (the guide tree), and that if a consensus structure does not have sufficient detail, it is less likely to provide useful constraints for the single-sequence method.</p

Structural characterization of naturally occurring RNA single mismatches

RNA is known to be involved in several cellular processes; however, it is only active when it is folded into its correct 3D conformation. The folding, bending and twisting of an RNA molecule is dependent upon the multitude of canonical and non-canonical secondary structure motifs. These motifs contribute to the structural complexity of RNA but also serve important integral biological functions, such as serving as recognition and binding sites for other biomolecules or small ligands. One of the most prevalent types of RNA secondary structure motifs are single mismatches, which occur when two canonical pairs are separated by a single non-canonical pair. To determine sequence–structure relationships and to identify structural patterns, we have systematically located, annotated and compared all available occurrences of the 30 most frequently occurring single mismatch-nearest neighbor sequence combinations found in experimentally determined 3D structures of RNA-containing molecules deposited into the Protein Data Bank. Hydrogen bonding, stacking and interaction of nucleotide edges for the mismatched and nearest neighbor base pairs are described and compared, allowing for the identification of several structural patterns. Such a database and comparison will allow researchers to gain insight into the structural features of unstudied sequences and to quickly look-up studied sequences

The Mode of Action of Maleic Hydrazide: Inhibition of Growth

Maleic hydrazide (MH) inhibits corn root elongation through an effect on cell division apparently without inhibiting cell enlargement. The decrease in the rate of elongation was apparent only after a considerable lag, over 14 hours, even with a concentration as high as 5 mM. MH (1 mM) did not inhibit His growth of roots from corn seeds given very large doses of Γ-irradiation or excised corn root segments including the elongation Zone or the cell enlargement induced by IAA in corn coleoptile sections. Many compounds including purines, pyrimidines, nucleosides. cysteine, pyridoxal, pyruvate. kinetin and CoCl 2 , many of which had previously been reported to alleviate MH inhibition in other tissues, were tested for their ability to prevent the inhibition of corn root elongation by MH, but none were effective. These data do not support the theory that MH acts by inhibiting the synthesis of or competing with some simple metabolite or hormone. Whatever its mechanism of action the failure of MH to inhibit cell enlargement in most systems indicates that it is fairly selective.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74891/1/j.1399-3054.1969.tb07375.x.pd

Predicting RNA secondary structure by the comparative approach: how to select the homologous sequences

<p>Abstract</p> <p>Background</p> <p>The secondary structure of an RNA must be known before the relationship between its structure and function can be determined. One way to predict the secondary structure of an RNA is to identify covarying residues that maintain the pairings (Watson-Crick, Wobble and non-canonical pairings). This "comparative approach" consists of identifying mutations from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. This can be due to poor quality alignment in stems or to the variability of certain sequences. This problem of sequence selection is currently unsolved.</p> <p>Results</p> <p>This paper describes an algorithm, <it>SSCA</it>, which measures the suitability of sequences for the comparative approach. It is based on evolutionary models with structure constraints, particularly those on sequence variations and stem alignment. We propose three models, based on different constraints on sequence alignments. We show the results of the <it>SSCA </it>algorithm for predicting the secondary structure of several RNAs. <it>SSCA </it>enabled us to choose sets of homologous sequences that gave better predictions than arbitrarily chosen sets of homologous sequences.</p> <p>Conclusion</p> <p><it>SSCA </it>is an algorithm for selecting combinations of RNA homologous sequences suitable for secondary structure predictions with the comparative approach.</p

Entropy Measures Quantify Global Splicing Disorders in Cancer

Most mammalian genes are able to express several splice variants in a phenomenon known as alternative splicing. Serious alterations of alternative splicing occur in cancer tissues, leading to expression of multiple aberrant splice forms. Most studies of alternative splicing defects have focused on the identification of cancer-specific splice variants as potential therapeutic targets. Here, we examine instead the bulk of non-specific transcript isoforms and analyze their level of disorder using a measure of uncertainty called Shannon's entropy. We compare isoform expression entropy in normal and cancer tissues from the same anatomical site for different classes of transcript variations: alternative splicing, polyadenylation, and transcription initiation. Whereas alternative initiation and polyadenylation show no significant gain or loss of entropy between normal and cancer tissues, alternative splicing shows highly significant entropy gains for 13 of the 27 cancers studied. This entropy gain is characterized by a flattening in the expression profile of normal isoforms and is correlated to the level of estimated cellular proliferation in the cancer tissue. Interestingly, the genes that present the highest entropy gain are enriched in splicing factors. We provide here the first quantitative estimate of splicing disruption in cancer. The expression of normal splice variants is widely and significantly disrupted in at least half of the cancers studied. We postulate that such splicing disorders may develop in part from splicing alteration in key splice factors, which in turn significantly impact multiple target genes

Evaluation of Glycine max mRNA clusters

BACKGROUND: Clustering the ESTs from a large dataset representing a single species is a convenient starting point for a number of investigations into gene discovery, genome evolution, expression patterns, and alternatively spliced transcripts. Several methods have been developed to accomplish this, the most widely available being UniGene, a public domain collection of gene-oriented clusters for over 45 different species created and maintained by NCBI. The goal is for each cluster to represent a unique gene, but currently it is not known how closely the overall results represent that reality. UniGene's build procedure begins with initial mRNA clusters before joining ESTs. UniGene's results for soybean indicate a significant amount of redundancy among some sequences reported to be unique mRNAs. To establish a valid non-redundant known gene set for Glycine max we applied our algorithm to the clustering of only mRNA sequences. The mRNA dataset was run through the algorithm using two different matching stringencies. The resulting cluster compositions were compared to each other and to UniGene. Clusters exhibiting differences among the three methods were analyzed by 1) nucleotide and amino acid alignment and 2) submitting authors conclusions to determine whether members of a single cluster represented the same gene or not. RESULTS: Of the 12 clusters that were examined closely most contained examples of sequences that did not belong in the same cluster. However, neither the two stringencies of PECT nor UniGene had a significantly greater record of accuracy in placing paralogs into separate clusters. CONCLUSION: Our results reveal that, although each method produces some errors, using multiple stringencies for matching or a sequential hierarchical method of increasing stringencies can provide more reliable results and therefore allow greater confidence in the vast majority of clusters that contain only ESTs and no mRNA sequences

RNAcentral: A vision for an international database of RNA sequences

During the last decade there has been a great increase in the number of noncoding RNA genes identified, including new classes such as microRNAs and piRNAs. There is also a large growth in the amount of experimental characterization of these RNA components. Despite this growth in information, it is still difficult for researchers to access RNA data, because key data resources for noncoding RNAs have not yet been created. The most pressing omission is the lack of a comprehensive RNA sequence database, much like UniProt, which provides a comprehensive set of protein knowledge. In this article we propose the creation of a new open public resource that we term RNAcentral, which will contain a comprehensive collection of RNA sequences and fill an important gap in the provision of biomedical databases. We envision RNA researchers from all over the world joining a federated RNAcentral network, contributing specialized knowledge and databases. RNAcentral would centralize key data that are currently held across a variety of databases, allowing researchers instant access to a single, unified resource. This resource would facilitate the next generation of RNA research and help drive further discoveries, including those that improve food production and human and animal health. We encourage additional RNA database resources and research groups to join this effort. We aim to obtain international network funding to further this endeavor

Effects of Restrained Sampling Space and Nonplanar Amino Groups on Free-Energy Predictions for RNA with Imino and Sheared Tandem GA Base Pairs Flanked by GC, CG, iGiC or iCiG Base Pairs

Guanine-adenine (GA) base pairs play important roles in determining the structure, dynamics, and stability of RNA. In RNA internal loops, GA base pairs often occur in tandem arrangements and their structure is context and sequence dependent. Calculations reported here test the thermodynamic integration (TI) approach with the amber99 force field by comparing computational predictions of free energy differences with the free energy differences expected on the basis of NMR determined structures of the RNA motifs (5′-GCGGACGC-3′)2, (5′-GCiGGAiCGC-3′)2, (5′-GGCGAGCC-3′)2, and (5′-GGiCGAiGCC-3′)2. Here, iG and iC denote isoguanosine and isocytidine, which have amino and carbonyl groups transposed relative to guanosine and cytidine. The NMR structures show that the GA base pairs adopt either imino (cis Watson−Crick/Watson−Crick A-G) or sheared (trans Hoogsteen/Sugar edge A-G) conformations depending on the identity and orientation of the adjacent base pair. A new mixing function for the TI method is developed that allows alchemical transitions in which atoms can disappear in both the initial and final states. Unrestrained calculations gave ΔG° values 2−4 kcal/mol different from expectations based on NMR data. Restraining the structures with hydrogen bond restraints did not improve the predictions. Agreement with NMR data was improved by 0.7 to 1.5 kcal/mol, however, when structures were restrained with weak positional restraints to sample around the experimentally determined NMR structures. The amber99 force field was modified to partially include pyramidalization effects of the unpaired amino group of guanosine in imino GA base pairs. This provided little or no improvement in comparisons with experiment. The marginal improvement is observed when the structure has potential cross-strand out-of-plane hydrogen bonding with the G amino group. The calculations using positional restraints and a nonplanar amino group reproduce the signs of ΔG° from the experimental results and are, thus, capable of providing useful qualitative insights complementing the NMR experiments. Decomposition of the terms in the calculations reveals that the dominant terms are from electrostatic and interstrand interactions other than hydrogen bonds in the base pairs. The results suggest that a better description of the backbone is key to reproducing the experimental free energy results with computational free energy predictions