P element temperature-specific transposition: a model for possible regulation of mobile elements activity by pre-mRNA secondary structure

P element is a DNA transposon, known to spread in genome using transposase activity. Its activity is tissue-specific and normally observed at high temperatures within 24°C to 29°C. Here, we present a predicted RNA secondary structure domain of P element pre-mRNA which could potentially regulate the temperature sensitivity of the P element activity. In canonical P elements, the structure is a small hairpin with double-helical part interrupted by a symmetric loop and a mismatch. In M type P elements, the A.A mismatch is substituted by an A-U base pair, stabilizing the structure. The hairpin structure covers the region involving the IVS-3 5′ splice site and both pseudo-splice sites F1 and F2. While the IVS-3 and F1 binding sites of U1 snRNA are located in the double-stranded part of the structure, the F2 site is exposed in the hairpin loop. The formation of this structure may interfere with landing of U1 snRNA on IVS-3 site, while F2 is positioned for the interaction. Alignment of P element sequences supports the proposed existence of the hairpin, showing high similarity for this region. The hairpin structure, stable at low temperatures, may prevent correct IVS-3 splicing. Conversely, temperature-induced destabilization of the hairpin structure may result in the splicing at the proper IVS-3 splice site. Taking into account the increasing amount of data demonstrating the important influence of RNA folding on phenotypes determined by alternative splicing a model for possible regulation of the activity of mobile elements by pre-mRNA secondary structure seems intriguing.Предсказана вторичная структура пре-мРНК P-элемента, которая, возможно, регулирует его активность и температурную чувствительность. Структура представляет собой шпильку, более стабильную в Р-элементах М-типа, в сравнении с каноническими. Регион, образующий шпильку, находится в области 5’ сайта сплайсинга третьего интрона (IVS-3), включая оба описанных псевдо-сайта сплайсинга - F1 и F2. В то время как истинный сайт и F1 расположены, главным образом, в двухцепочечной области шпильки, F2 - экспонирован в петле. Выравнивание последовательностей Р-элементов продемонстрировало высокую степень сходства для указанного региона, что свидетельствует в пользу существования предсказанной структуры. Формирование шпильки, по нашему мнению, может препятствовать связыванию U1 snRNA с истинным сайтом сплайсинга, и, напротив, индуцированная температурой дестабилизация шпильки может приводить к корректному сплайсингу IVS-3. Таким образом, предложена гипотеза о влиянии вторичной структуры пре-мРНК мобильного элемента на его активность.Передбачена вторинна структура пре-мРНК Р-елемента, що, можливо, регулює його активність та температурну чутливість. Структура являє собою шпильку, більш стабільну у Р-елементах М-типу, порівняно з канонічними. Регіон, що утворює шпильку розташований в області 5’ сайта сплайсинга третього інтрону (IVS-3), включає обидва відомих псевдо-сайта сплайсингу - F1 та F2. При цьому 5’ сайт сплайсингу IVS-3 та F1псевдо-сайт знаходяться у дволанцюговій частині шпильки, а F2 є єкспонованим у петлі. Вирівнювання послідовностей Р-елементів продемонструвало високий рівень подібності для вказаного регіону, що свідчить на користь існування передбаченої структури. Формування шпильки, на нашу думку, може перешкоджати зв’язуванню U1 snRNA з 5’ сайтом сплайсингу IVS-3, і, навпаки, індукована температурою дестабілізація шпильки може сприяти корректному сплайсингу третього інтрону. Таким чином, запропонована гіпотеза про вплив вторинної структури пре-мРНК мобільного елементу на його активність

Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations

Ab initio RNA secondary structure predictions have long dismissed helices interior to loops, so-called pseudoknots, despite their structural importance. Here, we report that many pseudoknots can be predicted through long time scales RNA folding simulations, which follow the stochastic closing and opening of individual RNA helices. The numerical efficacy of these stochastic simulations relies on an O(n^2) clustering algorithm which computes time averages over a continously updated set of n reference structures. Applying this exact stochastic clustering approach, we typically obtain a 5- to 100-fold simulation speed-up for RNA sequences up to 400 bases, while the effective acceleration can be as high as 100,000-fold for short multistable molecules (<150 bases). We performed extensive folding statistics on random and natural RNA sequences, and found that pseudoknots are unevenly distributed amongst RNAstructures and account for up to 30% of base pairs in G+C rich RNA sequences (Online RNA folding kinetics server including pseudoknots : http://kinefold.u-strasbg.fr/ ).Comment: 6 pages, 5 figure

A database of flavivirus RNA structures with a search algorithm for pseudoknots and triple base interactions

Horizon 2020(H2020)Computer Systems, Imagery and Medi

Structural motifs in the RNA encoded by the early nodulation gene enod40 of soybean

Biophysical Structural ChemistryAnimal science

All genera of Flaviviridae host a conserved Xrn1-resistant RNA motif

Computer Systems, Imagery and Medi

PseudoBase++: an extension of PseudoBase for easy searching, formatting and visualization of pseudoknots

Pseudoknots have been recognized to be an important type of RNA secondary structures responsible for many biological functions. PseudoBase, a widely used database of pseudoknot secondary structures developed at Leiden University, contains over 250 records of pseudoknots obtained in the past 25 years through crystallography, NMR, mutational experiments and sequence comparisons. To promptly address the growing analysis requests of the researchers on RNA structures and bring together information from multiple sources across the Internet to a single platform, we designed and implemented PseudoBase++, an extension of PseudoBase for easy searching, formatting and visualization of pseudoknots. PseudoBase++ (http://pseudobaseplusplus.utep.edu) maps the PseudoBase dataset into a searchable relational database including additional functionalities such as pseudoknot type. PseudoBase++ links each pseudoknot in PseudoBase to the GenBank record of the corresponding nucleotide sequence and allows scientists to automatically visualize RNA secondary structures with PseudoViewer. It also includes the capabilities of fine-grained reference searching and collecting new pseudoknot information

CyloFold: secondary structure prediction including pseudoknots

Computational RNA secondary structure prediction approaches differ by the way RNA pseudoknot interactions are handled. For reasons of computational efficiency, most approaches only allow a limited class of pseudoknot interactions or are not considering them at all. Here we present a computational method for RNA secondary structure prediction that is not restricted in terms of pseudoknot complexity. The approach is based on simulating a folding process in a coarse-grained manner by choosing helices based on established energy rules. The steric feasibility of the chosen set of helices is checked during the folding process using a highly coarse-grained 3D model of the RNA structures. Using two data sets of 26 and 241 RNA sequences we find that this approach is competitive compared to the existing RNA secondary structure prediction programs pknotsRG, HotKnots and UnaFold. The key advantages of the new method are that there is no algorithmic restriction in terms of pseudoknot complexity and a test is made for steric feasibility. Availability: The program is available as web server at the site: http://cylofold.abcc.ncifcrf.gov

Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB)

Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection. The raw DNA data in association to environmental descriptors of metabarcoding studies are made available in public sequence read archives. While this is potentially a valuable source of information for the investigation of Fungi across diverse environmental conditions, the annotation used to describe environment is heterogenous. Moreover, a uniform processing pipeline still needs to be applied to the available raw DNA data. Hence, a comprehensive framework to analyses these data in a large context is still lacking. We introduce the MycoDiversity DataBase, a database which includes public fungal metabarcoding data of environmental samples for the study of biodiversity patterns of Fungi. The framework we propose will contribute to our understanding of fungal biodiversity and aims to become a valuable source for large-scale analyses of patterns in space and time, in addition to assisting evolutionary and ecological research on Fungi

Complete nucleotide sequences and genome organization of a cherry isolate of cherry leaf roll virus

The complete nucleotide sequence of cherry leaf roll virus (CLRV, genus Nepovirus) from a naturally infected cherry tree (Prunus avium cv. Bing) in North America was determined. RNA1 and RNA2 consist of 7,893 and 6,492 nucleotides, respectively, plus a poly-(A) tail. Each RNA encodes a single potential open reading frame. The first 657 nucleotides of RNA1 and RNA2 are 99% identical and include the 5′-UTR and the first 214 deduced amino acids of the polyproteins following the first of two in-frame start codons. Phylogenetic analysis reveals close relationships between CLRV and members of subgroup C of the genus Nepovirus

Rfam: Wikipedia, clans and the “decimal” release

The Rfam database aims to catalogue non-coding RNAs through the use of sequence alignments and statistical profile models known as covariance models. In this contribution, we discuss the pros and cons of using the online encyclopedia, Wikipedia, as a source of community‐derived annotation. We discuss the addition of groupings of related RNA families into clans and new developments to the website. Rfam is available on the Web at http://rfam.sanger.ac.uk