Sequence Selectivity Research Articles

Multi-core shared tree based MP2MP RWA algorithms in large scale and multi-domain optical networks

The increasing demands of bandwidth-intensive parallel computing and collaborative applications, efficient service provisioning to support multipoint to multipoint (MP2MP) communications have attracted increasing attention. However, with the development of larger-scale and multi-domain optical networks, MP2MP RWA are introduced optimal domain sequence selection and core nodes belong to which domains problems which cannot be tackled by the conventional algorithms proposed aim at a signal domain. In this paper, we proposed a multi-core node shared multicast tree heuristic algorithm (MCSMT) which calculation could be parallelized, delay and minimal cost constrained for multi-domain optical networks. It could realize the accurate calculation of minimum number of cores and the hosted domains of the cores. The source and destination nodes were added in different shared trees respectively with delay constrained algorithms according to specific QoS selection strategy. At the same time, according to more complicated MP2MP algorithms we propose a PCE-cloud based control architecture for optical networks by applying the cloud computing technology (e.g. virtualization and parallel computing) to reform the control plane for improving system reliability, intelligence and maximizing resource utilization. The performances of the proposed heuristic with regard to the number of multi-core nodes, wavelength channel occupied and MP2MP setup latency are compared. In addition, the performance about path computing latency for PCE-cloud control architecture is compared with conversional control architecture.

Multi-objective elitist spotted hyena resource optimized flexible job shop scheduling

The job shop scheduling problem (JSSP) has drained a lot of consideration since it is one of the most important optimization problems in the manufacturing domain. The scheduling method is crucial for optimizing the objective of minimizing makespan among thousands of jobs, but evaluating machine capacity for achieving this goal remains challenging despite the development of various population-based optimization algorithms for job shop scheduling problems. To improve the efficiency of Job shop scheduling, a novel Multi-objective Elitist Spotted Hyena Monotonic Scheduling (MESHS) technique is introduced. The proposed MESHS technique includes two major processes: machine selection and operation sequences. The number of jobs is considered for solving the scheduling problem. First, the machine selection is performed by applying the Multi-objective Elitist Spotted Hyena optimization technique. The optimization technique selects the optimal machines parallelly based on multiple objective functions such as energy consumption, CPU utilization, and job completion time. The fitness of every machine is calculated based on these multiple objective functions using Levenberg–Marquardt method. Then the Elitist strategy is applied to select the optimal machine based on fitness. After the machine selection, the rate-monotonic preemptive scheduling is modeled to provide a robust operation sequence by assigning high-priority jobs to the optimal machines. As a result, efficient job scheduling is achieved with minimum time. Finally, the experimental valuation is carried out using a benchmark OR-Library dataset with different factors such as job shop scheduling efficiency, job scheduling time, makespan, and memory consumption concerning a number of jobs.

Comparative study on the target sequences of thaumatin-like protein (TLP) and internal transcribed spacer (ITS) in the detection of corn component in edible oil by ladder-shape melting temperature isothermal amplification (LMTIA)

Single copy thaumatin-like protein (TLP) genes and multiple copy internal transcribed spacer (ITS) genes from the nucleus of corn were selected as targets, designed and screened primers. The impact of target sequence selection on ladder-shape melting temperature isothermal amplification (LMTIA) detection of corn components in edible oil from aspects such as specificity, sensitivity, and stability were studied. The results showed that the LMTIA system targeting TLP has an optimal reaction temperature of 58 °C and can detect a minimum of 100 pg/μL of corn DNA, and the LMTIA system established with ITS as the target has higher sensitivity, with an optimal temperature of 59 °C, and can detect corn DNA as low as 1 pg/μL. Both systems have good specificity, stable reactions, and no false positive results were observed. Conclusion: ITS is more suitable as a target sequence for LMTIA detection of corn components in edible oil.

Phage-assisted evolution of highly active cytosine base editors with enhanced selectivity and minimal sequence context preference

TadA-derived cytosine base editors (TadCBEs) enable programmable C•G-to-T•A editing while retaining the small size, high on-target activity, and low off-target activity of TadA deaminases. Existing TadCBEs, however, exhibit residual A•T-to-G•C editing at certain positions and lower editing efficiencies at some sequence contexts and with non-SpCas9 targeting domains. To address these limitations, we use phage-assisted evolution to evolve CBE6s from a TadA-mediated dual cytosine and adenine base editor, discovering mutations at N46 and Y73 in TadA that prevent A•T-to-G•C editing and improve C•G-to-T•A editing with expanded sequence-context compatibility, respectively. In E. coli, CBE6 variants offer high C•G-to-T•A editing and no detected A•T-to-G•C editing in any sequence context. In human cells, CBE6 variants exhibit broad Cas domain compatibility and retain low off-target editing despite exceeding BE4max and previous TadCBEs in on-target editing efficiency. Finally, we show that the high selectivity of CBE6 variants is well-suited for therapeutically relevant stop codon installation without creating unwanted missense mutations from residual A•T-to-G•C editing.

The expanding roles of Nr6a1 in development and evolution.

The Nuclear Receptor (NR) family of transcriptional regulators possess the ability to sense signalling molecules and directly couple that to a transcriptional response. While this large class of proteins are united by sequence and structural homology, individual NR functional output varies greatly depending on their expression, ligand selectivity and DNA binding sequence specificity. Many NRs have remained somewhat enigmatic, with the absence of a defined ligand categorising them as orphan nuclear receptors. One example is Nuclear Receptor subfamily 6 group A member 1 (Nr6a1), an orphan nuclear receptor that has no close evolutionary homologs and thus is alone in subfamily 6. Nonetheless, Nr6a1 has emerged as an important player in the regulation of key pluripotency and developmental genes, as functionally critical for mid-gestational developmental progression and as a possible molecular target for driving evolutionary change in animal body plan. Here, we review the current knowledge on this enigmatic nuclear receptor and how it impacts development and evolution.

Deadenylation kinetics of mixed poly(A) tails at single-nucleotide resolution

Shortening of messenger RNA poly(A) tails, or deadenylation, is a rate-limiting step in mRNA decay and is highly regulated during gene expression. The incorporation of non-adenosines in poly(A) tails, or ‘mixed tailing’, has been observed in vertebrates and viruses. Here, to quantitate the effect of mixed tails, we mathematically modeled deadenylation reactions at single-nucleotide resolution using an in vitro deadenylation system reconstituted with the complete human CCR4–NOT complex. Applying this model, we assessed the disrupting impact of single guanosine, uridine or cytosine to be equivalent to approximately 6, 8 or 11 adenosines, respectively. CCR4–NOT stalls at the 0, −1 and −2 positions relative to the non-adenosine residue. CAF1 and CCR4 enzyme subunits commonly prefer adenosine but exhibit distinct sequence selectivities and stalling positions. Our study provides an analytical framework to monitor deadenylation and reveals the molecular basis of tail sequence-dependent regulation of mRNA stability.

Probing a Major DNA Weakness: Resolving the Groove and Sequence Selectivity of the Diimine Complex Λ‐[Ru(phen)2phi]2+

AbstractThe grooves of DNA provide recognition sites for many nucleic acid binding proteins and anticancer drugs such as the covalently binding cisplatin. Here we report a crystal structure showing, for the first time, groove selectivity by an intercalating ruthenium complex. The complex Λ‐[Ru(phen)2phi]2+, where phi=9,10‐phenanthrenediimine, is bound to the DNA decamer duplex d(CCGGTACCGG)2. The structure shows that the metal complex is symmetrically bound in the major groove at the central TA/TA step, and asymmetrically bound in the minor groove at the adjacent GG/CC steps. A third type of binding links the strands, in which each terminal cytosine base stacks with one phen ligand. The overall binding stoichiometry is four Ru complexes per duplex. Complementary biophysical measurements confirm the binding preference for the Λ‐enantiomer and show a high affinity for TA/TA steps and, more generally, TA‐rich sequences. A striking enantiospecific elevation of melting temperatures is found for oligonucleotides which include the TATA box sequence.

Probing a Major DNA Weakness: Resolving the Groove and Sequence Selectivity of the Diimine Complex Λ-[Ru(phen)2 phi]2.

The grooves of DNA provide recognition sites for many nucleic acid binding proteins and anticancer drugs such as the covalently binding cisplatin. Here we report a crystal structure showing, for the first time, groove selectivity by an intercalating ruthenium complex. The complex Λ-[Ru(phen)2 phi]2+ , where phi=9,10-phenanthrenediimine, is bound to the DNA decamer duplex d(CCGGTACCGG)2 . The structure shows that the metal complex is symmetrically bound in the major groove at the central TA/TA step, and asymmetrically bound in the minor groove at the adjacent GG/CC steps. A third type of binding links the strands, in which each terminal cytosine base stacks with one phen ligand. The overall binding stoichiometry is four Ru complexes per duplex. Complementary biophysical measurements confirm the binding preference for the Λ-enantiomer and show a high affinity for TA/TA steps and, more generally, TA-rich sequences. A striking enantiospecific elevation of melting temperatures is found for oligonucleotides which include the TATA box sequence.

Building digital patient pathways for the management and treatment of multiple sclerosis.

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.

An Assembly Sequence Planning Method Based on Multiple Optimal Solutions Genetic Algorithm

Assembly sequence planning (ASP) is an indispensable and important step in the intelligent assembly process, and aims to solve the optimal assembly sequence with the shortest assembly time as its optimization goal. This paper focuses on modular cabin construction for large cruise ships, tackling the complexities and challenges of part assembly during the process, based on real engineering problems. It introduces the multiple optimal solutions genetic algorithm (MOSGA). The MOSGA analyzes product constraints and establishes a mathematical model. Firstly, the traditional genetic algorithm (GA) is improved in the case of falling into the local optimum when facing complex problems, so that it can jump out of the local optimum under the condition of satisfying the processing constraints and achieve the global search effect. Secondly, the problem whereby the traditional search algorithm converges to the unique optimal solution is solved, and multiple unique optimal solutions that are more suitable for the actual assembly problem are solved. Thirdly, for a variety of restrictions and emergencies that may occur during the assembly process, the assembly sequence flexible planning (ASFP) method is introduced so that each assembly can be flexibly adjusted. Finally, an example is used to verify the feasibility and effectiveness of the method. This method improves the assembly efficiency and the diversity of assembly sequence selection, and can flexibly adjust the assembly sequence, which has important guiding significance for the ASP problem.

Assessment of paravalvular regurgitation after transcatheter aortic valve replacement using 2D multi-venc and 4D flow CMR.

To compare the novel 2D multi-venc and 4D flow acquisitions with the standard 2D flow acquisition for the assessment of paravalvular regurgitation (PVR) after TAVR using cardiac magnetic resonance (CMR)-derived regurgitant fraction (RF). In this prospective study, patients underwent CMR one month after TAVR to assess PVR using 2D multi-venc and 4D flow, in addition to standard 2D flow. Scatterplots and Bland-Altman plots were used to assess correlation and visualize agreement between techniques. Reproducibility of measurements was assessed with intraclass correlation coefficients. The study included 21 patients (mean age, 80 years ± 5 [SD], 9 men). Mean RF was 11.7 ± 10.0% using standard 2D flow, 10.6 ± 7.0% using 2D multi-venc flow, and 9.6 ± 7.3% using 4D flow. There was a very strong correlation between the RFs assessed with 2D multi-venc and standard 2D flow (r = 0.88, p < 0.001), and a strong correlation between the RFs assessed with 4D flow and standard 2D flow (r = 0.74, p < 0.001). Bland-Altman plots revealed no significant bias between the RFs (2D multi-venc: 1.3%; 4D flow: 0.3%). Intra- and interobserver reproducibility for 2D multi-venc flow were 0.98 and 0.97, respectively; and 0.92 and 0.90 for 4D flow, respectively. 2D multi-venc and 4D flow produce accurate quantification of PVR after TAVR. The fast acquisition of the 2D multi-venc sequence, and the free-breathing acquisition with retrospective plane selection of the 4D flow sequence provide useful advantages in clinical practice, especially in the frail TAVR population.

Genetic diversity of the S-type small subunit ribosomal RNA gene of Plasmodium knowlesi isolates from Sabah, Malaysian Borneo and Peninsular Malaysia

Objective: To determine the genetic diversity of Plasmodium (P.) knowlesi isolates from Sabah, Malaysian Borneo and Peninsular Malaysia, targeting the S-type SSU rRNA gene and including aspects of natural selection and haplotype. Methods: Thirty-nine blood samples infected with P. knowlesi were collected in Sabah, Malaysian Borneo and Peninsular Malaysia. The S-type SSU rRNA gene was amplified using polymerase chain reaction, cloned into a vector, and sequenced. The natural selection and haplotype of the S-type SSU rRNA gene sequences were determined using DnaSP v6 and illustrated using NETWORK v10. This study's 39 S-type SSU rRNA sequences and eight sequences from the Genbank database were subjected to phylogenetic analysis using MEGA 11. Results: Overall, the phylogenetic analysis showed no evidence of a geographical cluster of P. knowlesi isolates from different areas in Malaysia based on the S-type SSU rRNA gene sequences. The S-type SSU rRNA gene sequences were relatively conserved and with a purifying effect. Haplotype sharing of the S-type SSU rRNA gene was observed between the P. knowlesi isolates in Sabah, Malaysian Borneo, but not between Sabah, Malaysian Borneo and Peninsular Malaysia. Conclusions: This study suggests that the S-type SSU rRNA gene of P. knowlesi isolates in Sabah, Malaysian Borneo, and Peninsular Malaysia has fewer polymorphic sites, representing the conservation of the gene. These features make the S-type SSU rRNA gene suitable for comparative studies, such as determining the evolutionary relationships and common ancestry among P. knowlesi species.

Preferential formation of Z-RNA over intercalated motifs in long noncoding RNA.

Secondary structure is a principal determinant of lncRNA function, predominantly regarding scaffold formation and interfaces with target molecules. Noncanonical secondary structures that form in nucleic acids have known roles in regulating gene expression and include G-quadruplexes (G4s), intercalated motifs (iMs), and R-loops (RLs). In this paper, we used the computational tools G4-iM Grinder and QmRLFS-finder to predict the formation of each of these structures throughout the lncRNA transcriptome in comparison to protein-coding transcripts. The importance of the predicted structures in lncRNAs in biological contexts was assessed by combining our results with publicly available lncRNA tissue expression data followed by pathway analysis. The formation of predicted G4 (pG4) and iM (piM) structures in select lncRNA sequences was confirmed in vitro using biophysical experiments under near-physiological conditions. We find that the majority of the tested pG4s form highly stable G4 structures, and identify many previously unreported G4s in biologically important lncRNAs. In contrast, none of the piM sequences are able to form iM structures, consistent with the idea that RNA is unable to form stable iMs. Unexpectedly, these C-rich sequences instead form Z-RNA structures, which have not been previously observed in regions containing cytosine repeats and represent an interesting and underexplored target for protein-RNA interactions. Our results highlight the prevalence and potential structure-associated functions of noncanonical secondary structures in lncRNAs, and show G4 and Z-RNA structure formation in many lncRNA sequences for the first time, furthering the understanding of the structure-function relationship in lncRNAs.

Criteria for classification, nomenclature, and reference sequence selection for HIV sub-subtypes of CRF01_AE and CRF07_BC strains in China.

The available knowledge regarding classification, nomenclature, and reference sequence selection for the various sub-subtypes of circulating recombinant forms (CRFs) is inadequate to fulfill the growing demands of research focused on HIV prevention. We analyzed the spread of CRF01_AE and CRF07_BC strains, mainly in China, to complement and update the existing nomenclature and to propose a reference sequence selection criteria for sub-subtypes of CRFs.

Host Preference of &lt;i&gt;Xanthopimpla&lt;/i&gt; Saussure Parasitising &lt;i&gt;Sesamia inferens&lt;/i&gt; Walker

Host selection sequence of two parasitoids of under the genus Xanthopimpla Saussure viz., Xanthopimpla flavolineata (Xf) Cameron [Xf] and X. stemmator (Thunberg) (Xs) and suitability of various pupal stages of Sesamia inferens as a factitious host for rearing was investigated. There was no significant difference in egg laying between the single and repeated attempts by both Xf and Xs. The probing time of Xf and Xs in the rice stem with concealed host (2.26± 0.10 and 1.60± 0.13 min) and a hollow stem without a host was found to be 1.19± 0.14 and 0.59± 0.15 min, respectively. However, Xs did not parasitize the naked pupa. The number of ovipositor insertions was 1.50± 0.17 in concealed pupae and 0.92± 0.15 in hollow stem without host. Among the stages of S. inferens pupae tested for acceptance by Xf and Xs, the prepupa was preferred the most followed by one- and two-day-old pupa, while five- and six-day-old pupae were not preferred.

Efficient automated high dynamic range 3D measurement via deep reinforcement learning.

High dynamic range 3D measurement technology, utilizing multiple exposures, is pivotal in industrial metrology. However, selecting the optimal exposure sequence to balance measurement efficiency and quality remains challenging. This study reinterprets this challenge as a Markov decision problem and presents an innovative exposure selection method rooted in deep reinforcement learning. Our approach's foundation is the exposure image prediction network (EIPN), designed to predict images under specific exposures, thereby simulating a virtual environment. Concurrently, we establish a reward function that amalgamates considerations of exposure number, exposure time, coverage, and accuracy, providing a comprehensive task definition and precise feedback. Building upon these foundational elements, the exposure selection network (ESN) emerges as the centerpiece of our strategy, acting decisively as an agent to derive the optimal exposure sequence selection. Experiments prove that the proposed method can obtain similar coverage (0.997 vs. 1) and precision (0.0263 mm vs. 0.0230 mm) with fewer exposures (generally 4) compared to the results of 20 exposures.

Substrate selectivity and unique sequence signatures in SWEET/semiSWEET homologs of four taxonomic groups: Sequence analysis and phylogenetic studies.

The recently discovered SWEET (Sugar Will Eventually be Exported Transporter) proteins are involved in the selective transport of monosaccharides and disaccharides. The prokaryotic counterparts, semiSWEETs, form dimers with each monomer forming a triple-helix transmembrane bundle (THB). The longer eukaryotic SWEETs have seven transmembrane helices with two THBs and a linker helix. Structures of semiSWEETs/SWEETs have been determined experimentally. Experimental studies revealed the role of plant SWEETs in vital physiological processes and identified residues responsible for substrate selectivity. However, SWEETs/semiSWEETs from metazoans and bacteria are not characterized. In this study, we used structure-based sequence alignment and compared more than 2000 SWEET/semiSWEETs from four different taxonomic groups. Conservation of residue/chemical property was examined at all positions. Properties of clades/subclades of phylogenetic trees from each taxonomic group were analyzed. Conservation pattern of known residues in the selectivity-filter was used to predict the substrate preference of plant SWEETs and some clusters of metazoans and bacteria. Some residues at the gating and substrate-binding regions, pore-facing positions and at the helix-helix interface are conserved across all taxonomic groups. Conservation of polar/charged residues at specific pore-facing positions, helix-helix interface and in loops seems to be unique for plant SWEETs. Overall, the number of conserved residues is less in metazoan SWEETs. Plant and metazoan SWEETs exhibit high conservation of four and three proline residues respectively in "proline tetrad." Further experimental studies can validate the predicted substrate selectivity and significance of conserved polar/charged/aromatic residues at structurally and functionally important positions of SWEETs/semiSWEETs in plants, metazoans and bacteria.

Screening Selection of Hydrogen Evolution-Inhibiting and Zincphilic Alloy Anode for Aqueous Zn Battery.

The hydrogen evolution reaction (HER) and Zn dendrites growth are two entangled detrimental effects hindering the application of aqueous Zn batteries. The alloying strategy is studied to be a convenient avenue to stabilize Zn anodes, but there still lacks global understanding when selecting reliable alloy elements. Herein, it is proposed to evaluate the Zn alloying elements in a holistic way by considering their effects on HER, zincphilicity, price, and environmental-friendliness. Screening selection sequence is established through the theoretical evaluation of 17 common alloying elements according to their effects on hydrogen evolution and Zn nucleation thermodynamics. Two alloy electrodes with opposite predicted effects are prepared for experimental demonstration, i.e., HER-inhibiting Bi and HER-exacerbating Ni. Impressively, the optimum ZnBi alloy anode exhibits one order of magnitude lower hydrogen evolution rate than that of the pure Zn, leading to an ultra-long plating/stripping cycling life for more than 11000 cycles at a high current density of 20mA cm-2 and 81% capacity retention for 170 cycles in a Zn-V2O5 pouch cell. The study not only proposes a holistic alloy selection principle for Zn anode but also identifies a practically effective alloy element.

Selective whole-genome sequencing of Plasmodium parasites directly from blood samples by nanopore adaptive sampling.

Malaria is caused by parasites of the genus Plasmodium, and reached a global disease burden of 247 million cases in 2021. To study drug resistance mutations and parasite population dynamics, whole-genome sequencing of patient blood samples is commonly performed. However, the predominance of human DNA in these samples imposes the need for time-consuming laboratory procedures to enrich Plasmodium DNA. We used the Oxford Nanopore Technologies' adaptive sampling feature to circumvent this problem and enrich Plasmodium reads directly during the sequencing run. We demonstrate that adaptive nanopore sequencing efficiently enriches Plasmodium reads, which simplifies and shortens the timeline from blood collection to parasite sequencing. In addition, we show that the obtained data can be used for monitoring genetic markers, or to generate nearly complete genomes. Finally, owing to its inherent mobility, this technology can be easily applied on-site in endemic areas where patients would benefit the most from genomic surveillance.

ADVANCEMENTS IN GENOMIC TECHNOLOGIES AND THEIR IMPACT ON CROP IMPROVEMENT AND BREEDING METHODS

Recent advances in genome sequencing of essential crop plants allow genotype and phenotype data integration in crop development. Advanced statistical methods identified quantitative trait genes. Genomic prediction has been used successfully in breeding animals and is now also used in breeding plants. Biometric statistics, genome-wide markers, and phenotyping enhance gene discovery. This makes biotechnology agricultural plant solutions possible. Improved fertilizer efficiency requires precise plant phenotyping in multiple habitats and seasons, which was previously expensive. DNA sequencing, genetic engineering, and PCR-based marker-assisted selection have made it cheaper. New methods like next-generation sequencing can target climate-responsive crop development. It examines Oryza sativa L. flower opening and closing molecularly and hybrid breeding success in diverse plant types. It discusses CRISPR/Cas9 for crop trait improvement and metabolic studies for Triticum aestivum L. quality group determination. Genetic analysis should use species-specific techniques, according to the study. A Zea mays L. callus induction and growth study examined how media and growth conditions affect callus development. Another drought-stressed Triticum aestivum L. cultivar gene expression study suggests employing RNA editing to respond to environmental stress. PCR-based markers have helped scientists find important genes in landraces that have changed to survive harsh farming conditions, giving them targets for crop growth.