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Application of new genome editing technologies for plant improvement depends on efficient delivery of editing components into plant cells. For editing of canola, which is an important oil crop, CRISPR/Cas9 and Agrobacterium-mediated transformation of hypocotyl or stem segments have been the primary methods used. Here, we present the development of an efficient and high-throughput system for protoplast isolation, DNA-free editing, and production of edited canola plants. Protoplast polyethylene glycol (PEG)–mediated transfection was conducted with ribonucleoproteins (RNPs) comprising LbCas12a and a single guide RNA. Edits were found at a frequency of approximately 40% in protoplasts cultured for 2 d, in callus colonies derived from these protoplasts, and in regenerated plants. Out of 30 plants that were regenerated from the protoplasts, 12 were edited. Six of them were with biallelic mutations and another six had monoallelic mutations. Targeted deletions from 2 to 9 nucleotides were identified in the T0 edited plants. Analysis of T1 progeny confirmed that the RNP-based, DNA-free edits using this canola protoplast system are heritable.

High efficiency site-directed chromosomal integration of exogenous DNA in plants remains a challenge despite recent advances in genome editing technologies. One approach to mitigate this problem is to increase the effective concentration of the donor DNA at the target site of interest. HUH endonucleases (ENs) coordinate rolling circle replication. In vitro, they can form stable covalent bonds with DNA that carries their recognition motifs. When fused to a CRISPR-associated endonuclease, HUH ENs may improve integration rates by increasing the local donor concentration through tethering of the donor to the CRISPR nuclease. We tested this hypothesis by using chimeric proteins between LbCas12a as a CRISPR-associated endonuclease and the HUH EN from Faba Bean Necrotic Yellow Virus in soybean (Glycine max). Two fusion protein configurations were tested to integrate a 70-nt oligonucleotide donor into a commercially important target site using protoplasts and in planta transformation. Site-directed integration rates of the donor DNA, when tethered to the fusion protein, reached about 26% in plants and were up to four-fold higher than in untethered controls. Integrations via canonical homology-directed repair or non-homologous end joining were promoted by tethering in a similar fashion. This study is the first demonstration of HUH EN-associated tethering to improve site-directed DNA integration in plants.

Oxidative stress involves enormously in the development of chronic inflammatory bone disease, wherein the overproduction of reactive oxygen species (ROS) negatively impacts the bone remodeling via promoting osteoclastogenesis and inhibiting osteogenesis. Lacking effective therapies highlights the importance of finding novel treatments. Our previous study screened a novel bioactive peptide D7 and demonstrated it could enhance the cell behaviors and protect bone marrow mesenchymal stem cells (BMSCs). Since BMSCs are progenitor cells of osteoblast (OB), we therefore ask whether D7 could also protect against the progress of inflammatory osteolysis. To validate our hypothesis and elucidate the underlying mechanisms, we first performed network pharmacology-based analysis according to the molecule structure of D7, and then followed by pharmacological evaluation on D7 by in vitro lipopolysaccharide(LPS)-induced models. The result from network pharmacology identified 20 candidate targets of D7 for inflammatory osteolysis intervention. The further analysis of Gene Ontology (GO)/KEGG pathway enrichment suggested the therapeutic effect of D7 may primarily affect osteoclast (OC) differentiation and function during the inflammatory osteolysis. Through validating the real effects of D7 on OC and OB as postulated, results demonstrated suppressive effects of D7 on LPS-stimulated OC differentiation and resorption, via the inhibition on OC marker genes. Contrarily, by improving the expression of OB marker genes, D7 displayed promotive effects on OB differentiation and alleviated LPS-induced osteogenic damage. Further mechanism study revealed that D7 could reduce LPS-induced ROS formation and strengthen antioxidants expressions in both OC and OB precursors, ameliorating LPS-triggered redox imbalance in bone remodeling. Taken together, our findings unveiled therapeutic effects of D7 against LPS-induced inflammatory osteolysis through the suppression of oxidative stress and the restoration of the bone remodeling process, providing a new therapeutic candidate for chronic inflammatory bone diseases.

Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis. Retraining models leads to high latency and complex pipelines, which are impractical in clinical settings. The situation becomes more severe for ultrasound image analysis because of their large appearance shifts. In this paper, we propose a novel method for robust segmentation under unknown appearance shifts. Our contribution is three-fold. First, we advance a one-stage plug-and-play solution by embedding hierarchical style transfer units into a segmentation architecture. Our solution can remove appearance shifts and perform segmentation simultaneously. Second, we adopt Dynamic Instance Normalization to conduct precise and dynamic style transfer in a learnable manner, rather than previously fixed style normalization. Third, our solution is fast and lightweight for routine clinical adoption. Given 400*400 image input, our solution only needs an additional 0.2ms and 1.92M FLOPs to handle appearance shifts compared to the baseline pipeline. Extensive experiments are conducted on a large dataset from three vendors demonstrate our proposed method enhances the robustness of deep segmentation models., Comment: Accepted by IEEE ISBI 2021

Accurate standard plane (SP) localization is the fundamental step for prenatal ultrasound (US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical diagnosis. 2D US has to perform scanning for each SP, which is time-consuming and operator-dependent. While 3D US containing multiple SPs in one shot has the inherent advantages of less user-dependency and more efficiency. Automatically locating SP in 3D US is very challenging due to the huge search space and large fetal posture variations. Our previous study proposed a deep reinforcement learning (RL) framework with an alignment module and active termination to localize SPs in 3D US automatically. However, termination of agent search in RL is important and affects the practical deployment. In this study, we enhance our previous RL framework with a newly designed adaptive dynamic termination to enable an early stop for the agent searching, saving at most 67% inference time, thus boosting the accuracy and efficiency of the RL framework at the same time. Besides, we validate the effectiveness and generalizability of our algorithm extensively on our in-house multi-organ datasets containing 433 fetal brain volumes, 519 fetal abdomen volumes, and 683 uterus volumes. Our approach achieves localization error of 2.52mm/10.26 degrees, 2.48mm/10.39 degrees, 2.02mm/10.48 degrees, 2.00mm/14.57 degrees, 2.61mm/9.71 degrees, 3.09mm/9.58 degrees, 1.49mm/7.54 degrees for the transcerebellar, transventricular, transthalamic planes in fetal brain, abdominal plane in fetal abdomen, and mid-sagittal, transverse and coronal planes in uterus, respectively. Experimental results show that our method is general and has the potential to improve the efficiency and standardization of US scanning., Comment: Accepted by IEEE Transactions on Medical Imaging (12 pages, 8 figures, 11 tabels)

Standard plane recognition plays an important role in prenatal ultrasound (US) screening. Automatically recognizing the standard plane along with the corresponding anatomical structures in US image can not only facilitate US image interpretation but also improve diagnostic efficiency. In this study, we build a novel multi-label learning (MLL) scheme to identify multiple standard planes and corresponding anatomical structures of fetus simultaneously. Our contribution is three-fold. First, we represent the class correlation by word embeddings to capture the fine-grained semantic and latent statistical concurrency. Second, we equip the MLL with a graph convolutional network to explore the inner and outer relationship among categories. Third, we propose a novel cluster relabel-based contrastive learning algorithm to encourage the divergence among ambiguous classes. Extensive validation was performed on our large in-house dataset. Our approach reports the highest accuracy as 90.25\(\%\) for standard planes labeling, 85.59\(\%\) for planes and structures labeling and mAP as 94.63\(\%\). The proposed MLL scheme provides a novel perspective for standard plane recognition and can be easily extended to other medical image classification tasks.

3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic information not contained in 2D US. Moreover, 3D US can contain multiple standard planes (SPs) in one shot. Thus, automatically localizing SPs in 3D US has the potential to improve user-independence and scanning-efficiency. However, manual SP localization in 3D US is challenging because of the low image quality, huge search space and large anatomical variability. In this work, we propose a novel multi-agent reinforcement learning (MARL) framework to simultaneously localize multiple SPs in 3D US. Our contribution is four-fold. First, our proposed method is general and it can accurately localize multiple SPs in different challenging US datasets. Second, we equip the MARL system with a recurrent neural network (RNN) based collaborative module, which can strengthen the communication among agents and learn the spatial relationship among planes effectively. Third, we explore to adopt the neural architecture search (NAS) to automatically design the network architecture of both the agents and the collaborative module. Last, we believe we are the first to realize automatic SP localization in pelvic US volumes, and note that our approach can handle both normal and abnormal uterus cases. Extensively validated on two challenging datasets of the uterus and fetal brain, our proposed method achieves the average localization accuracy of 7.03 degrees/1.59mm and 9.75 degrees/1.19mm. Experimental results show that our light-weight MARL model has higher accuracy than state-of-the-art methods., Accepted by Medical Image Analysis (10 figures, 8 tabels)

Deep Neural Networks (DNNs) suffer from the performance degradation when image appearance shift occurs, especially in ultrasound (US) image segmentation. In this paper, we propose a novel and intuitive framework to remove the appearance shift, and hence improve the generalization ability of DNNs. Our work has three highlights. First, we follow the spirit of universal style transfer to remove appearance shifts, which was not explored before for US images. Without sacrificing image structure details, it enables the arbitrary style-content transfer. Second, accelerated with Adaptive Instance Normalization block, our framework achieved real-time speed required in the clinical US scanning. Third, an efficient and effective style image selection strategy is proposed to ensure the target-style US image and testing content US image properly match each other. Experiments on two large US datasets demonstrate that our methods are superior to state-of-the-art methods on making DNNs robust against various appearance shifts., IEEE International Symposium on Biomedical Imaging (IEEE ISBI 2020)

3D ultrasound (US) can facilitate detailed prenatal examinations for fetal growth monitoring. To analyze a 3D US volume, it is fundamental to identify anatomical landmarks of the evaluated organs accurately. Typical deep learning methods usually regress the coordinates directly or involve heatmap-matching. However, these methods struggle to deal with volumes with large sizes and the highly-varying positions and orientations of fetuses. In this work, we exploit an object detection framework to detect landmarks in 3D fetal facial US volumes. By regressing multiple parameters of the landmark-centered bounding box (B-box) with a strict criteria, the proposed model is able to pinpoint the exact location of the targeted landmarks. Specifically, the model uses a 3D region proposal network (RPN) to generate 3D candidate regions, followed by several 3D classification branches to select the best candidate. It also adopts an IoU-balance loss to improve communications between branches that benefits the learning process. Furthermore, it leverages a distance-based graph prior to regularize the training and helps to reduce false positive predictions. The performance of the proposed framework is evaluated on a 3D US dataset to detect five key fetal facial landmarks. Results showed the proposed method outperforms some of the state-of-the-art methods in efficacy and efficiency., Comment: IEEE International Symposium on Biomedical Imaging (IEEE ISBI 2020)

3D ultrasound (US) is widely used due to its rich diagnostic information, portability and low cost. Automated standard plane (SP) localization in US volume not only improves efficiency and reduces user-dependence, but also boosts 3D US interpretation. In this study, we propose a novel Multi-Agent Reinforcement Learning (MARL) framework to localize multiple uterine SPs in 3D US simultaneously. Our contribution is two-fold. First, we equip the MARL with a one-shot neural architecture search (NAS) module to obtain the optimal agent for each plane. Specifically, Gradient-based search using Differentiable Architecture Sampler (GDAS) is employed to accelerate and stabilize the training process. Second, we propose a novel collaborative strategy to strengthen agents’ communication. Our strategy uses recurrent neural network (RNN) to learn the spatial relationship among SPs effectively. Extensively validated on a large dataset, our approach achieves the accuracy of 7.05\(^{\circ }\)/2.21 mm, 8.62\(^{\circ }\)/2.36 mm and 5.93\(^{\circ }\)/0.89 mm for the mid-sagittal, transverse and coronal plane localization, respectively. The proposed MARL framework can significantly increase the plane localization accuracy and reduce the computational cost and model size.

Background Platelet-rich plasma (PRP) provides a nonsurgical approach for treating osteoarthritis (OA). Exosomes that play vital roles in intercellular communication have been studied extensively. Here, we investigated the therapeutic potential and molecular mechanism of exosomes derived from PRP (PRP-Exos) in alleviating OA. Methods Exosomes derived from PRP(PRP-Exos) were isolated and purified using the exoEasy Maxi Kit and then identified and analyzed. Primary rabbit chondrocytes were isolated and treated with interleukin 1 beta (IL-1β) to establish the OA model in vitro. Proliferation, migration, and apoptosis assays were measured and compared between PRP-Exos and activated PRP (PRP-As) to evaluate the therapeutic effects on OA. The mechanism involving the Wnt/β-catenin signaling pathway was investigated by Western blot analysis. In vivo, we established animal knee OA model by surgery to compare the therapeutic effect of PRP-Exos and PRP-As. Results We successfully isolated and purified exosomes from PRP using the exoEasy Maxi Kit. We also isolated and identified chondrocytes from the New Zealand white rabbit and established the IL-1β-induced OA model; meanwhile, PRP-Exos and PRP-As both inhibited the release of tumor necrosis factor-α(TNF-α) and there was no statistically significant difference between the two. In proliferation, migration, scratch assay, the promoting effect of PRP-Exos was significantly more better than PRP-As. Furthermore, PRP-Exos could significantly decreased apoptotic rate of OA chondrocyte compared with PRP-As. In Western blot analysis, the expression of β-catenin, and RUNX2, Wnt5a were increased in IL-1β-treated chondrocytes, but PRP-Exos and PRP-As could both reverse these changes, and the reversal effect of the former was better than the latter. In vivo, we found that both PRP-Exos and PRP-As displayed the progression of OA, and the effect of PRP-Exos was obviously better than PRP-As by chondrocyte count and Osteoarthritis Research Society International (OARSI) scoring system. Conclusion The therapeutic effects of PRP-Exos on OA were similar or better compared with those of PRP-As in vitro or in vivo. PRP-Exos acting as carriers containing growth factors derived from PRP present a novel therapy for OA by activating the Wnt/β-catenin signaling pathway.

PURPOSE The purpose of this study was to compare the diagnostic value of Young's modulus (E) and shear modulus (G) in the differential diagnosis of benign and malignant breast masses using sound touch elastography (STE) and to explore the relationship between G and E in breast lesions. METHODS A total of 96 consecutive women with 110 pathologically confirmed breast masses were included. All masses were detected by conventional and STE ultrasound. Emean, Emax, Emin, ESD, Gmean, Gmax, Gmin, and GSD were determined and evaluated for evidence of significant differences between benign and malignant breast masses. Receiver operator characteristics were used to compare the diagnostic efficacy of E and G and to determine the G cutoff value that would aid in the differential diagnosis of breast cancer. RESULTS Emean, Emax, ESD, Gmean, Gmax, and GSD in cases of malignant breast masses were significantly higher than those in cases of benign masses (P < 0.05). There was no significant difference between Emin and Gmin (P = 0.565). In applying the Emean, Emax, ESD, Gmean, Gmax, and GSD to the receiver operator characteristics: (1) the area under the curve (AUC) of Gmean and Gmax is greater than the AUC of Emean and Emax, and the AUC of ESD is equal to the AUC of GSD. (2) The sensitivity and specificity were highest when the Gmean was 10.14 kPa. They were 84.1% and 80.3% respectively. (3) The sensitivity and specificity were highest when the Gmax was 52.20 kPa. They were 88.6% and 87.9% respectively. CONCLUSIONS These preliminary results of STE evaluation of breast masses suggest that the diagnostic value of G is greater than E. Furthermore, STE is a valuable tool in the differential diagnosis of breast lesions.

Genetically modified (GM) crops have been developed and commercialized that utilize double stranded RNAs (dsRNA) to suppress a target gene(s), producing virus resistance, nutritional and quality traits. MON 87411 is a GM maize variety that leverages dsRNAs to selectively control corn rootworm through production of a 240 base pair (bp) dsRNA fragment targeting for suppression the western corn rootworm (Diabrotica virgifera virgifera) Snf7 gene (DvSnf7). A bioinformatics assessment found that endogenous corn small RNAs matched ∼450 to 2300 unique RNA transcripts that likely code for proteins in rat, mouse, and human, demonstrating safe dsRNA consumption by mammals. Mice were administered DvSnf7 RNA (968 nucleotides, including the 240 bp DvSnf7 dsRNA) at 1, 10, or 100 mg/kg by oral gavage in a 28-day repeat dose toxicity study. No treatment-related effects were observed in body weights, food consumption, clinical observations, clinical chemistry, hematology, gross pathology, or histopathology endpoints. Therefore, the No Observed Adverse Effect Level (NOAEL) for DvSnf7 RNA was 100 mg/kg, the highest dose tested. These results demonstrate that dsRNA for insect control does not produce adverse health effects in mammals at oral doses millions to billions of times higher than anticipated human exposures and therefore poses negligible risk to mammals.

The use of dsRNA to control insect pests via the RNA interference (RNAi) pathway is being explored by researchers globally. However, with every new class of insect control compounds, the evolution of insect resistance needs to be considered, and understanding resistance mechanisms is essential in designing durable technologies and effective resistance management strategies. To gain insight into insect resistance to dsRNA, a field screen with subsequent laboratory selection was used to establish a population of DvSnf7 dsRNA-resistant western corn rootworm, Diabrotica virgifera virgifera, a major maize insect pest. WCR resistant to ingested DvSnf7 dsRNA had impaired luminal uptake and resistance was not DvSnf7 dsRNA-specific, as indicated by cross resistance to all other dsRNAs tested. No resistance to the Bacillus thuringiensis Cry3Bb1 protein was observed. DvSnf7 dsRNA resistance was inherited recessively, located on a single locus, and autosomal. Together these findings will provide insights for dsRNA deployment for insect pest control.

Hybrid crops produce higher yields than their inbred parents due to heterosis. For high purity of hybrid seeds, it is critical to eliminate self-pollination. Manual or mechanical removal of male parts (such as detasseling in maize) is labor-intensive, fuel and time-consuming, and can cause physical damage to female plants, resulting in significant seed yield reductions. Many male-sterility systems either require a maintainer for male-sterile line propagation or are often affected by environmental factors. Roundup® Hybridization System (RHS) utilizes glyphosate to induce male sterility, which effectively eliminates the need for maintainer lines and removal of male parts for commercial hybrid seed production. The first-generation RHS (RHS1) is based on low expression of a glyphosate-insensitive 5-enolpyruvylshikimate-3-phosphate synthase (CP4 EPSPS) in pollen. This report presents the second-generation RHS (RHS2) technology built on RNA interference (RNAi) combined with CP4 EPSPS. It utilizes maize endogenous male tissue-specific small interfering RNAs (mts-siRNAs) to trigger cleavage of the CP4 EPSPS mRNA specifically in tassels, resulting in glyphosate-sensitive male cells due to lack of the CP4 EPSPS protein. Male sterility is then induced by glyphosate application at the stages critical for pollen development, and the male-sterile plants are used as the female parent to produce hybrid seed. The endogenous mts-siRNAs are conserved across maize germplasms, and the inducible male sterility was replicated in representative germplasms through introgression of a CP4 EPSPS transgene containing the mts-siRNA target sequence. This technology combines the relative simplicity and convenience of a systemic herbicide spray methodology with targeted protein expression to create an inducible male sterility system for industrial production of row crop hybrid seeds in an environmentally-independent manner.

Environmental RNAi (eRNAi) is a sequence-specific regulation of endogenous gene expression in a receptive organism by exogenous double-stranded RNA (dsRNA). Although demonstrated under artificial dietary conditions and via transgenic plant presentations in several herbivorous insects, the magnitude and consequence of exogenous dsRNA uptake and the role of eRNAi remains unknown under natural insect living conditions. Our analysis of coleopteran insects sensitive to eRNAi fed on wild-type plants revealed uptake of plant endogenous long dsRNAs, but not small RNAs. Subsequently, the dsRNAs were processed into 21 nt siRNAs by insects and accumulated in high quantities in insect cells. No accumulation of host plant-derived siRNAs was observed in lepidopteran larvae that are recalcitrant to eRNAi. Stability of ingested dsRNA in coleopteran larval gut followed by uptake and transport from the gut to distal tissues appeared to be enabling factors for eRNAi. Although a relatively large number of distinct coleopteran insect-processed plant-derived siRNAs had sequence complementarity to insect transcripts, the vast majority of the siRNAs were present in relatively low abundance, and RNA-seq analysis did not detect a significant effect of plant-derived siRNAs on insect transcriptome. In summary, we observed a broad genome-wide uptake of plant endogenous dsRNA and subsequent processing of ingested dsRNA into 21 nt siRNAs in eRNAi-sensitive insects under natural feeding conditions. In addition to dsRNA stability in gut lumen and uptake, dosage of siRNAs targeting a given insect transcript is likely an important factor in order to achieve measurable eRNAi-based regulation in eRNAi-competent insects that lack an apparent silencing amplification mechanism.

Fused deposition modelling is a simple additive manufacturing technology utilising fine filament extrusion of predominantly thermoplastic materials to build 3D objects layer by layer. This research explores the feasibility and the factors involved in using fused deposition modelling to produce natural fibre reinforced composite components. Uniform 3-mm filaments of both hemp and harakeke (Phormium tenax) in varying weight percentages within polylactic acid (PLA) polymer were successfully produced and used to print tensile test samples. Tensile test results supported harakeke to be a useful fibre in terms of mechanical properties achieved which surpassed the Young’s modulus and tensile strength of plain PLA samples by 42.3% and 5.4%, respectively.

Functional small RNAs, such as short interfering RNAs (siRNAs) and microRNAs (miRNAs), exist in freshly consumed fruits and vegetables. These siRNAs can be derived either from endogenous sequences or from viruses that infect them. Symptomatic tomatoes, watermelons, zucchini, and onions were purchased from grocery stores and investigated by small RNA sequencing. By aligning the obtained small RNA sequences to sequences of known viruses, four different viruses were identified as infecting these fruits and vegetables. Many of these virally derived small RNAs along with endogenous small RNAs were found to be highly complementary to human genes. However, the established history of safe consumption of these vegetables suggests that this sequence homology has little biological relevance. By extension, these results provide evidence for the safe use by humans and animals of genetically engineered crops using RNA-based suppression technologies, especially vegetable crops with virus resistance conferred by expression of siRNAs or miRNAs derived from viral sequences.

Long double-stranded RNAs (long dsRNAs) are precursors for the effector molecules of sequence-specific RNA-based gene silencing in eukaryotes. Plant cells can contain numerous endogenous long dsRNAs. This study demonstrates that such endogenous long dsRNAs in plants have sequence complementarity to human genes. Many of these complementary long dsRNAs have perfect sequence complementarity of at least 21 nucleotides to human genes; enough complementarity to potentially trigger gene silencing in targeted human cells if delivered in functional form. However, the number and diversity of long dsRNA molecules in plant tissue from crops such as lettuce, tomato, corn, soy and rice with complementarity to human genes that have a long history of safe consumption supports a conclusion that long dsRNAs do not present a significant dietary risk.

In a virus-infected plant, small interfering RNAs (siRNAs) corresponding to the viral genome form a large proportion of the small RNA population. It is possible to reassemble significant portions of the virus sequence from overlapping siRNA sequences and use these to identify the virus. We tested this technique with a resistance-breaking and a non-resistance-breaking strain of tomato spotted wilt virus (TSWV). We were able to assemble contigs covering 99% of the genomes of both viruses. The abundance of TSWV siRNAs allowed us to detect TSWV at early time points before the onset of symptoms, at levels too low for conventional detection. Combining traditional and bioinformatic detection methods, we also measured how replication of the resistance-breaking strain differed from the non-resistance-breaking strain in susceptible and resistant tomato varieties. We repeated this technique in identification of a squash-infecting geminivirus and also used it to identify an unspecified tospovirus.

Small interfering RNAs (siRNAs) and microRNAs (miRNAs) are effector molecules of RNA interference (RNAi), a highly conserved RNA-based gene suppression mechanism in plants, mammals and other eukaryotes. Endogenous RNAi-based gene suppression has been harnessed naturally and through conventional breeding to achieve desired plant phenotypes. The present study demonstrates that endogenous small RNAs, such as siRNAs and miRNAs, are abundant in soybean seeds, corn kernels, and rice grain, plant tissues that are traditionally used for food and feed. Numerous endogenous plant small RNAs were found to have perfect complementarity to human genes as well as those of other mammals. The abundance of endogenous small RNA molecules in grain from safely consumed food and feed crops such as soybean, corn, and rice and the homology of a number of these dietary small RNAs to human and animal genomes and transcriptomes establishes a history of safe consumption for dietary small RNAs.

Successful application of posttranscriptional gene silencing (PTGS) for gene function study in both plants and animals depends on high target specificity and silencing efficiency. By computational analysis with genome and/or transcriptome sequences of 25 plant species, we predicted that about 50% to 70% of gene transcripts in plants have potential off-targets when used for PTGS that could obscure experimental results. We have developed a publicly available Web-based computational tool called siRNA Scan to identify potential off-targets during PTGS. Some of the potential off-targets obtained from this tool were tested by measuring the amount of off-target transcripts using quantitative reverse transcription-PCR. Up to 50% of the predicted off-target genes tested in plants were actually silenced when tested experimentally. Our results suggest that a high risk of off-target gene silencing exists during PTGS in plants. Our siRNA Scan tool is useful to design better constructs for PTGS by minimizing off-target gene silencing in both plants and animals.

An improved quick detection method for fundamental wave and harmonics in single-phase AC source is presented. Single-phase inverter produces amount of harmonics, which directly affect the quality of electric energy[1-3]. This paper propose an improved method, which can fully detect the fundamental wave and harmonic. The method applies orthogonal transformation theory. The principle is demonstrated, and the results of Matlab simulation is presented to verify the validity of proposed theory.

The role of non-coding RNAs (ncRNAs), both short and long ncRNAs, in the regulation of gene expression has become evident in recent years. Non-coding RNA-based regulation is achieved through a variety of mechanisms; some are relatively well-characterized, while others are much less understood. MicroRNAs (miRNAs), a class of endogenous small RNAs, function as master regulators of gene expression in eukaryotic organisms. A notable, recently discovered role for long ncRNAs is that of miRNA decoys, also referred to as target mimics or sponges, in which long ncRNAs carry a short stretch of sequence sharing homology to miRNA-binding sites in endogenous targets. As a consequence, miRNA decoys are able to sequester and inactivate miRNA function. Engineered miRNA decoys are also efficacious and useful tools for studying gene function. We recently demonstrated that the potential of miRNA decoys to inactivate miRNAs in the model plants Arabidopsis thaliana and Nicotiana benthamiana is dependent on the level of sequence complementarity to miRNAs of interest. The flexibility of the miRNA decoy approach in sequence-dependent miRNA inactivation, backbone choice, ability to simultaneously inactivate multiple miRNAs, and more importantly, to achieve a desirable level of miRNA inactivation, makes it a potentially useful tool for crop improvement. This research addendum reports the functional extension of miRNA decoys from model plants to crops. Furthermore, endogenous miRNA decoys, first described in plants, have been proposed to play a significant role in regulating the transcriptome in eukaryotes. Using computational analysis, we have identified numerous endogenous sequences with potential miRNA decoy activity for conserved miRNAs in several plant species. Our data suggest that endogenous miRNA decoys can be widespread in plants and may be a component of the global gene expression regulatory network in plants.

Background Plants contain significant quantities of small RNAs (sRNAs) derived from various sRNA biogenesis pathways. Many of these sRNAs play regulatory roles in plants. Previous analysis revealed that numerous sRNAs in corn, rice and soybean seeds have high sequence similarity to animal genes. However, exogenous RNA is considered to be unstable within the gastrointestinal tract of many animals, thus limiting potential for any adverse effects from consumption of dietary RNA. A recent paper reported that putative plant miRNAs were detected in animal plasma and serum, presumably acquired through ingestion, and may have a functional impact in the consuming organisms. Results To address the question of how common this phenomenon could be, we searched for plant miRNAs sequences in public sRNA datasets from various tissues of mammals, chicken and insects. Our analyses revealed that plant miRNAs were present in the animal sRNA datasets, and significantly miR168 was extremely over-represented. Furthermore, all or nearly all (>96%) miR168 sequences were monocot derived for most datasets, including datasets for two insects reared on dicot plants in their respective experiments. To investigate if plant-derived miRNAs, including miR168, could accumulate and move systemically in insects, we conducted insect feeding studies for three insects including corn rootworm, which has been shown to be responsive to plant-produced long double-stranded RNAs. Conclusions Our analyses suggest that the observed plant miRNAs in animal sRNA datasets can originate in the process of sequencing, and that accumulation of plant miRNAs via dietary exposure is not universal in animals.

Background Since whole genome sequences of rice were made publically accessible, the number of articles onnew rice genes has increased remarkably. The Committee on Gene Symbolization, Nomenclature and Linkage(CGSNL) of the Rice Genetics Cooperative published the gene nomenclature system for rice and encouragedresearchers to follow the rules before publishing their results. The CGSNL provides an on-line registration systemfor newly identified rice genes to prevent conflicts and/or duplication of gene name in journal articles. Findings Recently, the CGSNL surveyed genes in the rice WRKY family in published journal articles and foundseveral duplicated gene names. Conclusions To discuss and resolve inconsistencies in WRKY gene nomenclature, the rice WRKY working groupwas established and redefined the nomenclature. This report announces the conclusion.