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Bacterial blight (BB) of rice is a devastating disease caused by Xanthomonas oryzae pv. oryzae (Xoo). The evolution of new pathogenic races of bacterial blight pathogen is always a potential threat for rice production. The deployment of pathotype-specific resistant genes in the host plants is a feasible strategy to develop BB-resistant varieties. Therefore, continuous disease monitoring, identification of Xoo pathotypes, and their distribution are crucial to managing BB. In this study, 71 Xoo isolates were collected from the Godavari delta in Andhra Pradesh (India) and their virulence profiles on rice BB differentials were characterized. Data revealed that different International Rice Bacterial Blight (IRBB) lines with single BB resistance genes were susceptible to 73.2%-97.2% of the isolates, except IRBB13 (possessing BB resistance gene, xa13) which showed a moderately susceptible or susceptible reaction to 47.9% of the isolates. Three gene combination rice differentials like IRBB56 (Xa4 + xa5 + xa13), IRBB57 (Xa4 + xa5 + Xa21), IRBB58 (Xa4 + xa13 + Xa21), and IRBB59 (xa5 + xa13 + Xa21) showed very broad-spectrum resistance to majority of the Xoo isolates from the region. None of the tested Xoo isolates were virulent on IRBB58 (Xa4 + xa13 + Xa21), IRBB60 (Xa4 + xa5 + xa13 + Xa21), and IRBB66 (Xa4 + xa5 + Xa7 + xa13 + Xa21). Based on the virulence reaction, 71 Xoo isolates were grouped into 10 major pathotypes. Highly virulent pathotypes viz., IXoPt # 14, 17, 19, and 22 can break the resistance of major BB-resistant genes and were commonly distributed throughout the surveyed regions. Genotypic data of 71 Xoo isolates using J3 primer divided them into three major clusters. Cluster I consisted of 24 Xoo isolates that belonged to pathotype IXoPt-19. Cluster II consisted of 41 Xoo isolates belonging to seven different pathotypes, and Cluster III was composed of six isolates from three different pathotypes. The findings of this study will be helpful to develop rice varieties with pathotype-specific broad-spectrum resistance against BB.

Rice yellow mottle virus (RYMV) causes one of the most devastating rice diseases in Africa. Management of RYMV is challenging. Genetic resistance provides the most effective and environment- friendly control. The recessive resistance locus rymv2 (OsCPR5.1) had been identified in African rice (O. glaberrima), however, introgression into O. sativa ssp. japonica and indica remains challenging due to crossing barriers. Here, we evaluated whether CRISPR/Cas9 genome editing of the two rice nucleoporin paralogs OsCPR5.1 (RYMV2) and OsCPR5.2 can be used to introduce RYMV resistance into the japonica variety Kitaake. Both paralogs had been shown to complement the defects of the Arabidopsis atcpr5 mutant, indicating partial redundancy. Despite striking sequence and structural similarities between the two paralogs, only oscpr5.1 loss-of-function mutants were fully resistant, while loss-of-function oscpr5.2 mutants remained susceptible, intimating that OsCPR5.1 plays a specific role in RYMV susceptibility. Notably, edited lines with short in-frame deletions or replacements in the N-terminal domain (predicted to be unstructured) of OsCPR5.1 were hypersusceptible to RYMV. In contrast to mutations in the single Arabidopsis AtCPR5 gene, which caused severely dwarfed plants, oscpr5.1 and oscpr5.2 single knockout mutants show neither substantial growth defects nor symptoms indicative of programmed cell death, possibly reflecting functional redundancy of the isoforms regarding other important functions. The specific editing of OsCPR5.1, while maintaining OsCPR5.2 activity, provides a promising strategy for generating RYMV-resistance in elite Oryza sativa lines as well as for effective stacking with other RYMV resistance genes or other traits.

SummaryRice yellow mottle virus (RYMV) causes one of the most devastating rice diseases in Africa. Management of RYMV is challenging. Genetic resistance provides the most effective and environment-friendly control. The recessive resistance locusrymv2(OsCPR5.1) had been identified in African rice (O. glaberrima), however, introgression intoO. sativa ssp. japonicaandindicaremains challenging due to crossing barriers. Here, we evaluated whether CRISPR/Cas9 genome editing of the two rice nucleoporin paralogsOsCPR5.1(RYMV2) andOsCPR5.2can be used to introduce RYMV resistance into thejaponicavariety Kitaake. Both paralogs had been shown to complement the defects of the Arabidopsisatcpr5mutant, indicating partial redundancy. Despite striking sequence and structural similarities between the two paralogs, only oscpr5.1loss-of-function mutants were fully resistant, while loss-of-functionoscpr5.2mutants remained susceptible, intimating thatOsCPR5.1plays a specific role in RYMV susceptibility. Notably, edited lines with short in-frame deletions or replacements in the N-terminal domain (predicted to be unstructured) ofOsCPR5.1were hypersusceptible to RYMV. In contrast to mutations in the single ArabidopsisAtCPR5gene, which caused severely dwarfed plants,oscpr5.1andoscpr5.2singleknockoutmutants show neither substantial growth defects nor symptoms indicative of programmed cell death, possibly reflecting functional redundancy of the isoforms regarding other important functions. The specific editing ofOsCPR5.1, while maintainingOsCPR5.2activity, provides a promising strategy for generating RYMV-resistance in eliteOryza sativalines as well as for effective stacking with other RYMV resistance genes or other traits.

Bacterial leaf blight (BB) of rice, caused byXanthomonas oryzaepv.oryzae(Xoo), threatens global food security and the livelihood of small-scale rice producers. Analyses ofXoocollections from Asia, Africa and the Americas demonstrated surprising continental segregation, despite robust global rice trade. Here, we report unprecedented BB outbreaks in Tanzania. The causative strains, unlike endemicXoo, carry Asian-type TAL effectors targeting the sucrose transporterSWEET11aand suppressingXa1. Phylogenomics clustered these strains withXoostrains from China. African rice varieties do not carry suitable resistance genes. To protect African rice production against this emerging threat, we developed a hybrid CRISPR-Cas9/Cpf1 system to edit six TALe-binding elements in threeSWEETpromoters of the East African elite variety Komboka. The edited lines show broad-spectrum resistance against Asian and African strains ofXoo, including strains recently discovered in Tanzania. This strategy could help to protect global rice crops from BB pandemics.

Autism Spectrum Disorder (ASD) is widely developing neurodevelopmental disorder. The ASD is a lifelong neurodevelopmental disorder that effects the social interaction and behavior of human beings. In this review, we presented structural magnetic resonance imaging (sMRI) studies that were examined in structural brain abnormalities of ASD patients. To date sMRI results were distinct, due to the diversity of the ASD itself. The accelerated brain volume is the uniform finding of ASD. However, the recent investigation reports have started to interpret the structural abnormalities of ASD patient’s brain. The most common abnormalities found in total brain volume, cerebellum, amygdala, hippocampal, basal ganglia, insula, gray and white matter. Limited sMRI research has been done on less than 2 years ASD children. Future research should include autistic children less than 2 years along with functional MRI and diffusion tensor imaging.

Virulence of Xanthomonas oryzae pv. oryzae (Xoo), which causes bacterial blight of rice, depends on induction of host SWEET sucrose efflux transporters. It remained unknown whether secreted sucrose serves bacterial nutrition or host defense. Here we identified the sux sucrose uptake/utilization locus of Xoo and demonstrate that it is necessary and sufficient for sucrose acquisition. Induction of sux genes during infection closely tracked induction of rice SWEET11a. sux mutants were defective in swimming, swarming, extracellular polysaccharide (EPS) production and biofilm formation. EPS synthesis in mutants was restored by the quorum-sensing factor DSF. Notably, transcripts for rate limiting steps in DSF production were unaffected by sucrose, transcripts of the DSF receptor were sucrose-inducible and increased during infection, indicating sensitization to DSF in response to sucrose supply. Sucrose induced the sigma factors RpoN1 and RpoN2 that regulate swimming, EPS and virulence. Furthermore, in contrast to Xanthomonas axonopodis pv. manihotis, virulence of Xoo depended critically on sux gene function. Together, pathogen-induced sucrose efflux from host cells likely induces bacterial sigma factors and sensitizes quorum signaling necessary for biofilm formation and colonization of the xylem, serves as energy source for swimming against the xylem stream, and as nutrient for growth.Author summaryIf we want to efficiently protect plants against infections, we need to understand the disease mechanisms. Bacterial blight is a major scourge for rice production in Asia and Africa. We had found that disease-causing bacteria use a set of keys, so-called TAL effectors, to switch on sugar transporter genes in rice leaves causing sucrose release around the bacteria. A key question was whether the sugars act primarily in activation of host defense, or serve as nutrients and signals for bacterial infection. Here we provide evidence that both the ability to attack as well as the growth of bacteria depend on sucrose uptake. We unravel a regulatory network including transcriptional regulators, quorum sensing, swimming, biofilm production and virulence that all depend on sucrose uptake. These discoveries may prove to be crucial for the development of strategies for protecting rice against this disease.

Rice is the most important staple crop in the developing world and its productivity is critical for food security, development, and poverty elimination. Worldwide, approximately 900 million people from low-income households depend on rice. Ninety percent of the global rice is produced in Asia, mainly by small-scale producers who farm 0.4 ha or less. Productivity is increasingly threatened by biotic stresses from viruses, bacteria, fungi, nematodes, insects, and arachnids. Nowadays, genome editing provides unique opportunities to generate variants of elite lines that are resistant to one or multiple diseases. We provide examples in which the simplest form of genome editing is used to block pathogens from exploiting host susceptibilities, thereby creating a robust broad-spectrum resistance. We highlight the editing of promoter sequences of rice SWEET sugar transporters, which led to resistance against Bacterial leaf blight (BLB) as a blueprint for the use of new breeding technologies in fighting other important crop diseases and for stacking with other useful traits. Notably, successful strategies for protecting against pathogen infections require more than just resistant rice lines, but also better maintenance and strategies to improve the living standards of small-scale producers.

RNAi mediated silencing of pectin degrading enzyme of R. solani gives a high level of resistance against sheath blight disease of rice. Rice sheath blight disease caused by Rhizoctonia solani Kuhn (telemorph; Thanatephorus cucumeris) is one of the most devastating fungal diseases which cause severe loss to rice grain production. In the absence of resistant cultivars, the disease is currently managed through fungicides which add to environmental pollution. To explore the potential of utilizing RNA interference (RNAi)-mediated resistance against sheath blight disease, we identified genes encoding proteins and enzymes involved in the RNAi pathway in this fungal pathogen. The RNAi target genes were deciphered by RNAseq analysis of a highly virulent strain of the R. solani grown in pectin medium. Additionally, pectin metabolism associated genes of R. solani were analyzed through transcriptome sequencing of infected rice tissues obtained from six diverse rice cultivars. One of the key candidate gene AG1IA_04727 encoding polygalacturonase (PG), which was observed to be significantly upregulated during infection, was targeted through RNAi to develop disease resistance. Stable expression of PG-RNAi construct in rice showed efficient silencing of AG1IA_04727 and suppression of sheath blight disease. This study highlights important information about the existence of RNAi machinery and key genes of R. solani which can be targeted through RNAi to develop pathogen-derived resistance, thus opening an alternative strategy for developing sheath blight-resistant rice cultivars.

In this paper we propose a segmentation algorithm for noisy Synthetic Aperture Radar (SAR) images. This method is based on k-means (KM) clustering and thresholding techniques. SAR images have huge employment in topography, remote sensing, and subsurface imaging. The segmentation of SAR images is always demanding because of the noise present in it. Speckle noise is the common noise present in SAR images. The median filter is utilized for noise removal. Clustering methods are customary segmentation techniques, but they do not give meticulous results. Hence we have performed image filtering and traditional thresholding methods along with clustering technique for effective results. In our proposed method, we have used k-means clustering method and Otsu thresholding for effective segmentation. Finally, morphological closing is performed for accurate results. The experimental results unveil that the proposed method has less error percentage.

In this paper, we propose an approach to detection and segmentation of liver tumors in noisy computed topography (CT) images. Image segmentation plays crucial role in medical image processing applications. Noise is quite common in medical images. It occurs while acquisition and transmission of images. The essential goal of this framework is to identify liver cancer by segmenting liver tumors from noisy CT scan images. Liver segmentation is difficult task in medical applications because inter-patient variability in size, shape and disease. In general CT scanning is used to inspect liver cancer. In this research work, the liver tumors are detected by the medical images in three stages, pre-processing stage, processing stage and detection stage. First in pre-processing stage, median filter is used to remove the noise from CT image, and then the denoised image is segmented by fuzzy c-means clustering (FCM) algorithm. Finally in the detection stage distance regularized level set evolution (DRLSE) is used to extract tumor boundaries. This algorithm is very much useful for identifying hepatocellular carcinoma (liver cancer). Experimental results on various noisy CT scan images show that the proposed method is efficient for extracting hepatic tumors from liver.

In this paper, we propose a novel framework for the segmentation of noisy images by incorporating the advantages of k-means clustering and distance regularized level set evolution (DRLSE). Level set methods and active contour models (ACMs) plays a vital role in the applications of image processing, robot vision, object recognition and computer vision. DRLSE model has recently become a powerful technique for image segmentation. DRLSE model eliminates the re-initialization problem in conventional level set method. DRLSE has been applied successfully into some fields like medical imaging, remote sensing and computer vision. However when it is applied to noisy images, It leads to significant drawbacks (number of iterations and computational time is increased). In order to avoid disadvantages of conventional DRLSE, we introduce a method to combine the median filtering, k-means clustering and DRLSE model. Firstly a noise free image is extracted by median filtering; then k-means clustering is applied to denoised image. The last stage is that the DRLSE model is applied for the extraction of object boundaries with pre segmentation process. The accuracy and the efficiency of the algorithm can be described on various noisy magnetic resonance (MR) brain images. The experiments show that our proposed method is more effective for noisy images.

Sheath blight disease of rice caused by Rhizoctonia solani is one of the most dreaded plant diseases faced by the rice farmers all over the world. None of the commercially cultivated rice varieties have sufficient level of field resistance, and the disease is presently being managed by chemical pesticides. In this study, 40 isolates of rice sheath blight pathogen, collected from diverse rice ecosystems from 12 different states of India, were characterized for their morphological, pathological and genetic variation. The isolates showed wide morphological variation in terms of size of sclerotia and abundance of sclerotia production. The virulence of each pathogen isolate was studied on four rice varieties, that is TN1, IR 64, Tetep and Swarnadhan in glasshouse, and observations were taken by measuring the relative lesion height. The relative lesion heights produced by these isolates on four different rice varieties varied widely. Genetic variation of the isolates was analysed using ISSR markers. The primers based on AG, GA, AC and CA repeats were informative and revealed polymorphism among the isolates. The polymorphism information content (PIC) of the primers ranged from 0.80 to 0.96, while the resolving power (Rp) ranged from 3.7 to 15.35. Largely, grouping of the isolates happened based on their geographical origin. One isolate from Titabar, Assam, and another from Adialabad, Telangana, were quite distinct from rest of the isolates.

RPHR-1005, the stable restorer line of the popular medium slender (MS) grain type rice hybrid, DRRH-3 was improved in this study for resistance against bacterial blight (BB) and blast diseases through marker-assisted backcross breeding (MABB). In this study, four major resistance genes (i.e., Xa21 and Xa33 for BB resistance and Pi2 and Pi54 for blast resistance) have been transferred to RPHR-1005 using RPBio Patho-1 (possessing Xa21 + Pi2), RPBio Patho-2 (possessing Xa21 + Pi54) and FBR1-15EM (possessing Xa33) as the donors. Foreground selection was carried out using PCR-based molecular markers specific for the target resistance genes and the major fertility restorer genes, Rf3 and Rf4, while background selection was carried out using a set of parental polymorphic rice SSR markers and backcrossing was continued uptoBC2 generation. At BC2F2, plants possessing the gene combination- Xa21 + Pi2, Xa21 + Pi54 and Xa33 in homozygous condition and with >92% recovery of the recurrent parent genome (RPG) were identified and intercrossed to combine all the four resistance genes. Twenty-two homozygous, pyramid lines of RPHR-1005 comprising of three single-gene containing lines, six 2-gene containing lines, eight 3-gene containing lines, and five 4-gene containing lines were identified among the double intercross lines at F3 generation (DICF3). They were then evaluated for their resistance against BB and blast, fertility restoration ability and for key agro-morphological traits. While single gene containing lines were resistant to either BB or blast, the 2-gene, 3-gene, and 4-gene pyramid lines showed good level of resistance against both and/or either of the two diseases. Most of the 2-gene, 3-gene, and 4-gene containing pyramid lines showed yield levels and other key agro-morphological and grain quality traits comparable to the original recurrent parent and showed complete fertility restoration ability, with a few showing higher yield as compared to RPHR-1005. Further, the experimental hybrids derived by crossing the gene-pyramid lines of RPHR-1005 with APMS6A (the female parent of DRRH-3), showed heterosis levels equivalent to or higher than DRRH-3. The results of present study exemplify the utility of MABB for targeted improvement of multiple traits in hybrid rice.

An innovative novel method for image segmentation is proposed in this paper, which combines the watershed transform, Improved FCM and level set method. The watershed transform is original used to pre-segment the image so as to get the initial partition of it. Some useful information of the primitive regions and boundaries can be obtained. The Improved fuzzy c-means (IFCM) was used to generate an initial contour curve which overcomes leaking at the boundary during the curve propagation. IFCM algorithm computes the fuzzy membership values for each pixel. On the source of IFCM the edge indicator function was redefined. Using the edge indicator function of an image was performed to extract the boundaries of objects on the origin of the pre-segmentation. Therefore, the proposed method is computationally efficient. The efficiency and accuracy of the algorithm is demonstrated. The above process of segmentation showed a considerable improvement in the evolution of the level set function.