The OsTIL1 lipocalin protects cell membranes from reactive oxygen species damage and maintains the 18:3-containing glycerolipid biosynthesis under cold stress in rice.

Lipocalins constitute a conserved protein family that binds to and transports a variety of lipids while fatty acid desaturases (FADs) are required for maintaining the cell membrane fluidity under cold stress. Nevertheless, it remains unclear whether plant lipocalins promote FADs for the cell membrane integrity under cold stress. Here, we identified the role of OsTIL1 lipocalin in FADs-mediated glycerolipid remodeling under cold stress. Overexpression and CRISPR/Cas9 mediated gene edition experiments demonstrated that OsTIL1 positively regulated cold stress tolerance by protecting the cell membrane integrity from reactive oxygen species damage and enhancing the activities of peroxidase and ascorbate peroxidase, which was confirmed by combined cold stress with a membrane rigidifier dimethyl sulfoxide or a H2 O2 scavenger dimethyl thiourea. OsTIL1 overexpression induced higher 18:3 content, and higher 18:3/18:2 and (18:2 + 18:3)/18:1 ratios than the wild type under cold stress whereas the gene edition mutant showed the opposite. Furthermore, the lipidomic analysis showed that OsTIL1 overexpression led to higher contents of 18:3-mediated glycerolipids, including galactolipids (monoglactosyldiacylglycerol and digalactosyldiacylglycerol) and phospholipids (phosphatidyl glycerol, phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl serine and phosphatidyl inositol) under cold stress. RNA-seq and enzyme linked immunosorbent assay analyses indicated that OsTIL1 overexpression enhanced the transcription and enzyme abundance of four ω-3 FADs (OsFAD3-1/3-2, 7, and 8) under cold stress. These results reveal an important role of OsTIL1 in maintaining the cell membrane integrity from oxidative damage under cold stress, providing a good candidate gene for improving cold tolerance in rice.

Expression of a dominant-negative AtNEET-H89C protein disrupts iron-sulfur metabolism and iron homeostasis in Arabidopsis.

Iron-sulfur (Fe-S) clusters play an essential role in plants as protein cofactors mediating diverse electron transfer reactions. Because they can react with oxygen to form reactive oxygen species (ROS) and inflict cellular damage, the biogenesis of Fe-S clusters is highly regulated. A recently discovered group of 2Fe-2S proteins, termed NEET proteins, was proposed to coordinate Fe-S, Fe and ROS homeostasis in mammalian cells. Here we report that disrupting the function of AtNEET, the sole member of the NEET protein family in Arabidopsis thaliana, triggers leaf-associated Fe-S- and Fe-deficiency responses, elevated Fe content in chloroplasts (1.2-1.5-fold), chlorosis, structural damage to chloroplasts and a high seedling mortality rate. Our findings suggest that disrupting AtNEET function disrupts the transfer of 2Fe-2S clusters from the chloroplastic 2Fe-2S biogenesis pathway to different cytosolic and chloroplastic Fe-S proteins, as well as to the cytosolic Fe-S biogenesis system, and that uncoupling this process triggers leaf-associated Fe-S- and Fe-deficiency responses that result in Fe over-accumulation in chloroplasts and enhanced ROS accumulation. We further show that AtNEET transfers its 2Fe-2S clusters to DRE2, a key protein of the cytosolic Fe-S biogenesis system, and propose that the availability of 2Fe-2S clusters in the chloroplast and cytosol is linked to Fe homeostasis in plants.

Higher-order Markov models for metagenomic sequence classification.

MOTIVATION: Alignment-free, stochastic models derived from k-mer distributions representing reference genome sequences have a rich history in the classification of DNA sequences. In particular, the variants of Markov models have previously been used extensively. Higher-order Markov models have been used with caution, perhaps sparingly, primarily because of the lack of enough training data and computational power. Advances in sequencing technology and computation have enabled exploitation of the predictive power of higher-order models. We, therefore, revisited higher-order Markov models and assessed their performance in classifying metagenomic sequences. RESULTS: Comparative assessment of higher-order models (HOMs, 9th order or higher) with interpolated Markov model, interpolated context model and lower-order models (8th order or lower) was performed on metagenomic datasets constructed using sequenced prokaryotic genomes. Our results show that HOMs outperform other models in classifying metagenomic fragments as short as 100 nt at all taxonomic ranks, and at lower ranks when the fragment size was increased to 250 nt. HOMs were also found to be significantly more accurate than local alignment which is widely relied upon for taxonomic classification of metagenomic sequences. A novel software implementation written in C++ performs classification faster than the existing Markovian metagenomic classifiers and can therefore be used as a standalone classifier or in conjunction with existing taxonomic classifiers for more robust classification of metagenomic sequences. AVAILABILITY AND IMPLEMENTATION: The software has been made available at https://github.com/djburks/SMM. CONTACT: Rajeev.Azad@unt.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MYB30 Orchestrates Systemic Reactive Oxygen Signaling and Plant Acclimation.

Systemic acquired acclimation (SAA) is a key biological process essential for plant survival under conditions of abiotic stress. SAA was recently shown to be controlled by a rapid systemic signaling mechanism termed the reactive oxygen species (ROS) wave in Arabidopsis (Arabidopsis thaliana). MYB30 is a key transcriptional regulator mediating many different biological processes. MYB30 was found to act downstream of the ROS wave in systemic tissues of Arabidopsis in response to local high light (HL) stress treatment. However, the function of MYB30 in systemic signaling and SAA is unknown. To determine the relationship among MYB30, the ROS wave, and systemic acclimation in Arabidopsis, the SAA response to HL stress of myb30 mutants and wild-type plants was determined. Although myb30 plants were found to display enhanced rates of ROS wave propagation and their local tissues acclimated to the HL stress, they were deficient in SAA to HL stress. Compared to wild type, the systemic transcriptomic response of myb30 plants was also deficient, lacking in the expression of over 3,500 transcripts. A putative set of 150 core transcripts directly associated with MYB30 function during HL stress was determined. Our study identifies MYB30 as a key regulator that links systemic ROS signaling with systemic transcriptomic responses, SAA, and plant acclimation to HL stress. In addition, it demonstrates that plant acclimation and systemic ROS signaling are interlinked and that the lack of systemic acclimation drives systemic ROS signaling to occur at faster rates, suggesting a feedback mechanism (potentially involving MYB30) between these two processes.

Identification and characterization of a core set of ROS wave-associated transcripts involved in the systemic acquired acclimation response of Arabidopsis to excess light.

Systemic acquired acclimation (SAA) plays a key role in optimizing growth and preventing damage associated with fluctuating or abrupt changes in the plant environment. To be effective, SAA has to occur at a rapid rate and depend on rapid signaling pathways that transmit signals from affected tissues to all parts of the plant. Although recent studies have identified several different rapid systemic signaling pathways that could mediate SAA, very little information is known about the extent of their involvement in mediating transcriptomic responses. Here we reveal that the systemic transcriptomic response of plants to excess light stress is extensive in its context and involves an early (2 min) and transient stage of transcript expression that includes thousands of genes. This early response is dependent on the respiratory burst oxidase homolog D protein, and the function of the reactive oxygen species (ROS) wave. We further identify a core set of transcripts associated with the ROS wave and suggest that some of these transcripts are involved in linking ROS with calcium signaling. Priming of a systemic leaf to become acclimated to a particular stress during SAA involves thousands of transcripts that display a rapid and transient expression pattern driven by the ROS wave.

Proactive interference apraxic agraphia: a writing and drawing disorder associated with corticobasal syndrome.

Proactive interference is when a previously performed task impairs performance on a current task. It is often associated with memory tasks and has not been reported to interfere with writing or drawing. We evaluated a left-handed man diagnosed with corticobasal syndrome who had a two-year history of progressive agraphia. On the sentence writing and clock drawing tasks, he initially wrote letters and numbers correctly but revealed an increase of movement errors as the tasks progressed. We propose the term "proactive interference apraxic agraphia" for this novel disorder. Prefrontal dysfunction may cause an impairment in disengaging from previously activated motor programs.

Tissue-specific differences in metabolites and transcripts contribute to the heterogeneity of ricinoleic acid accumulation in Ricinus communis L. (castor) seeds.

INTRODUCTION: Castor (Ricinus communis L.) seeds are valued for their production of oils which can comprise up to 90% hydroxy-fatty acids (ricinoleic acid). Castor oil contains mono-, di- and tri- ricinoleic acid containing triacylglycerols (TAGs). Although the enzymatic synthesis of ricinoleic acid is well described, the differential compartmentalization of these TAG molecular species has remained undefined. OBJECTIVES: To examine the distribution of hydroxy fatty acid accumulation within the endosperm and embryo tissues of castor seeds. METHODS: Matrix assisted laser desorption/ionization mass spectrometry imaging was used to map the distribution of triacylglycerols in tissue sections of castor seeds. In addition, the endosperm and embryo (cotyledons and embryonic axis) tissues were dissected and extracted for quantitative lipidomics analysis and Illumina-based RNA deep sequencing. RESULTS: This study revealed an unexpected heterogeneous tissue distribution of mono-, di- and tri- hydroxy-triacylglycerols in the embryo and endosperm tissues of castor seeds. Pathway analysis based on transcript abundance suggested that distinct embryo- and endosperm-specific mechanisms may exist for the shuttling of ricinoleic acid away from phosphatidylcholine (PC) and into hydroxy TAG production. The embryo-biased mechanism appears to favor removal of ricinoleic acid from PC through phophatidylcholine: diacylglycerol acyltransferase while the endosperm pathway appears to remove ricinoleic acid from the PC pool by preferences of phospholipase A (PLA2α) and/or phosphatidylcholine: diacylglycerol cholinephosphotransferase. CONCLUSIONS: Collectively, a combination of lipidomics and transcriptomics analyses revealed previously undefined spatial aspects of hydroxy fatty acid metabolism in castor seeds. These studies underscore a need for tissue-specific studies as a means to better understand the regulation of triacylglycerol accumulation in oilseeds.

Vertical and Radial Attentional Neglect in Corticobasal Syndrome.

Corticobasal degeneration (CBD), a tau-related neurodegenerative disease, is characterized by limb rigidity, dystonia, myoclonus, apraxia, and cognitive deficits. We report a patient with probable corticobasal syndrome, a major phenotype of CBD, who revealed both lower vertical and proximal radial attentional neglect on line bisection tests. Brain imaging revealed bilateral parietal atrophy with hypometabolism in the bilateral parietal, dorsolateral prefrontal, and premotor cortices. Bilateral impairment in the dorsal attentional network reduces the allocation of spatial attention to lower and proximal space, causing lower vertical and proximal radial attentional neglect. Screening for various types of spatial neglect may be important in tailoring management and rehabilitation strategies for patients with CBD.

Benchmarking RNA-Seq Aligners at Base-Level and Junction Base-Level Resolution Using the Arabidopsis thaliana Genome.

The utmost goal of selecting an RNA-Seq alignment software is to perform accurate alignments with a robust algorithm, which is capable of detecting the various intricacies underlying read-mapping procedures and beyond. Most alignment software tools are typically pre-tuned with human or prokaryotic data, and therefore may not be suitable for applications to other organisms, such as plants. The rapidly growing plant RNA-Seq databases call for the assessment of the alignment tools on curated plant data, which will aid the calibration of these tools for applications to plant transcriptomic data. We therefore focused here on benchmarking RNA-Seq read alignment tools, using simulated data derived from the model organism Arabidopsis thaliana. We assessed the performance of five popular RNA-Seq alignment tools that are currently available, based on their usage (citation count). By introducing annotated single nucleotide polymorphisms (SNPs) from The Arabidopsis Information Resource (TAIR), we recorded alignment accuracy at both base-level and junction base-level resolutions for each alignment tool. In addition to assessing the performance of the alignment tools at their default settings, accuracies were also recorded by varying the values of numerous parameters, including the confidence threshold and the level of SNP introduction. The performances of the aligners were found consistent under various testing conditions at the base-level accuracy; however, the junction base-level assessment produced varying results depending upon the applied algorithm. At the read base-level assessment, the overall performance of the aligner STAR was superior to other aligners, with the overall accuracy reaching over 90% under different test conditions. On the other hand, at the junction base-level assessment, SubRead emerged as the most promising aligner, with an overall accuracy over 80% under most test conditions.

RNA Sequencing Experimental Analysis Workflow Using Caenorhabditis elegans.

RNA sequencing is an approach to transcriptomic profiling that enables the detection of differentially expressed genes in response to genetic mutation or experimental treatment, among other uses. Here we describe a method for the use of a customizable, user-friendly bioinformatic pipeline to identify differentially expressed genes in RNA sequencing data obtained from C. elegans, with attention to the improvement in reproducibility and accuracy of results.

Diagnostic Outcomes of Concurrent DNA and RNA Sequencing in Individuals Undergoing Hereditary Cancer Testing.

Importance: Personalized surveillance, prophylaxis, and cancer treatment options for individuals with hereditary cancer predisposition are informed by results of germline genetic testing. Improvements to genomic technology, such as the availability of RNA sequencing, may increase identification of individuals eligible for personalized interventions by improving the accuracy and yield of germline testing. Objective: To assess the cumulative association of paired DNA and RNA testing with detection of disease-causing germline genetic variants and resolution of variants of uncertain significance (VUS). Design, Setting, and Participants: Paired DNA and RNA sequencing was performed on individuals undergoing germline testing for hereditary cancer indication at a single diagnostic laboratory from March 2019 through April 2020. Demographic characteristics, clinical data, and test results were curated as samples were received, and changes to variant classification were assessed over time. Data analysis was performed from May 2020 to June 2023. Main Outcomes and Measures: Main outcomes were increase in diagnostic yield, decrease in VUS rate, the overall results by variant type, the association of RNA evidence with variant classification, and the corresponding predicted effect on cancer risk management. Results: A total of 43 524 individuals were included (median [range] age at testing, 54 [2-101] years; 37 373 female individuals [85.7%], 6224 male individuals [14.3%], and 2 individuals of unknown sex [<0.1%]), with 43 599 tests. A total of 2197 (5.0%) were Ashkenazi Jewish, 1539 (3.5%) were Asian, 3077 (7.1%) were Black, 2437 (5.6%) were Hispanic, 27 793 (63.7%) were White, and 2049 (4.7%) were other race, and for 4507 individuals (10.3%), race and ethnicity were unknown. Variant classification was impacted in 549 individuals (1.3%). Medically significant upgrades were made in 97 individuals, including 70 individuals who had a variant reclassified from VUS to pathogenic/likely pathogenic (P/LP) and 27 individuals who had a novel deep intronic P/LP variant that would not have been detected using DNA sequencing alone. A total of 93 of 545 P/LP splicing variants (17.1%) were dependent on RNA evidence for classification, and 312 of 439 existing splicing VUS (71.1%) were resolved by RNA evidence. Notably, the increase in positive rate (3.1%) and decrease in VUS rate (-3.9%) was higher in Asian, Black, and Hispanic individuals combined compared to White individuals (1.6%; P = .02; and -2.5%; P < .001). Conclusions and Relevance: Findings of this diagnostic study demonstrate that the ability to perform RNA sequencing concurrently with DNA sequencing represents an important advancement in germline genetic testing by improving detection of novel variants and classification of existing variants. This expands the identification of individuals with hereditary cancer predisposition and increases opportunities for personalization of therapeutics and surveillance.

POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling.

We present here POSMM (pronounced 'Possum'), Python-Optimized Standard Markov Model classifier, which is a new incarnation of the Markov model approach to metagenomic sequence analysis. Built on the top of a rapid Markov model based classification algorithm SMM, POSMM reintroduces high sensitivity associated with alignment-free taxonomic classifiers to probe whole genome or metagenome datasets of increasingly prohibitive sizes. Logistic regression models generated and optimized using the Python sklearn library, transform Markov model probabilities to scores suitable for thresholding. Featuring a dynamic database-free approach, models are generated directly from genome fasta files per run, making POSMM a valuable accompaniment to many other programs. By combining POSMM with ultrafast classifiers such as Kraken2, their complementary strengths can be leveraged to produce higher overall accuracy in metagenomic sequence classification than by either as a standalone classifier. POSMM is a user-friendly and highly adaptable tool designed for broad use by the metagenome scientific community.

Selective laser vaporization of polypropylene mesh used in treatment of female stress urinary incontinence and pelvic organ prolapse: preliminary studies using a red diode laser.

BACKGROUND AND OBJECTIVES: The most common mesh-related complication experienced by patients undergoing transvaginal polypropylene synthetic slings for stress urinary incontinence (SUI) and transvaginal pelvic organ prolapse (POP) repair with mesh is vaginal mesh erosion. More than half of the patients who experience erosion from synthetic mesh require surgical excision which is technically challenging and risks damage to healthy adjacent tissue. This study explores selective laser vaporization of polypropylene suture/mesh materials commonly used in SUI and POP. MATERIALS AND METHODS: A compact, 7 Watt, 647-nm, red diode laser was operated with a radiant exposure of 81 J/cm(2) , pulse duration of 100 milliseconds, and 1.0-mm-diameter laser spot. The 647-nm wavelength was selected because its absorption by water, hemoglobin, and other tissue chromophores is low, while polypropylene absorption is high. Laser vaporization of ∼200-µm-diameter polypropylene suture/mesh strands, in contact with fresh urinary tissue samples was performed, ex vivo. Temperature mapping of suture/mesh samples with a thermal camera was also conducted. RESULTS: Selective vaporization of polypropylene suture and mesh using a single laser pulse was achieved with peak temperatures of 180 and 232°C, respectively, while direct laser irradiation of tissue alone resulted in only a 1°C temperature increase. CONCLUSIONS: Selective laser vaporization of polypropylene suture/mesh materials is feasible without significant thermal elevation in the adjacent tissue. This technique may be useful for treatment of eroded mesh after SUI or POP procedures that require surgical revision.

RNA-Seq Data Analysis Pipeline for Plants: Transcriptome Assembly, Alignment, and Differential Expression Analysis.

In this chapter, we describe methods for analyzing RNA-Seq data, presented as a flow along a pipeline beginning with raw data from a sequencer and ending with an output of differentially expressed genes and their functional characterization. The first section covers de novo transcriptome assembly for organisms lacking reference genomes or for those interested in probing against the background of organism-specific transcriptomes assembled from RNA-Seq data. Section 2 covers both gene- and transcript-level quantifications, leading to the third and final section on differential expression analysis between two or more conditions. The pipeline starts with raw sequence reads, followed by quality assessment and preprocessing of the input data to ensure a robust estimate of the transcripts and their differential regulation. The preprocessed data can be inputted into the de novo transcriptome flow to assemble transcripts, functionally annotated using tools such as InterProScan or Blast2Go and then forwarded to differential expression analysis flow, or directly inputted into the differential expression analysis flow if a reference genome is available. An online repository containing sample data has also been made available, as well as custom Python scripts to modify the output of the programs within the pipeline for various downstream analyses.

Mapping Strengths and Weaknesses of Different Clustering Approaches to Deciphering Bacterial Chimerism.

Bacterial genomes are chimeras of DNA of different ancestries. Deconstructing chimeric genomes is central to understanding the evolutionary trajectories of their disparate components and thus the organisms as a whole in the light of their evolutionary contexts. Of specific interest is to delineate and quantify native (vertically inherited) and alien (horizontally acquired) components of bacterial genomes and also specify genomic fractions that represent different donor sources. An agglomerative clustering procedure that prioritizes grouping of proximal similar genomic segments has previously been invoked for this purpose in conjunction with a recursive segmentation procedure. Surprisingly, however, the relative strengths and weaknesses of different clustering approaches to deciphering bacterial chimerism have not yet been investigated, despite the need to robustly interpret tens of thousands of completely sequenced bacterial genomes and nearly complete genome assemblies available in the public databases. To bridge this knowledge gap and develop more robust approaches, we assessed different clustering methods, including segment order based (proximal) clustering, hierarchical clustering, affinity propagation clustering, and a novel network clustering approach on chimeric genomes modeled after bacterial genomes representing a broad spectrum of compositional complexity. Although segment order-based clustering and network clustering compared favorably with the other approaches in discriminating between native and alien DNA at genome optimized settings, network clustering did consistently better than other methods at parametric settings optimized on all test genomes together. Segment order-based clustering and hierarchical clustering outperformed other methods in alien DNA identification while preserving donor identity in the genomes. Our study highlights the strengths and weaknesses of different approaches and suggests how this can be leveraged to achieve a more robust deconstruction of bacterial chimerism.

Analysis of transcribed sequences from young and mature zebrafish thrombocytes.

The zebrafish is an excellent model system to study thrombocyte function and development. Due to the difficulties in separating young and mature thrombocytes, comparative transcriptomics between these two cell types has not been performed. It is important to study these differences in order to understand the mechanism of thrombocyte maturation. Here, we performed single-cell RNA sequencing of the young and mature zebrafish thrombocytes and compared the two datasets for young and mature thrombocyte transcripts. We found a total of 9143 genes expressed cumulatively in both young and mature thrombocytes, and among these, 72% of zebrafish thrombocyte-expressed genes have human orthologs according to the Ensembl human genome annotation. We also found 397 uniquely expressed genes in young and 2153 uniquely expressed genes in mature thrombocytes. Of these 397 and 2153 genes, 272 and 1620 corresponded to human orthologous genes, respectively. Of all genes expressed in both young and mature thrombocytes, 4224 have been reported to be expressed in human megakaryocytes, and 1603 were found in platelets. Among these orthologs, 156 transcription factor transcripts in thrombocytes were found in megakaryocytes and 60 transcription factor transcripts were found in platelets including a few already known factors such as Nfe2 and Nfe212a (related to Nfe2) that are present in both megakaryocytes, and platelets. These results indicate that thrombocytes have more megakaryocyte features and since platelets are megakaryocyte fragments, platelets also appear to be thrombocyte equivalents. In conclusion, our study delineates the differential gene expression patterns of young and mature thrombocytes, highlighting the processes regulating thrombocyte maturation. Future knockdown studies of these young and mature thrombocyte-specific genes are feasible and will provide the basis for understanding megakaryocyte maturation.

Evaluation of pathways to the C-glycosyl isoflavone puerarin in roots of kudzu (Pueraria montana lobata).

Kudzu (Pueraria montana lobata) is used as a traditional medicine in China and Southeast Asia but is a noxious weed in the Southeastern United States. It produces both O- and C-glycosylated isoflavones, with puerarin (C-glucosyl daidzein) as an important bioactive compound. Currently, the stage of the isoflavone pathway at which the C-glycosyl unit is added remains unclear, with a recent report of direct C-glycosylation of daidzein contradicting earlier labeling studies supporting C-glycosylation at the level of chalcone. We have employed comparative mRNA sequencing of the roots from two Pueraria species, one of which produces puerarin (field collected P. montana lobata) and one of which does not (commercial Pueraria phaseoloides), to identify candidate uridine diphosphate glycosyltransferase (UGT) enzymes involved in puerarin biosynthesis. Expression of recombinant UGTs in Escherichia coli and candidate C-glycosyltransferases in Medicago truncatula were used to explore substrate specificities, and gene silencing of UGT and key isoflavone biosynthetic genes in kudzu hairy roots employed to test hypotheses concerning the substrate(s) for C-glycosylation. Our results confirm UGT71T5 as a C-glycosyltransferase of isoflavone biosynthesis in kudzu. Enzymatic, isotope labeling, and genetic analyses suggest that puerarin arises both from the direct action of UGT71T5 on daidzein and via a second route in which the C-glycosidic linkage is introduced to the chalcone isoliquiritigenin.

The Arabidopsis gene co-expression network.

Identifying genes that interact to confer a biological function to an organism is one of the main goals of functional genomics. High-throughput technologies for assessment and quantification of genome-wide gene expression patterns have enabled systems-level analyses to infer pathways or networks of genes involved in different functions under many different conditions. Here, we leveraged the publicly available, information-rich RNA-Seq datasets of the model plant Arabidopsis thaliana to construct a gene co-expression network, which was partitioned into clusters or modules that harbor genes correlated by expression. Gene ontology and pathway enrichment analyses were performed to assess functional terms and pathways that were enriched within the different gene modules. By interrogating the co-expression network for genes in different modules that associate with a gene of interest, diverse functional roles of the gene can be deciphered. By mapping genes differentially expressing under a certain condition in Arabidopsis onto the co-expression network, we demonstrate the ability of the network to uncover novel genes that are likely transcriptionally active but prone to be missed by standard statistical approaches due to their falling outside of the confidence zone of detection. To our knowledge, this is the first A. thaliana co-expression network constructed using the entire mRNA-Seq datasets (>20,000) available at the NCBI SRA database. The developed network can serve as a useful resource for the Arabidopsis research community to interrogate specific genes of interest within the network, retrieve the respective interactomes, decipher gene modules that are transcriptionally altered under certain condition or stage, and gain understanding of gene functions.

Mutational and splicing landscape in a cohort of 43,000 patients tested for hereditary cancer.

DNA germline genetic testing can identify individuals with cancer susceptibility. However, DNA sequencing alone is limited in its detection and classification of mRNA splicing variants, particularly those located far from coding sequences. Here we address the limitations of splicing variant identification and interpretation by pairing DNA and RNA sequencing and describe the mutational and splicing landscape in a clinical cohort of 43,524 individuals undergoing genetic testing for hereditary cancer predisposition.

AUA guideline for the diagnosis and treatment of interstitial cystitis/bladder pain syndrome.

PURPOSE: To provide a clinical framework for the diagnosis and treatment of interstitial cystitis/bladder pain syndrome. MATERIALS AND METHODS: A systematic review of the literature using the MEDLINE® database (search dates 1/1/83-7/22/09) was conducted to identify peer reviewed publications relevant to the diagnosis and treatment of interstitial cystitis/bladder pain syndrome. Insufficient evidence-based data were retrieved regarding diagnosis and, therefore, this portion of the Guideline is based on Clinical Principles and Expert Opinion statements. The review yielded an evidence base of 86 treatment articles after application of inclusion/exclusion criteria. These publications were used to create the majority of the treatment portion of the Guideline. When sufficient evidence existed, the body of evidence for a particular treatment was assigned a strength rating of A (high), B (moderate) or C (low). Additional treatment information is provided as Clinical Principles and Expert Opinion when insufficient evidence existed. See text and algorithm for definitions, and detailed diagnostic management, and treatment frameworks. RESULTS: The evidence-based guideline statements are provided for diagnosis and overall management of interstitial cystitis/bladder pain syndrome as well as for various treatments. The panel identified first through sixth line treatments as well as developed guideline statements on treatments that should not be offered. CONCLUSIONS: Interstitial cystitis/bladder pain syndrome is best identified and managed through use of a logical algorithm such as is presented in this Guideline. In the algorithm the panel identifies an overall management strategy for the interstitial cystitis/bladder pain syndrome patient. Diagnosis and treatment methodologies can be expected to change as the evidence base grows in the future.