RNA editing of microtubule-associated protein tau circular RNAs promotes their translation and tau tangle formation.

Aggregation of the microtubule-associated protein tau characterizes tauopathies, including Alzheimer's disease and frontotemporal lobar degeneration (FTLD-Tau). Gene expression regulation of tau is complex and incompletely understood. Here we report that the human tau gene (MAPT) generates two circular RNAs (circRNAs) through backsplicing of exon 12 to either exon 7 (12→7 circRNA) or exon 10 (12→10 circRNA). Both circRNAs lack stop codons. The 12→7 circRNA contains one start codon and is translated in a rolling circle, generating a protein consisting of multimers of the microtubule-binding repeats R1-R4. For the 12→10 circRNA, a start codon can be introduced by two FTLD-Tau mutations, generating a protein consisting of multimers of the microtubule-binding repeats R2-R4, suggesting that mutations causing FTLD may act in part through tau circRNAs. Adenosine to inosine RNA editing dramatically increases translation of circRNAs and, in the 12→10 circRNA, RNA editing generates a translational start codon by changing AUA to AUI. Circular tau proteins self-aggregate and promote aggregation of linear tau proteins. Our data indicate that adenosine to inosine RNA editing initiates translation of human circular tau RNAs, which may contribute to tauopathies.

Detection of Anomalies in Daily Activities Using Data from Smart Meters.

The massive deployment of smart meters in most Western countries in recent decades has allowed the creation and development of a significant variety of applications, mainly related to efficient energy management. The information provided about energy consumption has also been dedicated to the areas of social work and health. In this context, smart meters are considered single-point non-intrusive sensors that might be used to monitor the behaviour and activity patterns of people living in a household. This work describes the design of a short-term behavioural alarm generator based on the processing of energy consumption data coming from a commercial smart meter. The device captured data from a household for a period of six months, thus providing the consumption disaggregated per appliance at an interval of one hour. These data were used to train different intelligent systems, capable of estimating the predicted consumption for the next one-hour interval. Four different approaches have been considered and compared when designing the prediction system: a recurrent neural network, a convolutional neural network, a random forest, and a decision tree. By statistically analysing these predictions and the actual final energy consumption measurements, anomalies can be detected in the undertaking of three different daily activities: sleeping, breakfast, and lunch. The recurrent neural network achieves an F1-score of 0.8 in the detection of these anomalies for the household under analysis, outperforming other approaches. The proposal might be applied to the generation of a short-term alarm, which can be involved in future deployments and developments in the field of ambient assisted living.

FPGA-Microprocessor Based Sensor for Faults Detection in Induction Motors Using Time-Frequency and Machine Learning Methods.

Induction motors (IM) play a fundamental role in the industrial sector because they are robust, efficient, and low-cost machines. Changes in the environment, installation errors, or modifications to working conditions can generate faults in induction motors. The trend on IM fault detection is focused on the design techniques and sensors capable of evaluating multiple faults with various signals using non-invasive analysis. The methodology is based on processing electric current signals by applying the short-time Fourier transform (STFT). Additionally, the computation of the mean and standard deviation of infrared thermograms is proposed as main indicators. The proposed system combines both parameters by means of Support Vector Machine and k-nearest-neighbor classifiers. The development of the diagnostic system was done with digital hardware implementations using a Xilinx PYNQ Z2 card that integrates an FPGA with a microprocessor, thus taking advantage of the acquisition and processing of digital signals and images in hardware. The proposed method has proved to be effective for the classification of healthy (HLT), misalignment (MAMT), unbalance (UNB), damaged bearing (BDF), and broken rotor bar (BRB) faults with an accuracy close to 99%.

Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing.

DNA is a promising next-generation data storage medium, but challenges remain with synthesis costs and recording latency. Here, we describe a prototype of a DNA data storage system that uses an extended molecular alphabet combining natural and chemically modified nucleotides. Our results show that MspA nanopores can discriminate different combinations and ordered sequences of natural and chemically modified nucleotides in custom-designed oligomers. We further demonstrate single-molecule sequencing of the extended alphabet using a neural network architecture that classifies raw current signals generated by Oxford Nanopore sequencers with an average accuracy exceeding 60% (39× larger than random guessing). Molecular dynamics simulations show that the majority of modified nucleotides lead to only minor perturbations of the DNA double helix. Overall, the extended molecular alphabet may potentially offer a nearly 2-fold increase in storage density and potentially the same order of reduction in the recording latency, thereby enabling new implementations of molecular recorders.

First Draft Genome Assembly of Root-Lesion Nematode Pratylenchus scribneri Generated Using Long-Read Sequencing.

Root-lesion nematodes (genus Pratylenchus) belong to a diverse group of plant-parasitic nematodes (PPN) with a worldwide distribution. Despite being an economically important PPN group of more than 100 species, genome information related to Pratylenchus genus is scarcely available. Here, we report the draft genome assembly of Pratylenchus scribneri generated on the PacBio Sequel IIe System using the ultra-low DNA input HiFi sequencing workflow. The final assembly created using 500 nematodes consisted of 276 decontaminated contigs, with an average contig N50 of 1.72 Mb and an assembled draft genome size of 227.24 Mb consisting of 51,146 predicted protein sequences. The benchmarking universal single-copy ortholog (BUSCO) analysis with 3131 nematode BUSCO groups indicated that 65.4% of the BUSCOs were complete, whereas 24.0%, 41.4%, and 1.8% were single-copy, duplicated, and fragmented, respectively, and 32.8% were missing. The outputs from GenomeScope2 and Smudgeplots converged towards a diploid genome for P. scribneri. The data provided here will facilitate future studies on host plant-nematode interactions and crop protection at the molecular level.

Protein acetylation effects on enzyme activity and metabolic pathway fluxes.

Acetylation of proteins seems a widespread process found in the three domains of life. Several studies have shown that besides histones, acetylation of lysine residues also occurs in non-nuclear proteins. Hence, it has been suggested that this covalent modification is a mechanism that might regulate diverse metabolic pathways by modulating enzyme activity, stability, and/or subcellular localization or interaction with other proteins. However, protein acetylation levels seem to have low correlation with modification of enzyme activity and pathway fluxes. In addition, the results obtained with mutant enzymes that presumably mimic acetylation have frequently been over-interpreted. Moreover, there is a generalized lack of rigorous enzyme kinetic analysis in parallel to acetylation level determinations. The purpose of this review is to analyze the current findings on the impact of acetylation on metabolic enzymes and its repercussion on metabolic pathways function/regulation.

Wide mutational analysis to ascertain the functional roles of eL33 in ribosome biogenesis and translation initiation.

An extensive mutational analysis of RPL33A, encoding the yeast ribosomal protein L33A (eL33) allowed us to identify several novel rpl33a mutants with different translational phenotypes. Most of the rpl33a mutants are defective in the processing of 35S and 27S pre-rRNA precursors and the production of mature rRNAs, exhibiting reductions in the amounts of ribosomal subunits and altered polysome profiles. Some of the rpl33a mutants exhibit a Gcd- phenotype of constitutive derepression of GCN4 translation and strong slow growth phenotypes at several temperatures. Interestingly, some of the later mutants also show a detectable increase in the UUG/AUG translation initiation ratio that can be suppressed by eIF1 overexpression, suggesting a requirement for eL33 and a correct 60S/40S subunit ratio for the proper recognition of the AUG start codon. In addition to producing differential reductions in the rates of pre-rRNA maturation and perhaps in r-protein assembly, most of the point rpl33a mutations alter specific molecular interactions of eL33 with the rRNAs and other r-proteins in the 60S structure. Thus, rpl33a mutations cause distinctive effects on the abundance and/or functionality of 60S subunits, leading to more or less pronounced defects in the rates and fidelity of mRNA translation.

Genomic regions associated with virulence in Setosphaeria turcica identified by linkage mapping in a biparental population.

Northern corn leaf blight (NCLB) and sorghum leaf blight (SLB) are significant diseases of maize and sorghum, respectively, caused by the filamentous fungus Setosphaeria turcica. Strains of S. turcica are typically host-specific and infect either maize or sorghum. Host specificity in this pathogen is attributed to a single locus for maize and a second distinct locus for sorghum. To identify the genetic basis of host specificity in S. turcica, we generated a biparental population of S. turcica by crossing strains specific to maize and sorghum, phenotyped the population for leaf blight on sorghum and maize, genotyped the population to create a linkage map of S. turcica, and located candidate virulence regions. A total of 190 ascospores from 35 pseudothecia were isolated from the cross of maize and sorghum-specific strains. Greenhouse phenotyping of the biparental population (n = 144) showed independent inheritance of virulence, as indicated by a 1:1:1:1 segregation for virulence to maize, sorghum, both maize and sorghum, and avirulence to both crops. The population and host-specific parent strains were genotyped using genome skim sequencing on an Illumina NovaSeq 6000 platform resulting in over 780 million reads. A total of 32,635 variants including single nucleotide polymorphisms and indels were scored. There was evidence for a large deletion in the sorghum-specific strain of S. turcica. A genetic map consisting of 17 linkage groups spanning 3,069 centimorgans was constructed. Virulence to sorghum and maize mapped on distinct linkage groups with a significant QTL detected for virulence to maize. Furthermore, a single locus each for the in vitro traits hyphal growth rate and conidiation were identified and mapped onto two other linkage groups. In vitro traits did not correlate with in planta virulence complexity, suggesting that virulence on both hosts does not incur a fitness cost. Hyphal growth rate and conidiation were negatively correlated, indicating differences in hyphal growth versus dispersal ability for this pathogen. Identification of genetic regions underlying virulence specificity and saprotrophic growth traits in S. turcica provides a better understanding of the S. turcica- Andropogoneae pathosystem.

Simulation Tool and Online Demonstrator for CDMA-Based Ultrasonic Indoor Localization Systems.

This work presents the CODEUS platform, which includes a simulation tool together with an online experimental demonstrator to offer analysis and testing flexibility for researchers and developers in Ultrasonic Indoor Positioning Systems (UIPSs). The simulation platform allows most common encoding techniques and sequences to be tested in a configurable UIPS. It models the signal modulation and processing, the ultrasonic transducers' response, the beacon distribution, the channel propagation effects, the synchronism, and the application of different positioning algorithms. CODEUS provides results and performance analysis for different metrics and at different stages of the signal processing. The UIPS simulation tool is specified by means of the MATLAB© App-Designer environment, which enables the definition of a user-friendly interface. It has also been linked to an online demonstrator that can be managed remotely by means of a website, thus avoiding any hardware requirement or equipment on behalf of researchers. This demonstrator allows the selected transmission schemes, modulation or encoding techniques to be validated in a real UIPS, therefore enabling a fast and easy way of carrying out experimental tests in a laboratory environment, while avoiding the time-consuming tasks related to electronic design and prototyping in the UIPS field. Both simulator and online demonstrator are freely available for researchers and students through the corresponding website.

Infrared Thermography Smart Sensor for the Condition Monitoring of Gearbox and Bearings Faults in Induction Motors.

The monitoring of machine conditions is very important from the viewpoints of productivity, economic benefits, and maintenance. Several techniques have been proposed in which sensors are the key to providing relevant information to verify the system. Recently, the smart sensor concept is common, in which the sensors are integrated with a data processing unit executing dedicated algorithms used to generate meaningful information about the system in situ. Additionally, infrared thermography has gained relevance in monitoring processes, since the new infrared cameras have more resolution, smaller dimensions, reliability, functionality, and lower costs. These units were firstly used as secondary elements in the condition monitoring of machines, but thanks to modern techniques for data processing, the infrared sensors can be used to give a first, or even a direct, diagnosis in a nonintrusive way in industrial applications. Therefore, in this manuscript, the structure and development of an infrared-thermography-based smart sensor for diagnosing faults in the elements associated with induction motors, such as rolling bearings and the gearbox, is described. The smart sensor structure includes five main parts: an infrared primary sensor, a preprocessing module, an image processing module, classification of faults, and a user interface. The infrared primary sensor considers a low-cost micro thermal camera for acquiring the thermal images. The processing modules and the classification module implement the data processing algorithms into digital development boards, enabling smart system characteristics. Finally, the interface module allows the final users to require the smart sensor to perform processing actions and data visualization, with the additional feature that the diagnosis report can be provided by the system. The smart sensor is validated in a real experimental test bench, demonstrating its capabilities in different case studies.

HCV microelimination strategies: An interventional study in diagnosed patients without access to the system.

Hepatitis C virus (HCV) one-step diagnosis improves recovery in patients with active infection. However, patients with previous anti-HCV+ may be excluded. We aimed to identify and retrieve non-referred or lost-to-follow-up HCV-infected patients. All anti-HCV+ patients seen in our hospital between 2013 and 2018 were included. In the first phase, we identified anti-HCV+ patients who were not referred to the Gastroenterology Unit (GU) or lost-to-follow-up. In the second phase, recovered patients were invited for a one-step visit for liver evaluation. A total of 1330 anti-HCV+ patients were included: 21.7% had not been referred to GU, and 23.1% were lost-to-follow-up. In the second phase, 49.6% of patients were contacted, and 92.8% attended a medical consultation: 62.7% had active infection, 92.2% were treated, and 86.5% achieved SVR (ITT). We concluded that screening microbiological data and referring unidentified patients with active HCV infection directly to specialists is an effective tool in achieving HCV microelimination.

Using Perspective-n-Point Algorithms for a Local Positioning System Based on LEDs and a QADA Receiver.

The research interest on location-based services has increased during the last years ever since 3D centimetre accuracy inside intelligent environments could be confronted with. This work proposes an indoor local positioning system based on LED lighting, transmitted from a set of beacons to a receiver. The receiver is based on a quadrant photodiode angular diversity aperture (QADA) plus an aperture placed over it. This configuration can be modelled as a perspective camera, where the image position of the transmitters can be used to recover the receiver's 3D pose. This process is known as the perspective-n-point (PnP) problem, which is well known in computer vision and photogrammetry. This work investigates the use of different state-of-the-art PnP algorithms to localize the receiver in a large space of 2 × 2 m2 based on four co-planar transmitters and with a distance from transmitters to receiver up to 3.4 m. Encoding techniques are used to permit the simultaneous emission of all the transmitted signals and their processing in the receiver. In addition, correlation techniques (match filtering) are used to determine the image points projected from each emitter on the QADA. This work uses Monte Carlo simulations to characterize the absolute errors for a grid of test points under noisy measurements, as well as the robustness of the system when varying the 3D location of one transmitter. The IPPE algorithm obtained the best performance in this configuration. The proposal has also been experimentally evaluated in a real setup. The estimation of the receiver's position at three particular points for roll angles of the receiver of γ={0°, 120°, 210° and 300°} using the IPPE algorithm achieves average absolute errors and standard deviations of 4.33 cm, 3.51 cm and 28.90 cm; and 1.84 cm, 1.17 cm and 19.80 cm in the coordinates x, y and z, respectively. These positioning results are in line with those obtained in previous work using triangulation techniques but with the addition that the complete pose of the receiver (x, y, z, α, ß, γ) is obtained in this proposal.

Dynamic Adjustment of Weighted GCC-PHAT for Position Estimation in an Ultrasonic Local Positioning System.

Ultrasonic local positioning systems (ULPS) have been brought to the attention of researchers as one of the possibilities that can be used for indoor localization. Acoustic systems combine a suitable trade-off between precision, ease of development, and cost. This work proposes a method for measuring the time of arrival of encoded emissions from a set of ultrasonic beacons, which are used to implement an accurate ULPS. This method uses the generalized cross-correlation technique with PHAT filter and weighting factor ß (GCC-PHAT-ß). To improve the performance of the GCC-PHAT-ß in encoded emission detection, the employment is proposed of mixed-medium multiple-access techniques, based on code division and time division multiplexing of beacon emissions (CDMA and TDMA respectively), and to dynamically adjust the PHAT filter weighting factor. The receiver position is obtained by hyperbolic multilateration from the time differences of arrival (TDoA) between a reference beacon and the rest, thus avoiding the need for receiver synchronization. The results show how the dynamic adaptation of the weighting factor significantly reduces positioning errors from 20 cm to 2 cm in 80% of measurements. The simulated and real experiments prove that the proposed algorithms improve the performance of the ULPS in situations with lower signal-to-noise ratios (SNR) than 0 dB and in environments where the multipath effect makes it difficult to correctly detect the encoded ultrasonic emissions.

LOCATE-US: Indoor Positioning for Mobile Devices Using Encoded Ultrasonic Signals, Inertial Sensors and Graph-Matching.

Indoor positioning remains a challenge and, despite much research and development carried out in the last decade, there is still no standard as with the Global Navigation Satellite Systems (GNSS) outdoors. This paper presents an indoor positioning system called LOCATE-US with adjustable granularity for use with commercial mobile devices, such as smartphones or tablets. LOCATE-US is privacy-oriented and allows every device to compute its own position by fusing ultrasonic, inertial sensor measurements and map information. Ultrasonic Local Positioning Systems (U-LPS) based on encoded signals are placed in critical zones that require an accuracy below a few decimeters to correct the accumulated drift errors of the inertial measurements. These systems are well suited to work at room level as walls confine acoustic waves inside. To avoid audible artifacts, the U-LPS emission is set at 41.67 kHz, and an ultrasonic acquisition module with reduced dimensions is attached to the mobile device through the USB port to capture signals. Processing in the mobile device involves an improved Time Differences of Arrival (TDOA) estimation that is fused with the measurements from an external inertial sensor to obtain real-time location and trajectory display at a 10 Hz rate. Graph-matching has also been included, considering available prior knowledge about the navigation scenario. This kind of device is an adequate platform for Location-Based Services (LBS), enabling applications such as augmented reality, guiding applications, or people monitoring and assistance. The system architecture can easily incorporate new sensors in the future, such as UWB, RFiD or others.

Chemo-Enzymatic Synthesis of S. mansoni O-Glycans and Their Evaluation as Ligands for C-Type Lectin Receptors MGL, DC-SIGN, and DC-SIGNR.

Due to their interactions with C-type lectin receptors (CLRs), glycans from the helminth Schistosoma mansoni represent promising leads for treatment of autoimmune diseases, allergies or cancer. We chemo-enzymatically synthesized nine O-glycans based on the two predominant O-glycan cores observed in the infectious stages of schistosomiasis, the mucin core 2 and the S. mansoni core. The O-glycans were fucosylated next to a selection of N-glycans directly on a microarray slide using a recombinant fucosyltransferase and GDP-fucose or GDP-6-azidofucose as donor. Binding assays with fluorescently labelled human CLRs DC-SIGN, DC-SIGNR and MGL revealed the novel O-glycan O8 as the best ligand for MGL from our panel. Significant binding to DC-SIGN was also found for azido-fucosylated glycans. Contrasting binding specificities were observed between the monovalent carbohydrate recognition domain (CRD) and the tetravalent extracellular domain (ECD) of DC-SIGNR.

Characterization of an Ultrasonic Local Positioning System for 3D Measurements.

Indoor location and positioning systems (ILPS) are used to locate and track people, as well as mobile and/or connected targets, such as robots or smartphones, not only inside buildings with a lack of global navigation satellite systems (GNSS) signals but also in constrained outdoor situations with reduced coverage. Indoor positioning applications and their interest are growing in certain environments, such as commercial centers, airports, hospitals or factories. Several sensory technologies have already been applied to indoor positioning systems, where ultrasounds are a common solution due to its low cost and simplicity. This work proposes a 3D ultrasonic local positioning system (ULPS), based on a set of three asynchronous ultrasonic beacon units, capable of transmitting coded signals independently, and on a 3D mobile receiver prototype. The proposal is based on the aforementioned beacon unit, which consists of five ultrasonic transmitters oriented towards the same coverage area and has already been proven in 2D positioning by applying hyperbolic trilateration. Since there are three beacon units available, the final position is obtained by merging the partial results from each unit, implementing a minimum likelihood estimation (MLE) fusion algorithm. The approach has been characterized, and experimentally verified, trying to maximize the coverage zone, at least for typical sizes in most common public rooms and halls. The proposal has achieved a positioning accuracy below decimeters for 90% of the cases in the zone where the three ultrasonic beacon units are available, whereas these accuracies can degrade above decimeters according to whether the coverage from one or more beacon units is missing. The experimental workspace covers a large volume, where tests have been carried out at points placed in two different horizontal planes.

Transcriptome analysis of egg viability in rainbow trout, Oncorhynchus mykiss.

BACKGROUND: Maternal transcripts are accumulated in the oocyte during oogenesis to provide for protein synthesis from oocyte maturation through early embryonic development, when nuclear transcription is silenced. The maternal mRNAs have short poly(A) tails after undergoing post-transcriptional processing necessary for stabilizing them for storage. The transcripts undergo cytoplasmic polyadenylation when they are to be translated. Transcriptome analyses comparing total mRNA and elongated poly(A) mRNA content among eggs of different quality can provide insight into molecular mechanisms affecting egg developmental competence in rainbow trout. The present study used RNA-seq to compare transcriptomes of unfertilized eggs of rainbow trout females yielding different eyeing rates, following rRNA removal and poly(A) retention for construction of the libraries. RESULTS: The percentage of embryos to reach the 32-cell stage at 24 h post fertilization was significantly correlated to family eyeing rate, indicating that inviable embryos were developmentally compromised before zygotic genome activation. RNA sequencing identified 2 differentially expressed transcripts (DETs) from total mRNA sequencing comparing females with low-quality (< 5% eyeing), medium-quality (30-50% eyeing), and high-quality (> 80% eyeing) eggs. In contrast, RNA sequencing from poly(A) captured transcripts identified 945 DETs between low- and high-quality eggs, 1012 between low- and medium-quality eggs, and only 2 between medium- and high-quality eggs. The transcripts of mitochondrial genes were enriched with polyadenylated transcript sequencing and they were significantly reduced in low-quality eggs. Similarly, mitochondrial DNA was reduced in low-quality eggs compared with medium- and high-quality eggs. The functional gene analysis classified the 945 DETs between low- and high-quality eggs into 31 functional modules, many of which were related to ribosomal and mitochondrial functions. Other modules involved transcription, translation, cell division, apoptosis, and immune responses. CONCLUSIONS: Our results indicate that differences in egg quality may be derived from differences in maternal nuclear transcript activation and cytoplasmic polyadenylation before ovulation, as opposed to accumulation and storage of maternal nuclear transcripts during oogenesis. Transcriptome comparisons suggest low-quality eggs suffered from impaired oxidative phosphorylation and translation. The DETs identified in this study provide insight into developmental competence in rainbow trout eggs.

Genome of 'Charleston Gray', the principal American watermelon cultivar, and genetic characterization of 1,365 accessions in the U.S. National Plant Germplasm System watermelon collection.

Years of selection for desirable fruit quality traits in dessert watermelon (Citrullus lanatus) has resulted in a narrow genetic base in modern cultivars. Development of novel genomic and genetic resources offers great potential to expand genetic diversity and improve important traits in watermelon. Here, we report a high-quality genome sequence of watermelon cultivar 'Charleston Gray', a principal American dessert watermelon, to complement the existing reference genome from '97103', an East Asian cultivar. Comparative analyses between genomes of 'Charleston Gray' and '97103' revealed genomic variants that may underlie phenotypic differences between the two cultivars. We then genotyped 1365 watermelon plant introduction (PI) lines maintained at the U.S. National Plant Germplasm System using genotyping-by-sequencing (GBS). These PI lines were collected throughout the world and belong to three Citrullus species, C. lanatus, C. mucosospermus and C. amarus. Approximately 25 000 high-quality single nucleotide polymorphisms (SNPs) were derived from the GBS data using the 'Charleston Gray' genome as the reference. Population genomic analyses using these SNPs discovered a close relationship between C. lanatus and C. mucosospermus and identified four major groups in these two species correlated to their geographic locations. Citrullus amarus was found to have a distinct genetic makeup compared to C. lanatus and C. mucosospermus. The SNPs also enabled identification of genomic regions associated with important fruit quality and disease resistance traits through genome-wide association studies. The high-quality 'Charleston Gray' genome and the genotyping data of this large collection of watermelon accessions provide valuable resources for facilitating watermelon research, breeding and improvement.

Clostridium scindens ATCC 35704: Integration of Nutritional Requirements, the Complete Genome Sequence, and Global Transcriptional Responses to Bile Acids.

In the human gut, Clostridium scindens ATCC 35704 is a predominant bacterium and one of the major bile acid 7α-dehydroxylating anaerobes. While this organism is well-studied relative to bile acid metabolism, little is known about the basic nutrition and physiology of C. scindens ATCC 35704. To determine the amino acid and vitamin requirements of C. scindens, the leave-one-out (one amino acid group or vitamin) technique was used to eliminate the nonessential amino acids and vitamins. With this approach, the amino acid tryptophan and three vitamins (riboflavin, pantothenate, and pyridoxal) were found to be required for the growth of C. scindens In the newly developed defined medium, C. scindens fermented glucose mainly to ethanol, acetate, formate, and H2. The genome of C. scindens ATCC 35704 was completed through PacBio sequencing. Pathway analysis of the genome sequence coupled with transcriptome sequencing (RNA-Seq) under defined culture conditions revealed consistency with the growth requirements and end products of glucose metabolism. Induction with bile acids revealed complex and differential responses to cholic acid and deoxycholic acid, including the expression of potentially novel bile acid-inducible genes involved in cholic acid metabolism. Responses to toxic deoxycholic acid included expression of genes predicted to be involved in DNA repair, oxidative stress, cell wall maintenance/metabolism, chaperone synthesis, and downregulation of one-third of the genome. These analyses provide valuable insight into the overall biology of C. scindens which may be important in treatment of disease associated with increased colonic secondary bile acids.IMPORTANCEC. scindens is one of a few identified gut bacterial species capable of converting host cholic acid into disease-associated secondary bile acids such as deoxycholic acid. The current work represents an important advance in understanding the nutritional requirements and response to bile acids of the medically important human gut bacterium, C. scindens ATCC 35704. A defined medium has been developed which will further the understanding of bile acid metabolism in the context of growth substrates, cofactors, and other metabolites in the vertebrate gut. Analysis of the complete genome supports the nutritional requirements reported here. Genome-wide transcriptomic analysis of gene expression in the presence of cholic acid and deoxycholic acid provides a unique insight into the complex response of C. scindens ATCC 35704 to primary and secondary bile acids. Also revealed are genes with the potential to function in bile acid transport and metabolism.

Draft Assembly of Elite Inbred Line PH207 Provides Insights into Genomic and Transcriptome Diversity in Maize.

Intense artificial selection over the last 100 years has produced elite maize (Zea mays) inbred lines that combine to produce high-yielding hybrids. To further our understanding of how genome and transcriptome variation contribute to the production of high-yielding hybrids, we generated a draft genome assembly of the inbred line PH207 to complement and compare with the existing B73 reference sequence. B73 is a founder of the Stiff Stalk germplasm pool, while PH207 is a founder of Iodent germplasm, both of which have contributed substantially to the production of temperate commercial maize and are combined to make heterotic hybrids. Comparison of these two assemblies revealed over 2500 genes present in only one of the two genotypes and 136 gene families that have undergone extensive expansion or contraction. Transcriptome profiling revealed extensive expression variation, with as many as 10,564 differentially expressed transcripts and 7128 transcripts expressed in only one of the two genotypes in a single tissue. Genotype-specific genes were more likely to have tissue/condition-specific expression and lower transcript abundance. The availability of a high-quality genome assembly for the elite maize inbred PH207 expands our knowledge of the breadth of natural genome and transcriptome variation in elite maize inbred lines across heterotic pools.