Clusters of microRNAs emerge by new hairpins in existing transcripts

Genetic linkage may result in the expression of multiple products from a polycistronic transcript, under the control of a single promoter. In animals, protein-coding polycistronic transcripts are rare. However, microRNAs are frequently clustered in the genomes of animals, and these clusters are often transcribed as a single unit. The evolution of microRNA clusters has been the subject of much speculation, and a selective advantage of clusters of functionally related microRNAs is often proposed. However, the origin of microRNA clusters has not been so far explored. Here, we study the evolution of microRNA clusters in Drosophila melanogaster. We observed that the majority of microRNA clusters arose by the de novo formation of new microRNA-like hairpins in existing microRNA transcripts. Some clusters also emerged by tandem duplication of a single microRNA. Comparative genomics show that these clusters are unlikely to split or undergo rearrangements. We did not find any instances of clusters appearing by rearrangement of pre-existing microRNA genes. We propose a model for microRNA cluster evolution in which selection over one of the microRNAs in the cluster interferes with the evolution of the other linked microRNAs. Our analysis suggests that the study of microRNAs and small RNAs must consider linkage associations

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

Distinct contributions of extrastriate body area and temporoparietal junction in perceiving one's own and others' body.

The right temporoparietal cortex plays a critical role in body representation. Here, we applied repetitive transcranial magnetic stimulation (rTMS) over right extrastriate body area (EBA) and temporoparietal junction (TPJ) to investigate their causative roles in perceptual representations of one's own and others' body. Healthy women adjusted size-distorted pictures of their own body or of the body of another person according to how they perceived the body (subjective task) or how others perceived it (intersubjective task). In keeping with previous reports, at baseline, we found an overall underestimation of body size. Crucially, EBA-rTMS increased the underestimation bias when participants adjusted the images according to how others perceived their own or the other woman's body, suggesting a specific role of EBA in allocentric body representations. Conversely, TPJ-rTMS increased the underestimation bias when participants adjusted the body of another person, either a familiar other or a close friend, in both subjective and intersubjective tasks, suggesting an involvement of TPJ in representing others' bodies. These effects were body-specific, since no TMS-induced modulation was observed when participants judged a familiar object. The results suggest that right EBA and TPJ play active and complementary roles in the complex interaction between the perceptions of one's own and other people's body

A report on the Ghana country level inception workshop of the CGIAR Initiative on Aquatic Foods

Inception workshop of the Aquatic Foods initiative in Ghana held in September 2022. This workshop also aimed to convey multiple stakeholders and initiate cross-institutional collaboration for the uptake of aquatic food production in reservoirs

Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer

Abstract: Bladder cancer is the 10th most common and 13th most deadly cancer worldwide, with urothelial carcinomas being the most common type. Distinguishing between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is essential due to significant differences in management and prognosis. MRI may play an important diagnostic role in this setting. The Vesical Imaging Reporting and Data System (VI-RADS), a multiparametric MRI (mpMRI)-based consensus reporting platform, allows for standardized preoperative muscle invasion assessment in BCa with proven diagnostic accuracy. However, post-treatment assessment using VI-RADS is challenging because of anatomical changes, especially in the interpretation of the muscle layer. MRI techniques that provide tumor tissue physiological information, including diffusion-weighted (DW)- and dynamic contrast-enhanced (DCE)-MRI, combined with derived quantitative imaging biomarkers (QIBs), may potentially overcome the limitations of BCa evaluation when predominantly focusing on anatomic changes at MRI, particularly in the therapy response setting. Delta-radiomics, which encompasses the assessment of changes (Δ) in image features extracted from mpMRI data, has the potential to monitor treatment response. In comparison to the current Response Evaluation Criteria in Solid Tumors (RECIST), QIBs and mpMRI-based radiomics, in combination with artificial intelligence (AI)-based image analysis, may potentially allow for earlier identification of therapy-induced tumor changes. This review provides an update on the potential of QIBs and mpMRI-based radiomics and discusses the future applications of AI in BCa management, particularly in assessing treatment response. Critical relevance statement: Incorporating mpMRI-based quantitative imaging biomarkers, radiomics, and artificial intelligence into bladder cancer management has the potential to enhance treatment response assessment and prognosis prediction. Key Points: Quantitative imaging biomarkers (QIBs) from mpMRI and radiomics can outperform RECIST for bladder cancer treatments. AI improves mpMRI segmentation and enhances radiomics feature extraction effectively. Predictive models integrate imaging biomarkers and clinical data using AI tools. Multicenter studies with strict criteria validate radiomics and QIBs clinically. Consistent mpMRI and AI applications need reliable validation in clinical practice.</p

The CAP cancer protocols – a case study of caCORE based data standards implementation to integrate with the Cancer Biomedical Informatics Grid

BACKGROUND: The Cancer Biomedical Informatics Grid (caBIG™) is a network of individuals and institutions, creating a world wide web of cancer research. An important aspect of this informatics effort is the development of consistent practices for data standards development, using a multi-tier approach that facilitates semantic interoperability of systems. The semantic tiers include (1) information models, (2) common data elements, and (3) controlled terminologies and ontologies. The College of American Pathologists (CAP) cancer protocols and checklists are an important reporting standard in pathology, for which no complete electronic data standard is currently available. METHODS: In this manuscript, we provide a case study of Cancer Common Ontologic Representation Environment (caCORE) data standard implementation of the CAP cancer protocols and checklists model – an existing and complex paper based standard. We illustrate the basic principles, goals and methodology for developing caBIG™ models. RESULTS: Using this example, we describe the process required to develop the model, the technologies and data standards on which the process and models are based, and the results of the modeling effort. We address difficulties we encountered and modifications to caCORE that will address these problems. In addition, we describe four ongoing development projects that will use the emerging CAP data standards to achieve integration of tissue banking and laboratory information systems. CONCLUSION: The CAP cancer checklists can be used as the basis for an electronic data standard in pathology using the caBIG™ semantic modeling methodology

Experimental discovery of sRNAs in Vibrio cholerae by direct cloning, 5S/tRNA depletion and parallel sequencing

Direct cloning and parallel sequencing, an extremely powerful method for microRNA (miRNA) discovery, has not yet been applied to bacterial transcriptomes. Here we present sRNA-Seq, an unbiased method that allows for interrogation of the entire small, non-coding RNA (sRNA) repertoire in any prokaryotic or eukaryotic organism. This method includes a novel treatment that depletes total RNA fractions of highly abundant tRNAs and small subunit rRNA, thereby enriching the starting pool for sRNA transcripts with novel functionality. As a proof-of-principle, we applied sRNA-Seq to the human pathogen Vibrio cholerae. Our results provide information, at unprecedented depth, on the complexity of the sRNA component of a bacterial transcriptome. From 407 039 sequence reads, all 20 known V. cholerae sRNAs, 500 new, putative intergenic sRNAs and 127 putative antisense sRNAs were identified in a limited number of growth conditions examined. In addition, characterization of a subset of the newly identified transcripts led to the identification of a novel sRNA regulator of carbon metabolism. Collectively, these results strongly suggest that the number of sRNAs in bacteria has been greatly underestimated and that future efforts to analyze bacterial transcriptomes will benefit from direct cloning and parallel sequencing experiments aided by 5S/tRNA depletion

Targeted Destruction of Photosensitive Retinal Ganglion Cells with a Saporin Conjugate Alters the Effects of Light on Mouse Circadian Rhythms

Non-image related responses to light, such as the synchronization of circadian rhythms to the day/night cycle, are mediated by classical rod/cone photoreceptors and by a small subset of retinal ganglion cells that are intrinsically photosensitive, expressing the photopigment, melanopsin. This raises the possibility that the melanopsin cells may be serving as a conduit for photic information detected by the rods and/or cones. To test this idea, we developed a specific immunotoxin consisting of an anti-melanopsin antibody conjugated to the ribosome-inactivating protein, saporin. Intravitreal injection of this immunotoxin results in targeted destruction of melanopsin cells. We find that the specific loss of these cells in the adult mouse retina alters the effects of light on circadian rhythms. In particular, the photosensitivity of the circadian system is significantly attenuated. A subset of animals becomes non-responsive to the light/dark cycle, a characteristic previously observed in mice lacking rods, cones, and functional melanopsin cells. Mice lacking melanopsin cells are also unable to show light induced negative masking, a phenomenon known to be mediated by such cells, but both visual cliff and light/dark preference responses are normal. These data suggest that cells containing melanopsin do indeed function as a conduit for rod and/or cone information for certain non-image forming visual responses. Furthermore, we have developed a technique to specifically ablate melanopsin cells in the fully developed adult retina. This approach can be applied to any species subject to the existence of appropriate anti-melanopsin antibodies

The Community Land Model version 5 : description of new features, benchmarking, and impact of forcing uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5